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A comprehensive algorithm for determining whether a run-in strategy will be a cost-effective design modification in a
1Washington University School of Medicine, Division of Biostatistics, St. Louis, MO 63110.
Statistics in Medicine
|January 30, 1993
Summary
Implementing a run-in strategy in clinical trials can reduce costs and sample size, but its cost-effectiveness is stringent. Run-ins are most beneficial when excluding non-compliant or intolerant patients significantly improves trial outcomes.
Area of Science:
- Clinical Trials Methodology
- Health Economics
- Biostatistics
Background:
- Poor compliance and treatment intolerance in randomized clinical trials (RCTs) increase sample size requirements and costs.
- Run-in strategies are employed to mitigate these issues before patient randomization.
Purpose of the Study:
- To develop measures to assess the impact of run-in strategies on trial cost and sample size.
- To provide an algorithm for estimating the cost-effectiveness of run-in strategies in RCTs.
Main Methods:
- Development of specific measures sensitive to run-in effects on cost and sample size.
- Step-by-step algorithm for cost-effectiveness estimation.
- Analysis of factors influencing run-in cost-effectiveness, including per-patient costs, compliance impact, screening efficiency, and subject exclusion criteria.
Main Results:
- Run-in strategies are most cost-effective under specific conditions: high post-randomization costs, significant impact of poor compliance on response, low number of screened patients per eligible patient, inexpensive run-in, sustained compliance post-run-in, and exclusion of a substantial number of intolerant/non-compliant subjects.
- The conditions for cost-effectiveness are stringent, and run-ins may increase costs if their sole purpose is to exclude partial compliers.
Conclusions:
- Run-in strategies can enhance trial efficiency but require careful consideration of specific conditions for cost-effectiveness.
- Identifying and excluding a significant proportion of treatment-intolerant or non-responsive subjects is crucial for the economic viability of run-in strategies in RCTs.