tests/testthat/_snaps/hero.md
In PolicyAnalysisInc/heRoMod: Health Economic Modeling
Simple PSM produces correct results.
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AP4=
Code
exported
Output
$`Inputs - Settings`
# A tibble: 4 × 2
setting value
<chr> <chr>
1 disc_cost 0.03
2 disc_eff 0.03
3 cycle_length 30.4166666666667
4 n_cycles 240
$`Inputs - Strategies`
# A tibble: 2 × 2
name desc
<chr> <chr>
1 CHEMO Chemotherapy
2 TARGET Targeted Therapy
$`Inputs - States`
# A tibble: 3 × 4
name desc prob limit
<chr> <chr> <dbl> <dbl>
1 PF Progression-Free 1 0
2 PP Post-Progression 0 0
3 DEAD Dead 0 0
$`Inputs - Transitions`
# A tibble: 4 × 4
strategy endpoint cycle_length value
<chr> <chr> <dbl> <chr>
1 CHEMO PFS 1 pfs_chemo
2 TARGET PFS 1 pfs_target
3 CHEMO OS 1 os_chemo
4 TARGET OS 1 os_target
$`Inputs - Health Values`
# A tibble: 4 × 5
name description strategy state value
<chr> <chr> <chr> <chr> <chr>
1 pf_ly Progression-free life-years All PF cycle_length_years
2 pp_ly Post-progression life-years All PP cycle_length_years
3 pf_qalys Progression-free QALYs All PF pf_ly * pfs_util
4 pp_qalys Post-Progression QALYs All PP pp_ly * pps_util
$`Inputs - Econ Values`
# A tibble: 4 × 5
name description strategy state value
<chr> <chr> <chr> <chr> <chr>
1 med_cost Medication cost CHEMO PF chemo_cost * …
2 pf_care_cost Routine care cost, pre-progression All PF cycle_length_…
3 med_cost Label... TARGET PF target_cost *…
4 pp_care_cost Routine care cost, post-progression All PP cycle_length_…
$`Inputs - Health Summ`
# A tibble: 4 × 4
name description value wtp
<chr> <chr> <chr> <dbl>
1 lys Life-Years pf_ly 100000
2 lys Life-Years pp_ly 100000
3 qalys QALYs pf_qalys 150000
4 qalys QALYs pp_qalys 150000
$`Inputs - Econ Summ`
# A tibble: 3 × 3
name description value
<chr> <chr> <chr>
1 cost_hc Healthcare system costs med_cost
2 cost_hc Label... pf_care_cost
3 cost_hc Label... pp_care_cost
$`Inputs - Parameters`
# A tibble: 12 × 6
name desc value low high psa
<chr> <chr> <chr> <chr> <chr> <chr>
1 pfs_shape PFS shape parameter, chemo 1.2 bc * 0.75 bc * 1.25 "lognorma…
2 pfs_scale PFS scale parameter, chemo 40.3 bc * 0.75 bc * 1.25 "lognorma…
3 pfs_hr_target PFS HR, target 0.67 0.6 0.8 "lognorma…
4 os_shape OS shape parameter, chemo 1.1 0.95 1.34 "lognorma…
5 os_scale OS scale parameter, chemo 70.4 bc * 0.75 bc * 1.25 "lognorma…
6 os_hr_target OS HR, target 0.74 bc * 0.75 bc * 1.25 "lognorma…
7 chemo_cost Cost per month, chemo 2000 bc - 500 bc + 500 ""
8 target_cost Cost per month, target 10000 bc - 3000 bc + 3000 ""
9 pfs_cost Cost per month, PFS 1000 bc - 700 bc + 700 "normal(m…
10 pps_cost Cost per month, PPS 2000 0 10000 "normal(m…
11 pfs_util Utility value, PFS 0.82 bc - 0.05 bc + 0.05 "lognorma…
12 pps_util Utility value, PPS 0.68 bc - 0.1 bc + 0.1 "lognorma…
$`Inputs - Surv Dists`
# A tibble: 4 × 2
name value
<chr> <chr>
1 pfs_chemo "define_survival(dist = \"weibull\", pfs_shape, pfs_scale)"
2 os_chemo "define_survival(dist = \"weibull\", os_shape, os_scale)"
3 pfs_target "apply_hr(pfs_chemo, pfs_hr_target)"
4 os_target "apply_hr(os_chemo, os_hr_target)"
$`Calc - Params`
# A tibble: 480 × 31
strategy group state_time cycle model_time cycle_length_days
<chr> <chr> <dbl> <dbl> <dbl> <dbl>
1 CHEMO All Patients 1 1 1 30.4
2 CHEMO All Patients 1 2 2 30.4
3 CHEMO All Patients 1 3 3 30.4
4 CHEMO All Patients 1 4 4 30.4
5 CHEMO All Patients 1 5 5 30.4
6 CHEMO All Patients 1 6 6 30.4
7 CHEMO All Patients 1 7 7 30.4
8 CHEMO All Patients 1 8 8 30.4
9 CHEMO All Patients 1 9 9 30.4
10 CHEMO All Patients 1 10 10 30.4
# ℹ 470 more rows
# ℹ 25 more variables: cycle_length_weeks <dbl>, cycle_length_months <dbl>,
# cycle_length_years <dbl>, model_day <dbl>, model_week <dbl>,
# model_month <dbl>, model_year <dbl>, state_day <dbl>, state_week <dbl>,
# state_month <dbl>, state_year <dbl>, disc_h <dbl>, disc_e <dbl>,
# pfs_shape <dbl>, pfs_scale <dbl>, pfs_hr_target <dbl>, os_shape <dbl>,
# os_scale <dbl>, os_hr_target <dbl>, chemo_cost <dbl>, target_cost <dbl>, …
$`Calc - Trans`
# A tibble: 482 × 5
strategy group cycle pfs os
<chr> <chr> <dbl> <dbl> <dbl>
1 CHEMO All Patients 0 1 1
2 CHEMO All Patients 1 0.988 0.991
3 CHEMO All Patients 2 0.973 0.980
4 CHEMO All Patients 3 0.957 0.969
5 CHEMO All Patients 4 0.939 0.958
6 CHEMO All Patients 5 0.922 0.947
7 CHEMO All Patients 6 0.903 0.936
8 CHEMO All Patients 7 0.885 0.924
9 CHEMO All Patients 8 0.866 0.913
10 CHEMO All Patients 9 0.847 0.901
# ℹ 472 more rows
$`Calc - Unit Values`
# A tibble: 1,440 × 24
strategy group cycle state pf_ly pp_ly pf_qalys pp_qalys lys qalys med_cost
<chr> <chr> <dbl> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 CHEMO All … 1 DEAD 0 0 0 0 0 0 0
2 CHEMO All … 2 DEAD 0 0 0 0 0 0 0
3 CHEMO All … 3 DEAD 0 0 0 0 0 0 0
4 CHEMO All … 4 DEAD 0 0 0 0 0 0 0
5 CHEMO All … 5 DEAD 0 0 0 0 0 0 0
6 CHEMO All … 6 DEAD 0 0 0 0 0 0 0
7 CHEMO All … 7 DEAD 0 0 0 0 0 0 0
8 CHEMO All … 8 DEAD 0 0 0 0 0 0 0
9 CHEMO All … 9 DEAD 0 0 0 0 0 0 0
10 CHEMO All … 10 DEAD 0 0 0 0 0 0 0
# ℹ 1,430 more rows
# ℹ 13 more variables: pf_care_cost <dbl>, pp_care_cost <dbl>, cost_hc <dbl>,
# .disc_pf_ly <dbl>, .disc_pp_ly <dbl>, .disc_pf_qalys <dbl>,
# .disc_pp_qalys <dbl>, .disc_lys <dbl>, .disc_qalys <dbl>,
# .disc_med_cost <dbl>, .disc_pf_care_cost <dbl>, .disc_pp_care_cost <dbl>,
# .disc_cost_hc <dbl>
$`Calc - Values`
# A tibble: 480 × 23
strategy group cycle pf_ly pp_ly pf_qalys pp_qalys lys qalys med_cost
<chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 CHEMO All P… 1 0.0828 1.06e-4 0.0679 7.19e-5 0.0829 0.0680 1988.
2 CHEMO All P… 2 0.0817 4.04e-4 0.0670 2.75e-4 0.0821 0.0673 1961.
3 CHEMO All P… 3 0.0804 8.27e-4 0.0659 5.63e-4 0.0812 0.0665 1930.
4 CHEMO All P… 4 0.0790 1.32e-3 0.0648 8.94e-4 0.0803 0.0657 1896.
5 CHEMO All P… 5 0.0775 1.85e-3 0.0636 1.25e-3 0.0794 0.0648 1861.
6 CHEMO All P… 6 0.0760 2.40e-3 0.0623 1.63e-3 0.0784 0.0640 1825.
7 CHEMO All P… 7 0.0745 2.98e-3 0.0611 2.03e-3 0.0775 0.0631 1788.
8 CHEMO All P… 8 0.0730 3.57e-3 0.0598 2.43e-3 0.0765 0.0623 1751.
9 CHEMO All P… 9 0.0714 4.17e-3 0.0586 2.84e-3 0.0756 0.0614 1714.
10 CHEMO All P… 10 0.0698 4.77e-3 0.0573 3.25e-3 0.0746 0.0605 1676.
# ℹ 470 more rows
# ℹ 13 more variables: pf_care_cost <dbl>, pp_care_cost <dbl>, cost_hc <dbl>,
# .disc_pf_ly <dbl>, .disc_pp_ly <dbl>, .disc_pf_qalys <dbl>,
# .disc_pp_qalys <dbl>, .disc_lys <dbl>, .disc_qalys <dbl>,
# .disc_med_cost <dbl>, .disc_pf_care_cost <dbl>, .disc_pp_care_cost <dbl>,
# .disc_cost_hc <dbl>
$`Results - Trace`
# A tibble: 482 × 8
model_day model_week model_month model_year series PF PP DEAD
<dbl> <dbl> <dbl> <dbl> <chr> <dbl> <dbl> <dbl>
1 0 0 0 0 CHEMO 1 0 0
2 30.4 4.35 1 0.0833 CHEMO 0.988 0.00254 0.00924
3 60.8 8.69 2 0.167 CHEMO 0.973 0.00715 0.0197
4 91.3 13.0 3 0.25 CHEMO 0.957 0.0127 0.0306
5 122. 17.4 4 0.333 CHEMO 0.939 0.0189 0.0418
6 152. 21.7 5.00 0.417 CHEMO 0.922 0.0254 0.0531
7 182. 26.1 6.00 0.500 CHEMO 0.903 0.0323 0.0645
8 213. 30.4 7.00 0.583 CHEMO 0.885 0.0393 0.0759
9 243. 34.8 8.00 0.667 CHEMO 0.866 0.0464 0.0874
10 274. 39.1 9.00 0.750 CHEMO 0.847 0.0537 0.0988
# ℹ 472 more rows
$`Results - Trace (Corrected)`
# A tibble: 480 × 8
model_day model_week model_month model_year series PF PP DEAD
<dbl> <dbl> <dbl> <dbl> <chr> <dbl> <dbl> <dbl>
1 30.4 4.35 1 0.0833 CHEMO 0.994 0.00127 0.00462
2 60.8 8.69 2 0.167 CHEMO 0.981 0.00484 0.0145
3 91.3 13.0 3 0.25 CHEMO 0.965 0.00993 0.0252
4 122. 17.4 4 0.333 CHEMO 0.948 0.0158 0.0362
5 152. 21.7 5.00 0.417 CHEMO 0.930 0.0221 0.0474
6 182. 26.1 6.00 0.500 CHEMO 0.912 0.0288 0.0588
7 213. 30.4 7.00 0.583 CHEMO 0.894 0.0358 0.0702
8 243. 34.8 8.00 0.667 CHEMO 0.875 0.0429 0.0816
9 274. 39.1 9.00 0.750 CHEMO 0.857 0.0501 0.0931
10 304. 43.5 10 0.833 CHEMO 0.838 0.0573 0.105
# ℹ 470 more rows
$`Results - Outcomes`
# A tibble: 32 × 5
outcome series group disc value
<chr> <chr> <chr> <lgl> <dbl>
1 lys CHEMO pf_ly TRUE 2.93
2 lys TARGET pf_ly TRUE 3.97
3 lys TARGET vs. CHEMO pf_ly TRUE 1.04
4 lys CHEMO vs. TARGET pf_ly TRUE -1.04
5 lys CHEMO pp_ly TRUE 1.94
6 lys TARGET pp_ly TRUE 2.06
7 lys TARGET vs. CHEMO pp_ly TRUE 0.125
8 lys CHEMO vs. TARGET pp_ly TRUE -0.125
9 qalys CHEMO pf_qalys TRUE 2.40
10 qalys TARGET pf_qalys TRUE 3.25
# ℹ 22 more rows
$`Results - Costs`
# A tibble: 24 × 5
outcome series group disc value
<chr> <chr> <chr> <lgl> <dbl>
1 cost_hc CHEMO med_cost TRUE 70291.
2 cost_hc TARGET med_cost TRUE 476060.
3 cost_hc TARGET vs. CHEMO med_cost TRUE 405769.
4 cost_hc CHEMO vs. TARGET med_cost TRUE -405769.
5 cost_hc CHEMO pf_care_cost TRUE 35146.
6 cost_hc TARGET pf_care_cost TRUE 47606.
7 cost_hc TARGET vs. CHEMO pf_care_cost TRUE 12460.
8 cost_hc CHEMO vs. TARGET pf_care_cost TRUE -12460.
9 cost_hc CHEMO pp_care_cost TRUE 46441.
10 cost_hc TARGET pp_care_cost TRUE 49448.
# ℹ 14 more rows
$`Results - CE`
# A tibble: 4 × 11
hsumm esumm health_outcome econ_outcome series cost eff dcost deffect
<chr> <chr> <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl>
1 .disc_l… .dis… .disc_lys .disc_cost_… CHEMO 1.52e5 4.86 NA NA
2 .disc_l… .dis… .disc_lys .disc_cost_… TARGET 5.73e5 6.03 421236. 1.16
3 .disc_q… .dis… .disc_qalys .disc_cost_… CHEMO 1.52e5 3.72 NA NA
4 .disc_q… .dis… .disc_qalys .disc_cost_… TARGET 5.73e5 4.65 421236. 0.937
# ℹ 2 more variables: dref <chr>, icer <dbl>
$`Results - NMB`
# A tibble: 14 × 6
outcome series group disc type value
<chr> <chr> <chr> <lgl> <chr> <dbl>
1 lys TARGET vs. CHEMO pf_ly TRUE health 103836.
2 lys CHEMO vs. TARGET pf_ly TRUE health -103836.
3 lys TARGET vs. CHEMO pp_ly TRUE health 12530.
4 lys CHEMO vs. TARGET pp_ly TRUE health -12530.
5 qalys TARGET vs. CHEMO pf_qalys TRUE health 127718.
6 qalys CHEMO vs. TARGET pf_qalys TRUE health -127718.
7 qalys TARGET vs. CHEMO pp_qalys TRUE health 12781.
8 qalys CHEMO vs. TARGET pp_qalys TRUE health -12781.
9 cost_hc TARGET vs. CHEMO med_cost TRUE economic -405769.
10 cost_hc CHEMO vs. TARGET med_cost TRUE economic 405769.
11 cost_hc TARGET vs. CHEMO pf_care_cost TRUE economic -12460.
12 cost_hc CHEMO vs. TARGET pf_care_cost TRUE economic 12460.
13 cost_hc TARGET vs. CHEMO pp_care_cost TRUE economic -3007.
14 cost_hc CHEMO vs. TARGET pp_care_cost TRUE economic 3007.
Code
exported_limited
Output
$`Inputs - Settings`
# A tibble: 4 × 2
setting value
<chr> <chr>
1 disc_cost 0.03
2 disc_eff 0.03
3 cycle_length 30.4166666666667
4 n_cycles 240
$`Inputs - Strategies`
# A tibble: 2 × 2
name desc
<chr> <chr>
1 CHEMO Chemotherapy
2 TARGET Targeted Therapy
$`Inputs - States`
# A tibble: 3 × 4
name desc prob limit
<chr> <chr> <dbl> <dbl>
1 PF Progression-Free 1 0
2 PP Post-Progression 0 0
3 DEAD Dead 0 0
$`Inputs - Transitions`
# A tibble: 4 × 4
strategy endpoint cycle_length value
<chr> <chr> <dbl> <chr>
1 CHEMO PFS 1 pfs_chemo
2 TARGET PFS 1 pfs_target
3 CHEMO OS 1 os_chemo
4 TARGET OS 1 os_target
$`Inputs - Health Values`
# A tibble: 4 × 5
name description strategy state value
<chr> <chr> <chr> <chr> <chr>
1 pf_ly Progression-free life-years All PF cycle_length_years
2 pp_ly Post-progression life-years All PP cycle_length_years
3 pf_qalys Progression-free QALYs All PF pf_ly * pfs_util
4 pp_qalys Post-Progression QALYs All PP pp_ly * pps_util
$`Inputs - Econ Values`
# A tibble: 4 × 5
name description strategy state value
<chr> <chr> <chr> <chr> <chr>
1 med_cost Medication cost CHEMO PF chemo_cost * …
2 pf_care_cost Routine care cost, pre-progression All PF cycle_length_…
3 med_cost Label... TARGET PF target_cost *…
4 pp_care_cost Routine care cost, post-progression All PP cycle_length_…
$`Inputs - Health Summ`
# A tibble: 4 × 4
name description value wtp
<chr> <chr> <chr> <dbl>
1 lys Life-Years pf_ly 100000
2 lys Life-Years pp_ly 100000
3 qalys QALYs pf_qalys 150000
4 qalys QALYs pp_qalys 150000
$`Inputs - Econ Summ`
# A tibble: 3 × 3
name description value
<chr> <chr> <chr>
1 cost_hc Healthcare system costs med_cost
2 cost_hc Label... pf_care_cost
3 cost_hc Label... pp_care_cost
$`Inputs - Parameters`
# A tibble: 12 × 6
name desc value low high psa
<chr> <chr> <chr> <chr> <chr> <chr>
1 pfs_shape PFS shape parameter, chemo 1.2 bc * 0.75 bc * 1.25 "lognorma…
2 pfs_scale PFS scale parameter, chemo 40.3 bc * 0.75 bc * 1.25 "lognorma…
3 pfs_hr_target PFS HR, target 0.67 0.6 0.8 "lognorma…
4 os_shape OS shape parameter, chemo 1.1 0.95 1.34 "lognorma…
5 os_scale OS scale parameter, chemo 70.4 bc * 0.75 bc * 1.25 "lognorma…
6 os_hr_target OS HR, target 0.74 bc * 0.75 bc * 1.25 "lognorma…
7 chemo_cost Cost per month, chemo 2000 bc - 500 bc + 500 ""
8 target_cost Cost per month, target 10000 bc - 3000 bc + 3000 ""
9 pfs_cost Cost per month, PFS 1000 bc - 700 bc + 700 "normal(m…
10 pps_cost Cost per month, PPS 2000 0 10000 "normal(m…
11 pfs_util Utility value, PFS 0.82 bc - 0.05 bc + 0.05 "lognorma…
12 pps_util Utility value, PPS 0.68 bc - 0.1 bc + 0.1 "lognorma…
$`Inputs - Surv Dists`
# A tibble: 4 × 2
name value
<chr> <chr>
1 pfs_chemo "define_survival(dist = \"weibull\", pfs_shape, pfs_scale)"
2 os_chemo "define_survival(dist = \"weibull\", os_shape, os_scale)"
3 pfs_target "apply_hr(pfs_chemo, pfs_hr_target)"
4 os_target "apply_hr(os_chemo, os_hr_target)"
$`Calc - Params`
# A tibble: 20 × 31
strategy group state_time cycle model_time cycle_length_days
<chr> <chr> <dbl> <dbl> <dbl> <dbl>
1 CHEMO All Patients 1 1 1 30.4
2 CHEMO All Patients 1 2 2 30.4
3 CHEMO All Patients 1 3 3 30.4
4 CHEMO All Patients 1 4 4 30.4
5 CHEMO All Patients 1 5 5 30.4
6 CHEMO All Patients 1 6 6 30.4
7 CHEMO All Patients 1 7 7 30.4
8 CHEMO All Patients 1 8 8 30.4
9 CHEMO All Patients 1 239 239 30.4
10 CHEMO All Patients 1 240 240 30.4
11 TARGET All Patients 1 1 1 30.4
12 TARGET All Patients 1 2 2 30.4
13 TARGET All Patients 1 3 3 30.4
14 TARGET All Patients 1 4 4 30.4
15 TARGET All Patients 1 5 5 30.4
16 TARGET All Patients 1 6 6 30.4
17 TARGET All Patients 1 7 7 30.4
18 TARGET All Patients 1 8 8 30.4
19 TARGET All Patients 1 239 239 30.4
20 TARGET All Patients 1 240 240 30.4
# ℹ 25 more variables: cycle_length_weeks <dbl>, cycle_length_months <dbl>,
# cycle_length_years <dbl>, model_day <dbl>, model_week <dbl>,
# model_month <dbl>, model_year <dbl>, state_day <dbl>, state_week <dbl>,
# state_month <dbl>, state_year <dbl>, disc_h <dbl>, disc_e <dbl>,
# pfs_shape <dbl>, pfs_scale <dbl>, pfs_hr_target <dbl>, os_shape <dbl>,
# os_scale <dbl>, os_hr_target <dbl>, chemo_cost <dbl>, target_cost <dbl>,
# pfs_cost <dbl>, pps_cost <dbl>, pfs_util <dbl>, pps_util <dbl>
$`Calc - Trans`
# A tibble: 20 × 5
strategy group cycle pfs os
<chr> <chr> <dbl> <dbl> <dbl>
1 CHEMO All Patients 0 1 1
2 CHEMO All Patients 1 0.988 0.991
3 CHEMO All Patients 2 0.973 0.980
4 CHEMO All Patients 3 0.957 0.969
5 CHEMO All Patients 4 0.939 0.958
6 CHEMO All Patients 5 0.922 0.947
7 CHEMO All Patients 6 0.903 0.936
8 CHEMO All Patients 7 0.885 0.924
9 CHEMO All Patients 239 0.000210 0.0216
10 CHEMO All Patients 240 0.000202 0.0212
11 TARGET All Patients 0 1 1
12 TARGET All Patients 1 0.992 0.993
13 TARGET All Patients 2 0.982 0.985
14 TARGET All Patients 3 0.971 0.977
15 TARGET All Patients 4 0.959 0.969
16 TARGET All Patients 5 0.947 0.960
17 TARGET All Patients 6 0.934 0.952
18 TARGET All Patients 7 0.921 0.943
19 TARGET All Patients 239 0.00344 0.0585
20 TARGET All Patients 240 0.00334 0.0577
$`Calc - Unit Values`
# A tibble: 24 × 24
strategy group cycle state pf_ly pp_ly pf_qalys pp_qalys lys qalys
<chr> <chr> <dbl> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 CHEMO All Patie… 1 DEAD 0 0 0 0 0 0
2 CHEMO All Patie… 1 PF 0.0833 0 0.0683 0 0.0833 0.0683
3 CHEMO All Patie… 1 PP 0 0.0833 0 0.0567 0.0833 0.0567
4 CHEMO All Patie… 2 DEAD 0 0 0 0 0 0
5 CHEMO All Patie… 2 PF 0.0833 0 0.0683 0 0.0833 0.0683
6 CHEMO All Patie… 2 PP 0 0.0833 0 0.0567 0.0833 0.0567
7 CHEMO All Patie… 3 DEAD 0 0 0 0 0 0
8 CHEMO All Patie… 3 PF 0.0833 0 0.0683 0 0.0833 0.0683
9 CHEMO All Patie… 3 PP 0 0.0833 0 0.0567 0.0833 0.0567
10 CHEMO All Patie… 4 DEAD 0 0 0 0 0 0
# ℹ 14 more rows
# ℹ 14 more variables: med_cost <dbl>, pf_care_cost <dbl>, pp_care_cost <dbl>,
# cost_hc <dbl>, .disc_pf_ly <dbl>, .disc_pp_ly <dbl>, .disc_pf_qalys <dbl>,
# .disc_pp_qalys <dbl>, .disc_lys <dbl>, .disc_qalys <dbl>,
# .disc_med_cost <dbl>, .disc_pf_care_cost <dbl>, .disc_pp_care_cost <dbl>,
# .disc_cost_hc <dbl>
$`Calc - Values`
# A tibble: 20 × 23
strategy group cycle pf_ly pp_ly pf_qalys pp_qalys lys qalys
<chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 CHEMO All Patients 1 8.28e-2 1.06e-4 6.79e-2 7.19e-5 0.0829 0.0680
2 CHEMO All Patients 2 8.17e-2 4.04e-4 6.70e-2 2.75e-4 0.0821 0.0673
3 CHEMO All Patients 3 8.04e-2 8.27e-4 6.59e-2 5.63e-4 0.0812 0.0665
4 CHEMO All Patients 4 7.90e-2 1.32e-3 6.48e-2 8.94e-4 0.0803 0.0657
5 CHEMO All Patients 5 7.75e-2 1.85e-3 6.36e-2 1.25e-3 0.0794 0.0648
6 CHEMO All Patients 6 7.60e-2 2.40e-3 6.23e-2 1.63e-3 0.0784 0.0640
7 CHEMO All Patients 7 7.45e-2 2.98e-3 6.11e-2 2.03e-3 0.0775 0.0631
8 CHEMO All Patients 8 7.30e-2 3.57e-3 5.98e-2 2.43e-3 0.0765 0.0623
9 CHEMO All Patients 239 1.79e-5 1.80e-3 1.47e-5 1.22e-3 0.00181 0.00124
10 CHEMO All Patients 240 1.72e-5 1.76e-3 1.41e-5 1.20e-3 0.00178 0.00121
11 TARGET All Patients 1 8.30e-2 4.42e-5 6.81e-2 3.01e-5 0.0830 0.0681
12 TARGET All Patients 2 8.23e-2 1.88e-4 6.74e-2 1.28e-4 0.0824 0.0676
13 TARGET All Patients 3 8.14e-2 4.14e-4 6.67e-2 2.82e-4 0.0818 0.0670
14 TARGET All Patients 4 8.04e-2 6.86e-4 6.59e-2 4.66e-4 0.0811 0.0664
15 TARGET All Patients 5 7.94e-2 9.88e-4 6.51e-2 6.72e-4 0.0804 0.0658
16 TARGET All Patients 6 7.84e-2 1.31e-3 6.43e-2 8.93e-4 0.0797 0.0652
17 TARGET All Patients 7 7.73e-2 1.66e-3 6.34e-2 1.13e-3 0.0790 0.0645
18 TARGET All Patients 8 7.62e-2 2.01e-3 6.25e-2 1.37e-3 0.0782 0.0639
19 TARGET All Patients 239 2.91e-4 4.62e-3 2.38e-4 3.14e-3 0.00491 0.00338
20 TARGET All Patients 240 2.83e-4 4.56e-3 2.32e-4 3.10e-3 0.00484 0.00333
# ℹ 14 more variables: med_cost <dbl>, pf_care_cost <dbl>, pp_care_cost <dbl>,
# cost_hc <dbl>, .disc_pf_ly <dbl>, .disc_pp_ly <dbl>, .disc_pf_qalys <dbl>,
# .disc_pp_qalys <dbl>, .disc_lys <dbl>, .disc_qalys <dbl>,
# .disc_med_cost <dbl>, .disc_pf_care_cost <dbl>, .disc_pp_care_cost <dbl>,
# .disc_cost_hc <dbl>
$`Results - Trace`
# A tibble: 482 × 8
model_day model_week model_month model_year series PF PP DEAD
<dbl> <dbl> <dbl> <dbl> <chr> <dbl> <dbl> <dbl>
1 0 0 0 0 CHEMO 1 0 0
2 30.4 4.35 1 0.0833 CHEMO 0.988 0.00254 0.00924
3 60.8 8.69 2 0.167 CHEMO 0.973 0.00715 0.0197
4 91.3 13.0 3 0.25 CHEMO 0.957 0.0127 0.0306
5 122. 17.4 4 0.333 CHEMO 0.939 0.0189 0.0418
6 152. 21.7 5.00 0.417 CHEMO 0.922 0.0254 0.0531
7 182. 26.1 6.00 0.500 CHEMO 0.903 0.0323 0.0645
8 213. 30.4 7.00 0.583 CHEMO 0.885 0.0393 0.0759
9 243. 34.8 8.00 0.667 CHEMO 0.866 0.0464 0.0874
10 274. 39.1 9.00 0.750 CHEMO 0.847 0.0537 0.0988
# ℹ 472 more rows
$`Results - Trace (Corrected)`
# A tibble: 480 × 8
model_day model_week model_month model_year series PF PP DEAD
<dbl> <dbl> <dbl> <dbl> <chr> <dbl> <dbl> <dbl>
1 30.4 4.35 1 0.0833 CHEMO 0.994 0.00127 0.00462
2 60.8 8.69 2 0.167 CHEMO 0.981 0.00484 0.0145
3 91.3 13.0 3 0.25 CHEMO 0.965 0.00993 0.0252
4 122. 17.4 4 0.333 CHEMO 0.948 0.0158 0.0362
5 152. 21.7 5.00 0.417 CHEMO 0.930 0.0221 0.0474
6 182. 26.1 6.00 0.500 CHEMO 0.912 0.0288 0.0588
7 213. 30.4 7.00 0.583 CHEMO 0.894 0.0358 0.0702
8 243. 34.8 8.00 0.667 CHEMO 0.875 0.0429 0.0816
9 274. 39.1 9.00 0.750 CHEMO 0.857 0.0501 0.0931
10 304. 43.5 10 0.833 CHEMO 0.838 0.0573 0.105
# ℹ 470 more rows
$`Results - Outcomes`
# A tibble: 32 × 5
outcome series group disc value
<chr> <chr> <chr> <lgl> <dbl>
1 lys CHEMO pf_ly TRUE 2.93
2 lys TARGET pf_ly TRUE 3.97
3 lys TARGET vs. CHEMO pf_ly TRUE 1.04
4 lys CHEMO vs. TARGET pf_ly TRUE -1.04
5 lys CHEMO pp_ly TRUE 1.94
6 lys TARGET pp_ly TRUE 2.06
7 lys TARGET vs. CHEMO pp_ly TRUE 0.125
8 lys CHEMO vs. TARGET pp_ly TRUE -0.125
9 qalys CHEMO pf_qalys TRUE 2.40
10 qalys TARGET pf_qalys TRUE 3.25
# ℹ 22 more rows
$`Results - Costs`
# A tibble: 24 × 5
outcome series group disc value
<chr> <chr> <chr> <lgl> <dbl>
1 cost_hc CHEMO med_cost TRUE 70291.
2 cost_hc TARGET med_cost TRUE 476060.
3 cost_hc TARGET vs. CHEMO med_cost TRUE 405769.
4 cost_hc CHEMO vs. TARGET med_cost TRUE -405769.
5 cost_hc CHEMO pf_care_cost TRUE 35146.
6 cost_hc TARGET pf_care_cost TRUE 47606.
7 cost_hc TARGET vs. CHEMO pf_care_cost TRUE 12460.
8 cost_hc CHEMO vs. TARGET pf_care_cost TRUE -12460.
9 cost_hc CHEMO pp_care_cost TRUE 46441.
10 cost_hc TARGET pp_care_cost TRUE 49448.
# ℹ 14 more rows
$`Results - CE`
# A tibble: 4 × 11
hsumm esumm health_outcome econ_outcome series cost eff dcost deffect
<chr> <chr> <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl>
1 .disc_l… .dis… .disc_lys .disc_cost_… CHEMO 1.52e5 4.86 NA NA
2 .disc_l… .dis… .disc_lys .disc_cost_… TARGET 5.73e5 6.03 421236. 1.16
3 .disc_q… .dis… .disc_qalys .disc_cost_… CHEMO 1.52e5 3.72 NA NA
4 .disc_q… .dis… .disc_qalys .disc_cost_… TARGET 5.73e5 4.65 421236. 0.937
# ℹ 2 more variables: dref <chr>, icer <dbl>
$`Results - NMB`
# A tibble: 14 × 6
outcome series group disc type value
<chr> <chr> <chr> <lgl> <chr> <dbl>
1 lys TARGET vs. CHEMO pf_ly TRUE health 103836.
2 lys CHEMO vs. TARGET pf_ly TRUE health -103836.
3 lys TARGET vs. CHEMO pp_ly TRUE health 12530.
4 lys CHEMO vs. TARGET pp_ly TRUE health -12530.
5 qalys TARGET vs. CHEMO pf_qalys TRUE health 127718.
6 qalys CHEMO vs. TARGET pf_qalys TRUE health -127718.
7 qalys TARGET vs. CHEMO pp_qalys TRUE health 12781.
8 qalys CHEMO vs. TARGET pp_qalys TRUE health -12781.
9 cost_hc TARGET vs. CHEMO med_cost TRUE economic -405769.
10 cost_hc CHEMO vs. TARGET med_cost TRUE economic 405769.
11 cost_hc TARGET vs. CHEMO pf_care_cost TRUE economic -12460.
12 cost_hc CHEMO vs. TARGET pf_care_cost TRUE economic 12460.
13 cost_hc TARGET vs. CHEMO pp_care_cost TRUE economic -3007.
14 cost_hc CHEMO vs. TARGET pp_care_cost TRUE economic 3007.
Custom PSM produces correct results.
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Code
exported
Output
$`Inputs - Settings`
# A tibble: 4 × 2
setting value
<chr> <chr>
1 disc_cost 0.035
2 disc_eff 0.035
3 cycle_length 365
4 n_cycles 20
$`Inputs - Strategies`
# A tibble: 4 × 2
name desc
<chr> <chr>
1 myfo Myfosfamide
2 chpl Chemoplatin
3 chck Checkimab
4 rlps Relapsinib
$`Inputs - States`
# A tibble: 4 × 4
name desc prob limit
<chr> <chr> <chr> <dbl>
1 RESP Response dispatch_strategy(myfo = rr_myfo, chpl = rr_chpl, chck… 0
2 REL Relapse 0 0
3 REF Refractory C 0
4 DEAD Dead 0 0
$`Inputs - Transitions`
# A tibble: 4 × 5
strategy state formula id value
<chr> <chr> <chr> <chr> <chr>
1 All RESP rr * surv_prob(rfs, model_month) 6e50… rr *…
2 All REL rr * (surv_prob(os_resp, model_month) - surv_prob(… aefc… rr *…
3 All REF (1 - rr) * surv_prob(os_nresp, model_month) d1f8… (1 -…
4 All DEAD C 8c1d… C
$`Inputs - Health Values`
# A tibble: 6 × 5
name description strategy state value
<chr> <chr> <chr> <chr> <chr>
1 ly_resp Life Years in Response All RESP cycle_length_years
2 ly_nresp Life Years in Nonresponse All REL cycle_length_years
3 qalys_resp QALYs in Response All RESP util_resp * cycle_length…
4 qalys_nresp QALYs in Nonresponse All REL util_rel * cycle_length_…
5 ly_nresp Label... All REF cycle_length_years
6 qalys_nresp Label... All REF util_ref * cycle_length_…
$`Inputs - Econ Values`
# A tibble: 7 × 5
name description strategy state value
<chr> <chr> <chr> <chr> <chr>
1 cost_med Medication cost myfo RESP ucost_myfo * cycle_length…
2 cost_resp Routine care, response All All ucost_resp * cycle_length…
3 cost_nresp Routine care, nonresponse All All ucost_nresp * cycle_lengt…
4 cost_trans Transplant All REF rescale_prob(p_transplant…
5 cost_med Label... chpl RESP ucost_chpl * cycle_length…
6 cost_med Label... chck RESP ucost_chck * cycle_length…
7 cost_med Label... rlps RESP ucost_rlps * cycle_length…
$`Inputs - Health Summ`
# A tibble: 4 × 4
name description value wtp
<chr> <chr> <chr> <dbl>
1 lys Life-years ly_resp 20000
2 lys Life-years ly_nresp 20000
3 qalys Quality-adjusted life-years qalys_resp 30000
4 qalys Label... qalys_nresp 100000
$`Inputs - Econ Summ`
# A tibble: 4 × 3
name description value
<chr> <chr> <chr>
1 cost_hc Healthcare system costs cost_med
2 cost_hc Label... cost_resp
3 cost_hc Label... cost_nresp
4 cost_hc Label... cost_trans
$`Inputs - Parameters`
# A tibble: 21 × 6
name desc value low high psa
<chr> <chr> <chr> <chr> <chr> <chr>
1 rr_myfo Response rate, myfosfamide 0.31 "bc … "bc … "bin…
2 rr_chpl Response rate, chemoplatin 0.35 "bc … "bc … "bin…
3 rr_chck Response rate, checkimab 0.51 "bc … "bc … "bin…
4 rr_rlps Response rate, relapsinib 0.543 "bc … "bc … "bin…
5 rr Relapse rate dispatch_strate… "" "" ""
6 rfs_scale Scale parameter, RFS 6 "5.4… "7.1" "log…
7 rfs_shape Shape parameter, RFS 0.89 "0.7… "1.0… "log…
8 os_resp_meanlog log mean OS, responders 4 "3.4… "4.5… "nor…
9 os_resp_sdlog log SD OS, responders 0.71 "0.5… "0.9… "log…
10 os_nresp_rate Death rate, nonresponders 0.12 "0.0… "0.1… "log…
# ℹ 11 more rows
$`Inputs - Surv Dists`
# A tibble: 3 × 2
name value
<chr> <chr>
1 rfs "define_survival(shape = rfs_shape, scale = rfs_scale, dist = \"weib…
2 os_resp "define_survival(meanlog = os_resp_meanlog, sdlog = os_resp_sdlog, d…
3 os_nresp "define_survival(rate = os_nresp_rate, dist = \"exp\")"
$`Calc - Params`
# A tibble: 80 × 40
strategy group state_time cycle model_time cycle_length_days
<chr> <chr> <dbl> <dbl> <dbl> <dbl>
1 myfo All Patients 1 1 1 365
2 myfo All Patients 1 2 2 365
3 myfo All Patients 1 3 3 365
4 myfo All Patients 1 4 4 365
5 myfo All Patients 1 5 5 365
6 myfo All Patients 1 6 6 365
7 myfo All Patients 1 7 7 365
8 myfo All Patients 1 8 8 365
9 myfo All Patients 1 9 9 365
10 myfo All Patients 1 10 10 365
# ℹ 70 more rows
# ℹ 34 more variables: cycle_length_weeks <dbl>, cycle_length_months <dbl>,
# cycle_length_years <dbl>, model_day <dbl>, model_week <dbl>,
# model_month <dbl>, model_year <dbl>, state_day <dbl>, state_week <dbl>,
# state_month <dbl>, state_year <dbl>, disc_h <dbl>, disc_e <dbl>,
# rr_myfo <dbl>, rr_chpl <dbl>, rr_chck <dbl>, rr_rlps <dbl>, rr <dbl>,
# rfs_scale <dbl>, rfs_shape <dbl>, os_resp_meanlog <dbl>, …
$`Calc - Trans`
# A tibble: 84 × 9
model_day model_week model_month model_year series RESP REL REF
<dbl> <dbl> <dbl> <dbl> <chr> <dbl> <dbl> <dbl>
1 0 0 0 0 myfo 0.31 0 6.9 e-1
2 365 52.1 12 1 myfo 0.0486 0.256 1.63e-1
3 730 104. 24 2 myfo 0.0100 0.262 3.87e-2
4 1095 156. 36 3 myfo 0.00225 0.221 9.18e-3
5 1460 209. 48 4 myfo 0.000534 0.177 2.17e-3
6 1825 261. 60 5 myfo 0.000132 0.138 5.15e-4
7 2190 313. 72 6 myfo 0.0000336 0.108 1.22e-4
8 2555 365 84 7 myfo 0.00000877 0.0843 2.89e-5
9 2920 417. 96 8 myfo 0.00000234 0.0661 6.85e-6
10 3285 469. 108 9 myfo 0.000000636 0.0522 1.62e-6
# ℹ 74 more rows
# ℹ 1 more variable: DEAD <dbl>
$`Calc - Unit Values`
# A tibble: 320 × 26
strategy group cycle state ly_resp ly_nresp qalys_resp qalys_nresp lys
<chr> <chr> <dbl> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
1 chck All Patie… 1 DEAD 0 0 0 0 0
2 chck All Patie… 2 DEAD 0 0 0 0 0
3 chck All Patie… 3 DEAD 0 0 0 0 0
4 chck All Patie… 4 DEAD 0 0 0 0 0
5 chck All Patie… 5 DEAD 0 0 0 0 0
6 chck All Patie… 6 DEAD 0 0 0 0 0
7 chck All Patie… 7 DEAD 0 0 0 0 0
8 chck All Patie… 8 DEAD 0 0 0 0 0
9 chck All Patie… 9 DEAD 0 0 0 0 0
10 chck All Patie… 10 DEAD 0 0 0 0 0
# ℹ 310 more rows
# ℹ 17 more variables: qalys <dbl>, cost_med <dbl>, cost_resp <dbl>,
# cost_nresp <dbl>, cost_trans <dbl>, cost_hc <dbl>, .disc_ly_resp <dbl>,
# .disc_ly_nresp <dbl>, .disc_qalys_resp <dbl>, .disc_qalys_nresp <dbl>,
# .disc_lys <dbl>, .disc_qalys <dbl>, .disc_cost_med <dbl>,
# .disc_cost_resp <dbl>, .disc_cost_nresp <dbl>, .disc_cost_trans <dbl>,
# .disc_cost_hc <dbl>
$`Calc - Values`
# A tibble: 80 × 25
strategy group cycle ly_resp ly_nresp qalys_resp qalys_nresp lys qalys
<chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 chck All Pat… 1 2.95e-1 0.514 2.39e-1 0.326 0.809 0.565
2 chck All Pat… 2 4.82e-2 0.498 3.90e-2 0.329 0.546 0.368
3 chck All Pat… 3 1.01e-2 0.414 8.16e-3 0.277 0.424 0.285
4 chck All Pat… 4 2.29e-3 0.332 1.85e-3 0.222 0.334 0.224
5 chck All Pat… 5 5.48e-4 0.260 4.44e-4 0.174 0.261 0.175
6 chck All Pat… 6 1.36e-4 0.203 1.10e-4 0.136 0.203 0.136
7 chck All Pat… 7 3.48e-5 0.158 2.82e-5 0.106 0.158 0.106
8 chck All Pat… 8 9.14e-6 0.124 7.40e-6 0.0829 0.124 0.0829
9 chck All Pat… 9 2.45e-6 0.0973 1.98e-6 0.0652 0.0973 0.0652
10 chck All Pat… 10 6.67e-7 0.0770 5.40e-7 0.0516 0.0770 0.0516
# ℹ 70 more rows
# ℹ 16 more variables: cost_med <dbl>, cost_resp <dbl>, cost_nresp <dbl>,
# cost_trans <dbl>, cost_hc <dbl>, .disc_ly_resp <dbl>, .disc_ly_nresp <dbl>,
# .disc_qalys_resp <dbl>, .disc_qalys_nresp <dbl>, .disc_lys <dbl>,
# .disc_qalys <dbl>, .disc_cost_med <dbl>, .disc_cost_resp <dbl>,
# .disc_cost_nresp <dbl>, .disc_cost_trans <dbl>, .disc_cost_hc <dbl>
$`Results - Trace`
# A tibble: 84 × 9
model_day model_week model_month model_year series RESP REL REF
<dbl> <dbl> <dbl> <dbl> <chr> <dbl> <dbl> <dbl>
1 0 0 0 0 myfo 0.31 0 6.9 e-1
2 365 52.1 12 1 myfo 0.0486 0.256 1.63e-1
3 730 104. 24 2 myfo 0.0100 0.262 3.87e-2
4 1095 156. 36 3 myfo 0.00225 0.221 9.18e-3
5 1460 209. 48 4 myfo 0.000534 0.177 2.17e-3
6 1825 261. 60 5 myfo 0.000132 0.138 5.15e-4
7 2190 313. 72 6 myfo 0.0000336 0.108 1.22e-4
8 2555 365 84 7 myfo 0.00000877 0.0843 2.89e-5
9 2920 417. 96 8 myfo 0.00000234 0.0661 6.85e-6
10 3285 469. 108 9 myfo 0.000000636 0.0522 1.62e-6
# ℹ 74 more rows
# ℹ 1 more variable: DEAD <dbl>
$`Results - Trace (Corrected)`
# A tibble: 80 × 9
model_day model_week model_month model_year series RESP REL REF
<dbl> <dbl> <dbl> <dbl> <chr> <dbl> <dbl> <dbl>
1 365 52.1 12 1 myfo 0.179 0.128 4.27e-1
2 730 104. 24 2 myfo 0.0293 0.259 1.01e-1
3 1095 156. 36 3 myfo 0.00612 0.242 2.40e-2
4 1460 209. 48 4 myfo 0.00139 0.199 5.68e-3
5 1825 261. 60 5 myfo 0.000333 0.158 1.34e-3
6 2190 313. 72 6 myfo 0.0000827 0.123 3.19e-4
7 2555 365 84 7 myfo 0.0000212 0.0961 7.55e-5
8 2920 417. 96 8 myfo 0.00000556 0.0752 1.79e-5
9 3285 469. 108 9 myfo 0.00000149 0.0592 4.24e-6
10 3650 521. 120 10 myfo 0.000000405 0.0468 1.00e-6
# ℹ 70 more rows
# ℹ 1 more variable: DEAD <dbl>
$`Results - Outcomes`
# A tibble: 128 × 5
outcome series group disc value
<chr> <chr> <chr> <lgl> <dbl>
1 lys myfo ly_resp TRUE 0.215
2 lys chpl ly_resp TRUE 0.243
3 lys chck ly_resp TRUE 0.354
4 lys rlps ly_resp TRUE 0.377
5 lys chpl vs. myfo ly_resp TRUE 0.0277
6 lys chck vs. myfo ly_resp TRUE 0.139
7 lys rlps vs. myfo ly_resp TRUE 0.162
8 lys myfo vs. chpl ly_resp TRUE -0.0277
9 lys chck vs. chpl ly_resp TRUE 0.111
10 lys rlps vs. chpl ly_resp TRUE 0.134
# ℹ 118 more rows
$`Results - Costs`
# A tibble: 128 × 5
outcome series group disc value
<chr> <chr> <chr> <lgl> <dbl>
1 cost_hc myfo cost_med TRUE 9141.
2 cost_hc chpl cost_med TRUE 9302.
3 cost_hc chck cost_med TRUE 44162.
4 cost_hc rlps cost_med TRUE 58753.
5 cost_hc chpl vs. myfo cost_med TRUE 160.
6 cost_hc chck vs. myfo cost_med TRUE 35021.
7 cost_hc rlps vs. myfo cost_med TRUE 49612.
8 cost_hc myfo vs. chpl cost_med TRUE -160.
9 cost_hc chck vs. chpl cost_med TRUE 34861.
10 cost_hc rlps vs. chpl cost_med TRUE 49452.
# ℹ 118 more rows
$`Results - CE`
# A tibble: 8 × 11
hsumm esumm health_outcome econ_outcome series cost eff dcost deffect
<chr> <chr> <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl>
1 .disc_lys .dis… .disc_lys .disc_cost_… myfo 5.43e4 2.12 NA NA
2 .disc_lys .dis… .disc_lys .disc_cost_… chpl 5.44e4 2.29 103. 0.170
3 .disc_lys .dis… .disc_lys .disc_cost_… chck 8.90e4 2.97 34630. 0.681
4 .disc_lys .dis… .disc_lys .disc_cost_… rlps 1.04e5 3.11 14543. 0.140
5 .disc_qa… .dis… .disc_qalys .disc_cost_… myfo 5.43e4 1.42 NA NA
6 .disc_qa… .dis… .disc_qalys .disc_cost_… chpl 5.44e4 1.54 103. 0.120
7 .disc_qa… .dis… .disc_qalys .disc_cost_… chck 8.90e4 2.02 34630. 0.479
8 .disc_qa… .dis… .disc_qalys .disc_cost_… rlps 1.04e5 2.12 14543. 0.0989
# ℹ 2 more variables: dref <chr>, icer <dbl>
$`Results - NMB`
# A tibble: 96 × 6
outcome series group disc type value
<chr> <chr> <chr> <lgl> <chr> <dbl>
1 lys chpl vs. myfo ly_resp TRUE health 555.
2 lys chck vs. myfo ly_resp TRUE health 2774.
3 lys rlps vs. myfo ly_resp TRUE health 3231.
4 lys myfo vs. chpl ly_resp TRUE health -555.
5 lys chck vs. chpl ly_resp TRUE health 2219.
6 lys rlps vs. chpl ly_resp TRUE health 2676.
7 lys myfo vs. chck ly_resp TRUE health -2774.
8 lys chpl vs. chck ly_resp TRUE health -2219.
9 lys rlps vs. chck ly_resp TRUE health 458.
10 lys myfo vs. rlps ly_resp TRUE health -3231.
# ℹ 86 more rows
Code
exported_limited
Output
$`Inputs - Settings`
# A tibble: 4 × 2
setting value
<chr> <chr>
1 disc_cost 0.035
2 disc_eff 0.035
3 cycle_length 365
4 n_cycles 20
$`Inputs - Strategies`
# A tibble: 4 × 2
name desc
<chr> <chr>
1 myfo Myfosfamide
2 chpl Chemoplatin
3 chck Checkimab
4 rlps Relapsinib
$`Inputs - States`
# A tibble: 4 × 4
name desc prob limit
<chr> <chr> <chr> <dbl>
1 RESP Response dispatch_strategy(myfo = rr_myfo, chpl = rr_chpl, chck… 0
2 REL Relapse 0 0
3 REF Refractory C 0
4 DEAD Dead 0 0
$`Inputs - Transitions`
# A tibble: 4 × 5
strategy state formula id value
<chr> <chr> <chr> <chr> <chr>
1 All RESP rr * surv_prob(rfs, model_month) 6e50… rr *…
2 All REL rr * (surv_prob(os_resp, model_month) - surv_prob(… aefc… rr *…
3 All REF (1 - rr) * surv_prob(os_nresp, model_month) d1f8… (1 -…
4 All DEAD C 8c1d… C
$`Inputs - Health Values`
# A tibble: 6 × 5
name description strategy state value
<chr> <chr> <chr> <chr> <chr>
1 ly_resp Life Years in Response All RESP cycle_length_years
2 ly_nresp Life Years in Nonresponse All REL cycle_length_years
3 qalys_resp QALYs in Response All RESP util_resp * cycle_length…
4 qalys_nresp QALYs in Nonresponse All REL util_rel * cycle_length_…
5 ly_nresp Label... All REF cycle_length_years
6 qalys_nresp Label... All REF util_ref * cycle_length_…
$`Inputs - Econ Values`
# A tibble: 7 × 5
name description strategy state value
<chr> <chr> <chr> <chr> <chr>
1 cost_med Medication cost myfo RESP ucost_myfo * cycle_length…
2 cost_resp Routine care, response All All ucost_resp * cycle_length…
3 cost_nresp Routine care, nonresponse All All ucost_nresp * cycle_lengt…
4 cost_trans Transplant All REF rescale_prob(p_transplant…
5 cost_med Label... chpl RESP ucost_chpl * cycle_length…
6 cost_med Label... chck RESP ucost_chck * cycle_length…
7 cost_med Label... rlps RESP ucost_rlps * cycle_length…
$`Inputs - Health Summ`
# A tibble: 4 × 4
name description value wtp
<chr> <chr> <chr> <dbl>
1 lys Life-years ly_resp 20000
2 lys Life-years ly_nresp 20000
3 qalys Quality-adjusted life-years qalys_resp 30000
4 qalys Label... qalys_nresp 100000
$`Inputs - Econ Summ`
# A tibble: 4 × 3
name description value
<chr> <chr> <chr>
1 cost_hc Healthcare system costs cost_med
2 cost_hc Label... cost_resp
3 cost_hc Label... cost_nresp
4 cost_hc Label... cost_trans
$`Inputs - Parameters`
# A tibble: 21 × 6
name desc value low high psa
<chr> <chr> <chr> <chr> <chr> <chr>
1 rr_myfo Response rate, myfosfamide 0.31 "bc … "bc … "bin…
2 rr_chpl Response rate, chemoplatin 0.35 "bc … "bc … "bin…
3 rr_chck Response rate, checkimab 0.51 "bc … "bc … "bin…
4 rr_rlps Response rate, relapsinib 0.543 "bc … "bc … "bin…
5 rr Relapse rate dispatch_strate… "" "" ""
6 rfs_scale Scale parameter, RFS 6 "5.4… "7.1" "log…
7 rfs_shape Shape parameter, RFS 0.89 "0.7… "1.0… "log…
8 os_resp_meanlog log mean OS, responders 4 "3.4… "4.5… "nor…
9 os_resp_sdlog log SD OS, responders 0.71 "0.5… "0.9… "log…
10 os_nresp_rate Death rate, nonresponders 0.12 "0.0… "0.1… "log…
# ℹ 11 more rows
$`Inputs - Surv Dists`
# A tibble: 3 × 2
name value
<chr> <chr>
1 rfs "define_survival(shape = rfs_shape, scale = rfs_scale, dist = \"weib…
2 os_resp "define_survival(meanlog = os_resp_meanlog, sdlog = os_resp_sdlog, d…
3 os_nresp "define_survival(rate = os_nresp_rate, dist = \"exp\")"
$`Calc - Params`
# A tibble: 20 × 40
strategy group state_time cycle model_time cycle_length_days
<chr> <chr> <dbl> <dbl> <dbl> <dbl>
1 myfo All Patients 1 1 1 365
2 myfo All Patients 1 2 2 365
3 myfo All Patients 1 3 3 365
4 myfo All Patients 1 4 4 365
5 myfo All Patients 1 20 20 365
6 chpl All Patients 1 1 1 365
7 chpl All Patients 1 2 2 365
8 chpl All Patients 1 3 3 365
9 chpl All Patients 1 4 4 365
10 chpl All Patients 1 20 20 365
11 chck All Patients 1 1 1 365
12 chck All Patients 1 2 2 365
13 chck All Patients 1 3 3 365
14 chck All Patients 1 4 4 365
15 chck All Patients 1 20 20 365
16 rlps All Patients 1 1 1 365
17 rlps All Patients 1 2 2 365
18 rlps All Patients 1 3 3 365
19 rlps All Patients 1 4 4 365
20 rlps All Patients 1 20 20 365
# ℹ 34 more variables: cycle_length_weeks <dbl>, cycle_length_months <dbl>,
# cycle_length_years <dbl>, model_day <dbl>, model_week <dbl>,
# model_month <dbl>, model_year <dbl>, state_day <dbl>, state_week <dbl>,
# state_month <dbl>, state_year <dbl>, disc_h <dbl>, disc_e <dbl>,
# rr_myfo <dbl>, rr_chpl <dbl>, rr_chck <dbl>, rr_rlps <dbl>, rr <dbl>,
# rfs_scale <dbl>, rfs_shape <dbl>, os_resp_meanlog <dbl>,
# os_resp_sdlog <dbl>, os_nresp_rate <dbl>, util_resp <dbl>, …
$`Calc - Trans`
# A tibble: 84 × 9
model_day model_week model_month model_year series RESP REL REF
<dbl> <dbl> <dbl> <dbl> <chr> <dbl> <dbl> <dbl>
1 0 0 0 0 myfo 0.31 0 6.9 e-1
2 365 52.1 12 1 myfo 0.0486 0.256 1.63e-1
3 730 104. 24 2 myfo 0.0100 0.262 3.87e-2
4 1095 156. 36 3 myfo 0.00225 0.221 9.18e-3
5 1460 209. 48 4 myfo 0.000534 0.177 2.17e-3
6 1825 261. 60 5 myfo 0.000132 0.138 5.15e-4
7 2190 313. 72 6 myfo 0.0000336 0.108 1.22e-4
8 2555 365 84 7 myfo 0.00000877 0.0843 2.89e-5
9 2920 417. 96 8 myfo 0.00000234 0.0661 6.85e-6
10 3285 469. 108 9 myfo 0.000000636 0.0522 1.62e-6
# ℹ 74 more rows
# ℹ 1 more variable: DEAD <dbl>
$`Calc - Unit Values`
# A tibble: 32 × 26
strategy group cycle state ly_resp ly_nresp qalys_resp qalys_nresp lys
<chr> <chr> <dbl> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
1 chck All Patie… 1 DEAD 0 0 0 0 0
2 chck All Patie… 1 REF 0 1 0 0.61 1
3 chck All Patie… 1 REL 0 1 0 0.67 1
4 chck All Patie… 1 RESP 1 0 0.81 0 1
5 chck All Patie… 2 DEAD 0 0 0 0 0
6 chck All Patie… 2 REF 0 1 0 0.61 1
7 chck All Patie… 2 REL 0 1 0 0.67 1
8 chck All Patie… 2 RESP 1 0 0.81 0 1
9 chpl All Patie… 1 DEAD 0 0 0 0 0
10 chpl All Patie… 1 REF 0 1 0 0.61 1
# ℹ 22 more rows
# ℹ 17 more variables: qalys <dbl>, cost_med <dbl>, cost_resp <dbl>,
# cost_nresp <dbl>, cost_trans <dbl>, cost_hc <dbl>, .disc_ly_resp <dbl>,
# .disc_ly_nresp <dbl>, .disc_qalys_resp <dbl>, .disc_qalys_nresp <dbl>,
# .disc_lys <dbl>, .disc_qalys <dbl>, .disc_cost_med <dbl>,
# .disc_cost_resp <dbl>, .disc_cost_nresp <dbl>, .disc_cost_trans <dbl>,
# .disc_cost_hc <dbl>
$`Calc - Values`
# A tibble: 20 × 25
strategy group cycle ly_resp ly_nresp qalys_resp qalys_nresp lys qalys
<chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 chck All … 1 2.95e- 1 0.514 2.39e- 1 0.326 0.809 0.565
2 chck All … 2 4.82e- 2 0.498 3.90e- 2 0.329 0.546 0.368
3 chck All … 3 1.01e- 2 0.414 8.16e- 3 0.277 0.424 0.285
4 chck All … 4 2.29e- 3 0.332 1.85e- 3 0.222 0.334 0.224
5 chck All … 20 2.89e-12 0.0103 2.34e-12 0.00693 0.0103 0.00693
6 chpl All … 1 2.02e- 1 0.547 1.64e- 1 0.342 0.749 0.506
7 chpl All … 2 3.31e- 2 0.388 2.68e- 2 0.254 0.421 0.281
8 chpl All … 3 6.91e- 3 0.295 5.60e- 3 0.196 0.302 0.202
9 chpl All … 4 1.57e- 3 0.230 1.27e- 3 0.154 0.232 0.155
10 chpl All … 20 1.98e-12 0.00710 1.61e-12 0.00476 0.00710 0.00476
11 myfo All … 1 1.79e- 1 0.555 1.45e- 1 0.346 0.734 0.491
12 myfo All … 2 2.93e- 2 0.360 2.37e- 2 0.235 0.389 0.259
13 myfo All … 3 6.12e- 3 0.265 4.96e- 3 0.176 0.272 0.181
14 myfo All … 4 1.39e- 3 0.205 1.13e- 3 0.137 0.206 0.138
15 myfo All … 20 1.76e-12 0.00629 1.42e-12 0.00421 0.00629 0.00421
16 rlps All … 1 3.14e- 1 0.507 2.54e- 1 0.323 0.821 0.577
17 rlps All … 2 5.13e- 2 0.521 4.16e- 2 0.345 0.572 0.386
18 rlps All … 3 1.07e- 2 0.439 8.69e- 3 0.293 0.450 0.302
19 rlps All … 4 2.44e- 3 0.352 1.97e- 3 0.236 0.355 0.238
20 rlps All … 20 3.08e-12 0.0110 2.49e-12 0.00738 0.0110 0.00738
# ℹ 16 more variables: cost_med <dbl>, cost_resp <dbl>, cost_nresp <dbl>,
# cost_trans <dbl>, cost_hc <dbl>, .disc_ly_resp <dbl>, .disc_ly_nresp <dbl>,
# .disc_qalys_resp <dbl>, .disc_qalys_nresp <dbl>, .disc_lys <dbl>,
# .disc_qalys <dbl>, .disc_cost_med <dbl>, .disc_cost_resp <dbl>,
# .disc_cost_nresp <dbl>, .disc_cost_trans <dbl>, .disc_cost_hc <dbl>
$`Results - Trace`
# A tibble: 84 × 9
model_day model_week model_month model_year series RESP REL REF
<dbl> <dbl> <dbl> <dbl> <chr> <dbl> <dbl> <dbl>
1 0 0 0 0 myfo 0.31 0 6.9 e-1
2 365 52.1 12 1 myfo 0.0486 0.256 1.63e-1
3 730 104. 24 2 myfo 0.0100 0.262 3.87e-2
4 1095 156. 36 3 myfo 0.00225 0.221 9.18e-3
5 1460 209. 48 4 myfo 0.000534 0.177 2.17e-3
6 1825 261. 60 5 myfo 0.000132 0.138 5.15e-4
7 2190 313. 72 6 myfo 0.0000336 0.108 1.22e-4
8 2555 365 84 7 myfo 0.00000877 0.0843 2.89e-5
9 2920 417. 96 8 myfo 0.00000234 0.0661 6.85e-6
10 3285 469. 108 9 myfo 0.000000636 0.0522 1.62e-6
# ℹ 74 more rows
# ℹ 1 more variable: DEAD <dbl>
$`Results - Trace (Corrected)`
# A tibble: 80 × 9
model_day model_week model_month model_year series RESP REL REF
<dbl> <dbl> <dbl> <dbl> <chr> <dbl> <dbl> <dbl>
1 365 52.1 12 1 myfo 0.179 0.128 4.27e-1
2 730 104. 24 2 myfo 0.0293 0.259 1.01e-1
3 1095 156. 36 3 myfo 0.00612 0.242 2.40e-2
4 1460 209. 48 4 myfo 0.00139 0.199 5.68e-3
5 1825 261. 60 5 myfo 0.000333 0.158 1.34e-3
6 2190 313. 72 6 myfo 0.0000827 0.123 3.19e-4
7 2555 365 84 7 myfo 0.0000212 0.0961 7.55e-5
8 2920 417. 96 8 myfo 0.00000556 0.0752 1.79e-5
9 3285 469. 108 9 myfo 0.00000149 0.0592 4.24e-6
10 3650 521. 120 10 myfo 0.000000405 0.0468 1.00e-6
# ℹ 70 more rows
# ℹ 1 more variable: DEAD <dbl>
$`Results - Outcomes`
# A tibble: 128 × 5
outcome series group disc value
<chr> <chr> <chr> <lgl> <dbl>
1 lys myfo ly_resp TRUE 0.215
2 lys chpl ly_resp TRUE 0.243
3 lys chck ly_resp TRUE 0.354
4 lys rlps ly_resp TRUE 0.377
5 lys chpl vs. myfo ly_resp TRUE 0.0277
6 lys chck vs. myfo ly_resp TRUE 0.139
7 lys rlps vs. myfo ly_resp TRUE 0.162
8 lys myfo vs. chpl ly_resp TRUE -0.0277
9 lys chck vs. chpl ly_resp TRUE 0.111
10 lys rlps vs. chpl ly_resp TRUE 0.134
# ℹ 118 more rows
$`Results - Costs`
# A tibble: 128 × 5
outcome series group disc value
<chr> <chr> <chr> <lgl> <dbl>
1 cost_hc myfo cost_med TRUE 9141.
2 cost_hc chpl cost_med TRUE 9302.
3 cost_hc chck cost_med TRUE 44162.
4 cost_hc rlps cost_med TRUE 58753.
5 cost_hc chpl vs. myfo cost_med TRUE 160.
6 cost_hc chck vs. myfo cost_med TRUE 35021.
7 cost_hc rlps vs. myfo cost_med TRUE 49612.
8 cost_hc myfo vs. chpl cost_med TRUE -160.
9 cost_hc chck vs. chpl cost_med TRUE 34861.
10 cost_hc rlps vs. chpl cost_med TRUE 49452.
# ℹ 118 more rows
$`Results - CE`
# A tibble: 8 × 11
hsumm esumm health_outcome econ_outcome series cost eff dcost deffect
<chr> <chr> <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl>
1 .disc_lys .dis… .disc_lys .disc_cost_… myfo 5.43e4 2.12 NA NA
2 .disc_lys .dis… .disc_lys .disc_cost_… chpl 5.44e4 2.29 103. 0.170
3 .disc_lys .dis… .disc_lys .disc_cost_… chck 8.90e4 2.97 34630. 0.681
4 .disc_lys .dis… .disc_lys .disc_cost_… rlps 1.04e5 3.11 14543. 0.140
5 .disc_qa… .dis… .disc_qalys .disc_cost_… myfo 5.43e4 1.42 NA NA
6 .disc_qa… .dis… .disc_qalys .disc_cost_… chpl 5.44e4 1.54 103. 0.120
7 .disc_qa… .dis… .disc_qalys .disc_cost_… chck 8.90e4 2.02 34630. 0.479
8 .disc_qa… .dis… .disc_qalys .disc_cost_… rlps 1.04e5 2.12 14543. 0.0989
# ℹ 2 more variables: dref <chr>, icer <dbl>
$`Results - NMB`
# A tibble: 96 × 6
outcome series group disc type value
<chr> <chr> <chr> <lgl> <chr> <dbl>
1 lys chpl vs. myfo ly_resp TRUE health 555.
2 lys chck vs. myfo ly_resp TRUE health 2774.
3 lys rlps vs. myfo ly_resp TRUE health 3231.
4 lys myfo vs. chpl ly_resp TRUE health -555.
5 lys chck vs. chpl ly_resp TRUE health 2219.
6 lys rlps vs. chpl ly_resp TRUE health 2676.
7 lys myfo vs. chck ly_resp TRUE health -2774.
8 lys chpl vs. chck ly_resp TRUE health -2219.
9 lys rlps vs. chck ly_resp TRUE health 458.
10 lys myfo vs. rlps ly_resp TRUE health -3231.
# ℹ 86 more rows
Groups Model produces correct results.
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Code
exported
Output
$`Inputs - Settings`
# A tibble: 9 × 2
setting value
<chr> <chr>
1 disc_cost 0.03
2 disc_eff 0.03
3 n_cycles 40
4 method life-table
5 disc_method start
6 CycleLength 1
7 CycleLengthUnits years
8 ModelTimeframe 20
9 ModelTimeframeUnits years
$`Inputs - Groups`
# A tibble: 2 × 3
name weight start_age
<chr> <chr> <chr>
1 "\"adults\"" 0.8 60
2 "\"children\"" 0.2 12
$`Inputs - Strategies`
# A tibble: 3 × 2
name desc
<chr> <chr>
1 immun Immunotherapy
2 target Targeted therapy
3 chemo Chemotherapy
$`Inputs - States`
# A tibble: 3 × 4
name desc prob limit
<chr> <chr> <chr> <dbl>
1 rf Relapse-free 1 5
2 rel Post-relapse 0 5
3 dead Dead 0 1
$`Inputs - Transitions`
# A tibble: 6 × 4
strategy from to value
<chr> <chr> <chr> <chr>
1 All rf rel rfs_prob * (1 - rfs_mort)
2 All rf dead rfs_mort
3 All rf rf C
4 All rel dead rel_mort
5 All rel rel C
6 All dead dead 1
$`Inputs - Health Values`
# A tibble: 6 × 5
name label strategy state value
<chr> <chr> <chr> <chr> <chr>
1 febn Cases of febrile neutropenia All rf p_febn
2 lys_rf Relapse-free life years All rf cycle_length_years
3 lys_rel Post-relapse life years All rel cycle_length_years
4 qalys_rf Relapse-free QALYs All rf lys_rf * util_rf
5 qalys_rel Post-relapse QALYs All rel lys_rel* util_rel
6 qalys_febn Febrile neutropenia QALYs All rf febn * disutil_febn * …
$`Inputs - Econ Values`
# A tibble: 8 × 5
name label strategy state value
<chr> <chr> <chr> <chr> <chr>
1 cost_med Cost of medication chemo rf dose_chemo * freq_che…
2 cost_med Cost of medication target rf dose_target * freq_ta…
3 cost_med Cost of medication immun rf dose_immun * freq_imm…
4 cost_febn Cost of febrile neutropenia All rf ucost_febn * p_febn
5 cost_rf Routine care, relapse-free All rf ucost_rf * cycle_leng…
6 cost_rel Routine care, post-relapse All rel ucost_rel * cycle_len…
7 cost_term Cost of terminal care All rf→dead 50000
8 cost_term Cost of terminal care All rel→dead 50000
$`Inputs - Health Summ`
# A tibble: 5 × 4
name description value wtp
<chr> <chr> <chr> <dbl>
1 lys Life Years lys_rf 100000
2 lys Life Years lys_rel 100000
3 qalys QALYs qalys_rf 200000
4 qalys QALYs qalys_rel 200000
5 qalys QALYs qalys_febn 200000
$`Inputs - Econ Summ`
# A tibble: 4 × 4
name description value wtp
<chr> <chr> <chr> <dbl>
1 costs_hc Cost (HC) cost_med NA
2 costs_hc Cost (HC) cost_febn NA
3 costs_hc Cost (HC) cost_rf NA
4 costs_hc Cost (HC) cost_rel NA
$`Inputs - Parameters`
# A tibble: 38 × 6
name desc value low high psa
<chr> <chr> <chr> <chr> <chr> <chr>
1 current_age Current age "sta… "" "" ""
2 percent_male Percent male "0.4… "0.4" "0.6" "bet…
3 gp_mort_male Annualized general-population deat… "loo… "" "" ""
4 gp_mort_female Annualized general-population deat… "loo… "" "" ""
5 gp_mort Annualized general-population deat… "gp_… "" "" ""
6 gp_mort_per_cycle Per-cycle general-population death… "res… "" "" ""
7 rfs_p1 Relapse-free survival shape parame… "1.1… "bc … "bc … ""
8 rfs_p2 Relapse-free survival scale parame… "32.… "bc … "bc … ""
9 target_hr Hazard ratio of relapse, targeted … "0.6… "0.3" "0.8" ""
10 immun_hr Hazard ratio of relapse, immunothe… "0.3… "" "" ""
# ℹ 28 more rows
$`Tbl - life_table`
# A tibble: 240 × 5
age sex prob_death n_alive life_expectancy
<dbl> <chr> <dbl> <dbl> <dbl>
1 0 male 0.00632 100000 76.3
2 1 male 0.000396 99368 75.8
3 2 male 0.000282 99328 74.8
4 3 male 0.000212 99300 73.9
5 4 male 0.000186 99279 72.9
6 5 male 0.000162 99261 71.9
7 6 male 0.000144 99245 70.9
8 7 male 0.000129 99231 69.9
9 8 male 0.000114 99218 68.9
10 9 male 0.0001 99206 67.9
# ℹ 230 more rows
$`Calc - Params`
# A tibble: 600 × 59
strategy group state_time cycle model_time cycle_length_days
<chr> <chr> <dbl> <dbl> <dbl> <dbl>
1 immun adults 1 1 1 365
2 immun adults 1 2 2 365
3 immun adults 1 3 3 365
4 immun adults 1 4 4 365
5 immun adults 1 5 5 365
6 immun adults 1 6 6 365
7 immun adults 1 7 7 365
8 immun adults 1 8 8 365
9 immun adults 1 9 9 365
10 immun adults 1 10 10 365
# ℹ 590 more rows
# ℹ 53 more variables: cycle_length_weeks <dbl>, cycle_length_months <dbl>,
# cycle_length_years <dbl>, model_day <dbl>, model_week <dbl>,
# model_month <dbl>, model_year <dbl>, state_day <dbl>, state_week <dbl>,
# state_month <dbl>, state_year <dbl>, disc_h <dbl>, disc_e <dbl>,
# .group <chr>, start_age <dbl>, current_age <dbl>, percent_male <dbl>,
# gp_mort_male <dbl>, gp_mort_female <dbl>, gp_mort <dbl>, …
$`Calc - Trans`
# A tibble: 1,320 × 15
strategy group cycle from .rf_1 .rf_2 .rf_3 .rf_4 .rf_5 .rel_1 .rel_2 .rel_3
<chr> <chr> <dbl> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 immun adul… 1 .rf_1 0 0.860 0 0 0 0.116 0 0
2 immun adul… 1 .rf_2 0 0 0.842 0 0 0.134 0 0
3 immun adul… 1 .rf_3 0 0 0 0.834 0 0.142 0 0
4 immun adul… 1 .rf_4 0 0 0 0 0.828 0.148 0 0
5 immun adul… 1 .rf_5 0 0 0 0 0.824 0.152 0 0
6 immun adul… 1 .rel… 0 0 0 0 0 0 0.866 0
7 immun adul… 1 .rel… 0 0 0 0 0 0 0 0.800
8 immun adul… 1 .rel… 0 0 0 0 0 0 0 0
9 immun adul… 1 .rel… 0 0 0 0 0 0 0 0
10 immun adul… 1 .rel… 0 0 0 0 0 0 0 0
# ℹ 1,310 more rows
# ℹ 3 more variables: .rel_4 <dbl>, .rel_5 <dbl>, dead <dbl>
$`Calc - Unit Values`
# A tibble: 1,320 × 32
strategy group cycle state febn lys_rf lys_rel qalys_rf qalys_rel qalys_febn
<chr> <chr> <dbl> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 chemo adul… 1 .rel… 0 0 1 0 0.55 0
2 chemo adul… 2 .rel… 0 0 1 0 0.55 0
3 chemo adul… 3 .rel… 0 0 1 0 0.55 0
4 chemo adul… 4 .rel… 0 0 1 0 0.55 0
5 chemo adul… 5 .rel… 0 0 1 0 0.55 0
6 chemo adul… 6 .rel… 0 0 1 0 0.55 0
7 chemo adul… 7 .rel… 0 0 1 0 0.55 0
8 chemo adul… 8 .rel… 0 0 1 0 0.55 0
9 chemo adul… 9 .rel… 0 0 1 0 0.55 0
10 chemo adul… 10 .rel… 0 0 1 0 0.55 0
# ℹ 1,310 more rows
# ℹ 22 more variables: lys <dbl>, qalys <dbl>, cost_med <dbl>, cost_febn <dbl>,
# cost_rf <dbl>, cost_rel <dbl>, cost_term <dbl>, costs_hc <dbl>,
# .disc_febn <dbl>, .disc_lys_rf <dbl>, .disc_lys_rel <dbl>,
# .disc_qalys_rf <dbl>, .disc_qalys_rel <dbl>, .disc_qalys_febn <dbl>,
# .disc_lys <dbl>, .disc_qalys <dbl>, .disc_cost_med <dbl>,
# .disc_cost_febn <dbl>, .disc_cost_rf <dbl>, .disc_cost_rel <dbl>, …
$`Calc - Values`
# A tibble: 120 × 31
strategy group cycle febn lys_rf lys_rel qalys_rf qalys_rel qalys_febn
<chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 chemo adults 1 0.0128 0.850 0.138 0.697 0.0758 -0.000440
2 chemo adults 2 0.00872 0.581 0.367 0.477 0.202 -0.000301
3 chemo adults 3 0.00570 0.380 0.496 0.311 0.273 -0.000197
4 chemo adults 4 0.00363 0.242 0.532 0.199 0.292 -0.000125
5 chemo adults 5 0.00228 0.152 0.505 0.124 0.278 -0.0000786
6 chemo adults 6 0.00141 0.0940 0.444 0.0771 0.244 -0.0000487
7 chemo adults 7 0.000872 0.0581 0.369 0.0477 0.203 -0.0000301
8 chemo adults 8 0.000537 0.0358 0.296 0.0294 0.163 -0.0000185
9 chemo adults 9 0.000330 0.0220 0.231 0.0180 0.127 -0.0000114
10 chemo adults 10 0.000202 0.0135 0.177 0.0110 0.0973 -0.00000697
# ℹ 110 more rows
# ℹ 22 more variables: lys <dbl>, qalys <dbl>, cost_med <dbl>, cost_febn <dbl>,
# cost_rf <dbl>, cost_rel <dbl>, cost_term <dbl>, costs_hc <dbl>,
# .disc_febn <dbl>, .disc_lys_rf <dbl>, .disc_lys_rel <dbl>,
# .disc_qalys_rf <dbl>, .disc_qalys_rel <dbl>, .disc_qalys_febn <dbl>,
# .disc_lys <dbl>, .disc_qalys <dbl>, .disc_cost_med <dbl>,
# .disc_cost_febn <dbl>, .disc_cost_rf <dbl>, .disc_cost_rel <dbl>, …
$`Results - Trace`
# A tibble: 63 × 8
model_day model_week model_month model_year series rf rel dead
<dbl> <dbl> <dbl> <dbl> <chr> <dbl> <dbl> <dbl>
1 0 0 0 0 immun 1 0 0
2 365 52.1 12 1 immun 0.865 0.116 0.0193
3 730 104. 24 2 immun 0.730 0.217 0.0525
4 1095 156. 36 3 immun 0.610 0.286 0.104
5 1460 209. 48 4 immun 0.506 0.323 0.172
6 1825 261. 60 5 immun 0.416 0.334 0.250
7 2190 313. 72 6 immun 0.342 0.325 0.333
8 2555 365 84 7 immun 0.280 0.303 0.416
9 2920 417. 96 8 immun 0.229 0.275 0.496
10 3285 469. 108 9 immun 0.187 0.244 0.569
# ℹ 53 more rows
$`Results - Trace (Corrected)`
# A tibble: 60 × 8
model_day model_week model_month model_year series rf rel dead
<dbl> <dbl> <dbl> <dbl> <chr> <dbl> <dbl> <dbl>
1 365 52.1 12 1 immun 0.932 0.0581 0.00963
2 730 104. 24 2 immun 0.797 0.167 0.0359
3 1095 156. 36 3 immun 0.670 0.251 0.0784
4 1460 209. 48 4 immun 0.558 0.304 0.138
5 1825 261. 60 5 immun 0.461 0.328 0.211
6 2190 313. 72 6 immun 0.379 0.329 0.291
7 2555 365 84 7 immun 0.311 0.314 0.375
8 2920 417. 96 8 immun 0.255 0.289 0.456
9 3285 469. 108 9 immun 0.208 0.259 0.532
10 3650 521. 120 10 immun 0.170 0.228 0.602
# ℹ 50 more rows
$`Results - Outcomes`
# A tibble: 90 × 5
outcome series group disc value
<chr> <chr> <chr> <lgl> <dbl>
1 lys immun lys_rf TRUE 4.78
2 lys target lys_rf TRUE 3.28
3 lys chemo lys_rf TRUE 2.36
4 lys target vs. immun lys_rf TRUE -1.49
5 lys chemo vs. immun lys_rf TRUE -2.42
6 lys immun vs. target lys_rf TRUE 1.49
7 lys chemo vs. target lys_rf TRUE -0.924
8 lys immun vs. chemo lys_rf TRUE 2.42
9 lys target vs. chemo lys_rf TRUE 0.924
10 lys immun lys_rel TRUE 2.88
# ℹ 80 more rows
$`Results - Costs`
# A tibble: 72 × 5
outcome series group disc value
<chr> <chr> <chr> <lgl> <dbl>
1 costs_hc immun cost_med TRUE 48142.
2 costs_hc target cost_med TRUE 26459.
3 costs_hc chemo cost_med TRUE 67888.
4 costs_hc target vs. immun cost_med TRUE -21683.
5 costs_hc chemo vs. immun cost_med TRUE 19746.
6 costs_hc immun vs. target cost_med TRUE 21683.
7 costs_hc chemo vs. target cost_med TRUE 41429.
8 costs_hc immun vs. chemo cost_med TRUE -19746.
9 costs_hc target vs. chemo cost_med TRUE -41429.
10 costs_hc immun cost_febn TRUE 92.4
# ℹ 62 more rows
$`Results - CE`
# A tibble: 6 × 11
hsumm esumm health_outcome econ_outcome series cost eff dcost deffect
<chr> <chr> <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl>
1 .disc_lys .dis… .disc_lys .disc_costs… target 4.64e5 6.61 NA NA
2 .disc_lys .dis… .disc_lys .disc_costs… chemo 4.95e5 5.92 30931. -0.687
3 .disc_lys .dis… .disc_lys .disc_costs… immun 4.97e5 7.66 32728. 1.05
4 .disc_qa… .dis… .disc_qalys .disc_costs… target 4.64e5 4.52 NA NA
5 .disc_qa… .dis… .disc_qalys .disc_costs… chemo 4.95e5 3.89 30931. -0.627
6 .disc_qa… .dis… .disc_qalys .disc_costs… immun 4.97e5 5.50 32728. 0.981
# ℹ 2 more variables: dref <chr>, icer <dbl>
$`Results - NMB`
# A tibble: 54 × 6
outcome series group disc type value
<chr> <chr> <chr> <lgl> <chr> <dbl>
1 lys target vs. immun lys_rf TRUE health -149490.
2 lys chemo vs. immun lys_rf TRUE health -241881.
3 lys immun vs. target lys_rf TRUE health 149490.
4 lys chemo vs. target lys_rf TRUE health -92390.
5 lys immun vs. chemo lys_rf TRUE health 241881.
6 lys target vs. chemo lys_rf TRUE health 92390.
7 lys target vs. immun lys_rel TRUE health 44547.
8 lys chemo vs. immun lys_rel TRUE health 68251.
9 lys immun vs. target lys_rel TRUE health -44547.
10 lys chemo vs. target lys_rel TRUE health 23704.
# ℹ 44 more rows
Code
exported_limited
Output
$`Inputs - Settings`
# A tibble: 9 × 2
setting value
<chr> <chr>
1 disc_cost 0.03
2 disc_eff 0.03
3 n_cycles 40
4 method life-table
5 disc_method start
6 CycleLength 1
7 CycleLengthUnits years
8 ModelTimeframe 20
9 ModelTimeframeUnits years
$`Inputs - Groups`
# A tibble: 2 × 3
name weight start_age
<chr> <chr> <chr>
1 "\"adults\"" 0.8 60
2 "\"children\"" 0.2 12
$`Inputs - Strategies`
# A tibble: 3 × 2
name desc
<chr> <chr>
1 immun Immunotherapy
2 target Targeted therapy
3 chemo Chemotherapy
$`Inputs - States`
# A tibble: 3 × 4
name desc prob limit
<chr> <chr> <chr> <dbl>
1 rf Relapse-free 1 5
2 rel Post-relapse 0 5
3 dead Dead 0 1
$`Inputs - Transitions`
# A tibble: 6 × 4
strategy from to value
<chr> <chr> <chr> <chr>
1 All rf rel rfs_prob * (1 - rfs_mort)
2 All rf dead rfs_mort
3 All rf rf C
4 All rel dead rel_mort
5 All rel rel C
6 All dead dead 1
$`Inputs - Health Values`
# A tibble: 6 × 5
name label strategy state value
<chr> <chr> <chr> <chr> <chr>
1 febn Cases of febrile neutropenia All rf p_febn
2 lys_rf Relapse-free life years All rf cycle_length_years
3 lys_rel Post-relapse life years All rel cycle_length_years
4 qalys_rf Relapse-free QALYs All rf lys_rf * util_rf
5 qalys_rel Post-relapse QALYs All rel lys_rel* util_rel
6 qalys_febn Febrile neutropenia QALYs All rf febn * disutil_febn * …
$`Inputs - Econ Values`
# A tibble: 8 × 5
name label strategy state value
<chr> <chr> <chr> <chr> <chr>
1 cost_med Cost of medication chemo rf dose_chemo * freq_che…
2 cost_med Cost of medication target rf dose_target * freq_ta…
3 cost_med Cost of medication immun rf dose_immun * freq_imm…
4 cost_febn Cost of febrile neutropenia All rf ucost_febn * p_febn
5 cost_rf Routine care, relapse-free All rf ucost_rf * cycle_leng…
6 cost_rel Routine care, post-relapse All rel ucost_rel * cycle_len…
7 cost_term Cost of terminal care All rf→dead 50000
8 cost_term Cost of terminal care All rel→dead 50000
$`Inputs - Health Summ`
# A tibble: 5 × 4
name description value wtp
<chr> <chr> <chr> <dbl>
1 lys Life Years lys_rf 100000
2 lys Life Years lys_rel 100000
3 qalys QALYs qalys_rf 200000
4 qalys QALYs qalys_rel 200000
5 qalys QALYs qalys_febn 200000
$`Inputs - Econ Summ`
# A tibble: 4 × 4
name description value wtp
<chr> <chr> <chr> <dbl>
1 costs_hc Cost (HC) cost_med NA
2 costs_hc Cost (HC) cost_febn NA
3 costs_hc Cost (HC) cost_rf NA
4 costs_hc Cost (HC) cost_rel NA
$`Inputs - Parameters`
# A tibble: 38 × 6
name desc value low high psa
<chr> <chr> <chr> <chr> <chr> <chr>
1 current_age Current age "sta… "" "" ""
2 percent_male Percent male "0.4… "0.4" "0.6" "bet…
3 gp_mort_male Annualized general-population deat… "loo… "" "" ""
4 gp_mort_female Annualized general-population deat… "loo… "" "" ""
5 gp_mort Annualized general-population deat… "gp_… "" "" ""
6 gp_mort_per_cycle Per-cycle general-population death… "res… "" "" ""
7 rfs_p1 Relapse-free survival shape parame… "1.1… "bc … "bc … ""
8 rfs_p2 Relapse-free survival scale parame… "32.… "bc … "bc … ""
9 target_hr Hazard ratio of relapse, targeted … "0.6… "0.3" "0.8" ""
10 immun_hr Hazard ratio of relapse, immunothe… "0.3… "" "" ""
# ℹ 28 more rows
$`Tbl - life_table`
# A tibble: 240 × 5
age sex prob_death n_alive life_expectancy
<dbl> <chr> <dbl> <dbl> <dbl>
1 0 male 0.00632 100000 76.3
2 1 male 0.000396 99368 75.8
3 2 male 0.000282 99328 74.8
4 3 male 0.000212 99300 73.9
5 4 male 0.000186 99279 72.9
6 5 male 0.000162 99261 71.9
7 6 male 0.000144 99245 70.9
8 7 male 0.000129 99231 69.9
9 8 male 0.000114 99218 68.9
10 9 male 0.0001 99206 67.9
# ℹ 230 more rows
$`Calc - Params`
# A tibble: 24 × 59
strategy group state_time cycle model_time cycle_length_days
<chr> <chr> <dbl> <dbl> <dbl> <dbl>
1 immun adults 1 1 1 365
2 immun adults 1 2 2 365
3 immun adults 1 3 3 365
4 immun adults 1 4 4 365
5 immun children 1 1 1 365
6 immun children 1 2 2 365
7 immun children 1 3 3 365
8 immun children 1 4 4 365
9 target adults 1 1 1 365
10 target adults 1 2 2 365
# ℹ 14 more rows
# ℹ 53 more variables: cycle_length_weeks <dbl>, cycle_length_months <dbl>,
# cycle_length_years <dbl>, model_day <dbl>, model_week <dbl>,
# model_month <dbl>, model_year <dbl>, state_day <dbl>, state_week <dbl>,
# state_month <dbl>, state_year <dbl>, disc_h <dbl>, disc_e <dbl>,
# .group <chr>, start_age <dbl>, current_age <dbl>, percent_male <dbl>,
# gp_mort_male <dbl>, gp_mort_female <dbl>, gp_mort <dbl>, …
$`Calc - Trans`
# A tibble: 24 × 15
strategy group cycle from .rf_1 .rf_2 .rf_3 .rf_4 .rf_5 .rel_1 .rel_2 .rel_3
<chr> <chr> <dbl> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 immun adul… 1 .rf_1 0 0.860 0 0 0 0.116 0 0
2 immun adul… 1 .rf_2 0 0 0.842 0 0 0.134 0 0
3 immun adul… 1 .rf_3 0 0 0 0.834 0 0.142 0 0
4 immun adul… 1 .rf_4 0 0 0 0 0.828 0.148 0 0
5 immun chil… 1 .rf_1 0 0.881 0 0 0 0.118 0 0
6 immun chil… 1 .rf_2 0 0 0.862 0 0 0.137 0 0
7 immun chil… 1 .rf_3 0 0 0 0.854 0 0.146 0 0
8 immun chil… 1 .rf_4 0 0 0 0 0.848 0.151 0 0
9 target adul… 1 .rf_1 0 0.787 0 0 0 0.189 0 0
10 target adul… 1 .rf_2 0 0 0.758 0 0 0.218 0 0
# ℹ 14 more rows
# ℹ 3 more variables: .rel_4 <dbl>, .rel_5 <dbl>, dead <dbl>
$`Calc - Unit Values`
# A tibble: 66 × 32
strategy group cycle state febn lys_rf lys_rel qalys_rf qalys_rel qalys_febn
<chr> <chr> <dbl> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 chemo adul… 1 .rel… 0 0 1 0 0.55 0
2 chemo adul… 1 .rel… 0 0 1 0 0.55 0
3 chemo adul… 1 .rel… 0 0 1 0 0.55 0
4 chemo adul… 1 .rel… 0 0 1 0 0.55 0
5 chemo adul… 1 .rel… 0 0 1 0 0.55 0
6 chemo adul… 1 .rf_1 0.015 1 0 0.82 0 -0.000518
7 chemo adul… 1 .rf_2 0.015 1 0 0.82 0 -0.000518
8 chemo adul… 1 .rf_3 0.015 1 0 0.82 0 -0.000518
9 chemo adul… 1 .rf_4 0.015 1 0 0.82 0 -0.000518
10 chemo adul… 1 .rf_5 0.015 1 0 0.82 0 -0.000518
# ℹ 56 more rows
# ℹ 22 more variables: lys <dbl>, qalys <dbl>, cost_med <dbl>, cost_febn <dbl>,
# cost_rf <dbl>, cost_rel <dbl>, cost_term <dbl>, costs_hc <dbl>,
# .disc_febn <dbl>, .disc_lys_rf <dbl>, .disc_lys_rel <dbl>,
# .disc_qalys_rf <dbl>, .disc_qalys_rel <dbl>, .disc_qalys_febn <dbl>,
# .disc_lys <dbl>, .disc_qalys <dbl>, .disc_cost_med <dbl>,
# .disc_cost_febn <dbl>, .disc_cost_rf <dbl>, .disc_cost_rel <dbl>, …
$`Calc - Values`
# A tibble: 24 × 31
strategy group cycle febn lys_rf lys_rel qalys_rf qalys_rel qalys_febn
<chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 chemo adults 1 0.0128 0.850 0.138 0.697 0.0758 -0.000440
2 chemo adults 2 0.00872 0.581 0.367 0.477 0.202 -0.000301
3 chemo adults 3 0.00570 0.380 0.496 0.311 0.273 -0.000197
4 chemo adults 4 0.00363 0.242 0.532 0.199 0.292 -0.000125
5 chemo children 1 0.0129 0.859 0.141 0.704 0.0776 -0.000445
6 chemo children 2 0.00902 0.602 0.380 0.493 0.209 -0.000312
7 chemo children 3 0.00605 0.403 0.522 0.331 0.287 -0.000209
8 chemo children 4 0.00397 0.264 0.569 0.217 0.313 -0.000137
9 immun adults 1 0.00600 0.930 0.0578 0.763 0.0318 -0.000207
10 immun adults 2 0.00511 0.792 0.165 0.649 0.0910 -0.000176
# ℹ 14 more rows
# ℹ 22 more variables: lys <dbl>, qalys <dbl>, cost_med <dbl>, cost_febn <dbl>,
# cost_rf <dbl>, cost_rel <dbl>, cost_term <dbl>, costs_hc <dbl>,
# .disc_febn <dbl>, .disc_lys_rf <dbl>, .disc_lys_rel <dbl>,
# .disc_qalys_rf <dbl>, .disc_qalys_rel <dbl>, .disc_qalys_febn <dbl>,
# .disc_lys <dbl>, .disc_qalys <dbl>, .disc_cost_med <dbl>,
# .disc_cost_febn <dbl>, .disc_cost_rf <dbl>, .disc_cost_rel <dbl>, …
$`Results - Trace`
# A tibble: 63 × 8
model_day model_week model_month model_year series rf rel dead
<dbl> <dbl> <dbl> <dbl> <chr> <dbl> <dbl> <dbl>
1 0 0 0 0 immun 1 0 0
2 365 52.1 12 1 immun 0.865 0.116 0.0193
3 730 104. 24 2 immun 0.730 0.217 0.0525
4 1095 156. 36 3 immun 0.610 0.286 0.104
5 1460 209. 48 4 immun 0.506 0.323 0.172
6 1825 261. 60 5 immun 0.416 0.334 0.250
7 2190 313. 72 6 immun 0.342 0.325 0.333
8 2555 365 84 7 immun 0.280 0.303 0.416
9 2920 417. 96 8 immun 0.229 0.275 0.496
10 3285 469. 108 9 immun 0.187 0.244 0.569
# ℹ 53 more rows
$`Results - Trace (Corrected)`
# A tibble: 60 × 8
model_day model_week model_month model_year series rf rel dead
<dbl> <dbl> <dbl> <dbl> <chr> <dbl> <dbl> <dbl>
1 365 52.1 12 1 immun 0.932 0.0581 0.00963
2 730 104. 24 2 immun 0.797 0.167 0.0359
3 1095 156. 36 3 immun 0.670 0.251 0.0784
4 1460 209. 48 4 immun 0.558 0.304 0.138
5 1825 261. 60 5 immun 0.461 0.328 0.211
6 2190 313. 72 6 immun 0.379 0.329 0.291
7 2555 365 84 7 immun 0.311 0.314 0.375
8 2920 417. 96 8 immun 0.255 0.289 0.456
9 3285 469. 108 9 immun 0.208 0.259 0.532
10 3650 521. 120 10 immun 0.170 0.228 0.602
# ℹ 50 more rows
$`Results - Outcomes`
# A tibble: 90 × 5
outcome series group disc value
<chr> <chr> <chr> <lgl> <dbl>
1 lys immun lys_rf TRUE 4.78
2 lys target lys_rf TRUE 3.28
3 lys chemo lys_rf TRUE 2.36
4 lys target vs. immun lys_rf TRUE -1.49
5 lys chemo vs. immun lys_rf TRUE -2.42
6 lys immun vs. target lys_rf TRUE 1.49
7 lys chemo vs. target lys_rf TRUE -0.924
8 lys immun vs. chemo lys_rf TRUE 2.42
9 lys target vs. chemo lys_rf TRUE 0.924
10 lys immun lys_rel TRUE 2.88
# ℹ 80 more rows
$`Results - Costs`
# A tibble: 72 × 5
outcome series group disc value
<chr> <chr> <chr> <lgl> <dbl>
1 costs_hc immun cost_med TRUE 48142.
2 costs_hc target cost_med TRUE 26459.
3 costs_hc chemo cost_med TRUE 67888.
4 costs_hc target vs. immun cost_med TRUE -21683.
5 costs_hc chemo vs. immun cost_med TRUE 19746.
6 costs_hc immun vs. target cost_med TRUE 21683.
7 costs_hc chemo vs. target cost_med TRUE 41429.
8 costs_hc immun vs. chemo cost_med TRUE -19746.
9 costs_hc target vs. chemo cost_med TRUE -41429.
10 costs_hc immun cost_febn TRUE 92.4
# ℹ 62 more rows
$`Results - CE`
# A tibble: 6 × 11
hsumm esumm health_outcome econ_outcome series cost eff dcost deffect
<chr> <chr> <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl>
1 .disc_lys .dis… .disc_lys .disc_costs… target 4.64e5 6.61 NA NA
2 .disc_lys .dis… .disc_lys .disc_costs… chemo 4.95e5 5.92 30931. -0.687
3 .disc_lys .dis… .disc_lys .disc_costs… immun 4.97e5 7.66 32728. 1.05
4 .disc_qa… .dis… .disc_qalys .disc_costs… target 4.64e5 4.52 NA NA
5 .disc_qa… .dis… .disc_qalys .disc_costs… chemo 4.95e5 3.89 30931. -0.627
6 .disc_qa… .dis… .disc_qalys .disc_costs… immun 4.97e5 5.50 32728. 0.981
# ℹ 2 more variables: dref <chr>, icer <dbl>
$`Results - NMB`
# A tibble: 54 × 6
outcome series group disc type value
<chr> <chr> <chr> <lgl> <chr> <dbl>
1 lys target vs. immun lys_rf TRUE health -149490.
2 lys chemo vs. immun lys_rf TRUE health -241881.
3 lys immun vs. target lys_rf TRUE health 149490.
4 lys chemo vs. target lys_rf TRUE health -92390.
5 lys immun vs. chemo lys_rf TRUE health 241881.
6 lys target vs. chemo lys_rf TRUE health 92390.
7 lys target vs. immun lys_rel TRUE health 44547.
8 lys chemo vs. immun lys_rel TRUE health 68251.
9 lys immun vs. target lys_rel TRUE health -44547.
10 lys chemo vs. target lys_rel TRUE health 23704.
# ℹ 44 more rows
Simple Markov Model produces correct results.
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Code
exported
Output
$`Inputs - Settings`
# A tibble: 4 × 2
setting value
<chr> <chr>
1 disc_cost 0.03
2 disc_eff 0.03
3 cycle_length 365
4 n_cycles 20
$`Inputs - Strategies`
# A tibble: 2 × 2
name desc
<chr> <chr>
1 nat Natural History
2 new New Treatment
$`Inputs - States`
# A tibble: 3 × 4
name desc prob limit
<chr> <chr> <chr> <dbl>
1 well Patient is healthy 1 0
2 sick Patient is sick 0 0
3 dead Patient is dead 0 0
$`Inputs - Transitions`
# A tibble: 7 × 4
strategy from to value
<chr> <chr> <chr> <chr>
1 nat well sick p_sick_nat
2 new well sick p_sick_new
3 All well dead p_death_well
4 All well well C
5 All sick dead p_death_sick
6 All sick sick C
7 All dead dead 1
$`Inputs - Health Values`
# A tibble: 5 × 5
name description strategy state value
<chr> <chr> <chr> <chr> <chr>
1 well_lys Well life-years All well cycle_length_years
2 sick_lys Sick life-years All sick cycle_length_years
3 well_qalys Well QALYs nat All util_well_nat * well_lys
4 well_qalys Label... new All util_well_new * well_lys
5 sick_qalys Sick QALYs All All sick_lys * util_sick
$`Inputs - Econ Values`
# A tibble: 3 × 5
name description strategy state value
<chr> <chr> <chr> <chr> <chr>
1 med_cost Medication cost new well cost_new
2 term_cost Terminal care cost All sick→dead cost_hosp_stay
3 ae_cost Adverse Event Cost nat Model Start 100
$`Inputs - Health Summ`
# A tibble: 4 × 4
name description value wtp
<chr> <chr> <chr> <dbl>
1 lys Life-years well_lys 100000
2 lys Label... sick_lys 100000
3 qalys QALYs well_qalys 150000
4 qalys Label... sick_qalys 100000
$`Inputs - Econ Summ`
# A tibble: 3 × 3
name description value
<chr> <chr> <chr>
1 cost_hc Healthcare system costs med_cost
2 cost_hc Label... term_cost
3 cost_hc Healthcare system costs ae_cost
$`Inputs - Parameters`
# A tibble: 11 × 6
name desc value low high psa
<chr> <chr> <chr> <chr> <chr> <chr>
1 p_sick_nat Probability of getting sick, natura… 0.5 "bc … "bc … "bin…
2 p_sick_new Probability of getting sick, new dr… 0.30 "bc … "bc … "bin…
3 p_death_well Probability of dying while well 0.005 "0.0… "0.0… "bin…
4 p_death_sick Probability of dying while sick 0.08 "bc … "bc … "bin…
5 cost_new Cost per year of new drug 32000 "240… "480… ""
6 util_well_nat Utility value for well state, natur… 0.85 "" "" "log…
7 disutil_well_new Utility decrement associated with n… 0.02 "" "" "log…
8 disutil_sick Utility decrement associated with b… 0.23 "" "" "log…
9 cost_hosp_stay Cost of a hospital stay 85000 "" "" "nor…
10 util_well_new Utility value for well state, new d… util… "" "" ""
11 util_sick Utility value for sick state util… "" "" ""
$`Calc - Params`
# A tibble: 40 × 30
strategy group state_time cycle model_time cycle_length_days
<chr> <chr> <dbl> <dbl> <dbl> <dbl>
1 nat All Patients 1 1 1 365
2 nat All Patients 1 2 2 365
3 nat All Patients 1 3 3 365
4 nat All Patients 1 4 4 365
5 nat All Patients 1 5 5 365
6 nat All Patients 1 6 6 365
7 nat All Patients 1 7 7 365
8 nat All Patients 1 8 8 365
9 nat All Patients 1 9 9 365
10 nat All Patients 1 10 10 365
# ℹ 30 more rows
# ℹ 24 more variables: cycle_length_weeks <dbl>, cycle_length_months <dbl>,
# cycle_length_years <dbl>, model_day <dbl>, model_week <dbl>,
# model_month <dbl>, model_year <dbl>, state_day <dbl>, state_week <dbl>,
# state_month <dbl>, state_year <dbl>, disc_h <dbl>, disc_e <dbl>,
# p_sick_nat <dbl>, p_sick_new <dbl>, p_death_well <dbl>, p_death_sick <dbl>,
# cost_new <dbl>, util_well_nat <dbl>, disutil_well_new <dbl>, …
$`Calc - Trans`
# A tibble: 120 × 7
strategy group cycle from well sick dead
<chr> <chr> <dbl> <chr> <dbl> <dbl> <dbl>
1 nat All Patients 1 well 0.495 0.5 0.005
2 nat All Patients 1 sick 0 0.92 0.08
3 nat All Patients 1 dead 0 0 1
4 nat All Patients 2 well 0.495 0.5 0.005
5 nat All Patients 2 sick 0 0.92 0.08
6 nat All Patients 2 dead 0 0 1
7 nat All Patients 3 well 0.495 0.5 0.005
8 nat All Patients 3 sick 0 0.92 0.08
9 nat All Patients 3 dead 0 0 1
10 nat All Patients 4 well 0.495 0.5 0.005
# ℹ 110 more rows
$`Calc - Unit Values`
# A tibble: 120 × 24
strategy group cycle state well_lys sick_lys well_qalys sick_qalys lys
<chr> <chr> <dbl> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
1 nat All Patie… 1 dead 0 0 0 0 0
2 nat All Patie… 2 dead 0 0 0 0 0
3 nat All Patie… 3 dead 0 0 0 0 0
4 nat All Patie… 4 dead 0 0 0 0 0
5 nat All Patie… 5 dead 0 0 0 0 0
6 nat All Patie… 6 dead 0 0 0 0 0
7 nat All Patie… 7 dead 0 0 0 0 0
8 nat All Patie… 8 dead 0 0 0 0 0
9 nat All Patie… 9 dead 0 0 0 0 0
10 nat All Patie… 10 dead 0 0 0 0 0
# ℹ 110 more rows
# ℹ 15 more variables: qalys <dbl>, med_cost <dbl>, term_cost <dbl>,
# ae_cost <dbl>, cost_hc <dbl>, .disc_well_lys <dbl>, .disc_sick_lys <dbl>,
# .disc_well_qalys <dbl>, .disc_sick_qalys <dbl>, .disc_lys <dbl>,
# .disc_qalys <dbl>, .disc_med_cost <dbl>, .disc_term_cost <dbl>,
# .disc_ae_cost <dbl>, .disc_cost_hc <dbl>
$`Calc - Values`
# A tibble: 40 × 23
strategy group cycle well_lys sick_lys well_qalys sick_qalys lys qalys
<chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 nat All Patie… 1 0.748 0.25 0.635 0.155 0.998 0.790
2 nat All Patie… 2 0.370 0.604 0.315 0.374 0.974 0.689
3 nat All Patie… 3 0.183 0.740 0.156 0.459 0.924 0.615
4 nat All Patie… 4 0.0907 0.773 0.0771 0.479 0.863 0.556
5 nat All Patie… 5 0.0449 0.756 0.0381 0.469 0.801 0.507
6 nat All Patie… 6 0.0222 0.718 0.0189 0.445 0.740 0.464
7 nat All Patie… 7 0.0110 0.672 0.00935 0.417 0.683 0.426
8 nat All Patie… 8 0.00544 0.624 0.00463 0.387 0.629 0.391
9 nat All Patie… 9 0.00269 0.576 0.00229 0.357 0.579 0.360
10 nat All Patie… 10 0.00133 0.532 0.00113 0.330 0.533 0.331
# ℹ 30 more rows
# ℹ 14 more variables: med_cost <dbl>, term_cost <dbl>, ae_cost <dbl>,
# cost_hc <dbl>, .disc_well_lys <dbl>, .disc_sick_lys <dbl>,
# .disc_well_qalys <dbl>, .disc_sick_qalys <dbl>, .disc_lys <dbl>,
# .disc_qalys <dbl>, .disc_med_cost <dbl>, .disc_term_cost <dbl>,
# .disc_ae_cost <dbl>, .disc_cost_hc <dbl>
$`Results - Trace`
# A tibble: 42 × 8
model_day model_week model_month model_year series well sick dead
<dbl> <dbl> <dbl> <dbl> <chr> <dbl> <dbl> <dbl>
1 0 0 0 0 nat 1 0 0
2 365 52.1 12 1 nat 0.495 0.5 0.005
3 730 104. 24 2 nat 0.245 0.708 0.0475
4 1095 156. 36 3 nat 0.121 0.773 0.105
5 1460 209. 48 4 nat 0.0600 0.772 0.168
6 1825 261. 60 5 nat 0.0297 0.740 0.230
7 2190 313. 72 6 nat 0.0147 0.696 0.289
8 2555 365 84 7 nat 0.00728 0.648 0.345
9 2920 417. 96 8 nat 0.00360 0.600 0.397
10 3285 469. 108 9 nat 0.00178 0.553 0.445
# ℹ 32 more rows
$`Results - Trace (Corrected)`
# A tibble: 40 × 8
model_day model_week model_month model_year series well sick dead
<dbl> <dbl> <dbl> <dbl> <chr> <dbl> <dbl> <dbl>
1 365 52.1 12 1 nat 0.748 0.25 0.0025
2 730 104. 24 2 nat 0.370 0.604 0.0262
3 1095 156. 36 3 nat 0.183 0.740 0.0764
4 1460 209. 48 4 nat 0.0907 0.773 0.137
5 1825 261. 60 5 nat 0.0449 0.756 0.199
6 2190 313. 72 6 nat 0.0222 0.718 0.260
7 2555 365 84 7 nat 0.0110 0.672 0.317
8 2920 417. 96 8 nat 0.00544 0.624 0.371
9 3285 469. 108 9 nat 0.00269 0.576 0.421
10 3650 521. 120 10 nat 0.00133 0.532 0.467
# ℹ 30 more rows
$`Results - Outcomes`
# A tibble: 32 × 5
outcome series group disc value
<chr> <chr> <chr> <lgl> <dbl>
1 lys nat well_lys TRUE 1.44
2 lys new well_lys TRUE 2.60
3 lys new vs. nat well_lys TRUE 1.17
4 lys nat vs. new well_lys TRUE -1.17
5 lys nat sick_lys TRUE 7.78
6 lys new sick_lys TRUE 7.26
7 lys new vs. nat sick_lys TRUE -0.517
8 lys nat vs. new sick_lys TRUE 0.517
9 qalys nat well_qalys TRUE 1.22
10 qalys new well_qalys TRUE 2.16
# ℹ 22 more rows
$`Results - Costs`
# A tibble: 24 × 5
outcome series group disc value
<chr> <chr> <chr> <lgl> <dbl>
1 cost_hc nat med_cost TRUE 0
2 cost_hc new med_cost TRUE 83352.
3 cost_hc new vs. nat med_cost TRUE 83352.
4 cost_hc nat vs. new med_cost TRUE -83352.
5 cost_hc nat term_cost TRUE 51681.
6 cost_hc new term_cost TRUE 48161.
7 cost_hc new vs. nat term_cost TRUE -3520.
8 cost_hc nat vs. new term_cost TRUE 3520.
9 cost_hc nat ae_cost TRUE 100
10 cost_hc new ae_cost TRUE 0
# ℹ 14 more rows
$`Results - CE`
# A tibble: 4 × 11
hsumm esumm health_outcome econ_outcome series cost eff dcost deffect
<chr> <chr> <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl>
1 .disc_lys .dis… .disc_lys .disc_cost_… nat 5.18e4 9.22 NA NA
2 .disc_lys .dis… .disc_lys .disc_cost_… new 1.32e5 9.87 79732. 0.648
3 .disc_qa… .dis… .disc_qalys .disc_cost_… nat 5.18e4 6.05 NA NA
4 .disc_qa… .dis… .disc_qalys .disc_cost_… new 1.32e5 6.66 79732. 0.618
# ℹ 2 more variables: dref <chr>, icer <dbl>
$`Results - NMB`
# A tibble: 14 × 6
outcome series group disc type value
<chr> <chr> <chr> <lgl> <chr> <dbl>
1 lys new vs. nat well_lys TRUE health 116564.
2 lys nat vs. new well_lys TRUE health -116564.
3 lys new vs. nat sick_lys TRUE health -51719.
4 lys nat vs. new sick_lys TRUE health 51719.
5 qalys new vs. nat well_qalys TRUE health 140805.
6 qalys nat vs. new well_qalys TRUE health -140805.
7 qalys new vs. nat sick_qalys TRUE health -48098.
8 qalys nat vs. new sick_qalys TRUE health 48098.
9 cost_hc new vs. nat med_cost TRUE economic -83352.
10 cost_hc nat vs. new med_cost TRUE economic 83352.
11 cost_hc new vs. nat term_cost TRUE economic 3520.
12 cost_hc nat vs. new term_cost TRUE economic -3520.
13 cost_hc new vs. nat ae_cost TRUE economic 100
14 cost_hc nat vs. new ae_cost TRUE economic -100
Code
exported_limited
Output
$`Inputs - Settings`
# A tibble: 4 × 2
setting value
<chr> <chr>
1 disc_cost 0.03
2 disc_eff 0.03
3 cycle_length 365
4 n_cycles 20
$`Inputs - Strategies`
# A tibble: 2 × 2
name desc
<chr> <chr>
1 nat Natural History
2 new New Treatment
$`Inputs - States`
# A tibble: 3 × 4
name desc prob limit
<chr> <chr> <chr> <dbl>
1 well Patient is healthy 1 0
2 sick Patient is sick 0 0
3 dead Patient is dead 0 0
$`Inputs - Transitions`
# A tibble: 7 × 4
strategy from to value
<chr> <chr> <chr> <chr>
1 nat well sick p_sick_nat
2 new well sick p_sick_new
3 All well dead p_death_well
4 All well well C
5 All sick dead p_death_sick
6 All sick sick C
7 All dead dead 1
$`Inputs - Health Values`
# A tibble: 5 × 5
name description strategy state value
<chr> <chr> <chr> <chr> <chr>
1 well_lys Well life-years All well cycle_length_years
2 sick_lys Sick life-years All sick cycle_length_years
3 well_qalys Well QALYs nat All util_well_nat * well_lys
4 well_qalys Label... new All util_well_new * well_lys
5 sick_qalys Sick QALYs All All sick_lys * util_sick
$`Inputs - Econ Values`
# A tibble: 3 × 5
name description strategy state value
<chr> <chr> <chr> <chr> <chr>
1 med_cost Medication cost new well cost_new
2 term_cost Terminal care cost All sick→dead cost_hosp_stay
3 ae_cost Adverse Event Cost nat Model Start 100
$`Inputs - Health Summ`
# A tibble: 4 × 4
name description value wtp
<chr> <chr> <chr> <dbl>
1 lys Life-years well_lys 100000
2 lys Label... sick_lys 100000
3 qalys QALYs well_qalys 150000
4 qalys Label... sick_qalys 100000
$`Inputs - Econ Summ`
# A tibble: 3 × 3
name description value
<chr> <chr> <chr>
1 cost_hc Healthcare system costs med_cost
2 cost_hc Label... term_cost
3 cost_hc Healthcare system costs ae_cost
$`Inputs - Parameters`
# A tibble: 11 × 6
name desc value low high psa
<chr> <chr> <chr> <chr> <chr> <chr>
1 p_sick_nat Probability of getting sick, natura… 0.5 "bc … "bc … "bin…
2 p_sick_new Probability of getting sick, new dr… 0.30 "bc … "bc … "bin…
3 p_death_well Probability of dying while well 0.005 "0.0… "0.0… "bin…
4 p_death_sick Probability of dying while sick 0.08 "bc … "bc … "bin…
5 cost_new Cost per year of new drug 32000 "240… "480… ""
6 util_well_nat Utility value for well state, natur… 0.85 "" "" "log…
7 disutil_well_new Utility decrement associated with n… 0.02 "" "" "log…
8 disutil_sick Utility decrement associated with b… 0.23 "" "" "log…
9 cost_hosp_stay Cost of a hospital stay 85000 "" "" "nor…
10 util_well_new Utility value for well state, new d… util… "" "" ""
11 util_sick Utility value for sick state util… "" "" ""
$`Calc - Params`
# A tibble: 20 × 30
strategy group state_time cycle model_time cycle_length_days
<chr> <chr> <dbl> <dbl> <dbl> <dbl>
1 nat All Patients 1 1 1 365
2 nat All Patients 1 2 2 365
3 nat All Patients 1 3 3 365
4 nat All Patients 1 4 4 365
5 nat All Patients 1 5 5 365
6 nat All Patients 1 6 6 365
7 nat All Patients 1 7 7 365
8 nat All Patients 1 8 8 365
9 nat All Patients 1 19 19 365
10 nat All Patients 1 20 20 365
11 new All Patients 1 1 1 365
12 new All Patients 1 2 2 365
13 new All Patients 1 3 3 365
14 new All Patients 1 4 4 365
15 new All Patients 1 5 5 365
16 new All Patients 1 6 6 365
17 new All Patients 1 7 7 365
18 new All Patients 1 8 8 365
19 new All Patients 1 19 19 365
20 new All Patients 1 20 20 365
# ℹ 24 more variables: cycle_length_weeks <dbl>, cycle_length_months <dbl>,
# cycle_length_years <dbl>, model_day <dbl>, model_week <dbl>,
# model_month <dbl>, model_year <dbl>, state_day <dbl>, state_week <dbl>,
# state_month <dbl>, state_year <dbl>, disc_h <dbl>, disc_e <dbl>,
# p_sick_nat <dbl>, p_sick_new <dbl>, p_death_well <dbl>, p_death_sick <dbl>,
# cost_new <dbl>, util_well_nat <dbl>, disutil_well_new <dbl>,
# disutil_sick <dbl>, cost_hosp_stay <dbl>, util_well_new <dbl>, …
$`Calc - Trans`
# A tibble: 20 × 7
strategy group cycle from well sick dead
<chr> <chr> <dbl> <chr> <dbl> <dbl> <dbl>
1 nat All Patients 1 well 0.495 0.5 0.005
2 nat All Patients 1 sick 0 0.92 0.08
3 nat All Patients 1 dead 0 0 1
4 nat All Patients 2 well 0.495 0.5 0.005
5 nat All Patients 2 sick 0 0.92 0.08
6 nat All Patients 2 dead 0 0 1
7 nat All Patients 3 well 0.495 0.5 0.005
8 nat All Patients 3 sick 0 0.92 0.08
9 nat All Patients 20 sick 0 0.92 0.08
10 nat All Patients 20 dead 0 0 1
11 new All Patients 1 well 0.695 0.3 0.005
12 new All Patients 1 sick 0 0.92 0.08
13 new All Patients 1 dead 0 0 1
14 new All Patients 2 well 0.695 0.3 0.005
15 new All Patients 2 sick 0 0.92 0.08
16 new All Patients 2 dead 0 0 1
17 new All Patients 3 well 0.695 0.3 0.005
18 new All Patients 3 sick 0 0.92 0.08
19 new All Patients 20 sick 0 0.92 0.08
20 new All Patients 20 dead 0 0 1
$`Calc - Unit Values`
# A tibble: 24 × 24
strategy group cycle state well_lys sick_lys well_qalys sick_qalys lys
<chr> <chr> <dbl> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
1 nat All Patie… 1 dead 0 0 0 0 0
2 nat All Patie… 1 sick 0 1 0 0.62 1
3 nat All Patie… 1 well 1 0 0.85 0 1
4 nat All Patie… 2 dead 0 0 0 0 0
5 nat All Patie… 2 sick 0 1 0 0.62 1
6 nat All Patie… 2 well 1 0 0.85 0 1
7 nat All Patie… 3 dead 0 0 0 0 0
8 nat All Patie… 3 sick 0 1 0 0.62 1
9 nat All Patie… 3 well 1 0 0.85 0 1
10 nat All Patie… 4 dead 0 0 0 0 0
# ℹ 14 more rows
# ℹ 15 more variables: qalys <dbl>, med_cost <dbl>, term_cost <dbl>,
# ae_cost <dbl>, cost_hc <dbl>, .disc_well_lys <dbl>, .disc_sick_lys <dbl>,
# .disc_well_qalys <dbl>, .disc_sick_qalys <dbl>, .disc_lys <dbl>,
# .disc_qalys <dbl>, .disc_med_cost <dbl>, .disc_term_cost <dbl>,
# .disc_ae_cost <dbl>, .disc_cost_hc <dbl>
$`Calc - Values`
# A tibble: 20 × 23
strategy group cycle well_lys sick_lys well_qalys sick_qalys lys qalys
<chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 nat All Patie… 1 7.48e-1 0.25 0.635 0.155 0.998 0.790
2 nat All Patie… 2 3.70e-1 0.604 0.315 0.374 0.974 0.689
3 nat All Patie… 3 1.83e-1 0.740 0.156 0.459 0.924 0.615
4 nat All Patie… 4 9.07e-2 0.773 0.0771 0.479 0.863 0.556
5 nat All Patie… 5 4.49e-2 0.756 0.0381 0.469 0.801 0.507
6 nat All Patie… 6 2.22e-2 0.718 0.0189 0.445 0.740 0.464
7 nat All Patie… 7 1.10e-2 0.672 0.00935 0.417 0.683 0.426
8 nat All Patie… 8 5.44e-3 0.624 0.00463 0.387 0.629 0.391
9 nat All Patie… 19 2.38e-6 0.252 0.00000202 0.156 0.252 0.156
10 nat All Patie… 20 1.18e-6 0.232 0.00000100 0.144 0.232 0.144
11 new All Patie… 1 8.48e-1 0.15 0.703 0.093 0.998 0.796
12 new All Patie… 2 5.89e-1 0.392 0.489 0.243 0.981 0.732
13 new All Patie… 3 4.09e-1 0.538 0.340 0.333 0.947 0.673
14 new All Patie… 4 2.85e-1 0.617 0.236 0.383 0.902 0.619
15 new All Patie… 5 1.98e-1 0.653 0.164 0.405 0.851 0.569
16 new All Patie… 6 1.37e-1 0.660 0.114 0.409 0.798 0.524
17 new All Patie… 7 9.55e-2 0.649 0.0793 0.402 0.744 0.482
18 new All Patie… 8 6.64e-2 0.626 0.0551 0.388 0.692 0.443
19 new All Patie… 19 1.21e-3 0.284 0.00101 0.176 0.285 0.177
20 new All Patie… 20 8.43e-4 0.261 0.000700 0.162 0.262 0.163
# ℹ 14 more variables: med_cost <dbl>, term_cost <dbl>, ae_cost <dbl>,
# cost_hc <dbl>, .disc_well_lys <dbl>, .disc_sick_lys <dbl>,
# .disc_well_qalys <dbl>, .disc_sick_qalys <dbl>, .disc_lys <dbl>,
# .disc_qalys <dbl>, .disc_med_cost <dbl>, .disc_term_cost <dbl>,
# .disc_ae_cost <dbl>, .disc_cost_hc <dbl>
$`Results - Trace`
# A tibble: 42 × 8
model_day model_week model_month model_year series well sick dead
<dbl> <dbl> <dbl> <dbl> <chr> <dbl> <dbl> <dbl>
1 0 0 0 0 nat 1 0 0
2 365 52.1 12 1 nat 0.495 0.5 0.005
3 730 104. 24 2 nat 0.245 0.708 0.0475
4 1095 156. 36 3 nat 0.121 0.773 0.105
5 1460 209. 48 4 nat 0.0600 0.772 0.168
6 1825 261. 60 5 nat 0.0297 0.740 0.230
7 2190 313. 72 6 nat 0.0147 0.696 0.289
8 2555 365 84 7 nat 0.00728 0.648 0.345
9 2920 417. 96 8 nat 0.00360 0.600 0.397
10 3285 469. 108 9 nat 0.00178 0.553 0.445
# ℹ 32 more rows
$`Results - Trace (Corrected)`
# A tibble: 40 × 8
model_day model_week model_month model_year series well sick dead
<dbl> <dbl> <dbl> <dbl> <chr> <dbl> <dbl> <dbl>
1 365 52.1 12 1 nat 0.748 0.25 0.0025
2 730 104. 24 2 nat 0.370 0.604 0.0262
3 1095 156. 36 3 nat 0.183 0.740 0.0764
4 1460 209. 48 4 nat 0.0907 0.773 0.137
5 1825 261. 60 5 nat 0.0449 0.756 0.199
6 2190 313. 72 6 nat 0.0222 0.718 0.260
7 2555 365 84 7 nat 0.0110 0.672 0.317
8 2920 417. 96 8 nat 0.00544 0.624 0.371
9 3285 469. 108 9 nat 0.00269 0.576 0.421
10 3650 521. 120 10 nat 0.00133 0.532 0.467
# ℹ 30 more rows
$`Results - Outcomes`
# A tibble: 32 × 5
outcome series group disc value
<chr> <chr> <chr> <lgl> <dbl>
1 lys nat well_lys TRUE 1.44
2 lys new well_lys TRUE 2.60
3 lys new vs. nat well_lys TRUE 1.17
4 lys nat vs. new well_lys TRUE -1.17
5 lys nat sick_lys TRUE 7.78
6 lys new sick_lys TRUE 7.26
7 lys new vs. nat sick_lys TRUE -0.517
8 lys nat vs. new sick_lys TRUE 0.517
9 qalys nat well_qalys TRUE 1.22
10 qalys new well_qalys TRUE 2.16
# ℹ 22 more rows
$`Results - Costs`
# A tibble: 24 × 5
outcome series group disc value
<chr> <chr> <chr> <lgl> <dbl>
1 cost_hc nat med_cost TRUE 0
2 cost_hc new med_cost TRUE 83352.
3 cost_hc new vs. nat med_cost TRUE 83352.
4 cost_hc nat vs. new med_cost TRUE -83352.
5 cost_hc nat term_cost TRUE 51681.
6 cost_hc new term_cost TRUE 48161.
7 cost_hc new vs. nat term_cost TRUE -3520.
8 cost_hc nat vs. new term_cost TRUE 3520.
9 cost_hc nat ae_cost TRUE 100
10 cost_hc new ae_cost TRUE 0
# ℹ 14 more rows
$`Results - CE`
# A tibble: 4 × 11
hsumm esumm health_outcome econ_outcome series cost eff dcost deffect
<chr> <chr> <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl>
1 .disc_lys .dis… .disc_lys .disc_cost_… nat 5.18e4 9.22 NA NA
2 .disc_lys .dis… .disc_lys .disc_cost_… new 1.32e5 9.87 79732. 0.648
3 .disc_qa… .dis… .disc_qalys .disc_cost_… nat 5.18e4 6.05 NA NA
4 .disc_qa… .dis… .disc_qalys .disc_cost_… new 1.32e5 6.66 79732. 0.618
# ℹ 2 more variables: dref <chr>, icer <dbl>
$`Results - NMB`
# A tibble: 14 × 6
outcome series group disc type value
<chr> <chr> <chr> <lgl> <chr> <dbl>
1 lys new vs. nat well_lys TRUE health 116564.
2 lys nat vs. new well_lys TRUE health -116564.
3 lys new vs. nat sick_lys TRUE health -51719.
4 lys nat vs. new sick_lys TRUE health 51719.
5 qalys new vs. nat well_qalys TRUE health 140805.
6 qalys nat vs. new well_qalys TRUE health -140805.
7 qalys new vs. nat sick_qalys TRUE health -48098.
8 qalys nat vs. new sick_qalys TRUE health 48098.
9 cost_hc new vs. nat med_cost TRUE economic -83352.
10 cost_hc nat vs. new med_cost TRUE economic 83352.
11 cost_hc new vs. nat term_cost TRUE economic 3520.
12 cost_hc nat vs. new term_cost TRUE economic -3520.
13 cost_hc new vs. nat ae_cost TRUE economic 100
14 cost_hc nat vs. new ae_cost TRUE economic -100
Advanced Survival Modeling produces correct results.
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AP4=
TA447 Replication produces correct results.
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Shared State-Time produces correct results.
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Sparse Matrix produces correct results.
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PolicyAnalysisInc/heRoMod documentation built on March 23, 2024, 4:29 p.m.
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Simple PSM produces correct results.
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AP4=
Code
exported
Output
$`Inputs - Settings`
# A tibble: 4 × 2
setting value
<chr> <chr>
1 disc_cost 0.03
2 disc_eff 0.03
3 cycle_length 30.4166666666667
4 n_cycles 240
$`Inputs - Strategies`
# A tibble: 2 × 2
name desc
<chr> <chr>
1 CHEMO Chemotherapy
2 TARGET Targeted Therapy
$`Inputs - States`
# A tibble: 3 × 4
name desc prob limit
<chr> <chr> <dbl> <dbl>
1 PF Progression-Free 1 0
2 PP Post-Progression 0 0
3 DEAD Dead 0 0
$`Inputs - Transitions`
# A tibble: 4 × 4
strategy endpoint cycle_length value
<chr> <chr> <dbl> <chr>
1 CHEMO PFS 1 pfs_chemo
2 TARGET PFS 1 pfs_target
3 CHEMO OS 1 os_chemo
4 TARGET OS 1 os_target
$`Inputs - Health Values`
# A tibble: 4 × 5
name description strategy state value
<chr> <chr> <chr> <chr> <chr>
1 pf_ly Progression-free life-years All PF cycle_length_years
2 pp_ly Post-progression life-years All PP cycle_length_years
3 pf_qalys Progression-free QALYs All PF pf_ly * pfs_util
4 pp_qalys Post-Progression QALYs All PP pp_ly * pps_util
$`Inputs - Econ Values`
# A tibble: 4 × 5
name description strategy state value
<chr> <chr> <chr> <chr> <chr>
1 med_cost Medication cost CHEMO PF chemo_cost * …
2 pf_care_cost Routine care cost, pre-progression All PF cycle_length_…
3 med_cost Label... TARGET PF target_cost *…
4 pp_care_cost Routine care cost, post-progression All PP cycle_length_…
$`Inputs - Health Summ`
# A tibble: 4 × 4
name description value wtp
<chr> <chr> <chr> <dbl>
1 lys Life-Years pf_ly 100000
2 lys Life-Years pp_ly 100000
3 qalys QALYs pf_qalys 150000
4 qalys QALYs pp_qalys 150000
$`Inputs - Econ Summ`
# A tibble: 3 × 3
name description value
<chr> <chr> <chr>
1 cost_hc Healthcare system costs med_cost
2 cost_hc Label... pf_care_cost
3 cost_hc Label... pp_care_cost
$`Inputs - Parameters`
# A tibble: 12 × 6
name desc value low high psa
<chr> <chr> <chr> <chr> <chr> <chr>
1 pfs_shape PFS shape parameter, chemo 1.2 bc * 0.75 bc * 1.25 "lognorma…
2 pfs_scale PFS scale parameter, chemo 40.3 bc * 0.75 bc * 1.25 "lognorma…
3 pfs_hr_target PFS HR, target 0.67 0.6 0.8 "lognorma…
4 os_shape OS shape parameter, chemo 1.1 0.95 1.34 "lognorma…
5 os_scale OS scale parameter, chemo 70.4 bc * 0.75 bc * 1.25 "lognorma…
6 os_hr_target OS HR, target 0.74 bc * 0.75 bc * 1.25 "lognorma…
7 chemo_cost Cost per month, chemo 2000 bc - 500 bc + 500 ""
8 target_cost Cost per month, target 10000 bc - 3000 bc + 3000 ""
9 pfs_cost Cost per month, PFS 1000 bc - 700 bc + 700 "normal(m…
10 pps_cost Cost per month, PPS 2000 0 10000 "normal(m…
11 pfs_util Utility value, PFS 0.82 bc - 0.05 bc + 0.05 "lognorma…
12 pps_util Utility value, PPS 0.68 bc - 0.1 bc + 0.1 "lognorma…
$`Inputs - Surv Dists`
# A tibble: 4 × 2
name value
<chr> <chr>
1 pfs_chemo "define_survival(dist = \"weibull\", pfs_shape, pfs_scale)"
2 os_chemo "define_survival(dist = \"weibull\", os_shape, os_scale)"
3 pfs_target "apply_hr(pfs_chemo, pfs_hr_target)"
4 os_target "apply_hr(os_chemo, os_hr_target)"
$`Calc - Params`
# A tibble: 480 × 31
strategy group state_time cycle model_time cycle_length_days
<chr> <chr> <dbl> <dbl> <dbl> <dbl>
1 CHEMO All Patients 1 1 1 30.4
2 CHEMO All Patients 1 2 2 30.4
3 CHEMO All Patients 1 3 3 30.4
4 CHEMO All Patients 1 4 4 30.4
5 CHEMO All Patients 1 5 5 30.4
6 CHEMO All Patients 1 6 6 30.4
7 CHEMO All Patients 1 7 7 30.4
8 CHEMO All Patients 1 8 8 30.4
9 CHEMO All Patients 1 9 9 30.4
10 CHEMO All Patients 1 10 10 30.4
# ℹ 470 more rows
# ℹ 25 more variables: cycle_length_weeks <dbl>, cycle_length_months <dbl>,
# cycle_length_years <dbl>, model_day <dbl>, model_week <dbl>,
# model_month <dbl>, model_year <dbl>, state_day <dbl>, state_week <dbl>,
# state_month <dbl>, state_year <dbl>, disc_h <dbl>, disc_e <dbl>,
# pfs_shape <dbl>, pfs_scale <dbl>, pfs_hr_target <dbl>, os_shape <dbl>,
# os_scale <dbl>, os_hr_target <dbl>, chemo_cost <dbl>, target_cost <dbl>, …
$`Calc - Trans`
# A tibble: 482 × 5
strategy group cycle pfs os
<chr> <chr> <dbl> <dbl> <dbl>
1 CHEMO All Patients 0 1 1
2 CHEMO All Patients 1 0.988 0.991
3 CHEMO All Patients 2 0.973 0.980
4 CHEMO All Patients 3 0.957 0.969
5 CHEMO All Patients 4 0.939 0.958
6 CHEMO All Patients 5 0.922 0.947
7 CHEMO All Patients 6 0.903 0.936
8 CHEMO All Patients 7 0.885 0.924
9 CHEMO All Patients 8 0.866 0.913
10 CHEMO All Patients 9 0.847 0.901
# ℹ 472 more rows
$`Calc - Unit Values`
# A tibble: 1,440 × 24
strategy group cycle state pf_ly pp_ly pf_qalys pp_qalys lys qalys med_cost
<chr> <chr> <dbl> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 CHEMO All … 1 DEAD 0 0 0 0 0 0 0
2 CHEMO All … 2 DEAD 0 0 0 0 0 0 0
3 CHEMO All … 3 DEAD 0 0 0 0 0 0 0
4 CHEMO All … 4 DEAD 0 0 0 0 0 0 0
5 CHEMO All … 5 DEAD 0 0 0 0 0 0 0
6 CHEMO All … 6 DEAD 0 0 0 0 0 0 0
7 CHEMO All … 7 DEAD 0 0 0 0 0 0 0
8 CHEMO All … 8 DEAD 0 0 0 0 0 0 0
9 CHEMO All … 9 DEAD 0 0 0 0 0 0 0
10 CHEMO All … 10 DEAD 0 0 0 0 0 0 0
# ℹ 1,430 more rows
# ℹ 13 more variables: pf_care_cost <dbl>, pp_care_cost <dbl>, cost_hc <dbl>,
# .disc_pf_ly <dbl>, .disc_pp_ly <dbl>, .disc_pf_qalys <dbl>,
# .disc_pp_qalys <dbl>, .disc_lys <dbl>, .disc_qalys <dbl>,
# .disc_med_cost <dbl>, .disc_pf_care_cost <dbl>, .disc_pp_care_cost <dbl>,
# .disc_cost_hc <dbl>
$`Calc - Values`
# A tibble: 480 × 23
strategy group cycle pf_ly pp_ly pf_qalys pp_qalys lys qalys med_cost
<chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 CHEMO All P… 1 0.0828 1.06e-4 0.0679 7.19e-5 0.0829 0.0680 1988.
2 CHEMO All P… 2 0.0817 4.04e-4 0.0670 2.75e-4 0.0821 0.0673 1961.
3 CHEMO All P… 3 0.0804 8.27e-4 0.0659 5.63e-4 0.0812 0.0665 1930.
4 CHEMO All P… 4 0.0790 1.32e-3 0.0648 8.94e-4 0.0803 0.0657 1896.
5 CHEMO All P… 5 0.0775 1.85e-3 0.0636 1.25e-3 0.0794 0.0648 1861.
6 CHEMO All P… 6 0.0760 2.40e-3 0.0623 1.63e-3 0.0784 0.0640 1825.
7 CHEMO All P… 7 0.0745 2.98e-3 0.0611 2.03e-3 0.0775 0.0631 1788.
8 CHEMO All P… 8 0.0730 3.57e-3 0.0598 2.43e-3 0.0765 0.0623 1751.
9 CHEMO All P… 9 0.0714 4.17e-3 0.0586 2.84e-3 0.0756 0.0614 1714.
10 CHEMO All P… 10 0.0698 4.77e-3 0.0573 3.25e-3 0.0746 0.0605 1676.
# ℹ 470 more rows
# ℹ 13 more variables: pf_care_cost <dbl>, pp_care_cost <dbl>, cost_hc <dbl>,
# .disc_pf_ly <dbl>, .disc_pp_ly <dbl>, .disc_pf_qalys <dbl>,
# .disc_pp_qalys <dbl>, .disc_lys <dbl>, .disc_qalys <dbl>,
# .disc_med_cost <dbl>, .disc_pf_care_cost <dbl>, .disc_pp_care_cost <dbl>,
# .disc_cost_hc <dbl>
$`Results - Trace`
# A tibble: 482 × 8
model_day model_week model_month model_year series PF PP DEAD
<dbl> <dbl> <dbl> <dbl> <chr> <dbl> <dbl> <dbl>
1 0 0 0 0 CHEMO 1 0 0
2 30.4 4.35 1 0.0833 CHEMO 0.988 0.00254 0.00924
3 60.8 8.69 2 0.167 CHEMO 0.973 0.00715 0.0197
4 91.3 13.0 3 0.25 CHEMO 0.957 0.0127 0.0306
5 122. 17.4 4 0.333 CHEMO 0.939 0.0189 0.0418
6 152. 21.7 5.00 0.417 CHEMO 0.922 0.0254 0.0531
7 182. 26.1 6.00 0.500 CHEMO 0.903 0.0323 0.0645
8 213. 30.4 7.00 0.583 CHEMO 0.885 0.0393 0.0759
9 243. 34.8 8.00 0.667 CHEMO 0.866 0.0464 0.0874
10 274. 39.1 9.00 0.750 CHEMO 0.847 0.0537 0.0988
# ℹ 472 more rows
$`Results - Trace (Corrected)`
# A tibble: 480 × 8
model_day model_week model_month model_year series PF PP DEAD
<dbl> <dbl> <dbl> <dbl> <chr> <dbl> <dbl> <dbl>
1 30.4 4.35 1 0.0833 CHEMO 0.994 0.00127 0.00462
2 60.8 8.69 2 0.167 CHEMO 0.981 0.00484 0.0145
3 91.3 13.0 3 0.25 CHEMO 0.965 0.00993 0.0252
4 122. 17.4 4 0.333 CHEMO 0.948 0.0158 0.0362
5 152. 21.7 5.00 0.417 CHEMO 0.930 0.0221 0.0474
6 182. 26.1 6.00 0.500 CHEMO 0.912 0.0288 0.0588
7 213. 30.4 7.00 0.583 CHEMO 0.894 0.0358 0.0702
8 243. 34.8 8.00 0.667 CHEMO 0.875 0.0429 0.0816
9 274. 39.1 9.00 0.750 CHEMO 0.857 0.0501 0.0931
10 304. 43.5 10 0.833 CHEMO 0.838 0.0573 0.105
# ℹ 470 more rows
$`Results - Outcomes`
# A tibble: 32 × 5
outcome series group disc value
<chr> <chr> <chr> <lgl> <dbl>
1 lys CHEMO pf_ly TRUE 2.93
2 lys TARGET pf_ly TRUE 3.97
3 lys TARGET vs. CHEMO pf_ly TRUE 1.04
4 lys CHEMO vs. TARGET pf_ly TRUE -1.04
5 lys CHEMO pp_ly TRUE 1.94
6 lys TARGET pp_ly TRUE 2.06
7 lys TARGET vs. CHEMO pp_ly TRUE 0.125
8 lys CHEMO vs. TARGET pp_ly TRUE -0.125
9 qalys CHEMO pf_qalys TRUE 2.40
10 qalys TARGET pf_qalys TRUE 3.25
# ℹ 22 more rows
$`Results - Costs`
# A tibble: 24 × 5
outcome series group disc value
<chr> <chr> <chr> <lgl> <dbl>
1 cost_hc CHEMO med_cost TRUE 70291.
2 cost_hc TARGET med_cost TRUE 476060.
3 cost_hc TARGET vs. CHEMO med_cost TRUE 405769.
4 cost_hc CHEMO vs. TARGET med_cost TRUE -405769.
5 cost_hc CHEMO pf_care_cost TRUE 35146.
6 cost_hc TARGET pf_care_cost TRUE 47606.
7 cost_hc TARGET vs. CHEMO pf_care_cost TRUE 12460.
8 cost_hc CHEMO vs. TARGET pf_care_cost TRUE -12460.
9 cost_hc CHEMO pp_care_cost TRUE 46441.
10 cost_hc TARGET pp_care_cost TRUE 49448.
# ℹ 14 more rows
$`Results - CE`
# A tibble: 4 × 11
hsumm esumm health_outcome econ_outcome series cost eff dcost deffect
<chr> <chr> <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl>
1 .disc_l… .dis… .disc_lys .disc_cost_… CHEMO 1.52e5 4.86 NA NA
2 .disc_l… .dis… .disc_lys .disc_cost_… TARGET 5.73e5 6.03 421236. 1.16
3 .disc_q… .dis… .disc_qalys .disc_cost_… CHEMO 1.52e5 3.72 NA NA
4 .disc_q… .dis… .disc_qalys .disc_cost_… TARGET 5.73e5 4.65 421236. 0.937
# ℹ 2 more variables: dref <chr>, icer <dbl>
$`Results - NMB`
# A tibble: 14 × 6
outcome series group disc type value
<chr> <chr> <chr> <lgl> <chr> <dbl>
1 lys TARGET vs. CHEMO pf_ly TRUE health 103836.
2 lys CHEMO vs. TARGET pf_ly TRUE health -103836.
3 lys TARGET vs. CHEMO pp_ly TRUE health 12530.
4 lys CHEMO vs. TARGET pp_ly TRUE health -12530.
5 qalys TARGET vs. CHEMO pf_qalys TRUE health 127718.
6 qalys CHEMO vs. TARGET pf_qalys TRUE health -127718.
7 qalys TARGET vs. CHEMO pp_qalys TRUE health 12781.
8 qalys CHEMO vs. TARGET pp_qalys TRUE health -12781.
9 cost_hc TARGET vs. CHEMO med_cost TRUE economic -405769.
10 cost_hc CHEMO vs. TARGET med_cost TRUE economic 405769.
11 cost_hc TARGET vs. CHEMO pf_care_cost TRUE economic -12460.
12 cost_hc CHEMO vs. TARGET pf_care_cost TRUE economic 12460.
13 cost_hc TARGET vs. CHEMO pp_care_cost TRUE economic -3007.
14 cost_hc CHEMO vs. TARGET pp_care_cost TRUE economic 3007.
Code
exported_limited
Output
$`Inputs - Settings`
# A tibble: 4 × 2
setting value
<chr> <chr>
1 disc_cost 0.03
2 disc_eff 0.03
3 cycle_length 30.4166666666667
4 n_cycles 240
$`Inputs - Strategies`
# A tibble: 2 × 2
name desc
<chr> <chr>
1 CHEMO Chemotherapy
2 TARGET Targeted Therapy
$`Inputs - States`
# A tibble: 3 × 4
name desc prob limit
<chr> <chr> <dbl> <dbl>
1 PF Progression-Free 1 0
2 PP Post-Progression 0 0
3 DEAD Dead 0 0
$`Inputs - Transitions`
# A tibble: 4 × 4
strategy endpoint cycle_length value
<chr> <chr> <dbl> <chr>
1 CHEMO PFS 1 pfs_chemo
2 TARGET PFS 1 pfs_target
3 CHEMO OS 1 os_chemo
4 TARGET OS 1 os_target
$`Inputs - Health Values`
# A tibble: 4 × 5
name description strategy state value
<chr> <chr> <chr> <chr> <chr>
1 pf_ly Progression-free life-years All PF cycle_length_years
2 pp_ly Post-progression life-years All PP cycle_length_years
3 pf_qalys Progression-free QALYs All PF pf_ly * pfs_util
4 pp_qalys Post-Progression QALYs All PP pp_ly * pps_util
$`Inputs - Econ Values`
# A tibble: 4 × 5
name description strategy state value
<chr> <chr> <chr> <chr> <chr>
1 med_cost Medication cost CHEMO PF chemo_cost * …
2 pf_care_cost Routine care cost, pre-progression All PF cycle_length_…
3 med_cost Label... TARGET PF target_cost *…
4 pp_care_cost Routine care cost, post-progression All PP cycle_length_…
$`Inputs - Health Summ`
# A tibble: 4 × 4
name description value wtp
<chr> <chr> <chr> <dbl>
1 lys Life-Years pf_ly 100000
2 lys Life-Years pp_ly 100000
3 qalys QALYs pf_qalys 150000
4 qalys QALYs pp_qalys 150000
$`Inputs - Econ Summ`
# A tibble: 3 × 3
name description value
<chr> <chr> <chr>
1 cost_hc Healthcare system costs med_cost
2 cost_hc Label... pf_care_cost
3 cost_hc Label... pp_care_cost
$`Inputs - Parameters`
# A tibble: 12 × 6
name desc value low high psa
<chr> <chr> <chr> <chr> <chr> <chr>
1 pfs_shape PFS shape parameter, chemo 1.2 bc * 0.75 bc * 1.25 "lognorma…
2 pfs_scale PFS scale parameter, chemo 40.3 bc * 0.75 bc * 1.25 "lognorma…
3 pfs_hr_target PFS HR, target 0.67 0.6 0.8 "lognorma…
4 os_shape OS shape parameter, chemo 1.1 0.95 1.34 "lognorma…
5 os_scale OS scale parameter, chemo 70.4 bc * 0.75 bc * 1.25 "lognorma…
6 os_hr_target OS HR, target 0.74 bc * 0.75 bc * 1.25 "lognorma…
7 chemo_cost Cost per month, chemo 2000 bc - 500 bc + 500 ""
8 target_cost Cost per month, target 10000 bc - 3000 bc + 3000 ""
9 pfs_cost Cost per month, PFS 1000 bc - 700 bc + 700 "normal(m…
10 pps_cost Cost per month, PPS 2000 0 10000 "normal(m…
11 pfs_util Utility value, PFS 0.82 bc - 0.05 bc + 0.05 "lognorma…
12 pps_util Utility value, PPS 0.68 bc - 0.1 bc + 0.1 "lognorma…
$`Inputs - Surv Dists`
# A tibble: 4 × 2
name value
<chr> <chr>
1 pfs_chemo "define_survival(dist = \"weibull\", pfs_shape, pfs_scale)"
2 os_chemo "define_survival(dist = \"weibull\", os_shape, os_scale)"
3 pfs_target "apply_hr(pfs_chemo, pfs_hr_target)"
4 os_target "apply_hr(os_chemo, os_hr_target)"
$`Calc - Params`
# A tibble: 20 × 31
strategy group state_time cycle model_time cycle_length_days
<chr> <chr> <dbl> <dbl> <dbl> <dbl>
1 CHEMO All Patients 1 1 1 30.4
2 CHEMO All Patients 1 2 2 30.4
3 CHEMO All Patients 1 3 3 30.4
4 CHEMO All Patients 1 4 4 30.4
5 CHEMO All Patients 1 5 5 30.4
6 CHEMO All Patients 1 6 6 30.4
7 CHEMO All Patients 1 7 7 30.4
8 CHEMO All Patients 1 8 8 30.4
9 CHEMO All Patients 1 239 239 30.4
10 CHEMO All Patients 1 240 240 30.4
11 TARGET All Patients 1 1 1 30.4
12 TARGET All Patients 1 2 2 30.4
13 TARGET All Patients 1 3 3 30.4
14 TARGET All Patients 1 4 4 30.4
15 TARGET All Patients 1 5 5 30.4
16 TARGET All Patients 1 6 6 30.4
17 TARGET All Patients 1 7 7 30.4
18 TARGET All Patients 1 8 8 30.4
19 TARGET All Patients 1 239 239 30.4
20 TARGET All Patients 1 240 240 30.4
# ℹ 25 more variables: cycle_length_weeks <dbl>, cycle_length_months <dbl>,
# cycle_length_years <dbl>, model_day <dbl>, model_week <dbl>,
# model_month <dbl>, model_year <dbl>, state_day <dbl>, state_week <dbl>,
# state_month <dbl>, state_year <dbl>, disc_h <dbl>, disc_e <dbl>,
# pfs_shape <dbl>, pfs_scale <dbl>, pfs_hr_target <dbl>, os_shape <dbl>,
# os_scale <dbl>, os_hr_target <dbl>, chemo_cost <dbl>, target_cost <dbl>,
# pfs_cost <dbl>, pps_cost <dbl>, pfs_util <dbl>, pps_util <dbl>
$`Calc - Trans`
# A tibble: 20 × 5
strategy group cycle pfs os
<chr> <chr> <dbl> <dbl> <dbl>
1 CHEMO All Patients 0 1 1
2 CHEMO All Patients 1 0.988 0.991
3 CHEMO All Patients 2 0.973 0.980
4 CHEMO All Patients 3 0.957 0.969
5 CHEMO All Patients 4 0.939 0.958
6 CHEMO All Patients 5 0.922 0.947
7 CHEMO All Patients 6 0.903 0.936
8 CHEMO All Patients 7 0.885 0.924
9 CHEMO All Patients 239 0.000210 0.0216
10 CHEMO All Patients 240 0.000202 0.0212
11 TARGET All Patients 0 1 1
12 TARGET All Patients 1 0.992 0.993
13 TARGET All Patients 2 0.982 0.985
14 TARGET All Patients 3 0.971 0.977
15 TARGET All Patients 4 0.959 0.969
16 TARGET All Patients 5 0.947 0.960
17 TARGET All Patients 6 0.934 0.952
18 TARGET All Patients 7 0.921 0.943
19 TARGET All Patients 239 0.00344 0.0585
20 TARGET All Patients 240 0.00334 0.0577
$`Calc - Unit Values`
# A tibble: 24 × 24
strategy group cycle state pf_ly pp_ly pf_qalys pp_qalys lys qalys
<chr> <chr> <dbl> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 CHEMO All Patie… 1 DEAD 0 0 0 0 0 0
2 CHEMO All Patie… 1 PF 0.0833 0 0.0683 0 0.0833 0.0683
3 CHEMO All Patie… 1 PP 0 0.0833 0 0.0567 0.0833 0.0567
4 CHEMO All Patie… 2 DEAD 0 0 0 0 0 0
5 CHEMO All Patie… 2 PF 0.0833 0 0.0683 0 0.0833 0.0683
6 CHEMO All Patie… 2 PP 0 0.0833 0 0.0567 0.0833 0.0567
7 CHEMO All Patie… 3 DEAD 0 0 0 0 0 0
8 CHEMO All Patie… 3 PF 0.0833 0 0.0683 0 0.0833 0.0683
9 CHEMO All Patie… 3 PP 0 0.0833 0 0.0567 0.0833 0.0567
10 CHEMO All Patie… 4 DEAD 0 0 0 0 0 0
# ℹ 14 more rows
# ℹ 14 more variables: med_cost <dbl>, pf_care_cost <dbl>, pp_care_cost <dbl>,
# cost_hc <dbl>, .disc_pf_ly <dbl>, .disc_pp_ly <dbl>, .disc_pf_qalys <dbl>,
# .disc_pp_qalys <dbl>, .disc_lys <dbl>, .disc_qalys <dbl>,
# .disc_med_cost <dbl>, .disc_pf_care_cost <dbl>, .disc_pp_care_cost <dbl>,
# .disc_cost_hc <dbl>
$`Calc - Values`
# A tibble: 20 × 23
strategy group cycle pf_ly pp_ly pf_qalys pp_qalys lys qalys
<chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 CHEMO All Patients 1 8.28e-2 1.06e-4 6.79e-2 7.19e-5 0.0829 0.0680
2 CHEMO All Patients 2 8.17e-2 4.04e-4 6.70e-2 2.75e-4 0.0821 0.0673
3 CHEMO All Patients 3 8.04e-2 8.27e-4 6.59e-2 5.63e-4 0.0812 0.0665
4 CHEMO All Patients 4 7.90e-2 1.32e-3 6.48e-2 8.94e-4 0.0803 0.0657
5 CHEMO All Patients 5 7.75e-2 1.85e-3 6.36e-2 1.25e-3 0.0794 0.0648
6 CHEMO All Patients 6 7.60e-2 2.40e-3 6.23e-2 1.63e-3 0.0784 0.0640
7 CHEMO All Patients 7 7.45e-2 2.98e-3 6.11e-2 2.03e-3 0.0775 0.0631
8 CHEMO All Patients 8 7.30e-2 3.57e-3 5.98e-2 2.43e-3 0.0765 0.0623
9 CHEMO All Patients 239 1.79e-5 1.80e-3 1.47e-5 1.22e-3 0.00181 0.00124
10 CHEMO All Patients 240 1.72e-5 1.76e-3 1.41e-5 1.20e-3 0.00178 0.00121
11 TARGET All Patients 1 8.30e-2 4.42e-5 6.81e-2 3.01e-5 0.0830 0.0681
12 TARGET All Patients 2 8.23e-2 1.88e-4 6.74e-2 1.28e-4 0.0824 0.0676
13 TARGET All Patients 3 8.14e-2 4.14e-4 6.67e-2 2.82e-4 0.0818 0.0670
14 TARGET All Patients 4 8.04e-2 6.86e-4 6.59e-2 4.66e-4 0.0811 0.0664
15 TARGET All Patients 5 7.94e-2 9.88e-4 6.51e-2 6.72e-4 0.0804 0.0658
16 TARGET All Patients 6 7.84e-2 1.31e-3 6.43e-2 8.93e-4 0.0797 0.0652
17 TARGET All Patients 7 7.73e-2 1.66e-3 6.34e-2 1.13e-3 0.0790 0.0645
18 TARGET All Patients 8 7.62e-2 2.01e-3 6.25e-2 1.37e-3 0.0782 0.0639
19 TARGET All Patients 239 2.91e-4 4.62e-3 2.38e-4 3.14e-3 0.00491 0.00338
20 TARGET All Patients 240 2.83e-4 4.56e-3 2.32e-4 3.10e-3 0.00484 0.00333
# ℹ 14 more variables: med_cost <dbl>, pf_care_cost <dbl>, pp_care_cost <dbl>,
# cost_hc <dbl>, .disc_pf_ly <dbl>, .disc_pp_ly <dbl>, .disc_pf_qalys <dbl>,
# .disc_pp_qalys <dbl>, .disc_lys <dbl>, .disc_qalys <dbl>,
# .disc_med_cost <dbl>, .disc_pf_care_cost <dbl>, .disc_pp_care_cost <dbl>,
# .disc_cost_hc <dbl>
$`Results - Trace`
# A tibble: 482 × 8
model_day model_week model_month model_year series PF PP DEAD
<dbl> <dbl> <dbl> <dbl> <chr> <dbl> <dbl> <dbl>
1 0 0 0 0 CHEMO 1 0 0
2 30.4 4.35 1 0.0833 CHEMO 0.988 0.00254 0.00924
3 60.8 8.69 2 0.167 CHEMO 0.973 0.00715 0.0197
4 91.3 13.0 3 0.25 CHEMO 0.957 0.0127 0.0306
5 122. 17.4 4 0.333 CHEMO 0.939 0.0189 0.0418
6 152. 21.7 5.00 0.417 CHEMO 0.922 0.0254 0.0531
7 182. 26.1 6.00 0.500 CHEMO 0.903 0.0323 0.0645
8 213. 30.4 7.00 0.583 CHEMO 0.885 0.0393 0.0759
9 243. 34.8 8.00 0.667 CHEMO 0.866 0.0464 0.0874
10 274. 39.1 9.00 0.750 CHEMO 0.847 0.0537 0.0988
# ℹ 472 more rows
$`Results - Trace (Corrected)`
# A tibble: 480 × 8
model_day model_week model_month model_year series PF PP DEAD
<dbl> <dbl> <dbl> <dbl> <chr> <dbl> <dbl> <dbl>
1 30.4 4.35 1 0.0833 CHEMO 0.994 0.00127 0.00462
2 60.8 8.69 2 0.167 CHEMO 0.981 0.00484 0.0145
3 91.3 13.0 3 0.25 CHEMO 0.965 0.00993 0.0252
4 122. 17.4 4 0.333 CHEMO 0.948 0.0158 0.0362
5 152. 21.7 5.00 0.417 CHEMO 0.930 0.0221 0.0474
6 182. 26.1 6.00 0.500 CHEMO 0.912 0.0288 0.0588
7 213. 30.4 7.00 0.583 CHEMO 0.894 0.0358 0.0702
8 243. 34.8 8.00 0.667 CHEMO 0.875 0.0429 0.0816
9 274. 39.1 9.00 0.750 CHEMO 0.857 0.0501 0.0931
10 304. 43.5 10 0.833 CHEMO 0.838 0.0573 0.105
# ℹ 470 more rows
$`Results - Outcomes`
# A tibble: 32 × 5
outcome series group disc value
<chr> <chr> <chr> <lgl> <dbl>
1 lys CHEMO pf_ly TRUE 2.93
2 lys TARGET pf_ly TRUE 3.97
3 lys TARGET vs. CHEMO pf_ly TRUE 1.04
4 lys CHEMO vs. TARGET pf_ly TRUE -1.04
5 lys CHEMO pp_ly TRUE 1.94
6 lys TARGET pp_ly TRUE 2.06
7 lys TARGET vs. CHEMO pp_ly TRUE 0.125
8 lys CHEMO vs. TARGET pp_ly TRUE -0.125
9 qalys CHEMO pf_qalys TRUE 2.40
10 qalys TARGET pf_qalys TRUE 3.25
# ℹ 22 more rows
$`Results - Costs`
# A tibble: 24 × 5
outcome series group disc value
<chr> <chr> <chr> <lgl> <dbl>
1 cost_hc CHEMO med_cost TRUE 70291.
2 cost_hc TARGET med_cost TRUE 476060.
3 cost_hc TARGET vs. CHEMO med_cost TRUE 405769.
4 cost_hc CHEMO vs. TARGET med_cost TRUE -405769.
5 cost_hc CHEMO pf_care_cost TRUE 35146.
6 cost_hc TARGET pf_care_cost TRUE 47606.
7 cost_hc TARGET vs. CHEMO pf_care_cost TRUE 12460.
8 cost_hc CHEMO vs. TARGET pf_care_cost TRUE -12460.
9 cost_hc CHEMO pp_care_cost TRUE 46441.
10 cost_hc TARGET pp_care_cost TRUE 49448.
# ℹ 14 more rows
$`Results - CE`
# A tibble: 4 × 11
hsumm esumm health_outcome econ_outcome series cost eff dcost deffect
<chr> <chr> <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl>
1 .disc_l… .dis… .disc_lys .disc_cost_… CHEMO 1.52e5 4.86 NA NA
2 .disc_l… .dis… .disc_lys .disc_cost_… TARGET 5.73e5 6.03 421236. 1.16
3 .disc_q… .dis… .disc_qalys .disc_cost_… CHEMO 1.52e5 3.72 NA NA
4 .disc_q… .dis… .disc_qalys .disc_cost_… TARGET 5.73e5 4.65 421236. 0.937
# ℹ 2 more variables: dref <chr>, icer <dbl>
$`Results - NMB`
# A tibble: 14 × 6
outcome series group disc type value
<chr> <chr> <chr> <lgl> <chr> <dbl>
1 lys TARGET vs. CHEMO pf_ly TRUE health 103836.
2 lys CHEMO vs. TARGET pf_ly TRUE health -103836.
3 lys TARGET vs. CHEMO pp_ly TRUE health 12530.
4 lys CHEMO vs. TARGET pp_ly TRUE health -12530.
5 qalys TARGET vs. CHEMO pf_qalys TRUE health 127718.
6 qalys CHEMO vs. TARGET pf_qalys TRUE health -127718.
7 qalys TARGET vs. CHEMO pp_qalys TRUE health 12781.
8 qalys CHEMO vs. TARGET pp_qalys TRUE health -12781.
9 cost_hc TARGET vs. CHEMO med_cost TRUE economic -405769.
10 cost_hc CHEMO vs. TARGET med_cost TRUE economic 405769.
11 cost_hc TARGET vs. CHEMO pf_care_cost TRUE economic -12460.
12 cost_hc CHEMO vs. TARGET pf_care_cost TRUE economic 12460.
13 cost_hc TARGET vs. CHEMO pp_care_cost TRUE economic -3007.
14 cost_hc CHEMO vs. TARGET pp_care_cost TRUE economic 3007.
Custom PSM produces correct results.
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Code
exported
Output
$`Inputs - Settings`
# A tibble: 4 × 2
setting value
<chr> <chr>
1 disc_cost 0.035
2 disc_eff 0.035
3 cycle_length 365
4 n_cycles 20
$`Inputs - Strategies`
# A tibble: 4 × 2
name desc
<chr> <chr>
1 myfo Myfosfamide
2 chpl Chemoplatin
3 chck Checkimab
4 rlps Relapsinib
$`Inputs - States`
# A tibble: 4 × 4
name desc prob limit
<chr> <chr> <chr> <dbl>
1 RESP Response dispatch_strategy(myfo = rr_myfo, chpl = rr_chpl, chck… 0
2 REL Relapse 0 0
3 REF Refractory C 0
4 DEAD Dead 0 0
$`Inputs - Transitions`
# A tibble: 4 × 5
strategy state formula id value
<chr> <chr> <chr> <chr> <chr>
1 All RESP rr * surv_prob(rfs, model_month) 6e50… rr *…
2 All REL rr * (surv_prob(os_resp, model_month) - surv_prob(… aefc… rr *…
3 All REF (1 - rr) * surv_prob(os_nresp, model_month) d1f8… (1 -…
4 All DEAD C 8c1d… C
$`Inputs - Health Values`
# A tibble: 6 × 5
name description strategy state value
<chr> <chr> <chr> <chr> <chr>
1 ly_resp Life Years in Response All RESP cycle_length_years
2 ly_nresp Life Years in Nonresponse All REL cycle_length_years
3 qalys_resp QALYs in Response All RESP util_resp * cycle_length…
4 qalys_nresp QALYs in Nonresponse All REL util_rel * cycle_length_…
5 ly_nresp Label... All REF cycle_length_years
6 qalys_nresp Label... All REF util_ref * cycle_length_…
$`Inputs - Econ Values`
# A tibble: 7 × 5
name description strategy state value
<chr> <chr> <chr> <chr> <chr>
1 cost_med Medication cost myfo RESP ucost_myfo * cycle_length…
2 cost_resp Routine care, response All All ucost_resp * cycle_length…
3 cost_nresp Routine care, nonresponse All All ucost_nresp * cycle_lengt…
4 cost_trans Transplant All REF rescale_prob(p_transplant…
5 cost_med Label... chpl RESP ucost_chpl * cycle_length…
6 cost_med Label... chck RESP ucost_chck * cycle_length…
7 cost_med Label... rlps RESP ucost_rlps * cycle_length…
$`Inputs - Health Summ`
# A tibble: 4 × 4
name description value wtp
<chr> <chr> <chr> <dbl>
1 lys Life-years ly_resp 20000
2 lys Life-years ly_nresp 20000
3 qalys Quality-adjusted life-years qalys_resp 30000
4 qalys Label... qalys_nresp 100000
$`Inputs - Econ Summ`
# A tibble: 4 × 3
name description value
<chr> <chr> <chr>
1 cost_hc Healthcare system costs cost_med
2 cost_hc Label... cost_resp
3 cost_hc Label... cost_nresp
4 cost_hc Label... cost_trans
$`Inputs - Parameters`
# A tibble: 21 × 6
name desc value low high psa
<chr> <chr> <chr> <chr> <chr> <chr>
1 rr_myfo Response rate, myfosfamide 0.31 "bc … "bc … "bin…
2 rr_chpl Response rate, chemoplatin 0.35 "bc … "bc … "bin…
3 rr_chck Response rate, checkimab 0.51 "bc … "bc … "bin…
4 rr_rlps Response rate, relapsinib 0.543 "bc … "bc … "bin…
5 rr Relapse rate dispatch_strate… "" "" ""
6 rfs_scale Scale parameter, RFS 6 "5.4… "7.1" "log…
7 rfs_shape Shape parameter, RFS 0.89 "0.7… "1.0… "log…
8 os_resp_meanlog log mean OS, responders 4 "3.4… "4.5… "nor…
9 os_resp_sdlog log SD OS, responders 0.71 "0.5… "0.9… "log…
10 os_nresp_rate Death rate, nonresponders 0.12 "0.0… "0.1… "log…
# ℹ 11 more rows
$`Inputs - Surv Dists`
# A tibble: 3 × 2
name value
<chr> <chr>
1 rfs "define_survival(shape = rfs_shape, scale = rfs_scale, dist = \"weib…
2 os_resp "define_survival(meanlog = os_resp_meanlog, sdlog = os_resp_sdlog, d…
3 os_nresp "define_survival(rate = os_nresp_rate, dist = \"exp\")"
$`Calc - Params`
# A tibble: 80 × 40
strategy group state_time cycle model_time cycle_length_days
<chr> <chr> <dbl> <dbl> <dbl> <dbl>
1 myfo All Patients 1 1 1 365
2 myfo All Patients 1 2 2 365
3 myfo All Patients 1 3 3 365
4 myfo All Patients 1 4 4 365
5 myfo All Patients 1 5 5 365
6 myfo All Patients 1 6 6 365
7 myfo All Patients 1 7 7 365
8 myfo All Patients 1 8 8 365
9 myfo All Patients 1 9 9 365
10 myfo All Patients 1 10 10 365
# ℹ 70 more rows
# ℹ 34 more variables: cycle_length_weeks <dbl>, cycle_length_months <dbl>,
# cycle_length_years <dbl>, model_day <dbl>, model_week <dbl>,
# model_month <dbl>, model_year <dbl>, state_day <dbl>, state_week <dbl>,
# state_month <dbl>, state_year <dbl>, disc_h <dbl>, disc_e <dbl>,
# rr_myfo <dbl>, rr_chpl <dbl>, rr_chck <dbl>, rr_rlps <dbl>, rr <dbl>,
# rfs_scale <dbl>, rfs_shape <dbl>, os_resp_meanlog <dbl>, …
$`Calc - Trans`
# A tibble: 84 × 9
model_day model_week model_month model_year series RESP REL REF
<dbl> <dbl> <dbl> <dbl> <chr> <dbl> <dbl> <dbl>
1 0 0 0 0 myfo 0.31 0 6.9 e-1
2 365 52.1 12 1 myfo 0.0486 0.256 1.63e-1
3 730 104. 24 2 myfo 0.0100 0.262 3.87e-2
4 1095 156. 36 3 myfo 0.00225 0.221 9.18e-3
5 1460 209. 48 4 myfo 0.000534 0.177 2.17e-3
6 1825 261. 60 5 myfo 0.000132 0.138 5.15e-4
7 2190 313. 72 6 myfo 0.0000336 0.108 1.22e-4
8 2555 365 84 7 myfo 0.00000877 0.0843 2.89e-5
9 2920 417. 96 8 myfo 0.00000234 0.0661 6.85e-6
10 3285 469. 108 9 myfo 0.000000636 0.0522 1.62e-6
# ℹ 74 more rows
# ℹ 1 more variable: DEAD <dbl>
$`Calc - Unit Values`
# A tibble: 320 × 26
strategy group cycle state ly_resp ly_nresp qalys_resp qalys_nresp lys
<chr> <chr> <dbl> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
1 chck All Patie… 1 DEAD 0 0 0 0 0
2 chck All Patie… 2 DEAD 0 0 0 0 0
3 chck All Patie… 3 DEAD 0 0 0 0 0
4 chck All Patie… 4 DEAD 0 0 0 0 0
5 chck All Patie… 5 DEAD 0 0 0 0 0
6 chck All Patie… 6 DEAD 0 0 0 0 0
7 chck All Patie… 7 DEAD 0 0 0 0 0
8 chck All Patie… 8 DEAD 0 0 0 0 0
9 chck All Patie… 9 DEAD 0 0 0 0 0
10 chck All Patie… 10 DEAD 0 0 0 0 0
# ℹ 310 more rows
# ℹ 17 more variables: qalys <dbl>, cost_med <dbl>, cost_resp <dbl>,
# cost_nresp <dbl>, cost_trans <dbl>, cost_hc <dbl>, .disc_ly_resp <dbl>,
# .disc_ly_nresp <dbl>, .disc_qalys_resp <dbl>, .disc_qalys_nresp <dbl>,
# .disc_lys <dbl>, .disc_qalys <dbl>, .disc_cost_med <dbl>,
# .disc_cost_resp <dbl>, .disc_cost_nresp <dbl>, .disc_cost_trans <dbl>,
# .disc_cost_hc <dbl>
$`Calc - Values`
# A tibble: 80 × 25
strategy group cycle ly_resp ly_nresp qalys_resp qalys_nresp lys qalys
<chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 chck All Pat… 1 2.95e-1 0.514 2.39e-1 0.326 0.809 0.565
2 chck All Pat… 2 4.82e-2 0.498 3.90e-2 0.329 0.546 0.368
3 chck All Pat… 3 1.01e-2 0.414 8.16e-3 0.277 0.424 0.285
4 chck All Pat… 4 2.29e-3 0.332 1.85e-3 0.222 0.334 0.224
5 chck All Pat… 5 5.48e-4 0.260 4.44e-4 0.174 0.261 0.175
6 chck All Pat… 6 1.36e-4 0.203 1.10e-4 0.136 0.203 0.136
7 chck All Pat… 7 3.48e-5 0.158 2.82e-5 0.106 0.158 0.106
8 chck All Pat… 8 9.14e-6 0.124 7.40e-6 0.0829 0.124 0.0829
9 chck All Pat… 9 2.45e-6 0.0973 1.98e-6 0.0652 0.0973 0.0652
10 chck All Pat… 10 6.67e-7 0.0770 5.40e-7 0.0516 0.0770 0.0516
# ℹ 70 more rows
# ℹ 16 more variables: cost_med <dbl>, cost_resp <dbl>, cost_nresp <dbl>,
# cost_trans <dbl>, cost_hc <dbl>, .disc_ly_resp <dbl>, .disc_ly_nresp <dbl>,
# .disc_qalys_resp <dbl>, .disc_qalys_nresp <dbl>, .disc_lys <dbl>,
# .disc_qalys <dbl>, .disc_cost_med <dbl>, .disc_cost_resp <dbl>,
# .disc_cost_nresp <dbl>, .disc_cost_trans <dbl>, .disc_cost_hc <dbl>
$`Results - Trace`
# A tibble: 84 × 9
model_day model_week model_month model_year series RESP REL REF
<dbl> <dbl> <dbl> <dbl> <chr> <dbl> <dbl> <dbl>
1 0 0 0 0 myfo 0.31 0 6.9 e-1
2 365 52.1 12 1 myfo 0.0486 0.256 1.63e-1
3 730 104. 24 2 myfo 0.0100 0.262 3.87e-2
4 1095 156. 36 3 myfo 0.00225 0.221 9.18e-3
5 1460 209. 48 4 myfo 0.000534 0.177 2.17e-3
6 1825 261. 60 5 myfo 0.000132 0.138 5.15e-4
7 2190 313. 72 6 myfo 0.0000336 0.108 1.22e-4
8 2555 365 84 7 myfo 0.00000877 0.0843 2.89e-5
9 2920 417. 96 8 myfo 0.00000234 0.0661 6.85e-6
10 3285 469. 108 9 myfo 0.000000636 0.0522 1.62e-6
# ℹ 74 more rows
# ℹ 1 more variable: DEAD <dbl>
$`Results - Trace (Corrected)`
# A tibble: 80 × 9
model_day model_week model_month model_year series RESP REL REF
<dbl> <dbl> <dbl> <dbl> <chr> <dbl> <dbl> <dbl>
1 365 52.1 12 1 myfo 0.179 0.128 4.27e-1
2 730 104. 24 2 myfo 0.0293 0.259 1.01e-1
3 1095 156. 36 3 myfo 0.00612 0.242 2.40e-2
4 1460 209. 48 4 myfo 0.00139 0.199 5.68e-3
5 1825 261. 60 5 myfo 0.000333 0.158 1.34e-3
6 2190 313. 72 6 myfo 0.0000827 0.123 3.19e-4
7 2555 365 84 7 myfo 0.0000212 0.0961 7.55e-5
8 2920 417. 96 8 myfo 0.00000556 0.0752 1.79e-5
9 3285 469. 108 9 myfo 0.00000149 0.0592 4.24e-6
10 3650 521. 120 10 myfo 0.000000405 0.0468 1.00e-6
# ℹ 70 more rows
# ℹ 1 more variable: DEAD <dbl>
$`Results - Outcomes`
# A tibble: 128 × 5
outcome series group disc value
<chr> <chr> <chr> <lgl> <dbl>
1 lys myfo ly_resp TRUE 0.215
2 lys chpl ly_resp TRUE 0.243
3 lys chck ly_resp TRUE 0.354
4 lys rlps ly_resp TRUE 0.377
5 lys chpl vs. myfo ly_resp TRUE 0.0277
6 lys chck vs. myfo ly_resp TRUE 0.139
7 lys rlps vs. myfo ly_resp TRUE 0.162
8 lys myfo vs. chpl ly_resp TRUE -0.0277
9 lys chck vs. chpl ly_resp TRUE 0.111
10 lys rlps vs. chpl ly_resp TRUE 0.134
# ℹ 118 more rows
$`Results - Costs`
# A tibble: 128 × 5
outcome series group disc value
<chr> <chr> <chr> <lgl> <dbl>
1 cost_hc myfo cost_med TRUE 9141.
2 cost_hc chpl cost_med TRUE 9302.
3 cost_hc chck cost_med TRUE 44162.
4 cost_hc rlps cost_med TRUE 58753.
5 cost_hc chpl vs. myfo cost_med TRUE 160.
6 cost_hc chck vs. myfo cost_med TRUE 35021.
7 cost_hc rlps vs. myfo cost_med TRUE 49612.
8 cost_hc myfo vs. chpl cost_med TRUE -160.
9 cost_hc chck vs. chpl cost_med TRUE 34861.
10 cost_hc rlps vs. chpl cost_med TRUE 49452.
# ℹ 118 more rows
$`Results - CE`
# A tibble: 8 × 11
hsumm esumm health_outcome econ_outcome series cost eff dcost deffect
<chr> <chr> <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl>
1 .disc_lys .dis… .disc_lys .disc_cost_… myfo 5.43e4 2.12 NA NA
2 .disc_lys .dis… .disc_lys .disc_cost_… chpl 5.44e4 2.29 103. 0.170
3 .disc_lys .dis… .disc_lys .disc_cost_… chck 8.90e4 2.97 34630. 0.681
4 .disc_lys .dis… .disc_lys .disc_cost_… rlps 1.04e5 3.11 14543. 0.140
5 .disc_qa… .dis… .disc_qalys .disc_cost_… myfo 5.43e4 1.42 NA NA
6 .disc_qa… .dis… .disc_qalys .disc_cost_… chpl 5.44e4 1.54 103. 0.120
7 .disc_qa… .dis… .disc_qalys .disc_cost_… chck 8.90e4 2.02 34630. 0.479
8 .disc_qa… .dis… .disc_qalys .disc_cost_… rlps 1.04e5 2.12 14543. 0.0989
# ℹ 2 more variables: dref <chr>, icer <dbl>
$`Results - NMB`
# A tibble: 96 × 6
outcome series group disc type value
<chr> <chr> <chr> <lgl> <chr> <dbl>
1 lys chpl vs. myfo ly_resp TRUE health 555.
2 lys chck vs. myfo ly_resp TRUE health 2774.
3 lys rlps vs. myfo ly_resp TRUE health 3231.
4 lys myfo vs. chpl ly_resp TRUE health -555.
5 lys chck vs. chpl ly_resp TRUE health 2219.
6 lys rlps vs. chpl ly_resp TRUE health 2676.
7 lys myfo vs. chck ly_resp TRUE health -2774.
8 lys chpl vs. chck ly_resp TRUE health -2219.
9 lys rlps vs. chck ly_resp TRUE health 458.
10 lys myfo vs. rlps ly_resp TRUE health -3231.
# ℹ 86 more rows
Code
exported_limited
Output
$`Inputs - Settings`
# A tibble: 4 × 2
setting value
<chr> <chr>
1 disc_cost 0.035
2 disc_eff 0.035
3 cycle_length 365
4 n_cycles 20
$`Inputs - Strategies`
# A tibble: 4 × 2
name desc
<chr> <chr>
1 myfo Myfosfamide
2 chpl Chemoplatin
3 chck Checkimab
4 rlps Relapsinib
$`Inputs - States`
# A tibble: 4 × 4
name desc prob limit
<chr> <chr> <chr> <dbl>
1 RESP Response dispatch_strategy(myfo = rr_myfo, chpl = rr_chpl, chck… 0
2 REL Relapse 0 0
3 REF Refractory C 0
4 DEAD Dead 0 0
$`Inputs - Transitions`
# A tibble: 4 × 5
strategy state formula id value
<chr> <chr> <chr> <chr> <chr>
1 All RESP rr * surv_prob(rfs, model_month) 6e50… rr *…
2 All REL rr * (surv_prob(os_resp, model_month) - surv_prob(… aefc… rr *…
3 All REF (1 - rr) * surv_prob(os_nresp, model_month) d1f8… (1 -…
4 All DEAD C 8c1d… C
$`Inputs - Health Values`
# A tibble: 6 × 5
name description strategy state value
<chr> <chr> <chr> <chr> <chr>
1 ly_resp Life Years in Response All RESP cycle_length_years
2 ly_nresp Life Years in Nonresponse All REL cycle_length_years
3 qalys_resp QALYs in Response All RESP util_resp * cycle_length…
4 qalys_nresp QALYs in Nonresponse All REL util_rel * cycle_length_…
5 ly_nresp Label... All REF cycle_length_years
6 qalys_nresp Label... All REF util_ref * cycle_length_…
$`Inputs - Econ Values`
# A tibble: 7 × 5
name description strategy state value
<chr> <chr> <chr> <chr> <chr>
1 cost_med Medication cost myfo RESP ucost_myfo * cycle_length…
2 cost_resp Routine care, response All All ucost_resp * cycle_length…
3 cost_nresp Routine care, nonresponse All All ucost_nresp * cycle_lengt…
4 cost_trans Transplant All REF rescale_prob(p_transplant…
5 cost_med Label... chpl RESP ucost_chpl * cycle_length…
6 cost_med Label... chck RESP ucost_chck * cycle_length…
7 cost_med Label... rlps RESP ucost_rlps * cycle_length…
$`Inputs - Health Summ`
# A tibble: 4 × 4
name description value wtp
<chr> <chr> <chr> <dbl>
1 lys Life-years ly_resp 20000
2 lys Life-years ly_nresp 20000
3 qalys Quality-adjusted life-years qalys_resp 30000
4 qalys Label... qalys_nresp 100000
$`Inputs - Econ Summ`
# A tibble: 4 × 3
name description value
<chr> <chr> <chr>
1 cost_hc Healthcare system costs cost_med
2 cost_hc Label... cost_resp
3 cost_hc Label... cost_nresp
4 cost_hc Label... cost_trans
$`Inputs - Parameters`
# A tibble: 21 × 6
name desc value low high psa
<chr> <chr> <chr> <chr> <chr> <chr>
1 rr_myfo Response rate, myfosfamide 0.31 "bc … "bc … "bin…
2 rr_chpl Response rate, chemoplatin 0.35 "bc … "bc … "bin…
3 rr_chck Response rate, checkimab 0.51 "bc … "bc … "bin…
4 rr_rlps Response rate, relapsinib 0.543 "bc … "bc … "bin…
5 rr Relapse rate dispatch_strate… "" "" ""
6 rfs_scale Scale parameter, RFS 6 "5.4… "7.1" "log…
7 rfs_shape Shape parameter, RFS 0.89 "0.7… "1.0… "log…
8 os_resp_meanlog log mean OS, responders 4 "3.4… "4.5… "nor…
9 os_resp_sdlog log SD OS, responders 0.71 "0.5… "0.9… "log…
10 os_nresp_rate Death rate, nonresponders 0.12 "0.0… "0.1… "log…
# ℹ 11 more rows
$`Inputs - Surv Dists`
# A tibble: 3 × 2
name value
<chr> <chr>
1 rfs "define_survival(shape = rfs_shape, scale = rfs_scale, dist = \"weib…
2 os_resp "define_survival(meanlog = os_resp_meanlog, sdlog = os_resp_sdlog, d…
3 os_nresp "define_survival(rate = os_nresp_rate, dist = \"exp\")"
$`Calc - Params`
# A tibble: 20 × 40
strategy group state_time cycle model_time cycle_length_days
<chr> <chr> <dbl> <dbl> <dbl> <dbl>
1 myfo All Patients 1 1 1 365
2 myfo All Patients 1 2 2 365
3 myfo All Patients 1 3 3 365
4 myfo All Patients 1 4 4 365
5 myfo All Patients 1 20 20 365
6 chpl All Patients 1 1 1 365
7 chpl All Patients 1 2 2 365
8 chpl All Patients 1 3 3 365
9 chpl All Patients 1 4 4 365
10 chpl All Patients 1 20 20 365
11 chck All Patients 1 1 1 365
12 chck All Patients 1 2 2 365
13 chck All Patients 1 3 3 365
14 chck All Patients 1 4 4 365
15 chck All Patients 1 20 20 365
16 rlps All Patients 1 1 1 365
17 rlps All Patients 1 2 2 365
18 rlps All Patients 1 3 3 365
19 rlps All Patients 1 4 4 365
20 rlps All Patients 1 20 20 365
# ℹ 34 more variables: cycle_length_weeks <dbl>, cycle_length_months <dbl>,
# cycle_length_years <dbl>, model_day <dbl>, model_week <dbl>,
# model_month <dbl>, model_year <dbl>, state_day <dbl>, state_week <dbl>,
# state_month <dbl>, state_year <dbl>, disc_h <dbl>, disc_e <dbl>,
# rr_myfo <dbl>, rr_chpl <dbl>, rr_chck <dbl>, rr_rlps <dbl>, rr <dbl>,
# rfs_scale <dbl>, rfs_shape <dbl>, os_resp_meanlog <dbl>,
# os_resp_sdlog <dbl>, os_nresp_rate <dbl>, util_resp <dbl>, …
$`Calc - Trans`
# A tibble: 84 × 9
model_day model_week model_month model_year series RESP REL REF
<dbl> <dbl> <dbl> <dbl> <chr> <dbl> <dbl> <dbl>
1 0 0 0 0 myfo 0.31 0 6.9 e-1
2 365 52.1 12 1 myfo 0.0486 0.256 1.63e-1
3 730 104. 24 2 myfo 0.0100 0.262 3.87e-2
4 1095 156. 36 3 myfo 0.00225 0.221 9.18e-3
5 1460 209. 48 4 myfo 0.000534 0.177 2.17e-3
6 1825 261. 60 5 myfo 0.000132 0.138 5.15e-4
7 2190 313. 72 6 myfo 0.0000336 0.108 1.22e-4
8 2555 365 84 7 myfo 0.00000877 0.0843 2.89e-5
9 2920 417. 96 8 myfo 0.00000234 0.0661 6.85e-6
10 3285 469. 108 9 myfo 0.000000636 0.0522 1.62e-6
# ℹ 74 more rows
# ℹ 1 more variable: DEAD <dbl>
$`Calc - Unit Values`
# A tibble: 32 × 26
strategy group cycle state ly_resp ly_nresp qalys_resp qalys_nresp lys
<chr> <chr> <dbl> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
1 chck All Patie… 1 DEAD 0 0 0 0 0
2 chck All Patie… 1 REF 0 1 0 0.61 1
3 chck All Patie… 1 REL 0 1 0 0.67 1
4 chck All Patie… 1 RESP 1 0 0.81 0 1
5 chck All Patie… 2 DEAD 0 0 0 0 0
6 chck All Patie… 2 REF 0 1 0 0.61 1
7 chck All Patie… 2 REL 0 1 0 0.67 1
8 chck All Patie… 2 RESP 1 0 0.81 0 1
9 chpl All Patie… 1 DEAD 0 0 0 0 0
10 chpl All Patie… 1 REF 0 1 0 0.61 1
# ℹ 22 more rows
# ℹ 17 more variables: qalys <dbl>, cost_med <dbl>, cost_resp <dbl>,
# cost_nresp <dbl>, cost_trans <dbl>, cost_hc <dbl>, .disc_ly_resp <dbl>,
# .disc_ly_nresp <dbl>, .disc_qalys_resp <dbl>, .disc_qalys_nresp <dbl>,
# .disc_lys <dbl>, .disc_qalys <dbl>, .disc_cost_med <dbl>,
# .disc_cost_resp <dbl>, .disc_cost_nresp <dbl>, .disc_cost_trans <dbl>,
# .disc_cost_hc <dbl>
$`Calc - Values`
# A tibble: 20 × 25
strategy group cycle ly_resp ly_nresp qalys_resp qalys_nresp lys qalys
<chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 chck All … 1 2.95e- 1 0.514 2.39e- 1 0.326 0.809 0.565
2 chck All … 2 4.82e- 2 0.498 3.90e- 2 0.329 0.546 0.368
3 chck All … 3 1.01e- 2 0.414 8.16e- 3 0.277 0.424 0.285
4 chck All … 4 2.29e- 3 0.332 1.85e- 3 0.222 0.334 0.224
5 chck All … 20 2.89e-12 0.0103 2.34e-12 0.00693 0.0103 0.00693
6 chpl All … 1 2.02e- 1 0.547 1.64e- 1 0.342 0.749 0.506
7 chpl All … 2 3.31e- 2 0.388 2.68e- 2 0.254 0.421 0.281
8 chpl All … 3 6.91e- 3 0.295 5.60e- 3 0.196 0.302 0.202
9 chpl All … 4 1.57e- 3 0.230 1.27e- 3 0.154 0.232 0.155
10 chpl All … 20 1.98e-12 0.00710 1.61e-12 0.00476 0.00710 0.00476
11 myfo All … 1 1.79e- 1 0.555 1.45e- 1 0.346 0.734 0.491
12 myfo All … 2 2.93e- 2 0.360 2.37e- 2 0.235 0.389 0.259
13 myfo All … 3 6.12e- 3 0.265 4.96e- 3 0.176 0.272 0.181
14 myfo All … 4 1.39e- 3 0.205 1.13e- 3 0.137 0.206 0.138
15 myfo All … 20 1.76e-12 0.00629 1.42e-12 0.00421 0.00629 0.00421
16 rlps All … 1 3.14e- 1 0.507 2.54e- 1 0.323 0.821 0.577
17 rlps All … 2 5.13e- 2 0.521 4.16e- 2 0.345 0.572 0.386
18 rlps All … 3 1.07e- 2 0.439 8.69e- 3 0.293 0.450 0.302
19 rlps All … 4 2.44e- 3 0.352 1.97e- 3 0.236 0.355 0.238
20 rlps All … 20 3.08e-12 0.0110 2.49e-12 0.00738 0.0110 0.00738
# ℹ 16 more variables: cost_med <dbl>, cost_resp <dbl>, cost_nresp <dbl>,
# cost_trans <dbl>, cost_hc <dbl>, .disc_ly_resp <dbl>, .disc_ly_nresp <dbl>,
# .disc_qalys_resp <dbl>, .disc_qalys_nresp <dbl>, .disc_lys <dbl>,
# .disc_qalys <dbl>, .disc_cost_med <dbl>, .disc_cost_resp <dbl>,
# .disc_cost_nresp <dbl>, .disc_cost_trans <dbl>, .disc_cost_hc <dbl>
$`Results - Trace`
# A tibble: 84 × 9
model_day model_week model_month model_year series RESP REL REF
<dbl> <dbl> <dbl> <dbl> <chr> <dbl> <dbl> <dbl>
1 0 0 0 0 myfo 0.31 0 6.9 e-1
2 365 52.1 12 1 myfo 0.0486 0.256 1.63e-1
3 730 104. 24 2 myfo 0.0100 0.262 3.87e-2
4 1095 156. 36 3 myfo 0.00225 0.221 9.18e-3
5 1460 209. 48 4 myfo 0.000534 0.177 2.17e-3
6 1825 261. 60 5 myfo 0.000132 0.138 5.15e-4
7 2190 313. 72 6 myfo 0.0000336 0.108 1.22e-4
8 2555 365 84 7 myfo 0.00000877 0.0843 2.89e-5
9 2920 417. 96 8 myfo 0.00000234 0.0661 6.85e-6
10 3285 469. 108 9 myfo 0.000000636 0.0522 1.62e-6
# ℹ 74 more rows
# ℹ 1 more variable: DEAD <dbl>
$`Results - Trace (Corrected)`
# A tibble: 80 × 9
model_day model_week model_month model_year series RESP REL REF
<dbl> <dbl> <dbl> <dbl> <chr> <dbl> <dbl> <dbl>
1 365 52.1 12 1 myfo 0.179 0.128 4.27e-1
2 730 104. 24 2 myfo 0.0293 0.259 1.01e-1
3 1095 156. 36 3 myfo 0.00612 0.242 2.40e-2
4 1460 209. 48 4 myfo 0.00139 0.199 5.68e-3
5 1825 261. 60 5 myfo 0.000333 0.158 1.34e-3
6 2190 313. 72 6 myfo 0.0000827 0.123 3.19e-4
7 2555 365 84 7 myfo 0.0000212 0.0961 7.55e-5
8 2920 417. 96 8 myfo 0.00000556 0.0752 1.79e-5
9 3285 469. 108 9 myfo 0.00000149 0.0592 4.24e-6
10 3650 521. 120 10 myfo 0.000000405 0.0468 1.00e-6
# ℹ 70 more rows
# ℹ 1 more variable: DEAD <dbl>
$`Results - Outcomes`
# A tibble: 128 × 5
outcome series group disc value
<chr> <chr> <chr> <lgl> <dbl>
1 lys myfo ly_resp TRUE 0.215
2 lys chpl ly_resp TRUE 0.243
3 lys chck ly_resp TRUE 0.354
4 lys rlps ly_resp TRUE 0.377
5 lys chpl vs. myfo ly_resp TRUE 0.0277
6 lys chck vs. myfo ly_resp TRUE 0.139
7 lys rlps vs. myfo ly_resp TRUE 0.162
8 lys myfo vs. chpl ly_resp TRUE -0.0277
9 lys chck vs. chpl ly_resp TRUE 0.111
10 lys rlps vs. chpl ly_resp TRUE 0.134
# ℹ 118 more rows
$`Results - Costs`
# A tibble: 128 × 5
outcome series group disc value
<chr> <chr> <chr> <lgl> <dbl>
1 cost_hc myfo cost_med TRUE 9141.
2 cost_hc chpl cost_med TRUE 9302.
3 cost_hc chck cost_med TRUE 44162.
4 cost_hc rlps cost_med TRUE 58753.
5 cost_hc chpl vs. myfo cost_med TRUE 160.
6 cost_hc chck vs. myfo cost_med TRUE 35021.
7 cost_hc rlps vs. myfo cost_med TRUE 49612.
8 cost_hc myfo vs. chpl cost_med TRUE -160.
9 cost_hc chck vs. chpl cost_med TRUE 34861.
10 cost_hc rlps vs. chpl cost_med TRUE 49452.
# ℹ 118 more rows
$`Results - CE`
# A tibble: 8 × 11
hsumm esumm health_outcome econ_outcome series cost eff dcost deffect
<chr> <chr> <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl>
1 .disc_lys .dis… .disc_lys .disc_cost_… myfo 5.43e4 2.12 NA NA
2 .disc_lys .dis… .disc_lys .disc_cost_… chpl 5.44e4 2.29 103. 0.170
3 .disc_lys .dis… .disc_lys .disc_cost_… chck 8.90e4 2.97 34630. 0.681
4 .disc_lys .dis… .disc_lys .disc_cost_… rlps 1.04e5 3.11 14543. 0.140
5 .disc_qa… .dis… .disc_qalys .disc_cost_… myfo 5.43e4 1.42 NA NA
6 .disc_qa… .dis… .disc_qalys .disc_cost_… chpl 5.44e4 1.54 103. 0.120
7 .disc_qa… .dis… .disc_qalys .disc_cost_… chck 8.90e4 2.02 34630. 0.479
8 .disc_qa… .dis… .disc_qalys .disc_cost_… rlps 1.04e5 2.12 14543. 0.0989
# ℹ 2 more variables: dref <chr>, icer <dbl>
$`Results - NMB`
# A tibble: 96 × 6
outcome series group disc type value
<chr> <chr> <chr> <lgl> <chr> <dbl>
1 lys chpl vs. myfo ly_resp TRUE health 555.
2 lys chck vs. myfo ly_resp TRUE health 2774.
3 lys rlps vs. myfo ly_resp TRUE health 3231.
4 lys myfo vs. chpl ly_resp TRUE health -555.
5 lys chck vs. chpl ly_resp TRUE health 2219.
6 lys rlps vs. chpl ly_resp TRUE health 2676.
7 lys myfo vs. chck ly_resp TRUE health -2774.
8 lys chpl vs. chck ly_resp TRUE health -2219.
9 lys rlps vs. chck ly_resp TRUE health 458.
10 lys myfo vs. rlps ly_resp TRUE health -3231.
# ℹ 86 more rows
Groups Model produces correct results.
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Code
exported
Output
$`Inputs - Settings`
# A tibble: 9 × 2
setting value
<chr> <chr>
1 disc_cost 0.03
2 disc_eff 0.03
3 n_cycles 40
4 method life-table
5 disc_method start
6 CycleLength 1
7 CycleLengthUnits years
8 ModelTimeframe 20
9 ModelTimeframeUnits years
$`Inputs - Groups`
# A tibble: 2 × 3
name weight start_age
<chr> <chr> <chr>
1 "\"adults\"" 0.8 60
2 "\"children\"" 0.2 12
$`Inputs - Strategies`
# A tibble: 3 × 2
name desc
<chr> <chr>
1 immun Immunotherapy
2 target Targeted therapy
3 chemo Chemotherapy
$`Inputs - States`
# A tibble: 3 × 4
name desc prob limit
<chr> <chr> <chr> <dbl>
1 rf Relapse-free 1 5
2 rel Post-relapse 0 5
3 dead Dead 0 1
$`Inputs - Transitions`
# A tibble: 6 × 4
strategy from to value
<chr> <chr> <chr> <chr>
1 All rf rel rfs_prob * (1 - rfs_mort)
2 All rf dead rfs_mort
3 All rf rf C
4 All rel dead rel_mort
5 All rel rel C
6 All dead dead 1
$`Inputs - Health Values`
# A tibble: 6 × 5
name label strategy state value
<chr> <chr> <chr> <chr> <chr>
1 febn Cases of febrile neutropenia All rf p_febn
2 lys_rf Relapse-free life years All rf cycle_length_years
3 lys_rel Post-relapse life years All rel cycle_length_years
4 qalys_rf Relapse-free QALYs All rf lys_rf * util_rf
5 qalys_rel Post-relapse QALYs All rel lys_rel* util_rel
6 qalys_febn Febrile neutropenia QALYs All rf febn * disutil_febn * …
$`Inputs - Econ Values`
# A tibble: 8 × 5
name label strategy state value
<chr> <chr> <chr> <chr> <chr>
1 cost_med Cost of medication chemo rf dose_chemo * freq_che…
2 cost_med Cost of medication target rf dose_target * freq_ta…
3 cost_med Cost of medication immun rf dose_immun * freq_imm…
4 cost_febn Cost of febrile neutropenia All rf ucost_febn * p_febn
5 cost_rf Routine care, relapse-free All rf ucost_rf * cycle_leng…
6 cost_rel Routine care, post-relapse All rel ucost_rel * cycle_len…
7 cost_term Cost of terminal care All rf→dead 50000
8 cost_term Cost of terminal care All rel→dead 50000
$`Inputs - Health Summ`
# A tibble: 5 × 4
name description value wtp
<chr> <chr> <chr> <dbl>
1 lys Life Years lys_rf 100000
2 lys Life Years lys_rel 100000
3 qalys QALYs qalys_rf 200000
4 qalys QALYs qalys_rel 200000
5 qalys QALYs qalys_febn 200000
$`Inputs - Econ Summ`
# A tibble: 4 × 4
name description value wtp
<chr> <chr> <chr> <dbl>
1 costs_hc Cost (HC) cost_med NA
2 costs_hc Cost (HC) cost_febn NA
3 costs_hc Cost (HC) cost_rf NA
4 costs_hc Cost (HC) cost_rel NA
$`Inputs - Parameters`
# A tibble: 38 × 6
name desc value low high psa
<chr> <chr> <chr> <chr> <chr> <chr>
1 current_age Current age "sta… "" "" ""
2 percent_male Percent male "0.4… "0.4" "0.6" "bet…
3 gp_mort_male Annualized general-population deat… "loo… "" "" ""
4 gp_mort_female Annualized general-population deat… "loo… "" "" ""
5 gp_mort Annualized general-population deat… "gp_… "" "" ""
6 gp_mort_per_cycle Per-cycle general-population death… "res… "" "" ""
7 rfs_p1 Relapse-free survival shape parame… "1.1… "bc … "bc … ""
8 rfs_p2 Relapse-free survival scale parame… "32.… "bc … "bc … ""
9 target_hr Hazard ratio of relapse, targeted … "0.6… "0.3" "0.8" ""
10 immun_hr Hazard ratio of relapse, immunothe… "0.3… "" "" ""
# ℹ 28 more rows
$`Tbl - life_table`
# A tibble: 240 × 5
age sex prob_death n_alive life_expectancy
<dbl> <chr> <dbl> <dbl> <dbl>
1 0 male 0.00632 100000 76.3
2 1 male 0.000396 99368 75.8
3 2 male 0.000282 99328 74.8
4 3 male 0.000212 99300 73.9
5 4 male 0.000186 99279 72.9
6 5 male 0.000162 99261 71.9
7 6 male 0.000144 99245 70.9
8 7 male 0.000129 99231 69.9
9 8 male 0.000114 99218 68.9
10 9 male 0.0001 99206 67.9
# ℹ 230 more rows
$`Calc - Params`
# A tibble: 600 × 59
strategy group state_time cycle model_time cycle_length_days
<chr> <chr> <dbl> <dbl> <dbl> <dbl>
1 immun adults 1 1 1 365
2 immun adults 1 2 2 365
3 immun adults 1 3 3 365
4 immun adults 1 4 4 365
5 immun adults 1 5 5 365
6 immun adults 1 6 6 365
7 immun adults 1 7 7 365
8 immun adults 1 8 8 365
9 immun adults 1 9 9 365
10 immun adults 1 10 10 365
# ℹ 590 more rows
# ℹ 53 more variables: cycle_length_weeks <dbl>, cycle_length_months <dbl>,
# cycle_length_years <dbl>, model_day <dbl>, model_week <dbl>,
# model_month <dbl>, model_year <dbl>, state_day <dbl>, state_week <dbl>,
# state_month <dbl>, state_year <dbl>, disc_h <dbl>, disc_e <dbl>,
# .group <chr>, start_age <dbl>, current_age <dbl>, percent_male <dbl>,
# gp_mort_male <dbl>, gp_mort_female <dbl>, gp_mort <dbl>, …
$`Calc - Trans`
# A tibble: 1,320 × 15
strategy group cycle from .rf_1 .rf_2 .rf_3 .rf_4 .rf_5 .rel_1 .rel_2 .rel_3
<chr> <chr> <dbl> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 immun adul… 1 .rf_1 0 0.860 0 0 0 0.116 0 0
2 immun adul… 1 .rf_2 0 0 0.842 0 0 0.134 0 0
3 immun adul… 1 .rf_3 0 0 0 0.834 0 0.142 0 0
4 immun adul… 1 .rf_4 0 0 0 0 0.828 0.148 0 0
5 immun adul… 1 .rf_5 0 0 0 0 0.824 0.152 0 0
6 immun adul… 1 .rel… 0 0 0 0 0 0 0.866 0
7 immun adul… 1 .rel… 0 0 0 0 0 0 0 0.800
8 immun adul… 1 .rel… 0 0 0 0 0 0 0 0
9 immun adul… 1 .rel… 0 0 0 0 0 0 0 0
10 immun adul… 1 .rel… 0 0 0 0 0 0 0 0
# ℹ 1,310 more rows
# ℹ 3 more variables: .rel_4 <dbl>, .rel_5 <dbl>, dead <dbl>
$`Calc - Unit Values`
# A tibble: 1,320 × 32
strategy group cycle state febn lys_rf lys_rel qalys_rf qalys_rel qalys_febn
<chr> <chr> <dbl> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 chemo adul… 1 .rel… 0 0 1 0 0.55 0
2 chemo adul… 2 .rel… 0 0 1 0 0.55 0
3 chemo adul… 3 .rel… 0 0 1 0 0.55 0
4 chemo adul… 4 .rel… 0 0 1 0 0.55 0
5 chemo adul… 5 .rel… 0 0 1 0 0.55 0
6 chemo adul… 6 .rel… 0 0 1 0 0.55 0
7 chemo adul… 7 .rel… 0 0 1 0 0.55 0
8 chemo adul… 8 .rel… 0 0 1 0 0.55 0
9 chemo adul… 9 .rel… 0 0 1 0 0.55 0
10 chemo adul… 10 .rel… 0 0 1 0 0.55 0
# ℹ 1,310 more rows
# ℹ 22 more variables: lys <dbl>, qalys <dbl>, cost_med <dbl>, cost_febn <dbl>,
# cost_rf <dbl>, cost_rel <dbl>, cost_term <dbl>, costs_hc <dbl>,
# .disc_febn <dbl>, .disc_lys_rf <dbl>, .disc_lys_rel <dbl>,
# .disc_qalys_rf <dbl>, .disc_qalys_rel <dbl>, .disc_qalys_febn <dbl>,
# .disc_lys <dbl>, .disc_qalys <dbl>, .disc_cost_med <dbl>,
# .disc_cost_febn <dbl>, .disc_cost_rf <dbl>, .disc_cost_rel <dbl>, …
$`Calc - Values`
# A tibble: 120 × 31
strategy group cycle febn lys_rf lys_rel qalys_rf qalys_rel qalys_febn
<chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 chemo adults 1 0.0128 0.850 0.138 0.697 0.0758 -0.000440
2 chemo adults 2 0.00872 0.581 0.367 0.477 0.202 -0.000301
3 chemo adults 3 0.00570 0.380 0.496 0.311 0.273 -0.000197
4 chemo adults 4 0.00363 0.242 0.532 0.199 0.292 -0.000125
5 chemo adults 5 0.00228 0.152 0.505 0.124 0.278 -0.0000786
6 chemo adults 6 0.00141 0.0940 0.444 0.0771 0.244 -0.0000487
7 chemo adults 7 0.000872 0.0581 0.369 0.0477 0.203 -0.0000301
8 chemo adults 8 0.000537 0.0358 0.296 0.0294 0.163 -0.0000185
9 chemo adults 9 0.000330 0.0220 0.231 0.0180 0.127 -0.0000114
10 chemo adults 10 0.000202 0.0135 0.177 0.0110 0.0973 -0.00000697
# ℹ 110 more rows
# ℹ 22 more variables: lys <dbl>, qalys <dbl>, cost_med <dbl>, cost_febn <dbl>,
# cost_rf <dbl>, cost_rel <dbl>, cost_term <dbl>, costs_hc <dbl>,
# .disc_febn <dbl>, .disc_lys_rf <dbl>, .disc_lys_rel <dbl>,
# .disc_qalys_rf <dbl>, .disc_qalys_rel <dbl>, .disc_qalys_febn <dbl>,
# .disc_lys <dbl>, .disc_qalys <dbl>, .disc_cost_med <dbl>,
# .disc_cost_febn <dbl>, .disc_cost_rf <dbl>, .disc_cost_rel <dbl>, …
$`Results - Trace`
# A tibble: 63 × 8
model_day model_week model_month model_year series rf rel dead
<dbl> <dbl> <dbl> <dbl> <chr> <dbl> <dbl> <dbl>
1 0 0 0 0 immun 1 0 0
2 365 52.1 12 1 immun 0.865 0.116 0.0193
3 730 104. 24 2 immun 0.730 0.217 0.0525
4 1095 156. 36 3 immun 0.610 0.286 0.104
5 1460 209. 48 4 immun 0.506 0.323 0.172
6 1825 261. 60 5 immun 0.416 0.334 0.250
7 2190 313. 72 6 immun 0.342 0.325 0.333
8 2555 365 84 7 immun 0.280 0.303 0.416
9 2920 417. 96 8 immun 0.229 0.275 0.496
10 3285 469. 108 9 immun 0.187 0.244 0.569
# ℹ 53 more rows
$`Results - Trace (Corrected)`
# A tibble: 60 × 8
model_day model_week model_month model_year series rf rel dead
<dbl> <dbl> <dbl> <dbl> <chr> <dbl> <dbl> <dbl>
1 365 52.1 12 1 immun 0.932 0.0581 0.00963
2 730 104. 24 2 immun 0.797 0.167 0.0359
3 1095 156. 36 3 immun 0.670 0.251 0.0784
4 1460 209. 48 4 immun 0.558 0.304 0.138
5 1825 261. 60 5 immun 0.461 0.328 0.211
6 2190 313. 72 6 immun 0.379 0.329 0.291
7 2555 365 84 7 immun 0.311 0.314 0.375
8 2920 417. 96 8 immun 0.255 0.289 0.456
9 3285 469. 108 9 immun 0.208 0.259 0.532
10 3650 521. 120 10 immun 0.170 0.228 0.602
# ℹ 50 more rows
$`Results - Outcomes`
# A tibble: 90 × 5
outcome series group disc value
<chr> <chr> <chr> <lgl> <dbl>
1 lys immun lys_rf TRUE 4.78
2 lys target lys_rf TRUE 3.28
3 lys chemo lys_rf TRUE 2.36
4 lys target vs. immun lys_rf TRUE -1.49
5 lys chemo vs. immun lys_rf TRUE -2.42
6 lys immun vs. target lys_rf TRUE 1.49
7 lys chemo vs. target lys_rf TRUE -0.924
8 lys immun vs. chemo lys_rf TRUE 2.42
9 lys target vs. chemo lys_rf TRUE 0.924
10 lys immun lys_rel TRUE 2.88
# ℹ 80 more rows
$`Results - Costs`
# A tibble: 72 × 5
outcome series group disc value
<chr> <chr> <chr> <lgl> <dbl>
1 costs_hc immun cost_med TRUE 48142.
2 costs_hc target cost_med TRUE 26459.
3 costs_hc chemo cost_med TRUE 67888.
4 costs_hc target vs. immun cost_med TRUE -21683.
5 costs_hc chemo vs. immun cost_med TRUE 19746.
6 costs_hc immun vs. target cost_med TRUE 21683.
7 costs_hc chemo vs. target cost_med TRUE 41429.
8 costs_hc immun vs. chemo cost_med TRUE -19746.
9 costs_hc target vs. chemo cost_med TRUE -41429.
10 costs_hc immun cost_febn TRUE 92.4
# ℹ 62 more rows
$`Results - CE`
# A tibble: 6 × 11
hsumm esumm health_outcome econ_outcome series cost eff dcost deffect
<chr> <chr> <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl>
1 .disc_lys .dis… .disc_lys .disc_costs… target 4.64e5 6.61 NA NA
2 .disc_lys .dis… .disc_lys .disc_costs… chemo 4.95e5 5.92 30931. -0.687
3 .disc_lys .dis… .disc_lys .disc_costs… immun 4.97e5 7.66 32728. 1.05
4 .disc_qa… .dis… .disc_qalys .disc_costs… target 4.64e5 4.52 NA NA
5 .disc_qa… .dis… .disc_qalys .disc_costs… chemo 4.95e5 3.89 30931. -0.627
6 .disc_qa… .dis… .disc_qalys .disc_costs… immun 4.97e5 5.50 32728. 0.981
# ℹ 2 more variables: dref <chr>, icer <dbl>
$`Results - NMB`
# A tibble: 54 × 6
outcome series group disc type value
<chr> <chr> <chr> <lgl> <chr> <dbl>
1 lys target vs. immun lys_rf TRUE health -149490.
2 lys chemo vs. immun lys_rf TRUE health -241881.
3 lys immun vs. target lys_rf TRUE health 149490.
4 lys chemo vs. target lys_rf TRUE health -92390.
5 lys immun vs. chemo lys_rf TRUE health 241881.
6 lys target vs. chemo lys_rf TRUE health 92390.
7 lys target vs. immun lys_rel TRUE health 44547.
8 lys chemo vs. immun lys_rel TRUE health 68251.
9 lys immun vs. target lys_rel TRUE health -44547.
10 lys chemo vs. target lys_rel TRUE health 23704.
# ℹ 44 more rows
Code
exported_limited
Output
$`Inputs - Settings`
# A tibble: 9 × 2
setting value
<chr> <chr>
1 disc_cost 0.03
2 disc_eff 0.03
3 n_cycles 40
4 method life-table
5 disc_method start
6 CycleLength 1
7 CycleLengthUnits years
8 ModelTimeframe 20
9 ModelTimeframeUnits years
$`Inputs - Groups`
# A tibble: 2 × 3
name weight start_age
<chr> <chr> <chr>
1 "\"adults\"" 0.8 60
2 "\"children\"" 0.2 12
$`Inputs - Strategies`
# A tibble: 3 × 2
name desc
<chr> <chr>
1 immun Immunotherapy
2 target Targeted therapy
3 chemo Chemotherapy
$`Inputs - States`
# A tibble: 3 × 4
name desc prob limit
<chr> <chr> <chr> <dbl>
1 rf Relapse-free 1 5
2 rel Post-relapse 0 5
3 dead Dead 0 1
$`Inputs - Transitions`
# A tibble: 6 × 4
strategy from to value
<chr> <chr> <chr> <chr>
1 All rf rel rfs_prob * (1 - rfs_mort)
2 All rf dead rfs_mort
3 All rf rf C
4 All rel dead rel_mort
5 All rel rel C
6 All dead dead 1
$`Inputs - Health Values`
# A tibble: 6 × 5
name label strategy state value
<chr> <chr> <chr> <chr> <chr>
1 febn Cases of febrile neutropenia All rf p_febn
2 lys_rf Relapse-free life years All rf cycle_length_years
3 lys_rel Post-relapse life years All rel cycle_length_years
4 qalys_rf Relapse-free QALYs All rf lys_rf * util_rf
5 qalys_rel Post-relapse QALYs All rel lys_rel* util_rel
6 qalys_febn Febrile neutropenia QALYs All rf febn * disutil_febn * …
$`Inputs - Econ Values`
# A tibble: 8 × 5
name label strategy state value
<chr> <chr> <chr> <chr> <chr>
1 cost_med Cost of medication chemo rf dose_chemo * freq_che…
2 cost_med Cost of medication target rf dose_target * freq_ta…
3 cost_med Cost of medication immun rf dose_immun * freq_imm…
4 cost_febn Cost of febrile neutropenia All rf ucost_febn * p_febn
5 cost_rf Routine care, relapse-free All rf ucost_rf * cycle_leng…
6 cost_rel Routine care, post-relapse All rel ucost_rel * cycle_len…
7 cost_term Cost of terminal care All rf→dead 50000
8 cost_term Cost of terminal care All rel→dead 50000
$`Inputs - Health Summ`
# A tibble: 5 × 4
name description value wtp
<chr> <chr> <chr> <dbl>
1 lys Life Years lys_rf 100000
2 lys Life Years lys_rel 100000
3 qalys QALYs qalys_rf 200000
4 qalys QALYs qalys_rel 200000
5 qalys QALYs qalys_febn 200000
$`Inputs - Econ Summ`
# A tibble: 4 × 4
name description value wtp
<chr> <chr> <chr> <dbl>
1 costs_hc Cost (HC) cost_med NA
2 costs_hc Cost (HC) cost_febn NA
3 costs_hc Cost (HC) cost_rf NA
4 costs_hc Cost (HC) cost_rel NA
$`Inputs - Parameters`
# A tibble: 38 × 6
name desc value low high psa
<chr> <chr> <chr> <chr> <chr> <chr>
1 current_age Current age "sta… "" "" ""
2 percent_male Percent male "0.4… "0.4" "0.6" "bet…
3 gp_mort_male Annualized general-population deat… "loo… "" "" ""
4 gp_mort_female Annualized general-population deat… "loo… "" "" ""
5 gp_mort Annualized general-population deat… "gp_… "" "" ""
6 gp_mort_per_cycle Per-cycle general-population death… "res… "" "" ""
7 rfs_p1 Relapse-free survival shape parame… "1.1… "bc … "bc … ""
8 rfs_p2 Relapse-free survival scale parame… "32.… "bc … "bc … ""
9 target_hr Hazard ratio of relapse, targeted … "0.6… "0.3" "0.8" ""
10 immun_hr Hazard ratio of relapse, immunothe… "0.3… "" "" ""
# ℹ 28 more rows
$`Tbl - life_table`
# A tibble: 240 × 5
age sex prob_death n_alive life_expectancy
<dbl> <chr> <dbl> <dbl> <dbl>
1 0 male 0.00632 100000 76.3
2 1 male 0.000396 99368 75.8
3 2 male 0.000282 99328 74.8
4 3 male 0.000212 99300 73.9
5 4 male 0.000186 99279 72.9
6 5 male 0.000162 99261 71.9
7 6 male 0.000144 99245 70.9
8 7 male 0.000129 99231 69.9
9 8 male 0.000114 99218 68.9
10 9 male 0.0001 99206 67.9
# ℹ 230 more rows
$`Calc - Params`
# A tibble: 24 × 59
strategy group state_time cycle model_time cycle_length_days
<chr> <chr> <dbl> <dbl> <dbl> <dbl>
1 immun adults 1 1 1 365
2 immun adults 1 2 2 365
3 immun adults 1 3 3 365
4 immun adults 1 4 4 365
5 immun children 1 1 1 365
6 immun children 1 2 2 365
7 immun children 1 3 3 365
8 immun children 1 4 4 365
9 target adults 1 1 1 365
10 target adults 1 2 2 365
# ℹ 14 more rows
# ℹ 53 more variables: cycle_length_weeks <dbl>, cycle_length_months <dbl>,
# cycle_length_years <dbl>, model_day <dbl>, model_week <dbl>,
# model_month <dbl>, model_year <dbl>, state_day <dbl>, state_week <dbl>,
# state_month <dbl>, state_year <dbl>, disc_h <dbl>, disc_e <dbl>,
# .group <chr>, start_age <dbl>, current_age <dbl>, percent_male <dbl>,
# gp_mort_male <dbl>, gp_mort_female <dbl>, gp_mort <dbl>, …
$`Calc - Trans`
# A tibble: 24 × 15
strategy group cycle from .rf_1 .rf_2 .rf_3 .rf_4 .rf_5 .rel_1 .rel_2 .rel_3
<chr> <chr> <dbl> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 immun adul… 1 .rf_1 0 0.860 0 0 0 0.116 0 0
2 immun adul… 1 .rf_2 0 0 0.842 0 0 0.134 0 0
3 immun adul… 1 .rf_3 0 0 0 0.834 0 0.142 0 0
4 immun adul… 1 .rf_4 0 0 0 0 0.828 0.148 0 0
5 immun chil… 1 .rf_1 0 0.881 0 0 0 0.118 0 0
6 immun chil… 1 .rf_2 0 0 0.862 0 0 0.137 0 0
7 immun chil… 1 .rf_3 0 0 0 0.854 0 0.146 0 0
8 immun chil… 1 .rf_4 0 0 0 0 0.848 0.151 0 0
9 target adul… 1 .rf_1 0 0.787 0 0 0 0.189 0 0
10 target adul… 1 .rf_2 0 0 0.758 0 0 0.218 0 0
# ℹ 14 more rows
# ℹ 3 more variables: .rel_4 <dbl>, .rel_5 <dbl>, dead <dbl>
$`Calc - Unit Values`
# A tibble: 66 × 32
strategy group cycle state febn lys_rf lys_rel qalys_rf qalys_rel qalys_febn
<chr> <chr> <dbl> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 chemo adul… 1 .rel… 0 0 1 0 0.55 0
2 chemo adul… 1 .rel… 0 0 1 0 0.55 0
3 chemo adul… 1 .rel… 0 0 1 0 0.55 0
4 chemo adul… 1 .rel… 0 0 1 0 0.55 0
5 chemo adul… 1 .rel… 0 0 1 0 0.55 0
6 chemo adul… 1 .rf_1 0.015 1 0 0.82 0 -0.000518
7 chemo adul… 1 .rf_2 0.015 1 0 0.82 0 -0.000518
8 chemo adul… 1 .rf_3 0.015 1 0 0.82 0 -0.000518
9 chemo adul… 1 .rf_4 0.015 1 0 0.82 0 -0.000518
10 chemo adul… 1 .rf_5 0.015 1 0 0.82 0 -0.000518
# ℹ 56 more rows
# ℹ 22 more variables: lys <dbl>, qalys <dbl>, cost_med <dbl>, cost_febn <dbl>,
# cost_rf <dbl>, cost_rel <dbl>, cost_term <dbl>, costs_hc <dbl>,
# .disc_febn <dbl>, .disc_lys_rf <dbl>, .disc_lys_rel <dbl>,
# .disc_qalys_rf <dbl>, .disc_qalys_rel <dbl>, .disc_qalys_febn <dbl>,
# .disc_lys <dbl>, .disc_qalys <dbl>, .disc_cost_med <dbl>,
# .disc_cost_febn <dbl>, .disc_cost_rf <dbl>, .disc_cost_rel <dbl>, …
$`Calc - Values`
# A tibble: 24 × 31
strategy group cycle febn lys_rf lys_rel qalys_rf qalys_rel qalys_febn
<chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 chemo adults 1 0.0128 0.850 0.138 0.697 0.0758 -0.000440
2 chemo adults 2 0.00872 0.581 0.367 0.477 0.202 -0.000301
3 chemo adults 3 0.00570 0.380 0.496 0.311 0.273 -0.000197
4 chemo adults 4 0.00363 0.242 0.532 0.199 0.292 -0.000125
5 chemo children 1 0.0129 0.859 0.141 0.704 0.0776 -0.000445
6 chemo children 2 0.00902 0.602 0.380 0.493 0.209 -0.000312
7 chemo children 3 0.00605 0.403 0.522 0.331 0.287 -0.000209
8 chemo children 4 0.00397 0.264 0.569 0.217 0.313 -0.000137
9 immun adults 1 0.00600 0.930 0.0578 0.763 0.0318 -0.000207
10 immun adults 2 0.00511 0.792 0.165 0.649 0.0910 -0.000176
# ℹ 14 more rows
# ℹ 22 more variables: lys <dbl>, qalys <dbl>, cost_med <dbl>, cost_febn <dbl>,
# cost_rf <dbl>, cost_rel <dbl>, cost_term <dbl>, costs_hc <dbl>,
# .disc_febn <dbl>, .disc_lys_rf <dbl>, .disc_lys_rel <dbl>,
# .disc_qalys_rf <dbl>, .disc_qalys_rel <dbl>, .disc_qalys_febn <dbl>,
# .disc_lys <dbl>, .disc_qalys <dbl>, .disc_cost_med <dbl>,
# .disc_cost_febn <dbl>, .disc_cost_rf <dbl>, .disc_cost_rel <dbl>, …
$`Results - Trace`
# A tibble: 63 × 8
model_day model_week model_month model_year series rf rel dead
<dbl> <dbl> <dbl> <dbl> <chr> <dbl> <dbl> <dbl>
1 0 0 0 0 immun 1 0 0
2 365 52.1 12 1 immun 0.865 0.116 0.0193
3 730 104. 24 2 immun 0.730 0.217 0.0525
4 1095 156. 36 3 immun 0.610 0.286 0.104
5 1460 209. 48 4 immun 0.506 0.323 0.172
6 1825 261. 60 5 immun 0.416 0.334 0.250
7 2190 313. 72 6 immun 0.342 0.325 0.333
8 2555 365 84 7 immun 0.280 0.303 0.416
9 2920 417. 96 8 immun 0.229 0.275 0.496
10 3285 469. 108 9 immun 0.187 0.244 0.569
# ℹ 53 more rows
$`Results - Trace (Corrected)`
# A tibble: 60 × 8
model_day model_week model_month model_year series rf rel dead
<dbl> <dbl> <dbl> <dbl> <chr> <dbl> <dbl> <dbl>
1 365 52.1 12 1 immun 0.932 0.0581 0.00963
2 730 104. 24 2 immun 0.797 0.167 0.0359
3 1095 156. 36 3 immun 0.670 0.251 0.0784
4 1460 209. 48 4 immun 0.558 0.304 0.138
5 1825 261. 60 5 immun 0.461 0.328 0.211
6 2190 313. 72 6 immun 0.379 0.329 0.291
7 2555 365 84 7 immun 0.311 0.314 0.375
8 2920 417. 96 8 immun 0.255 0.289 0.456
9 3285 469. 108 9 immun 0.208 0.259 0.532
10 3650 521. 120 10 immun 0.170 0.228 0.602
# ℹ 50 more rows
$`Results - Outcomes`
# A tibble: 90 × 5
outcome series group disc value
<chr> <chr> <chr> <lgl> <dbl>
1 lys immun lys_rf TRUE 4.78
2 lys target lys_rf TRUE 3.28
3 lys chemo lys_rf TRUE 2.36
4 lys target vs. immun lys_rf TRUE -1.49
5 lys chemo vs. immun lys_rf TRUE -2.42
6 lys immun vs. target lys_rf TRUE 1.49
7 lys chemo vs. target lys_rf TRUE -0.924
8 lys immun vs. chemo lys_rf TRUE 2.42
9 lys target vs. chemo lys_rf TRUE 0.924
10 lys immun lys_rel TRUE 2.88
# ℹ 80 more rows
$`Results - Costs`
# A tibble: 72 × 5
outcome series group disc value
<chr> <chr> <chr> <lgl> <dbl>
1 costs_hc immun cost_med TRUE 48142.
2 costs_hc target cost_med TRUE 26459.
3 costs_hc chemo cost_med TRUE 67888.
4 costs_hc target vs. immun cost_med TRUE -21683.
5 costs_hc chemo vs. immun cost_med TRUE 19746.
6 costs_hc immun vs. target cost_med TRUE 21683.
7 costs_hc chemo vs. target cost_med TRUE 41429.
8 costs_hc immun vs. chemo cost_med TRUE -19746.
9 costs_hc target vs. chemo cost_med TRUE -41429.
10 costs_hc immun cost_febn TRUE 92.4
# ℹ 62 more rows
$`Results - CE`
# A tibble: 6 × 11
hsumm esumm health_outcome econ_outcome series cost eff dcost deffect
<chr> <chr> <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl>
1 .disc_lys .dis… .disc_lys .disc_costs… target 4.64e5 6.61 NA NA
2 .disc_lys .dis… .disc_lys .disc_costs… chemo 4.95e5 5.92 30931. -0.687
3 .disc_lys .dis… .disc_lys .disc_costs… immun 4.97e5 7.66 32728. 1.05
4 .disc_qa… .dis… .disc_qalys .disc_costs… target 4.64e5 4.52 NA NA
5 .disc_qa… .dis… .disc_qalys .disc_costs… chemo 4.95e5 3.89 30931. -0.627
6 .disc_qa… .dis… .disc_qalys .disc_costs… immun 4.97e5 5.50 32728. 0.981
# ℹ 2 more variables: dref <chr>, icer <dbl>
$`Results - NMB`
# A tibble: 54 × 6
outcome series group disc type value
<chr> <chr> <chr> <lgl> <chr> <dbl>
1 lys target vs. immun lys_rf TRUE health -149490.
2 lys chemo vs. immun lys_rf TRUE health -241881.
3 lys immun vs. target lys_rf TRUE health 149490.
4 lys chemo vs. target lys_rf TRUE health -92390.
5 lys immun vs. chemo lys_rf TRUE health 241881.
6 lys target vs. chemo lys_rf TRUE health 92390.
7 lys target vs. immun lys_rel TRUE health 44547.
8 lys chemo vs. immun lys_rel TRUE health 68251.
9 lys immun vs. target lys_rel TRUE health -44547.
10 lys chemo vs. target lys_rel TRUE health 23704.
# ℹ 44 more rows
Simple Markov Model produces correct results.
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Code
exported
Output
$`Inputs - Settings`
# A tibble: 4 × 2
setting value
<chr> <chr>
1 disc_cost 0.03
2 disc_eff 0.03
3 cycle_length 365
4 n_cycles 20
$`Inputs - Strategies`
# A tibble: 2 × 2
name desc
<chr> <chr>
1 nat Natural History
2 new New Treatment
$`Inputs - States`
# A tibble: 3 × 4
name desc prob limit
<chr> <chr> <chr> <dbl>
1 well Patient is healthy 1 0
2 sick Patient is sick 0 0
3 dead Patient is dead 0 0
$`Inputs - Transitions`
# A tibble: 7 × 4
strategy from to value
<chr> <chr> <chr> <chr>
1 nat well sick p_sick_nat
2 new well sick p_sick_new
3 All well dead p_death_well
4 All well well C
5 All sick dead p_death_sick
6 All sick sick C
7 All dead dead 1
$`Inputs - Health Values`
# A tibble: 5 × 5
name description strategy state value
<chr> <chr> <chr> <chr> <chr>
1 well_lys Well life-years All well cycle_length_years
2 sick_lys Sick life-years All sick cycle_length_years
3 well_qalys Well QALYs nat All util_well_nat * well_lys
4 well_qalys Label... new All util_well_new * well_lys
5 sick_qalys Sick QALYs All All sick_lys * util_sick
$`Inputs - Econ Values`
# A tibble: 3 × 5
name description strategy state value
<chr> <chr> <chr> <chr> <chr>
1 med_cost Medication cost new well cost_new
2 term_cost Terminal care cost All sick→dead cost_hosp_stay
3 ae_cost Adverse Event Cost nat Model Start 100
$`Inputs - Health Summ`
# A tibble: 4 × 4
name description value wtp
<chr> <chr> <chr> <dbl>
1 lys Life-years well_lys 100000
2 lys Label... sick_lys 100000
3 qalys QALYs well_qalys 150000
4 qalys Label... sick_qalys 100000
$`Inputs - Econ Summ`
# A tibble: 3 × 3
name description value
<chr> <chr> <chr>
1 cost_hc Healthcare system costs med_cost
2 cost_hc Label... term_cost
3 cost_hc Healthcare system costs ae_cost
$`Inputs - Parameters`
# A tibble: 11 × 6
name desc value low high psa
<chr> <chr> <chr> <chr> <chr> <chr>
1 p_sick_nat Probability of getting sick, natura… 0.5 "bc … "bc … "bin…
2 p_sick_new Probability of getting sick, new dr… 0.30 "bc … "bc … "bin…
3 p_death_well Probability of dying while well 0.005 "0.0… "0.0… "bin…
4 p_death_sick Probability of dying while sick 0.08 "bc … "bc … "bin…
5 cost_new Cost per year of new drug 32000 "240… "480… ""
6 util_well_nat Utility value for well state, natur… 0.85 "" "" "log…
7 disutil_well_new Utility decrement associated with n… 0.02 "" "" "log…
8 disutil_sick Utility decrement associated with b… 0.23 "" "" "log…
9 cost_hosp_stay Cost of a hospital stay 85000 "" "" "nor…
10 util_well_new Utility value for well state, new d… util… "" "" ""
11 util_sick Utility value for sick state util… "" "" ""
$`Calc - Params`
# A tibble: 40 × 30
strategy group state_time cycle model_time cycle_length_days
<chr> <chr> <dbl> <dbl> <dbl> <dbl>
1 nat All Patients 1 1 1 365
2 nat All Patients 1 2 2 365
3 nat All Patients 1 3 3 365
4 nat All Patients 1 4 4 365
5 nat All Patients 1 5 5 365
6 nat All Patients 1 6 6 365
7 nat All Patients 1 7 7 365
8 nat All Patients 1 8 8 365
9 nat All Patients 1 9 9 365
10 nat All Patients 1 10 10 365
# ℹ 30 more rows
# ℹ 24 more variables: cycle_length_weeks <dbl>, cycle_length_months <dbl>,
# cycle_length_years <dbl>, model_day <dbl>, model_week <dbl>,
# model_month <dbl>, model_year <dbl>, state_day <dbl>, state_week <dbl>,
# state_month <dbl>, state_year <dbl>, disc_h <dbl>, disc_e <dbl>,
# p_sick_nat <dbl>, p_sick_new <dbl>, p_death_well <dbl>, p_death_sick <dbl>,
# cost_new <dbl>, util_well_nat <dbl>, disutil_well_new <dbl>, …
$`Calc - Trans`
# A tibble: 120 × 7
strategy group cycle from well sick dead
<chr> <chr> <dbl> <chr> <dbl> <dbl> <dbl>
1 nat All Patients 1 well 0.495 0.5 0.005
2 nat All Patients 1 sick 0 0.92 0.08
3 nat All Patients 1 dead 0 0 1
4 nat All Patients 2 well 0.495 0.5 0.005
5 nat All Patients 2 sick 0 0.92 0.08
6 nat All Patients 2 dead 0 0 1
7 nat All Patients 3 well 0.495 0.5 0.005
8 nat All Patients 3 sick 0 0.92 0.08
9 nat All Patients 3 dead 0 0 1
10 nat All Patients 4 well 0.495 0.5 0.005
# ℹ 110 more rows
$`Calc - Unit Values`
# A tibble: 120 × 24
strategy group cycle state well_lys sick_lys well_qalys sick_qalys lys
<chr> <chr> <dbl> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
1 nat All Patie… 1 dead 0 0 0 0 0
2 nat All Patie… 2 dead 0 0 0 0 0
3 nat All Patie… 3 dead 0 0 0 0 0
4 nat All Patie… 4 dead 0 0 0 0 0
5 nat All Patie… 5 dead 0 0 0 0 0
6 nat All Patie… 6 dead 0 0 0 0 0
7 nat All Patie… 7 dead 0 0 0 0 0
8 nat All Patie… 8 dead 0 0 0 0 0
9 nat All Patie… 9 dead 0 0 0 0 0
10 nat All Patie… 10 dead 0 0 0 0 0
# ℹ 110 more rows
# ℹ 15 more variables: qalys <dbl>, med_cost <dbl>, term_cost <dbl>,
# ae_cost <dbl>, cost_hc <dbl>, .disc_well_lys <dbl>, .disc_sick_lys <dbl>,
# .disc_well_qalys <dbl>, .disc_sick_qalys <dbl>, .disc_lys <dbl>,
# .disc_qalys <dbl>, .disc_med_cost <dbl>, .disc_term_cost <dbl>,
# .disc_ae_cost <dbl>, .disc_cost_hc <dbl>
$`Calc - Values`
# A tibble: 40 × 23
strategy group cycle well_lys sick_lys well_qalys sick_qalys lys qalys
<chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 nat All Patie… 1 0.748 0.25 0.635 0.155 0.998 0.790
2 nat All Patie… 2 0.370 0.604 0.315 0.374 0.974 0.689
3 nat All Patie… 3 0.183 0.740 0.156 0.459 0.924 0.615
4 nat All Patie… 4 0.0907 0.773 0.0771 0.479 0.863 0.556
5 nat All Patie… 5 0.0449 0.756 0.0381 0.469 0.801 0.507
6 nat All Patie… 6 0.0222 0.718 0.0189 0.445 0.740 0.464
7 nat All Patie… 7 0.0110 0.672 0.00935 0.417 0.683 0.426
8 nat All Patie… 8 0.00544 0.624 0.00463 0.387 0.629 0.391
9 nat All Patie… 9 0.00269 0.576 0.00229 0.357 0.579 0.360
10 nat All Patie… 10 0.00133 0.532 0.00113 0.330 0.533 0.331
# ℹ 30 more rows
# ℹ 14 more variables: med_cost <dbl>, term_cost <dbl>, ae_cost <dbl>,
# cost_hc <dbl>, .disc_well_lys <dbl>, .disc_sick_lys <dbl>,
# .disc_well_qalys <dbl>, .disc_sick_qalys <dbl>, .disc_lys <dbl>,
# .disc_qalys <dbl>, .disc_med_cost <dbl>, .disc_term_cost <dbl>,
# .disc_ae_cost <dbl>, .disc_cost_hc <dbl>
$`Results - Trace`
# A tibble: 42 × 8
model_day model_week model_month model_year series well sick dead
<dbl> <dbl> <dbl> <dbl> <chr> <dbl> <dbl> <dbl>
1 0 0 0 0 nat 1 0 0
2 365 52.1 12 1 nat 0.495 0.5 0.005
3 730 104. 24 2 nat 0.245 0.708 0.0475
4 1095 156. 36 3 nat 0.121 0.773 0.105
5 1460 209. 48 4 nat 0.0600 0.772 0.168
6 1825 261. 60 5 nat 0.0297 0.740 0.230
7 2190 313. 72 6 nat 0.0147 0.696 0.289
8 2555 365 84 7 nat 0.00728 0.648 0.345
9 2920 417. 96 8 nat 0.00360 0.600 0.397
10 3285 469. 108 9 nat 0.00178 0.553 0.445
# ℹ 32 more rows
$`Results - Trace (Corrected)`
# A tibble: 40 × 8
model_day model_week model_month model_year series well sick dead
<dbl> <dbl> <dbl> <dbl> <chr> <dbl> <dbl> <dbl>
1 365 52.1 12 1 nat 0.748 0.25 0.0025
2 730 104. 24 2 nat 0.370 0.604 0.0262
3 1095 156. 36 3 nat 0.183 0.740 0.0764
4 1460 209. 48 4 nat 0.0907 0.773 0.137
5 1825 261. 60 5 nat 0.0449 0.756 0.199
6 2190 313. 72 6 nat 0.0222 0.718 0.260
7 2555 365 84 7 nat 0.0110 0.672 0.317
8 2920 417. 96 8 nat 0.00544 0.624 0.371
9 3285 469. 108 9 nat 0.00269 0.576 0.421
10 3650 521. 120 10 nat 0.00133 0.532 0.467
# ℹ 30 more rows
$`Results - Outcomes`
# A tibble: 32 × 5
outcome series group disc value
<chr> <chr> <chr> <lgl> <dbl>
1 lys nat well_lys TRUE 1.44
2 lys new well_lys TRUE 2.60
3 lys new vs. nat well_lys TRUE 1.17
4 lys nat vs. new well_lys TRUE -1.17
5 lys nat sick_lys TRUE 7.78
6 lys new sick_lys TRUE 7.26
7 lys new vs. nat sick_lys TRUE -0.517
8 lys nat vs. new sick_lys TRUE 0.517
9 qalys nat well_qalys TRUE 1.22
10 qalys new well_qalys TRUE 2.16
# ℹ 22 more rows
$`Results - Costs`
# A tibble: 24 × 5
outcome series group disc value
<chr> <chr> <chr> <lgl> <dbl>
1 cost_hc nat med_cost TRUE 0
2 cost_hc new med_cost TRUE 83352.
3 cost_hc new vs. nat med_cost TRUE 83352.
4 cost_hc nat vs. new med_cost TRUE -83352.
5 cost_hc nat term_cost TRUE 51681.
6 cost_hc new term_cost TRUE 48161.
7 cost_hc new vs. nat term_cost TRUE -3520.
8 cost_hc nat vs. new term_cost TRUE 3520.
9 cost_hc nat ae_cost TRUE 100
10 cost_hc new ae_cost TRUE 0
# ℹ 14 more rows
$`Results - CE`
# A tibble: 4 × 11
hsumm esumm health_outcome econ_outcome series cost eff dcost deffect
<chr> <chr> <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl>
1 .disc_lys .dis… .disc_lys .disc_cost_… nat 5.18e4 9.22 NA NA
2 .disc_lys .dis… .disc_lys .disc_cost_… new 1.32e5 9.87 79732. 0.648
3 .disc_qa… .dis… .disc_qalys .disc_cost_… nat 5.18e4 6.05 NA NA
4 .disc_qa… .dis… .disc_qalys .disc_cost_… new 1.32e5 6.66 79732. 0.618
# ℹ 2 more variables: dref <chr>, icer <dbl>
$`Results - NMB`
# A tibble: 14 × 6
outcome series group disc type value
<chr> <chr> <chr> <lgl> <chr> <dbl>
1 lys new vs. nat well_lys TRUE health 116564.
2 lys nat vs. new well_lys TRUE health -116564.
3 lys new vs. nat sick_lys TRUE health -51719.
4 lys nat vs. new sick_lys TRUE health 51719.
5 qalys new vs. nat well_qalys TRUE health 140805.
6 qalys nat vs. new well_qalys TRUE health -140805.
7 qalys new vs. nat sick_qalys TRUE health -48098.
8 qalys nat vs. new sick_qalys TRUE health 48098.
9 cost_hc new vs. nat med_cost TRUE economic -83352.
10 cost_hc nat vs. new med_cost TRUE economic 83352.
11 cost_hc new vs. nat term_cost TRUE economic 3520.
12 cost_hc nat vs. new term_cost TRUE economic -3520.
13 cost_hc new vs. nat ae_cost TRUE economic 100
14 cost_hc nat vs. new ae_cost TRUE economic -100
Code
exported_limited
Output
$`Inputs - Settings`
# A tibble: 4 × 2
setting value
<chr> <chr>
1 disc_cost 0.03
2 disc_eff 0.03
3 cycle_length 365
4 n_cycles 20
$`Inputs - Strategies`
# A tibble: 2 × 2
name desc
<chr> <chr>
1 nat Natural History
2 new New Treatment
$`Inputs - States`
# A tibble: 3 × 4
name desc prob limit
<chr> <chr> <chr> <dbl>
1 well Patient is healthy 1 0
2 sick Patient is sick 0 0
3 dead Patient is dead 0 0
$`Inputs - Transitions`
# A tibble: 7 × 4
strategy from to value
<chr> <chr> <chr> <chr>
1 nat well sick p_sick_nat
2 new well sick p_sick_new
3 All well dead p_death_well
4 All well well C
5 All sick dead p_death_sick
6 All sick sick C
7 All dead dead 1
$`Inputs - Health Values`
# A tibble: 5 × 5
name description strategy state value
<chr> <chr> <chr> <chr> <chr>
1 well_lys Well life-years All well cycle_length_years
2 sick_lys Sick life-years All sick cycle_length_years
3 well_qalys Well QALYs nat All util_well_nat * well_lys
4 well_qalys Label... new All util_well_new * well_lys
5 sick_qalys Sick QALYs All All sick_lys * util_sick
$`Inputs - Econ Values`
# A tibble: 3 × 5
name description strategy state value
<chr> <chr> <chr> <chr> <chr>
1 med_cost Medication cost new well cost_new
2 term_cost Terminal care cost All sick→dead cost_hosp_stay
3 ae_cost Adverse Event Cost nat Model Start 100
$`Inputs - Health Summ`
# A tibble: 4 × 4
name description value wtp
<chr> <chr> <chr> <dbl>
1 lys Life-years well_lys 100000
2 lys Label... sick_lys 100000
3 qalys QALYs well_qalys 150000
4 qalys Label... sick_qalys 100000
$`Inputs - Econ Summ`
# A tibble: 3 × 3
name description value
<chr> <chr> <chr>
1 cost_hc Healthcare system costs med_cost
2 cost_hc Label... term_cost
3 cost_hc Healthcare system costs ae_cost
$`Inputs - Parameters`
# A tibble: 11 × 6
name desc value low high psa
<chr> <chr> <chr> <chr> <chr> <chr>
1 p_sick_nat Probability of getting sick, natura… 0.5 "bc … "bc … "bin…
2 p_sick_new Probability of getting sick, new dr… 0.30 "bc … "bc … "bin…
3 p_death_well Probability of dying while well 0.005 "0.0… "0.0… "bin…
4 p_death_sick Probability of dying while sick 0.08 "bc … "bc … "bin…
5 cost_new Cost per year of new drug 32000 "240… "480… ""
6 util_well_nat Utility value for well state, natur… 0.85 "" "" "log…
7 disutil_well_new Utility decrement associated with n… 0.02 "" "" "log…
8 disutil_sick Utility decrement associated with b… 0.23 "" "" "log…
9 cost_hosp_stay Cost of a hospital stay 85000 "" "" "nor…
10 util_well_new Utility value for well state, new d… util… "" "" ""
11 util_sick Utility value for sick state util… "" "" ""
$`Calc - Params`
# A tibble: 20 × 30
strategy group state_time cycle model_time cycle_length_days
<chr> <chr> <dbl> <dbl> <dbl> <dbl>
1 nat All Patients 1 1 1 365
2 nat All Patients 1 2 2 365
3 nat All Patients 1 3 3 365
4 nat All Patients 1 4 4 365
5 nat All Patients 1 5 5 365
6 nat All Patients 1 6 6 365
7 nat All Patients 1 7 7 365
8 nat All Patients 1 8 8 365
9 nat All Patients 1 19 19 365
10 nat All Patients 1 20 20 365
11 new All Patients 1 1 1 365
12 new All Patients 1 2 2 365
13 new All Patients 1 3 3 365
14 new All Patients 1 4 4 365
15 new All Patients 1 5 5 365
16 new All Patients 1 6 6 365
17 new All Patients 1 7 7 365
18 new All Patients 1 8 8 365
19 new All Patients 1 19 19 365
20 new All Patients 1 20 20 365
# ℹ 24 more variables: cycle_length_weeks <dbl>, cycle_length_months <dbl>,
# cycle_length_years <dbl>, model_day <dbl>, model_week <dbl>,
# model_month <dbl>, model_year <dbl>, state_day <dbl>, state_week <dbl>,
# state_month <dbl>, state_year <dbl>, disc_h <dbl>, disc_e <dbl>,
# p_sick_nat <dbl>, p_sick_new <dbl>, p_death_well <dbl>, p_death_sick <dbl>,
# cost_new <dbl>, util_well_nat <dbl>, disutil_well_new <dbl>,
# disutil_sick <dbl>, cost_hosp_stay <dbl>, util_well_new <dbl>, …
$`Calc - Trans`
# A tibble: 20 × 7
strategy group cycle from well sick dead
<chr> <chr> <dbl> <chr> <dbl> <dbl> <dbl>
1 nat All Patients 1 well 0.495 0.5 0.005
2 nat All Patients 1 sick 0 0.92 0.08
3 nat All Patients 1 dead 0 0 1
4 nat All Patients 2 well 0.495 0.5 0.005
5 nat All Patients 2 sick 0 0.92 0.08
6 nat All Patients 2 dead 0 0 1
7 nat All Patients 3 well 0.495 0.5 0.005
8 nat All Patients 3 sick 0 0.92 0.08
9 nat All Patients 20 sick 0 0.92 0.08
10 nat All Patients 20 dead 0 0 1
11 new All Patients 1 well 0.695 0.3 0.005
12 new All Patients 1 sick 0 0.92 0.08
13 new All Patients 1 dead 0 0 1
14 new All Patients 2 well 0.695 0.3 0.005
15 new All Patients 2 sick 0 0.92 0.08
16 new All Patients 2 dead 0 0 1
17 new All Patients 3 well 0.695 0.3 0.005
18 new All Patients 3 sick 0 0.92 0.08
19 new All Patients 20 sick 0 0.92 0.08
20 new All Patients 20 dead 0 0 1
$`Calc - Unit Values`
# A tibble: 24 × 24
strategy group cycle state well_lys sick_lys well_qalys sick_qalys lys
<chr> <chr> <dbl> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
1 nat All Patie… 1 dead 0 0 0 0 0
2 nat All Patie… 1 sick 0 1 0 0.62 1
3 nat All Patie… 1 well 1 0 0.85 0 1
4 nat All Patie… 2 dead 0 0 0 0 0
5 nat All Patie… 2 sick 0 1 0 0.62 1
6 nat All Patie… 2 well 1 0 0.85 0 1
7 nat All Patie… 3 dead 0 0 0 0 0
8 nat All Patie… 3 sick 0 1 0 0.62 1
9 nat All Patie… 3 well 1 0 0.85 0 1
10 nat All Patie… 4 dead 0 0 0 0 0
# ℹ 14 more rows
# ℹ 15 more variables: qalys <dbl>, med_cost <dbl>, term_cost <dbl>,
# ae_cost <dbl>, cost_hc <dbl>, .disc_well_lys <dbl>, .disc_sick_lys <dbl>,
# .disc_well_qalys <dbl>, .disc_sick_qalys <dbl>, .disc_lys <dbl>,
# .disc_qalys <dbl>, .disc_med_cost <dbl>, .disc_term_cost <dbl>,
# .disc_ae_cost <dbl>, .disc_cost_hc <dbl>
$`Calc - Values`
# A tibble: 20 × 23
strategy group cycle well_lys sick_lys well_qalys sick_qalys lys qalys
<chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 nat All Patie… 1 7.48e-1 0.25 0.635 0.155 0.998 0.790
2 nat All Patie… 2 3.70e-1 0.604 0.315 0.374 0.974 0.689
3 nat All Patie… 3 1.83e-1 0.740 0.156 0.459 0.924 0.615
4 nat All Patie… 4 9.07e-2 0.773 0.0771 0.479 0.863 0.556
5 nat All Patie… 5 4.49e-2 0.756 0.0381 0.469 0.801 0.507
6 nat All Patie… 6 2.22e-2 0.718 0.0189 0.445 0.740 0.464
7 nat All Patie… 7 1.10e-2 0.672 0.00935 0.417 0.683 0.426
8 nat All Patie… 8 5.44e-3 0.624 0.00463 0.387 0.629 0.391
9 nat All Patie… 19 2.38e-6 0.252 0.00000202 0.156 0.252 0.156
10 nat All Patie… 20 1.18e-6 0.232 0.00000100 0.144 0.232 0.144
11 new All Patie… 1 8.48e-1 0.15 0.703 0.093 0.998 0.796
12 new All Patie… 2 5.89e-1 0.392 0.489 0.243 0.981 0.732
13 new All Patie… 3 4.09e-1 0.538 0.340 0.333 0.947 0.673
14 new All Patie… 4 2.85e-1 0.617 0.236 0.383 0.902 0.619
15 new All Patie… 5 1.98e-1 0.653 0.164 0.405 0.851 0.569
16 new All Patie… 6 1.37e-1 0.660 0.114 0.409 0.798 0.524
17 new All Patie… 7 9.55e-2 0.649 0.0793 0.402 0.744 0.482
18 new All Patie… 8 6.64e-2 0.626 0.0551 0.388 0.692 0.443
19 new All Patie… 19 1.21e-3 0.284 0.00101 0.176 0.285 0.177
20 new All Patie… 20 8.43e-4 0.261 0.000700 0.162 0.262 0.163
# ℹ 14 more variables: med_cost <dbl>, term_cost <dbl>, ae_cost <dbl>,
# cost_hc <dbl>, .disc_well_lys <dbl>, .disc_sick_lys <dbl>,
# .disc_well_qalys <dbl>, .disc_sick_qalys <dbl>, .disc_lys <dbl>,
# .disc_qalys <dbl>, .disc_med_cost <dbl>, .disc_term_cost <dbl>,
# .disc_ae_cost <dbl>, .disc_cost_hc <dbl>
$`Results - Trace`
# A tibble: 42 × 8
model_day model_week model_month model_year series well sick dead
<dbl> <dbl> <dbl> <dbl> <chr> <dbl> <dbl> <dbl>
1 0 0 0 0 nat 1 0 0
2 365 52.1 12 1 nat 0.495 0.5 0.005
3 730 104. 24 2 nat 0.245 0.708 0.0475
4 1095 156. 36 3 nat 0.121 0.773 0.105
5 1460 209. 48 4 nat 0.0600 0.772 0.168
6 1825 261. 60 5 nat 0.0297 0.740 0.230
7 2190 313. 72 6 nat 0.0147 0.696 0.289
8 2555 365 84 7 nat 0.00728 0.648 0.345
9 2920 417. 96 8 nat 0.00360 0.600 0.397
10 3285 469. 108 9 nat 0.00178 0.553 0.445
# ℹ 32 more rows
$`Results - Trace (Corrected)`
# A tibble: 40 × 8
model_day model_week model_month model_year series well sick dead
<dbl> <dbl> <dbl> <dbl> <chr> <dbl> <dbl> <dbl>
1 365 52.1 12 1 nat 0.748 0.25 0.0025
2 730 104. 24 2 nat 0.370 0.604 0.0262
3 1095 156. 36 3 nat 0.183 0.740 0.0764
4 1460 209. 48 4 nat 0.0907 0.773 0.137
5 1825 261. 60 5 nat 0.0449 0.756 0.199
6 2190 313. 72 6 nat 0.0222 0.718 0.260
7 2555 365 84 7 nat 0.0110 0.672 0.317
8 2920 417. 96 8 nat 0.00544 0.624 0.371
9 3285 469. 108 9 nat 0.00269 0.576 0.421
10 3650 521. 120 10 nat 0.00133 0.532 0.467
# ℹ 30 more rows
$`Results - Outcomes`
# A tibble: 32 × 5
outcome series group disc value
<chr> <chr> <chr> <lgl> <dbl>
1 lys nat well_lys TRUE 1.44
2 lys new well_lys TRUE 2.60
3 lys new vs. nat well_lys TRUE 1.17
4 lys nat vs. new well_lys TRUE -1.17
5 lys nat sick_lys TRUE 7.78
6 lys new sick_lys TRUE 7.26
7 lys new vs. nat sick_lys TRUE -0.517
8 lys nat vs. new sick_lys TRUE 0.517
9 qalys nat well_qalys TRUE 1.22
10 qalys new well_qalys TRUE 2.16
# ℹ 22 more rows
$`Results - Costs`
# A tibble: 24 × 5
outcome series group disc value
<chr> <chr> <chr> <lgl> <dbl>
1 cost_hc nat med_cost TRUE 0
2 cost_hc new med_cost TRUE 83352.
3 cost_hc new vs. nat med_cost TRUE 83352.
4 cost_hc nat vs. new med_cost TRUE -83352.
5 cost_hc nat term_cost TRUE 51681.
6 cost_hc new term_cost TRUE 48161.
7 cost_hc new vs. nat term_cost TRUE -3520.
8 cost_hc nat vs. new term_cost TRUE 3520.
9 cost_hc nat ae_cost TRUE 100
10 cost_hc new ae_cost TRUE 0
# ℹ 14 more rows
$`Results - CE`
# A tibble: 4 × 11
hsumm esumm health_outcome econ_outcome series cost eff dcost deffect
<chr> <chr> <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl>
1 .disc_lys .dis… .disc_lys .disc_cost_… nat 5.18e4 9.22 NA NA
2 .disc_lys .dis… .disc_lys .disc_cost_… new 1.32e5 9.87 79732. 0.648
3 .disc_qa… .dis… .disc_qalys .disc_cost_… nat 5.18e4 6.05 NA NA
4 .disc_qa… .dis… .disc_qalys .disc_cost_… new 1.32e5 6.66 79732. 0.618
# ℹ 2 more variables: dref <chr>, icer <dbl>
$`Results - NMB`
# A tibble: 14 × 6
outcome series group disc type value
<chr> <chr> <chr> <lgl> <chr> <dbl>
1 lys new vs. nat well_lys TRUE health 116564.
2 lys nat vs. new well_lys TRUE health -116564.
3 lys new vs. nat sick_lys TRUE health -51719.
4 lys nat vs. new sick_lys TRUE health 51719.
5 qalys new vs. nat well_qalys TRUE health 140805.
6 qalys nat vs. new well_qalys TRUE health -140805.
7 qalys new vs. nat sick_qalys TRUE health -48098.
8 qalys nat vs. new sick_qalys TRUE health 48098.
9 cost_hc new vs. nat med_cost TRUE economic -83352.
10 cost_hc nat vs. new med_cost TRUE economic 83352.
11 cost_hc new vs. nat term_cost TRUE economic 3520.
12 cost_hc nat vs. new term_cost TRUE economic -3520.
13 cost_hc new vs. nat ae_cost TRUE economic 100
14 cost_hc nat vs. new ae_cost TRUE economic -100
Advanced Survival Modeling produces correct results.
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TA447 Replication produces correct results.
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Shared State-Time produces correct results.
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Sparse Matrix produces correct results.
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