The lack of statistical theory for the planning of early detection trials has resulted in current trials being sub-optimal. We develop probability models that address three characteristics of early detection trials: (i) the optimal time of analysis and length of follow-up; (ii) the optimal spacing between examinations; and (iii) the planning of trials where the numbers of examinations versus sample size are balanced for fixed costs. The optimization criterion is to maximize the power of the statistical test for comparing mortality. The theory will be utilized to evaluate the benefit of early detection of disease combined with treatment as well as to review current breast trials.

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