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
Authors: Lombardo Flavia L. , Lorenzini Patrizia , Mayer Flavia , Massari Marco , Piscopo Paola , Bacigalupo Ilaria , Ancidoni Antonio , Sciancalepore Francesco , Locuratolo Nicoletta , Remoli Giulia , Salemme Simone , Cappa Stefano , Perani Daniela , Spadin Patrizia , Tagliavini Fabrizio , Redolfi Alberto , Cotelli Maria , Marra Camillo , Caraglia Naike , Vecchio Fabrizio , Miraglia Francesca , Rossini Paolo Maria , Vanacore Nicola ,   the INTERCEPTOR Network, Belfiglio Maurizio , Muscio Cristina , Quaranta Davide , Cassetta Emanuele , Barbagallo Mario , Gabelli Carlo , Luzzi Simona , Lauretani Fulvio , Rainero Innocenzo , Ferrarese Carlo , Zanetti Orazio , Marcon Michela , Nobili Flavio Mariano , Pelliccioni Giuseppe , Capellari Sabina , Sinforiani Elena , Tedeschi Gioacchino , Gerace Carmen , Bonanni Laura , Sorbi Sandro , Parnetti Lucilla 
Published: July 2024

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