Metabolic and inflammatory biomarker trajectories after a cancer diagnosis and the risk of cardiovascular diseases

Abstract

Abstract Cancer patients face a high comorbidity burden of cardiovascular diseases (CVD). There is little evidence about stratifying cancer patients for their CVD risk. Here, we conduct a cohort study (1985-2020) to examine post-cancer biomarker trajectories and their associations with subsequent CVD risk. We identify biomarker trajectories after cancer diagnosis for 11 biomarkers using latent class growth modelling. Through Cox regression, we find that cancer patients with initially high and subsequently increasing glucose levels have a 110% higher CVD risk than those with low-stable levels. A low-stable albumin level, even within the normal range, is associated with elevated CVD risk, whereas patients with initially low-stable but subsequently increasing uric acid levels exhibit a 20% reduced risk of CVD. These findings suggest that specific trajectories of glucose, albumin, and uric acid are associated with CVD risk. Further research should elucidate underlying biological mechanisms and validate these associations to improve CVD prevention in cancer patients.