A Nomogram Based on the Log Odds of Positive Lymph Nodes Predicts the Prognosis of Patients With Distal Cholangiocarcinoma After Surgery

To study the prognostic significance in gallbladder cancer (GBC) patients of the four N stage methods of log odds of positive lymph nodes (LODDS), lymph node ratio (LNR), and N stage in the 7th and 8th editions of the American Joint Committee on Cancer (AJCC), and to establish a prognostic model of GBC based on LODDS. Data of 1,321 patients with GBC who underwent surgical resection of lymph nodes from 2010 to 2014 were collected from the Surveillance, Epidemiology, and End Results (SEER) database. We then randomly divided these data into a training set (n=925) and a validation set (n=396). C-index, Akaike information criterion (AIC), and area under the curve (AUC) were calculated to evaluate the accuracy of LODDS, LNR, and N stage in the 7th and 8th editions of the AJCC. Cox multivariate analysis was performed to determine whether LODDS was an independent prognostic factor, and a nomogram model was established. C-index was used to evaluate the accuracy of the nomogram. A receiver operating characteristic (ROC) curve was drawn and the area under the AUC was calculated to evaluate the accuracy of the nomogram in predicting patients' 1-, 3-, and 5-year overall survival (OS). Univariate analysis showed that the four methods were all correlated with OS. Through C-index, AIC and AUC, We found that LODDS had the best accuracy of the four methods. C-index and AUC analysis revealed that the nomogram based on LODDS had excellent prognostic ability. All the results were verified in the validation set. LODDS is an independent prognostic factor for GBC patients, and it is the best N stage in the SEER database. This new nomogram-containing LODDS system is a great model to predict the prognosis of GBC patients.

BackgroundThe prognostic performance of four lymph node classifications, the 8th American Joint Committee on Cancer (AJCC) Tumor Node Metastasis (TNM) N stage, lymph node ratio (LNR), log odds of positive lymph nodes (LODDS), and examined lymph nodes (ELN) in early-onset pancreatic cancer (EOPC) remains unclear.MethodsThe Surveillance, Epidemiology, and End Results (SEER) database was searched for patients with EOPC from 2004 to 2016. 1048 patients were randomly divided into training (n = 733) and validation sets (n = 315). The predictive abilities of the four lymph node staging systems were compared using the Akaike information criteria (AIC), receiver operating characteristic area under the curve (AUC), and C-index. Multivariate Cox analysis was performed to identify independent risk factors. A nomogram based on lymph node classification with the strongest predictive ability was established. The nomogram’s precision was verified by the C-index, calibration curves, and AUC. Kaplan–Meier analysis and log-rank tests were used to compare differences in survival at each stage of the nomogram.ResultsCompared with the 8th N stage, LODDS, and ELN, LNR had the highest C-index and AUC and the lowest AIC. Multivariate analysis showed that N stage, LODDS, LNR were independent risk factors associated with cancer specific survival (CSS), but not ELN. In the training set, the AUC values for the 1-, 3-, and 5-year CSS of the nomogram were 0.663, 0.728, and 0.760, respectively and similar results were observed in the validation set. In addition, Kaplan–Meier survival analysis showed that the nomogram was also an important factor in the risk stratification of EOPC.ConclusionWe analyzed the predictive power of the four lymph node staging systems and found that LNR had the strongest predictive ability. Furthermore, the novel nomogram prognostic staging mode based on LNR was also an important factor in the risk stratification of EOPC.

BackgroundThe metastatic status of regional lymph nodes is an effective risk factor for the prognosis of distal cholangiocarcinoma (dCCA). But existing lymph node staging is not accurate enough and is susceptible to interference. This study aims to explore the predictive ability of the log odds of positive lymph nodes (LODDS) staging system of dCCA compared with existing lymph node staging systems.MethodsA total of 928 dCCA patients were selected from the Surveillance, Epidemiology, and End Results (SEER) database as the training cohort, and 207 dCCA patients from West China Hospital who underwent surgery were reviewed as the validation cohort. The least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression were conducted to identify the most meaningful factors relevant to prognosis. The performance of four lymph node stage systems was compared by a model-based approach.ResultAge at diagnosis, pathological grade, American Joint Committee on Cancer (AJCC) tumor 7th T stage, tumor size, radiotherapy, chemotherapy, and lymph node stage system were independent prognostic factors. The model with the LODDS system had a better model fit with the highest C-index (0.679) and 1-/3-/5- area under the receiver operating characteristic curve (AUC) (0.739/0.671/0.658) as well as the lowest Akaike information criterion (AIC) (5,020.52). External validation results from 207 dCCA patients showed a C-index of 0.647 and 1-/3-/5-AUC of 0.740/0.683/0.589. Compared with the lymph node ratio (LNR), AJCC 8th N system, and 7th N system, the 5-year net reclassification improvement (NRI) of the LODDS system was 0.030 (95% CI: −0.079 to 0.147), 0.042 (95% CI: −0.062 to 0.139), and 0.040 (95% CI: −0.057 to 0.146), respectively. The integrated discrimination improvement (IDI) of LODDS improved compared with the LNR model (0.016; 95% CI: −0.001 to 0.036), AJCC 8th N system (0.020; 95% CI: 0.003–0.037), and AJCC 7th N system (0.019; 95% CI: 0.002–0.036). Decision curve analysis (DCA) also shows a greater net benefit of LODDS. In lymph node-negative patients, LODDS reveals a positive linear relationship with the hazard ratio (HR). The stage capacity of LODDS in a subgroup analysis stratified by examined lymph node number (ELNN) was consistent.ConclusionsThe LODDS lymph node stage system has superior predictive performance as compared with the LNR, AJCC 7th, and 8th lymph node stage systems. Meanwhile, LODDS has a more detailed staging ability and good stability.

Accurate staging is essential in cancer care. The American Joint Committee on Cancer (AJCC) TNM staging system is commonly used but is subject to the risk of stage migration. Recent literature suggests that the log odds of positive lymph nodes (LODDS) and positive lymph node ratio (LNR) may have superior predictive values and are considered alternatives to the N-category. However, their predictive performance in gastric signet ring cell carcinoma (GSRC) remains vague. This study aims to explore the association between three lymph node (LN) staging systems (AJCC N-category, LODDS, and LNR) and outcomes in GSRC, and assess the predictive power. Eligible patients with GSRC from 2004 to 2015 were collected from the Surveillance, Epidemiology, and End Results database. The time-dependent receiver-operating characteristic (ROC) analysis, area under the curve (AUC), and integrated discrimination improvement (IDI) were used to assess the predictive performance of the three LN stages (AJCC N-category, LODDS, and LNR). In the multivariate analysis of all GSRC patients and the subgroup of patients with ≤ 15 LNs examined, both the LODDS and LNR were significant survival prognostic factors. The time-dependent ROC curves of the LODDS and LNR exhibited higher sensitivity and specificity when compared to the N-category curve. The AUCs at 1, 3, and 5 years demonstrated that the predictive performance of LODDS and LNR was significantly better than the N-category (all P < 0.05). IDI of LODDS and LNR also showed sufficient fit and attractive net benefit in prediction and clinical application. LODDS and LNR were remarkable prognosticators for survival in GSRC patients. Their predictive performance was better than that of the N-category, indicating that LODDS and LNR could ameliorate the predictive precision of survival risk and could replace the N-category in predicting the outcomes of GSRC patients.

BackgroundLog odds of positive lymph nodes (LODDS) is a novel and promising ratio-based lymph node (LN) staging system in many malignancies. This study aimed to evaluate the prognostic value of LODDS, and comprehensively compare the prognostic predictive performance of LODDS with the American Joint Committee on Cancer (AJCC) N classification, number of positive lymph node (NPLN), and lymph node ratio (LNR) among node-positive lung squamous cell carcinoma (SCC) patients after surgery.MethodsWe identified 2,561 patients with N1/N2 stage SCC diagnosed between 2004 and 2014 from the Surveillance, Epidemiology, and End Results (SEER) database. X-tile analysis was used to calculate the optimal cut-off value for each staging system. Univariable and Multivariable Cox regression analyses were used to assess the association of cancer-specific survival (CSS), and overall survival (OS) with N, NPLN, LNR, and LODDS, separately, and integrally. Moreover, linear trend χ2 score, likelihood ratio (LR) test, Akaike information criterion (AIC), and Harrell concordance index (C-index) were adopted as criteria for assessing the predictive ability of each model.ResultsThe optimal cut-off values for NPLN, LNR, and LODDS were 3, 0.28, and −0.37, respectively. N, NPLN, LNR, and LODDS were identified as independent prognostic predictors for CSS and OS in patients with SCC when each of them was incorporated into multivariable Cox model separately. Additionally, LODDS had the higher linear trend χ2 score, higher LR χ2 test score, lower AIC, and higher C-index compared to the other three systems. Moreover, a combination of N, NPLN, and LODDS was superior to any staging system alone for predicting prognosis.ConclusionsLODDS showed better predictive performance than N, NPLN, and LNR among patients with node-positive SCC after surgery. A combination of LODDS and the current AJCC TNM classification has the potential for becoming a better staging method to more precisely predicting prognosis.

This study aimed to explore the prognostic impact that the log odds of positive lymph nodes (LODDS) has on medullary thyroid cancer (MTC) and to develop a nomogram incorporating LODDS to predict the cancer-specific survival (CSS) of MTC. Data from 1110 MTC patients after total thyroidectomy were collected from the Surveillance, Epidemiology, and End Results (SEER) database and divided into training and validation cohorts. The prognostic efficiency of N status from the American Joint Committee on Cancer (AJCC) staging system, the number of positive lymph nodes (PLNN), and LODDS were compared using the Harrell concordance index (C-index), the Akaike information criterion (AIC), and area under the receiver operating characteristic (ROC) curve (AUC). A multivariate Cox analysis was performed to determine the independent prognostic factors, and a nomogram based on LODDS was constructed. The nomogram's performance was assessed with the C-index, AUC, calibration curves, and decision curve analysis (DCA). Among the three lymph node (LN) staging systems, LODDS showed the highest accuracy in predicting CSS for MTC. In the training cohort, the C-index of the LODDS-based nomogram was 0.895. The AUCs were 0.949, 0.917, 0.925, and 0.901 for predicting 1-, 3-, 5- and 10-year CSS, respectively. The calibration plots and DCA showed the superior clinical applicability of the nomogram. These results were verified in the validation cohort. As an independent prognostic factor for MTC, LODDS demonstrated superior prognostic efficiency over N status and PLNN. This LODDS-based nomogram yielded better performance than the AJCC tumor-node-metastasis (TNM) staging system in predicting CSS after surgery for MTC.

Accurate staging plays a pivotal role in cancer care. The lymph node (LN) ratio (LNR) and the log odds of positive LNs (LODDS) have been suggested as alternatives to the N staging since the TNM system has the risk of stage migration. The prognostic significance of LNR and LODDS in young patients with gastric cancer (GC) has not been reported. This study aims to investigate the correlations between LNR and LODDS and survival of young patients with GC, and compare the predictive performance of these LN staging methods. GC patients before the age of 40 from 2004 to 2016 in the Surveillance, Epidemiology and End Results database were enrolled. The prognostic evaluation of the N factor, LNR and LODDS was compared using the time-dependent receiver operating characteristic (ROC) analysis, area under the curve (AUC), C-index and Akaike information criterion (AIC). Multivariate survival analysis identified that the LNR and LODDS were significantly independent prognostic indicators for overall survival (OS) in young patients with GC and in the subgroups comprised of patients with ≤15 LNs examined. The time-dependent ROC curves of the LNR and LODDS were continuously superior to that of the N factor in predicting OS during the observation period. And the AUCs revealed that the predictive accuracy of the LNR and LODDS was remarkably superior to the N factor at 1 and 3 years (P<0.05). The model incorporating LNR or LODDS had higher C-index and lower AIC when comparing to the model incorporating the N factor. The LNR and LODDS improve accuracy of survival risk prediction in young patients with GC when comparing to the N factor. These two novel LN classification methods should be considered as alternatives to the N staging for the prognostic prediction of young patients with GC.

Background&lt;p&gt;The metastatic status of regional lymph nodes is an effective risk factor for the prognosis of distal cholangiocarcinoma (dCCA). But existing lymph node staging is not accurate enough and is susceptible to interference. This study aims to explore the predictive ability of the log odds of positive lymph nodes (LODDS) staging system of dCCA compared with existing lymph node staging systems.&lt;/p&gt;Methods&lt;p&gt;A total of 928 dCCA patients were selected from the Surveillance, Epidemiology, and End Results (SEER) database as the training cohort, and 207 dCCA patients from West China Hospital who underwent surgery were reviewed as the validation cohort. The least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression were conducted to identify the most meaningful factors relevant to prognosis. The performance of four lymph node stage systems was compared by a model-based approach.&lt;/p&gt;Result&lt;p&gt;Age at diagnosis, pathological grade, American Joint Committee on Cancer (AJCC) tumor 7th T stage, tumor size, radiotherapy, chemotherapy, and lymph node stage system were independent prognostic factors. The model with the LODDS system had a better model fit with the highest C-index (0.679) and 1-/3-/5- area under the receiver operating characteristic curve (AUC) (0.739/0.671/0.658) as well as the lowest Akaike information criterion (AIC) (5,020.52). External validation results from 207 dCCA patients showed a C-index of 0.647 and 1-/3-/5-AUC of 0.740/0.683/0.589. Compared with the lymph node ratio (LNR), AJCC 8th N system, and 7th N system, the 5-year net reclassification improvement (NRI) of the LODDS system was 0.030 (95% CI: −0.079 to 0.147), 0.042 (95% CI: −0.062 to 0.139), and 0.040 (95% CI: −0.057 to 0.146), respectively. The integrated discrimination improvement (IDI) of LODDS improved compared with the LNR model (0.016; 95% CI: −0.001 to 0.036), AJCC 8th N system (0.020; 95% CI: 0.003–0.037), and AJCC 7th N system (0.019; 95% CI: 0.002–0.036). Decision curve analysis (DCA) also shows a greater net benefit of LODDS. In lymph node-negative patients, LODDS reveals a positive linear relationship with the hazard ratio (HR). The stage capacity of LODDS in a subgroup analysis stratified by examined lymph node number (ELNN) was consistent.&lt;/p&gt;Conclusions&lt;p&gt;The LODDS lymph node stage system has superior predictive performance as compared with the LNR, AJCC 7th, and 8th lymph node stage systems. Meanwhile, LODDS has a more detailed staging ability and good stability.&lt;/p&gt;

The purpose of this study was to compare the predictive value of different lymph node staging systems and to develop an optimal prognostic nomogram for predicting distant metastasis in pancreatic ductal adenocarcinoma (PDAC). Our study involved 6364 patients selected from the Surveillance, Epidemiology, and End Results (SEER) database and 126 patients from China. Independent risk factors for distant metastasis were screened by univariate and multivariate logistic regression analyses, and a model-based comparison of different lymph node staging systems was conducted. Furthermore, we developed a nomogram for predicting distant metastasis using the optimal performance lymph node staging system. The lymph node ratio (LNR), log odds of positive lymph nodes (LODDS), age, primary site, grade, tumor size, American Joint Committee on Cancer (AJCC) 7th Edition T stage, and radiotherapy recipient status were significant predictors of distant metastasis in PDAC patients. The model with the LODDS was a better fit than the model with the LNR. We developed a nomogram model based on LODDS and six clinical parameters. The area under the curve (AUC) and concordance index (C-index) of 0.753 indicated that this model satisfied the discrimination criteria. Kaplan–Meier curves indicate a significant difference in OS among patients with different metastasis risks. LODDS seems to have a superior ability to predict distant metastasis in PDAC patients compared with the AJCC 8th Edition N stage, PLN and LNR staging systems. Moreover, we developed a nomogram model for predicting distant metastasis. Clinicians can use the model to detect patients at high risk of distant metastasis and to make further clinical decisions.

BACKGROUND/AIMS:The N-stage of TNM systems considers only the number of metastatic lymph nodes (NMLN) in breast cancer (BC).However, new lymph node parameters refer to the number of harvested lymph nodes (NHLN) and negative lymph nodes (NNLN), which have had an increasing significance in the current literature.This study aimed to compare NHLN, NNLN, lymph node ratio (LNR), modified lymph node ratio (mLNR), and log odds of positive lymph nodes (LODDS) against the standard American Joint Committee on Cancer (AJCC) N-stage for the prognosis of BC patients. MATERIALS AND METHODS:This study was designed retrospectively.The socio-demographic data, clinical features, histopathological factors, treatment modalities, receptor status of BC, and lymph node related parameters (AJCC N, LNR, mLNR, LODDS) were identified.Then, lymph node related parameters were compared for cancer-related mortality (CRM), cancer recurrence, disease-free survival (DFS), and overall survival (OS). RESULTS:Eight hundred seven women who underwent surgery for BC were included in this study according to its eligibility criteria.The mean follow-up period was 113.3474.85(range: 6-378) months.The NHLN was 21.249.22,the NMLN was 4.857.38,the NNLN was 16.399.48,the LNR was 0.230.29, the mLNR was 5.387.38 and the LODDS was -0.740.80 on average.During the follow-up period, 42 (5.2%)patients had local recurrence, 188 (23.3%) had distant metastases, and 252 (31.2%) patients died due to BC. NMLN, LNR, mLNR, and LODDS were found to be significantly higher, and NNLN was significantly lower in those patients with cancer recurrence and CRM (p<0.001).AJCC N-stages, and also LNR, mLNR, and LODDS groups according to the calculated cut-off values, were significant for DFS and OS according to survival analysis.In Cox regression analysis, only LODDS was a significant independent risk factor for OS [p=0.014,heart rate (HR)=3.78,95% confidence interval (CI) for HR: 1.30-10.94)]. CONCLUSION:The results indicated that LODDS was more successful compared to other lymph node staging systems, especially for OS.However, randomized prospective controlled studies with larger samples and homogeneous study groups are needed to create standard classification systems as alternatives to AJCC N.

Objective: To compare the prognostic predictive performance of six lymph node (LN) staging schemes: American Joint Committee on Cancer (AJCC) N stage, number of retrieved lymph nodes (NRLN), number of positive lymph nodes (NPLN), number of negative lymph nodes (NNLN), lymph node ratio (LNR), and log odds of positive lymph nodes (LODDS) among node-positive endometrioid endometrial cancer (EEC) patients.Methods: A total of 3,533 patients diagnosed with node-positive EEC between 2010 and 2016 from the Surveillance, Epidemiology, and End Results (SEER) database were retrospectively analyzed. We applied X-tile software to identify the optimal cutoff value for different staging schemes. Univariate and multivariate Cox regression models were used to assess the relationships between different LN schemes and survival outcomes [disease-specific survival (DSS) and overall survival (OS)]. Moreover, Akaike information criterion (AIC) and Harrell concordance index (C-index) were used to evaluate the predictive performance of each scheme in both continuous and categorical patterns.Results: N stage (N1/N2) was not an independent prognostic factor for node-positive EEC patients based on multivariate analysis (DSS: p = 0.235; OS: p = 0.145). Multivariate model incorporating LNR demonstrated the most superior goodness of fit regardless of continuous or categorical pattern. Regarding discrimination power of the models, LNR outperformed other models in categorical pattern (OS: C-index = 0.735; DSS: C-index = 0.737); however, LODDS obtained the highest C-index in continuous pattern (OS: 0.736; DSS: 0.739).Conclusions: N stage (N1/N2) was unable to differentiate the prognosis for node-positive EEC patients in our study. However, LNR and LODDS schemes seemed to have a better predictive performance for these patients than other number-based LN schemes whether in DSS or OS, which revealed that LNR and LODDS should be more helpful in prognosis assessment for node-positive EEC patients than AJCC N stage.

BackgroundThis study aimed to compare the predictive efficacy of four different lymph node (LN) staging systems on the overall survival (OS) of patients with surgically resected perihilar cholangiocarcinoma (pCCA), and construct a novel prognostic nomogram to predict OS in pCCA patients.MethodsPatients with pCCA that underwent surgical resection between 2004 to 2016 were selected from the Surveillance, Epidemiology, and End Results (SEER) database (n=1,173). Patients were randomly divided into a modeling cohort and an internal verification cohort. To compare the prognostic efficacy of four different N staging systems [American Joint Committee on Cancer (AJCC) 7th and 8th edition N stages, lymph node ratio (LNR), and log odds of positive lymph nodes (LODDS)], we used three different evaluation methods: Harrell’s index of concordance (C-index), Akaike information criterion (AIC), and area under the receiver operating characteristic (ROC) curve (AUC). Multivariate analysis was used to identify independent prognostic factors and validate LODDS in the modeling cohort. A nomogram was then constructed to predict 1-, 3-, and 5-year survival. The nomogram was validated using Harrell’s C-indexes and calibration curves.ResultsOf the four different N staging methods, LODDS was considered to be the most effective LN staging system for evaluating the prognosis of patients with surgically resected pCCA, according to the values calculated for C-index, AUC, and AIC. After validation by C-indexes and calibration curves, the constructed nomogram accurately predicted the OS of pCCA patients.ConclusionsFor patients with surgically resected pCCA, LODDS was found to be the most accurate N staging system. The novel LODDS-based nomogram constructed in this study provides an accurate method for predicting patient survival in pCCA.

Methods such as the number of positive lymph nodes (nPLN), lymph node ratio (LNR), and log odds of positive lymph nodes (LODDS) are used to predict prognosis in patients with non-small cell lung cancer (NSCLC). We hypothesized that LODDS could be a superior independent predictor of prognosis and aimed to compare its effectiveness with nPLN and LNR in predicting survival outcomes in stage I-IIIA NSCLC patients. We utilized data from the Surveillance, Epidemiology, and End Results (SEER) 17 registry (2010-2019) to study NSCLC patients, focusing on those who underwent surgery with confirmed lymph node involvement (N1 or N2 disease). We aimed to compare overall survival (OS) and cancer-specific survival (CSS) based on nPLN, LNR, and LODDS. Kaplan-Meier and Cox regression analyses were employed to evaluate survival, with thresholds determined using X-tile software. An XGBoost model was constructed to predict overall survival in patients using three features: LODDS, LNR, and PLN. SHapley Additive exPlanations (SHAP) analysis was applied to assess feature importance and provide interpretable insights into the model's predictions. The study analyzed 3,132 eligible NSCLC patients from the SEER database, predominantly male (53.07%) with adenocarcinoma (43.65%) or squamous cell carcinoma (29.76%). Survival outcomes were assessed using nPLN, LNR, and LODDS. LODDS showed superior predictive value for both OS and CSS compared to nPLN and LNR, as indicated by a larger Log Likelihood Ratio (LLR) and smaller Akaike Information Criterion (AIC). Higher scores on npLN, LNR, and LODDS were strongly related with a poorer prognosis, according to Kaplan-Meier analyses (P < 0.001). The SHAP (SHapley Additive exPlanations) analysis of the XGBoost model demonstrated that the LODDS exhibited the highest SHAP values (0.25) for predicting overall survival in patients, consistently outperforming the LNR and the number of nPLN across both training and validation datasets. Compared to the nPLN and LNR staging systems, LODDS demonstrates superior prognostic power for patients with stage I-IIIA NSCLC undergoing lobectomy or pneumonectomy. By integrating both positive and negative lymph node information, LODDS offers a refined risk stratification that is particularly valuable in cases with high lymph node heterogeneity.

Comparison of 4 lymph node staging systems for the prognostic prediction of esophagogastric junction adenocarcinoma with ≤15 retrieved lymph nodes

BackgroundElderly 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.MethodsUsing 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.ResultsLODDS demonstrated superior prognostic discrimination compared to pN and LNR across all cohorts (training C-index: LODDS 0.602 vs. pN 0.573 vs. LNR 0.579). The final nomogram incorporated race, tumor stage (T stage), metastasis stage (M stage), chemotherapy status, and LODDS. It showed robust performance: training C-index =0.647 [95% confidence interval (CI): 0.622–0.672], internal validation C-index 0.650 (95% CI: 0.611–0.690), and external validation C-index =0.729 (95% CI: 0.687–0.770). Calibration curves indicated strong agreement between predicted and observed survival. LODDS maintained superior stratification within the ≥80-year subgroup. Risk stratification based on the nomogram significantly differentiated survival outcomes (log-rank P<0.001).ConclusionsLODDS 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.