BMC Medical Informatics and Decision Making· 2026Q1
Analyzing determinants of biological age through systematic review of prediction models
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- 2026year
Short summary
A systematic review of biological age prediction models found that variables computable from routine clinical data, such as BMI, blood pressure, and cholesterol, are the most frequently used and closest to clinical implementation.
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Key points
- Biological age models use diverse variables, hindering standardization.
- BMI, blood pressure, and cholesterol are the most frequently used predictors across models.
- Models utilizing routine clinical data are closest to practical clinical implementation.
- A synthesis of predictor variables is lacking until now.
AI-generated from the title and abstract; the full text is not read.
Abstract
Chronological age is an inadequate indicator of an individual’s functional state, and a large number of models now estimate biological age from biological and clinical measurements. These models differ widely in the variables they use, and no synthesis exists of which variables recur across models that can be computed from data generated during ordinary clinical care. This review identifies and characterises those variables and appraises how close such models are to clinical implementation.
The authors' abstract, as published at the source. BMC Medical Informatics and Decision Making, 2026 · DOI ↗
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Field: Geriatrics and Gerontology
Geriatrics and GerontologyMedicine