title: Back to basics: explaining sample size in outcome trials, are statisticians doing a thorough job?
abstract: Time to event outcome trials in clinical research are typically large, expensive and high-profile affairs. Such trials are commonplace in oncology and cardiovascular therapeutic areas but are also seen in other areas such as respiratory in indications like chronic obstructive pulmonary disease. Their progress is closely monitored and results are often eagerly awaited. Once available, the top line result is often big news, at least within the therapeutic area in which it was conducted, and the data are subsequently fully scrutinized in a series of high-profile publications. In such circumstances, the statistician has a vital role to play in the design, conduct, analysis and reporting of the trial. In particular, in drug development it is incumbent on the statistician to ensure at the outset that the sizing of the trial is fully appreciated by their medical, and other non-statistical, drug development team colleagues and that the risk of delivering a statistically significant but clinically unpersuasive result is minimized. The statistician also has a key role in advising the team when, early in the life of an outcomes trial, a lower than anticipated event rate appears to be emerging. This paper highlights some of the important features relating to outcome trial sample sizing and makes a number of simple recommendations aimed at ensuring a better, common understanding of the interplay between sample size and power and the final result required to provide a statistically positive and clinically persuasive outcome.
authors.affiliation: AstraZeneca Pharmaceuticals, CMOs Office, Alderley Park, Macclesfield, UK. kevin.carroll2@astrazeneca.com
authors.forename: Kevin J
authors.initials: KJ
authors.lastname: Carroll
mesh_terms: D056808:Biostatistics / Q000379:methods*; D002986:Clinical Trials as Topic / Q000706:statistics & numerical data*; D055808:Drug Discovery / Q000379:methods / Q000706:statistics & numerical data*; D006287:Health Planning Guidelines; D006801:Humans; D015233:Models, Statistical; D018401:Sample Size; D016896:Treatment Outcome