Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
Department of Biostatistics, Johns Hopkins University, Bloomberg School of Public Health, Baltimore, MD 21205, USA.
Brain. 2018 Mar 1;141(3):877-887. doi: 10.1093/brain/awx365.
Recent evidence indicates that measures from cerebrospinal fluid, MRI scans and cognitive testing obtained from cognitively normal individuals can be used to predict likelihood of progression to mild cognitive impairment several years later, for groups of individuals. However, it remains unclear whether these measures are useful for predicting likelihood of progression for an individual. The increasing focus on early intervention in clinical trials for Alzheimer's disease emphasizes the importance of improving the ability to identify which cognitively normal individuals are more likely to progress over time, thus allowing researchers to efficiently screen participants, as well as determine the efficacy of any treatment intervention. The goal of this study was to determine which measures, obtained when individuals were cognitively normal, predict on an individual basis, the onset of clinical symptoms associated with a diagnosis of mild cognitive impairment due to Alzheimer's disease. Cognitively normal participants (n = 224, mean baseline age = 57 years) were evaluated with a range of measures, including: cerebrospinal fluid amyloid-β and phosphorylated-tau, hippocampal and entorhinal cortex volume, cognitive tests scores and APOE genotype. They were then followed to determine which individuals developed mild cognitive impairment over time (mean follow-up = 11 years). The primary outcome was progression from normal cognition to the onset of clinical symptoms of mild cognitive impairment due to Alzheimer's disease at 5 years post-baseline. Time-dependent receiver operating characteristic analyses examined the sensitivity and specificity of individual measures, and combinations of measures, as predictors of the outcome. Six measures, in combination, were the most parsimonious predictors of transition to mild cognitive impairment 5 years after baseline (area under the curve = 0.85; sensitivity = 0.80, specificity = 0.75). The addition of variables from each domain significantly improved the accuracy of prediction. The incremental accuracy of prediction achieved by adding individual measures or sets of measures successively to one another was also examined, as might be done when enrolling individuals in a clinical trial. The results indicate that biomarkers obtained when individuals are cognitively normal can be used to predict which individuals are likely to develop clinical symptoms at 5 years post-baseline. As a number of the measures included in the study could also be used as subject selection criteria in a clinical trial, the findings also provide information about measures that would be useful for screening in a clinical trial aimed at individuals with preclinical Alzheimer's disease.
最近的证据表明,从脑脊液、MRI 扫描和认知测试中获取的认知正常个体的指标可以用于预测几年后轻度认知障碍的进展可能性,适用于个体群体。然而,这些指标是否可用于预测个体的进展可能性仍不清楚。临床试验中对阿尔茨海默病早期干预的日益关注强调了提高识别认知正常个体随时间进展更有可能的能力的重要性,从而使研究人员能够有效地筛选参与者,并确定任何治疗干预的疗效。本研究的目的是确定在个体基础上,哪些在个体认知正常时获得的指标可以预测与阿尔茨海默病引起的轻度认知障碍相关的临床症状的发作。对 224 名认知正常的参与者(平均基线年龄为 57 岁)进行了一系列指标的评估,包括:脑脊液淀粉样蛋白-β和磷酸化 tau、海马和内嗅皮质体积、认知测试分数和 APOE 基因型。然后对他们进行随访,以确定哪些人随着时间的推移发展为轻度认知障碍(平均随访时间=11 年)。主要结局是从正常认知进展到基线后 5 年出现与阿尔茨海默病相关的轻度认知障碍的临床症状。时间依赖的接收器工作特征分析检查了个体指标及其组合作为结果预测指标的敏感性和特异性。六项指标的组合是预测基线后 5 年轻度认知障碍进展的最简约预测指标(曲线下面积=0.85;敏感性=0.80,特异性=0.75)。从每个领域添加变量显著提高了预测的准确性。还检查了通过依次向彼此添加个体指标或指标集来逐步增加预测精度的增量准确性,这可能是在将个体纳入临床试验时完成的。结果表明,在认知正常的个体中获得的生物标志物可用于预测哪些个体在基线后 5 年可能出现临床症状。由于研究中包含的多项指标也可作为临床试验中的受试者选择标准,因此研究结果还提供了有关对旨在针对有临床前阿尔茨海默病的个体的临床试验进行筛选有用的指标的信息。