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Combination of C-Reactive Protein and Neutrophil-to-Lymphocyte Ratio as a Novel Prognostic Index in Patients With Bladder Cancer After Radical Cystectomy.


ABSTRACT:

Background

Inflammation is widely considered an important hallmark of cancer and associated with poor postoperative survival. The objective of this study is to assess the significance of preoperative C-NLR, a new inflammation-based index that includes preoperative C-reactive protein (CRP) and neutrophil-to-lymphocyte ratio (NLR), on therapeutic outcomes for bladder cancer (BC) patients after radical cystectomy (RC).

Materials and methods

BC patients who underwent RC between 2010 and 2019 were retrospectively analyzed from our medical center. The predictive effect of CRP, NLR, and C-NLR on the survival of BC patients were analyzed by the receiver operating characteristic (ROC) curves. The relationship between C-NLR and postoperative survival was investigated by Cox regression. The corresponding nomograms were built based on the Cox regression results of overall survival (OS) and disease-free survival (DFS), which were further validated by ROC curves, decision curve analysis (DCA) curves, and calibration curves.

Results

Of the 199 eligible patients, 83 (41.70%) were classified as high C-NLR group and the remaining 116 (58.30%) were classified as low C-NLR group. ROC analysis showed that C-NLR had the largest area under curve (AUC) compared to CRP and NLR. Multivariate analysis revealed that T-stage and C-NLR [high C-NLR vs. low C-NLR, hazard ratio (HR) = 2.478, 95% confidence interval (CI), 1.538-3.993, p < 0.001] were independent predictors of OS, whereas T-stage, M-stage, and C-NLR (high C-NLR vs. low C-NLR, HR = 2.817, 95% CI, 1.667-4.762, p < 0.001) were independent predictors of DFS. ROC and DCA analysis demonstrated better accuracy and discrimination of 3- and 5-year OS and DFS with C-NLR-based nomogram compared to TNM stage. The calibration curve reconfirmed the accurate predicting performance of nomograms.

Conclusion

C-NLR is a reliable predictor of long-term prognosis of BC patients after RC and will contribute to the optimization of individual therapy for BC patients.

SUBMITTER: Wang Y 

PROVIDER: S-EPMC8674495 | biostudies-literature |

REPOSITORIES: biostudies-literature

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