ArticleNeuropsychopharmacology : official publication of the American College of Neuropsychopharmacology2020
A multipredictor model to predict the conversion of mild cognitive impairment to Alzheimer's disease by using a predictive nomogram.
Article in Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers, 2 of them syntheses that pooled it.
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Who cites it
52 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Effect of acupuncture on brain regions modulation of mild cognitive impairment: A meta-analysis of functional magnetic resonance imaging studies.Frontiers in aging neuroscience · 2022Pooled it
- Prediction Models for Conversion From Mild Cognitive Impairment to Alzheimer's Disease: A Systematic Review and Meta-Analysis.Frontiers in aging neuroscience · 2022Pooled it
- Radiomic model for differentiating parotid pleomorphic adenoma from parotid adenolymphoma based on MRI images.BMC medical imaging · 2021Trial
- Integration of glymphatic system function and hippocampal radiomics for diagnosis and conversion prediction of Alzheimer's disease.BMC medical imaging · 2026Article
- The Development of a Model to Predict Cognitive Decline Within 12 Months in Home Care Clients.Journal of clinical nursing · 2026Article
- Mild cognitive impairment-to-Alzheimer's dementia progression risk: the contribution of the Interceptor project.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- Platelet proteomic signatures of amyloid β-positive mild cognitive impairment and Alzheimer's disease.Molecular brain · 2026Article
- Should all MCI with Alzheimer's biological diagnosis receive anti-amyloid therapy?Cell death & disease · 2026Review
- Repurposing Imeglimin for Chemotherapy-Induced Cognitive Impairment: Targeting Mitochondrial Dysfunction and Neuroinflammation.Cellular and molecular neurobiology · 2026Review
- Circulating C-reactive protein influences polygenic risk of inflammatory genes expressed in brain endothelia for Alzheimer's disease.Neurobiology of disease · 2026Article
- Diagnostic and prognostic multimodal prediction models in Alzheimer's disease: A scoping review.Journal of Alzheimer's disease : JAD · 2025Article
- The impact of blood MCP-1 levels on Alzheimer's disease with genetic variation at the NAV3 and UNC5C loci.Translational psychiatry · 2025Article
- Deep adaptive learning predicts and diagnoses CSVD-related cognitive decline using radiomics from TNPJ digital medicine · 2025Article
- Dissecting the clinical and pathological prognosis of MCI patients who reverted to normal cognition: a longitudinal study.BMC medicine · 2025Article
- Interpretable machine learning for precision cognitive aging.Frontiers in computational neuroscience · 2025Article
- Identification of texture MRI brain abnormalities on Fibromyalgia syndrome using interpretable machine learning models.Scientific reports · 2024Article
- Significance of plasma p-tau217 in predicting long-term dementia risk in older community residents: Insights from machine learning approaches.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024Article
- Structural, static, and dynamic functional MRI predictors for conversion from mild cognitive impairment to Alzheimer's disease: Inter-cohort validation of Shanghai Memory Study and ADNI.Human brain mapping · 2024Article
- Comparison of Commonly Measured Plasma and Cerebrospinal Fluid Proteins and Their Significance for the Characterization of Cognitive Impairment Status.Journal of Alzheimer's disease : JAD · 2024Article
- A Two-Year Observational Study to Evaluate Conversion Rates from High- and Low-Risk Patients with Amnestic Mild Cognitive Impairment to Probable Alzheimer's Disease in a Real-World Setting.Journal of Alzheimer's disease reports · 2024Article
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9 authors.
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Abstract
Predicting the probability of converting from mild cognitive impairment (MCI) to Alzheimer's disease (AD) is still a challenging task. This study aims at providing a personalized MCI-to-AD conversion estimation by using a multipredictor nomogram that integrates neuroimaging features, cerebrospinal fluid (CSF) biomarker, and clinical assessments. To do so, 290 MCI patients were collected from the Alzheimer's Disease Neuroimaging Initiative (ADNI), of whom 76 has converted to AD and 214 remained with MCI. All subjects were randomly divided into a primary and validation cohort. Radiomics signature (Rad-sig) was obtained based on 17 cerebral cortex features selected by using Least Absolute Shrinkage and Selection Operator (LASSO) algorithm. Clinical factors and amyloid-beta peptide (Aβ) concentration were selected by using Spearman correlation between the converted and not-converted patients. Then, a nomogram that combines image features, clinical factor, and Aβ concentration was constructed and validated. Furthermore, we explored the associations between various predictors from the macro- to the microperspective by assessing gene expression patterns. Our results showed that the multipredictor nomogram (C-index 0.978 and 0.956 in both cohorts, respectively) outperformed the nomogram using either Rad-sig or Aβ concentration as individual predictors. Significant associations were found between neuropsychological scores, cerebral cortex features, Aβ levels, and underlying gene pathways. Our study may have a clinical impact as a powerful predictive tool for predicting the conversion probability of MCI and providing associations between cognitive impairment, structural changes, Aβ levels, and underlying biological patterns from the macro- to the microperspective.
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