Age-range dependence and prediction compression in blood-based chronological-age models

The dependence of test-set R² on the variation of chronological age is established, but blood-age models are often compared without their evaluation age distributions, absolute errors, or simple baselines. We examined these reporting issues in routine blood-based age prediction and compared the age spans and R² values reported by earlier studies. We analyzed 17 routine blood biomarkers in a Saudi laboratory cohort of 18,651 adults aged 20–84 years and an independent NHANES 2017–2018 cohort of 2,067 adults aged 20–79 years. Random Forest models were refitted and assessed with five-fold out-of-fold prediction within broad and restricted age windows, alongside training-fold mean-age and sex-only baselines. We assessed prediction-range slopes, biomarker variance components, and model-class robustness. A targeted, non-systematic comparison extracted reported age spans and held-out R² from four primary blood-based age-model reports. Saudi and NHANES broad-range R² values were 0.382 and 0.378, respectively. At ages 30–74 years they were 0.278 and 0.280, and at ages 40–64 years they were 0.134 and 0.074. Within individual decades, R² was near zero or negative. At ages 40–64, the model reduced mean absolute error relative to the sex-only baseline by 0.51 years in Saudi and 0.30 years in NHANES. Predicted-age slopes were 0.356 and 0.337. Published reports showed differing R² values even at similar age spans and a non-monotonic pattern across separately fitted age strata; the literature comparison therefore cannot assign between-study differences to age width. Broad-range R² can coexist with compressed predictions and little added age discrimination within narrow windows. The age-variance dependence of R² is not a new statistical finding; these data show its practical reporting consequences for a defined biomarker panel. Studies should report age distribution, absolute error, baselines, validation design, and prediction-range slope alongside R². Chronological-age fit alone does not validate biological aging.

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Journal
BMC Medical Informatics and Decision Making
Published
2026-10-09
DOI
https://doi.org/10.1186/s12911-026-03898-z
Primary Topic
Forensic Anthropology and Bioarchaeology Studies
Type
article
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article

Age-range dependence and prediction compression in blood-based chronological-age models

Ali Hanbashi, El Mahdi Khribch, Abdulaziz Alrashdi, John Parrington et al.
BMC Medical Informatics and Decision Making
Forensic Anthropology and Bioarchaeology Studies
article

Age-range dependence and prediction compression in blood-based chronological-age models

Ali Hanbashi, El Mahdi Khribch, Abdulaziz Alrashdi, John Parrington, Hussain Mohammed Mujalli, Walaa Rabie, Mohammed Abdu Khobrani, Eissa A. Jafari, Fahad Y. Sabei
article en

Abstract

The dependence of test-set R² on the variation of chronological age is established, but blood-age models are often compared without their evaluation age distributions, absolute errors, or simple baselines. We examined these reporting issues in routine blood-based age prediction and compared the age spans and R² values reported by earlier studies. We analyzed 17 routine blood biomarkers in a Saudi laboratory cohort of 18,651 adults aged 20–84 years and an independent NHANES 2017–2018 cohort of 2,067 adults aged 20–79 years. Random Forest models were refitted and assessed with five-fold out-of-fold prediction within broad and restricted age windows, alongside training-fold mean-age and sex-only baselines. We assessed prediction-range slopes, biomarker variance components, and model-class robustness. A targeted, non-systematic comparison extracted reported age spans and held-out R² from four primary blood-based age-model reports. Saudi and NHANES broad-range R² values were 0.382 and 0.378, respectively. At ages 30–74 years they were 0.278 and 0.280, and at ages 40–64 years they were 0.134 and 0.074. Within individual decades, R² was near zero or negative. At ages 40–64, the model reduced mean absolute error relative to the sex-only baseline by 0.51 years in Saudi and 0.30 years in NHANES. Predicted-age slopes were 0.356 and 0.337. Published reports showed differing R² values even at similar age spans and a non-monotonic pattern across separately fitted age strata; the literature comparison therefore cannot assign between-study differences to age width. Broad-range R² can coexist with compressed predictions and little added age discrimination within narrow windows. The age-variance dependence of R² is not a new statistical finding; these data show its practical reporting consequences for a defined biomarker panel. Studies should report age distribution, absolute error, baselines, validation design, and prediction-range slope alongside R². Chronological-age fit alone does not validate biological aging.

BMC Medical Informatics and Decision Making
The University of Sydney (AU), Cairo University (EG), Qassim University (SA), Khalifa University of Science and Technology (AE), Université Paris-Saclay (FR), University of Oxford (GB), Institut des Neurosciences Paris-Saclay (FR), Institut des Sciences des Plantes de Paris Saclay (FR), Jazan University (SA)
Openalex Percentile: Top 4%
Forensic Anthropology and Bioarchaeology Studies
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