Retrospective study of FaceAge as a biomarker for prognosis and treatment stratification in a large-scale oncology cohort

Humans age at different rates, and facial characteristics may yield insight into biological age and physiological health. FaceAge, a deep learning system estimating biological age from facial photographs, has shown potential as a biomarker for cancer prognosis. A multinational retrospective study investigated the prognostic value of extreme discordance between FaceAge and chronological age (‘FaceAge - Age’) in predicting survival and early mortality across a large dataset of 28 cancer types. The study included 24,556 cancer patients aged 60 years or older receiving radiation therapy between 2008 and 2023. FaceAge was older than chronological age in 65% (median FaceAge 74 years versus Age 70 years). On multivariate analysis, FaceAge – Age ≥ 10 years predicted higher mortality risk (HR 1.26; p<0.001) and early mortality at 30 days (OR 1.38; p <0.001), whereas FaceAge – Age ≤ 5 years predicted lower mortality risk (HR 0.90; p <0.001). The authors conclude that extreme discordance between FaceAge and chronological age is a novel, independent predictor of survival and early mortality.