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Estimating cure proportion in cancer clinical trials using flexible parametric cure models
Yuka Sano1, Shiro Tanaka2, Tosiya Sato3
1Data Science Department, National Cerebral and Cardiovascular Center, Osaka, Japan. sano.yuka@ncvc.go.jp.
BJC Reports
|November 8, 2024
Summary
Estimating cancer cure proportion requires careful cure model selection. Flexible parametric cure models can be sensitive to knot placement, impacting cure estimates in clinical trials.
Area of Science:
- Biostatistics
- Clinical Trials
- Cancer Research
Background:
- Estimating the cure proportion is crucial in cancer clinical trials.
- Cure models implicitly define a cure point, but its impact on estimates is unclear.
Purpose of the Study:
- To assess the sensitivity of cure proportion estimates to knot placement in flexible parametric cure models.
- To evaluate model performance and cure point determination using simulation.
Main Methods:
- Utilized data from the CheckMate 141 immuno-oncology clinical trial.
- Examined knot number and placement in flexible parametric cure models.
- Conducted a simulation study to evaluate model performance.
Main Results:
- The last knot's position significantly impacted cure proportion estimates and model fit.
- Placing the last knot at the last observed event time led to overestimation.
- Bias was reduced by placing the last knot later.
Conclusions:
- Flexible parametric cure models offer an alternative to the Kaplan-Meier method for cure proportion estimation.
- Careful consideration of cure point placement is essential for accurate estimates.
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