Dataset Information

Combination of Total Psoas Index and Albumin-Globulin Score for the Prognosis Prediction of Bladder Cancer Patients After Radical Cystectomy: A Population-Based Study.

ABSTRACT:

Background

Sarcopenia as the loss of skeletal muscle mass is related with poor postoperative survival. This work purposed to evaluate the prognostic prediction of the total psoas index (TPI), albumin-globulin score (AGS), and the combination of TPI and AGS (CTA) in bladder cancer (BCa) patients after radical cystectomy.

Methods

BCa patients that received radical cystectomy between 2012 and 2020 were retrieved from our medical center. The calculation of TPI was based on the plain computed tomography images. The predictive effects of TPI, AGS, and CTA grade on survival of BCa patients were analyzed and compared with the albumin-globulin ratio (AGR) through the receiver operating characteristic (ROC) curves. A nomogram was further established based on the Cox regression results from CTA grade and clinicopathological characteristics, which are verified by the decision curve analysis (DCA).

Results

A total of 112 eligible patients diagnosed as BCa were included in this study for retrospective analysis. The patients with lower TPI or higher AGS grade (1/2) contained poorer overall survival (OS) and disease-free survival (DFS). Divided by CTA grade, there were 35 (31.25%) patients in grade 1 associated with the best postoperative prognosis, which was accompanied with increased TPI and decreased AGS. The CTA grade could better predict postoperative outcomes compared with TPI, AGR, and AGS for the highest area under the curve (AUC; 0.674 of OS and 0.681 of DFS). The 3- and 5-year OS and DFS nomograms were conducted based on CTA grade and clinical variables, with a higher predictive performance than the TNM stage.

Conclusion

This study revealed that the novel index CTA functioned as an effective prognostic predictor for postoperative OS and DFS of BCa patients after radical cystectomy. Preoperative assessment of CTA would contribute to optimizing clinical therapies.

SUBMITTER: Wang K

PROVIDER: S-EPMC8488353 | biostudies-literature |

REPOSITORIES: biostudies-literature

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