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Abstract:
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The decision to initiate treatment to prevent outcomes related to the development of cardiovascular disease, diabetes, depression and other chronic conditions is often based on subjects crossing a threshold of a diagnostic measurement taken on a continuous scale. Prevention studies designed to evaluate the risk of reaching those thresholds face numerous challenges. Along with the practical challenges of recruiting subjects at higher risk of crossing the threshold (population enrichment) and collecting measurements at multiple time points to immediately identify disease cases, there are statistical challenges related to the baseline distribution of subjects enrolled in the trial (potential for false negatives at screening) and the need to reduce the chance of subjects being incorrectly identified as disease cases (false positives at diagnosis). This work will evaluate the impact of various baseline distributional assumptions, single versus multiple diagnostic endpoints/criteria, the utility of confirmatory diagnostic measurements, and the use of absolute versus change from baseline diagnostic criteria on the ability to differentiate treatments with respect to disease progression.
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