Development and validation of clinical prediction model for post-treatment recurrence in high-risk non-muscle invasive bladder cancer after BCG intravesical instillation

To investigate the factors influencing the efficacy of intravesical Bacille Calmette-Guérin (BCG) instillation after transurethral resection of bladder tumor (TURBT) in patients with intermediate- and high-risk non-muscle invasive bladder cancer (NMIBC), and to construct a prediction model for recurrence after BCG treatment.

A retrospective cohort study was conducted on the subjected patients diagnosed with intermediate- and high-risk NMIBC undergoing TURBT followed by standard BCG instillation. The 110 patients treated in Department of Urology of Army Medical Center of PLA from January 2018 to December 2023 were assigned into a training set, while the 52 patients treated at Department of Urology of General Hospital of Central Theater Command from January 2015 to December 2020 were into an external validation set. A total of 17 variables were included and analyzed. Univariate and multivariate Cox regression analyses were performed to identify factors associated with recurrence after BCG instillation, and nomograms were plotted to predict 1-year, 3-year, and 5-year recurrence-free survival (RFS). Calibration curve, decision curve analysis (DCA), and receiver operating characteristic (ROC) curve analysis were conducted for internal and external validation to evaluate the predictive performance and clinical utility of the model.

In the training set, 26 patients (23.64%) experienced recurrence during the follow-up period, with a median RFS of 32.00 (18.00~50.50) months. Univariate Cox regression analysis suggested that platelet count, eosinophil to lymphocyte ratio (ELR), neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), systemic immune inflammation (SII) index, and neutrophil-monocyte to lymphocyte ratio (NMLR), pathological T1 stage (pT1) tumor and hemoglobin, albumin, lymphocyte, and platelet (HALP) score were potential factors influencing recurrence after BCG instillation. Multivariate Cox regression analysis identified high HALP score (HR= 0.185, 95%CI: 0.046~0.736, P=0.017) as an independent protective factor, while high ELR (HR=3.599, 95%CI: 1.505~8.608, P=0.004) and pT1 stage (HR=3.240, 95%CI: 1.191~8.818, P=0.021) were independent risk factors for recurrence. Based on this, a nomogram prediction model was constructed. The calibration curves demonstrated good agreement between predicted and actual 1-, 3-, and 5-year recurrence risks. Decision curve analysis indicated clinical utility across a wide threshold probability range. In the training set, the model showed strong predictive performance for 1-(AUC=0.842), 3-(AUC=0.847), and 5-year (AUC=0.887) recurrence risks, which was further validated in the external cohort.

Higher HALP score prior to BCG instillation therapy is a protective factor against tumor recurrence, while higher ELR and pT1 stage are risk factors. Our nomogram prediction model based on HALP score, ELR and pathological T stage, can identify individuals at high risk of recurrence after BCG instillation therapy.