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The Alzheimer's prevention initiative composite cognitive test score: Sample size estimates for the evaluation of preclinical Alzheimer's disease treatments in presenilin 1 E280A mutation carriers

机译:阿尔茨海默氏症预防倡议综合认知测试评分:评估早老素1 E280A突变携带者临床前阿尔茨海默氏病治疗的样本量估计

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Objective: To identify a cognitive composite that is sensitive to tracking preclinical Alzheimer's disease decline to be used as a primary end point in treatment trials. Method: We capitalized on longitudinal data collected from 1995 to 2010 from cognitively unimpaired presenilin 1 (PSEN1) E280A mutation carriers from the world's largest known early-onset autosomal dominant Alzheimer's disease kindred to identify a composite cognitive test with the greatest statistical power to track preclinical Alzheimer's disease decline and estimate the number of carriers age 30 years and older needed to detect a treatment effect in the Alzheimer's Prevention Initiative's (API) preclinical Alzheimer's disease treatment trial. The mean-to-standard-deviation ratios (MSDRs) of change over time were calculated in a search for the optimal combination of 1 to 7 cognitive tests/subtests drawn from the neuropsychological test battery in cognitively unimpaired mutation carriers during a 2- and 5-year follow-up period (n = 78 and 57), using data from noncarriers (n = 31 and 56) during the same time period to correct for aging and practice effects. Combinations that performed well were then evaluated for robustness across follow-up years, occurrence of selected items within top-performing combinations, and representation of relevant cognitive domains. Results: The optimal test combination included Consortium to Establish a Registry for Alzheimer's Disease (CERAD) Word List Recall, CERAD Boston Naming Test (high frequency items), Mini-Mental State Examination (MMSE) Orientation to Time, CERAD Constructional Praxis, and Raven's Progressive Matrices (Set A), with an MSDR of 1.62. This composite is more sensitive than using either the CERAD Word List Recall (MSDR = 0.38) or the entire CERAD-Col battery (MSDR = 0.76). A sample size of 75 cognitively normal PSEN1 E280A mutation carriers aged 30 years and older per treatment arm allows for a detectable treatment effect of 29% in a 60-month trial (80% power, P = .05). Conclusions: We have identified a composite cognitive test score representing multiple cognitive domains that, compared to the most sensitive single test item, has improved power to track preclinical Alzheimer's disease decline in autosomal dominant Alzheimer's disease mutation carriers and to evaluate preclinical Alzheimer's disease treatments. This API composite cognitive test score will be used as the primary end point in the first API trial in cognitively unimpaired autosomal dominant Alzheimer's disease carriers within 15 years of their estimated age at clinical onset. We have independently confirmed our findings in a separate cohort of cognitively healthy older adults who progressed to the clinical stages of late-onset Alzheimer's disease, described in a separate report, and continue to refine the composite in independent cohorts and compared with other analytic approaches.
机译:目的:确定对追踪临床前阿尔茨海默氏病下降敏感的认知复合物,将其用作治疗试验的主要终点。方法:我们利用从1995年至2010年从世界上最大的已知早发型常染色体显性遗传性阿尔茨海默氏病的认知未受损的早老素1(PSEN1)E280A突变携带者收集的纵向数据中,鉴定出一种具有最大统计能力的复合认知测试,以追踪临床前阿尔茨海默氏病下降,并估计在阿尔茨海默氏症预防倡议(API)的临床前阿尔茨海默氏病治疗试验中检测出治疗效果所需的30岁及30岁以上的携带者数量。计算随时间变化的均值与标准差之比(MSDR),以求在2到5期间认知无障碍的突变携带者中从神经心理学测试电池中提取的1到7个认知测验/子测验的最佳组合年随访期(n = 78和57),使用同一时期内非携带者(n = 31和56)的数据校正衰老和实践效果。然后评估表现良好的组合在接下来的几年中的健壮性,表现最佳的组合中所选项目的出现以及相关认知域的表示。结果:最佳测试组合包括:建立阿尔茨海默氏病注册机构(CERAD)单词列表召回联盟,CERAD波士顿命名测试(高频项目),按时间的小心理状态考试(MMSE),CERAD构造实践和Raven's渐进式矩阵(A组),MSDR为1.62。与使用CERAD单词列表重调用(MSDR = 0.38)或整个CERAD-Col电池(MSDR = 0.76)相比,此复合文件更加敏感。在60个月的试验中,每个治疗组75个年龄在30岁及以上的认知正常PSEN1 E280A突变携带者的样本量可实现29%的可检测治疗效果(80%功效,P = 0.05)。结论:我们已经确定了代表多个认知领域的综合认知测试评分,与最敏感的单个测试项目相比,该评分提高了追踪常染色体显性遗传阿尔茨海默氏病突变携带者的临床前阿尔茨海默氏病下降以及评估临床前阿尔茨海默氏病治疗的能力。该API综合认知测验分数将在其估计发病年龄的15年内,在认知无损害的常染色体显性遗传性阿尔茨海默氏病携带者的首次API试验中用作主要终点。我们已经在另一组认知健康的成年人中独立确认了我们的发现,这些成年人已发展至迟发性阿尔茨海默氏病的临床阶段(在另一份报告中进行了描述),并继续在独立的队列中完善组合,并与其他分析方法进行了比较。

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