Back to basics: explaining sample size in outcome trials, are statisticians doing a thorough job?

Area of Science:

• Clinical Trials
• Biostatistics
• Drug Development

Background:

• Time to event outcome trials are large, expensive, and high-profile, common in oncology, cardiovascular, and respiratory diseases.
• These trials are closely monitored, with results eagerly awaited and heavily scrutinized in publications.
• Statisticians are integral to the design, conduct, analysis, and reporting of these critical studies.

Purpose of the Study:

• To highlight key features of outcome trial sample sizing.
• To provide recommendations for a common understanding of sample size, power, and persuasive outcomes.
• To minimize the risk of statistically significant but clinically unpersuasive results in drug development.

Main Methods:

• The paper discusses important features related to sample sizing in time to event outcome trials.
• It emphasizes the statistician's role in ensuring appropriate trial sizing and managing event rate expectations.
• Recommendations are made to improve the understanding of sample size and power dynamics.

Main Results:

• Effective sample size determination is crucial for the success of clinical outcome trials.
• Statisticians must ensure teams understand trial sizing and the balance between statistical significance and clinical relevance.
• Early identification of event rate deviations is vital for adaptive trial management.

Conclusions:

• Optimizing sample size and power is essential for achieving statistically positive and clinically persuasive outcomes in clinical trials.
• Clear communication and understanding between statisticians and non-statistical teams are paramount.
• Proactive statistical guidance can mitigate risks and enhance the interpretability of trial results.