Your statistical health consultancy CHM CRO TEMP WORK staying healthy getting healthy team health Forest Plots in Survival Subgroup Analyses
Agenda CRO – getting healthy Motivation ADTTE dummy data Macro for forest plots Summary Forest Plots in Survival Subgroup Analyses 1/12
Motivation CRO – getting healthy • Survival subgroup analysis, e.g. study from oncology Forest Plots in Survival Subgroup Analyses 2/12
Motivation CRO – getting healthy • Survival subgroup analysis, e.g. study from oncology • Effect of study drug vs. placebo: Hazard ratio (HR) and confidence interval (CI) Forest Plots in Survival Subgroup Analyses 2/12
Motivation CRO – getting healthy • Survival subgroup analysis, e.g. study from oncology • Effect of study drug vs. placebo: Hazard ratio (HR) and confidence interval (CI) • Comparing HRs and CIs among various subgroups Forest Plots in Survival Subgroup Analyses 2/12
Motivation CRO – getting healthy • Survival subgroup analysis, e.g. study from oncology • Effect of study drug vs. placebo: Hazard ratio (HR) and confidence interval (CI) • Comparing HRs and CIs among various subgroups à Forest plot Forest Plots in Survival Subgroup Analyses 2/12
Motivation CRO – getting healthy Simple example : 3/12 http://genometoolbox.blogspot.com/2014/06/easy-forest-plots-in-r.html
Motivation CRO – getting healthy • Many endpoints in the study (Death, Progression free survival, ...) Forest Plots in Survival Subgroup Analyses 4/12
Motivation CRO – getting healthy • Many endpoints in the study (Death, Progression free survival, ...) • Different confidence levels (e.g. 95% à 80%) Forest Plots in Survival Subgroup Analyses 4/12
Motivation CRO – getting healthy • Many endpoints in the study (Death, Progression free survival, ...) • Different confidence levels (e.g. 95% à 80%) • Stratification ( à different model) Forest Plots in Survival Subgroup Analyses 4/12
Motivation CRO – getting healthy • Many endpoints in the study (Death, Progression free survival, ...) • Different confidence levels (e.g. 95% à 80%) • Stratification ( à different model) • In our case: about 40 different forest plots Forest Plots in Survival Subgroup Analyses 4/12
Motivation CRO – getting healthy • Many endpoints in the study (Death, Progression free survival, ...) • Different confidence levels (e.g. 95% à 80%) • Stratification ( à different model) • In our case: about 40 different forest plots à Macro needed! Forest Plots in Survival Subgroup Analyses 4/12
Motivation CRO – getting healthy • Many endpoints in the study (Death, Progression free survival, ...) • Different confidence levels (e.g. 95% à 80%) • Stratification ( à different model) • In our case: about 40 different forest plots à Macro needed! • Macro: ADTTE data as input à Forest plot as output Forest Plots in Survival Subgroup Analyses 4/12
ADTTE dummy data CRO – getting healthy Ob Subject Gender Age BMI at Treatment Parameter Censor Analysis Analysis s identifier group baseline code variable value value unit 1 123450000 Female >= 85 < 25 Study drug PFS 0 301 Days 1 2 123450000 Female >= 85 < 25 Study drug DEATH 1 315 Days 1 3 123450004 Male 65-74 25-30 Placebo PFS 1 1 Days 2 4 123450004 Male 65-74 25-30 Placebo DEATH 1 1 Days 2 5 123450011 Male < 65 > 30 Study drug PFS 0 51 Days 4 6 123450011 Male < 65 > 30 Study drug DEATH 0 94 Days 4 7 123450021 Female 75-84 . Placebo PFS 0 23 Days 0 8 123450021 Female 75-84 . Placebo DEATH 1 23 Days 5/12 0
CRO – getting healthy Macro for forest plots %macro_forest_plot() Forest Plots in Survival Subgroup Analyses
CRO – getting healthy Requirements & layout: • CI level & endpoint apparent in the title 7/12
CRO – getting healthy Requirements & layout: • CI level & endpoint apparent in the title • HRs & CIs for each subgroup category + Subgroup size 7/12
CRO – getting healthy Requirements & layout: • CI level & endpoint apparent in the title • HRs & CIs for each subgroup category + Subgroup size • Survival data: Events & censored patients 7/12
CRO – getting healthy Requirements & layout: • CI level & endpoint apparent in the title • HRs & CIs for each subgroup category + Subgroup size • Survival data: Events & censored patients • Median survival times 7/12
CRO – getting healthy Requirements & layout: • CI level & endpoint apparent in the title • HRs & CIs for each subgroup category + Subgroup size • Survival data: Events & censored patients • Median survival times • Footnotes 7/12
CRO – getting healthy Requirements & layout: • CI level & endpoint apparent in the title • HRs & CIs for each subgroup category + Subgroup size • Survival data: Events & censored patients • Median survival times • Footnotes 7/12
CRO – getting healthy Requirements: Options • CI level & endpoint apparent in the title • HRs & CIs for each subgroup category + Subgroup size • Survival data: Events & censored patients • Median survival times • Footnotes 8/12
CRO – getting healthy Requirements: Options • CI level & endpoint apparent in the title • HRs & CIs for each PROC subgroup category PHREG + Subgroup size • Survival data: Events & censored patients • Median survival times • Footnotes 8/12
CRO – getting healthy Requirements: Options • CI level & endpoint apparent in the title • HRs & CIs for each PROC subgroup category PHREG + Subgroup size & • Survival data: Events PROC & censored patients LIFETEST • Median survival times • Footnotes 8/12
CRO – getting healthy Requirements: Options • CI level & endpoint apparent in the title • HRs & CIs for each PROC subgroup category PHREG + Subgroup size & • Survival data: Events PROC & censored patients LIFETEST • Median survival times • Footnotes Standard footnotes 8/12
CRO – getting healthy Requirements: Options • CI level & endpoint apparent in the title • HRs & CIs for each PROC subgroup category PHREG + Subgroup size & • Survival data: Events PROC & censored patients LIFETEST • Median survival times • Footnotes Standard footnotes 8/12
Main input: CRO – getting healthy ADTT E data Requirements: Options • CI level & endpoint apparent in the title • HRs & CIs for each PROC subgroup category PHREG + Subgroup size & • Survival data: Events PROC & censored patients LIFETEST • Median survival times • Footnotes Standard footnotes 8/12
Main input: CRO – getting healthy ADTT E data Requirements: Options • CI level & endpoint apparent in the title • HRs & CIs for each PROC subgroup category PHREG + Subgroup size & • Survival data: Events PROC & censored patients LIFETEST • Median survival times • Footnotes Standard footnotes 8/12
Main input: CRO – getting healthy ADTT E data Requirements: Options • CI level & endpoint apparent in the title • HRs & CIs for each PROC subgroup category PHREG Survival + Subgroup size & data • Survival data: Events PROC & censored patients LIFETEST • Median survival times • Footnotes Standard footnotes 8/12
Main input: CRO – getting healthy ADTT E data Requirements: Options • CI level & endpoint PROC apparent in the title SGPLOT • HRs & CIs for each PROC subgroup category PHREG Survival + Subgroup size & data • Survival data: Events PROC & censored patients LIFETEST • Median survival times • Footnotes Standard footnotes 8/12
Main input: CRO – getting healthy ADTT E data Requirements: Options • CI level & endpoint PROC apparent in the title SGPLOT • HRs & CIs for each PROC subgroup category PHREG Survival + Subgroup size & Forest data • Survival data: Events PROC plot with & censored patients LIFETEST title & • Median survival times table • Footnotes Standard footnotes 6/9
Main input: CRO – getting healthy ADTT E data Requirements: Options • CI level & endpoint PROC apparent in the title SGPLOT • HRs & CIs for each PROC subgroup category PHREG Survival + Subgroup size & Forest data • Survival data: Events PROC plot with & censored patients LIFETEST title, • Median survival times table & • Footnotes Standard footnotes footnotes 6/9
CRO – getting healthy Macro call – example 1: %macro_forest_plot( endpoint = pfs , ci_level = 95 , sgrp_vlst = sex agegr01n , sgrp_lbls = Gender~Age Group , footnote1 = Up to five additional footnotes (footnote1- footnote5) possible. ); 9/12
CRO – getting healthy Macro call – example 1: %macro_forest_plot( endpoint = pfs , ci_level = 95 , sgrp_vlst = sex agegr01n , sgrp_lbls = Gender~Age Group , footnote1 = Up to five additional footnotes (footnote1- footnote5) possible. ); 9/12
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