May 28, 2020

Different methods of analysis applied to the same clinical trial data set can lead to different conclusions. It is therefore important that the statistical analysis approach for a randomised controlled trial is pre-specified, and any changes or additions to the planned analysis should be flagged alongside trial results. This provides full transparency and allows for a thorough evaluation of the results. In a new review of trials published in high impact journals, we identified a large proportion of trials (61%) with one or more undisclosed change to the planned primary analysis approach. To see more results click the below link for the full open access publication of the review.    

May 17, 2020

In clinical trials it is most typical that some participant outcomes will not be available. This may be due to missed participant visits, trial withdrawal or other unplanned and uncontrollable events. Therefore often some required data will be missing from the analysis. When there are missing data, it is important that the primary analysis of the trial is conducted under the most plausible assumption for the missing data. Sensitivity analysis under a range of different credible assumptions should then be undertaken to assess how robust the trial results are. One method which readily enables contextually relevant sensitivity analysis, and has recently seen increased discussion and developments in the statistical literature, is Controlled Multiple Imputation.  In this new tutorial article, an overview of Controlled Multiple Imputation procedures, and a practical guide to their use for sensitivity analysis of a continuous outcome is provided. Worked examples and Stata code are included to facilitate adoption of such methods, to enable robust evaluation of clinical trial results.

March 23, 2020

Recently Inverse Probability of Treatment Weighting (IPTW) using the propensity score has been proposed as an alternative to standard regression methods for baseline covariate adjustment in the analysis of randomized trials (Williamson et al. 2013). Motivated by some recent small trial analyses we explored the properties of IPTW for covariate adjustment within small trial settings. A simulation study and a re-analysis of a pediatric eczema trial involving 60 children revealed the performance of the IPTW variance estimator proposed by Williamson et al. was sub-optimal with smaller sample sizes. We therefore caution against the use of IPTW in small sample settings without small-sample modifications when the sample size is less than 150 and particularly when the sample size <100. In larger samples IPTW using the propensity score method can however be a useful tool for adjustment. When IPTW is used with large samples we demonstrate how the bootstrap variance may be a simpler route to variance estimation, given this incorporates the estimation of the propensity score.

February 11, 2020

Anca went to visit the London PHASTAR team in Chiswick for their monthly company meeting to present some of the research that’s been going on at ICTU, as well as her systematic review that investigates how rescue medication is defined, reported, and adjusted for in randomised controlled trials. It was also amazing to hear Jennifer Roger’s presentation describing her experience with her BBC Watchdog appearance, where companies within a different industry were ranked to establish who was the best and who was the worst when considering factors such as complaints, customer satisfaction, and cost. 

February 10, 2020

The protocol for an individual patient data meta-analysis to establish whether early skin care interventions, such as moisturisers, can prevent eczema or food allergy is now available. Published in the Cochrane database, this protocol provides details of the planned analyses that will be conducted by Suzie Cro and Victoria Cornelius. The primary analysis will estimate the pooled treatment policy effect of early skincare interventions on eczema and food allergy. Sensitivity analysis will also explore the pooled effect of complying with early skin care intervention. Subgroup analyses will explore whether risk for atopy, based on genotype and family history are associated with the pooled treatment effect. Results coming later this year!