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tests/testthat/_snaps/response_biomarkers_subgroups.md
In tern: Create Common TLGs Used in Clinical Trials
extract_rsp_biomarkers functions as expected with valid input and default arguments
Code
res
Output
biomarker biomarker_label n_tot n_rsp prop or
1 AGE Age 200 164 0.8200000 0.9950509
2 BMRKR1 Continuous Level Biomarker 1 200 164 0.8200000 0.9765311
3 AGE Age 110 91 0.8272727 1.0082471
4 BMRKR1 Continuous Level Biomarker 1 110 91 0.8272727 0.9771788
5 AGE Age 90 73 0.8111111 0.9849219
6 BMRKR1 Continuous Level Biomarker 1 90 73 0.8111111 0.9720575
7 AGE Age 70 53 0.7571429 0.9348856
8 BMRKR1 Continuous Level Biomarker 1 70 53 0.7571429 1.1595718
9 AGE Age 68 58 0.8529412 0.9868318
10 BMRKR1 Continuous Level Biomarker 1 68 58 0.8529412 0.8793711
11 AGE Age 62 53 0.8548387 1.0700781
12 BMRKR1 Continuous Level Biomarker 1 62 53 0.8548387 0.8856737
lcl ucl conf_level pval pval_label subgroup var
1 0.9459879 1.046659 0.95 0.8474980 p-value (Wald) All Patients ALL
2 0.8819556 1.081248 0.95 0.6477107 p-value (Wald) All Patients ALL
3 0.9348405 1.087418 0.95 0.8313629 p-value (Wald) F SEX
4 0.8623205 1.107336 0.95 0.7174615 p-value (Wald) F SEX
5 0.9210816 1.053187 0.95 0.6567888 p-value (Wald) M SEX
6 0.8125165 1.162925 0.95 0.7566895 p-value (Wald) M SEX
7 0.8579986 1.018663 0.95 0.1241263 p-value (Wald) LOW BMRKR2
8 0.9578324 1.403802 0.95 0.1289696 p-value (Wald) LOW BMRKR2
9 0.8802767 1.106285 0.95 0.8201327 p-value (Wald) MEDIUM BMRKR2
10 0.7308739 1.058040 0.95 0.1731530 p-value (Wald) MEDIUM BMRKR2
11 0.9671640 1.183943 0.95 0.1892413 p-value (Wald) HIGH BMRKR2
12 0.7231318 1.084751 0.95 0.2405613 p-value (Wald) HIGH BMRKR2
var_label row_type
1 All Patients content
2 All Patients content
3 Sex analysis
4 Sex analysis
5 Sex analysis
6 Sex analysis
7 Continuous Level Biomarker 2 analysis
8 Continuous Level Biomarker 2 analysis
9 Continuous Level Biomarker 2 analysis
10 Continuous Level Biomarker 2 analysis
11 Continuous Level Biomarker 2 analysis
12 Continuous Level Biomarker 2 analysis
extract_rsp_biomarkers works as expected with other custom options
Code
res
Output
biomarker subgroup
4 AGE low
5 AGE low/medium
6 AGE low/medium/high
tabulate_rsp_biomarkers works as expected with valid input
Code
res
Output
Total n Responders Response (%) Odds Ratio 95% CI p-value (Wald)
—————————————————————————————————————————————————————————————————————————————————————————————————————————————————
Age
All Patients 200 164 82.0% 1.00 (0.95, 1.05) 0.8475
Sex
F 110 91 82.7% 1.01 (0.93, 1.09) 0.8314
M 90 73 81.1% 0.98 (0.92, 1.05) 0.6568
Continuous Level Biomarker 2
LOW 70 53 75.7% 0.93 (0.86, 1.02) 0.1241
MEDIUM 68 58 85.3% 0.99 (0.88, 1.11) 0.8201
HIGH 62 53 85.5% 1.07 (0.97, 1.18) 0.1892
Continuous Level Biomarker 1
All Patients 200 164 82.0% 0.98 (0.88, 1.08) 0.6477
Sex
F 110 91 82.7% 0.98 (0.86, 1.11) 0.7175
M 90 73 81.1% 0.97 (0.81, 1.16) 0.7567
Continuous Level Biomarker 2
LOW 70 53 75.7% 1.16 (0.96, 1.40) 0.1290
MEDIUM 68 58 85.3% 0.88 (0.73, 1.06) 0.1732
HIGH 62 53 85.5% 0.89 (0.72, 1.08) 0.2406
Code
res
Output
$col_x
[1] 4
$col_ci
[1] 5
$col_symbol_size
[1] 1
$forest_header
[1] "Lower\nBetter" "Higher\nBetter"
tabulate_rsp_biomarkers functions as expected with NULL subgroups
Code
res
Output
Total n Responders Response (%) Odds Ratio 95% CI p-value (Wald)
———————————————————————————————————————————————————————————————————————————————————————————————————————————————
Age
All Patients 200 164 82.0% 1.00 (0.95, 1.05) 0.8475
Continuous Level Biomarker 1
All Patients 200 164 82.0% 0.98 (0.88, 1.08) 0.6477
tabulate_rsp_biomarkers works with only a single biomarker in the data frame
Code
res
Output
Total n Responders Response (%) Odds Ratio 95% CI p-value (Wald)
———————————————————————————————————————————————————————————————————————————————————————————————————————————————
Continuous Level Biomarker 1
All Patients 400 282 70.5% 0.98 (0.95, 1.01) 0.3000
tabulate_rsp_biomarkers na_str argument works as expected
Code
res
Output
Total n Responders Response (%) Odds Ratio 95% CI p-value (Wald)
—————————————————————————————————————————————————————————————————————————————————————————————————————————————————
Age
All Patients 200 164 82.0% 1.00 (0.95, 1.05) 0.8475
Sex
F 110 91 82.7% <No data> (0.93, 1.09) 0.8314
M 90 73 81.1% <No data> (0.92, 1.05) 0.6568
Continuous Level Biomarker 2
LOW 70 53 75.7% 0.93 (0.86, 1.02) 0.1241
MEDIUM 68 58 85.3% 0.99 (0.88, 1.11) 0.8201
HIGH 62 53 85.5% 1.07 (0.97, 1.18) 0.1892
Continuous Level Biomarker 1
All Patients 200 164 82.0% <No data> (0.88, 1.08) 0.6477
Sex
F 110 91 82.7% <No data> (0.86, 1.11) 0.7175
M 90 73 81.1% 0.97 (0.81, 1.16) 0.7567
Continuous Level Biomarker 2
LOW 70 53 75.7% 1.16 (0.96, 1.40) 0.1290
MEDIUM 68 58 85.3% 0.88 (0.73, 1.06) 0.1732
HIGH 62 53 85.5% 0.89 (0.72, 1.08) 0.2406
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extract_rsp_biomarkers functions as expected with valid input and default arguments
Code
res
Output
biomarker biomarker_label n_tot n_rsp prop or
1 AGE Age 200 164 0.8200000 0.9950509
2 BMRKR1 Continuous Level Biomarker 1 200 164 0.8200000 0.9765311
3 AGE Age 110 91 0.8272727 1.0082471
4 BMRKR1 Continuous Level Biomarker 1 110 91 0.8272727 0.9771788
5 AGE Age 90 73 0.8111111 0.9849219
6 BMRKR1 Continuous Level Biomarker 1 90 73 0.8111111 0.9720575
7 AGE Age 70 53 0.7571429 0.9348856
8 BMRKR1 Continuous Level Biomarker 1 70 53 0.7571429 1.1595718
9 AGE Age 68 58 0.8529412 0.9868318
10 BMRKR1 Continuous Level Biomarker 1 68 58 0.8529412 0.8793711
11 AGE Age 62 53 0.8548387 1.0700781
12 BMRKR1 Continuous Level Biomarker 1 62 53 0.8548387 0.8856737
lcl ucl conf_level pval pval_label subgroup var
1 0.9459879 1.046659 0.95 0.8474980 p-value (Wald) All Patients ALL
2 0.8819556 1.081248 0.95 0.6477107 p-value (Wald) All Patients ALL
3 0.9348405 1.087418 0.95 0.8313629 p-value (Wald) F SEX
4 0.8623205 1.107336 0.95 0.7174615 p-value (Wald) F SEX
5 0.9210816 1.053187 0.95 0.6567888 p-value (Wald) M SEX
6 0.8125165 1.162925 0.95 0.7566895 p-value (Wald) M SEX
7 0.8579986 1.018663 0.95 0.1241263 p-value (Wald) LOW BMRKR2
8 0.9578324 1.403802 0.95 0.1289696 p-value (Wald) LOW BMRKR2
9 0.8802767 1.106285 0.95 0.8201327 p-value (Wald) MEDIUM BMRKR2
10 0.7308739 1.058040 0.95 0.1731530 p-value (Wald) MEDIUM BMRKR2
11 0.9671640 1.183943 0.95 0.1892413 p-value (Wald) HIGH BMRKR2
12 0.7231318 1.084751 0.95 0.2405613 p-value (Wald) HIGH BMRKR2
var_label row_type
1 All Patients content
2 All Patients content
3 Sex analysis
4 Sex analysis
5 Sex analysis
6 Sex analysis
7 Continuous Level Biomarker 2 analysis
8 Continuous Level Biomarker 2 analysis
9 Continuous Level Biomarker 2 analysis
10 Continuous Level Biomarker 2 analysis
11 Continuous Level Biomarker 2 analysis
12 Continuous Level Biomarker 2 analysis
extract_rsp_biomarkers works as expected with other custom options
Code
res
Output
biomarker subgroup
4 AGE low
5 AGE low/medium
6 AGE low/medium/high
tabulate_rsp_biomarkers works as expected with valid input
Code
res
Output
Total n Responders Response (%) Odds Ratio 95% CI p-value (Wald)
—————————————————————————————————————————————————————————————————————————————————————————————————————————————————
Age
All Patients 200 164 82.0% 1.00 (0.95, 1.05) 0.8475
Sex
F 110 91 82.7% 1.01 (0.93, 1.09) 0.8314
M 90 73 81.1% 0.98 (0.92, 1.05) 0.6568
Continuous Level Biomarker 2
LOW 70 53 75.7% 0.93 (0.86, 1.02) 0.1241
MEDIUM 68 58 85.3% 0.99 (0.88, 1.11) 0.8201
HIGH 62 53 85.5% 1.07 (0.97, 1.18) 0.1892
Continuous Level Biomarker 1
All Patients 200 164 82.0% 0.98 (0.88, 1.08) 0.6477
Sex
F 110 91 82.7% 0.98 (0.86, 1.11) 0.7175
M 90 73 81.1% 0.97 (0.81, 1.16) 0.7567
Continuous Level Biomarker 2
LOW 70 53 75.7% 1.16 (0.96, 1.40) 0.1290
MEDIUM 68 58 85.3% 0.88 (0.73, 1.06) 0.1732
HIGH 62 53 85.5% 0.89 (0.72, 1.08) 0.2406
Code
res
Output
$col_x
[1] 4
$col_ci
[1] 5
$col_symbol_size
[1] 1
$forest_header
[1] "Lower\nBetter" "Higher\nBetter"
tabulate_rsp_biomarkers functions as expected with NULL subgroups
Code
res
Output
Total n Responders Response (%) Odds Ratio 95% CI p-value (Wald)
———————————————————————————————————————————————————————————————————————————————————————————————————————————————
Age
All Patients 200 164 82.0% 1.00 (0.95, 1.05) 0.8475
Continuous Level Biomarker 1
All Patients 200 164 82.0% 0.98 (0.88, 1.08) 0.6477
tabulate_rsp_biomarkers works with only a single biomarker in the data frame
Code
res
Output
Total n Responders Response (%) Odds Ratio 95% CI p-value (Wald)
———————————————————————————————————————————————————————————————————————————————————————————————————————————————
Continuous Level Biomarker 1
All Patients 400 282 70.5% 0.98 (0.95, 1.01) 0.3000
tabulate_rsp_biomarkers na_str argument works as expected
Code
res
Output
Total n Responders Response (%) Odds Ratio 95% CI p-value (Wald)
—————————————————————————————————————————————————————————————————————————————————————————————————————————————————
Age
All Patients 200 164 82.0% 1.00 (0.95, 1.05) 0.8475
Sex
F 110 91 82.7% <No data> (0.93, 1.09) 0.8314
M 90 73 81.1% <No data> (0.92, 1.05) 0.6568
Continuous Level Biomarker 2
LOW 70 53 75.7% 0.93 (0.86, 1.02) 0.1241
MEDIUM 68 58 85.3% 0.99 (0.88, 1.11) 0.8201
HIGH 62 53 85.5% 1.07 (0.97, 1.18) 0.1892
Continuous Level Biomarker 1
All Patients 200 164 82.0% <No data> (0.88, 1.08) 0.6477
Sex
F 110 91 82.7% <No data> (0.86, 1.11) 0.7175
M 90 73 81.1% 0.97 (0.81, 1.16) 0.7567
Continuous Level Biomarker 2
LOW 70 53 75.7% 1.16 (0.96, 1.40) 0.1290
MEDIUM 68 58 85.3% 0.88 (0.73, 1.06) 0.1732
HIGH 62 53 85.5% 0.89 (0.72, 1.08) 0.2406
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