Assessment of body composition in the advanced stage of castration-resistant prostate cancer: special focus on sarcopenia.

PURPOSE

To assess the prevalence of sarcopenia and whether body composition parameters are associated with disease progression and overall survival (OS) in castration-resistant prostate cancer (CRPC) patients.

MATERIALS AND METHODS

This single-centre retrospective study evaluated data of 186 consecutive patients who underwent chemohormonal therapy between 2005 and 2016 as first-line systemic treatment for CRPC. Skeletal muscle and fat indices were determined using computerized tomography data before initiation of chemotherapy. Sarcopenia was defined as SMI of <55 cm/m. Visceral-to-subcutaneous fat ratio and skeletal muscle volume were calculated with body composition specific areas. Harrell's concordance index was used for predictive accuracy.

RESULTS

A total of 154 (82.8%) patients met the criteria for sarcopenia; 139 (74.7%) individuals completed at least six cycles of docetaxel. Within a median follow-up of 24.1 months, age (HR 1.03, 95% CI 1.01-1.06, p = 0.02), high PSA (1.55, 95% CI 1.07-2.25, p = 0.02) and low skeletal muscle volume (HR 1.61, 95% CI 1.10-2.35, p = 0.02) were the only independent prognostic factor for tumor progression. Overall, 93 (50%) patients died during the follow-up period. The established prognosticator, the prechemotherapy presence of liver metastases (HR 1.32, 95% CI 1.08-1.61, p < 0.01) was associated with shorter OS. Moreover, we noted that patients with an elevated visceral-to-subcutaneous fat ratio tended to have a shorter OS (p = 0.06).

CONCLUSION

The large majority of men with CRPC suffers from sarcopenia. In our cohort, low skeletal muscle volume was an independent adverse prognosticator for progression of disease. We could not detect a statistically significant body composition parameter for OS, although patients with a high proportion of visceral fat had a trend for shorter OS. However, we suggest that body composition parameters determined by CT data can provide useful objective prognostic factors that may support tailored treatment decision-making.