Development and validation of a prognostic model for overall survival in pN0 esophageal cancer patients after neoadjuvant chemotherapy: a SEER database-based study

Introduction

Esophageal cancer (EC) is one of the most common gastrointestinal malignancies, with persistently high global incidence and mortality rates. According to statistical data, there were approximately 604,000 new cases of EC worldwide in 2020, accounting for 3.1% of all malignant tumors and ranking as the eighth most common cancer. Additionally, there were approximately 544,000 deaths attributed to EC, representing 5.5% of all cancer-related deaths and ranking as the sixth leading cause of cancer mortality (1). Squamous cell carcinoma (SCC) and adenocarcinoma (AC) together account for more than 95% of all EC cases (2). Among these, the incidence of esophageal SCC is particularly high in East Asia and Central Asia (3). In contrast, patients with esophageal AC are predominantly concentrated in Europe, North America, and Oceania (4). Due to the aggressive nature of EC and the prevalence of late-stage diagnosis, the implementation of early detection programs in high-incidence regions (such as China and Japan) is of critical importance. With advancements in endoscopic technology, the potential for early diagnosis has significantly improved (5). In recent years, significant advancements in surgical techniques and comprehensive treatment strategies have led to a notable reduction in perioperative complications and mortality rates as compared to the past. However, for patients with EC relying solely on surgical treatment, long-term survival outcomes remain suboptimal, with a 5-year survival rate of less than 25% (6).

Multiple large-scale prospective clinical trials have demonstrated that neoadjuvant chemotherapy combined with surgery significantly improves the R0 resection rate, increases the pathological complete response rate, and reduces the local recurrence rate (7-9). Based on these research findings, neoadjuvant therapy combined with surgery has been recommended as the standard treatment approach for EC (10). Factors such as the lymph node ratio, lymph node metastasis, and the number of lymph nodes dissected have been confirmed to be significant prognostic indicators for EC (11-14). Particularly in patients receiving neoadjuvant chemotherapy, the assessment of lymph nodes may significantly influence the final treatment outcomes. Therefore, determining the optimal number of lymph nodes to dissect is crucial for improving patient prognosis. However, existing models often overlook the distinct biological behaviors of SCC and AC, leading to heterogeneous recommendations for lymph node dissection thresholds (e.g., 12–25 lymph nodes across studies, with no clear distinction by histology). The TNM staging system for tumor lymph node metastasis is an important tool for assessing disease progression in EC patients. It categorizes tumor size, lymph node involvement, and distant metastasis, providing clinicians with comprehensive information about the patient’s disease status. However, it overlooks other factors that may influence prognosis. Research has shown that nutritional status (CONUT), inflammatory markers (NLR), tumor length, and diameter are all closely related to the prognosis of patients with EC. Therefore, relying solely on the TNM staging system may not provide a comprehensive prediction of patient survival (15). Clinically, accurate overall survival (OS) prediction for pN0 patients is essential for tailoring post-operative management, yet current tools lack precision due to limited integration of histology-specific lymph node thresholds and key clinical variables.

Therefore, this study aims to address these gaps by: (I) defining histology-specific lymph node dissection thresholds associated with improved survival; and (II) developing a nomogram incorporating lymph node count and clinical factors to enhance OS prediction in pN0 EC after neoadjuvant therapy. We present this article in accordance with the TRIPOD reporting checklist (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-910/rc).

Methods

Study population

The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.

The data for this study were obtained from the Surveillance, Epidemiology, and End Results (SEER) database, established by the National Cancer Institute in the United States. The SEER database includes cancer incidence and survival data from multiple regions across the United States, serving as a critical resource for cancer epidemiological research and clinical outcome analysis. We analyzed 17 registry regions from the SEER dataset. Through use of SEER*Stat software, the study population was retrieved based on tumor location and pathological type for the period spanning 2007 to 2021. Variables included in the study were age, sex, race, marital status, histopathology, tumor location, differentiation grade, T stage, M stage, TNM stage, number of lymph nodes, surgery, radiotherapy, chemotherapy, neoadjuvant chemotherapy, survival status, and survival months. The primary endpoint was OS, defined as the time from diagnosis to death or the last follow-up. Patients were stratified by histology (SCC/AC) and randomly divided into a training set (70%) and validation set (30%) to develop and test the nomogram, ensuring balanced distribution of key variables.

The inclusion criteria for patients were as follows: (I) diagnosis of primary EC; (II) age older than 18 years; (III) histological type classified as esophageal SCC [International Classification of Disease (ICD) codes: 8051, 8070, 8074, and 8083] or esophageal AC (ICD codes: 8140, 8200, 8430, and 8560) according to the World Health Organization (WHO) classification of digestive system tumors [2019]; (IV) diagnosis made between 2007 and 2021; (V) neoadjuvant chemotherapy; (VI) radical esophagectomy after neoadjuvant chemotherapy; (VII) postoperative staging classified as pN0; and (VIII) complete postoperative follow-up data available. Meanwhile, the exclusion criteria were as follows: (I) preoperative diagnosis of metastatic cancer or other primary malignant tumors; (II) survival duration of less than 1 month; (III) incomplete neoadjuvant chemotherapy or surgical intervention; and (IV) loss to follow-up or incomplete follow-up information.

Statistical methods

All continuous variables are expressed as the median and interquartile range (IQR), while categorical variables and stratified information are expressed as percentages or counts. To investigate the linear relationship between the number of lymph nodes dissected and survival status, this study employed restricted cubic spline regression analysis. The critical point for this relationship was identified by selecting the number of lymph nodes dissected corresponding to a hazard ratio (HR) of 1 as the threshold. We subsequently reported the results from unadjusted, minimally adjusted, and fully adjusted models. Additionally, patients were divided into two groups based on the critical value, and Kaplan-Meier (KM) survival analysis was conducted to calculate the 5-year survival rate. For patients with esophageal SCC and AC, a 7:3 ratio was used to randomly allocate them into a training set and a validation set. The training set was used to develop the nomogram, while the validation set served for external validation of the results. Initially, univariate Cox regression analysis was performed, and variables with two-sided P value <0.05 were included in the multivariate Cox regression analysis. Two-sided P value <0.05 in the multivariate regression results was regarded as statistically significant. In the training set, independent prognostic variables were selected from the Cox regression analysis results to construct the nomogram. To evaluate the predictive accuracy of the model, the Harrell concordance index (C-index) was employed for assessment, and calibration curves were created to compare the nomogram-predicted survival with actual survival outcomes. A value >0.5 indicates better-than-random prediction, with 0.6–0.7 considered moderate and >0.7 excellent. The clinical value of the nomogram was further validated using receiver operating characteristic (ROC) curves and decision curve analysis (DCA). Performance thresholds for area under the curve (AUC) were defined as follows: an AUC of 0.5 indicates performance equivalent to random chance; values between 0.7 and 0.8 denote acceptable discriminative ability; and values exceeding 0.8 are considered to reflect excellent predictive accuracy. Two-sided P value less than 0.05 indicated statistical significance. All analyses were performed with R 4.2.2 software (http://www.Rproject.org; The R Foundation for Statistical Computing, Vienna, Austria) and Free Statistics software version 2.0 (Beijing FreeClinical Medical Technology Co., Ltd., Beijing, China).

Results

Participant characteristics

From 2007 to 2021, we identified 58,851 patients with EC from the SEER database, of whom 39,100 were diagnosed with esophageal SCC or esophageal AC. Among them, 1,710 patients were staged pN0 after they underwent esophagectomy following neoadjuvant chemotherapy. From this cohort, we excluded 199 patients with a lymph node dissection count of 0 or an unknown number, 8 patients with a survival duration of less than 1 month or an unknown survival duration, 50 patients with an unknown race or marital status, and 60 patients with unspecified T or M staging. Ultimately, the study included 1,393 pN0 patients who underwent esophagectomy after neoadjuvant chemotherapy (Figure 1). Among the included patients with EC, the median age was 63 years, with males constituting 82.1% of the cohort. White patients accounted for 90.2% of the total population, and there were 1,120 cases of esophageal AC, representing 80.4% of the sample. The majority (82.5%) of patients had primary lesions located in the lower esophagus. Table 1 summarizes the baseline characteristics of the participants.

Figure 1 Flowchart of patients inclusion. EAC, esophageal adenocarcinoma; EC, esophageal cancer; ESCC, esophageal squamous cell carcinoma; ICD, International Classification of Disease; pN0, pathological N0; SEER, Surveillance, Epidemiology, and End Results.

Relationship between the number of lymph nodes dissected and survival outcomes

In this study, we employed restricted cubic spline smoothing to investigate the relationship between the number of lymph nodes dissected and survival status in patients with esophageal SCC and AC (Figure 2). The results demonstrated a significant linear relationship between the number of dissected lymph nodes and survival status for both types of cancer. Specifically, for patients with SCC, the minimum number of lymph nodes dissected, corresponding to an HR of 1, was found to be 13. In contrast, for patients with AC, the minimum number of lymph nodes was determined to be 15 when the HR was 1. These findings indicate that when the number of lymph nodes dissected falls below these critical values, patients experience poorer survival outcomes. Conversely, a number exceeding these thresholds is associated with significantly improved survival rates and a marked reduction in disease risk. Thus, 13 and 15 lymph nodes can be regarded as prognostic thresholds for survival outcomes in patients with esophageal SCC and AC, respectively. In SCC patients, a lymph node dissection exceeding 13 was significantly associated with improved survival. Similarly, in patients with AC, dissection of more than 15 lymph nodes was significantly associated with improved survival.

Figure 2 The relationship for the number of lymph node resections with survival status. (A) Restricted cubic spline for survival status of patients with ESCC. (B) Restricted cubic spline for the survival status of patients with EAC. EAC, esophageal adenocarcinoma; ESCC, esophageal squamous cell carcinoma.

Multivariate Cox regression analysis was conducted to assess the independent effect of the number of lymph nodes dissected on survival status (Table 2). In patients with esophageal SCC, those with more than 13 lymph nodes dissected had significantly improved survival outcomes compared to those with 13 or fewer lymph nodes dissected. The results indicated that the unadjusted HR was 0.65 [95% confidence interval (CI): 0.47–0.91; P=0.01]. After adjustments were made for age and gender, the HR was 0.59 (95% CI: 0.42–0.82; P=0.002). Further adjustment for gender, age, race, marital status, primary location, T stage, M stage, TNM stage, grade, and radiotherapy yielded an HR of 0.58 (95% CI: 0.40–0.82; P=0.002). In patients with esophageal AC, those with more than 15 lymph nodes dissected also demonstrated significantly better survival outcomes compared to those with 15 or fewer. The unadjusted HR was 0.73 (95% CI: 0.61–0.86; P<0.001). After adjustments were made for age and gender, the HR was 0.71 (95% CI: 0.60–0.85; P<0.001). When further adjustments were made for gender, age, race, marital status, primary location, T stage, M stage, TNM stage, grade, and radiotherapy, the HR was 0.69 (95% CI: 0.58–0.82: P<0.001).

This study systematically evaluated the correlation between the number of lymph nodes dissected and survival rates in patients with esophageal SCC and AC via KM curve analysis (Figure 3). In patients with esophageal SCC, the results indicated that those with more than 13 lymph nodes dissected had a higher 5-year survival rate as compared to those with 13 or fewer lymph nodes (P=0.007), suggesting a better prognosis. For patients with esophageal AC, those with more than 15 lymph nodes dissected had superior survival outcomes as compared to those with 15 or fewer lymph nodes (P=0.001).

Figure 3 Kaplan-Meier curves of the OS of patients based on number of lymph node resections. (A) Patients with ESCC. (B) Patients with EAC. EAC, esophageal adenocarcinoma; ESCC, esophageal squamous cell carcinoma; LN, lymph node; OS, overall survival.

Regression model and nomogram construction

For development of the predictive nomogram, patients were divided into training and validation sets at ratio of 7:3 ratio, both for patients with SCC (n=273) and for patients with AC (n=1,120). Tables S1,S2 present the baseline demographic and clinical characteristics of patients with esophageal SCC and AC in both the training and validation cohorts.

In patients with esophageal SCC, the training set included 192 individuals, who were grouped based on the number of lymph nodes dissected into those with >13 lymph nodes and those with ≤13 lymph nodes. Univariate analysis revealed that being male (P=0.001) and having more than 13 lymph nodes dissected (P=0.01) were significantly associated with patient survival (Table 3). Multivariate analysis indicated that female sex (HR =0.52, 95% CI: 0.37–0.74; P<0.001) and more than 13 lymph nodes dissected (HR =0.60, 95% CI: 0.43–0.85; P=0.004) remained independent factors influencing OS. For esophageal AC, the training set included 784 individuals, who were similarly categorized based on the number of lymph nodes dissected into those with >15 lymph nodes and those with ≤15 lymph nodes. Univariate analysis indicated that male sex (P<0.001), an age older than 63 years (P<0.001), more than 15 lymph nodes dissected (P=0.001), M stage (P<0.001), and TNM stage (P=0.002) were all significantly correlated with survival (Table 4). Multivariate analysis indicated that female sex (HR =0.51, 95% CI: 0.38–0.70; P<0.001), an age older than 63 years (HR =1.40, 95% CI: 1.18–1.65; P<0.001), and M stage (HR =1.90, 95% CI: 1.43–2.53; P<0.001) remained independent factors affecting OS (Table 4).

Variables with a P value less than 0.05 in the multivariate analysis were included in subsequent predictive models to estimate the 1-, 3-, and 5-year OS for pN0 patients undergoing esophagectomy after neoadjuvant chemotherapy. For esophageal SCC, a nomogram was constructed incorporating two variables: gender and the number of lymph nodes dissected (Figure 4A). For esophageal AC, a separate nomogram was developed that included four variables: gender, age, the number of lymph nodes dissected, and M staging (Figure 4B).

Figure 4 A novel nomogram for predicting the OS of patients. (A) Patients with ESCC. (B) Patients with EAC. Sex: 1, male; 2, female; age: 1, ≤63 years; 2, >63 years; LN (A): 1, ≤13; 2, >13; LN (B): 1, ≤15; 2, >15. EAC, esophageal adenocarcinoma; ESCC, esophageal squamous cell carcinoma; LN, lymph node; OS, overall survival.

To further validate the predictive performance and clinical applicability of the constructed models, we conducted internal validation. In patients with esophageal SCC, the C-index for the training set was 0.593, while for the validation set, it was 0.677. Additionally, the calibration curves for the 1-, 3-, and 5-year OS demonstrated a good agreement between the observed survival status and the predicted survival rates from the nomogram in both the training and validation sets (Figure 5). We also plotted ROC curves to assess the accuracy of the OS predictions at 1, 3, and 5 years (Figure 6): the AUC values in the training cohort were 0.614, 0.582, and 0.623, respectively, while in the validation cohort, they were 0.773, 0.678, and 0.651, respectively. Subsequently, we employed DCA to further validate the clinical value of the nomogram (Figure 7). Both ROC analysis and DCA were used to compare the nomogram with traditional TNM staging. The results indicated that the nomogram outperformed traditional TNM staging in predicting OS for both the training and validation sets. The ROC results showed that the predictive performance of the nomogram was significantly superior to that of TNM staging, and DCA further confirmed the enhanced clinical efficacy of the nomogram in predicting OS. In patients with esophageal AC, the C-index for the training set was 0.599, and for the validation set, it was 0.634. The calibration curves for 1-, 3-, and 5-year OS also showed good alignment between the observed survival status and the predicted survival rates from the nomogram in both the training and validation sets (Figure 8). The AUC values for the training set were 0.614, 0.626, and 0.624 for 1, 3, and 5 years, respectively, while in the validation set, they were 0.696, 0.664, and 0.640, respectively (Figure 9). The ROC analysis results indicated that the predictive performance of the nomogram was significantly better than that of TNM staging. Furthermore, DCA also demonstrated that the nomogram had stronger clinical efficacy in predicting OS (Figure 10).

Figure 5 Calibration curves for predicting the 1-, 3- and 5-year OS in patients with ESCC in the training cohort (A-C) and the validation cohort (D-F). The red dots represent the accuracy of the nomogram prediction. The closer the red line is to the gray line, the greater is the accuracy of the nomogram. ESCC, esophageal squamous cell carcinoma; OS, overall survival.

Figure 6 ROC analysis for predicting the 1-, 3-, and 5-year OS of patients with ESCC based on the nomogram and TNM stage in the training cohort (A-C) and the validation cohort (D-F). Model 1 is the nomogram, and Model 2 is the TNM stage. AUC, area under the curve; CI, confidence interval; ESCC, esophageal squamous cell carcinoma; OS, overall survival; ROC, receiver operating characteristic; TNM, tumor-node-metastasis.

Figure 7 DCA for predicting the 1-, 3-, and 5-year OS of patients with ESCC based on the nomogram and TNM stage in the training cohort (A-C) and the validation cohort (D-F). Model 1 is the nomogram, and Model 2 is the TNM stage. DCA, decision curve analysis; ESCC, esophageal squamous cell carcinoma; OS, overall survival; TNM, tumor-node-metastasis.

Figure 8 Calibration curves for predicting the 1-, 3- and 5-year OS of patients with EAC in the training cohort (A-C) and the validation cohort (D-F). The red dots represent the accuracy of the nomogram prediction. The closer the red line is to the gray line, the greater is the accuracy of the nomogram. EAC, esophageal adenocarcinoma; OS, overall survival.

Figure 9 ROC analysis for predicting the 1-, 3- and 5-year OS of patients with EAC based on the nomogram and TNM stage in the training cohort (A-C) and in the validation cohort (D-F). Model 1 is the nomogram, and Model 2 is the TNM stage. AUC, area under the curve; CI, confidence interval; EAC, esophageal adenocarcinoma; OS, overall survival; ROC, receiver operating characteristic; TNM, tumor-node-metastasis.

Figure 10 DCA for predicting the 1-, 3- and 5-year OS of patients with EAC based on the nomogram and TNM stage in the training cohort (A-C) and the validation cohort (D-F). Model 1 is the nomogram, and Model 2 is the TNM stage. DCA, decision curve analysis; EAC, esophageal adenocarcinoma; OS, overall survival; TNM, tumor-node-metastasis.

Discussion

This study identified a significant association between the number of lymph nodes dissected and survival outcomes in patients with esophageal SCC and AC. The findings indicate that for patients with SCC, the minimum number of lymph nodes to be dissected is 13, while for those with AC, it is 15 (Figure 2). Multivariate Cox regression analysis demonstrates that when the number of lymph nodes dissected exceeds these critical thresholds, patients experience a significant improvement in survival outcomes (Table 2). KM curve analysis further confirmed that patients with more than the critical number of lymph nodes dissected have higher 5-year survival rates (Figure 3). The differences in the optimal number of lymph nodes to be dissected between esophageal SCC and esophageal adenocarcinoma (EAC) mainly stem from the distinct lymph node metastasis patterns of these two types of cancers. Patients with adenocarcinoma have a significantly higher rate of lymph node positivity and a higher lymph node metastasis rate compared to those with SCC. Additionally, adenocarcinoma patients are at a higher risk of distant lymph node metastasis, while SCC patients more commonly exhibit lymph node metastasis in the upper and middle segments of the esophagus (16). These differences lead to varying requirements for the extent of lymph node dissection in the two types of cancer. For example, adenocarcinoma patients typically require dissection of a larger number of lymph nodes to ensure accurate staging and to improve survival rates (17).

There is considerable debate regarding the extent of lymph node dissection during surgery. On the one hand, a more comprehensive lymph node dissection can lead to more accurate staging; on the other hand, extensive lymph node dissection is associated with a higher incidence of postoperative complications, particularly in the short term (18,19). Notably, neoadjuvant immunotherapy has emerged as an emerging strategy for locally advanced EC in recent years (20). Neoadjuvant chemotherapy can reduce tumor staging, eliminate micrometastases, and alleviate tumor-related symptoms, thereby increasing the likelihood of radical resection and decreasing the risk of lymph node metastasis (21,22). A study suggest a positive correlation between the extent of lymph node dissection and survival rates in all pN0 cancer patients, recommending a more extensive lymph node dissection for these patients (23). Regarding the optimal minimum number of lymph nodes to be dissected for the best survival rates, the recommendations vary. Other researchers have attempted to determine the minimum number based on cancer characteristics (14,24-26). Recommendations in other studies have included 12, 18, 20, 23, and 60 lymph nodes (27-30). Despite the proposed pathological staging after neoadjuvant therapy, a study indicated that the staging system must continually evolve to accurately reflect lymph node downstaging post-neoadjuvant therapy (31). Lutfi et al. found that in patients with EC who achieved pathological complete response after neoadjuvant therapy and esophagectomy, those who had 15 or more lymph nodes sampled had higher 5-year survival rates as compared to those with fewer than 15 sampled (56.1% vs. 50.0%; P=0.01) (32), Williams et al. noted that although combined immunotherapy may reduce the burden of lymph node metastasis, dissection of ≥15 lymph nodes is still required to avoid understaging (33), which is consistent with our findings. Therefore, our study underscores the importance of the number of lymph nodes dissected in the prognostic assessment of EC treatment and provides a scientific basis for future treatment guidelines.

Lymph nodes are secondary lymphoid organs distributed throughout the body and serve as crucial coordination points for immune surveillance (34). Lymphatic vessels are key pathways for antigen presentation, transporting fluids, cells, and soluble factors unidirectionally from peripheral tissues to the lymph nodes, where they undergo filtration before returning to the bloodstream (35). Lymph nodes create a microenvironment that facilitates the activation of T cells and B cells. Activated immune cells are capable of recognizing and attacking tumor cells, thereby limiting their growth and metastasis (36). Cells within the tumor microenvironment, such as tumor-associated macrophages and fibroblasts, may contribute to the production of tumor-promoting factors. These factors may include vascular endothelial growth factor C, which is associated with lymphangiogenesis in lymph nodes and may correlate with tumor metastatic progression (37,38). Qiu et al. found that the efficacy of programmed cell death protein 1 (PD-1) inhibitors (such as camrelizumab) in SCC was significantly associated with cutaneous capillary proliferation—a marker of immune activation—suggesting that SCC responses to immunotherapy rely more on local inflammatory reactions. This may reduce distant lymph node metastasis, thereby lowering the threshold for lymph node dissection (39). Tumor cells that metastasize to lymph nodes exhibit a series of metabolic adaptations that enhance their metastatic potential. Hou et al. found that the rate of lymph node skip metastasis in SCC was as high as 28%, further explaining why the threshold for SCC is lower than that for adenocarcinoma—regional lymph node dissection can already cover most metastatic pathways (40). These metabolic changes may suppress T-cell responses by depriving them of essential nutrients and other factors (41). When tumors occupy lymph nodes, they induce a state of tumor-specific immune tolerance, allowing tumor cells to survive in the lymph nodes and evade immune surveillance (42). Cells within the tumor microenvironment may inhibit immune responses by secreting immunosuppressive factors such as transforming growth factor-β (TGF-β) and interleukin-10 (IL-10), promoting the survival and dissemination of tumor cells within the lymph nodes (43). Tumor-associated macrophages and regulatory T cells may foster an immunosuppressive environment in the lymph nodes, aiding tumor cells in evading immune detection (44).

In a study involving 50 patients, systematic lymph node dissection was performed, resulting in the identification of 1,840 lymph nodes. These lymph nodes underwent additional examination through immunohistochemistry via the AE1/AE3 anti-cytokeratin antibody to facilitate the detection of micrometastases (45). In addition to routine hematoxylin and eosin (HE) staining, the study employed supplementary immunohistochemical staining techniques to enhance the detection rate of micrometastases. This approach aided in the early identification of micrometastases that may not be evident through conventional HE staining (46). Although the findings indicated that the presence of micrometastases did not significantly impact OS or disease-free survival among patients, the detection of micrometastases may provide prognostic information, especially in assessing tumor lymphatic spread and developing treatment strategies (47). On average, each patient had 37 lymph nodes dissected (ranging from 6 to 136), suggesting that extensive lymph node dissection was performed, which may help reduce tumor burden (48). Despite the study not finding a significant prognostic impact of micrometastases, comprehensive lymph node dissection may nonetheless decrease the chances of tumor cell dissemination, potentially improving patient survival rates and quality of life (49). The study mentioned two types of systematic lymph node dissection: two- and three-field dissection. This distinction may reflect variations in tumor burden and lymph node involvement across different patients (50). Overall, the research indicates that dissecting more lymph nodes may contribute to reducing tumor burden and facilitate the early detection of micrometastases, ultimately improving the survival rates for patients.

The eighth edition of the TNM staging system published by the American Joint Committee on Cancer (AJCC) and the International Union Against Cancer (UICC) remains the globally recognized standard for EC staging. Despite updates to this system, the impact of neoadjuvant therapy and the variability in patient responses to treatment remain inadequately reflected in the existing staging framework, posing challenges to accurate prognostic assessment (51). Consequently, numerous methods have been proposed for the evaluation of the long-term prognosis of patients with EC based on the number of lymph nodes dissected and other factors. Our study focused on patients with esophageal SCC and developed a nomogram model that incorporates age and the number of lymph nodes dissected. After training and validation, the nomogram consistently demonstrated higher AUC values than did the TNM staging system. For patients with esophageal AC, the model included age, gender, M stage, and the number of lymph nodes dissected, and the predictive performance of this nomogram surpassed that of the TNM staging system. Our model highlights significant differences in patient survival rates at specific thresholds of lymph node dissection—information that is not fully captured by traditional TNM staging. By emphasizing individualized predictions and incorporating specific variables such as lymph node count, our model offers a more precise prognostic assessment. The conventional TNM staging can serve as a foundational framework, which, when combined with our model, may provide a more comprehensive evaluation of prognosis.

Our study involved several limitations which should be noted. First, as we employed a retrospective design, there was an inherent risk of selection bias. Second, the research primarily relied on the SEER database, which represents a singular data source and may limit the external validity of our findings. Since the patient data in the SEER database are predominantly derived from the United States, there are limitations related to factors such as ethnicity and healthcare resources, making it possible that our results may not fully apply to populations in other regions or countries. Additionally, the SEER database lacks comprehensive information on patients’ overall health status, complications, and quality of life, which may affect the thoroughness of treatment choices and prognostic assessments. Our proposed model requires further validation; thus, future large-scale prospective studies and explorations of biomarkers are needed to verify the impact of lymph node dissection quantity on patient prognosis. These endeavors may help to reduce the biases associated with retrospective studies and improve the representativeness of the sample.

Conclusions

In conclusion, this study identified a significant association between the number of lymph nodes dissected and survival prognosis in patients with esophageal SCC and AC. Specifically, the minimum number of lymph nodes identified for SCC patients was 13, while for AC patients, it was 15. Patients with a number of lymph nodes removed lower than these thresholds exhibited significantly worse survival outcomes. Moreover, multivariate Cox regression analysis and KM curves corroborated this finding, indicating that the number of lymph nodes dissected is an important independent factor affecting OS. Most probably, dissecting more lymph nodes results in more accurate staging of pN0, and avoids understaging. Additionally, the constructed nomogram model demonstrated notable clinical application potential in predicting patient survival, outperforming traditional TNM staging and providing valuable information for clinical decision-making.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the TRIPOD reporting checklist. Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-910/rc

Peer Review File: Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-910/prf

Funding: This work was supported by the Beijing Medical Award Foundation (No. YXJL-2020-0785-0351), the Wu Jieping Medical Foundation (No. 320.6750.2022-19-88), the Science and Technology Program of the Joint Fund of Scientific Research for the Public Hospitals of the Inner Mongolia Academy of Medical Sciences (Nos. 2023GLLH0123 and 2023GLLH0131), the Inner Mongolia Medical University Joint Project (No. YKD2024LH021), the Beijing University Cancer Hospital Inner Mongolia Hospital “Qingmiao” Talent Plan (Nos. QM202325 and QM202312), the Zhungeer Banner Science and Technology Planning Program (No. 2020YY-05), and Inner Mongolia Hospital of Peking University Cancer Hospital - Demonstration Project for the Reform and High-quality Development of Public Hospitals (Gastrointestinal Tumors + Thoracic Tumors) Construction of Clinical Key Specialties (No. 12024YNQN013).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-910/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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(English Language Editor: J. Gray)