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Updated: Jun 29, 2025

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Derivative survival analyses: Analysis methods to derive survival outcomes for the remainder patient cohort without
1Robert H. Lurie Comprehensive Cancer Center of Northwestern University, Chicago, IL, USA; Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
Abstract:
It is not uncommon for industry-sponsored randomized controlled trials to publish survival curves/data for the overall patient cohort("A+B") and for a favorable subgroup ("A") pre-specified or post hoc, but not the survival curves/data for the remainder cohort("B"). Consequently, following regulatory approval of the intervention treatment for the overall patient population if the primary endpoint is met, it is common for cancer patients representing the remainder cohort (B) to be treated as per the results of the overall cohort (A+B). To overcome this important issue in clinical decision-making, this study aimed to identify methods to accurately derive the survival curves and/or hazard ratio (95% confidence interval) for the remainder cohort (B), utilizing published curves and hazard ratios (95% confidence intervals) of the overall (A+B) and favorable subgroup (A) cohorts. The analysis methods (method I and method II) presented here, termed "derivative survival analyses," enable accurate assessment of survival outcomes in the remainder cohort without individual patient data.
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