Perils of Randomized Controlled Trial Survival Extrapolation Assuming Treatment Effect Waning: Why the Distinction Between Marginal and Conditional Estimates Matters [Editor's Choice]

Mar 1, 2024, 00:00 AM
10.1016/j.jval.2023.12.008
https://www.valueinhealthjournal.com/article/S1098-3015(23)06241-1/fulltext
Section Title : METHODOLOGY
Section Order : 347
First Page : 347

Objectives

A long-term, constant, protective treatment effect is a strong assumption when extrapolating survival beyond clinical trial follow-up; hence, sensitivity to treatment effect waning is commonly assessed for economic evaluations. Forcing a hazard ratio (HR) to 1 does not necessarily estimate loss of individual-level treatment effect accurately because of HR selection bias. A simulation study was designed to explore the behavior of marginal HRs under a waning conditional (individual-level) treatment effect and demonstrate bias in forcing a marginal HR to 1 when the estimand is “survival difference with individual-level waning”.

Methods

Data were simulated under 4 parameter combinations (varying prognostic strength of heterogeneity and treatment effect). Time-varying marginal HRs were estimated in scenarios where the true conditional HR attenuated to 1. Restricted mean survival time differences, estimated having constrained the marginal HR to 1, were compared with true values to assess bias induced by marginal constraints.

Results

Under loss of conditional treatment effect, the marginal HR took a value >1 because of covariate imbalances. Constraining this value to 1 lead to restricted mean survival time difference bias of up to 0.8 years (57% increase). Inflation of effect size estimates also increased with the magnitude of initial protective treatment effect.

Conclusions

Important differences exist between survival extrapolations assuming marginal versus conditional treatment effect waning. When a marginal HR is constrained to 1 to assess efficacy under individual-level treatment effect waning, the survival benefits associated with the new treatment will be overestimated, and incremental cost-effectiveness ratios will be underestimated.

https://www.valueinhealthjournal.com/action/showCitFormats?pii=S1098-3015(23)06241-1&doi=10.1016/j.jval.2023.12.008
HEOR Topics :
  • Decision Modeling & Simulation
  • Methodological & Statistical Research
  • Modeling and simulation
  • Oncology
  • Specific Diseases & Conditions
  • Study Approaches
Tags :
  • efficacy waning
  • hazard ratio noncollapsability
  • health technology assessment
  • survival extrapolation
  • treatment effect waning
Regions :
  • North America