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

Introduction

Bladder cancer ranks as the tenth most common malignancy globally. Global Cancer Statistics 2020 reported over 570,000 new cases, with muscle-invasive bladder cancer (MIBC) patients exhibiting poor prognoses and a 5-year overall survival (OS) rate below 50% (1,2). The current standard treatment for MIBC is radical cystectomy (RC) combined with pelvic lymph node dissection (PLND) (3). Lymph node metastasis is a critical determinant of prognosis in MIBC, with clinical data indicating that approximately 25–30% of MIBC patients harbor regional lymph node metastasis at the time of RC (4). Consequently, precise preoperative assessment of lymph node status is essential for prognostic stratification and guiding individualized therapeutic strategies.

Age is a significant independent risk factor for bladder cancer. Epidemiological studies in the United States indicate a median age at diagnosis of 73 years (5,6). With accelerating global population aging, the incidence of bladder cancer among elderly patients is projected to rise. Notably, this population receives standard treatment regimens at significantly lower rates compared to younger patients. Most studies define elderly bladder cancer patients as those aged ≥70 years (7-10). Due to substantial clinical heterogeneity within this elderly population, the traditional American Joint Committee on Cancer (AJCC) tumor-node-metastasis (TNM) staging system may have limitations in accurately predicting survival outcomes. Therefore, there is an urgent need to develop novel prognostic models to enable more precise individualized prognosis assessment and provide reliable evidence for clinical decision-making in elderly bladder cancer patients.

The traditional pathological lymph node (pN) stage system, based solely on the number of positive lymph nodes (PLNs), may lead to staging inaccuracies due to variations in the extent of lymph node dissection or the number of lymph nodes retrieved (11). The precise counts of examined lymph nodes (ELNs) and PLNs are often overlooked, yet represent crucial clinicopathological information for prognostic prediction. Numerous studies have focused on developing predictive models incorporating novel lymph node metrics. The lymph node ratio (LNR) and the log odds of PLNs (LODDS) have been validated in multiple studies to enhance the prognostic assessment of lymph node status across various malignancies (12-14). LNR is defined as the ratio of PLN to ELN, while LODDS represents the logarithm of the ratio of PLN to negative lymph nodes. In bladder cancer, the prognostic value of both LNR and LODDS has also been established (15,16). Importantly, several small-scale studies suggest that LNR and LODDS may offer superior prognostic discrimination compared to the traditional pN system (16-18). Given that elderly bladder cancer patients experience higher morbidity and mortality rates than younger cohorts (19), LNR and LODDS may hold particular clinical significance for this group. However, research specifically investigating LNR and LODDS in elderly bladder cancer patients remains limited.

This study leverages large-scale population data from the National Cancer Institute’s Surveillance, Epidemiology, and End Results (SEER) database to evaluate the prognostic value of pN, LNR, and LODDS in elderly bladder cancer patients following RC. Furthermore, to mitigate redundancy and overfitting, we employed least absolute shrinkage and selection operator (LASSO) regression to identify the most significant factors associated with OS for nomogram construction. External validation was performed using an independent cohort from our institution. We present this article in accordance with the TRIPOD reporting checklist (available at https://tau.amegroups.com/article/view/10.21037/tau-2025-475/rc).

Methods

Patients and study design

Data were extracted from the SEER database (http://seer.cancer.gov/seerstat), representing approximately 30% of the United States population. The database provides detailed clinicopathological characteristics, demographic information, and survival outcomes. Using SEER*Stat software (version 9.0.41), we identified 133,632 bladder cancer patients [International Classification of Diseases for Oncology, third edition (ICD-O-3) codes C67.0–C67.9] diagnosed between 2004 and 2015 across 17 registries. Inclusion criteria were: (I) histopathologically confirmed bladder cancer; (II) first primary malignant tumor; and (III) treatment with RC (surgery codes A50–80). Exclusion criteria comprised: (I) age <70 years; (II) missing or zero survival time; (III) missing TNM stage or T0 disease; (IV) unknown lymph node dissection status or PLN count; (V) missing baseline characteristics (e.g., age, sex); and (VI) unknown surgical. After exclusions, 1,018 eligible patients were included. Following established methodologies (20,21), patients were randomly allocated 7:3 into training (n=712) and internal validation (n=306) cohorts. This allocation optimizes model stability (larger training set) while maintaining adequate validation power to assess generalizability and prevent overfitting.

For external validation, 260 elderly bladder cancer patients treated at The Affiliated Hospital of Qingdao University (February 2013 to December 2021) meeting identical inclusion/exclusion criteria were enrolled. Follow-up continued until January 2025. Three independent investigators performed data collection: two conducted initial extraction, while the third independently verified data accuracy and consistency. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Ethics Committee of The Affiliated Hospital of Qingdao University (No. QYFYWZLL30231) and individual consent for this retrospective analysis was waived. Patient selection is detailed in Figure 1.

Figure 1 Study flowchart illustrating patient selection process and cohort allocation. SEER, Surveillance, Epidemiology, and End Results; TNM, tumor-node-metastasis.

Variables

Collected variables included: baseline demographics (age at diagnosis, sex, race), tumor characteristics [size, tumor stage (T stage), node stage (N stage), metastasis stage (M stage)], treatment information (chemotherapy status, surgical procedure), number of ELNs, number of PLNs, and survival variables (vital status, survival time). LNR was calculated as PLN/ELN. LODDS was computed as log[(PLN + 0.5)/(ELN − PLN + 0.5)]. The primary endpoint was OS, defined as the interval from diagnosis to death from any cause.

Statistical analysis

Continuous variables were presented as mean ± standard deviation (SD) or median [interquartile range (IQR)]. Categorical variables were reported as frequencies (percentages). Predictive performance of LODDS, LNR, and pN stage was compared using time-dependent area under the curve (AUC) and Harrell’s concordance index (C-index). Univariate Cox regression and LASSO regression identified variables significantly associated with OS. Significant predictors from LASSO were entered into multivariable Cox proportional hazards regression to determine independent prognostic factors. Using these factors, a nomogram predicting 1-, 3-, and 5-year OS was constructed with the rms package (v6.7.1) in R. Subsequently, the training cohort was stratified into subgroups (70–79 years, n=522; ≥80 years, n=190) based on age for additional analysis.

Model performance was assessed via internal and external validation. Discrimination was evaluated using the C-index and time-dependent receiver operating characteristic (ROC) curves. Calibration curves assessed agreement between predicted and observed survival probabilities. Bootstrap resampling (1,000 repetitions) further validated discrimination and calibration. Patients were stratified into low-, intermediate-, and high-risk groups based on nomogram-derived risk scores using optimal cutoffs determined by X-tile software (v3.6.1, Yale University, New Haven, CT, USA).

All analyses were performed using SPSS 26.0 (IBM Corp., Armonk, NY, USA) and R software (v4.4.3, R Foundation for Statistical Computing, Vienna, Austria). A two-sided α level of 0.05 defined statistical significance.

Results

Patient baseline characteristics

A total of 1,018 eligible elderly bladder cancer patients from the SEER database were included. Patients were randomly allocated to a training cohort (n=712) and internal validation cohort (n=306). An additional external validation cohort comprised 260 patients from our institution. Baseline characteristics differed significantly across cohorts (χ² test, detailed in Table 1). Within the SEER cohort, 76.03% (774/1,018) were male and 88.90% (905/1,018) were White. Pathologically, 70.24% (715/1,018) had T2/T3 disease and 63.75% (649/1,018) had tumors >3 cm. In the external cohort, 83.50% (217/260) were male, 59.62% (155/260) had T2/T3 disease, and 60.80% (158/260) had tumors >3 cm. Comprehensive clinicopathological features are presented in Table 1.

Predictive performance of pN, LNR, and LODDS

As shown in Table 2, the prognostic performance of pN stage, LNR, and LODDS was evaluated across cohorts. In the training cohort, Harrell’s C-index values were 0.573 for pN, 0.579 for LNR, and 0.602 for LODDS. LODDS demonstrated superior discrimination, evidenced by higher time-dependent AUC values for 1-, 3-, and 5-year OS compared to pN and LNR (LODDS: AUC =0.624, 0.651, 0.657; pN: AUC =0.614, 0.620, 0.607; LNR: AUC =0.616, 0.629, 0.619). Consistent with prior studies (22,23), LODDS outperformed conventional lymph node staging metrics in our cohort.

Prognostic factor selection and nomogram construction

Nine clinical parameters were initially assessed for association with OS in the training cohort. Univariate Cox analysis revealed significant associations for eight parameters (P<0.05), except tumor size (P=0.08). LASSO regression of significant univariate predictors identified seven non-zero coefficient variables: sex, race, T stage, N stage, M stage, chemotherapy status, and LODDS (Figure 2A,2B). These independent prognostic factors were incorporated into a multivariable Cox model (Table 3) to develop a nomogram predicting 1-, 3-, and 5-year OS (Figure 2C). Nomogram utilization involves: (I) assigning points per variable level; (II) summing total points; and (III) projecting total points to the survival probability axis.

Figure 2 Feature selection using LASSO Cox regression and nomogram construction. (A) LASSO coefficient profiles of the eight candidate predictors. (B) Optimal parameter (λ) selection in the LASSO model via 10-fold cross-validation. (C) Prognostic nomogram for predicting 1-, 3-, and 5-year OS in elderly bladder cancer patients. LASSO, least absolute shrinkage and selection operator; LODDS, log odds of positive lymph nodes; M, metastasis; OS, overall survival; T, tumor.

Nomogram validation and calibration

The nomogram demonstrated robust discrimination: C-index was 0.647 [95% confidence interval (CI): 0.622–0.672] in training, 0.650 (95% CI: 0.611–0.690) in internal validation, and 0.729 (95% CI: 0.687–0.770) in external validation. Time-dependent ROC analysis further confirmed predictive accuracy: AUC values for 1-/3-/5-year OS were 0.702/0.718/0.714 (training, Figure 3A), 0.742/0.739/0.704 (internal validation, Figure 3B), and 0.770/0.767/0.759 (external validation, Figure 3C). Calibration curves showed good agreement between predicted and observed survival probabilities at 1, 3, and 5 years across all cohorts, closely aligning with the 45° reference line (Figure 4A-4C).

Figure 3 Prognostic accuracy of the nomogram assessed by time-dependent ROC curves and AUC values for OS at 1, 3, and 5 years in the training cohort (A), internal validation cohort (B), and external validation cohort (C). AUC, area under the curve; OS, overall survival; ROC, receiver operating characteristic.

Figure 4 Calibration curves of the nomogram for predicting OS: (A) 1-, 3-, and 5-year survival in the training cohort; (B) 1-, 3-, and 5-year survival in the internal validation cohort; (C) 1-, 3-, and 5-year survival in the external validation cohort. C-index, concordance index; CI, confidence interval; OS, overall survival.

Elderly subgroup analysis and LODDS prognostic value

Patients aged ≥80 years present unique management challenges due to frequent frailty, comorbidities, and treatment limitations. The training cohort was stratified into 70–79 years (n=522) and ≥80 years (n=190) subgroups. Baseline characteristics were balanced except for chemotherapy status (P<0.001, Table S1). LODDS maintained superior prognostic stratification over pN and LNR in both subgroups (Table S2). Optimal LODDS cutoffs (−3.05 and −1.61) identified via X-tile stratified patients into low-risk (≤−3.05), intermediate-risk (−3.05 to −1.61), and high-risk (>−1.61) groups with significantly distinct survival (log-rank P<0.05; Figure S1).

Risk stratification based on nomogram

Nomogram-derived risk scores were standardized to a 0–100 scale. Using X-tile-determined cutoffs (31.14 and 53.23), patients were stratified into low-risk (≤31.14), intermediate-risk (31.14–53.23), and high-risk (>53.23) groups (24). Kaplan-Meier analysis confirmed significantly different OS among risk groups (log-rank P<0.001; Figure 5), validating the clinical utility of this stratification system.

Figure 5 Kaplan-Meier curves demonstrating OS stratification by risk groups in the training cohort based on the nomogram prediction. CI, confidence interval; HR, hazard ratio; OS, overall survival; ref., reference.

Discussion

Bladder cancer represents a common genitourinary malignancy exhibiting rising incidence among elderly populations (1). Management and prognostic assessment of elderly patients pose significant challenges due to age-related physiological decline and frequent comorbidities. Notably, consensus on defining “elderly” remains limited (25). As life expectancy increases globally, the traditional threshold of 65 years inadequately reflects physiological status (26). Aligning with established methodology in RC studies (7-10,27-29), we defined elderly as ≥70 years. Evidence suggests distinct tumor biology and poorer prognosis in elderly bladder cancer patients compared to younger counterparts (30). To our knowledge, this is the first study to systematically evaluate the prognostic value of pN stage, LNR, and LODDS specifically in elderly patients undergoing RC, subsequently developing a novel nomogram for individualized survival prediction and clinical decision support.

Our analysis confirmed LODDS as a robust prognostic marker for OS in elderly bladder cancer patients. LODDS demonstrated superior discrimination (training C-index =0.602) compared to conventional pN staging (0.573) and LNR (0.579). Age-specific LODDS cutoffs (<−3.05, −3.05 to −1.61, >−1.61) derived via X-tile analysis further enhanced risk stratification. We therefore developed a multivariable nomogram incorporating LODDS alongside race, T stage, M stage, and chemotherapy status. The model demonstrated strong performance across cohorts: external validation yielded a C-index of 0.729 (95% CI: 0.687–0.770) with time-dependent AUC values of 0.770, 0.767, and 0.759 for 1-, 3-, and 5-year survival, respectively. These findings establish LODDS as a reliable prognostic biomarker, improving risk stratification precision and informing personalized therapeutic strategies for elderly patients.

While prior studies have identified prognostic factors in bladder cancer, systematic research focusing specifically on elderly populations remains scarce. Our study addresses this gap by developing a concise, validated prognostic model tailored to elderly patients. Existing evidence confirms the number of PLNs as a critical independent predictor of survival and disease progression in bladder cancer (31-34). Adequate lymph node dissection is paramount for accurate staging and prognosis; a multicenter retrospective study demonstrated that higher lymph node yield independently correlates with reduced recurrence risk after RC (35). Nevertheless, consensus regarding optimal lymph node dissection extent remains elusive (36).

LODDS has demonstrated superior prognostic performance over traditional nodal staging (pN) and metastatic lymph node count in multiple malignancies including gastric, breast, colorectal, and lung cancers (37-41). In bladder cancer, studies by Jin et al. (15) and Salari et al. (16) similarly established LODDS’s superiority over pN and LNR in muscle-invasive and urothelial subtypes, respectively. Our findings corroborate this, showing that elevated LODDS correlates significantly with adverse outcomes, potentially reflecting increased tumor burden or inadequate nodal assessment. This metric enhances prognostic precision, supporting individualized clinical decision-making.

The advent of immune checkpoint inhibitors has transformed management of node-positive (pN+) urothelial carcinoma (42). However, elderly patients often exhibit reduced treatment tolerance due to frailty, comorbidities, and heightened immune-related toxicity risks (43). Our subgroup analysis revealed only 18.9% of octogenarians received chemotherapy, underscoring therapeutic challenges in this vulnerable population. In this context, our LODDS-based nomogram provides critical risk stratification, effectively identifying patient subgroups with significant survival differences. This facilitates tailored management: optimizing palliative and surveillance strategies for high-risk patients ineligible for intensive therapy, while avoiding overtreatment in low-risk individuals, particularly those with treatment contraindications.

Notably, significant baseline differences existed between the SEER and external cohorts (T2–3 disease: 70.24% vs. 59.62%; chemotherapy administration: 30.45% vs. 6.90%), reflecting real-world heterogeneity. Crucially, the model maintained strong discrimination in the external cohort (C-index =0.729; 95% CI 0.687–0.770). Importantly, within the ≥80-year subgroup, LODDS (C-index =0.564) outperformed pN (C-index =0.551) and LNR (C-index =0.559), confirming the model’s applicability across diverse elderly populations.

Several limitations warrant consideration. First, the SEER database lacks granular chemotherapy details (e.g., neoadjuvant vs. adjuvant regimens), potentially influencing interpretation despite “chemotherapy status” being an independent predictor. Second, heterogeneity in lymph node dissection techniques across institutions may impact LODDS consistency, necessitating careful interpretation across surgical practices. Third, inherent selection bias in retrospective designs may limit generalizability. Finally, absence of detailed data on specific chemotherapeutic agents and immunotherapy regimens—critical factors influencing outcomes in node-positive disease—represents a significant constraint.

Conclusions

This study establishes the superior prognostic value of LODDS compared to traditional pN and LNR in elderly (≥70 years) bladder cancer patients undergoing RC. We developed and validated a novel, robust nomogram incorporating LODDS, alongside critical factors (race, T stage, M stage, chemotherapy status), for predicting 1-, 3-, and 5-year OS. The model demonstrated good discrimination (C-index: training 0.647, internal validation 0.650, external validation 0.729) and calibration across cohorts. LODDS provided enhanced risk stratification, particularly within the ≥80-year subgroup. This LODDS-based nomogram offers a valuable clinical tool for individualized survival prediction and treatment decision-making in this vulnerable, growing patient population. Limitations include retrospective design and lack of detailed chemotherapy/immunotherapy data.

Acknowledgments

The authors gratefully acknowledge the Surveillance, Epidemiology, and End Results (SEER) Program (http://seer.cancer.gov/seerstat) for providing open access to their comprehensive database, which is essential for this study. Data were accessed on March 26, 2025.

Footnote

Reporting Checklist: The authors have completed the TRIPOD reporting checklist. Available at https://tau.amegroups.com/article/view/10.21037/tau-2025-475/rc

Data Sharing Statement: Available at https://tau.amegroups.com/article/view/10.21037/tau-2025-475/dss

Peer Review File: Available at https://tau.amegroups.com/article/view/10.21037/tau-2025-475/prf

Funding: None.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tau.amegroups.com/article/view/10.21037/tau-2025-475/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Ethics Committee of The Affiliated Hospital of Qingdao University (No. QYFYWZLL30231) and individual consent for this retrospective analysis was waived.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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