Evaluation of Treatment Effect with Paired Failure Times in a Single-Arm Phase II Trial in Oncology

Matthieu Texier1, Federico Rotolo1,2, Michel Ducreux3

  • 1Biostatistics and Epidemiology Unit, Gustave Roussy, Université Paris-Saclay, 94805 Villejuif, France.

Insights

This study compares methods for evaluating cancer drug efficacy using the growth modulation index (GMI). The nonparametric method is recommended for its robustness, though the parametric approach offers supplementary insights.

Area of Science:

  • Oncology
  • Clinical Trial Design
  • Biostatistics

Background:

  • Traditional tumor shrinkage metrics are insufficient for cytostatic cancer drugs.
  • Alternative endpoints like the growth modulation index (GMI) are needed for early-phase trials.

Purpose of the Study:

  • To compare parametric and nonparametric methods for estimating the rate of patients achieving a GMI above a threshold in single-arm phase II trials.
  • To evaluate the impact of design parameters on these estimation methods.

Main Methods:

  • Investigated a parametric method using time-to-progression distributions.
  • Employed a nonparametric method utilizing a midrank estimator.
  • Conducted simulations to assess operating characteristics and parameter impacts (censoring, dependence, distribution).

Main Results:

  • The nonparametric estimator showed slight underestimation of the rate and conservative confidence intervals.
  • The parametric estimator tended to overestimate the rate and produced anticonservative confidence intervals.
  • The nonparametric method demonstrated greater robustness to censoring.

Conclusions:

  • The nonparametric method is recommended for estimating GMI-based treatment effects due to its robustness.
  • The parametric method can serve as a supplementary tool in specific contexts.

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