Abstract
BackgroundMissing data can complicate the interpretability of a clinical trial, especially if the proportion is substantial and if there are different, potentially outcome-dependent causes.MethodsWe aimed to obtain unbiased estimates, in the presence of a high level of missing data, for the intervention effects in a prodromal Alzheimer’s disease trial: the LipiDiDiet study. We used a competing risk joint model that can simultaneously model each patient’s longitudinal outcome trajectory in combination with the timing and type of missingness.ResultsUsing the competing risk joint model, we were able to provide unbiased estimates of the intervention effects in the presence of the different types of missingness. For the LipiDiDiet study, the intervention effects remained statistically significant after this correction for the timing and type of missingness.ConclusionMissing data is a common problem in (Alzheimer) clinical trials. It is important to realize that statistical techniques make specific assumptions about the missing data mechanisms. When there are different missing data sources, a competing risk joint model is a powerful method because it can explicitly model the association between the longitudinal data and each type of missingness.Trial registrationDutch Trial Register, NTR1705. Registered on 9 March 2009
Highlights
Missing data can complicate the interpretability of a clinical trial, especially if the proportion is substantial and if there are different, potentially outcome-dependent causes
This paper focuses on the data of a randomized controlled trial in individuals with prodromal Alzheimer’s disease (AD), the LipiDiDiet trial [3, 4]
We observe a general pattern that the higher the baseline cognitive performance according to the Neuropsychological Test Battery (NTB) 5-item composite, the longer the subjects remained in the trial
Summary
Missing data can complicate the interpretability of a clinical trial, especially if the proportion is substantial and if there are different, potentially outcome-dependent causes. Clinical trials in AD studying the efficacy on disease progression typically require long follow-up periods [2]. A frequent problem associated with follow-up studies is missing data, especially in the case of long-term followup. Missing data may result from subjects dropping out of a trial, for instance, when they move away or lose motivation to participate. If subjects who terminate the trial early are systematically different from completers, the resulting missing data pose challenges on the statistical analysis. The trial had an initial 24-month intervention period, with the trial design allowing subjects to continue for a maximum of 72 months of randomized, controlled, double-blind, parallel-group intervention. Previous clinical studies showed benefits on memory and functional connectivity in patients with mild and moderate AD [12,13,14]
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