Prognostic impact of nephrectomy and a prediction model for estimating the survival benefit of nephrectomy for patients with clear cell renal cell carcinoma (ccRCC)

Introduction

In the past few decades, renal cancer incidence has progressively increased globally, exhibiting an approximate 1% annual increase in diagnoses (1,2). Clear cell renal cell carcinoma (ccRCC), the predominant RCC subtype originating from renal tubular epithelium, accounts for 70–80% of renal malignancies (3). ccRCC exhibits high aggressiveness with cancer-attributable mortality reaching 8.2% (4). Although nephrectomy remains the therapeutic standard, it is associated with substantial perioperative risks, including hemorrhagic complications and postoperative morbidity. Technological advancements have produced alternative therapeutic modalities such as combined targeted-immunotherapy, radiofrequency ablation, and interventional embolization. These personalized approaches confer critical clinical benefits, including renal parenchymal preservation, fewer procedural hazards, survival extension, and enhanced quality of life. Consequently, the necessity of aggressive nephrectomy for all ccRCC patients warrants careful reconsideration. However, reliable studies comparing survival outcomes of ccRCC patients treated and not treated with nephrectomy remain critically lacking, substantially impeding precision oncology implementation in ccRCC management (5).

Our study utilized population-scale data from the Surveillance, Epidemiology, and End Results (SEER) program and The Cancer Genome Atlas (TCGA) to bridge this gap. We aimed to evaluate nephrectomy-associated survival impacts in ccRCC cohorts and construct a novel integrated clinicopathological model to predict survival benefit from nephrectomy. We assessed the ability of the model to discriminate, calibrate, and provide clinical net benefit and found that the model demonstrated robust capability for personalized prognostic stratification in ccRCC management. We present this article in accordance with the TRIPOD reporting checklist (available at https://tau.amegroups.com/article/view/10.21037/tau-2025-550/rc).

Methods

Data collection

The 2000–2021 SEER database served as the primary data source for this study. After applying stringent inclusion criteria, 31,824 ccRCC patients with complete clinicopathological information were enrolled. An independent external validation cohort was established, containing 498 ccRCC patients from the TCGA database to enhance model generalizability. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.

Statistical analysis

Categorical variables were analyzed using the Chi-square test, and continuous variables were analyzed using the Student’s t-test. Propensity score matching (PSM) was performed to mitigate selection bias and balance baseline characteristics between the nephrectomy and non-nephrectomy groups in the SEER cohort.

Kaplan-Meier analysis was performed to compare survival differences between the nephrectomy and non-nephrectomy groups within the SEER cohort. Multivariate Cox regression analysis was subsequently conducted to identify independent risk factors for survival.

Univariate and multivariate Cox regression analyses of the SEER cohort were performed to develop and internally validate a prognostic nomogram for nephrectomy-treated patients. The resulting model was then externally validated using the TCGA data. The model’s performance was rigorously assessed. Calibration curves were used to assess agreement between predicted and observed survival probabilities. Receiver operating characteristic (ROC) curves and the concordance index (C-index) were used to quantify the discriminative ability, and decision curve analysis (DCA) was used to assess the clinical utility.

All analyses were performed using R (v4.3.1) and SPSS (v26.0), with statistical significance determined by a two-tailed P value <0.05.

Results

Table 1 presents the clinicopathological characteristics of patients from the SEER database before and after PSM. After PSM, the matched cohort comprised 1,076 patients in both the nephrectomy and non-nephrectomy groups. Following matching, no significant differences were observed in age, gender, tumor (T) stage, node (N) stage, or metastasis (M) stage between the groups. However, significant differences in these characteristics existed before PSM. Crucially, a significant difference in overall survival (OS) between the two groups was evident both before and after PSM.

Kaplan-Meier analysis was performed on the SEER cohort to assess the survival benefit of nephrectomy in ccRCC patients. Nephrectomy significantly prolonged OS compared to non-nephrectomy treatment [hazard ratio (HR) =0.415, P<0.05; Figure 1]. Subsequent multivariate Cox regression analysis, adjusted for clinicopathological confounders, confirmed nephrectomy as an independent protective factor for OS in ccRCC patients (HR =0.322, P<0.05; Table 2).

Figure 1 Kaplan-Meier curves of OS in ccRCC patients stratified by nephrectomy in the SEER cohort. ccRCC, clear cell renal cell carcinoma; OS, overall survival; SEER, the Surveillance, Epidemiology, and End Results program.

Subgroup analyses, stratified by age, gender, tumor laterality, tumor stage, TNM stage and differentiation grade, were conducted to validate the applicability of these findings across diverse patient profiles. Figure 2 illustrates consistent survival benefits associated with nephrectomy treatment in all subgroups. These results indicate that while the benefit magnitude varied, nephrectomy appeared to confer survival advantages to all subgroups of ccRCC patients.

Figure 2 Forest plots showing the difference of OS between ccRCC patients with nephrectomy and without nephrectomy in subgroup stratified by clinicopathological characteristics in SEER cohort. ccRCC, clear cell renal cell carcinoma; CI, confidence interval; HR, hazard ratio; M, metastasis; N, node; OS, overall survival; SEER, Surveillance, Epidemiology, and End Results; T, tumor.

Given our previous findings on the crucial role of nephrectomy in prolonging patients’ survival, we further explored the factors influencing the efficacy of nephrectomy treatment. Table 3 presents the results of univariate and multivariate Cox regression analyses. The results indicated that age, gender, tumor grade, TNM stage and differentiation grade independently predicted OS in nephrectomy-treated ccRCC patients (P<0.05).

A prognostic nomogram was designed to predict OS in post-nephrectomy ccRCC cases. It was derived from the multivariate Cox regression model, and incorporated the above independent established predictors. The SEER cohort was randomized into training (n=21,501) and internal validation (n=9,215) subsets at a 7:3 ratio. Additionally, patients from the TCGA database constituted an external validation cohort (Figure 3). The demographic and clinical characteristics of these cohorts are presented in Table 4.

Figure 3 Flowchart of the predictive model development process. ccRCC, clear cell renal cell carcinoma; PSM, propensity score matching; SEER, Surveillance, Epidemiology, and End Results; TCGA, The Cancer Genome Atlas.

The predictors in the nomogram consisted of age, gender, differentiation grade, TNM and tumor stage (Figure 4). The model demonstrated strong predictive accuracy in the training cohort [C-index 0.734, 95% confidence interval (CI): 0.727–0.741], the internal validation cohort (C-index 0.733, 95% CI: 0.722–0.744) and the external validation cohort (C-index 0.785, 95% CI: 0.747–0.823). These findings were further supported by ROC analysis (Figure 5A-5C). The calibration curves revealed excellent agreement between the predicted and observed OS probabilities (Figure 6A-6C) and the DCA comparing the nomogram to individual clinicopathological risk factors consistently showed that the nomogram provided the highest net benefit across a wide range of OS probability thresholds in all cohorts (Figure 7A-7C).

Figure 4 Nomogram for predicting overall survival in ccRCC patients with nephrectomy. ccRCC, clear cell renal cell carcinoma; M, metastasis; N, node; T, tumor.

Figure 5 ROC curves of the nomogram and individual clinicopathological characteristics. ROC curve of 1-year (left), 3-year (middle), and 5-year (right) OS in training cohort (A), internal validation cohort (B) and external validation cohort (C). AUC, area under the curve; M, metastasis; N, node; ROC, receiver operating characteristic; T, tumor.

Figure 6 Calibration curves of the nomogram. Calibration curve of 1-year (left), 3-year (middle), and 5-year (right) OS in training cohort (A), internal validation cohort (B) and external validation cohort (C). OS, overall survival.

Figure 7 DCA curves of the nomogram. DCA curve of 1-year (left), 3-year (middle), and 5-year (right) OS in training cohort (A), internal validation cohort (B) and external validation cohort (C). DCA, decision curve analysis; M, metastasis; N, node; OS, overall survival; T, tumor.

The Karakiewicz nomogram is a widely utilized predictive model for survival outcomes in patients with localized renal cell carcinoma (6). Therefore, we conducted comparative analyses against this predictive model to validate our model’s prognostic accuracy in ccRCC patients. Our nomogram demonstrated significantly superior discriminative ability across 1-, 3-, and 5-year survival predictions within both the training and internal validation cohorts compared to the Karakiewicz nomogram (Figure 8A,8B). Collectively, these results confirmed the enhanced risk-stratification capability of our nomogram within the nephrectomy-treated ccRCC patient population.

Figure 8 ROC curves of the nomogram and the Karakiewicz nomogram. ROC curve of 1-year (left), 3-year (middle), and 5-year (right) OS in training cohort (A) and internal validation cohort (B). AUC, area under the curve; OS, overall survival; ROC, receiver operating characteristic.

Discussion

This study evaluated the impact of nephrectomy on OS in patients with ccRCC. The results demonstrated that a consistent survival benefits of nephrectomy across all ccRCC pathological characteristics. While non-nephrectomy treatments such as targeted therapy represent viable alternatives for elderly patients and those with early-stage, or advanced disease, nephrectomy remains a primary treatment approach for these patients.

As the most common subtype of RCC, ccRCC is recognized for its aggressive behavior. Despite adherence to postoperative surveillance guidelines, the 5-year survival rate for patients remains as low as 12% (7). Consequently, accurately predicting individual cancer-specific mortality risk following nephrectomy is crucial for tailoring treatment and personalizing surveillance strategies (8). Although previous studies have reported several nomograms predicting OS in patients with ccRCC (9-12), debate persists regarding the independent prognostic factors for ccRCC patients treated with nephrectomy. In this study, we focused on the clinical and pathological factors associated with ccRCC. Univariate and multivariate Cox regression analyses confirmed four clinicopathologic factors as independent risk factors for OS in nephrectomy-treated ccRCC patients by univariate and multivariate Cox regression analyses, including age, gender, tumor stage and grade.

Age is consistently recognized as a significant prognostic factor across malignancies and is a key factor related to prognosis in patients with RCC (13,14). Recently, Liao et al. evaluated the risk factors of ccRCC patients in different age cohorts and identified age as an independent predictor for both OS and cancer-specific survival (CSS) (15). An analysis of localized ccRCC patients by Dabestani et al. revealed significantly elevated cancer-specific mortality risk in patients >75 years compared to those aged 18–60 or 60–75 years (16). Consistent with previous studies, our study showed age as an independent predictor of OS in nephrectomy-treated ccRCC patients. We further established gender as an independent risk factor for OS in nephrectomy-treated ccRCC patients. These gender-based survival disparities appear to be multifactorial in origin. First, some tumor-associated genes show different expression between males and females, particularly those regulating immune, inflammatory, and metabolic pathways (17). Second, divergent sex hormone levels constitute another significant determinant of survival outcomes (18). Finally, RCC-related risk factors, including viral hepatitis, chronic kidney disease, hypertension, and smoking behaviors, demonstrate male predominance (19,20). These elements collectively potentiate ccRCC pathogenesis and progression, thereby exacerbating gender-specific survival differences.

Among the prognostic determinants, tumor grade and TNM stage constitute critical determinants for assessing the prognosis of patients with malignancies. Previous studies have consistently incorporated these parameters into prognostic models. Aligning with established literature, our analysis confirmed that advanced tumor stage and higher grade independently predicted poorer OS in nephrectomy-treated ccRCC patients and were key components of our predictive nomogram. The multivariate Cox regression revealed longer OS in patients with grade II tumors compared to other grades. However, univariate analysis demonstrated no significant OS difference between grades I and II, indicating that the detrimental survival impact becomes markedly pronounced at higher tumor grades (grades III–IV).

Several predictive models have been established for predicting survival outcomes in RCC patients. Among these, we selected the Karakiewicz nomogram for the comparative assessment of predictive performance, as all its incorporated predictors were available within our cohorts. The Karakiewicz nomogram integrates TNM stage, tumor grade and tumor size as key prognostic variables (21). Our predictive model exhibited superior discriminative ability for OS in nephrectomy-treated ccRCC patients compared to the Karakiewicz nomogram. However, it is important to note that the Karakiewicz nomogram was developed and validated for predicting CSS in a cohort of patients with localized renal cell carcinoma, encompassing the major histological subtypes (clear-cell, papillary, and chromophobe RCC). In contrast, the present nomogram was specifically designed for ccRCC and included patients across all disease stages, from localized to metastatic. The superior discriminative ability of our model is likely attributable to two key factors: its specificity for a single histological entity (ccRCC) with a distinct disease biology, and its applicability to the prognostically heterogeneous advanced disease population. Therefore, our nomogram may provide a valuable tool for refining individual prognosis following nephrectomy in patients with advanced ccRCC. This could aid in personalizing postoperative surveillance intensity, improving patient counseling regarding disease trajectory, and potentially informing risk-adapted strategies for adjuvant or metastasectomy timing.

Although our study developed a predictive nomogram for postoperative OS encompassing both localized and advanced ccRCC, several limitations warrant consideration. First, despite the substantial size of the SEER database, the cohort of non-nephrectomy managed ccRCC patients was limited, potentially restricting generalizability. Second, while PSM balanced the available clinicopathologic features, some unmeasured confounders could have introduced residual bias, particularly performance status and comorbidities absent in the SEER data. Third, for patients with metastatic disease, the lack of detailed data on systemic therapy regimens (e.g., tyrosine kinase inhibitors and immunotherapy) in the SEER database is a constraint, as these treatments profoundly influence OS. Future studies integrating treatment variables are warranted to further refine prognostic assessment in this subgroup. Fourth, the term “nephrectomy” used in this study was based on registry data and encompassed both partial and radical nephrectomies without distinction. Consequently, our findings should be interpreted as reflecting the overall oncological outcomes associated with the principle of surgical resection as a treatment strategy. Future studies, with access to more granular surgical data are warranted to compare the long-term survival outcomes between these two surgical approaches in the ccRCC population. Finally, our analysis did not account for competing risks, which may affect the interpretation of survival outcomes, especially in subgroups where non-cancer mortality is substantial, such as elderly or low-risk patients. Subsequent multicenter studies with expanded cohorts will specifically investigate CSS outcomes to further elucidate the distinct effects of nephrectomy on cancer-related mortality.

Conclusions

This study established nephrectomy as an OS-prolonging intervention for ccRCC patients irrespective of clinicopathological features, confirming its status as the primary therapeutic approach. We additionally developed and validated a prognostic nomogram for postoperative OS, which demonstrated robust reliability and immediate clinical applicability.

Acknowledgments

We would like to thank MogoEdit (https://www.mogoedit.com) for its English editing during the preparation of this manuscript.

Footnote

Reporting Checklist: The authors have completed the TRIPOD reporting checklist. Available at https://tau.amegroups.com/article/view/10.21037/tau-2025-550/rc

Peer Review File: Available at https://tau.amegroups.com/article/view/10.21037/tau-2025-550/prf

Funding: This study was supported by National Natural Science Foundation of China (No. 82172777).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tau.amegroups.com/article/view/10.21037/tau-2025-550/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.

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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