3884 Identifying biomarkers of accelerated ageing in cancer patients from routine clinical data

Abstract Introduction Cancer and ageing have a bidirectional relationship: age is the strongest risk factor for cancer, and cancer and treatments can accelerate ageing. Consequently, biological age of patients with cancer is likely to deviate from chronological age. Validated biomarkers of biological age are needed to quantify this and stratify interventions to minimise accelerated ageing. Methods Using the BioAge R Package, PhenoAge was calculated from eight blood test results of patients attending the Geriatric Oncology Liaison Development (GOLD) clinic at Guy’s Hospital between 2022 and 2025. PhenoAgeAccel, a biomarker of accelerated ageing, was the residual from a linear regression of PhenoAge by age. Results Data were available for 173 patients (62% male). Mean PhenoAge was higher than mean age (84.3 (12.6) vs 76.2 (7.24), p < 0.001), though the two were correlated (r = 0.579, p < 0.001). Unlike age, PhenoAge and PhenoAgeAccel were associated with one-year mortality (PhenoAge OR = 1.083, 95% CI: 1.038–1.136; PhenoAgeAccel OR = 1.096, 95% CI: 1.047–1.155, p < 0.001). In all patients, PhenoAge correlated with Clinical Frailty Scale and Timed Up and Go (CFS: Rs = 0.31, p < 0.001; TUG: Rs = 0.25, p < 0.005), whereas there were no correlations with age (CFS: Rs = 0.1, p = 0.21; TUG: Rs = 0.16, p = 0.07). PhenoAgeAccel correlated with the number of CGA interventions made per patient (Rs = 0.17, p < 0.05), but age and PhenoAge did not. Patients with diabetes had a higher PhenoAgeAccel (3.40 (9.78) vs −1.71 (10.53), p = 0.002). In patients receiving systemic anti-cancer treatment (SACT), PhenoAgeAccel pre-SACT was lower than when measured post-SACT (2.18 (10.64) vs. -2.87 (7.98); p = 0.048) overall and in matched samples (n = 21, 7.76 ± 11.98 vs −2.87 ± 7.98, p < 0.001). Conclusions PhenoAgeAccel is a promising biomarker to identify older people with cancer who may benefit from holistic geriatric assessment, dose reductions, or future geroprotective measures. This process could be automated through integration of PhenoAge within electronic healthcare record systems and clinician alerts.