A New Look at P Values for Randomized Clinical Trials.

Area of Science:

• Biostatistics
• Clinical Trial Design
• Evidence-Based Medicine

Background:

• Analysis of 23,551 randomized clinical trials from the Cochrane Database.
• Identified widespread low statistical power in trials for actual effects.
• Observed overestimation of treatment effects and misinterpretation of significant/nonsignificant results.

Purpose of the Study:

• To reinterpret P values using a reference population of studies.
• To develop an empirical guide for interpreting P values in clinical trials.
• To address issues of overestimation, incorrect effect signs, and replication failures.

Main Methods:

• Examined primary efficacy results from a large cohort of systematic reviews.
• Estimated statistical power for actual effects versus stated effect sizes.
• Reinterpreted P value significance in the context of a reference study population.

Main Results:

• Statistically significant findings often overestimate true effects.
• Nonsignificant results may still indicate important effects.
• Developed a guide for P value interpretation, including effect overestimation, probability of incorrect effect sign, and predictive power.

Conclusions:

• Provides a novel interpretation of P values for clinical trialists.
• Helps researchers avoid naive P value interpretations and overoptimistic effect sizes.
• Findings are relevant to medical research and other fields suffering from low statistical power.