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Statistical design for a confirmatory trial with a continuous predictive biomarker: A case study.

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Summary

Designing confirmatory trials for targeted therapies is challenging with continuous biomarkers. A novel biomarker sequential testing approach effectively identifies responsive subpopulations, outperforming other methods in simulations.

Keywords:
Biomarker cutoff selectionClinical trial optimizationGroup-sequential designMultiplicityPersonalized medicineSubgroup identification

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Area of Science:

  • Clinical trial design
  • Biostatistics
  • Translational medicine

Background:

  • Targeted therapies often exhibit efficacy in specific subpopulations defined by biomarker activation.
  • Designing confirmatory trials is complex when biomarkers have continuous values and pre-clinical data is strong but clinical data is limited.
  • Interim evaluations of biomarker-defined subpopulations add further design complexity.

Purpose of the Study:

  • To compare different strategies for designing confirmatory trials for targeted therapies with continuous biomarkers.
  • To evaluate a novel biomarker sequential testing approach against existing methods.
  • To provide guidance for future clinical trial designs involving novel targeted therapies.

Main Methods:

  • Comparison of several trial design strategies: a naive threshold nomination approach, a modified "explore and confirm" strategy, and a novel biomarker sequential testing approach.
  • Utilizing simulations to evaluate strategy performance under conditions with limited prior information for biomarker threshold determination.
  • Considering interim analyses for both all-comers and biomarker-defined subpopulations.

Main Results:

  • The novel biomarker sequential testing approach demonstrated superior performance compared to other strategies.
  • This outperformance was particularly evident when limited prior information was available for determining the biomarker threshold.
  • The proposed design was successfully implemented in a clinical trial for simtuzumab (RAINIER study).

Conclusions:

  • The novel biomarker sequential testing approach is a robust and effective strategy for designing confirmatory trials of targeted therapies with continuous biomarkers.
  • This method offers advantages when biomarker thresholds are not well-defined pre-clinically.
  • The successful implementation in the RAINIER study serves as a valuable case study for future trial designs.