## =======================================================================================================================
## FILENAME: shuang.R
## PROJECT: cost-effectiveness of prostate cancer screening in Sweden
## PURPOSE: To provide input data as parameters for the simulation
## AUTHOR: Shuang Hao
## UPDATED: 2022-01-27
ShuangParameters <- function(year=2018) {
stopifnot(year %in% 2018:2020)
base2018=list(
Andreas = FALSE, # general flag to use Shuang's parameters
## Swedish governmental report on organised PSA testing (p.22):
## https://www.socialstyrelsen.se/SiteCollectionDocuments/2018-2-13-halsoekonomisk-analys.pdf
## Based on the Swedish south region 2017:
## http://sodrasjukvardsregionen.se/avtal-priser/regionala-priser-och-ersattningar-foregaende-ar/
## S3M cost from Karolinska University Laboratory (KUL):
## https://www.karolinska.se/KUL/Alla-anvisningar/Anvisning/10245
## Latest cost for 2018
cost_parameters = c("Invitation" = 7 # Invitation letter
+ 7, # Results letter
"Formal PSA" = 355.82 # test sampling, primary care
+ 57.4 # PSA analysis
+ 0 * 1493.43, # No GP primary care
"Formal panel" = 355.82 # test sampling, primary care
+ 57.4 # PSA analysis not included in panel price
+ 3300 # From BergusMedical (official lab for Sthlm3)
+ 0 * 1493.43, # No GP for formal
"Opportunistic PSA" = 57.4 # PSA analysis
+ 0.2 * 1493.43, # GP primary care
"Opportunistic panel" = 57.4 # PSA analysis not included in panel price
+ 3300 # From BergusMedical (official lab for Sthlm3)
+ 0.2 * 1493.43, # GP primary care
"Biopsy" = 3010 # Systematic biopsy cost (SBx)
+ 4238.25, # Pathology of biopsy
"MRI" = 3500, # MRI cost
"Combined biopsy" = 3010*1.5 # Biopsy cost (SBx|TBx) ?Double the price
+ 4238.25, # Pathology of biopsy
"Assessment" = 1460, # Urologist and nurse consultation
"Prostatectomy" = 121170.69 # Robot assisted surgery
+ 6302.19*20*0.25 # Radiation therapy
+ 1460*1, # Urology and nurse visit
"Radiation therapy" = 6302.19*20 # Radiation therapy
+ 3903.27*1 # Oncologist new visit
+ 1683.36*1 # Oncologist further visit
+ 400*20 # Nurse visit
+ 67490.20*0.2, # Hormone therapy
"Active surveillance - yearly - w/o MRI" = 1460 # Urology visit and nurse visit
+ 355.82*3 # PSA sampling
+ 57.4*3 # PSA analysis
+ 3010*0.33 # Systematic biopsy
+ 4238.25*0.33, # Pathology of biopsy
"Active surveillance - yearly - with MRI" = 1460 # Urology visit and nurse visit
+ 355.82*3 # PSA sampling
+ 57.4*3 # PSA analysis
+ 3500*0.33 # MRI cost
+ 3010*1.5*0.33 # Biopsy cost (SBx|TBx)
+ 4238.25*0.33, # Pathology of biopsy
"ADT+chemo" = 71579.64*1.5, # NEW: Chemo and hormone therapy
"Post-Tx follow-up - yearly first" = 1460 # Urologist and nurse consultation
+ 355.82 # PSA test sampling
+ 57.4, # PSA analysis
"Post-Tx follow-up - yearly after" = 355.82 # PSA test sampling
+ 57.4 # PSA analysis,
+ 146, # Telefollow-up by urologist
"Palliative therapy - yearly" = 161593.05, # Palliative care cost
"Terminal illness" = 161593.05*0.5), # Terminal illness cost
## Swedish governmental report on organised PSA testing (p.23):
## https://www.socialstyrelsen.se/SiteCollectionDocuments/2018-2-13-halsoekonomisk-analys.pdf
## Swedish official statitics on mean salary for general population at working age
## https://www.scb.se/hitta-statistik/statistik-efter-amne/arbetsmarknad/loner-och-arbetskostnader/lonestrukturstatistik-hela-ekonomin/pong/tabell-och-diagram/genomsnittlig-manadslon-efter-sektor/
## Percentage of social and employee contribution on salary 37.13% for abetare
## https://www.ekonomifakta.se/Fakta/Skatter/Skatt-pa-arbete/Sociala-avgifter-over-tid/
## Exchange rate from SEK to EUR from the national bank
## https://www.riksbank.se/sv/statistik/sok-rantor--valutakurser/arsgenomsnitt-valutakurser/?y=2018&m=12&s=Comma&f=y
## Consumer price index
## https://www.scb.se/hitta-statistik/statistik-efter-amne/priser-och-konsumtion/konsumentprisindex/konsumentprisindex-kpi/pong/tabell-och-diagram/konsumentprisindex-kpi/kpi-faststallda-tal-1980100/
## Employment proportion
## http://www.statistikdatabasen.scb.se/pxweb/sv/ssd/START__AM__AM0401__AM0401A/NAKUBefolkning2Ar/?loadedQueryId=63385&timeType=from&timeValue=2001
## Updated to year 2018
production = data.frame(ages = c(0, 54, 64, 74),
values=apply(
rbind(0.891, 0.781, 0.169, 0), # employment portion, full time
1,
function(empl) empl*
30.7/40* # average working hours
34600*12* # average salary
1.3713)), # including non-optional social fees
lost_production_years= c("Formal PSA"=2/24/365.25,
"Formal panel"=2/24/365.25,
"Opportunistic PSA"=2/24/365.25,
"Opportunistic panel"=2/24/365.25,
"MRI"=2/24/365.25,
"Biopsy"=2/24/365.25,
"Combined biopsy"=2/24/365.25,
"Assessment"=2/24/365.25, # do we need this?
"Prostatectomy"=6/52,
"Radiation therapy"=8/52,
"Active surveillance - yearly - w/o MRI"=
3 * 2/24/365.25 # PSA tests
+ 1 * 2/24/365.25 # Urologist visit
+ 0.33 * 2/24/365.25, # Biopsy (SBx)
"Active surveillance - yearly - with MRI"=
3 * 2/24/365.25 # PSA tests
+ 1 * 2/24/365.25 # Urologist visit
+ 0.33 * 2/24/365.25 # MRI
+ 0.33 * 2/24/365.25, # Combined biopsy (TBx|SBx)
"Post-Tx follow-up - yearly" =
2/24/365.25, # PSA tests (Same for first year and following years)
"Premature mortality" = 0, # To discuss, depending on the age of death
"Long-term sick leave" = 0.0768*67.52/365.25, # 7.68% employed PCa patients (50-64) have long-term sick leave (based on 2016 data)
## "Early retirement" = 0.00203*235.5/365.25, # 0.203% employed PCa patients (50-64) have early retirement (based on 2016 data)
"Terminal illness" = 6/12), # Should delete, should be reflected from sick leave or disability pension
## Latest review 2019 based on Heijnsdijk 2012, Magnus 2019 and extended review by Shuang - PORPUS-U
utility_estimates = c("Invitation" = 1, # Heijnsdijk 2012
"Formal PSA" = 0.99, # Heijnsdijk 2012
"Formal panel" = 0.99, # Heijnsdijk 2012
"Opportunistic PSA" = 0.99, # Heijnsdijk 2012
"Opportunistic panel" = 0.99, # Heijnsdijk 2012
"Biopsy" = 0.90, # Heijnsdijk 2012
"Cancer diagnosis" = 0.80, # Heijnsdijk 2012
"Prostatectomy part 1" = 0.860, # Magnus 2019 (Krahn 2009, Ku 2009)
"Prostatectomy part 2" = 0.900, # Magnus 2019 (Krahn 2009, Ku 2009)
"Radiation therapy part 1" = 0.890, # Krahn 2009
"Radiation therapy part 2" = 0.920, # Krahn 2009
"Active surveillance" = 0.980, # Loeb 2018
"Postrecovery period" = 0.930, # Magnus 2019 (Avila 2014, Bremner 2014, Krahn 2013, Ku 2009)
"ADT+chemo" = 0.803, # Krahn 2003
"Palliative therapy" = 0.680, # *15D value; Magnus 2019 (Farrkila 2014, Torvinen 2013)
"Terminal illness" = 0.40, # Heijnsdijk 2012
"Death" = 0.00),
## Utility duration is given in years.
utility_duration = c("Invitation" = 0.0,
"Formal PSA" = 1/52,
"Formal panel" = 1/52,
"Opportunistic PSA" = 1/52,
"Opportunistic panel" = 1/52,
"Biopsy" = 3/52,
"Combined biopsy" = 3/52,
"Cancer diagnosis" = 1/12,
"Prostatectomy part 1" = 2/12,
"Prostatectomy part 2" = 10/12,
"Radiation therapy part 1" = 2/12,
"Radiation therapy part 2" = 10/12,
"Active surveillance" = 7,
"Postrecovery period" = 9,
"ADT+chemo" = 1.5, # Assumption!!!
"Palliative therapy" = 12/12, # Palliative therapy
"Terminal illness" = 6/12),
pMRIposG0=0.4515496, # Pr(MRI+ | ISUP 0 || undetectable) 2020-03-23
pMRIposG1=0.7145305, # Pr(MRI+ | ISUP 1 && detectable) 2020-03-23
pMRIposG2=0.9305352, # Pr(MRI+ | ISUP 2+ && detectable) 2020-03-23
pSBxG0ifG1=0.1402583, # Pr(SBx gives ISUP 0 | ISUP 1) 2020-03-23
pSBxG0ifG2=0.1032593, # Pr(SBx gives ISUP 0 | ISUP 2) 2020-03-23
pSBxG1ifG2=0.119, # Pr(SBx gives ISUP 1 | ISUP 2) (not used)
pTBxG0ifG1_MRIpos=0, # Pr(TBx gives ISUP 0 | ISUP 1, MRI+) #Updated 2020-03-24 from Bx -> TBx
pTBxG0ifG2_MRIpos=0, # Pr(TBx gives ISUP 0 | ISUP 2, MRI+) #Updated 2020-03-24 from Bx -> TBx
pTBxG1ifG2_MRIpos=0, # Pr(TBx gives ISUP 1 | ISUP 2, MRI+) (not used) #Updated 2020-03-24 from Bx -> TBx
currency_rate = 1/10.2567, # Riksbanken 2018
mu0=c(0.002644, 0.000207, 9.5e-05, 0.00014, 0.000114, 5.6e-05, 6.4e-05, 9e-05, 5.5e-05, 6.4e-05,
6.1e-05, 7.1e-05, 9.1e-05, 0.000146, 0.000113, 0.000157, 0.000231, 0.000311, 0.000374, 0.000507,
0.000519, 0.000649, 0.000614, 0.000678, 0.000713, 0.000677, 0.000698, 0.000698, 0.000714, 0.000766,
0.000669, 0.000764, 0.00074, 0.000691, 0.000722, 0.000685, 0.000738, 0.000745, 0.000773, 0.000831,
0.000971, 0.001013, 0.001022, 0.00119, 0.001322, 0.001345, 0.001672, 0.0018, 0.002111, 0.002327,
0.002626, 0.002744, 0.002851, 0.003482, 0.003782, 0.004206, 0.004645, 0.004845, 0.005491, 0.006256,
0.00687, 0.007793, 0.008251, 0.009231, 0.010119, 0.011176, 0.012616, 0.013612, 0.01474, 0.016834,
0.018531, 0.020063, 0.021987, 0.024831, 0.028604, 0.031887, 0.03597, 0.040838, 0.045803, 0.050884,
0.058464, 0.06515, 0.074592, 0.08552, 0.096554, 0.10965, 0.123894, 0.140601, 0.155434, 0.181008,
0.201892, 0.227595, 0.25149, 0.28064, 0.30848, 0.344113, 0.366119, 0.419757, 0.436817, 0.485551,
0.569208, 0.57603, 0.622803, 0.600511, 0.786461, 0.823125)
## 2010-2014 death rates from human mortality database https://www.mortality.org/,
## find "Sweden" and click on 1x5 death rates https://www.mortality.org/hmd/SWE/STATS/Mx_1x5.txt,
## Access date: 2020-03-26
## Note on 2020-12-09: due to the update from the Human Mortality database, data before age 80 kept the same from last access (0.05884)
## Note on 2020-12-09: Data from age80 changed slightly
)
base2019 <-
modifyList(base2018,
## Swedish governmental report on organised PSA testing (p.23 6.2 Organiserad prostatacancertestning):
## https://kunskapsbanken.cancercentrum.se/diagnoser/prostatacancer/vardprogram/f
## Based on the Swedish south region 2017:
## http://sodrasjukvardsregionen.se/avtal-priser/regionala-priser-och-ersattningar-foregaende-ar/
## S3M unit cost ("list price") from A23 Lab (Ola Steinberg):
## https://a23lab.se/stockholm3/
## Latest cost for 2019
list(cost_parameters = c("Invitation" = 7.12 # Invitation letter
+ 7.12, # Results letter
"Formal PSA" = 362.16 # test sampling, primary care
+ 58.42 # PSA analysis
+ 0 * 1520.08, # No GP primary care
"Formal panel" = 362.16 # test sampling, primary care
+ 58.42 # PSA analysis not included in panel price
+ 2300 # From A23 Lab (Ola Steinberg (list price from A23 Lab)
+ 0 * 1520.08, # No GP for formal
"Opportunistic PSA" = 58.42 # PSA analysis
+ 0.2 * 1520.08, # GP primary care
"Opportunistic panel" = 58.42 # PSA analysis not included in panel price
+ 2300 # From BergusMedical (official lab for Sthlm3)
+ 0.2 * 1520.08, # GP primary care
"Biopsy" = 3063.71 # Systematic biopsy cost (SBx)
+ 4313.88, # Pathology of biopsy
"MRI" = 3562.45, # MRI cost
"Combined biopsy" = 3063.71*1.5 # Biopsy cost (SBx|TBx) ?Double the price
+ 4313.88, # Pathology of biopsy
"Assessment" = 1486.05, # Urologist and nurse consultation
"Prostatectomy" = 117426.74 # Robot assisted surgery
+ 6414.65*20*0.25 # Radiation therapy
+ 1486.05*1, # Urology and nurse visit
"Radiation therapy" = 6414.65*20 # Radiation therapy
+ 3972.92*1 # Oncologist new visit
+ 1713.40*1 # Oncologist further visit
+ 407.14*20 # Nurse visit
+ 68694.51*0.2, # Hormone therapy
"Active surveillance - yearly - w/o MRI" = 1486.05 # Urology visit and nurse visit
+ 362.16*3 # PSA sampling
+ 58.42*3 # PSA analysis
+ 3063.71*0.33 # Systematic biopsy (SBx)
+ 4313.88*0.33, # Pathology of biopsy
"Active surveillance - yearly - with MRI" = 1486.05 # Urology visit and nurse visit
+ 362.16*3 # PSA sampling
+ 58.42*3 # PSA analysis
+ 3562.45*0.33 # MRI cost
+ 3063.71*1.5*0.33 # Biopsy cost (SBx|TBx)
+ 4313.88*0.33, # Pathology of biopsy
"ADT+chemo" = 72856.91*1.5, # NEW: Chemo and hormone therapy
"Post-Tx follow-up - yearly first" = 1486.05 # Urologist and nurse consultation
+ 362.16 # PSA test sampling
+ 58.42, # PSA analysis
"Post-Tx follow-up - yearly after" = 362.16 # PSA test sampling
+ 58.42 # PSA analysis,
+ 148.61, # Telefollow-up by urologist
"Palliative therapy - yearly" = 164476.53,# Palliative care cost
"Terminal illness" = 164476.53*0.5), # Terminal illness cost
## Swedish governmental report on organised PSA testing (p.23):
## https://www.socialstyrelsen.se/SiteCollectionDocuments/2018-2-13-halsoekonomisk-analys.pdf
## Swedish official statitics on mean salary for general population at working age
## https://www.scb.se/hitta-statistik/statistik-efter-amne/arbetsmarknad/loner-och-arbetskostnader/lonestrukturstatistik-hela-ekonomin/pong/tabell-och-diagram/genomsnittlig-manadslon-efter-sektor/
## Average working weekly working hours in Sweden 2019
## https://https://www.statista.com/statistics/528482/sweden-average-weekly-working-hours/
## Percentage of social and employee contribution on salary 37.00% for abetare
## https://www.ekonomifakta.se/Fakta/Skatter/Skatt-pa-arbete/Sociala-avgifter-over-tid/
## Exchange rate from SEK to EUR from the national bank
## https://www.riksbank.se/sv/statistik/sok-rantor--valutakurser/arsgenomsnitt-valutakurser/?y=2018&m=12&s=Comma&f=y
## Consumer price index
## https://www.scb.se/hitta-statistik/statistik-efter-amne/priser-och-konsumtion/konsumentprisindex/konsumentprisindex-kpi/pong/tabell-och-diagram/konsumentprisindex-kpi/kpi-faststallda-tal-1980100/
## Employment proportion
## http://www.statistikdatabasen.scb.se/pxweb/sv/ssd/START__AM__AM0401__AM0401A/NAKUBefolkning2Ar/?loadedQueryId=63385&timeType=from&timeValue=2001
## Updated to year 2019
production = data.frame(ages = c(0, 54, 64, 74),
values=apply(
rbind(0.89, 0.779, 0.175, 0), # employment portion, full time
1,
function(empl) empl*
30.2/40* # average working hours
34000*12* # average salary
1.3700)), # including non-optional social fees
## Updated currency exchange rate
currency_rate = 1/10.5892, # Riksbanken 2019
mu0=c(0.002438,0.000177,0.000126,0.000068,0.000119,0.000099,0.000070,0.000042,0.000068,0.000023,
0.000050,0.000067,0.000089,0.000101,0.000131,0.000147,0.000166,0.000291,0.000415,0.000482,
0.000569,0.000602,0.000602,0.000582,0.000720,0.000823,0.000673,0.000735,0.000747,0.000699,
0.000698,0.000664,0.000758,0.000766,0.000718,0.000813,0.000847,0.000797,0.000785,0.000913,
0.001033,0.000985,0.001118,0.001084,0.001194,0.001278,0.001440,0.001436,0.001682,0.002005,
0.002083,0.002207,0.002719,0.002982,0.003331,0.003674,0.004121,0.004430,0.004757,0.005319,
0.006225,0.006676,0.007804,0.008453,0.009510,0.010282,0.011912,0.012557,0.013540,0.015319,
0.016865,0.018438,0.020668,0.022392,0.025004,0.028228,0.031763,0.035649,0.040985,0.045583,
0.052091,0.059322,0.067212,0.076669,0.087961,0.101087,0.115534,0.131556,0.147308,0.169331,
0.194948,0.215649,0.242328,0.270844,0.300826,0.335924,0.371850,0.411620,0.432771,0.482348,
0.526314,0.536479,0.665380,0.477720,0.845950,0.821827,1.135842,2.321872,6.000000)))
## 2015-2019 death rates from human mortality database https://www.mortality.org/,
## find "Sweden" and click on 1x5 death rates https://www.mortality.org/hmd/SWE/STATS/Mx_1x5.txt,
## Access date: 2020-12-08
## Note 2020-12-09: mu0 from age 0 to age 109
base2020 <-
modifyList(base2019,
## Swedish governmental report on organised PSA testing (p.23 6.2 Organiserad prostatacancertestning):
## https://kunskapsbanken.cancercentrum.se/diagnoser/prostatacancer/vardprogram/f
## Based on the Swedish south region 2017:
## http://sodrasjukvardsregionen.se/avtal-priser/regionala-priser-och-ersattningar-foregaende-ar/
## S3M unit cost ("list price") from A23 Lab (Ola Steinberg):
## https://a23lab.se/stockholm3/
## Latest cost for 2020
list(cost_parameters = c("Invitation" = 7.16 # Invitation letter
+ 7.16, # Results letter
"Formal PSA" = 363.96 # test sampling, primary care
+ 58.71 # PSA analysis
+ 0 * 1527.63, # No GP primary care
"Formal panel" = 363.96 # test sampling, primary care
+ 58.71 # PSA analysis not included in panel price
+ 2300 # From A23 Lab (Ola Steinberg (list price from A23 Lab)
+ 0 * 1527.63, # No GP for formal
"Opportunistic PSA" = 58.71 # PSA analysis
+ 0.2 * 1527.63, # GP primary care
"Opportunistic panel" = 58.71 # PSA analysis not included in panel price
+ 2300 # From BergusMedical (official lab for Sthlm3)
+ 0.2 * 1527.63, # GP primary care
"Biopsy" = 3010 # Systematic biopsy cost (SBx)
+ 4335.30, # Pathology of biopsy
"MRI" = 3500, # MRI cost
"Combined biopsy" = 3010*1.5 # Biopsy cost (SBx|TBx) ?Double the price
+ 4335.30, # Pathology of biopsy
"Assessment" = 1460, # Urologist and nurse consultation
"Prostatectomy" = 118009.91 # Robot assisted surgery
+ 6446.51*20*0.25 # Radiation therapy
+ 1460*1, # Urology and nurse visit
"Radiation therapy" = 6446.51*20 # Radiation therapy
+ 3992.65*1 # Oncologist new visit
+ 1721.90*1 # Oncologist further visit
+ 400*20 # Nurse visit
+ 69035.66*0.2, # Hormone therapy
"Active surveillance - yearly - w/o MRI" = 1460 # Urology visit and nurse visit
+ 363.96*3 # PSA sampling
+ 58.71*3 # PSA analysis
+ 3010*0.33 # Systematic biopsy (SBx)
+ 4335.30*0.33, # Pathology of biopsy
"Active surveillance - yearly - with MRI" = 1493.43 # Urology visit and nurse visit
+ 363.96*3 # PSA sampling
+ 58.71*3 # PSA analysis
+ 3500*0.33 # MRI cost
+ 3010*1.5*0.33 # Biopsy cost (SBx|TBx)
+ 4335.30*0.33, # Pathology of biopsy
"ADT+chemo" = 145216, # Drug treatment for metastasis
"Post-Tx follow-up - yearly first" = 1460 # Urologist and nurse consultation
+ 363.96 # PSA test sampling
+ 58.71, # PSA analysis
"Post-Tx follow-up - yearly after" = 363.96 # PSA test sampling
+ 58.71 # PSA analysis,
+ 146, # Telefollow-up by urologist
"Palliative therapy - yearly" = 165293.35,# Palliative care cost
"Terminal illness" = 165293.35*0.5), # Terminal illness cost
## Swedish governmental report on organised PSA testing (p.23):
## https://www.socialstyrelsen.se/SiteCollectionDocuments/2018-2-13-halsoekonomisk-analys.pdf
## Swedish official statistics on mean salary for general population at working age
## https://www.scb.se/hitta-statistik/statistik-efter-amne/arbetsmarknad/loner-och-arbetskostnader/lonestrukturstatistik-hela-ekonomin/pong/tabell-och-diagram/genomsnittlig-manadslon-efter-sektor/
## Average working weekly working hours in Sweden 2019
## https://https://www.statista.com/statistics/528482/sweden-average-weekly-working-hours/
## Percentage of social and employee contribution on salary 37.00% for abetare
## https://www.ekonomifakta.se/Fakta/Skatter/Skatt-pa-arbete/Sociala-avgifter-over-tid/
## Exchange rate from SEK to EUR from the national bank
## https://www.riksbank.se/sv/statistik/sok-rantor--valutakurser/arsgenomsnitt-valutakurser/?y=2018&m=12&s=Comma&f=y
## Consumer price index
## https://www.scb.se/hitta-statistik/statistik-efter-amne/priser-och-konsumtion/konsumentprisindex/konsumentprisindex-kpi/pong/tabell-och-diagram/konsumentprisindex-kpi/kpi-faststallda-tal-1980100/
## Employment proportion
## http://www.statistikdatabasen.scb.se/pxweb/sv/ssd/START__AM__AM0401__AM0401A/NAKUBefolkning2Ar/?loadedQueryId=63385&timeType=from&timeValue=2001
## Updated to year 2020
production = data.frame(ages = c(0, 54, 64, 74),
values=apply(
rbind(0.884, 0.778, 0.186, 0), # employment portion, full time
1,
function(empl) empl*
29.2/40* # average working hours 2020
36100*12* # average salary 2020
1.3720)), # including non-optional social fees 2020
## Updated currency exchange rate
currency_rate = 1/10.4867, # Riksbanken 2020
## Updated test characteristics 2022-01-11 (based on logit transform)
pMRIposG0=0.184292645141448, # Pr(MRI+ | ISUP 0 || undetectable)
pMRIposG1=0.316652231007673, # Pr(MRI+ | ISUP 1 && detectable)
pMRIposG2=0.836863636375978, # Pr(MRI+ | ISUP 2+ && detectable)
pSBxG0ifG1=0.0632272407816892, # Pr(SBx gives ISUP 0 | ISUP 1)
pSBxG0ifG2=0.0990348918673406 # Pr(SBx gives ISUP 0 | ISUP 2)
))
if(year==2018) base2018 else (if(year==2019) base2019 else base2020)
}
## Update the background health state values using Burström (2001, for men in Sweden) - Previously Burström (2006, for general population in Stockholm)
ShuangTables <- list(background_utilities =
data.frame(lower=c(0, 20, 30, 40, 50, 60, 70, 80),
upper=c(20, 30, 40, 50, 60, 70, 80, 1.0e55),
utility=c(1, 0.91, 0.90, 0.86, 0.84, 0.83, 0.81, 0.74)))
## Code to compare results
compareParameters <- function(year1,year2) {
p1 = ShuangParameters(year1)
p2 = ShuangParameters(year2)
n1 = names(p1)
n2 = names(p2)
if (any(diff <- setdiff(n1,n2))) print(diff)
if (any(diff <- setdiff(n2,n1))) print(diff)
for (name in n1[n1 %in% n2]) {
if (length(p1[[name]]) != length(p2[[name]])) {
print(name)
cat("Different lengths:\n")
print(p1[[name]])
print(p2[[name]])
} else if(any(p1[[name]] != p2[[name]])) {
print(name)
cat("Differences:\n")
print(p1[[name]]-p2[[name]])
}
}
}
## compareParameters(2018,2019)
## compareParameters(2019,2020)
## ShuangParameters(2018)$cost_parameters
## ShuangParameters(2019)$cost_parameters
## ShuangParameters(2020)$cost_parameters
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