Background: Prevalence of disease phenotype in clinical practice is often not given adequate importance during formulation, validation, and implementation of diagnostic tests in clinical research and development. After promising biomarkers have been identified as potential screening diagnostics, an important strategic question for optimal decision-making in clinical development of a therapeutic is when to choose an enrichment study design over the traditional all-comer randomized control trial design.
Methods: A hypothetical example of a cholesterol lowering treatment is used to illustrate influences of key statistical criteria and clinical considerations for choosing study designs. Computer simulations demonstrate how results of such analyses can aid in deciding whether or not to choose enrichment study designs.
Results: This study shows how understanding of disease prevalence in practice, predictive values of diagnostic test, and prespecified establishment of a clinically meaningful minimum effectiveness all need to be integrated to insure clinical trial success and appropriate benefit to targeted patient subgroups. The most important statistical and clinical considerations were the anticipated effect size, phenotype prevalence, predictive values of diagnostics test, study power, and desired clinically meaningful difference.
Conclusions: This study illustrates how successful clinical studies can be designed with careful planning and utilization of computer simulations to increase not only the probability of trial success but also to demonstrate to payers convincing evidence of clinical effectiveness. A six-step checklist is recommended as an evidence-based guideline to assist in decision-making on whether or not to adopt a diagnostics enriched clinical study design.
Keywords: Clinical trial, biomarker, screening diagnostics, clinical effectiveness, personalized healthcare, stratified medicine, computer simulation