Planning and Monitoring Equitable Clinical Trial Enrollment Using Goal Programming

Insights

This study introduces a goal-programming approach to create equitable enrollment plans for clinical trials. The model ensures diverse patient representation, improving the generalizability of treatment benefits across all populations.

Area of Science:

  • Clinical Trials Methodology
  • Health Equity Research
  • Health Services Research

Background:

  • Randomized clinical trials (RCTs) are crucial for evaluating treatment efficacy but often lack diverse patient representation.
  • Enrollment plans may underrepresent patient groups with protected attributes (gender, race, ethnicity), limiting generalizability.
  • Ensuring equitable participation in clinical trials is a key concern for major health organizations and policymakers.

Purpose of the Study:

  • To propose a novel goal-programming approach for designing equitable enrollment plans in randomized clinical trials.
  • To integrate measurable enrollment goals addressing patient representativeness and cost-efficiency.
  • To enhance the validity of scientific analysis and subgroup disparity evaluations.

Main Methods:

  • Developed a goal-programming model to create equitable enrollment plans for RCTs.
  • Evaluated the model using enrollment data from the Systolic Blood Pressure Intervention Trial (SPRINT).
  • Assessed model performance in single and multisite trial settings, including site selection strategies.

Main Results:

  • The model successfully generated equitable enrollment plans satisfying multiple objectives, including sample representativeness and cost.
  • The approach demonstrated the ability to detect and correct deviations from enrollment targets during the trial.
  • Site selection strategies within the model showed potential for achieving nationally representative study populations.

Conclusions:

  • The proposed goal-programming model offers a robust method for prospectively designing and retrospectively evaluating equitable RCT enrollment.
  • This approach can improve the generalizability of trial findings and support the analysis of subgroup disparities.
  • Implementing such models can lead to more inclusive and representative clinical research, ultimately benefiting diverse patient populations.

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