Abstract
In clinical trials, power calculation is often performed based on a single primary endpoint to determine sample size required for achieving study objective with a desired power at a pre-specified level of significance. In practice, power calculation based on a single primary endpoint has been criticized. First, how to select the single primary endpoint among a group of primary endpoints? Second, a single primary endpoint may not be sufficient to adequately inform complex cohorts, the disease status and/or treatment effect of the test treatment under investigation. Third, different study endpoints with different data types (e.g., continuous versus binary response) may result in different sample sizes. In addition, with a given sample size, some (single) endpoints may achieve the study objective while others fail to do so. In this opinion article, a conceptual innovation is the development of a therapeutic index that fully utilizes information from all relevant study endpoints proposed.
Highlights
Power analysis for sample size calculation is often performed based on a single primary study endpoint, a co-primary endpoint, or a composite endpoint for determining a sample size required for achieving the study objective with a desired power at a pre-specified level of significance
The selected single primary endpoint may be highly related to other endpoints which are not selected as the primary endpoint for the intended trial
Concluding Remarks about 32% (18 out of 57) of oncology regulatory submissions were approved based on a survival endpoint
Summary
Power analysis for sample size calculation (power calculation) is often performed based on a single primary study endpoint, a co-primary endpoint, or a composite endpoint for determining a sample size required for achieving the study objective with a desired power at a pre-specified level of significance. For (statistical) convenience sake, a single primary endpoint is often selected for power calculation. The selected single primary endpoint may be highly related to other endpoints which are not selected as the primary endpoint for the intended trial These endpoints carry more or less valuable information regarding safety and effectiveness of the test treatment under investigation. We may put patients at greater risk or withhold potentially beneficial interventions, due to the inherent flaw of single endpoint selection This opinion article intends to address these dilemmas by proposing the development of an index which can utilize information collected from all relevant study endpoints for a more accurate and reliable assessment of the safety and effectiveness of the test treatment under investigation. Some concluding remarks are given in the last section of this article
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