Patients with non-muscle invasive bladder cancer (NMIBC) have a high possibility of recurrence after surgery. We aimed to assess the factors associated with tumor recurrence and to construct a nomogram model that can contribute to personalized treatment plans of each patient.
496 patients with primary bladder cancer (BC) from 2 centers were retrospectively analyzed. Preoperative neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio (PLR), systemic immune-inflammation index (SII), and traditional clinical parameters were collected, then using univariate and multivariate Cox regression analysis to find out the independent risk factors associated with tumor recurrence among them, and then these independent factors were incorporated into the nomogram model. The internal calibration curves and the external calibration curves were used to verify their usefulness.
In the training cohort, 150 patients (43.1%) experienced recurrence. After Cox regression analysis, the independent risk factors affecting recurrence-free survival (RFS) were tumor grade, immediate postoperative instillation therapy (IPPIT), NLR, and SII. These factors were used to construct a model to predict RFS 1, 2, 3, and 5 years of NMIBC patients after surgery. And then, we found that the constructed model outperforms the conventional model in terms of accuracy and predictability, the results were verified by statistical tests.
Preoperative inflammatory response markers have a predictive value for postoperative recurrence in patients with NMIBC. The constructed nomogram model can be helpful in guiding personalized clinical evaluation and subsequent treatment.