ArticleTranslational andrology and urology2025
A log odds of positive lymph nodes (LODDS)-based nomogram for survival prediction in elderly bladder cancer patients after radical cystectomy: development and validation using SEER and Chinese cohorts.
Article in Translational andrology and urology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Beyond staging: toward a layered risk architecture after radical cystectomy for bladder cancer.Translational andrology and urology · 2026Article
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6 authors.
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Abstract
Background: Elderly patients (≥70 years) with bladder cancer undergoing radical cystectomy (RC) represent a vulnerable population with heterogeneous outcomes. Traditional pathological lymph node (pN) staging has limitations. This study evaluated the prognostic value of lymph node ratio (LNR) and log odds of positive lymph nodes (LODDS) compared to pN and developed a novel nomogram for this demographic. Methods: Using data from the National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER) database [2004-2015], 1,018 elderly bladder cancer patients post-RC were identified and randomly split into training (n=712) and internal validation (n=306) cohorts. An independent external cohort (n=260) was included. Predictive performance of pN, LNR, and LODDS was assessed using time-dependent area under the curve (AUC) and concordance index (C-index). Prognostic factors were identified via least absolute shrinkage and selection operator (LASSO) and multivariable Cox regression. A nomogram predicting 1-, 3-, and 5-year overall survival (OS) was constructed and validated. Results: LODDS demonstrated superior prognostic discrimination compared to pN and LNR across all cohorts (training C-index: LODDS 0.602 Conclusions: LODDS provides enhanced prognostic stratification over pN and LNR in elderly bladder cancer patients post-RC. The developed and validated LODDS-based nomogram offers a practical tool for individualized survival prediction, aiding clinical decision-making in this growing population.
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