Moving Forward. Adaptive Eligibility Criteria, Alternate Trial Designs, and Subgroup Analysis. Elizabeth Garrett-Mayer, PhD

Transcription

1 Moving Forward Adaptive Eligibility Criteria, Alternate Trial Designs, and Subgroup Analysis Elizabeth Garrett-Mayer, PhD

2 Eligibility Trade-offs Broad eligibility Pros: Heterogeneous group Can generalize to large populations Faster accrual Cons More variability in outcomes May require larger sample size Inferences may not actually apply to entire target population Narrow eligibility Pros Homogeneous group Relatively small variance in outcomes Inferences are more precise Small sample size is sufficient Cons Cannot generalize Slow accrual

3 Refresher: Adaptive trials FDA s draft guidance on adaptive designs in drug development (Feb 2010) Robert T. O Neill, PhD / OTS, CDER, FDA, an adaptive design clinical study is defined as a study that includes a prospectively planned and specified modification or potential for modification of one or more specified aspects of the study design and hypotheses, based on analysis of data from subjects in the study. Analyses of the accumulating study data are often performed at prospectively planned points within the study, may be performed in a fully blinded manner or in a non-blinded manner, The term prospective here means that the adaptation was planned before data were examined in an unblinded form by any personnel involved in planning for the revision. Revisions made or proposed after an unblinded interim analysis raise major concerns about study integrity, possible design changes need to be prospectively defined and carefully implemented to avoid risking irresolvable uncertainty in the interpretation of study results.

4 Adaptive trial approaches: Key Ideas Pre-planned Decision rules, outcomes, and methods are clearly defined Adaptations planned before data are observed

5 Novel ideas (Large) expansion cohorts in early phase dose finding trials Allow subgroup evaluations for safety and/or efficacy Have developed in recent years with large cohort sizes Independent monitoring committees DSMCs common in large randomized efficacy trials New role in early phase studies with large numbers of patients Adaptations based on toxicity signals. (More than just safety stopping ) Coinage of term seamless development Implies adaptive-hybrid approach. Use knowledge gained to allow protocol to evolve over time.

6 Independent monitoring committees for guiding expansion cohorts Still a somewhat vague notion: no trial has enacted one (right?) Prowell et al, NEJM; 13 Apr 2016, in the context of large dose finding studies for FIH trials: The use of an independent data and safety monitoring committee whose role is to review clinical trial data and make recommendations regarding changes to the trial s conduct may also provide important quality control.in a multiple-expansion cohort trial, such a committee would take scheduled pauses to review safety and efficacy data from existing cohorts, advise investigators about the addition or closure of cohorts, provide external transparency, and ensure the trial s statistical integrity Much broader role than traditional DSMB. Must be incredibly familiar with patient population yet not conflicted with the study Still statistically risky to make game time decisions on what to do next.

7 Not novel ideas Cohorts should be pre-defined in some way Either cohort population is pre-defined Or, method for defining/selecting population is pre-defined Guidelines for expanding/contracting should be outlined Sample sizes for signal should have some justification Common wisdom says cohort size >20 should have accompanying statistical justification Bayesian approaches: Complex in the planning Often logical for adding/removing subgroups in an adaptive design.

8 Phase of study Recommendations by phase? Will the same recommendations apply in early vs. late phase trials? Dose finding: broad population, pre-treated patients, exploratory objectives, lots of unknowns, Large randomized trial: narrower population, focused question, fewer unknowns (but in narrower population) Dose finding followed by expansions in subgroups a logical place for exploring safety and efficacy. (Phase 1.5) Lots of work has been done to address subgroups in the context of (predefined) biomarkers. Leveraging that work may help.

9 Biomarker-based study designs Note that study design will depend on primary outcome. Designs developed based on efficacy, but could apply to safety outcomes. Translational Cancer Research, 2014

10 Example: Interaction design for comparative trial Biomarker design Stratification by HIV status Biomarker + Randomization Standard Treatment HIV+ Randomization Standard Treatment Biomarker Designation Biomarker - Randomization Standard Treatment HIV status HIV- Randomization Standard Treatment

11 Similarly for single arm (i.e. earlier phase) trials Objectives and outcomes need to be defined clearly Does a sample size maximum or minimum need to be defined in subgroups? What statistical power will there be to evaluate subgroups? Do we even want to power the subgroups? Would hierarchical designs ( borrowing strength across groups ) help in this context? Both safety and efficacy can be incorporated as outcomes.

12 Take-home points How and when to include these subpopulations in trials depends: Prevalence of subgroup in larger population Anticipated risk-level of intervention Phase of study Other options for patients Prognosis Level of evidence desired (i.e., how the objectives are posed) Engage your statisticians early and often.