Department of Statistics, University of California, Irvine, Bren Hall 2019, Irvine, CA, 92697-1250, USA.
Institute for Memory Impairments and Neurological Disorders, University of California, Irvine, Irvine, CA, USA.
Alzheimers Res Ther. 2021 Jan 8;13(1):16. doi: 10.1186/s13195-020-00762-8.
Early study exit is detrimental to statistical power and increases the risk for bias in Alzheimer's disease clinical trials. Previous analyses in early phase academic trials demonstrated associations between rates of trial incompletion and participants' study partner type, with participants enrolling with non-spouse study partners being at greater risk.
We conducted secondary analyses of two multinational phase III trials of semagacestat, an oral gamma secretase inhibitor, for mild-to-moderate AD dementia. Cox's proportional hazards regression model was used to estimate the relationship between study partner type and the risk of early exit from the trial after adjustment for a priori identified potential confounding factors. Additionally, we used a random forest model to identify top predictors of dropout.
Among participants with spousal, adult child, and other study partners, respectively, 35%, 38%, and 36% dropped out or died prior to protocol-defined study completion, respectively. In unadjusted models, the risk of trial incompletion differed by study partner type (unadjusted p value = 0.027 for test of differences by partner type), but in models adjusting for potential confounding factors, the differences were not statistically significant (p value = 0.928). In exploratory modeling, participant age was identified as the primary characteristic to explain the relationship between study partner type and the risk of failing to complete the trial. Participant age was also the strongest predictor of trial incompletion in the random forest model.
After adjustment for age, no differences in the risk of incompletion were observed when comparing participants with different study partner types in these trials. Differences between our findings and the findings of previous studies may be explained by differences in trial phase, size, geographic regions, or the composition of academic and non-academic sites.
早期退出研究对统计效力有害，并增加阿尔茨海默病临床试验中出现偏倚的风险。先前在早期学术试验中的分析表明，试验完成率与参与者的研究伙伴类型之间存在关联，与非配偶研究伙伴一起参与研究的参与者风险更高。
我们对两项semagacestat（一种口服γ分泌酶抑制剂）治疗轻度至中度 AD 痴呆的 III 期多国试验进行了二次分析。使用 Cox 比例风险回归模型来估计研究伙伴类型与试验提前退出的风险之间的关系，调整了预先确定的潜在混杂因素。此外，我们还使用随机森林模型来确定辍学的主要预测因素。
在有配偶、成年子女和其他研究伙伴的参与者中，分别有 35%、38%和 36%在协议规定的研究完成之前退出或死亡。在未调整的模型中，研究伙伴类型的试验完成风险不同（按伙伴类型检验的未调整 p 值=0.027），但在调整潜在混杂因素的模型中，差异无统计学意义（p 值=0.928）。在探索性建模中，参与者年龄被确定为解释研究伙伴类型与完成试验的风险之间关系的主要特征。参与者年龄也是随机森林模型中试验不完成的最强预测因素。
在调整年龄后，在这些试验中比较不同研究伙伴类型的参与者时，未观察到完成率风险的差异。我们的研究结果与先前研究结果之间的差异可能是由于试验阶段、规模、地理区域或学术和非学术站点的组成不同所致。
Zotero 插件