A framework for prospectively defining progression rules for internal pilot studies monitoring recruitment

Lisa V Hampson1,2, Paula R Williamson3, Martin J Wilby4

  • 11 Department of Mathematics and Statistics, Medical and Pharmaceutical Statistics Research Unit, Lancaster University, Lancaster, UK.

Insights

Many clinical trials fail to meet recruitment targets, risking underpowered results. This study introduces a framework for internal pilot studies with pre-specified progression rules to optimize trial planning and resource allocation.

Area of Science:

  • Clinical Trial Design
  • Biostatistics
  • Health Services Research

Background:

  • Publicly funded trials frequently miss recruitment targets within planned durations.
  • Missed recruitment can lead to decisions about extending funding or facing underpowered analyses.
  • Current feasibility assessments and progression rules are often ad hoc and lack criteria for evaluating recruitment strategy adaptations.

Purpose of the Study:

  • To develop a framework for planning and designing internal pilot studies.
  • To enable early trial termination for poor recruitment or continuation for adequate enrolment.
  • To establish pre-specified, optimal progression rules for internal pilot studies.

Main Methods:

  • Development of a novel two-stage design for internal pilot studies.
  • Derivation of optimal progression rules to minimize expected trial overrun.
  • Incorporation of criteria for evaluating the success of recruitment strategy adaptations.

Main Results:

  • The proposed framework allows for pre-specified progression rules agreed upon before trial commencement.
  • It provides a method to stop trials early if recruitment is insufficient or continue if adequate.
  • The framework includes evaluating recruitment adaptations when initial progress is neither sufficient nor insufficient.

Conclusions:

  • The developed framework offers a structured approach to internal pilot studies, improving trial planning and efficiency.
  • Optimal progression rules minimize delays and maximize the probability of successful study completion.
  • This methodology addresses the need for robust, pre-specified criteria in clinical trial recruitment and adaptation.

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