ArticleJournal of Alzheimer's disease : JAD2024
Predicting Conversion Time from Mild Cognitive Impairment to Dementia with Interval-Censored Models.
Article in Journal of Alzheimer's disease : JAD, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- [Progress on prognostic assessment methods for mild cognitive impairment].Zhejiang da xue xue bao. Yi xue ban = Journal of Zhejiang University. Medical sciences · 2026Review
- Penalized estimation of linear transformation models for interval-censored data with time-dependent covariates.Statistical methods in medical research · 2026Article
- Testing disease progression under the proportional reduction in decline in Alzheimer's disease studies.Journal of applied statistics · 2026Article
- Sample size determination for a study with variable follow-up time.Journal of biopharmaceutical statistics · 2025Article
- Blood biomarkers as surrogate endpoints in Alzheimer's disease research.Frontiers in aging neuroscience · 2025Article
- Comparison between treatment-placebo difference and saved time measures to assess treatment effect in Alzheimer's disease.Journal of Alzheimer's disease reportsArticle
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Authors and funding
6 authors.
Funding
Abstract
Background: Mild cognitive impairment (MCI) patients are at a high risk of developing Alzheimer's disease and related dementias (ADRD) at an estimated annual rate above 10%. It is clinically and practically important to accurately predict MCI-to-dementia conversion time. Objective: It is clinically and practically important to accurately predict MCI-to-dementia conversion time by using easily available clinical data. Methods: The dementia diagnosis often falls between two clinical visits, and such survival outcome is known as interval-censored data. We utilized the semi-parametric model and the random forest model for interval-censored data in conjunction with a variable selection approach to select important measures for predicting the conversion time from MCI to dementia. Two large AD cohort data sets were used to build, validate, and test the predictive model. Results: We found that the semi-parametric model can improve the prediction of the conversion time for patients with MCI-to-dementia conversion, and it also has good predictive performance for all patients. Conclusions: Interval-censored data should be analyzed by using the models that were developed for interval- censored data to improve the model performance.
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Registered trials
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