Design and analysis features used in small population and rare disease trials: A targeted review.

OBJECTIVE: Frequentist trials in Rare disease/small population trials often require unfeasibly large sample size to detect minimum clinically important differences. A targeted review was performed investigating what design and analysis methods these trials use when facing restricted recruitment. STUDY DESIGN AND SETTING: Targeted Review searching EMBASE and MEDLINE for Phase II-IV RCTs reporting 'rare' disease or 'small population' within title or abstract, since 2009. RESULTS: A total of 6,128 articles were screened with 64 trials eligible (4 Bayesian, 60 frequentist trials). Frequentists trials had planned power ranging 72-90% (median: 80%) but reported recruiting a mean of 6.6% below the planned sample size (n=38) [median 0%, IQR (-5%, 5%)], most used standard type 1 error (52 used 5% and 1 used 1%), and the average standardised effect was high (0.7) with 50% missing their assumed level. Of the 4 Bayesian trials, 3 used informed priors, 2 and 1 trials performed sensitivity analysis for the impact of priors on design and analysis respectively. Historical data, expert consensus, or both were used to construct informative priors. Bayesian trials required 30%-2400% less participants than using frequentist frameworks. CONCLUSION: Bayesian trials required lower sample size through use of informative priors. Most frequentists didn't achieve their target sample size. Bayesian methods offer promising solutions for such trials but are underutilised