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Blinding is a commonly used method of not telling participants which treatment a subject is receiving. Blinding is a critical part of a randomized control trial or RCT. It reduces the bias that affects the results. In an RCT, blinding is used in the form of a placebo. A placebo effect occurs when untreated subjects falsely believe they have received the treatment and report improved symptoms. A placebo or a dummy treatment is administered to subjects to negate the bias caused by such an effect.
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The principal stratum strategy offers a robust method for estimating causal treatment effects in specific patient groups, particularly when dealing with intercurrent events like anti-drug antibodies in biosimilar trials. This approach addresses biases inherent in traditional subgroup analyses.

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Area of Science:

  • Biostatistics
  • Clinical Trial Methodology
  • Pharmacovigilance

Background:

  • The ICH E9 (R1) Addendum introduced the estimand framework to refine research questions in clinical trials.
  • Intercurrent events (ICE) require specific strategies for accurate treatment effect estimation.
  • Traditional subgroup analyses based on post-randomization variables like immunogenicity can introduce bias.

Purpose of the Study:

  • To examine the principal stratum strategy for estimating causal treatment effects in specific subpopulations.
  • To address the challenges of using post-randomization variables, such as anti-drug antibodies (ADAs), as intercurrent events.
  • To demonstrate the implementation of the principal stratum strategy in a biosimilar trial.

Main Methods:

  • Utilized the principal stratum strategy, leveraging counterfactuals and a missing data perspective.
  • Applied a multiple imputation approach with longitudinal measurements.
  • Implemented the strategy in a Phase 3 equivalence trial for a rheumatoid arthritis biosimilar.

Main Results:

  • The principal stratum strategy enables estimation of treatment effects in subpopulations defined by intercurrent events.
  • Demonstrated a method to create analysis datasets for subpopulations with ADAs as ICE.
  • Highlighted the strategy's reliance on unobserved states and the need for complex modeling.

Conclusions:

  • The principal stratum strategy provides a statistically sound pathway for estimating causal effects in specific subpopulations affected by intercurrent events.
  • This method offers an alternative to biased subgroup analyses for variables like immunogenicity.
  • Successful implementation requires rigorous modeling and careful consideration of assumptions regarding unobserved states.