Translational andrology and urology · 2026
Derivation and validation of the SLNA score: a tumor size-location-number-apperance model to predict transurethral resection of bladder tumor (TURBT) complexity.
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Zhang Hui, Zhang Chen, Xu Jinshan, Wang Maoyu, Sheng Chaoyang, Xu Yang, Zhu Jinpeng, Zeng Shuxiong, Xu Chuanliang, Zhang Zhensheng
Аннотация
BACKGROUND: Transurethral resection of bladder tumor (TURBT) is the core surgical procedure for the diagnosis and treatment of bladder cancer, with significant variations in its surgical complexity that directly affect the difficulty of surgical operation, the risk of perioperative complications, and the efficacy of postoperative management. This study aimed to develop a scoring system to evaluate the complexity of TURBT and provide a reference for preoperative assessment and postoperative management of bladder cancer patients.
METHODS: A retrospective analysis was performed on 388 patients who underwent TURBT from January 2022 to June 2023. The complexity of TURBT was defined based on serious complications (Clavien-Dindo ≥3), operation time >50 minutes, and incomplete resection. A nomogram was constructed to predict complexity based on factors such as tumor size, number of tumors, tumor location, and recurrence. The entire cohort (n=388) was randomly partitioned into: a development/training set (70%, n=272) for model construction and an internal validation/testing set (30%, n=116) for performance assessment. Statistical analysis was conducted using univariate and multivariate logistic regression, and the accuracy was assessed using the receiver operating characteristic (ROC) curve.
RESULTS: Of the 388 patients, 276 were classified as having non-complex TURBT, and 112 as complex. Factors significantly associated with complexity included larger tumor size, tumor location, age and gender. The nomogram achieved an area under the curve (AUC) of 0.92 [95% confidence interval (CI): 0.89-0.96] in the training set and 0.87 (95% CI: 0.78-0.96) in the validation set.
CONCLUSIONS: The proposed nomogram effectively predicts the complexity of TURBT using preoperative clinical data. This scoring system can aid surgeons in preoperative planning and improve patient outcomes by standardizing the assessment of TURBT complexity across institutions.
METHODS: A retrospective analysis was performed on 388 patients who underwent TURBT from January 2022 to June 2023. The complexity of TURBT was defined based on serious complications (Clavien-Dindo ≥3), operation time >50 minutes, and incomplete resection. A nomogram was constructed to predict complexity based on factors such as tumor size, number of tumors, tumor location, and recurrence. The entire cohort (n=388) was randomly partitioned into: a development/training set (70%, n=272) for model construction and an internal validation/testing set (30%, n=116) for performance assessment. Statistical analysis was conducted using univariate and multivariate logistic regression, and the accuracy was assessed using the receiver operating characteristic (ROC) curve.
RESULTS: Of the 388 patients, 276 were classified as having non-complex TURBT, and 112 as complex. Factors significantly associated with complexity included larger tumor size, tumor location, age and gender. The nomogram achieved an area under the curve (AUC) of 0.92 [95% confidence interval (CI): 0.89-0.96] in the training set and 0.87 (95% CI: 0.78-0.96) in the validation set.
CONCLUSIONS: The proposed nomogram effectively predicts the complexity of TURBT using preoperative clinical data. This scoring system can aid surgeons in preoperative planning and improve patient outcomes by standardizing the assessment of TURBT complexity across institutions.