title: Design and analysis of trials with rare outcomes: examples from trials in herpes transmission and influenza prophylaxis.
abstract: For trials with rare outcomes, the number of events to be observed drives the power of the study rather than the proportions of subjects with the event and this is an important consideration when determining sample size. The stratified version of Fisher's exact test was described by Cox as long ago as 1966, but it is only recently that computing power has allowed this to be performed routinely. The issue of stratified analysis can also be addressed through permutation tests and their implementation for multicentre trials where randomisation is stratified by site has potential value. Where the time to event is available, analysis using a proportional hazards model has a potentially valuable role but estimates of differences in proportions are often required particularly for non-inferiority studies and typical software employed for these analyses uses an asymptotic approximation rather than an exact analysis. It is important to assess the impact of missing data on such trials. This can be approached through examination of the pattern of missing data and the covariates predicting discontinuation as well as through sensitivity analysis. Sensitivity analyses need to be done carefully using realistic alternative assumptions and an appealing approach is to impute events for subjects with missing data using the observed placebo rate. Issues of design and analysis for trials with rare outcomes are discussed in the context of two examples-one from a trial designed to investigate transmission of herpes and one that studied prophylaxis of influenza.
authors.affiliation: GlaxoSmithKline Research and Development, Greenford Road, Greenford, Middlesex UB6 0HE, UK. oliver.n.keene@gsk.com
authors.forename: Oliver
authors.initials: O
authors.lastname: Keene
mesh_terms: D018890:Chemoprevention; D006558:Herpes Genitalis / Q000188:drug therapy / Q000635:transmission; D006801:Humans; D007251:Influenza, Human / Q000517:prevention & control; D009735:Nursing Homes; D016016:Proportional Hazards Models; D016032:Randomized Controlled Trials as Topic / Q000379:methods* / Q000706:statistics & numerical data; D012107:Research Design; D012307:Risk Factors; D018401:Sample Size; D012680:Sensitivity and Specificity; D012747:Sexual Partners; D016896:Treatment Outcome