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Dynamic borrowing methods for basket trials with order restrictions.

Lauren Kanapka1, Anastasia Ivanova1

  • 1Department of Biostatistics, The University of North Carolina, Chapel Hill, NC, USA.

Journal of Biopharmaceutical Statistics
|April 2, 2026
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Summary
This summary is machine-generated.

Order-restricted methods for basket trials can reduce sample sizes by 10% when response order assumptions hold. However, these methods risk inflated type 1 error rates and reduced power if assumptions are violated.

Keywords:
Basket trialsBayesian model averagingadaptive lassodynamic borrowingorder restricted inference

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Area of Science:

  • Biostatistics
  • Clinical Trial Design
  • Pharmacology

Background:

  • Basket trials evaluate new therapies across multiple patient subgroups (baskets) under a single protocol.
  • Subgroups can be defined by disease type, biomarkers, or patient characteristics.
  • Prior knowledge of response order between baskets can inform trial design.

Purpose of the Study:

  • To modify existing dynamic borrowing methods for single-arm basket trials with binary endpoints.
  • To incorporate known response order information between baskets.
  • To assess the impact of order-restricted methods on sample size and statistical performance.

Main Methods:

  • Modification of two previously published dynamic borrowing methods.
  • Incorporation of known response order assumptions between baskets.
  • Evaluation of statistical properties including sample size, type 1 error rate, and power.

Main Results:

  • Order-restricted methods require marginally smaller sample sizes (approx. 10% reduction for a five-basket trial) when order assumptions are met.
  • When order assumptions hold and the study is adequately powered, these methods are efficient.
  • Violations of order assumptions lead to inflated type 1 error rates and reduced power.

Conclusions:

  • Incorporating known response orders into dynamic borrowing methods can improve sample size efficiency in basket trials.
  • Careful consideration of order assumptions is crucial, as violations can negatively impact trial validity.
  • These modified methods offer a potential advantage when prior biological or clinical information supports response order.