Abstract
BackgroundClinical trials with longitudinally measured outcomes are often plagued by missing data due to patients withdrawing or dropping out from the trial before completing the measurement schedule. The reasons for dropout are sometimes clearly known and recorded during the trial, but in many instances these reasons are unknown or unclear. Often such reasons for dropout are non-ignorable. However, the standard methods for analysing longitudinal outcome data assume that missingness is non-informative and ignore the reasons for dropout, which could result in a biased comparison between the treatment groups.MethodsIn this article, as a post hoc analysis, we explore the impact of informative dropout due to competing reasons on the evaluation of treatment effect in the MAGNETIC trial, the largest randomised placebo-controlled study to date comparing the addition of nebulised magnesium sulphate to standard treatment in acute severe asthma in children. We jointly model longitudinal outcome and informative dropout process to incorporate the information regarding the reasons for dropout by treatment group.ResultsThe effect of nebulised magnesium sulphate compared with standard treatment is evaluated more accurately using a joint longitudinal-competing risk model by taking account of such complexities. The corresponding estimates indicate that the rate of dropout due to good prognosis is about twice as high in the magnesium group compared with standard treatment.ConclusionsWe emphasise the importance of identifying reasons for dropout and undertaking an appropriate statistical analysis accounting for such dropout. The joint modelling approach accounting for competing reasons for dropout is proposed as a general approach for evaluating the sensitivity of conclusions to assumptions regarding missing data in clinical trials with longitudinal outcomes.Trial registrationEudraCT number 2007-006227-12. Registration date 18 Mar 2008.Electronic supplementary materialThe online version of this article (doi:10.1186/s13063-016-1342-0) contains supplementary material, which is available to authorized users.
Highlights
Clinical trials with longitudinally measured outcomes are often plagued by missing data due to patients withdrawing or dropping out from the trial before completing the measurement schedule
The graphical summaries of Asthma Severity Score (ASS) dropout trajectories indicated that most children were clinically well and ready to be discharged at the time of withdrawal from the trial in the magnesium group [6], this claim is yet to be justified on the basis of a formal statistical analysis
According to a recent review [5], MAGNETIC is the first clinical trial that in which researchers have reported fitting the standard joint model in a sensitivity analysis to account for informative dropout [6]
Summary
Clinical trials with longitudinally measured outcomes are often plagued by missing data due to patients withdrawing or dropping out from the trial before completing the measurement schedule. The standard methods for analysing longitudinal outcome data assume that missingness is non-informative and ignore the reasons for dropout, which could result in a biased comparison between the treatment groups. We explore the impact of informative dropout due to competing reasons on the evaluation of the effect of nebulised magnesium sulphate in the MAGNEsium Trial in Children (MAGNETIC; Current Controlled Trials identifier ISRCTN81456894). MAGNETIC is the largest randomised, double-blind, placebo-controlled study to date comparing the addition of nebulised magnesium sulphate to standard treatment in acute severe asthma in children. The reasons for dropout were sometimes clearly known and recorded during the trial; in many instances these reasons were unknown or unclear
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
