Recent advances in methodology for clinical trials in small populations: the InSPiRe project

Abstract

Where there are a limited number of patients, such as in a rare disease, clinical trials in these small populations present several challenges, including statistical issues. This led to an EU FP7 call for proposals in 2013. One of the three projects funded was the Innovative Methodology for Small Populations Research (InSPiRe) project. This paper summarizes the main results of the project, which was completed in 2017.The InSPiRe project has led to development of novel statistical methodology for clinical trials in small populations in four areas. We have explored new decision-making methods for small population clinical trials using a Bayesian decision-theoretic framework to compare costs with potential benefits, developed approaches for targeted treatment trials, enabling simultaneous identification of subgroups and confirmation of treatment effect for these patients, worked on early phase clinical trial design and on extrapolation from adult to pediatric studies, developing methods to enable use of pharmacokinetics and pharmacodynamics data, and also developed improved robust meta-analysis methods for a small number of trials to support the planning, analysis and interpretation of a trial as well as enabling extrapolation between patient groups. In addition to scientific publications, we have contributed to regulatory guidance and produced free software in order to facilitate implementation of the novel methods.

A multicenter, randomized, placebo-controlled, double-blind phase 3 trial with open-arm comparison indicates safety and efficacy of nephroprotective therapy with ramipril in children with Alport’s syndrome

“…Therefore, we enriched and confirmed our efficacy data by supplementing the RCT with data comparing the open arm of our trial with untreated children from the US (Figures 2 and 3). 19 The beneficial ramipril effect was sustained in comparison to the considerably healthier untreated children from the US with a less-severe genotype, less-severe disease, younger age, and much less albuminuria (see Supplementary Table S3) with an unadjusted HR of 0.86 (95% CI 0.41-1.81). In the open-arm group, 57.1% (24 of 42) of children were pretreated with an ACEi, reflecting a sicker population.…”

“…Adjusted for age and disease status at baseline, ramipril again reduced progression by almost 50% (adjusted HR 0.53; 0.22-1.29), although the reduction was not significant according to the classical mathematical definition (Figure 2). [19][20][21] Using a Bayesian evidence synthesis approach, the findings of the nonrandomized comparison were incorporated into the RCT. This resulted in an HR of 0.52 in virtually the same treatment effect, but a more precise estimate, indicated by a much shorter 95% CI of 0.19-1.39 (compared to 0.12-2.20; Figure 2).…”

Systematic review of statistical methods for safety data in malaria chemoprevention in pregnancy trials

“…For rare events, Bayesian approaches can be considered since they do not depend on asymptotic properties when handling rare events and can incorporate prior/external information [33]. Future research work can further consider adapting/extending recently developed statistical methods for rare disease or small population clinical trials towards analysis of rare safety outcomes in IPTp trials [34][35][36].…”

Systematic review of statistical methods for safety data in malaria chemoprevention in pregnancy trials

“…For rare events, Bayesian approaches can be considered since they do not depend on asymptotic properties when handling rare events and can incorporate prior/external information (34). Future research work can further consider adapting/extending recently developed statistical methods for rare disease or small population clinical trials towards analysis of rare safety outcomes in IPTp trials (35)(36)(37). This review agrees with other similar publications focusing on drug safety assessment in clinical trials that have noted the need for further improvement in the statistical analysis of the safety data (8,38).…”