Imaging-based biological age gap

1. Imaging-based biological age gap improves non-lung cancer mortality prediction in humans (pooled C-index 0.69 vs 0.73, difference +0.04, 95% CI 0.03–0.04, p < 0.001).

   “Addition of age gap improved model concordance of non-lung cancer death compared to a model with clinical variables alone (pooled C-index = 0.69 vs 0.73, difference + 0.04, 95% CI 0.03–0.04, p < 0.001).”

   Humansprediction of non-lung cancer death in lung cancer screening participants5 yearsn = 12,478

   Imaging-based biological age estimation predicts competing mortality risk in lung cancer screening

   Research Square·10 Aug 2026Preprint

1. Imaging-based biological age gap predicts lung cancer in humans (sHR 1.3, 95% CI 1.2–1.5 per decade).

   “compared to lung cancer diagnosis (sHR = 1.3, 95% CI 1.2–1.5).”

   Humansin lung cancer screening participants5 yearsn = 12,478

   Imaging-based biological age estimation predicts competing mortality risk in lung cancer screening

   Research Square·10 Aug 2026Preprint

More on Lung cancer

1. Imaging-based biological age gap predicts mortality in humans (sHR 2.0, 95% CI 1.8–2.3 per decade).

   “The subdistribution hazard ratio (sHR) for each decade of age gap for non-lung cancer related death was higher (sHR = 2.0, 95% CI 1.8–2.3)”

   Humansin lung cancer screening participants5 yearsn = 12,478

   Imaging-based biological age estimation predicts competing mortality risk in lung cancer screening

   Research Square·10 Aug 2026Preprint