Five-year Survival Analyses on Non-Pathological Complete Response Esophageal Squamous Cell Carcinoma Patients after Neoadjuvant Regimens plus Surgery: a Propensity Score Matching, Real-World Cohort Study

Five-year Survival Analyses on Non-Pathological Complete Response Esophageal Squamous Cell Carcinoma Patients after Neoadjuvant Regimens plus Surgery: a Propensity Score Matching, Real-World Cohort Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Five-year Survival Analyses on Non-Pathological Complete Response Esophageal Squamous Cell Carcinoma Patients after Neoadjuvant Regimens plus Surgery: a Propensity Score Matching, Real-World Cohort Study Weibin Liu, Yujie Deng, Yan Lin, Yijin Lin, Xuejin Zheng, Weikun Su, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8484860/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Background Non-pathological complete response (non-pCR) is common in esophageal squamous cell carcinoma (ESCC) patients after neoadjuvant therapy, yet evidence guiding long-term outcome and postoperative risk stratification in the immunotherapy era remains limited. Methods We retrospectively enrolled consecutive ESCC patients treated with neoadjuvant immunochemotherapy (nICT) or chemotherapy alone (nCT) followed by esophagectomy and restricted analyses to non-pCR cases. Primary endpoints were five-year overall survival (OS) and event-free survival (EFS). Propensity score matching analysis and 60-month censoring were used to reduce differences between groups. Cox proportional hazards model was used for analysis. Results Among 366 non-pCR patients, 164 matched pairs were generated. After matching, nICT demonstrated a higher major pathological response (MPR) rate (19.5% vs 6.1%), a lower ypT4 proportion (3.7% vs 22.0%) and fewer recurrence/metastasis rate (40.2% vs 58.5%) (all p < 0.001). Five-year OS rate (50.6% vs 37.2%, p = 0.014) and EFS rate (50.0% vs 31.1%, p < 0.001) were higher in nICT group. In matched multivariable Cox model, nICT was independently associated with improved EFS (P = 0.005) but not OS (P = 0.707). Adverse EFS was independently associated with open esophagectomy (OE) (p = 0.003), ypN2-3 ( p < 0.001) and perineural invasion (PNI) (p = 0.003), while lower Ki-67 (p = 0.035) and postoperative adjuvant treatment (p = 0.012) were associated with improved EFS. For OS, PNI was an adverse factor (p = 0.004), whereas postoperative adjuvant treatment was a protective one (p < 0.001). Conclusion Among non-pCR ESCC patients after neoadjuvant therapy and surgery, nICT was associated with lower recurrence risk and improved five-year EFS compared with nCT, whereas a significant OS advantage was not observed. Pathological factors (PNI, high Ki-67, and residual nodal burden) and postoperative treatment were important correlates of long-term outcomes and may inform postoperative risk stratification and management. esophageal squamous cell carcinoma non-pathological complete response neoadjuvant immunochemotherapy perineural invasion Ki-67 Figures Figure 1 Figure 2 Figure 3 Introduction Esophageal squamous cell carcinoma (ESCC) remains a major cause of cancer-related mortality worldwide, particularly in Northern Europe, China and East Asia 1 , 2 . Currently, neoadjuvant chemoradiotherapy (nCRT) or neoadjuvant chemotherapy (nCT) combined with surgery remains the standard treatment for locally advanced esophageal cancer (EC) 3 – 5 . With the advent and wide application of immune checkpoint blockades, such as PD-1/PD-L1 inhibitors, neoadjuvant immunochemotherapy (nICT) has turned out an important part of the multimodal treatment of ESCC 6 . Phase II-III trials and real-world cohort studies had consistently shown that nICT improves pathological complete response (pCR) rates and may probably translate into survival benefits compared with chemotherapy alone 7 – 10 . Although pCR is a well-recognized favorable surrogate endpoint, a majority of patients would inevitably have residual disease (non-pCR) after neoadjuvant therapy 11 . In clinical practice, non-pCR patients represent a biologically heterogeneous and clinically prevalent population with substantial risk of recurrence in tumor site or distant metastasis, for whom optimal postoperative risk stratification, surveillance intensity, and adjuvant strategy remain uncertain 12 , 13 . Moreover, while pathological response metrics are increasingly used to benchmark neoadjuvant regimens, the extent to which pathologic response fully captures long-term benefit remains debated 14 , 15 . Our current study therefore focused on the clinically prevalent non-pCR population, aiming to determine whether neoadjuvant regimen choice (nICT or nCT) remains prognostically relevant after resection. We compared long-term outcomes using propensity score matching and standardized follow-up windows, and we explored clinicopathological predictors that could support pathology-anchored postoperative risk stratification. Methods 2.1. Study design and patients This was a single-center retrospective cohort study conducted at Fujian Medical University Cancer Hospital. Consecutive patients with histologically confirmed as ESCC who received neoadjuvant therapy followed by esophagectomy with lymphadenectomy between January 2017 and December 2023 were screened ( Fig. 1 ) . The inclusion criteria were: (1) histologically confirmed as ESCC; (2) underwent preoperative nICT or nCT; and (3) underwent esophagectomy and lymphadenectomy. The exclusion criteria were: (1) cervical or esophagogastric junction ESCC; (2) esophageal adenocarcinoma, small cell carcinoma, or other histology; (3) Non-regional lymph node metastasis and/or distant organ metastasis, except supraclavicular lymph node metastasis; (4) received preoperative other antitumor therapies; (5) simultaneously combined with other malignant tumors; (6) incomplete medical records; and (7) patients with pCR. 2.2. Neoadjuvant therapy and surgery All patients completed at least one cycle of neoadjuvant therapy before surgery, administered every 3 weeks. nCT consists of a taxane (paclitaxel, albumin-bound paclitaxel, or docetaxel) plus a platinum agent (cisplatin, carboplatin, lobaplatin, or nedaplatin). nICT includes the addition of a PD-1 inhibitor (pembrolizumab, camrelizumab, tislelizumab, toripalimab, serplulimab or sintilimab) to the nCT base regimen. All patients underwent esophagectomy and lymphadenectomy after neoadjuvant therapy. Surgeries included open esophagectomy (OE) or minimally invasive esophagectomy (MIE), mainly McKeown or Ivor-Lewis procedure. Resected tumor and lymph node specimens were evaluated by two independent pathologists. pCR was defined as the absence of any viable cancer cells at both the primary tumor site and the regional lymph nodes and major pathological response (MPR) was defined as < 10% viable tumor cells in the primary tumor bed 16 . All patients except pCR were classified as non-pCR. 2.3. Collection of clinicopathological data Data were collected from the hospital's medical record, including: age, gender, body mass index (BMI), personal medical history, esophageal tumor location, neoadjuvant treatment regimen, surgical data, pathological data, clinical TNM staging (cT, cN and cM), and auxiliary examination data. The pathological data include TNM staging (ypT, ypN and ypM), perineural invasion (PNI), lymphovascular invasion (LVI), tumor pathological response, Ki-67, histologic grade and margin status, etc. TNM staging was based on the AJCC 8th edition 17 . Ki-67 was divided into high (> 0.65) and low ( < = 0.65) groups according to the median. Postoperative treatment (post_treatment) information is postoperative adjuvant therapy, excluding treatment after recurrence and/or metastasis. 2.4. Endpoints and Follow-up The study endpoints were five-year OS and five-year EFS. OS was defined as the time from initiation of neoadjuvant therapy to death from any cause. EFS was defined as the time from initiation of neoadjuvant therapy to the first occurrence of recurrence/metastasis or death, whichever occurred first. To mitigate bias from unequal follow-up between regimens, survival time was administratively censored at 60 months for both endpoints. Patients without an event were censored at the last follow-up date or 60 months, whichever came first. Follow-up was conducted through outpatient reviews, inpatient records, and telephone inquiry. Recurrence/metastasis was confirmed by imaging and/or pathological examination. 2.5. Statistical analysis Continuous variables were described with the use of medians (Q1, Q3) and categorical variables with the use of counts (percentages). Differences between groups were compared using the chi-square test or Fisher’s exact test for categorical variables and the Wilcoxon rank-sum test for continuous variables as appropriate. Propensity scores were estimated using logistic regression including the covariates listed in Table 1 , followed by 1:1 optimal pair matching without replacement (MatchIt package, R). Covariate balance was assessed using standardized mean differences. OS and EFS were estimated using the Kaplan-Meier method and compared using the log-rank test. Cox proportional hazards models were used for univariable and multivariable analyses in both the overall cohort and the matched cohort; robust standard errors clustered by matched pair were used for analyses after propensity score matching (PSM). All tests were two-sided and p < 0.05 was considered statistically significant. Analyses were conducted using R software (Version 4.2.2). Table 1 Baseline characteristics before and after propensity score matching. Characteristics Unmatched Matched nICT N = 202 nCT N = 164 p-value nICT N = 164 nCT N = 164 p-value Age , Median (Q1, Q3) 62 (56, 68) 60 (55, 66) 0.045 1 62 (55, 67) 60 (55, 66) 0.155 1 Sex , n (%) 0.195 2 0.286 2 Female 38 (19%) 40 (24%) 32 (20%) 40 (24%) Male 164 (81%) 124 (76%) 132 (80%) 124 (76%) BMI , Median (Q1, Q3) 21.48 (19.37, 23.42) 21.55 (20.01, 23.82) 0.199 1 21.62 (19.51, 23.58) 21.55 (20.01, 23.82) 0.551 1 Smoker , n (%) 82 (41%) 66 (40%) 0.946 2 66 (40%) 66 (40%) > 0.999 2 Drinker , n (%) 38 (19%) 32 (20%) 0.865 2 33 (20%) 32 (20%) 0.890 2 cT , n (%) 0.387 2 0.517 2 T1-2 31 (15%) 20 (12%) 24 (15%) 20 (12%) T3-4 171 (85%) 144 (88%) 140 (85%) 144 (88%) cN , n (%) 0.719 2 0.721 2 N0 30 (15%) 26 (16%) 22 (13%) 26 (16%) N1-2 161 (80%) 126 (77%) 132 (80%) 126 (77%) N3 11 (5%) 12 (7%) 10 (6%) 12 (7%) cM , n (%) 0.079 3 > 0.999 3 M0 195 (97%) 163 (99%) 164 (100%) 163 (99%) M1 (lymph nodes) 7 (3%) 1 (1%) 0 (0%) 1 (1%) Neoadjuvant treatment cycles , n (%) < 0.001 2 0.604 2 1 21 (10%) 18 (11%) 19 (12%) 18 (11%) 2 145 (72%) 139 (85%) 134 (82%) 139 (85%) ˃=3 36 (18%) 7 (4%) 11 (7%) 7 (4%) Surgical type , n (%) 0.001 2 0.024 2 MIE 167 (83%) 112 (68%) 130 (79%) 112 (68%) OE 35 (17%) 52 (32%) 34 (21%) 52 (32%) Resection degree , n (%) 0.057 2 0.170 2 Non-R0 41 (20%) 21 (13%) 30 (18%) 21 (13%) R0 161 (80%) 143 (87%) 134 (82%) 143 (87%) Post_treatment , n (%) 0.467 2 0.629 2 No 65 (32%) 47 (29%) 51 (31%) 47 (29%) Yes 137 (68%) 117 (71%) 113 (69%) 117 (71%) 1 Wilcoxon rank sum test; 2 Pearson's Chi-squared test; 3 Fisher's exact test. Abbreviations: nICT, neoadjuvant immunochemotherapy; nCT, neoadjuvant chemotherapy; MIE, Minimally Invasive Esophagectomy; OE, Open Esophagectomy; Post_treatment, postoperative adjuvant therapy. Legends: Table 1 presents the basic clinical characteristic data of the two groups (nICT vs nCT) before and after PSM. Results 3.1. Patient base characteristics A total of 366 non-pCR patients were included (nICT = 202; nCT = 164). Before matching, several characteristics differed between groups, including age, neoadjuvant cycle distribution, and surgical approach. PSM yielded 164 well-matched pairs and improved comparability between treatment groups (Table 1 ). 3.2. Pathological findings Post-treatment pathological staging, tumor response, pathological risk features and are summarized in Table 2 . After matching, patients receiving nICT had a higher rate of MPR (19.5% vs 6.1%) and a lower proportion of ypT4 (3.7% vs 22.0%) compared with nCT, suggesting deeper tumor regression. The five-year OS rate and five-year EFS rate of the nICT group were both higher than those of the nCT group (five-year OS rate, 50.6% vs 37.2%; p = 0.014; five-year EFS rate, 50.0% vs 31.1%; p < 0.001). The incidence of recurrence/metastasis during follow-up was also lower in the nICT group (40.2% vs 58.5%, p < 0.001). Table 2 Post-treatment pathological characteristics and postoperative outcomes before and after propensity score matching. Characteristic Unmatched Matched nICT N = 202 nCT N = 164 p-value nICT N = 164 nCT N = 164 p-value 1 Ki-67 , Median (Q1, Q3) 0.60 (0.50, 0.80) 0.70 (0.50, 0.80) 0.946 1 0.65 (0.50, 0.80) 0.70 (0.50, 0.80) 0.801 1 Ki-67 Group , n (%) 0.744 2 0.878 2 High 65 (48.9%) 47 (51.1%) 54 (50.0%) 47 (51.1%) Low 68 (51.1%) 45 (48.9%) 54 (50.0%) 45 (48.9%) Histologic Grade , n (%) 0.117 3 0.113 3 G1 36 (19.3%) 18 (11.4%) 30 (19.9%) 18 (11.4%) G2 147 (78.6%) 135 (85.4%) 117 (77.5%) 135 (85.4%) G3 4 (2.1%) 5 (3.2%) 4 (2.6%) 5 (3.2%) PNI , n (%) 76 (37.6%) 40 (24.4%) 0.007 2 58 (35.4%) 40 (24.4%) 0.030 2 LVI , n (%) 107 (53.0%) 80 (48.8%) 0.425 2 88 (53.7%) 80 (48.8%) 0.377 2 Tumor response , n (%) < 0.001 2 < 0.001 2 MPR 41 (20.3%) 10 (6.1%) 32 (19.5%) 10 (6.1%) PR 161 (79.7%) 154 (93.9%) 132 (80.5%) 154 (93.9%) ypT , n (%) < 0.001 2 < 0.001 2 T0-2 79 (39.1%) 36 (22.0%) 64 (39.0%) 36 (22.0%) T3 115 (56.9%) 92 (56.1%) 94 (57.3%) 92 (56.1%) T4 8 (4.0%) 36 (22.0%) 6 (3.7%) 36 (22.0%) ypN , n (%) 0.178 2 0.119 2 N0 99 (49.0%) 78 (47.6%) 77 (47.0%) 78 (47.6%) N1 64 (31.7%) 42 (25.6%) 56 (34.1%) 42 (25.6%) N2-3 39 (19.3%) 44 (26.8%) 31 (18.9%) 44 (26.8%) ypM , n (%) 0.865 2 > 0.999 2 M0 185 (91.6%) 151 (92.1%) 151 (92.1%) 151 (92.1%) M1(lymph nodes) 17 (8.4%) 13 (7.9%) 13 (7.9%) 13 (7.9%) OS , Median (Q1, Q3) 859 (631, 1,213) 1,075 (508, 2,129) < 0.001 1 860 (680, 1,224) 1,075 (508, 2,129) 0.004 1 EFS , Median (Q1, Q3) 747 (341, 1,091) 645 (261, 2,041) 0.178 1 774 (357, 1115) 645 (261, 2,041) 0.270 1 Five-year OS rate, n(%) 99 (49.0%) 61 (37.2%) 0.023 2 83 (50.6%) 61 (37.2%) 0.014 2 Five-year EFS rate, n(%) 98 (48.5%) 51 (31.1%) < 0.001 2 82 (50.0%) 51 (31.1%) < 0.001 2 Recurrence/Metastasis , n (%) 83 (41.1%) 96 (58.5%) < 0.001 2 66 (40.2%) 96 (58.5%) < 0.001 2 1 Wilcoxon rank sum test, 2 Pearson's Chi-squared test, 3 Fisher's exact test. Abbreviations: nICT, neoadjuvant immunochemotherapy; nCT, neoadjuvant chemotherapy; PNI, perineural invasion; LVI, lymphovascular invasion; MPR, major pathological response; OS, overall survival; EFS, event-free survival. Legends: Table 2 presents the postoperative pathological characteristics and five-year survival data of the two groups before and after PSM. 3.3. Univariate and multivariate regression analyses of the five-year OS and EFS. Cox regression results for five-year OS and five-year EFS are presented in Supplementary table 1 –2 . After matching, nICT was associated with a significantly lower risk of EFS events (HR 0.55, 95% CI 0.36–0.84; P = 0.005). In contrast, five-year OS did not differ significantly between treatment groups (HR 0.94, 95% CI 0.70–1.27; P = 0.707). In the matched multivariable model for EFS, OE (HR 1.87, 95% CI 1.24–2.83; p = 0.003), ypN2-3 (HR 2.82, 95% CI 1.55–5.11; p < 0.001), and PNI (HR 1.93, 95% CI 1.24-3.00; p = 0.003) were independently associated with worse EFS. In addition, lower Ki-67 (HR 0.65, 95% CI 0.44–0.97; p = 0.035) and postoperative adjuvant treatment (HR 0.57, 95% CI 0.36–0.88; p = 0.012) are protective factors for EFS. For OS, PNI was an adverse factor (HR 1.66, 95% CI 1.17–2.36; p = 0.004), whereas postoperative adjuvant treatment was protective (HR 0.54, 95% CI 0.39–0.77; p < 0.001). The main influencing factors associated with 5-year OS and 5-year EFS are shown in Fig. 2 forest plots and Fig. 3 survival curves. Discussion In this real-world cohort restricted to the clinically prevalent non-pCR ESCC population, nICT was associated with a meaningful reduction in relapse risk and improvement in long-term EFS compared with nCT after rigorous adjustment, including propensity score matching and administrative censoring at 60 months. Specifically, the nICT group demonstrated higher 5-year OS and 5-year EFS rates than the nCT group, and in the matched cohort nICT was linked to a significantly lower risk of EFS events, whereas the difference in 5-year OS was not statistically significant. These research results indicate that even if a patient does not achieve pCR, nICT can still show clinically benefits. Beyond regimen selection, we identified a set of post-treatment pathological aggressiveness markers that independently stratified risk. In the matched multivariable model, ypN2-3 was among the strongest predictors of adverse EFS, underscoring the dominant prognostic role of residual nodal burden after neoadjuvant therapy. This is consistent with contemporary evidence showing that post-neoadjuvant nodal status (ypN) remains a major determinant of recurrence and survival after induction therapy and surgery in esophageal cancer, and that nodal downstaging is associated with superior outcomes 18 , 19 . We further identified post-treatment pathological aggressiveness markers, including PNI, LVI, high Ki-67, and margin status (non-R0 resection), as independent predictors of adverse outcomes. The prognostic impact of PNI and LVI in our cohort aligns with prior evidence that these histopathologic features indicate aggressive invasion patterns and a higher propensity for dissemination 20 . A recent study incorporating PNI and LVI demonstrated their utility for recurrence risk modeling after neoadjuvant chemoradiotherapy and esophagectomy in ESCC 21 . Evidence also continues to support the prognostic relevance of margin involvement definitions (e.g., circumferential resection margin) for recurrence and survival, providing a rationale for incorporating margin status into postoperative risk assessment 22 . In addition, high Ki-67 expression indicates higher proliferative activity and is associated with poorer survival rates in patients with esophageal squamous cell carcinoma, which is consistent with previous study 23 , 24 . These variables are readily available in routine pathology and may support practical, pathology-anchored risk stratification to guide surveillance intensity and adjuvant decision-making. The protective association of postoperative adjuvant treatment across both OS and EFS in our matched cohort suggested that postoperative systemic therapy may partially mitigate residual micrometastatic risk in high-risk non-pCR patients. This interpretation is consistent with the evolving paradigm that adjuvant systemic therapy can translate residual pathological risk into improved disease control after multimodality management, supported by the emerging overall survival analysis from CheckMate 577 and corroborated by contemporary real-world matched comparisons of adjuvant nivolumab following neoadjuvant chemoradiotherapy and resection 25 , 26 . In addition, retrospective evidence further suggests that postoperative adjuvant therapy after neoadjuvant immunochemotherapy can benefit patients in pathological high-risk subgroups 13 . However, different regimens of postoperative adjuvant therapy and patient compliance may affect the readability of related outcomes. Prospective trials are still needed in the non-pCR population after neoadjuvant therapy to determine the best drug and patient selection criteria. The association between open esophagectomy and worse OS/EFS should be interpreted cautiously. Randomized trials comparing minimally invasive and open approaches reported reduced pulmonary complications with minimally invasive or hybrid techniques, with broadly comparable long-term oncologic survival 27 . Surgical approach may partially capture tumor extent, technical complexity, or perioperative complication burden, any of which could influence survival outcomes. The association between OE and worse OS/EFS should be interpreted cautiously, because operative approach may reflect confounding by indication (tumor extent, technical complexity), center/surgeon factors, and postoperative complication burden rather than a direct causal effect. Recent large systematic review indicate that MIE was superior to OE treatment in terms of blood loss, pulmonary complications, and length of hospital stay, but showed a balance in mortality, survival, and oncologic outcomes 28 . Notably, other high-quality studies have shown improved survival with MIE compared with OE 29,30 . At present, MIE should be recommended as a preferred surgical procedure. Several limitations should be mentioned: (1) As a single-center retrospective cohort study, selection bias and information bias were inevitable, and in the future a multicenter retrospective study would be conducted to further validate the current findings; (2) Different specific drugs within the neoadjuvant categories, despite sharing similar mechanisms, might have potential inter-drug differences affecting the outcomes; (3) Missingness in key variables such as Ki-67 and histologic grade was non-negligible; (4) Imaging modalities like CT have inherent false positives and negatives in assessing lymph node metastasis, potentially affecting accuracy in recurrence evaluation. Despite these limitations, the findings suggest that neoadjuvant regimen choice and post-treatment pathology provide effective prognostic information in non-pCR ESCC patients. Conclusions Among non-pCR ESCC patients after neoadjuvant therapy and surgery, nICT was associated with lower recurrence risk and improved five-year EFS compared with nCT, whereas a significant OS advantage was not observed. Pathological factors (PNI, high Ki-67, and residual nodal burden) and postoperative treatment were important correlates of long-term outcomes and may inform postoperative risk stratification and management. Abbreviations ESCC, esophageal squamous cell carcinoma; nICT, neoadjuvant immunochemotherapy; nCT, neoadjuvant chemotherapy; MIE, minimally invasive esophagectomy; OE, open esophagectomy; Post_treatment, postoperative adjuvant therapy; PNI, perineural invasion; LVI, lymphovascular invasion; non-pCR, non-pathological complete response; pCR, pathological complete response; MPR, major pathological response; OS, overall survival; EFS, event-free survival; PSM, propensity score matching. Declarations Ethics approval and consent to participate The study was approved by the Human Ethics Review Committee of Fujian Medical University Cancer Hospital (Approval No.: K2025-340-01), and relevant informed consent was waived. Consent for publication Not applicable. Competing interests The authors declare no competing interests. Availability of data and materials Data sharing is not applicable to this article as no new data were created or analyzed in this study. Funding This study was supported in part by Fujian Research and Training Grants for Young and Middle-aged Leaders in Healthcare (to Chen X.), the Natural Science Foundation of Fujian Province (Grant No: 2025J011193 to Chen X.) and Special Scientific Research Project of the Fujian Provincial Finance Department Undertaken by Fuzhou Traditional Chinese Medicine Hospital. (to Deng Y.). Author Contributions Conceptualization and Methodology: Weibin Liu, Yujie Deng, Xiaohui Chen and Yan Lin; Investigation and Resources: Weibin Liu, Yijin Lin, Weikun Su, Jiarong Zhang, Weijin Xiao and Yi Shi; Data curation and Formal analysis: Weibin Liu, Yujie Deng, Xiaohui Chen and Xuejin Zheng; Visualization: Weibin Liu and Yan Lin; Funding acquisition: Yujie Deng and Xiaohui Chen; Supervision and Project administration: Xiaohui Chen; Manuscript writing and editing: all authors. All authors have read and approved the final manuscript. Acknowledgements Not applicable Conflict of Interest The authors declared that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. References Bray F, 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. https://doi.org/10.3322/caac.21834 . He S, et al. Cancer profiles in China and comparisons with the USA: a comprehensive analysis in the incidence, mortality, survival, staging, and attribution to risk factors. Sci China Life Sci. 2024;67:122–31. https://doi.org/10.1007/s11427-023-2423-1 . Eyck BM, et al. Ten-Year Outcome of Neoadjuvant Chemoradiotherapy Plus Surgery for Esophageal Cancer: The Randomized Controlled CROSS Trial. J Clin Oncol. 2021;39:1995–2004. https://doi.org/10.1200/jco.20.03614 . Yang H, et al. Long-term Efficacy of Neoadjuvant Chemoradiotherapy Plus Surgery for the Treatment of Locally Advanced Esophageal Squamous Cell Carcinoma: The NEOCRTEC5010 Randomized Clinical Trial. JAMA Surg. 2021;156:721–9. https://doi.org/10.1001/jamasurg.2021.2373 . Matsuda S, et al. Real-world Evaluation of the Efficacy of Neoadjuvant DCF Over CF in Esophageal Squamous Cell Carcinoma: Propensity Score–matched Analysis From 85 Authorized Institutes for Esophageal Cancer in Japan. Ann Surg. 2023;278:e35–42. https://doi.org/10.1097/sla.0000000000005533 . Yang H, Wang F, Hallemeier CL, Lerut T, Fu J. Oesophageal cancer. Lancet. 2024;404:1991–2005. https://doi.org/10.1016/s0140-6736(24)02226-8 . Liu J, 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. https://doi.org/10.1136/jitc-2021-004291 . Qin J, et al. Neoadjuvant chemotherapy with or without camrelizumab in resectable esophageal squamous cell carcinoma: the randomized phase 3 ESCORT-NEO/NCCES01 trial. Nat Med. 2024;30:2549–57. https://doi.org/10.1038/s41591-024-03064-w . Zheng Y, et al. Perioperative toripalimab plus neoadjuvant chemotherapy might improve outcomes in resectable esophageal cancer: an interim analysis of a phase III randomized clinical trial. Cancer Commun (Lond). 2024;44:1214–27. https://doi.org/10.1002/cac2.12604 . Shang X, et al. A prospective study of neoadjuvant pembrolizumab plus chemotherapy for resectable esophageal squamous cell carcinoma: The Keystone-001 trial. Cancer Cell. 2024;42:1747–e17631747. https://doi.org/10.1016/j.ccell.2024.09.008 . Gaber CE, et al. Pathologic complete response in patients with esophageal cancer receiving neoadjuvant chemotherapy or chemoradiation: A systematic review and meta-analysis. Cancer Med. 2024;13:e7076. https://doi.org/10.1002/cam4.7076 . Lin L, et al. A pathologic classification approach in esophageal squamous cell carcinoma following neoadjuvant immunochemotherapy: Distinguishing postoperative outcomes and exploring the potential benefit of adjuvant therapy. J Thorac Cardiovasc Surg. 2025;170:1284–e12941212. https://doi.org/10.1016/j.jtcvs.2025.06.012 . Feng J, Wang L, Yang X, Chen Q. Adjuvant immunotherapy after neoadjuvant immunochemotherapy and esophagectomy for esophageal squamous cell carcinoma: a real-world study. Front Immunol. 2024;15:1456193. https://doi.org/10.3389/fimmu.2024.1456193 . Hong Z, et al. Major pathologic response as a prognostic surrogate in esophageal squamous cell carcinoma patients receiving neoadjuvant chemotherapy/chemoimmunotherapy: A multi-center cohort study. Eur J Surg Oncol. 2025;51:109500. https://doi.org/10.1016/j.ejso.2024.109500 . Sugiyama K, et al. Is pathological response an adequate surrogate marker for survival in neoadjuvant therapy with immune checkpoint inhibitors? ESMO Open. 2025;10:104122. https://doi.org/10.1016/j.esmoop.2024.104122 . Becker K, et al. Histomorphology and grading of regression in gastric carcinoma treated with neoadjuvant chemotherapy. Cancer. 2003;98:1521–30. https://doi.org/10.1002/cncr.11660 . Rice TW, Ishwaran H, Ferguson MK, Blackstone EH, Goldstraw P. Cancer of the Esophagus and Esophagogastric Junction: An Eighth Edition Staging Primer. J Thorac Oncol. 2017;12:36–42. https://doi.org/10.1016/j.jtho.2016.10.016 . Leng X, et al. Prognostic Impact of Postoperative Lymph Node Metastases After Neoadjuvant Chemoradiotherapy for Locally Advanced Squamous Cell Carcinoma of Esophagus: From the Results of NEOCRTEC5010, a Randomized Multicenter Study. Ann Surg. 2021;274:e1022–9. https://doi.org/10.1097/sla.0000000000003727 . Huang Y, et al. Impact of lymph node dissection on survival after neoadjuvant immunochemotherapy for esophageal squamous cell cancer: a double-center real-world retrospective study. Cancer Immunol Immunother. 2025;74:303. https://doi.org/10.1007/s00262-025-04168-z . Xiong J, et al. The impact of perineural invasion on prognosis in esophageal cancer patients after surgery: a systematic review and meta-analysis. Front Oncol. 2025;15:1629335. https://doi.org/10.3389/fonc.2025.1629335 . Zhou J, et al. Lymphovascular and Perineural Invasion After Neoadjuvant Therapy in Esophageal Squamous Carcinoma. Ann Thorac Surg. 2023;115:1386–94. https://doi.org/10.1016/j.athoracsur.2022.07.052 . Elshaer AM, et al. The prognostic value of circumferential resection margin (CRM) definition and location in esophageal cancer: A 12-year cohort study. Eur J Surg Oncol. 2025;51:110138. https://doi.org/10.1016/j.ejso.2025.110138 . Wang Y, Dai M, Chen X. Prognostic and clinicopathological value of Ki-67 in patients with oesophageal squamous cell carcinoma: a systematic review and meta-analysis. BMJ Open. 2024;14:e083637. https://doi.org/10.1136/bmjopen-2023-083637 . Zheng J, et al. Exploratory analyses of the associations between Ki-67 expression, lymph node metastasis, and prognosis in patients with esophageal squamous cell cancer. PeerJ. 2025;13:e19062. https://doi.org/10.7717/peerj.19062 . Verhoeven RHA, et al. Adjuvant nivolumab after chemoradiotherapy and resection for patients with esophageal cancer: A real-world matched comparison of overall survival. Int J Cancer. 2025. https://doi.org/10.1002/ijc.70168 . Kelly RJ, Ajani JA, Kuzdzal J. Adjuvant nivolumab in resected esophageal or gastroesophageal junction cancer. N Engl J Med. 2021;384:1191–203. https://doi.org/10.1056/NEJMoa2032125 . Mariette C, Markar SR, Dabakuyo-Yonli TS. Hybrid minimally invasive esophagectomy for esophageal cancer. N Engl J Med. 2019;380:152–62. https://doi.org/10.1056/NEJMoa1805101 . Dunne N, Davey MG, Donlon NE. Comparing outcomes following open, hybrid, minimally invasive, and robotic-assisted esophagectomy: A systematic review. Eur J Surg Oncol. 2026;52:110531. https://doi.org/10.1016/j.ejso.2025.110531 . Henckens SPG, et al. Recurrence and Survival After Minimally Invasive and Open Esophagectomy for Esophageal Cancer: A Post Hoc Analysis of the Ensure Study. Ann Surg. 2024;280:267–73. https://doi.org/10.1097/sla.0000000000006280 . Igaue S, et al. Long-term Survival in Esophageal Cancer: Comparison of Minimally Invasive and Open Esophagectomy. Ann Thorac Surg. 2025;119:805–14. https://doi.org/10.1016/j.athoracsur.2024.09.004 . Additional Declarations No competing interests reported. Supplementary Files Supplementarytables.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 28 Jan, 2026 Reviewers agreed at journal 25 Jan, 2026 Reviewers invited by journal 23 Jan, 2026 Editor invited by journal 02 Jan, 2026 Editor assigned by journal 01 Jan, 2026 Submission checks completed at journal 01 Jan, 2026 First submitted to journal 30 Dec, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8484860","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":580186765,"identity":"3e5d62d6-a17c-4d56-bc0f-3d125f73ee7e","order_by":0,"name":"Weibin Liu","email":"","orcid":"","institution":"Clinical Oncology School of Fujian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Weibin","middleName":"","lastName":"Liu","suffix":""},{"id":580186766,"identity":"dd246d96-c600-42f7-8e93-01eb249d9702","order_by":1,"name":"Yujie Deng","email":"","orcid":"","institution":"The First Affiliated Hospital of Fujian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yujie","middleName":"","lastName":"Deng","suffix":""},{"id":580186767,"identity":"f2d309c5-9739-452e-aee8-dde0c5d0d5d7","order_by":2,"name":"Yan Lin","email":"","orcid":"","institution":"Clinical Oncology School of Fujian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yan","middleName":"","lastName":"Lin","suffix":""},{"id":580186768,"identity":"b2460d93-e4de-4b55-9469-5ba0d4904975","order_by":3,"name":"Yijin Lin","email":"","orcid":"","institution":"Clinical Oncology School of Fujian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yijin","middleName":"","lastName":"Lin","suffix":""},{"id":580186769,"identity":"de25434b-d6c2-476b-bc90-5ad8cee28f12","order_by":4,"name":"Xuejin Zheng","email":"","orcid":"","institution":"Interdisciplinary Institute of Medical Engineering of Fuzhou University","correspondingAuthor":false,"prefix":"","firstName":"Xuejin","middleName":"","lastName":"Zheng","suffix":""},{"id":580186770,"identity":"8e575f65-9bf1-47ae-b449-522f8903f6f3","order_by":5,"name":"Weikun Su","email":"","orcid":"","institution":"Clinical Oncology School of Fujian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Weikun","middleName":"","lastName":"Su","suffix":""},{"id":580186771,"identity":"5c7a7f8f-d6bc-4ca5-a3cf-be0acbbd499e","order_by":6,"name":"Weijin Xiao","email":"","orcid":"","institution":"Clinical Oncology School of Fujian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Weijin","middleName":"","lastName":"Xiao","suffix":""},{"id":580186772,"identity":"f6e249c8-8bb3-44fc-be3c-6ab43555f5d5","order_by":7,"name":"Yi Shi","email":"","orcid":"","institution":"Clinical Oncology School of Fujian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yi","middleName":"","lastName":"Shi","suffix":""},{"id":580186773,"identity":"941d9d72-6960-4219-853b-3ca5141470ca","order_by":8,"name":"Jiarong Zhang","email":"","orcid":"","institution":"Clinical Oncology School of Fujian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Jiarong","middleName":"","lastName":"Zhang","suffix":""},{"id":580186774,"identity":"78c68e6b-12c3-483d-82a2-f7e4813a142d","order_by":9,"name":"Xiaohui Chen","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA50lEQVRIiWNgGAWjYBACxgYoYcDe+MAALHSAaC08hw2I0wLXZyCRDNFBUAtze/vDx4U77BK3Sz5mKLrZxiDHdyOB8XMBPgt6zhgbzzyTbGw5O5nBOLeNwVjyRgKz9Ax8WmbksEnzth2QM7idfwCkJXHDjQQ2Zh68WtKf/wZq4TG4eRhsSz0RWhLMmMG23GAGa0kwIKgF6BfpmW3JxgZngH7JOSdhOPPMw2ZpfFoMgSH2ubDNLnHD8cNsxjllNvJ8x5MPfsarpQEY0FA2GzBiJBig0YsbyDMgtDA/wKt0FIyCUTAKRiwAALyMS/G3ccTTAAAAAElFTkSuQmCC","orcid":"","institution":"Clinical Oncology School of Fujian Medical University","correspondingAuthor":true,"prefix":"","firstName":"Xiaohui","middleName":"","lastName":"Chen","suffix":""}],"badges":[],"createdAt":"2025-12-31 01:23:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8484860/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8484860/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":101364318,"identity":"7ac8ee7f-d3fb-4be1-a73f-42f992cded1a","added_by":"auto","created_at":"2026-01-29 00:47:36","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":2292799,"visible":true,"origin":"","legend":"\u003cp\u003ePatient inclusion flowchart (non-pCR cohort: N=366; after Propensity Score Matched: nICT=164, nCT=164).\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-8484860/v1/b27234c1500e22124c714e6f.png"},{"id":101398082,"identity":"afc119f1-8356-46ec-a085-16759ceac74c","added_by":"auto","created_at":"2026-01-29 09:39:31","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1631905,"visible":true,"origin":"","legend":"\u003cp\u003eForest plots of univariable and multivariable regression analyses for five-year OS and five-year EFS. Forest plots showing hazard ratios (HRs) with 95% confidence intervals (CIs) for factors associated with five-year overall survival (OS) and five-year event-free survival (EFS) after propensity score matching (PSM). OS1 and EFS1 denote univariable Cox proportional hazards models, whereas OS2 and EFS2 denote multivariable Cox proportional hazards models. HR \u0026gt;1 indicate increased risk of OS or EFS events, and HR \u0026lt;1 indicate decreased risk.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-8484860/v1/1fcfee4100beff2d3acc3699.png"},{"id":101364321,"identity":"457ec367-c012-4b40-a41b-1c6f10771c2b","added_by":"auto","created_at":"2026-01-29 00:47:36","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":4473148,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan–Meier survival curves and cumulative event curves for five-year OS and five-year EFS by key clinicopathological factors. Panels A1–A9 display OS according to each factor, and panels B1–B9 display the corresponding cumulative incidence of EFS events. A1/B1, group (nICT vs nCT); A2/B2, lymphovascular invasion (No vs Yes); A3/B3, resection degree (R0 vs non-R0); A4/B4, postoperative pathological T staging (ypT0-2 vs ypT3 vs ypT4); A5/B5, surgery (MIE vs OE); A6/B6, perineural invasion (No vs Yes); A7/B7, Ki-67 (Low vs High); A8/B8, postoperative pathological N staging (ypN0 vs ypN1 vs ypN2-3); A9/B9, post_treatment (No vs Yes).\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-8484860/v1/2d82e43dfc623e8c81226783.png"},{"id":101399403,"identity":"0607cb6e-dbf4-401e-bad5-52da0179ce22","added_by":"auto","created_at":"2026-01-29 09:53:00","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":9690410,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8484860/v1/0a8af5c7-beed-4aad-a512-4af1eefb113f.pdf"},{"id":101398623,"identity":"f99cc679-d168-41d3-b90c-df97eab4bfba","added_by":"auto","created_at":"2026-01-29 09:43:05","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":54191,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarytables.docx","url":"https://assets-eu.researchsquare.com/files/rs-8484860/v1/42e0d6ceedf298d686fbbc32.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Five-year Survival Analyses on Non-Pathological Complete Response Esophageal Squamous Cell Carcinoma Patients after Neoadjuvant Regimens plus Surgery: a Propensity Score Matching, Real-World Cohort Study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eEsophageal squamous cell carcinoma (ESCC) remains a major cause of cancer-related mortality worldwide, particularly in Northern Europe, China and East Asia\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Currently, neoadjuvant chemoradiotherapy (nCRT) or neoadjuvant chemotherapy (nCT) combined with surgery remains the standard treatment for locally advanced esophageal cancer (EC)\u003csup\u003e\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. With the advent and wide application of immune checkpoint blockades, such as PD-1/PD-L1 inhibitors, neoadjuvant immunochemotherapy (nICT) has turned out an important part of the multimodal treatment of ESCC\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Phase II-III trials and real-world cohort studies had consistently shown that nICT improves pathological complete response (pCR) rates and may probably translate into survival benefits compared with chemotherapy alone\u003csup\u003e\u003cspan additionalcitationids=\"CR8 CR9\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAlthough pCR is a well-recognized favorable surrogate endpoint, a majority of patients would inevitably have residual disease (non-pCR) after neoadjuvant therapy\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. In clinical practice, non-pCR patients represent a biologically heterogeneous and clinically prevalent population with substantial risk of recurrence in tumor site or distant metastasis, for whom optimal postoperative risk stratification, surveillance intensity, and adjuvant strategy remain uncertain\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. Moreover, while pathological response metrics are increasingly used to benchmark neoadjuvant regimens, the extent to which pathologic response fully captures long-term benefit remains debated\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eOur current study therefore focused on the clinically prevalent non-pCR population, aiming to determine whether neoadjuvant regimen choice (nICT or nCT) remains prognostically relevant after resection. We compared long-term outcomes using propensity score matching and standardized follow-up windows, and we explored clinicopathological predictors that could support pathology-anchored postoperative risk stratification.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Study design and patients\u003c/h2\u003e \u003cp\u003eThis was a single-center retrospective cohort study conducted at Fujian Medical University Cancer Hospital. Consecutive patients with histologically confirmed as ESCC who received neoadjuvant therapy followed by esophagectomy with lymphadenectomy between January 2017 and December 2023 were screened \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. The inclusion criteria were: (1) histologically confirmed as ESCC; (2) underwent preoperative nICT or nCT; and (3) underwent esophagectomy and lymphadenectomy. The exclusion criteria were: (1) cervical or esophagogastric junction ESCC; (2) esophageal adenocarcinoma, small cell carcinoma, or other histology; (3) Non-regional lymph node metastasis and/or distant organ metastasis, except supraclavicular lymph node metastasis; (4) received preoperative other antitumor therapies; (5) simultaneously combined with other malignant tumors; (6) incomplete medical records; and (7) patients with pCR.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Neoadjuvant therapy and surgery\u003c/h2\u003e \u003cp\u003eAll patients completed at least one cycle of neoadjuvant therapy before surgery, administered every 3 weeks. nCT consists of a taxane (paclitaxel, albumin-bound paclitaxel, or docetaxel) plus a platinum agent (cisplatin, carboplatin, lobaplatin, or nedaplatin). nICT includes the addition of a PD-1 inhibitor (pembrolizumab, camrelizumab, tislelizumab, toripalimab, serplulimab or sintilimab) to the nCT base regimen. All patients underwent esophagectomy and lymphadenectomy after neoadjuvant therapy. Surgeries included open esophagectomy (OE) or minimally invasive esophagectomy (MIE), mainly McKeown or Ivor-Lewis procedure. Resected tumor and lymph node specimens were evaluated by two independent pathologists. pCR was defined as the absence of any viable cancer cells at both the primary tumor site and the regional lymph nodes and major pathological response (MPR) was defined as \u0026lt;\u0026thinsp;10% viable tumor cells in the primary tumor bed\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. All patients except pCR were classified as non-pCR.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Collection of clinicopathological data\u003c/h2\u003e \u003cp\u003eData were collected from the hospital's medical record, including: age, gender, body mass index (BMI), personal medical history, esophageal tumor location, neoadjuvant treatment regimen, surgical data, pathological data, clinical TNM staging (cT, cN and cM), and auxiliary examination data. The pathological data include TNM staging (ypT, ypN and ypM), perineural invasion (PNI), lymphovascular invasion (LVI), tumor pathological response, Ki-67, histologic grade and margin status, etc. TNM staging was based on the AJCC 8th edition\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. Ki-67 was divided into high (\u0026gt;\u0026thinsp;0.65) and low (\u0026thinsp;\u0026lt;\u0026thinsp;=\u0026thinsp;0.65) groups according to the median. Postoperative treatment (post_treatment) information is postoperative adjuvant therapy, excluding treatment after recurrence and/or metastasis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Endpoints and Follow-up\u003c/h2\u003e \u003cp\u003eThe study endpoints were five-year OS and five-year EFS. OS was defined as the time from initiation of neoadjuvant therapy to death from any cause. EFS was defined as the time from initiation of neoadjuvant therapy to the first occurrence of recurrence/metastasis or death, whichever occurred first. To mitigate bias from unequal follow-up between regimens, survival time was administratively censored at 60 months for both endpoints. Patients without an event were censored at the last follow-up date or 60 months, whichever came first. Follow-up was conducted through outpatient reviews, inpatient records, and telephone inquiry. Recurrence/metastasis was confirmed by imaging and/or pathological examination.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Statistical analysis\u003c/h2\u003e \u003cp\u003eContinuous variables were described with the use of medians (Q1, Q3) and categorical variables with the use of counts (percentages). Differences between groups were compared using the chi-square test or Fisher\u0026rsquo;s exact test for categorical variables and the Wilcoxon rank-sum test for continuous variables as appropriate. Propensity scores were estimated using logistic regression including the covariates listed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, followed by 1:1 optimal pair matching without replacement (MatchIt package, R). Covariate balance was assessed using standardized mean differences. OS and EFS were estimated using the Kaplan-Meier method and compared using the log-rank test. Cox proportional hazards models were used for univariable and multivariable analyses in both the overall cohort and the matched cohort; robust standard errors clustered by matched pair were used for analyses after propensity score matching (PSM). All tests were two-sided and p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant. Analyses were conducted using R software (Version 4.2.2).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline characteristics before and after propensity score matching.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eUnmatched\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eMatched\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003enICT\u003c/b\u003e \u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;202\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003enCT\u003c/b\u003e \u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;164\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003ep-value\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003enICT\u003c/b\u003e \u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;164\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003enCT\u003c/b\u003e \u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;164\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003ep-value\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e, Median (Q1, Q3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e62 (56, 68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60 (55, 66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.045\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e62 (55, 67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e60 (55, 66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.155\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.195\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.286\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38 (19%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40 (24%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e32 (20%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e40 (24%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e164 (81%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e124 (76%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e132 (80%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e124 (76%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBMI\u003c/b\u003e, Median (Q1, Q3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21.48 (19.37, 23.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.55 (20.01, 23.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.199\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21.62 (19.51, 23.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21.55 (20.01, 23.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.551\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSmoker\u003c/b\u003e, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e82 (41%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66 (40%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.946\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e66 (40%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e66 (40%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.999\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDrinker\u003c/b\u003e, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38 (19%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32 (20%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.865\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e33 (20%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e32 (20%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.890\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ecT\u003c/b\u003e, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.387\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.517\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT1-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31 (15%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20 (12%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24 (15%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20 (12%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT3-4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e171 (85%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e144 (88%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e140 (85%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e144 (88%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ecN\u003c/b\u003e, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.719\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.721\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30 (15%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26 (16%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22 (13%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e26 (16%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN1-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e161 (80%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e126 (77%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e132 (80%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e126 (77%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11 (5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10 (6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12 (7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ecM\u003c/b\u003e, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.079\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.999\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eM0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e195 (97%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e163 (99%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e164 (100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e163 (99%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eM1 (lymph nodes)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1 (1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNeoadjuvant treatment cycles\u003c/b\u003e, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.604\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21 (10%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18 (11%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19 (12%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e18 (11%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e145 (72%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e139 (85%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e134 (82%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e139 (85%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e˃=3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36 (18%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11 (7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7 (4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSurgical type\u003c/b\u003e, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.024\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMIE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e167 (83%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e112 (68%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e130 (79%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e112 (68%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35 (17%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52 (32%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e34 (21%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e52 (32%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eResection degree\u003c/b\u003e, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.057\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.170\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-R0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41 (20%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21 (13%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30 (18%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21 (13%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eR0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e161 (80%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e143 (87%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e134 (82%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e143 (87%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePost_treatment\u003c/b\u003e, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.467\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.629\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e65 (32%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47 (29%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e51 (31%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e47 (29%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e137 (68%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e117 (71%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e113 (69%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e117 (71%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003csup\u003e1\u003c/sup\u003eWilcoxon rank sum test; \u003csup\u003e2\u003c/sup\u003ePearson's Chi-squared test; \u003csup\u003e3\u003c/sup\u003eFisher's exact test. Abbreviations: nICT, neoadjuvant immunochemotherapy; nCT, neoadjuvant chemotherapy; MIE, Minimally Invasive Esophagectomy; OE, Open Esophagectomy; Post_treatment, postoperative adjuvant therapy.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eLegends: Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents the basic clinical characteristic data of the two groups (nICT vs nCT) before and after PSM.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Patient base characteristics\u003c/h2\u003e \u003cp\u003eA total of 366 non-pCR patients were included (nICT\u0026thinsp;=\u0026thinsp;202; nCT\u0026thinsp;=\u0026thinsp;164). Before matching, several characteristics differed between groups, including age, neoadjuvant cycle distribution, and surgical approach. PSM yielded 164 well-matched pairs and improved comparability between treatment groups (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Pathological findings\u003c/h2\u003e \u003cp\u003ePost-treatment pathological staging, tumor response, pathological risk features and are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. After matching, patients receiving nICT had a higher rate of MPR (19.5% vs 6.1%) and a lower proportion of ypT4 (3.7% vs 22.0%) compared with nCT, suggesting deeper tumor regression. The five-year OS rate and five-year EFS rate of the nICT group were both higher than those of the nCT group (five-year OS rate, 50.6% vs 37.2%; p\u0026thinsp;=\u0026thinsp;0.014; five-year EFS rate, 50.0% vs 31.1%; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The incidence of recurrence/metastasis during follow-up was also lower in the nICT group (40.2% vs 58.5%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePost-treatment pathological characteristics and postoperative outcomes before and after propensity score matching.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eUnmatched\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eMatched\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003enICT\u003c/b\u003e \u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;202\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003enCT\u003c/b\u003e \u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;164\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003ep-value\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003enICT\u003c/b\u003e \u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;164\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003enCT\u003c/b\u003e \u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;164\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003ep-value\u003c/b\u003e\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eKi-67\u003c/b\u003e, Median (Q1, Q3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.60 (0.50, 0.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.70 (0.50, 0.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.946\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.65 (0.50, 0.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.70 (0.50, 0.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.801\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eKi-67 Group\u003c/b\u003e, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.744\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.878\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e65 (48.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47 (51.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e54 (50.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e47 (51.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e68 (51.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45 (48.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e54 (50.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e45 (48.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHistologic Grade\u003c/b\u003e, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.117\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.113\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36 (19.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18 (11.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30 (19.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e18 (11.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e147 (78.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e135 (85.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e117 (77.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e135 (85.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (2.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (3.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4 (2.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5 (3.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePNI\u003c/b\u003e, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e76 (37.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40 (24.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.007\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e58 (35.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e40 (24.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.030\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLVI\u003c/b\u003e, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e107 (53.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e80 (48.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.425\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e88 (53.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e80 (48.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.377\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTumor response\u003c/b\u003e, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMPR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41 (20.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (6.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e32 (19.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10 (6.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e161 (79.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e154 (93.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e132 (80.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e154 (93.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eypT\u003c/b\u003e, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT0-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e79 (39.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36 (22.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e64 (39.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e36 (22.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e115 (56.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e92 (56.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e94 (57.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e92 (56.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (4.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36 (22.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6 (3.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e36 (22.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eypN\u003c/b\u003e, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.178\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.119\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e99 (49.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e78 (47.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e77 (47.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e78 (47.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e64 (31.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42 (25.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e56 (34.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e42 (25.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN2-3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39 (19.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44 (26.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e31 (18.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e44 (26.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eypM\u003c/b\u003e, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.865\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.999\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eM0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e185 (91.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e151 (92.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e151 (92.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e151 (92.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eM1(lymph nodes)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17 (8.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (7.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13 (7.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13 (7.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOS\u003c/b\u003e, Median (Q1, Q3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e859 (631, 1,213)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,075 (508, 2,129)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e860 (680, 1,224)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1,075 (508, 2,129)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.004\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEFS\u003c/b\u003e, Median (Q1, Q3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e747 (341, 1,091)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e645 (261, 2,041)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.178\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e774 (357, 1115)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e645 (261, 2,041)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.270\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFive-year OS rate, n(%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e99 (49.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61 (37.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.023\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e83 (50.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e61 (37.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.014\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFive-year EFS rate, n(%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e98 (48.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51 (31.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e82 (50.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e51 (31.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRecurrence/Metastasis\u003c/b\u003e, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e83 (41.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e96 (58.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e66 (40.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e96 (58.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003csup\u003e1\u003c/sup\u003eWilcoxon rank sum test, \u003csup\u003e2\u003c/sup\u003ePearson's Chi-squared test, \u003csup\u003e3\u003c/sup\u003eFisher's exact test. Abbreviations: nICT, neoadjuvant immunochemotherapy; nCT, neoadjuvant chemotherapy; PNI, perineural invasion; LVI, lymphovascular invasion; MPR, major pathological response; OS, overall survival; EFS, event-free survival.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eLegends: Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents the postoperative pathological characteristics and five-year survival data of the two groups before and after PSM.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Univariate and multivariate regression analyses of the five-year OS and EFS.\u003c/h2\u003e \u003cp\u003eCox regression results for five-year OS and five-year EFS are presented in \u003cb\u003eSupplementary table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026ndash;2\u003c/b\u003e. After matching, nICT was associated with a significantly lower risk of EFS events (HR 0.55, 95% CI 0.36\u0026ndash;0.84; P\u0026thinsp;=\u0026thinsp;0.005). In contrast, five-year OS did not differ significantly between treatment groups (HR 0.94, 95% CI 0.70\u0026ndash;1.27; P\u0026thinsp;=\u0026thinsp;0.707). In the matched multivariable model for EFS, OE (HR 1.87, 95% CI 1.24\u0026ndash;2.83; p\u0026thinsp;=\u0026thinsp;0.003), ypN2-3 (HR 2.82, 95% CI 1.55\u0026ndash;5.11; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and PNI (HR 1.93, 95% CI 1.24-3.00; p\u0026thinsp;=\u0026thinsp;0.003) were independently associated with worse EFS. In addition, lower Ki-67 (HR 0.65, 95% CI 0.44\u0026ndash;0.97; p\u0026thinsp;=\u0026thinsp;0.035) and postoperative adjuvant treatment (HR 0.57, 95% CI 0.36\u0026ndash;0.88; p\u0026thinsp;=\u0026thinsp;0.012) are protective factors for EFS. For OS, PNI was an adverse factor (HR 1.66, 95% CI 1.17\u0026ndash;2.36; p\u0026thinsp;=\u0026thinsp;0.004), whereas postoperative adjuvant treatment was protective (HR 0.54, 95% CI 0.39\u0026ndash;0.77; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The main influencing factors associated with 5-year OS and 5-year EFS are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e forest plots and Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e survival curves.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this real-world cohort restricted to the clinically prevalent non-pCR ESCC population, nICT was associated with a meaningful reduction in relapse risk and improvement in long-term EFS compared with nCT after rigorous adjustment, including propensity score matching and administrative censoring at 60 months. Specifically, the nICT group demonstrated higher 5-year OS and 5-year EFS rates than the nCT group, and in the matched cohort nICT was linked to a significantly lower risk of EFS events, whereas the difference in 5-year OS was not statistically significant. These research results indicate that even if a patient does not achieve pCR, nICT can still show clinically benefits.\u003c/p\u003e \u003cp\u003eBeyond regimen selection, we identified a set of post-treatment pathological aggressiveness markers that independently stratified risk. In the matched multivariable model, ypN2-3 was among the strongest predictors of adverse EFS, underscoring the dominant prognostic role of residual nodal burden after neoadjuvant therapy. This is consistent with contemporary evidence showing that post-neoadjuvant nodal status (ypN) remains a major determinant of recurrence and survival after induction therapy and surgery in esophageal cancer, and that nodal downstaging is associated with superior outcomes\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e,\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. We further identified post-treatment pathological aggressiveness markers, including PNI, LVI, high Ki-67, and margin status (non-R0 resection), as independent predictors of adverse outcomes. The prognostic impact of PNI and LVI in our cohort aligns with prior evidence that these histopathologic features indicate aggressive invasion patterns and a higher propensity for dissemination\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. A recent study incorporating PNI and LVI demonstrated their utility for recurrence risk modeling after neoadjuvant chemoradiotherapy and esophagectomy in ESCC\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. Evidence also continues to support the prognostic relevance of margin involvement definitions (e.g., circumferential resection margin) for recurrence and survival, providing a rationale for incorporating margin status into postoperative risk assessment\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. In addition, high Ki-67 expression indicates higher proliferative activity and is associated with poorer survival rates in patients with esophageal squamous cell carcinoma, which is consistent with previous study\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. These variables are readily available in routine pathology and may support practical, pathology-anchored risk stratification to guide surveillance intensity and adjuvant decision-making.\u003c/p\u003e \u003cp\u003eThe protective association of postoperative adjuvant treatment across both OS and EFS in our matched cohort suggested that postoperative systemic therapy may partially mitigate residual micrometastatic risk in high-risk non-pCR patients. This interpretation is consistent with the evolving paradigm that adjuvant systemic therapy can translate residual pathological risk into improved disease control after multimodality management, supported by the emerging overall survival analysis from CheckMate 577 and corroborated by contemporary real-world matched comparisons of adjuvant nivolumab following neoadjuvant chemoradiotherapy and resection\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e,\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. In addition, retrospective evidence further suggests that postoperative adjuvant therapy after neoadjuvant immunochemotherapy can benefit patients in pathological high-risk subgroups\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. However, different regimens of postoperative adjuvant therapy and patient compliance may affect the readability of related outcomes. Prospective trials are still needed in the non-pCR population after neoadjuvant therapy to determine the best drug and patient selection criteria.\u003c/p\u003e \u003cp\u003eThe association between open esophagectomy and worse OS/EFS should be interpreted cautiously. Randomized trials comparing minimally invasive and open approaches reported reduced pulmonary complications with minimally invasive or hybrid techniques, with broadly comparable long-term oncologic survival\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. Surgical approach may partially capture tumor extent, technical complexity, or perioperative complication burden, any of which could influence survival outcomes.\u003c/p\u003e \u003cp\u003eThe association between OE and worse OS/EFS should be interpreted cautiously, because operative approach may reflect confounding by indication (tumor extent, technical complexity), center/surgeon factors, and postoperative complication burden rather than a direct causal effect. Recent large systematic review indicate that MIE was superior to OE treatment in terms of blood loss, pulmonary complications, and length of hospital stay, but showed a balance in mortality, survival, and oncologic outcomes\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. Notably, other high-quality studies have shown improved survival with MIE compared with OE\u003csup\u003e29,30\u003c/sup\u003e. At present, MIE should be recommended as a preferred surgical procedure.\u003c/p\u003e \u003cp\u003eSeveral limitations should be mentioned: (1) As a single-center retrospective cohort study, selection bias and information bias were inevitable, and in the future a multicenter retrospective study would be conducted to further validate the current findings; (2) Different specific drugs within the neoadjuvant categories, despite sharing similar mechanisms, might have potential inter-drug differences affecting the outcomes; (3) Missingness in key variables such as Ki-67 and histologic grade was non-negligible; (4) Imaging modalities like CT have inherent false positives and negatives in assessing lymph node metastasis, potentially affecting accuracy in recurrence evaluation. Despite these limitations, the findings suggest that neoadjuvant regimen choice and post-treatment pathology provide effective prognostic information in non-pCR ESCC patients.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eAmong non-pCR ESCC patients after neoadjuvant therapy and surgery, nICT was associated with lower recurrence risk and improved five-year EFS compared with nCT, whereas a significant OS advantage was not observed. Pathological factors (PNI, high Ki-67, and residual nodal burden) and postoperative treatment were important correlates of long-term outcomes and may inform postoperative risk stratification and management.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eESCC, esophageal squamous cell carcinoma;\u003c/p\u003e\n\u003cp\u003enICT, neoadjuvant immunochemotherapy;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003enCT, neoadjuvant chemotherapy;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMIE, minimally invasive esophagectomy;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOE, open esophagectomy;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePost_treatment, postoperative adjuvant therapy;\u003c/p\u003e\n\u003cp\u003ePNI, perineural invasion;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eLVI, lymphovascular invasion;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003enon-pCR, non-pathological complete response;\u003c/p\u003e\n\u003cp\u003epCR, pathological complete response;\u003c/p\u003e\n\u003cp\u003eMPR, major pathological response;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOS, overall survival;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eEFS, event-free survival;\u003c/p\u003e\n\u003cp\u003ePSM, propensity score matching.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was approved by the Human Ethics Review Committee of Fujian Medical University Cancer Hospital (Approval No.: K2025-340-01), and relevant informed consent was waived.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData sharing is not applicable to this article as no new data were created or analyzed in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported in part by Fujian Research and Training Grants for Young and Middle-aged Leaders in Healthcare (to Chen X.), the Natural Science Foundation of Fujian Province (Grant No: 2025J011193 to Chen X.) and Special Scientific Research Project of the Fujian Provincial Finance Department Undertaken by Fuzhou Traditional Chinese Medicine Hospital. (to Deng Y.).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization and Methodology: Weibin Liu, Yujie Deng, Xiaohui Chen and Yan Lin; Investigation and Resources: Weibin Liu, Yijin Lin, Weikun Su, Jiarong Zhang, Weijin Xiao and Yi Shi; Data curation and Formal analysis: Weibin Liu, Yujie Deng, Xiaohui Chen and Xuejin Zheng; Visualization: Weibin Liu and Yan Lin; Funding acquisition: Yujie Deng and Xiaohui Chen; Supervision and Project administration: Xiaohui Chen; Manuscript writing and editing: all authors. All authors have read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declared that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBray F, 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\u0026ndash;63. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3322/caac.21834\u003c/span\u003e\u003cspan address=\"10.3322/caac.21834\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHe S, et al. Cancer profiles in China and comparisons with the USA: a comprehensive analysis in the incidence, mortality, survival, staging, and attribution to risk factors. Sci China Life Sci. 2024;67:122\u0026ndash;31. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s11427-023-2423-1\u003c/span\u003e\u003cspan address=\"10.1007/s11427-023-2423-1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEyck BM, et al. Ten-Year Outcome of Neoadjuvant Chemoradiotherapy Plus Surgery for Esophageal Cancer: The Randomized Controlled CROSS Trial. J Clin Oncol. 2021;39:1995\u0026ndash;2004. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1200/jco.20.03614\u003c/span\u003e\u003cspan address=\"10.1200/jco.20.03614\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYang H, et al. Long-term Efficacy of Neoadjuvant Chemoradiotherapy Plus Surgery for the Treatment of Locally Advanced Esophageal Squamous Cell Carcinoma: The NEOCRTEC5010 Randomized Clinical Trial. JAMA Surg. 2021;156:721\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1001/jamasurg.2021.2373\u003c/span\u003e\u003cspan address=\"10.1001/jamasurg.2021.2373\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMatsuda S, et al. Real-world Evaluation of the Efficacy of Neoadjuvant DCF Over CF in Esophageal Squamous Cell Carcinoma: Propensity Score\u0026ndash;matched Analysis From 85 Authorized Institutes for Esophageal Cancer in Japan. Ann Surg. 2023;278:e35\u0026ndash;42. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1097/sla.0000000000005533\u003c/span\u003e\u003cspan address=\"10.1097/sla.0000000000005533\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYang H, Wang F, Hallemeier CL, Lerut T, Fu J. Oesophageal cancer. Lancet. 2024;404:1991\u0026ndash;2005. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/s0140-6736(24)02226-8\u003c/span\u003e\u003cspan address=\"10.1016/s0140-6736(24)02226-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu J, 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. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1136/jitc-2021-004291\u003c/span\u003e\u003cspan address=\"10.1136/jitc-2021-004291\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eQin J, et al. Neoadjuvant chemotherapy with or without camrelizumab in resectable esophageal squamous cell carcinoma: the randomized phase 3 ESCORT-NEO/NCCES01 trial. Nat Med. 2024;30:2549\u0026ndash;57. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41591-024-03064-w\u003c/span\u003e\u003cspan address=\"10.1038/s41591-024-03064-w\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZheng Y, et al. Perioperative toripalimab plus neoadjuvant chemotherapy might improve outcomes in resectable esophageal cancer: an interim analysis of a phase III randomized clinical trial. Cancer Commun (Lond). 2024;44:1214\u0026ndash;27. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/cac2.12604\u003c/span\u003e\u003cspan address=\"10.1002/cac2.12604\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShang X, et al. A prospective study of neoadjuvant pembrolizumab plus chemotherapy for resectable esophageal squamous cell carcinoma: The Keystone-001 trial. Cancer Cell. 2024;42:1747\u0026ndash;e17631747. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.ccell.2024.09.008\u003c/span\u003e\u003cspan address=\"10.1016/j.ccell.2024.09.008\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGaber CE, et al. Pathologic complete response in patients with esophageal cancer receiving neoadjuvant chemotherapy or chemoradiation: A systematic review and meta-analysis. Cancer Med. 2024;13:e7076. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/cam4.7076\u003c/span\u003e\u003cspan address=\"10.1002/cam4.7076\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLin L, et al. A pathologic classification approach in esophageal squamous cell carcinoma following neoadjuvant immunochemotherapy: Distinguishing postoperative outcomes and exploring the potential benefit of adjuvant therapy. J Thorac Cardiovasc Surg. 2025;170:1284\u0026ndash;e12941212. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jtcvs.2025.06.012\u003c/span\u003e\u003cspan address=\"10.1016/j.jtcvs.2025.06.012\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFeng J, Wang L, Yang X, Chen Q. Adjuvant immunotherapy after neoadjuvant immunochemotherapy and esophagectomy for esophageal squamous cell carcinoma: a real-world study. Front Immunol. 2024;15:1456193. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3389/fimmu.2024.1456193\u003c/span\u003e\u003cspan address=\"10.3389/fimmu.2024.1456193\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHong Z, et al. Major pathologic response as a prognostic surrogate in esophageal squamous cell carcinoma patients receiving neoadjuvant chemotherapy/chemoimmunotherapy: A multi-center cohort study. Eur J Surg Oncol. 2025;51:109500. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.ejso.2024.109500\u003c/span\u003e\u003cspan address=\"10.1016/j.ejso.2024.109500\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSugiyama K, et al. Is pathological response an adequate surrogate marker for survival in neoadjuvant therapy with immune checkpoint inhibitors? ESMO Open. 2025;10:104122. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.esmoop.2024.104122\u003c/span\u003e\u003cspan address=\"10.1016/j.esmoop.2024.104122\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBecker K, et al. Histomorphology and grading of regression in gastric carcinoma treated with neoadjuvant chemotherapy. Cancer. 2003;98:1521\u0026ndash;30. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/cncr.11660\u003c/span\u003e\u003cspan address=\"10.1002/cncr.11660\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRice TW, Ishwaran H, Ferguson MK, Blackstone EH, Goldstraw P. Cancer of the Esophagus and Esophagogastric Junction: An Eighth Edition Staging Primer. J Thorac Oncol. 2017;12:36\u0026ndash;42. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jtho.2016.10.016\u003c/span\u003e\u003cspan address=\"10.1016/j.jtho.2016.10.016\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLeng X, et al. Prognostic Impact of Postoperative Lymph Node Metastases After Neoadjuvant Chemoradiotherapy for Locally Advanced Squamous Cell Carcinoma of Esophagus: From the Results of NEOCRTEC5010, a Randomized Multicenter Study. Ann Surg. 2021;274:e1022\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1097/sla.0000000000003727\u003c/span\u003e\u003cspan address=\"10.1097/sla.0000000000003727\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHuang Y, et al. Impact of lymph node dissection on survival after neoadjuvant immunochemotherapy for esophageal squamous cell cancer: a double-center real-world retrospective study. Cancer Immunol Immunother. 2025;74:303. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s00262-025-04168-z\u003c/span\u003e\u003cspan address=\"10.1007/s00262-025-04168-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXiong J, et al. The impact of perineural invasion on prognosis in esophageal cancer patients after surgery: a systematic review and meta-analysis. Front Oncol. 2025;15:1629335. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3389/fonc.2025.1629335\u003c/span\u003e\u003cspan address=\"10.3389/fonc.2025.1629335\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhou J, et al. Lymphovascular and Perineural Invasion After Neoadjuvant Therapy in Esophageal Squamous Carcinoma. Ann Thorac Surg. 2023;115:1386\u0026ndash;94. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.athoracsur.2022.07.052\u003c/span\u003e\u003cspan address=\"10.1016/j.athoracsur.2022.07.052\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eElshaer AM, et al. The prognostic value of circumferential resection margin (CRM) definition and location in esophageal cancer: A 12-year cohort study. Eur J Surg Oncol. 2025;51:110138. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.ejso.2025.110138\u003c/span\u003e\u003cspan address=\"10.1016/j.ejso.2025.110138\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang Y, Dai M, Chen X. Prognostic and clinicopathological value of Ki-67 in patients with oesophageal squamous cell carcinoma: a systematic review and meta-analysis. BMJ Open. 2024;14:e083637. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1136/bmjopen-2023-083637\u003c/span\u003e\u003cspan address=\"10.1136/bmjopen-2023-083637\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZheng J, et al. Exploratory analyses of the associations between Ki-67 expression, lymph node metastasis, and prognosis in patients with esophageal squamous cell cancer. PeerJ. 2025;13:e19062. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.7717/peerj.19062\u003c/span\u003e\u003cspan address=\"10.7717/peerj.19062\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVerhoeven RHA, et al. Adjuvant nivolumab after chemoradiotherapy and resection for patients with esophageal cancer: A real-world matched comparison of overall survival. Int J Cancer. 2025. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/ijc.70168\u003c/span\u003e\u003cspan address=\"10.1002/ijc.70168\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKelly RJ, Ajani JA, Kuzdzal J. Adjuvant nivolumab in resected esophageal or gastroesophageal junction cancer. N Engl J Med. 2021;384:1191\u0026ndash;203. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1056/NEJMoa2032125\u003c/span\u003e\u003cspan address=\"10.1056/NEJMoa2032125\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMariette C, Markar SR, Dabakuyo-Yonli TS. Hybrid minimally invasive esophagectomy for esophageal cancer. N Engl J Med. 2019;380:152\u0026ndash;62. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1056/NEJMoa1805101\u003c/span\u003e\u003cspan address=\"10.1056/NEJMoa1805101\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDunne N, Davey MG, Donlon NE. Comparing outcomes following open, hybrid, minimally invasive, and robotic-assisted esophagectomy: A systematic review. Eur J Surg Oncol. 2026;52:110531. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.ejso.2025.110531\u003c/span\u003e\u003cspan address=\"10.1016/j.ejso.2025.110531\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHenckens SPG, et al. Recurrence and Survival After Minimally Invasive and Open Esophagectomy for Esophageal Cancer: A Post Hoc Analysis of the Ensure Study. Ann Surg. 2024;280:267\u0026ndash;73. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1097/sla.0000000000006280\u003c/span\u003e\u003cspan address=\"10.1097/sla.0000000000006280\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIgaue S, et al. Long-term Survival in Esophageal Cancer: Comparison of Minimally Invasive and Open Esophagectomy. Ann Thorac Surg. 2025;119:805\u0026ndash;14. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.athoracsur.2024.09.004\u003c/span\u003e\u003cspan address=\"10.1016/j.athoracsur.2024.09.004\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"esophageal squamous cell carcinoma, non-pathological complete response, neoadjuvant immunochemotherapy, perineural invasion, Ki-67","lastPublishedDoi":"10.21203/rs.3.rs-8484860/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8484860/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eNon-pathological complete response (non-pCR) is common in esophageal squamous cell carcinoma (ESCC) patients after neoadjuvant therapy, yet evidence guiding long-term outcome and postoperative risk stratification in the immunotherapy era remains limited.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe retrospectively enrolled consecutive ESCC patients treated with neoadjuvant immunochemotherapy (nICT) or chemotherapy alone (nCT) followed by esophagectomy and restricted analyses to non-pCR cases. Primary endpoints were five-year overall survival (OS) and event-free survival (EFS). Propensity score matching analysis and 60-month censoring were used to reduce differences between groups. Cox proportional hazards model was used for analysis.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eAmong 366 non-pCR patients, 164 matched pairs were generated. After matching, nICT demonstrated a higher major pathological response (MPR) rate (19.5% vs 6.1%), a lower ypT4 proportion (3.7% vs 22.0%) and fewer recurrence/metastasis rate (40.2% vs 58.5%) (all p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Five-year OS rate (50.6% vs 37.2%, p\u0026thinsp;=\u0026thinsp;0.014) and EFS rate (50.0% vs 31.1%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) were higher in nICT group. In matched multivariable Cox model, nICT was independently associated with improved EFS (P\u0026thinsp;=\u0026thinsp;0.005) but not OS (P\u0026thinsp;=\u0026thinsp;0.707). Adverse EFS was independently associated with open esophagectomy (OE) (p\u0026thinsp;=\u0026thinsp;0.003), ypN2-3 ( p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and perineural invasion (PNI) (p\u0026thinsp;=\u0026thinsp;0.003), while lower Ki-67 (p\u0026thinsp;=\u0026thinsp;0.035) and postoperative adjuvant treatment (p\u0026thinsp;=\u0026thinsp;0.012) were associated with improved EFS. For OS, PNI was an adverse factor (p\u0026thinsp;=\u0026thinsp;0.004), whereas postoperative adjuvant treatment was a protective one (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eAmong non-pCR ESCC patients after neoadjuvant therapy and surgery, nICT was associated with lower recurrence risk and improved five-year EFS compared with nCT, whereas a significant OS advantage was not observed. Pathological factors (PNI, high Ki-67, and residual nodal burden) and postoperative treatment were important correlates of long-term outcomes and may inform postoperative risk stratification and management.\u003c/p\u003e","manuscriptTitle":"Five-year Survival Analyses on Non-Pathological Complete Response Esophageal Squamous Cell Carcinoma Patients after Neoadjuvant Regimens plus Surgery: a Propensity Score Matching, Real-World Cohort Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-29 00:47:31","doi":"10.21203/rs.3.rs-8484860/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-01-28T14:39:39+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"65224539258446622483117262425969641543","date":"2026-01-25T13:22:21+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-01-23T15:30:23+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-01-02T15:46:59+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-02T00:56:24+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-02T00:55:39+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Cancer","date":"2025-12-31T01:09:59+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3ea1c417-e4f2-4993-a7c6-a34e5327ac60","owner":[],"postedDate":"January 29th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-01-29T00:47:32+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-29 00:47:31","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8484860","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8484860","identity":"rs-8484860","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}