Prognostic significance of sarcopenia and systemic inflammation for patients with renal cell carcinoma following nephrectomy

Background: To clarify the prognostic effect of preoperative sarcopenia and systemic inflammation, and to develop a nomogram for predicting overall survival (OS) of patients with renal cell carcinoma (RCC) following partial or radical nephrectomy.

Methods: Patients with RCC following nephrectomy from the First Affiliated Hospital of Soochow University during January 2018 to September 2020 were included in this study. The relationship between sarcopenia and inflammatory markers was identified by logistic regression analysis. Then univariable Cox regression analysis, LASSO regression analysis and multivariable Cox regression analysis were analyzed sequentially to select the independent prognostic factors. Kaplan-Meier survival curves were applied to ascertain the prognostic value. Finally, the identified independent predictors were incorporated in a nomogram, which was internally validated and compared with other methods.

Results: A total of 276 patients were enrolled, and 96 (34.8%) were diagnosed with sarcopenia, which was significantly associated with neutrophil-to-lymphocyte ratio (NLR). Sarcopenia and elevated inflammation markers, i.e., NLR, platelet-to-lymphocyte ratio (PLR) and the modified Glasgow Prognostic Score (mGPS), were independent factors for determining the OS. The model had good discrimination with Concordance index of 0.907 (95% CI: 0.882-0.931), and the calibration plots performed well. Both net reclassification index (NRI) and integrated discriminant improvement (IDI) exhibited better performance of the nomogram compared with clinical stage-based, sarcopenia-based and integrated "NLR+PLR+mGPS" methods. Moreover, decision curve analysis showed a net benefit of the nomogram at a threshold probability greater than 20%.

Conclusions: Preoperative sarcopenia was significantly associated with NLR. A novel nomogram with well validation was developed for risk stratification, prognosis tracking and personalized therapeutics of RCC patients.