The article by Ronald J Feise discusses the need for p-value adjustment in clinical trials when multiple outcome measures (MOMs) are used. The primary aim is to evaluate whether p-value adjustments are necessary to compensate for the increased risk of Type I errors (false positives) when testing multiple hypotheses simultaneously. The author presents two perspectives: the classic view, which advocates for p-value adjustments to reduce the chance of false positives, and the rational analysis, which raises practical objections to these adjustments, including the arbitrary and inconsistent definition of "family-wise error rate" and the potential increase in Type II errors (false negatives). Feise suggests that researchers should balance statistical significance with the magnitude of effect, the quality of the study, and findings from other studies. He recommends either selecting a primary outcome measure or using a global assessment measure instead of adjusting the p-value. The article also provides strategies for both readers and authors to make informed decisions, emphasizing the importance of evaluating the quality of the study and the clinical relevance of the findings.The article by Ronald J Feise discusses the need for p-value adjustment in clinical trials when multiple outcome measures (MOMs) are used. The primary aim is to evaluate whether p-value adjustments are necessary to compensate for the increased risk of Type I errors (false positives) when testing multiple hypotheses simultaneously. The author presents two perspectives: the classic view, which advocates for p-value adjustments to reduce the chance of false positives, and the rational analysis, which raises practical objections to these adjustments, including the arbitrary and inconsistent definition of "family-wise error rate" and the potential increase in Type II errors (false negatives). Feise suggests that researchers should balance statistical significance with the magnitude of effect, the quality of the study, and findings from other studies. He recommends either selecting a primary outcome measure or using a global assessment measure instead of adjusting the p-value. The article also provides strategies for both readers and authors to make informed decisions, emphasizing the importance of evaluating the quality of the study and the clinical relevance of the findings.