Survival risk prediction nomogram for patients with resectable esophageal squamous cell carcinoma receiving neoadjuvant immunochemotherapy followed by surgery: a retrospective study

Introduction

Esophageal cancer ranks as the seventh leading cause of cancer-related mortality worldwide, with China exhibiting the highest incidence in the East Asian region (1). Data from the most recent report by the National Cancer Center of China in 2022 indicate that esophageal cancer is the fifth most common malignancy among males and ranks tenth among females in terms of cancer incidence (2). Esophageal squamous cell carcinoma (ESCC) is the predominant pathological type of esophageal cancer in China, accounting for more than 90% of cases (3). Most patients with ESCC are diagnosed at a locally advanced stage; although distant metastases are often absent, tumors are generally large and may invade surrounding lymph nodes or adjacent organs, making curative surgery alone suboptimal. Consequently, there is a clinical preference for multimodal treatment approaches. The results from the CROSS (4) and NEOCRTEC5010 (5) trials have established neoadjuvant chemoradiotherapy (NCRT) as a standard treatment for patients with locally advanced ESCC. Nevertheless, NCRT has demonstrated limited improvements in the overall prognosis for patients with locally advanced ESCC and may pose safety concerns that offset potential survival benefits. The emergence of immune checkpoint inhibitors (ICIs) has introduced new opportunities for neoadjuvant treatment in locally advanced esophageal cancer (6,7). Clinical studies have shown that the neoadjuvant immunochemotherapy (NICT) enhances surgical resection and pathological response rates, while maintaining a manageable safety profile (8,9).

However, most of these studies lack long-term survival data, and the long-term efficacy of NICT remains underexplored. In this retrospective study, we aim to analyze the effectiveness of NICT in real-world settings and report survival outcomes for patients with regular follow-up. Our goal is to identify factors and protective elements associated with survival benefits, which may guide postoperative adjuvant treatment choices for this patient population. Ultimately, we seek to improve both event-free survival (EFS) and overall survival (OS) in resectable ESCC. We present this article in accordance with the TRIPOD reporting checklist (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-1027/rc).

Methods

Patients

This study included patients with ESCC who received NICT, followed by McKeown esophagectomy, at Department of Thoracic Surgery, Guangdong Provincial People’s Hospital, between January 2019 and December 2022. The inclusion criteria were: (I) confirmed ESCC diagnosed via preoperative biopsy; (II) completion of radical surgical resection, including a combined transthoracic and transabdominal subtotal esophagectomy with regional lymphadenectomy; (III) availability of comprehensive clinical and pathological data; and (IV) ability to adhere to scheduled follow-up visits. The exclusion criteria were: (I) history of surgery or diagnosis with any M1 stage disease; (II) receipt of neoadjuvant chemotherapy (NCT) or NCRT prior to esophagectomy; (III) instances of salvage surgery; (IV) presence of other systemic malignancies; and (V) mortality within 90 days post-surgery. A total of 132 patients who initiated NICT during the study period were screened. Among them, 44 were excluded according to the exclusion criteria. The remaining 88 patients who met all eligibility criteria were consecutively included in the final analysis. The cohort consisted of 44 males and 44 females, with a mean age of 63.6 years.

Treatment protocol

The NICT regimen consisted of the intravenous administration of a taxane paired with a platinum-based chemotherapeutic agent and a programmed death-1 (PD-1) or programmed death-ligand 1 (PD-L1) inhibitor, administered every 3 weeks. The PD-1 inhibitors used included camrelizumab, nivolumab, pembrolizumab, sintilimab, and tislelizumab, with only one patient receiving the PD-L1 inhibitor durvalumab. After completing at least one cycle of neoadjuvant therapy, physical examinations, routine laboratory tests, and contrast-enhanced chest and abdominal computed tomography (CT) or positron emission tomography (PET)/CT scans were conducted to evaluate surgical indications and timing. Radical esophagectomy was performed 4–6 weeks following the completion of neoadjuvant treatment. All patients underwent the McKeown procedure, a three-incision radical esophagectomy involving cervical, thoracic, and abdominal approaches. The esophagus was mobilized via the right thoracic approach, and thoracic lymphadenectomy was performed, followed by repositioning to a supine position to mobilize the stomach and perform abdominal lymphadenectomy. An incision was made in the left neck to mobilize and transect the cervical esophagus. The gastric lesser curvature and gastroesophageal junction were resected to construct a tubular stomach, which was then anastomosed to the esophagus in the left neck using either mechanical or manual techniques.

Follow-up

Patients were followed up every 3 months during the first year after surgery and every 6 months thereafter. The primary endpoint of this study was EFS, defined as the duration from the date of surgery to the occurrence of any event, such as local recurrence, involvement of lymph nodes, distant metastasis, or death, or to the date of the patient’s last known disease-free status. The last follow-up date for this study is set for July 31, 2024. During follow-up, oncological assessments were conducted using chest CT, abdominal and cervical ultrasound, or CT, with endoscopy, radionuclide bone imaging, or PET/CT scans performed as needed. The median follow-up time in our cohort was 31.5 (range, 12–47) months.

Study variables

Tumor location, tumor staging [including TNM stage, clinical primary tumor stage (cT), clinical lymph node stage (cN), pathological primary tumor stage (pT), and pathological lymph node stage (pN)], EFS, recurrence/metastasis/death status, R0 resection rate, cycles of neoadjuvant therapy, choice of immunotherapy drug, pathological complete response (pCR) rate, and major pathological response (MPR) rate.

Statistical analysis

Continuous variables were expressed as the mean ± standard deviation (SD) or as the median and range, while categorical variables were presented as counts and percentages. Comparisons between groups of categorical data were made using the χ² test, and comparisons between groups of continuous data were performed using the independent samples t-test. Univariate analysis was used to identify statistically significant factors, which were then analyzed using logistic regression to determine independent risk factors affecting survival. Predictors for the multivariate model were selected based on both strong clinical relevance and statistical significance in univariate analysis to maintain an appropriate events-to-predictors ratio. Although the possibility of merging certain categories such as cN1 and cN3 was considered to simplify the model, these variables were retained as separate indicators because of their distinct prognostic significance observed in this cohort. A nomogram prediction model was constructed using R software, and the predictive capability of the model was assessed using receiver operating characteristic (ROC) curve analysis. A significance level of P<0.05 was considered statistically significant. Statistical analysis were performed using SPSS 25.0 software (IBM Corp., Armonk, NY, USA), with visualizations generated using GraphPad Prism version 8.0.2 and R software.

Ethical approval

The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments, and was approved by the Ethics Review Committee of Guangdong Provincial People’s Hospital (No. KY2023-499-01). All participants enrolled in the study were fully informed and provided written informed consent.

Results

Patients’ characteristics

The study included 88 patients who were divided into two groups based on outcomes. During the follow-up period, 30 patients reached the study endpoint (confirmed recurrence, metastasis, or death) and were categorized as the experimental group. The remaining 58 patients, who did not reach the endpoint, were categorized as the control group. Baseline characteristics of patients in both groups were compared through differential analysis, as detailed in Table 1. Patient survival curves based on EFS were plotted and are presented in Figure 1.

Figure 1 Kaplan-Meier curve for event-free survival in the entire study cohort.

Univariate and multivariate analysis of survival risk factors

Univariate analysis indicated that male gender, age, neoadjuvant treatment cycles, body mass index (BMI), upper tumor location, middle tumor location, cT1–3, cN1, cN3, pN1–2, tumor downstaging, and treatment with pembrolizumab were associated risk factors for postoperative survival in patients receiving NICT (P<0.05). Based on the results of the univariate analysis, statistically significant factors were selected for multivariate logistic regression analysis. The findings suggested that age, cycles of neoadjuvant therapy, cT2, cN1, cN3, and pN1–2 were independent risk factors for postoperative survival in these patients (P<0.05) (Table 2).

Construction and evaluation of the nomogram prediction model

Based on the multivariate analysis, age, neoadjuvant treatment cycles, cT2, cN1, cN3, and pN1–2 were identified as predictors of postoperative survival risk for patients undergoing NICT. Using R software, we calculated the area under the curve (AUC) to be 0.927 [95% confidence interval (CI): 0.873–0.982] (Figure 2). To visually represent patient survival risk, we developed a nomogram model based on these independent predictors, allowing for the prediction of postoperative survival risk based on risk factor scores (Figure 3). The predictive model was validated by 1,000 bootstrap resamplings, resulting in an AUC of 0.923 (95% CI: 0.866–0.979). The calibration curve demonstrated good accuracy for the model (Figure 4), indicating a high predictive value.

Figure 2 ROC curve for the prediction model. The AUC was 0.927 (95% CI: 0.873–0.982). The optimal cut-off value was 0.405, yielding a sensitivity of 86.7% and a specificity of 87.9% (Youden index =0.746). AUC, area under the curve; CI, confidence interval; ROC, receiver operating characteristic.

Figure 3 Nomogram model for predicting survival risk of NICT following surgery. N, node; NICT, neoadjuvant immunochemotherapy; ntc, neoadjuvant treatment cycles; T, tumor.

Figure 4 Calibration curve of prediction model.

Discussion

Surgery remains an effective treatment option for most patients with ESCC. However, for locally advanced ESCC, the R0 resection rate is low, and the risk of early postoperative recurrence is high, highlighting the urgent need for neoadjuvant treatment. The concept of neoadjuvant therapy originated in the 1980s, when researchers proposed preoperative chemotherapy or radiotherapy to reduce tumor size and stage, and to destroy circulating tumor cells and micrometastases, thus enhancing long-term survival (10). Despite improvements in surgical techniques and chemoradiotherapy strategies for ESCC, clinical benefits remain suboptimal, and survival rates following multimodal treatment and esophagectomy are still low. According to the World Esophageal Cancer Collaboration, the 5-year OS rates for ypStage I and ypStage II are approximately 50% and 30%, respectively (11). Furthermore, 31–39% of patients with locally advanced esophageal cancer experience recurrence within 3–5 years post-surgery (12,13).

The combination with immunotherapy holds significant promise for improving clinical outcomes in ESCC patients. NICT has a sound theoretical foundation: the cytotoxic effects of chemotherapy on tumor cells generate a rich source of antigens and cytokines, which can support and enhance immune responses, potentially augmenting adaptive immunity (14,15). Studies suggest that ESCC exhibits relatively higher levels of immune-related biomarkers compared to esophageal adenocarcinoma (EAC), indicating potential sensitivity to ICIs (16). The KEYNOTE-181 trial also demonstrated that ESCC has a better response to immunotherapy than EAC (17). In fact, NICT is increasingly being used, and neoadjuvant therapy followed by esophagectomy has become a potential curative strategy for patients with locally advanced ESCC. Published clinical studies have reported pCR rates ranging from 16.7% to 50.0%, and MPR rates from 41.7% to 72.2%, indicating promising short-term efficacy (8,18-21).

However, even though the advent of immunotherapy has significantly improved the overall prognosis for patients with ESCC, long-term outcomes remain suboptimal, with 5-year survival rates remaining at a low level, even for patients diagnosed at an early stage and undergoing radical surgery. Therefore, developing a prognostic model for ESCC that accurately reflects clinical realities could not only aid in identifying high-risk patients with poor prognosis but also potentially assist in optimizing clinical strategies. The prognosis of ESCC patients is a heterogeneous and multifactorial process, influenced by constantly changing pathophysiological states. Various stages, tumor locations, and treatment modalities all impact patient prognosis, making the predictive power of single indicators inadequate.

A prediction model should be grounded in evidence-based medicine and leverage clinical data, which might include factors such as patient age, medical history, imaging results, degree of lesion differentiation, and molecular biological characteristics, to forecast patient outcomes. Upon reviewing the literature, we discovered that while there are studies examining the efficacy and safety of sequential surgery following NICT, there are few models utilizing clinical data to predict long-term survival risk for ESCC patients (22). This study aims to address this gap by developing a survival risk prediction model for resectable ESCC patients who receive NICT followed by surgery. Although the prognostic significance of TNM staging and age is well established, our study provides a context-specific risk stratification tool tailored to the NICT-treated ESCC population—a group not addressed by existing prediction models. The results indicate that factors such as age, number of neoadjuvant therapy cycles, cT, cN, and pN significantly impact the survival of patients undergoing this treatment sequence. As individuals age, the functional capacity of various body systems gradually declines, which may affect their tolerance to combination chemoradiotherapy and surgery, potentially impacting overall prognosis. Retrospective studies have indicated that advanced age is a predictive factor for poorer 1-, 3-, and 5-year all-cause mortality rates in patients with ESCC (23). Research by Jia et al. (24) has shown that age is an independent factor affecting survival in early-stage esophageal cancer patients. Liu et al. found that progression-free survival (PFS) in ESCC patients aged 65 years or older is associated with disease-related mortality (25). Another study by Cheng et al. revealed that the 5-year OS rate is significantly lower in patients diagnosed at an age greater than 65 years (26). Our study aligns with these conclusions, indicating that survival risk scores increase with age, suggesting that treatment plans for elderly patients should be carefully selected based on functional status and expected lifespan.

The optimal treatment duration for NICT in ESCC remains to be determined. A randomized phase II trial involving patients with locally advanced ESCC reported comparable pathological response and 2-year PFS rates between those receiving 2 and 3 cycles of neoadjuvant therapy (71.4% vs. 71.1%, P=0.669) (27). A retrospective study found that 3–4 cycles of combined NCRT result in higher pCR rates (47.9% vs. 12.5%, P<0.001) and 2-year disease-free survival (DFS) rates (88.1% vs. 68.0%, P=0.025) compared to 2 cycles (28). Our study suggests that longer neoadjuvant treatments are associated with reduced survival risks, potentially due to increased exposure to primary tumor antigens, enhancing the strength and duration of tumor-specific T-cell responses, leading to higher MPR rates (29). However, excessively prolonged immunotherapy may increase the incidence of immune adverse events. The number of neoadjuvant treatment cycles is influenced by patient condition, disease burden, and other factors, necessitating further long-term follow-up and large-sample prospective trials to assess the impact on survival outcomes.

Research conducted by scholars in Taiwan indicated that cT, cN, and OS are significant according to univariate analysis, with both remaining independent prognostic factors in a multivariate Cox regression model (26). The 8th edition of the American Joint Committee on Cancer (AJCC) Cancer Staging Manual also considers tumor size as an independent predictor of prognosis (30). In our study, both cT3 and cN3 corresponded to the highest risk scores, reflecting the tumor burden before treatment, making their significant association with survival risk clinically relevant. In the results, univariate analysis showed that cT1, cT2, and cT3 were all related risk factors for survival, while multivariate analysis showed that cT2 was more significant than other stages. The reason may be that the uncertainty of T2 clinical stage makes the treatment strategy of esophageal cancer more challenging: about 50% of esophageal cancer with clinical staging T2N0M0 is downgraded by pathology because of the low accuracy of endoscopic ultrasound. When the underlying advanced disease is underestimated as cT2 N0M0, patients will miss the opportunity to get the potential benefits of neoadjuvant therapy, which will affect the over survival (31). Our results further suggest that, in postoperative pathological staging, lymph node staging serves as an independent prognostic factor for survival risk in ESCC patients, more so than primary tumor staging. This conclusion is supported by multiple clinical studies: as early as 2004, research identified pN0 stage as a strong predictor of survival (32), and in metastatic ESCC, lymph node response is more closely linked with the development of lymph node metastasis, distant metastasis, and dissemination than primary tumor response (33). Pathological lymph node response is considered a better predictor of long-term survival than primary tumor response (34), further validating the role of pathological lymph node staging as an independent predictor of survival risk in ESCC patients.

It is important to note that although some studies have suggested that pCR can serve as an early surrogate endpoint for predicting survival outcomes in patients receiving NICT (35), and that MPR is significantly associated with improved OS and considered a strong prognostic factor (36), in our study, neither pCR nor MPR emerged as independent predictors of postoperative survival risk in patients undergoing NICT. This may be due to the limited number of cases, which may not fully capture the survival predictive benefits of pathological response. Additionally, some patients who achieved pCR or MPR experienced non-disease-related mortality, which might have influenced the survival analysis. Another potential explanation is the heterogeneous distribution of pCR and MPR in our cohort, which may be influenced by baseline disease burden, variations in treatment regimens, and biological aggressiveness of the disease. These factors could attenuate the observable prognostic impact of pathological response. Moreover, competing risks, such as early recurrence despite favorable pathological response, may further obscure the survival advantage typically associated with pCR and MPR.

The ideal neoadjuvant treatment achieves a high pCR rate and long-term survival with minimal surgical interference and ease of clinical application. There is variability in neoadjuvant treatment effectiveness among ESCC patients, and due to the stringent inclusion and exclusion criteria in clinical trials, our real-world study population appears more vulnerable and has more diverse outcomes than those in clinical research. Therefore, enhancing our understanding of the factors influencing efficacy and effectively utilizing survival prediction models is crucial for assessing patient prognosis, selecting adjuvant treatment plans, developing follow-up strategies, and advancing precision medicine.

There are some limitations in this study. First, this retrospective study is based on patients from a single center, implying that, despite multivariate analysis, selection bias cannot be entirely ruled out, which has limited the number of eligible patients with adequate follow-up time. This restricts the clinical generalizability and dissemination of the study findings to some extent. Moreover, our study lacks immune-related biomarkers such as PD-L1 expression or tumor mutational burden due to inconsistent availability during the study period. This limits the biological interpretability of the model and underscores the need for biomarker-integrated predictive models in future prospective studies. Second, this study does not provide details on treatment regimens following recurrence or metastasis, or the potential for non-disease-related mortality, which may impact EFS. Third, given the relatively short and heterogeneous follow-up and limited number of events, we used logistic regression to reduce the risk of model instability and overfitting, although this inevitably sacrifices some temporal survival information. Fourth, the model was internally validated, which might limit its generalization ability. Future work will aim to expand the sample size, incorporate a broader range of variable parameters such as laboratory test results and pathological features, and conduct large-scale, prospective, multicenter studies with external validation to further enhance model predictive performance.

Conclusions

In summary, our study suggests that age, neoadjuvant treatment cycles, cT, cN, and pN significantly impact the survival of patients undergoing sequential radical surgery following NICT. Early postoperative intervention for patients assessed as high risk is crucial, and timely adjuvant therapy post-recovery could potentially extend EFS and even OS. Through retrospective analysis, we identified risk factors for survival in resectable ESCC patients who underwent NICT followed by surgery, and developed a clinical predictive nomogram model that performs well in both discrimination accuracy and calibration. This model provides clinicians with a visual assessment tool, which may be useful in clinical practice for life planning, postoperative treatment, and customized follow-up, offering significant clinical guidance applications.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the TRIPOD reporting checklist. Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-1027/rc

Data Sharing Statement: Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-1027/dss

Peer Review File: Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-1027/prf

Funding: This work was supported by the National Natural Science Foundation of China (Nos. 82472751 and 82302260) and the Natural Science Foundation of Guangdong Province (Nos. 2022A1515012469 and 2023A1515010507).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-1027/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, and was approved by the Ethics Review Committee of Guangdong Provincial People’s Hospital (No. KY2023-499-01). All participants enrolled in the study were fully informed and provided written informed consent.

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/.

References

1. Bray F, Laversanne M, Sung H, et al. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 2024;74:229-63. [Crossref] [PubMed]
2. Han B, Zheng R, Zeng H, et al. Cancer incidence and mortality in China, 2022. J Natl Cancer Cent 2024;4:47-53. [Crossref] [PubMed]
3. Liang H, Fan JH, Qiao YL. Epidemiology, etiology, and prevention of esophageal squamous cell carcinoma in China. Cancer Biol Med 2017;14:33-41. [Crossref] [PubMed]
4. van Hagen P, Hulshof MC, van Lanschot JJ, et al. Preoperative chemoradiotherapy for esophageal or junctional cancer. N Engl J Med 2012;366:2074-84. [Crossref] [PubMed]
5. Yang H, Liu H, Chen Y, et al. Neoadjuvant Chemoradiotherapy Followed by Surgery Versus Surgery Alone for Locally Advanced Squamous Cell Carcinoma of the Esophagus (NEOCRTEC5010): A Phase III Multicenter, Randomized, Open-Label Clinical Trial. J Clin Oncol 2018;36:2796-803. [Crossref] [PubMed]
6. Wang H, Song C, Zhao X, et al. Evaluation of neoadjuvant immunotherapy and traditional neoadjuvant therapy for resectable esophageal cancer: a systematic review and single-arm and network meta-analysis. Front Immunol 2023;14:1170569. [Crossref] [PubMed]
7. Liu Y, Bao Y, Yang X, et al. Efficacy and safety of neoadjuvant immunotherapy combined with chemoradiotherapy or chemotherapy in esophageal cancer: A systematic review and meta-analysis. Front Immunol 2023;14:1117448. [Crossref] [PubMed]
8. Yang W, Xing X, Yeung SJ, et al. Neoadjuvant programmed cell death 1 blockade combined with chemotherapy for resectable esophageal squamous cell carcinoma. J Immunother Cancer 2022;10:e003497. [Crossref] [PubMed]
9. Duan H, Wang T, Luo Z, et al. A multicenter single-arm trial of sintilimab in combination with chemotherapy for neoadjuvant treatment of resectable esophageal cancer (SIN-ICE study). Ann Transl Med 2021;9:1700. [Crossref] [PubMed]
10. Frei E 3rd. What's in a name--neoadjuvant. J Natl Cancer Inst 1988;80:1088-9. [Crossref] [PubMed]
11. Rice TW, Ishwaran H, Kelsen DP, et al. Recommendations for neoadjuvant pathologic staging (ypTNM) of cancer of the esophagus and esophagogastric junction for the 8th edition AJCC/UICC staging manuals. Dis Esophagus 2016;29:906-12.
12. Xi M, Yang Y, Zhang L, et al. Multi-institutional Analysis of Recurrence and Survival After Neoadjuvant Chemoradiotherapy of Esophageal Cancer: Impact of Histology on Recurrence Patterns and Outcomes. Ann Surg 2019;269:663-70. [Crossref] [PubMed]
13. Kong M, Shen J, Zhou C, et al. Prognostic factors for survival in esophageal squamous cell carcinoma (ESCC) patients with a complete regression of the primary tumor (ypT0) after neoadjuvant chemoradiotherapy (NCRT) followed by surgery. Ann Transl Med 2020;8:1129. [Crossref] [PubMed]
14. Liu WM, Fowler DW, Smith P, et al. Pre-treatment with chemotherapy can enhance the antigenicity and immunogenicity of tumours by promoting adaptive immune responses. Br J Cancer 2010;102:115-23. [Crossref] [PubMed]
15. Salas-Benito D, Pérez-Gracia JL, Ponz-Sarvisé M, et al. Paradigms on Immunotherapy Combinations with Chemotherapy. Cancer Discov 2021;11:1353-67. [Crossref] [PubMed]
16. Salem ME, Puccini A, Xiu J, et al. Comparative Molecular Analyses of Esophageal Squamous Cell Carcinoma, Esophageal Adenocarcinoma, and Gastric Adenocarcinoma. Oncologist 2018;23:1319-27. [Crossref] [PubMed]
17. Kojima T, Shah MA, Muro K, et al. Randomized Phase III KEYNOTE-181 Study of Pembrolizumab Versus Chemotherapy in Advanced Esophageal Cancer. J Clin Oncol 2020;38:4138-48. [Crossref] [PubMed]
18. Liu J, Yang Y, Liu Z, et al. Multicenter, single-arm, phase II trial of camrelizumab and chemotherapy as neoadjuvant treatment for locally advanced esophageal squamous cell carcinoma. J Immunother Cancer 2022;10:e004291. [Crossref] [PubMed]
19. Zhang Z, Hong ZN, Xie S, et al. Neoadjuvant sintilimab plus chemotherapy for locally advanced esophageal squamous cell carcinoma: a single-arm, single-center, phase 2 trial (ESONICT-1). Ann Transl Med 2021;9:1623. [Crossref] [PubMed]
20. Liu J, Li J, Lin W, et al. Neoadjuvant camrelizumab plus chemotherapy for resectable, locally advanced esophageal squamous cell carcinoma (NIC-ESCC2019): A multicenter, phase 2 study. Int J Cancer 2022;151:128-37. [Crossref] [PubMed]
21. Yan X, Duan H, Ni Y, et al. Tislelizumab combined with chemotherapy as neoadjuvant therapy for surgically resectable esophageal cancer: A prospective, single-arm, phase II study (TD-NICE). Int J Surg 2022;103:106680. [Crossref] [PubMed]
22. Eil R, Diggs BS, Wang SJ, et al. Nomogram for predicting the benefit of neoadjuvant chemoradiotherapy for patients with esophageal cancer: a SEER-Medicare analysis. Cancer 2014;120:492-8. [Crossref] [PubMed]
23. Xie SH, Santoni G, Mälberg K, et al. Prediction Model of Long-term Survival After Esophageal Cancer Surgery. Ann Surg 2021;273:933-9. [Crossref] [PubMed]
24. Jia R, Xiao W, Zhang H, et al. Comparative study of treatment options and construction nomograms to predict survival for early-stage esophageal cancer: a population-based study. Scand J Gastroenterol 2021;56:635-46. [Crossref] [PubMed]
25. Liu J, Li Y, Chen Y, et al. Long-Term Treatment Outcomes of the Elder Patients with Locally Advanced Thoracic Esophageal Squamous Cell Carcinoma with Definitive Chemoradiotherapy or Radiotherapy. Contrast Media Mol Imaging 2022;2022:3678441. [Crossref] [PubMed]
26. Cheng YF, Chen HS, Wu SC, et al. Esophageal squamous cell carcinoma and prognosis in Taiwan. Cancer Med 2018;7:4193-201. [Crossref] [PubMed]
27. Makino T, Yamasaki M, Tanaka K, et al. Multicenter randomised trial of two versus three courses of preoperative cisplatin and fluorouracil plus docetaxel for locally advanced oesophageal squamous cell carcinoma. Br J Cancer 2022;126:1555-62. [Crossref] [PubMed]
28. Lv H, Huang C, Li J, et al. The survival outcomes of neoadjuvant sintilimab combined with chemotherapy in patients with locally advanced esophageal squamous cell carcinoma. Front Immunol 2022;13:1100750. [Crossref] [PubMed]
29. Kwiatkowski DJ, Rusch VW, Chaft JE, et al. Neoadjuvant atezolizumab in resectable non-small cell lung cancer (NSCLC): Interim analysis and biomarker data from a multicenter study (LCMC3). J Clin Oncol 2019;37:8503.
30. Zhong H, Ma R, Gong L, et al. Comparison of the prognostic value of the seventh and eighth edition of The AJCC Esophageal Cancer Staging System for the patients with stage II and III esophageal squamous cell carcinoma. Zhonghua Wai Ke Za Zhi 2017;55:903-8.
31. Tasnim S, Raja S, Blackstone EH, et al. Clinical T2 N0 M0 Esophageal Cancer: Identifying Predictive Factors of Upstaging. Ann Thorac Surg 2024;117:1121-7. [Crossref] [PubMed]
32. Mariette C, Taillier G, Van Seuningen I, et al. Factors affecting postoperative course and survival after en bloc resection for esophageal carcinoma. Ann Thorac Surg 2004;78:1177-83. [Crossref] [PubMed]
33. Urakawa S, Makino T, Yamasaki M, et al. Lymph Node Response to Neoadjuvant Chemotherapy as an Independent Prognostic Factor in Metastatic Esophageal Cancer. Ann Surg 2021;273:1141-9. [Crossref] [PubMed]
34. Hagi T, Makino T, Yamasaki M, et al. Pathological Regression of Lymph Nodes Better Predicts Long-term Survival in Esophageal Cancer Patients Undergoing Neoadjuvant Chemotherapy Followed by Surgery. Ann Surg 2022;275:1121-9. [Crossref] [PubMed]
35. Guo Y, Xu X, Wang T, et al. Efficacy, safety, and survival of neoadjuvant immunotherapy plus chemotherapy in locally advanced esophageal squamous cell carcinoma: A real-world retrospective study. Int Immunopharmacol 2024;138:112558. [Crossref] [PubMed]
36. Tomasello G, Petrelli F, Ghidini M, et al. Tumor regression grade and survival after neoadjuvant treatment in gastro-esophageal cancer: A meta-analysis of 17 published studies. Eur J Surg Oncol 2017;43:1607-16. [Crossref] [PubMed]