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Sarcopenia as a Prognostic Biomarker of Advanced Urothelial Carcinoma
Authors:Hiroshi Fukushima  Minato Yokoyama  Yasukazu Nakanishi  Ken-ichi Tobisu  Fumitaka Koga
Institution:Department of Urology, Tokyo Metropolitan Cancer and Infectious Diseases Center, Komagome Hospital, Tokyo, Japan.; Fondazione IRCCS Istituto Nazionale dei Tumori, ITALY,
Abstract:

Objectives

Sarcopenia, a novel concept reflecting the degenerative loss of skeletal muscle mass, is an objective indicator of cancer cachexia. We investigated its role as a prognostic biomarker in advanced urothelial carcinoma (UC) patients.

Methods

This retrospective study consisted of 88 UC patients with cT4 and/or metastases to lymph nodes/distant organs. Skeletal muscle index (SMI), an indicator of whole-body muscle mass, was measured from computed tomography (CT) images at the diagnosis. Sarcopenia was defined as SMIs of <43 cm2/m2 for males with body mass index (BMI) <25 cm2/m2, <53 cm2/m2 for males with BMI ≥25 cm2/m2, and <41 cm2/m2 for females. Predictors of overall survival (OS) were examined using Cox proportional hazard models.

Results

Sixty-seven patients (76%) died during the median follow-up of 13 months. The median OS rate was 13 months. Multivariate analysis revealed that SMI was a significant and independent predictor of shorter OS (hazard ratio (HR) 0.90, P <0.001). In the present cohort, 53 (60%) were diagnosed with sarcopenia. The median OS rates were 11 and 31 months for sarcopenic and non-sarcopenic patients, respectively (P <0.001). On multivariate analysis, sarcopenia was a significant and independent predictor of shorter OS (HR 3.36, P <0.001), along with higher C-reactive protein (CRP) (P = 0.001), upper urinary tract cancer (P = 0.007), higher lactate dehydrogenase (LDH) (P = 0.047), and higher alkaline phosphatase (ALP) (P = 0.048).

Conclusion

Sarcopenia, which is readily evaluated on routine CT scans, is a useful prognostic biomarker of advanced UC. Non-sarcopenic patients can expect long-term survival. Evaluating sarcopenia can be helpful for decision-making processes in the management of advanced UC patients.
Keywords:
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