Simone Salemme, Flavia Lucia Lombardo, Eleonora Lacorte, Francesco Sciancalepore, Giulia Remoli, Ilaria Bacigalupo, Paola Piscopo, Giovanna Zamboni, Paolo Maria Rossini, Stefano Francesco Cappa, Daniela Perani, Patrizia Spadin, Fabrizio Tagliavini, Nicola Vanacore, Antonio Ancidoni
{"title":"The prognosis of mild cognitive impairment: A systematic review and meta-analysis.","authors":"Simone Salemme, Flavia Lucia Lombardo, Eleonora Lacorte, Francesco Sciancalepore, Giulia Remoli, Ilaria Bacigalupo, Paola Piscopo, Giovanna Zamboni, Paolo Maria Rossini, Stefano Francesco Cappa, Daniela Perani, Patrizia Spadin, Fabrizio Tagliavini, Nicola Vanacore, Antonio Ancidoni","doi":"10.1002/dad2.70074","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>Knowledge gaps remain about the prognosis of mild cognitive impairment (MCI). Conversion rates to dementia vary widely, and reversion to normal cognition has gained attention. This review updates evidence on MCI conversion risk and probability of stability and reversion.</p><p><strong>Methods: </strong>We searched databases for studies on MCI prognosis with ≥3 years of follow-up, established criteria for MCI and dementia, and performed a meta-analysis using a random-effects model to assess conversion risk, reversion, and stability probability. Meta-regressions identified sources of heterogeneity and guided subgroup analysis.</p><p><strong>Results: </strong>From 89 studies (mean follow-up: 5.2 years), conversion risk was 41.5% (38.3%-44.7%) in clinical and 27.0% (22.0%-32.0%) in population-based studies, with Alzheimer's dementia as the most common outcome. Stability rates were 49.3% (clinical) and 49.8% (population). Reversion was 8.7% (clinical) and 28.2% (population).</p><p><strong>Discussion: </strong>Our findings highlight higher conversion in clinical settings and 30% reversion in population studies, calling for sustainable care pathway development.</p><p><strong>Highlights: </strong>Prognosis for mild cognitive impairment (MCI) varies by setting; dementia risk is higher and the probability of reversion is lower in clinical-based studies.In both clinical and population settings, cognitive stability is ≈50%.A reorganization of health services could ensure sustainable care for individuals with MCI.Significant heterogeneity in MCI studies impacts data interpretation; follow-up length is crucial.Long-term prognosis studies on MCI in low- and middle-income countries are urgently needed.</p>","PeriodicalId":53226,"journal":{"name":"Alzheimer''s and Dementia: Diagnosis, Assessment and Disease Monitoring","volume":"17 1","pages":"e70074"},"PeriodicalIF":4.0000,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11898010/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Alzheimer''s and Dementia: Diagnosis, Assessment and Disease Monitoring","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1002/dad2.70074","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Introduction: Knowledge gaps remain about the prognosis of mild cognitive impairment (MCI). Conversion rates to dementia vary widely, and reversion to normal cognition has gained attention. This review updates evidence on MCI conversion risk and probability of stability and reversion.
Methods: We searched databases for studies on MCI prognosis with ≥3 years of follow-up, established criteria for MCI and dementia, and performed a meta-analysis using a random-effects model to assess conversion risk, reversion, and stability probability. Meta-regressions identified sources of heterogeneity and guided subgroup analysis.
Results: From 89 studies (mean follow-up: 5.2 years), conversion risk was 41.5% (38.3%-44.7%) in clinical and 27.0% (22.0%-32.0%) in population-based studies, with Alzheimer's dementia as the most common outcome. Stability rates were 49.3% (clinical) and 49.8% (population). Reversion was 8.7% (clinical) and 28.2% (population).
Discussion: Our findings highlight higher conversion in clinical settings and 30% reversion in population studies, calling for sustainable care pathway development.
Highlights: Prognosis for mild cognitive impairment (MCI) varies by setting; dementia risk is higher and the probability of reversion is lower in clinical-based studies.In both clinical and population settings, cognitive stability is ≈50%.A reorganization of health services could ensure sustainable care for individuals with MCI.Significant heterogeneity in MCI studies impacts data interpretation; follow-up length is crucial.Long-term prognosis studies on MCI in low- and middle-income countries are urgently needed.
期刊介绍:
Alzheimer''s & Dementia: Diagnosis, Assessment & Disease Monitoring (DADM) is an open access, peer-reviewed, journal from the Alzheimer''s Association® that will publish new research that reports the discovery, development and validation of instruments, technologies, algorithms, and innovative processes. Papers will cover a range of topics interested in the early and accurate detection of individuals with memory complaints and/or among asymptomatic individuals at elevated risk for various forms of memory disorders. The expectation for published papers will be to translate fundamental knowledge about the neurobiology of the disease into practical reports that describe both the conceptual and methodological aspects of the submitted scientific inquiry. Published topics will explore the development of biomarkers, surrogate markers, and conceptual/methodological challenges. Publication priority will be given to papers that 1) describe putative surrogate markers that accurately track disease progression, 2) biomarkers that fulfill international regulatory requirements, 3) reports from large, well-characterized population-based cohorts that comprise the heterogeneity and diversity of asymptomatic individuals and 4) algorithmic development that considers multi-marker arrays (e.g., integrated-omics, genetics, biofluids, imaging, etc.) and advanced computational analytics and technologies.