4.6 Article

Development and validation of a preoperative nomogram to predict lymph node metastasis in patients with bladder urothelial carcinoma

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Publisher

SPRINGER
DOI: 10.1007/s00432-023-04978-7

Keywords

Bladder cancer; Lymph node metastasis; Bladder urothelial carcinoma; Cancer risk; Nomogram; External validation

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This study aimed to develop and validate a nomogram for preoperatively predicting lymph node metastasis in bladder urothelial carcinoma patients. Patient data including demographics, pathology, imaging, and laboratory data were collected. Independent preoperative risk factors were identified and used to develop the nomogram. The nomogram showed good predictive accuracy and clinical applicability in both internal and external validation.
PurposePredicting lymph node metastasis (LNM) in patients with bladder urothelial carcinoma (BUC) before radical cystectomy aids clinical decision making. Here, we aimed to develop and validate a nomogram to preoperatively predict LNM in BUC patients.MethodsPatients with histologically confirmed BUC, who underwent radical cystectomy and bilateral lymphadenectomy, were retrospectively recruited from two institutions. Patients from one institution were enrolled in the primary cohort, while those from the other were enrolled in the external validation cohort. Patient demographic, pathological (using transurethral resection of the bladder tumor specimens), imaging, and laboratory data were recorded. Univariate and multivariate logistic regression analyses were performed to explore the independent preoperative risk factors and develop the nomogram. Internal and external validation was conducted to assess nomogram performance.Results522 and 215 BUC patients were enrolled in the primary and external validation cohorts, respectively. We identified tumor grade, infiltration, extravesical invasion, LNM on imaging, tumor size, and serum creatinine levels as independent preoperative risk factors, which were subsequently used to develop the nomogram. The nomogram showed a good predictive accuracy, with area under the receiver operator characteristic curve values of 0.817 and 0.825 for the primary and external validation cohorts, respectively. The corrected C-indexes, calibration curves (after 1000 bootstrap resampling), decision curve analysis results, and clinical impact curves demonstrated that the nomogram performed well in both cohorts and was highly clinically applicable.ConclusionWe developed a nomogram to preoperatively predict LNM in BUC, which was highly accurate, reliable, and clinically applicable.

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