Adjusting for treatment switching in randomised controlled trials - A simulation study and a simplified two-stage
Nicholas R Latimer1, K R Abrams2, P C Lambert2,3
11 School of Health and Related Research, University of Sheffield, Sheffield, UK.
Statistical Methods in Medical Research
|November 23, 2014
Summary
Estimating cancer treatment benefits requires adjusting for treatment switching in clinical trials. A simplified two-stage Weibull method shows promise for accurate survival benefit estimation across various scenarios.
Area of Science:
- Biostatistics
- Clinical Trials
- Health Technology Assessment
Background:
- Treatment switching in randomized controlled trials (RCTs) confounds overall survival benefit estimates.
- Accurate estimates of unconfounded survival benefits are crucial for health technology assessment.
- Existing switching adjustment methods' performance in realistic scenarios is unclear.
Purpose of the Study:
- To evaluate the bias of different statistical methods for adjusting treatment switching in RCTs.
- To identify the most reliable method for estimating true overall survival benefit in the presence of switching.
- To compare method performance under varying conditions like treatment effect time-dependency and switching proportions.
Main Methods:
- Simulation of RCTs with treatment switching based on patient prognosis.
- Systematic variation of parameters: treatment effect size, time-dependency, switching proportions, and disease severity.
- Assessment of adjustment methods using bias, coverage, and mean squared error against true restricted mean survival.
Main Results:
- Rank preserving structural failure time models (RPSFTM) and iterative methods showed low bias for non-time-dependent treatment effects.
- These methods exhibited higher bias with time-dependent effects, similar to inverse probability of censoring weights (IPCW).
- IPCW and structural nested models showed high bias when switching proportions exceeded 85%.
Conclusions:
- A simplified two-stage Weibull method demonstrated low bias across all simulated scenarios.
- This method is a suitable adjustment approach when the treatment switching mechanism is appropriate.
- Careful selection of adjustment methods is vital for reliable survival benefit estimation in cancer clinical trials.
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