Development of a prediction model of conversion to Alzheimer's disease in people with mild cognitive impairment: the statistical analysis plan of the INTERCEPTOR project.

Flavia L Lombardo, Patrizia Lorenzini, Flavia Mayer, Marco Massari, Paola Piscopo, Ilaria Bacigalupo, Antonio Ancidoni, Francesco Sciancalepore, Nicoletta Locuratolo, Giulia Remoli, Simone Salemme, Stefano Cappa, Daniela Perani, Patrizia Spadin, Fabrizio Tagliavini, Alberto Redolfi, Maria Cotelli, Camillo Marra, Naike Caraglia, Fabrizio Vecchio, Francesca Miraglia, Paolo Maria Rossini, Nicola Vanacore
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Abstract

Background: In recent years, significant efforts have been directed towards the research and development of disease-modifying therapies for dementia. These drugs focus on prodromal (mild cognitive impairment, MCI) and/or early stages of Alzheimer's disease (AD). Literature evidence indicates that a considerable proportion of individuals with MCI do not progress to dementia. Identifying individuals at higher risk of developing dementia is essential for appropriate management, including the prescription of new disease-modifying therapies expected to become available in clinical practice in the near future.

Methods: The ongoing INTERCEPTOR study is a multicenter, longitudinal, interventional, non-therapeutic cohort study designed to enroll 500 individuals with MCI aged 50-85 years. The primary aim is to identify a biomarker or a set of biomarkers able to accurately predict the conversion from MCI to AD dementia within 3 years of follow-up. The biomarkers investigated in this study are neuropsychological tests (mini-mental state examination (MMSE) and delayed free recall), brain glucose metabolism ([18F]FDG-PET), MRI volumetry of the hippocampus, EEG brain connectivity, cerebrospinal fluid (CSF) markers (p-tau, t-tau, Aβ1-42, Aβ1-42/1-40 ratio, Aβ1-42/p-Tau ratio) and APOE genotype. The baseline visit includes a full cognitive and neuropsychological evaluation, as well as the collection of clinical and socio-demographic information. Prognostic models will be developed using Cox regression, incorporating individual characteristics and biomarkers through stepwise selection. Model performance will be evaluated in terms of discrimination and calibration and subjected to internal validation using the bootstrapping procedure. The final model will be visually represented as a nomogram.

Discussion: This paper contains a detailed description of the statistical analysis plan to ensure the reproducibility and transparency of the analysis. The prognostic model developed in this study aims to identify the population with MCI at higher risk of developing AD dementia, potentially eligible for drug prescriptions. The nomogram could provide a valuable tool for clinicians for risk stratification and early treatment decisions.

Trial registration: ClinicalTrials.gov NCT03834402. Registered on February 8, 2019.

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开发轻度认知障碍患者转为阿尔茨海默病的预测模型:INTERCEPTOR 项目的统计分析计划。
背景:近年来,人们一直致力于研究和开发痴呆症的疾病改变疗法。这些药物主要针对阿尔茨海默病(AD)的前驱期(轻度认知障碍,MCI)和/或早期阶段。文献证据表明,相当一部分 MCI 患者不会发展为痴呆症。识别痴呆症高危人群对于进行适当的管理至关重要,包括在不久的将来在临床实践中使用新的疾病改变疗法:正在进行的 INTERCEPTOR 研究是一项多中心、纵向、干预性、非治疗性队列研究,旨在招募 500 名 50-85 岁的 MCI 患者。研究的主要目的是确定一种或一组生物标志物,以便在3年随访期内准确预测MCI向AD痴呆的转化。本研究调查的生物标志物包括神经心理测试(迷你精神状态检查(MMSE)和延迟自由回忆)、脑葡萄糖代谢([18F]FDG-PET)、海马体磁共振成像容积、脑电图脑连接、脑脊液(CSF)标志物(p-tau、t-tau、Aβ1-42、Aβ1-42/1-40 比值、Aβ1-42/p-Tau 比值)和 APOE 基因型。基线访问包括全面的认知和神经心理学评估,以及临床和社会人口信息的收集。将使用 Cox 回归法建立预后模型,并通过逐步选择的方法纳入个体特征和生物标志物。将从区分度和校准方面对模型性能进行评估,并使用引导程序进行内部验证。最终的模型将以提名图的形式直观呈现:本文详细描述了统计分析计划,以确保分析的可重复性和透明度。本研究开发的预后模型旨在确定哪些MCI患者有较高风险发展为AD痴呆,从而有可能获得药物处方。该提名图可为临床医生提供一个宝贵的工具,用于风险分层和早期治疗决策:试验注册:ClinicalTrials.gov NCT03834402。注册日期:2019年2月8日。
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