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Personalized prediction of progression in pre‐dementia patients based on individual biomarker profile: A development and validation study
Alzheimer s & Dementia ( IF 13.0 ) Pub Date : 2021-09-28 , DOI: 10.1002/alz.12363
Line Kühnel 1, 2 , Vincent Bouteloup 3, 4 , Jérémie Lespinasse 3, 4 , Geneviève Chêne 3, 4 , Carole Dufouil 3, 4 , José Luis Molinuevo 1 , Lars Lau Raket 1, 5 ,
Affiliation  

AbstractIntroductionThe prognosis of patients at the pre‐dementia stage is difficult to define. The aim of this study is to develop and validate a biomarker‐based continuous model for predicting the individual cognitive level at any future moment. In addition to personalized prognosis, such a model could reduce trial sample size requirements by allowing inclusion of a homogenous patient population.MethodsDisease‐progression modeling of longitudinal cognitive scores of pre‐dementia patients (baseline Clinical Dementia Rating ≤ 0.5) was used to derive a biomarker profile that was predictive of patient's cognitive progression along the dementia continuum. The biomarker profile model was developed and validated in the MEMENTO cohort and externally validated in the Alzheimer's Disease Neuroimaging Initiative.ResultsOf nine candidate biomarkers in the development analysis, three cerebrospinal fluid and two magnetic resonance imaging measures were selected to form the final biomarker profile. The model‐based prognosis of individual future cognitive deficit was shown to significantly improve when incorporating biomarker information on top of cognition and demographic data. In trial power calculations, adjusting the primary analysis for the baseline biomarker profile reduced sample size requirements by ≈10%. Compared to conventional cognitive cut‐offs, inclusion criteria based on biomarker‐profile cut‐offs resulted in up to 28% reduced sample size requirements due to increased homogeneity in progression patterns.DiscussionThe biomarker profile allows prediction of personalized trajectories of future cognitive progression. This enables accurate personalized prognosis in clinical care and better selection of patient populations for clinical trials. A web‐based application for prediction of patients’ future cognitive progression is available online.

中文翻译:

基于个体生物标志物概况的痴呆前期患者进展的个性化预测:一项开发和验证研究

摘要介绍痴呆前期患者的预后很难确定。本研究的目的是开发和验证基于生物标记的连续模型,用于预测未来任何时刻的个人认知水平。除了个性化预后之外,这种模型还可以通过允许纳入同质患者群体来减少试验样本量要求。方法使用痴呆前患者的纵向认知评分(基线临床痴呆评分≤0.5)的疾病进展模型来得出生物标志物谱,该生物标志物谱可预测患者沿痴呆连续体的认知进展。该生物标志物概况模型是在 MMENTO 队列中开发和验证的,并在阿尔茨海默病神经影像计划中进行了外部验证。结果在开发分析中的九个候选生物标志物中,选择了三个脑脊液和两个磁共振成像测量来形成最终的生物标志物概况。当将生物标志物信息纳入认知和人口统计数据之上时,基于模型的个人未来认知缺陷的预后被证明可以显着改善。在试验功效计算中,调整基线生物标志物概况的主要分析将样本量要求减少了约 10%。与传统的认知截止值相比,由于进展模式的同质性增加,基于生物标志物轮廓截止值的纳入标准导致样本量要求减少了 28%。讨论生物标志物概况可以预测未来认知进展的个性化轨迹。这使得临床护理中能够实现准确的个性化预后,并更好地选择临床试验的患者群体。可以在线获取基于网络的应用程序,用于预测患者未来的认知进展。
更新日期:2021-09-28
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