Skeletal muscle mass as a prognostic indicator of outcomes in ovarian cancer: a systematic review and meta-analysis

Abstract

BackgroundMuscle mass plays a key role in predicting clinical outcomes in cancer. This systematic review and meta-analysis aimed to evaluate whether computed tomography (CT) scan indexes of muscle mass quantity and quality could be used as prognostic factors in ovarian cancer.MethodsThree electronic bibliographic databases (MEDLINE, Web of Science, and Cochrane Central Register of Controlled Trials) were used to conduct a systematic literature search from inception to January 2020. The primary outcome was overall survival. Pooled analyses of hazard ratios (HRs) and 95% confidence intervals (CIs) were performed with Review Manager 5.3. Heterogeneity was assessed by measuring inconsistency (I2 based on the χ2 test). Secondary outcomes included progression free survival, disease free survival, postoperative complications, and chemotoxicity. Study quality and quality of evidence were assessed.ResultsA total of 15 studies were included in the systematic review, of which six studies (1226 patients) were included in the meta-analysis. Summary unadjusted HRs (HR 1.11, 95% CI 0.84 to 1.46, p=0.47) and adjusted HRs (HR 1.10, 95% CI 0.84 to 1.43, p=0.49) did not show a significant association between low skeletal muscle index and overall survival (p>0.05) in ovarian cancer. Instead, although the quality of evidence was low, pooled data of three studies, comprising 679 patients, showed a significant association between low skeletal muscle radiodensity and poor overall survival (HR 1.63, 95% CI 1.28 to 2.07, p<0.0001). Moreover, the heterogeneity between studies precluded the possibility of performing a meta-analysis and reaching conclusions for progression free survival, disease free survival, surgical complications, and chemotoxicity.ConclusionsThis work suggested that the measurement of skeletal muscle radiodensity by routine CT scan at diagnosis, with standardization of diagnostic criteria, could be a reliable tool to select at risk patients and to individualize effective nutritional strategies. However, prospective homogeneous studies with a larger number of patients are required to confirm these results.