Body composition and melanoma incidence risk: insights from a longitudinal lung cancer screening cohort

Objective: This study explored the association between low-dose computed tomography (LDCT)-derived body composition and melanoma incidence risk. Methods: LDCT scans from the Pittsburgh Lung Screening Study (n=3,422, 22 follow-up years) were analyzed. Body composition features were segmented and quantified from baseline scans using in-house artificial intelligence algorithms. Features were selected before modeling. Fine-Gray subdistribution hazard models assessed the association between body composition and melanoma incidence. Model performance was evaluated using time-dependent area under the curve (AUC). Restricted mean survival time (RMST) compared melanoma-free survival across BMI and body composition groups at 5, 10, and 15 years. Participants were stratified into risk groups, with risk estimated at each time point. Sex-specific analyses were conducted separately. Statistical significance was defined as p<0.05. Results: Among 3,422 participants, 80 developed melanoma (43 males, 37 females). In the overall model, visceral adipose tissue (VAT) volume (hazard ratio HR=1.27), skeletal muscle (SM) density (HR=0.81), and bone density (HR=1.33) were included, achieving a 21-year AUC of 0.68 (95% CI: 0.65-0.70). The male-specific model included only SM density (HR=0.74; AUC=0.67, 95% CI: 0.65-0.68). The female-specific model (AUC=0.68, 95% CI: 0.65-0.71) included VAT volume (HR=1.47), intramuscular adipose tissue (IMAT) ratio (HR=0.67), and bone density (HR=1.75). Higher VAT, IMAT volume, and lower SM density showed shorter melanoma-free survival and stratified risk better than BMI. Males exhibited higher estimated risk than females. Conclusion: LDCT-derived body composition metrics may provide incidental insights into melanoma risk during lung cancer screening, though their predictive utility remains limited and warrants further investigation.