Comparative Analysis of Adjuvant Radiotherapy, Lymph Node Dissection, and Metastatic Positive Rate on Prognosis in T3-4N+ Gastroesophageal Junction Cancer: A Study Based on SEER Database and External Validation in China

Comparative Analysis of Adjuvant Radiotherapy, Lymph Node Dissection, and Metastatic Positive Rate on Prognosis in T3-4N+ Gastroesophageal Junction Cancer: A Study Based on SEER Database and External Validation in China | 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 Comparative Analysis of Adjuvant Radiotherapy, Lymph Node Dissection, and Metastatic Positive Rate on Prognosis in T3-4N+ Gastroesophageal Junction Cancer: A Study Based on SEER Database and External Validation in China chenrui tian, Haodi Yu, Qingyu Zhang, Shundong Cang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4476751/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Adjuvant radiotherapy (ART) is recognized as a pivotal therapeutic modality capable of augmenting the overall survival(OS) outcomes in patients afflicted with gastroesophageal junction cancer (GEJ) at the T3-4N+ stage. However, there remains a need for comprehensive investigations into the optimal timing of radiotherapy administration relative to surgery. Furthermore, the number of regional nodes examined(RNE) and the metastasis lymph node ratio (MLR) exert discernible impacts on the prognosis of such patients. Our study endeavors to delve deeper into elucidating the interplay between ART and surgical interventions, while assessing the prognostic significance of RNE and MLR, with the ultimate goal of developing a nomogram to accurately predict the 5-year survival rate for T3-4N+ gastric cancer patients. Patients and Methods 7,709 patients with GEJ cancer were involved from the Surveillance, Epidemiology, and End Results (SEER) database, spanning 2010 to 2019. 335 gastric cancer patients were involved from the Henan Provincial People's Hospital (HPPH), spanning 2015 to 2019. OS was analyzed using the log-rank test and multivariate analysis. The Cox regression models were valuable in predicting outcomes for these cancers. Receiver operating characteristic curve (ROC) and Decision Curve Analysis (DCA) were used to validate predictive model. Restricted cubic splines (RCS) were employed to analyze the potential nonlinear relationship between RNE and prognosis. Additionally, the relationship between MLR and prognosis was examined using the same method. RESULTS We found that esophageal adenocarcinoma exhibited a superior response to preoperative radiotherapy(p<0.001). However, the timing of radiotherapy for gastric adenocarcinoma post-operation did not significantly affect outcomes (p=0.6). Age, tumor grade, lymph node stage, RNE, type of surgery, and timing of radiotherapyrelative to surgery emerged as crucial prognostic factors for T3-4N+ gastric cancers. Additionally, the analysis showed no significant nonlinear relationship between RNE (with a threshold of 15) and patient survival in esophageal and gastric adenocarcinomas (p>0.05), suggesting consistent findings across varying levels of lymph node removal. CONCLUSIONS Esophageal adenocarcinoma demonstrates a greater therapeutic response to preoperative radiotherapy. Our nomogram provides an effective tool for predicting the 5-year prognosis of T3-4N+ gastric adenocarcinoma. Moreover, our analysis suggests that the removal of 15 lymph nodes may not represent the optimal strategy for lymph node dissection. Additionally, MLR emerges as a significant prognostic factor influencing outcomes in patients with both esophageal and gastric cancer. Gastroesophageal Junction Cancer Adjuvant radiotherapy Overall survival Lymph Node Excision Metastatic lymph node ratio Surgery Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Introduction The management of GEJ cancers presents a significant clinical challenge, leading to active debate over the optimal treatment approach. Recent research has focused on clarifying the role of ART in conjunction with chemotherapy. The CROSS trial( 1 ) provided foundational evidence supporting neoadjuvant chemoradiotherapy(NCRT) while the FLOT4-AIO trial( 2 ) highlighted the benefits of neoadjuvant chemotherapy(NCT), contributing to the current body of literature informing clinical practice. Several studies have compared survival outcomes in patients treated with perioperative CT(POC) alone versus those receiving radiation before surgery(RST) indicating that adding radiation can improve survival outcomes for patients with gastric and GEJ adenocarcinomas( 3 – 6 ). The advantages of RST could downstage T2-3 gastric cancer, increase the likelihood of a complete R0 resection, and offer better tolerability( 7 ). TOPGEAR ( 8 ) examined the incremental benefits of adding RST to chemotherapy. While radiotherapy has been associated with better local disease management, as noted by Reynolds et al.( 9 ), it also increases the higher risk of toxicity. An Randomized Controlled Trial(RCT) demonstrated that the addition of RST to POC appears to be associated with an increased risk of death in patients with resectable stage IB to stage IIIC gastric and GEJ cancers( 10 ). Besides, in the Asian population, the ARTIST trial which focused on Asian patients with post-D2 lymph node dissection, did not show positive results in stage IA or IB gastric cancers, but subgroup analysis suggested that ART could potentially benefit a subset of patients with nodal involvement or intestinal histology type( 11 ). Additionally, the decision to add radiotherapy depends on tumor staging, patient health status, RNE( 12 ), and potential response to treatment. Currently, the evidence remains unclear about the advantages of using NRT or ART for those with resectable, locally advanced tumors at the GEJ( 13 ). Therefore, the safety and feasibility of RST in GEJ cancers need more research. In this study, we aimed to compare the survival differences among ART, surgical methods, RNE, and MLR in patients with T3-4N + GEJ, and to establish a prognostic model for gastric cancer. Methods Database and Participants Patients diagnosed with GEJ cancer were extracted from 18 registries of the Surveillance, Epidemiology, and End Results database (SEER database 2000–2019) and Henan Provincial People's Hospital (HPPH 2015–2019) clinical message. In the SEER database, the primary cancer sites were coded according to the "Primary site label". We included tumors from five regions at the GEJ: C15.5 Lower third of the esophagus, C15.9 Esophagus NOS, C16.0 Cardia, C16.1 Fundus of the stomach, C16.9 Stomach NOS. For each patient, the following information was collected: Age, Sex, Race recode, Grade, RX Summ–Surg/Rad Seq, Chemotherapy recode (yes, no/unknown), Radiation recode, RX Summ–Systemic/Sur Seq, AJCC 7th TNM stage, SEER other cause of death classification, SEER cause-specific death classification, Survival months, Vital.status.recode.study.cutoff.used, Histology.recode-broad.groupings, COD to site rec KM, COD to site recode, Regional.nodes.examined.(1988+), CS.tumor.size. (2004–2015), Regional nodes examined (1988+), Regional nodes positive (1988+), and positive rate of lymph node metastasis. In the HPPH set, the following information included: Age, Sex, Grade, Primary site, Chemotherapy, Radiation, Surgery, AJCC 7th TNM stage, Survival months, Status, the number of lymph node dissections, and Histology. Patients from the SEER database received chemotherapy, but it is not known whether it was administered before or after surgery. Statistical analysis All statistical analyses in this study were used by R software version (4.3.1) ( http://www.rproject.org/ ). We utilized the "survminer" and "survival" packages to create Kaplan-Meier (KM) survival curves. A multivariable Cox hazard model was constructed, including variables that had a two-sided p-value of less than 0.05. To identify significant variables, we applied forward and backward selection methods. Using the "rms" package, we developed a nomogram for gastric cancer to predict 1-year, 3-year, and 5-year survival probabilities. We expressed the model's results in terms of hazard ratios (HRs) with 95% confidence intervals (CIs). To assess the accuracy of the nomogram, we plotted calibration curves, using a bootstrap method with 1000 resamples. We evaluated the model's discriminative ability by calculating the AUC. DCA was also used to appraise the clinical usefulness of nomogram. The packages "tidycmprsk," "gtsummary," "ggsurvfit," and "ggprism" were employed to construct cumulative incidence curves for competing risks, which helped us analyze the impact of radiotherapy and surgery, as well as RNE, on the overall mortality risk associated with different surgical methods. Additionally, we utilized RCS curves to investigate any nonlinear relationship between RNE and the mortality risk. Results Baseline Characteristics of the Study Population A total of 7,709 patients with GEJ cancers were identified from the SEER database. Among them 3,176 patients (1,380 with cardia cancer, 1,522 with esophagus cancer, and 274 with gastric cancer) were selected for further analysis. Additionally, we included 312 patients with gastric cancer from HPPH. All patients underwent chemotherapy, although it remains unclear whether these chemotherapy were conducted preoperatively or postoperatively. The flowchart illustrating the selection process for the study population is presented in Fig. 1 . Clinical and demographic characteristics of GEJ cancer patients from the SEER database are summarized in Table 1 . Table 1 Baseline Characteristics of the Study Population Cardia Esophagus Stomach Overall (N = 1380) (N = 1522) (N = 274) (N = 3176) Age =60 900 (65.2%) 1008 (66.2%) 183 (66.8%) 2091 (65.8%) 50–60 329 (23.8%) 376 (24.7%) 59 (21.5%) 764 (24.1%) Sex Female 235 (17.0%) 185 (12.2%) 106 (38.7%) 526 (16.6%) Male 1145 (83.0%) 1337 (87.8%) 168 (61.3%) 2650 (83.4%) Race Black 64 (4.6%) 39 (2.6%) 39 (14.2%) 142 (4.5%) Other 107 (7.8%) 63 (4.1%) 58 (21.2%) 228 (7.2%) White 1209 (87.6%) 1420 (93.3%) 177 (64.6%) 2806 (88.4%) Grade G1 71 (5.1%) 73 (4.8%) 11 (4.0%) 155 (4.9%) G2 542 (39.3%) 680 (44.7%) 77 (28.1%) 1299 (40.9%) G3 749 (54.3%) 756 (49.7%) 179 (65.3%) 1684 (53.0%) G4 18 (1.3%) 13 (0.9%) 7 (2.6%) 38 (1.2%) Histology AEC 1366 (99.0%) 1358 (89.2%) 272 (99.3%) 2996 (94.3%) SECC 14 (1.0%) 164 (10.8%) 2 (0.7%) 180 (5.7%) Tstage T1 126 (9.1%) 165 (10.8%) 17 (6.2%) 308 (9.7%) T2 196 (14.2%) 265 (17.4%) 33 (12.0%) 494 (15.6%) T3 965 (69.9%) 1024 (67.3%) 127 (46.4%) 2116 (66.6%) T4 93 (6.7%) 68 (4.5%) 97 (35.4%) 258 (8.1%) Nstage N0 364 (26.4%) 458 (30.1%) 67 (24.5%) 889 (28.0%) N1 590 (42.8%) 703 (46.2%) 71 (25.9%) 1364 (42.9%) N2 278 (20.1%) 275 (18.1%) 56 (20.4%) 609 (19.2%) N3 148 (10.7%) 86 (5.7%) 80 (29.2%) 314 (9.9%) RNE < 15 596 (43.2%) 782 (51.4%) 93 (33.9%) 1471 (46.3%) ≥ 15 784 (56.8%) 740 (48.6%) 181 (66.1%) 1705 (53.7%) Rad.saq No radiation and/or cancer-directed surgery 333 (24.1%) 181 (11.9%) 141 (51.5%) 655 (20.6%) Radiation after surgery 212 (15.4%) 113 (7.4%) 127 (46.4%) 452 (14.2%) Radiation before and after surgery 34 (2.5%) 51 (3.4%) 0 (0%) 85 (2.7%) Radiation prior to surgery 794 (57.5%) 1162 (76.3%) 6 (2.2%) 1962 (61.8%) Surgery both before and after radiation 7 (0.5%) 15 (1.0%) 0 (0%) 22 (0.7%) Tumor.size ≤ 1mm 3 (0.2%) 2 (0.1%) 0 (0%) 5 (0.2%) ≥ 989mm 15 (1.1%) 10 (0.7%) 1 (0.4%) 26 (0.8%) 2-988mm 1362 (98.7%) 1510 (99.2%) 273 (99.6%) 3145 (99.0%) RNE: number of lymph nodes removed; Rad.saq: sequence of radiotherapy and surgery 2. Survival Outcome of GEJ Cancers The KM survival analysis focused on assessing the impact of the number of resected lymph nodes, the timing of radiotherapy, and the type of surgical procedure on survival outcomes in adenocarcinomas of the lower esophagus, GEJ and upper part of the stomach. Our findings revealed that in T3-4N + gastric cancers, patients who underwent RST did not exhibit a significant survival advantage compared to those who did not (29 months vs. 26 months; p = 0.6). Similarly, the choice of surgical approach, ranging from limited excision to full resection, did not result in significantly different survival rates (32 months vs. 22 months; p = 0.092). However, patients who had more than 15 lymph nodes removed experienced notebly better survival than those with fewer than 15 lymph nodes removed (31 months vs. 18.5 months; p = 0.003). In esophageal adenocarcinoma cases, RST significantly improved median overall survival(mOS) than those who received radiation after surgery(SRT) (34 months vs. 18 months; p < 0.001). Additionally, cardia adenocarcinoma patients with more extensive lymph node removal enjoyed longer mOS(33 months vs. 27 months; p = 0.006) (Fig. 2 ). 3. Prognostic factors for gastric cancer patients and nomogram validation In patients with esophageal adenocarcinoma, stages N2 and N3 are significantly associated with a poor prognosis. Similarly, for individuals with cardia adenocarcinoma, age exceeding 60 years and the presence of N2 or N3 cancer stages are correlate with an adverse prognosis. Conversely, the dissection of 15 or more lymph nodes is associated with a more faborable prognosis. An analysis of 175 patients with advanced (T3-4N+) gastric cancer was conducted to identify prognostic factors affecting OS. Using forward and backward selection methods, significant variables were determined. For patients with gastric cancer, advanced age (> 60 years) or the manifestation of N2 or N3 stage disease portend a poorer prognosis. However, the prognosis is more favorable for patients with 15 or more local lymph nodes removed. (Table 2 a, b, c). Based on the identified prognostic factors, a nomogram was developed to forecast the 1-year, 3-year, and 5-year survival probabilities (Fig. 3 ). The calibration curves showed high consistencies between the predicted and actual survival rates both in the training and validation cohorts(Fig. 4 ). Subsequent ROC analysis of the nomogram, assessing the likelihood of 1-year, 3-year, and 5-year OS, yielded AUC values of 0.766, 0.785, and 0.766 for the training set, and 0.752, 0.827, and 0.859 for the validation set, respectively. These results underscored a robust agreement between the predicted OS and actual outcomes in both the training and validation cohorts (Fig. 5 ). Additionally, DCA curves further corroborated the nomogram's efficacy in clinical practice, affirming its favorable performance (Fig. 6 ). Table 2 a Multivariable prognostic factors for gastric cancer patients Gastric HR CI95 P-value Age =60 2.48 1.29–4.77 0.0064 50–60 1.38 0.66–2.87 0.3962 Sex Female Reference Male 1.04 0.68–1.59 0.8621 Race Black Reference Other 0.87 0.46–1.64 0.6701 White 0.96 0.56–1.62 0.8686 Grade G1 Reference G2 0.93 0.21–4.12 0.9201 G3 2.02 0.48–8.6 0.3397 G4 1.72 0.29–10.11 0.5465 Nstage N1 Reference N2 1.92 1.12–3.29 0.017 N3 3.78 2.22–6.43 0 Rad.saq No radiation Reference Radiation after surgery 0.67 0.44–1.02 0.0623 Radiation prior to surgery 0.48 0.13–1.75 0.2691 Surgery Gastrectomy1 Reference Gastrectomy2 1.43 0.97–2.09 0.0702 Tumor.size ≤ 1mm Reference 2-988mm 1.72 0.23–13.11 0.6006 RNE < 15 Reference ≥ 15 0.4 0.26–0.62 0 RNE: number of lymph nodes removed; Rad.saq: sequence of radiotherapy and surgery Table 2 b Multivariable prognostic factors for esophagus cancer patients Esophagus HR CI95 P-value Age =60 1.31 0.94–1.81 0.1112 50–60 1.23 0.87–1.75 0.2398 Sex Female Reference Male 1.24 0.92–1.69 0.1628 Race Black Reference Other 0.63 0.27–1.47 0.286 White 0.87 0.45–1.7 0.6877 Grade G1 Reference G2 0.97 0.6–1.59 0.9081 G3 1.11 0.68–1.79 0.6802 G4 1.67 0.68–4.14 0.2659 Nstage N1 Reference N2 1.24 1.02–1.52 0.0335 N3 1.91 1.41–2.59 0 Rad.saq No radiation Reference Radiation after surgery 1.44 0.94–2.21 0.0947 Radiation before and after surgery 1.17 0.68–2.02 0.5667 Radiation prior to surgery 1.06 0.78–1.44 0.7055 Surgery both before and after radiation 2.2 0.87–5.58 0.0951 Surgery Esophagectomy1 Reference Esophagectomy2 1.16 0.94–1.44 0.176 Tumor.size ≤ 1mm Reference ≥ 989mm 0.26 0.02–4.24 0.3469 2-988mm 0.41 0.06–2.94 0.3745 RNE < 15 Reference ≥ 15 0.83 0.69–1 0.0552 RNE: number of lymph nodes removed; Rad.saq: sequence of radiotherapy and surgery 4. Cumulative Incidences of GEJ Cancers and RCS. We performed an analysis to assess the cumulative risk of mortality about lymph node dissection count, surgical approaches, and radiotherapy sequencing across gastric, cardia, and esophageal adenocarcinomas. For esophageal adenocarcinoma, RST significantly reduced the cumulative mortality risk compared to SRT (p < 0.001). However, in gastric cancer, there was no significant difference in mortality risk between patients receiving SRT and those who did not undergo any form of radiation therapy (p = 0.7) (Fig. 7 ). Additionally, we assessed the link between the quantity of lymph node dissections, MLR, and the risk of death using RCS curves. The analysis revealed a decrease in mortality risk with an increased RNE. Nonetheless, an MLR of over 10% raised the mortality risk for both gastric and esophageal adenocarcinoma patients (Fig. 8 ). In addition, our analysis of the specific number of lymph nodes resected showed that the benefit for gastric cancer patients who had more than 36–37 lymph nodes resected may be marginal. Similarly, the benefit for patients with esophageal adenocarcinoma who had more than 28–29 lymph nodes resected may also be marginal(Fig. 9 ). Discussion GEJ cancers rank among the most prevalent gastrointestinal malignancies worldwide.( 14 ). Clinicians have long been focused on optimizing treatment approaches for these tumors. While various strategies, such as chemotherapy alone or in combination with radiotherapy, have been employed, it remains unclear which approach yields superior patient outcomes. A meta-analysis comparing neoadjuvant chemotherapy (NCT) and radiotherapy demonstrated a significant benefit of concurrent chemoradiotherapy (CRT) (p < 0.0001) and chemotherapy alone (p = 0.005) over surgical intervention alone. However, the superiority of CRT over chemotherapy alone was marginal and not statistically significant (p = 0.07). Previous evidence supported both NCRT and NCT preceding surgery( 15 ). While several studies have focused on the benefits of adjuvant CRT in addition to surgical intervention, there is a notable lack of research that specifically investigates the prognostic implications of RNE and MLR respectively in advanced tumors at the GEJ( 16 , 17 ). Therefore, our research contributes to the current understanding of adjuvant therapies by examining the impact of lymph node dissection on the outcomes of advanced GEJ cancers. For patients with T3-4N + gastric cancer, the performance of postoperative radiation therapy did not show a difference in prognosis (P = 0.57). It was noteworthy that according to the data collected from the SEER database, only 3 cases received radical surgical treatment (RST), while 87 received standard radiation therapy (SRT). Therefore, we were unable to conduct a more precise analysis of RST and SRT. In our hospital's patient data, postoperative ART was not administered to patients with T3-4N + gastric cancer. Notably, RST exhibited a pronounced benefit in esophageal adenocarcinoma, in contrast to SRT (p < 0.001), while the trend was not observed in cardia cancer (p = 0.07). The current consensus and guidelines tend to favor the RST or chemotherapy for advanced stages. For example, the NCCN guidelines point out that for T3-4N + tumors at the bottom of the stomach in the GEJ area, where surgery fails to meet the D2 standard or R1 resection( 6 , 18 , 19 ), SRT is more suitable for patients with high-risk factors. Consideration should be given to incorporating additional radiation therapy based on chemotherapy. Previous studies have indicated potential benefits of postoperative radiation therapy, particularly in cases of suboptimal surgical resection or absence of D2 lymph node dissection.( 14 , 15 , 18 ). However, for patients who have undergone D2 resection, postoperative radiotherapy may not be necessary, especially considering treatment toxicity.( 20 ) Currently, the majority of research conclusions on gastric cancer are more inclined toward RST rather than SRT( 21 , 22 ). RST has been shown to reduce the size of locally advanced esophageal tumors and confer a survival benefit( 23 ), although it also affects the physiological status of adjacent normal lymph node tissue( 24 ). Giugliano et al. pointed out that RNE in specimens from patients who had undergone previous radiotherapy was relatively diminished. This phenomenon may be attributed to local fibrosis and structural loss of lymph nodes induced by radiotherapy, leading to inadequate lymph node excision. It was found that the RNE(< 15 and ≥ 15) was not significantly associated with prognosis(P = 0.87)( 25 ) while Hui-Ju Ho provided a different conclusion( 26 ). Conversely, our findings, as revealed by RCS curves, suggest that the removal of 15 lymph nodes might not serve as the optimal prognostic indicator for both esophageal and gastric cancer. Instead, our results indicate that a higher number of lymph nodes removed (RNE) correlates with a reduction in mortality. Furthermore, analysis of the change in slope of the curve revealed that the benefits to patients may not significantly increase beyond an RNE exceeding 36–37 during gastric cancer surgery. Similarly, in esophageal adenocarcinoma, patients may not derive significant additional benefits after the removal of 28–29 lymph nodes. Additionally, further analysis of the MLR showed a positive rate greater than 10% increases the risk of mortality( 27 , 28 ). MLR appears to offer a more accurate and objective assessment of prognosis in T3N3 gastric cancer compared to traditional pN staging( 29 – 32 ) and it might be a significant independent risk factor for OS and recurrence free survival( 33 , 34 ). Moreover, radiotherapy was associated with prolonged mOS in patients with MLR ranging from 10–25% (P = 0.002) and those with MLR > 25% (P < 0.0001). However, no significant difference was observed between concurrent CRT and chemotherapy alone among patients with 0% MLR (P = 0.16) and those with MLR ranging from 1–9% (P = 0.088)( 12 ). Nonetheless, current research on the impact of MLR staging on the prognosis of gastric cancer is inconsistent, with most studies indicating that a higher ratio correlates with a worse prognosis( 35 – 37 ). This variability may be due to the use of different cutoff values, potentially introducing bias in the measured survival prognosis. Consequently, further research is needed to elucidate the relationship between MLR and radiotherapy. Conclusions The study revealed that SRT might not necessary for gastric cancer patients, whereas RST was found to be advantageous for those with esophageal adenocarcinoma. In cases of cardia adenocarcinoma, the addition of radiation, either before or after surgery, did not alter the prognosis. Notably, the removal of more than 15 lymph nodes was associated with superior prognosis compared to cases with fewer than 15 nodes removed, and this benefit increased with the removal of even more nodes. Additionally, a higher MLR was correlated with a better prognosis. The nomogram for T3-4N + gastric cancer provides a valuable predictive tool for estimating 5-year survival probability. Abbreviations ART adjuvant radiotherapy RST radiation before surgery SRT radiation after surgery RCS restricted cubic spline RNE regional.nodes.examined NCRT neoadjuvant chemoradiotherapy ROC receiver operating characteristic DCA decision curve analysis POC perioperative chemotherapy MLR metastatic lymph node ratio GEJ gastroesophageal junction cancer SEER Surveillance, Epidemiology, and End Results database HPPH Henan Provincial People’s Hospital OS overall survival mOS median overall survival CRT chemoradiotherapy NCT neoadjuvant chemotherapy Declarations Competing interests The authors report no conflict of interest. Author’s contributions T.C.R and Z.Q.Y designed the study. T.C.R and Y.H.D. collected the data. T.C.R and Y.H.D. analyzed the data. T.C.R and Z.Q.Y organized and revised the manuscript. C.S.D supervised the manuscript. All authors read and approved the final manuscript. Availability of data and materials The dataset was abstracted from the SEER database (https://seer.cancer.gov/). The name of the dataset we abstracted was "Incidence-SEER Research Data Plus,17 Registries, Nov 2021 Sub (2000-2019)". The data from HPPH used and analyzed during the current study are available from the corresponding author upon reasonable request. Funding This work was supported by grants from the Key Research and Development Project of Henan Province (231111311900) and Henan scientific and technological project (242102310029). Ethics approval and consent to participate The patients in the Henan Provincial People's Hospital and SEER database could not be identified, so the analyses and reporting of the data in our study were exempt from review by the Ethics Board of Henan Provincial People's Hospital Affiliated to Zhengzhou University. The requirement for written informed consent to participate was also waived. Consent for publication Not applicable. References Shapiro J, van Lanschot JJB, Hulshof M, van Hagen P, van Berge Henegouwen MI, Wijnhoven BPL, et al. Neoadjuvant chemoradiotherapy plus surgery versus surgery alone for oesophageal or junctional cancer (CROSS): long-term results of a randomised controlled trial. Lancet Oncol. 2015;16(9):1090–8. Al-Batran SE, Homann N, Pauligk C, Goetze TO, Meiler J, Kasper S, et al. Perioperative chemotherapy with fluorouracil plus leucovorin, oxaliplatin, and docetaxel versus fluorouracil or capecitabine plus cisplatin and epirubicin for locally advanced, resectable gastric or gastro-oesophageal junction adenocarcinoma (FLOT4): a randomised, phase 2/3 trial. Lancet. 2019;393(10184):1948–57. Miccio JA, Oladeru OT, Yang J, Xue Y, Choi M, Zhang Y, et al. Neoadjuvant vs. adjuvant treatment of Siewert type II gastroesophageal junction cancer: an analysis of data from the surveillance, epidemiology, and end results (SEER) registry. J Gastrointest Oncol. 2016;7(3):403–10. Stahl M, Walz MK, Riera-Knorrenschild J, Stuschke M, Sandermann A, Bitzer M, et al. Preoperative chemotherapy versus chemoradiotherapy in locally advanced adenocarcinomas of the oesophagogastric junction (POET): Long-term results of a controlled randomised trial. Eur J Cancer. 2017;81:183–90. Greally M, Agarwal R, Ilson DH. Optimal management of gastroesophageal junction cancer. Cancer. 2019;125(12):1990–2001. Cellini F, Morganti AG, Di Matteo FM, Mattiucci GC, Valentini V. Clinical management of gastroesophageal junction tumors: past and recent evidences for the role of radiotherapy in the multidisciplinary approach. Radiat Oncol. 2014;9:45. Ajani JA, Winter K, Okawara GS, Donohue JH, Pisters PW, Crane CH, et al. Phase II trial of preoperative chemoradiation in patients with localized gastric adenocarcinoma (RTOG 9904): quality of combined modality therapy and pathologic response. J Clin Oncol. 2006;24(24):3953–8. Leong T, Smithers BM, Haustermans K, Michael M, Gebski V, Miller D, et al. TOPGEAR: A Randomized, Phase III Trial of Perioperative ECF Chemotherapy with or Without Preoperative Chemoradiation for Resectable Gastric Cancer: Interim Results from an International, Intergroup Trial of the AGITG, TROG, EORTC and CCTG. Ann Surg Oncol. 2017;24(8):2252–8. Power DG, Reynolds JV. Localized adenocarcinoma of the esophagogastric junction–is there a standard of care? Cancer Treat Rev. 2010;36(5):400–9. Tian S, Jiang R, Madden NA, Ferris MJ, Buchwald ZS, Xu KM, et al. Survival outcomes in patients with gastric and gastroesophageal junction adenocarcinomas treated with perioperative chemotherapy with or without preoperative radiotherapy. Cancer. 2020;126(1):37–45. Lee J, Lim DH, Kim S, Park SH, Park JO, Park YS, et al. Phase III trial comparing capecitabine plus cisplatin versus capecitabine plus cisplatin with concurrent capecitabine radiotherapy in completely resected gastric cancer with D2 lymph node dissection: the ARTIST trial. J Clin Oncol. 2012;30(3):268–73. Jabo B, Selleck MJ, Morgan JW, Lum SS, Bahjri K, Aljehani M, et al. Role of lymph node ratio in selection of adjuvant treatment (chemotherapy vs. chemoradiation) in patients with resected gastric cancer. J Gastrointest Oncol. 2018;9(4):708–17. Yuan M, Bao Y, Ma Z, Men Y, Wang Y, Hui Z. The Optimal Treatment for Resectable Esophageal Cancer: A Network Meta-Analysis of 6168 Patients. Front Oncol. 2021;11:628706. Shah MA, Kennedy EB, Alarcon-Rozas AE, Alcindor T, Bartley AN, Malowany AB, et al. Immunotherapy and Targeted Therapy for Advanced Gastroesophageal Cancer: ASCO Guideline. J Clin Oncol. 2023;41(7):1470–91. Sjoquist KM, Burmeister BH, Smithers BM, Zalcberg JR, Simes RJ, Barbour A, et al. Survival after neoadjuvant chemotherapy or chemoradiotherapy for resectable oesophageal carcinoma: an updated meta-analysis. Lancet Oncol. 2011;12(7):681–92. Li N, Xiang X, Zhao D, Wang X, Tang Y, Chi Y, et al. Preoperative versus postoperative chemo-radiotherapy for locally advanced gastric cancer: a multicenter propensity score-matched analysis. BMC Cancer. 2022;22(1):212. Xiang M, Chang DT, Heestand GM, Pollom EL. Survival after neoadjuvant approaches to gastroesophageal junction cancer. Gastric Cancer. 2020;23(1):175–83. Stiekema J, Trip AK, Jansen EP, Aarts MJ, Boot H, Cats A, et al. Does adjuvant chemoradiotherapy improve the prognosis of gastric cancer after an r1 resection? Results from a dutch cohort study. Ann Surg Oncol. 2015;22(2):581–8. Smyth EC, Nilsson M, Grabsch HI, van Grieken NC, Lordick F. Gastric cancer. Lancet. 2020;396(10251):635–48. Park SH, Lim DH, Sohn TS, Lee J, Zang DY, Kim ST, et al. A randomized phase III trial comparing adjuvant single-agent S1, S-1 with oxaliplatin, and postoperative chemoradiation with S-1 and oxaliplatin in patients with node-positive gastric cancer after D2 resection: the ARTIST 2 trial(☆). Ann Oncol. 2021;32(3):368–74. Zhou YJ, Lu XF, Meng JL, Wang XY, Zhang QW, Chen JN, et al. Neo-adjuvant radiation therapy provides a survival advantage in T3-T4 nodal positive gastric and gastroesophageal junction adenocarcinoma: a SEER database analysis. BMC Cancer. 2021;21(1):771. Zhang N, Fei Q, Gu J, Yin L, He X. Progress of preoperative and postoperative radiotherapy in gastric cancer. World J Surg Oncol. 2018;16(1):187. Solomon N, Zhuge Y, Cheung M, Franceschi D, Koniaris LG. The roles of neoadjuvant radiotherapy and lymphadenectomy in the treatment of esophageal adenocarcinoma. Ann Surg Oncol. 2010;17(3):791–803. Bollschweiler E, Besch S, Drebber U, Schroder W, Monig SP, Vallbohmer D, et al. Influence of neoadjuvant chemoradiation on the number and size of analyzed lymph nodes in esophageal cancer. Ann Surg Oncol. 2010;17(12):3187–94. Giugliano DN, Berger AC, Pucci MJ, Rosato EL, Evans NR, Meidl H, et al. Comparative Quantitative Lymph Node Assessment in Localized Esophageal Cancer Patients After R0 Resection With and Without Neoadjuvant Chemoradiation Therapy. J Gastrointest Surg. 2017;21(9):1377–84. Ho HJ, Chen HS, Hung WH, Hsu PK, Wu SC, Chen HC, et al. Survival Impact of Total Resected Lymph Nodes in Esophageal Cancer Patients With and Without Neoadjuvant Chemoradiation. Ann Surg Oncol. 2018;25(13):3820–32. Ergenc M, Uprak TK, Akin MI, Hekimoglu EE, Celikel CA, Yegen C. Prognostic significance of metastatic lymph node ratio in gastric cancer: a Western-center analysis. BMC Surg. 2023;23(1):220. Topcu R, Sahiner IT, Kendirci M, Erkent M, Sezikli I, Tutan MB. Does lymph node ratio (metastasis/total lymph node count) affect survival and prognosis in gastric cancer? Saudi Med J. 2022;43(2):139–45. Kutlu OC, Watchell M, Dissanaike S. Metastatic lymph node ratio successfully predicts prognosis in western gastric cancer patients. Surg Oncol. 2015;24(2):84–8. Wang X, Chen Y, Gao Y, Zhang H, Guan Z, Dong Z, et al. Predicting gastric cancer outcome from resected lymph node histopathology images using deep learning. Nat Commun. 2021;12(1):1637. Zhu J, Xue Z, Zhang S, Guo X, Zhai L, Shang S, et al. Integrated analysis of the prognostic role of the lymph node ratio in node-positive gastric cancer: A meta-analysis. Int J Surg. 2018;57:76–83. Bilici A, Selcukbiricik F, Seker M, Oven BB, Olmez OF, Yildiz O, et al. Prognostic Significance of Metastatic Lymph Node Ratio in Patients with pN3 Gastric Cancer Who Underwent Curative Gastrectomy. Oncol Res Treat. 2019;42(4):209–16. Kano K, Yamada T, Yamamoto K, Komori K, Watanabe H, Takahashi K, et al. Evaluation of Lymph Node Staging Systems as Independent Prognosticators in Remnant Gastric Cancer Patients with an Insufficient Number of Harvested Lymph Nodes. Ann Surg Oncol. 2021;28(5):2866–76. Kano K, Yamada T, Komori K, Watanabe H, Takahashi K, Fujikawa H, et al. The Prognostic Value of Lymph Node Ratio in Locally Advanced Esophageal Cancer Patients Who Received Neoadjuvant Chemotherapy. Ann Surg Oncol. 2021;28(13):8464–72. Chen Y, Li C, Du Y, Xu Q, Ying J, Luo C. Prognostic and predictive value of metastatic lymph node ratio in stage III gastric cancer after D2 nodal dissection. Oncotarget. 2017;8(41):70841–6. Erstad DJ, Blum M, Estrella JS, Das P, Minsky BD, Ajani JA, et al. Benchmarks for nodal yield and ratio for node-positive gastric cancer. Surgery. 2021;170(4):1231–9. Alatengbaolide, Lin D, Li Y, Xu H, Chen J, Wang B, et al. Lymph node ratio is an independent prognostic factor in gastric cancer after curative resection (R0) regardless of the examined number of lymph nodes. Am J Clin Oncol. 2013;36(4):325–30. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-4476751","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":311614657,"identity":"d945b75f-0279-49a9-9867-2f6af591487f","order_by":0,"name":"chenrui tian","email":"","orcid":"","institution":"Xinxiang Medical University","correspondingAuthor":false,"prefix":"","firstName":"chenrui","middleName":"","lastName":"tian","suffix":""},{"id":311614659,"identity":"f6c613f8-a84a-4433-83f8-e2d85a8d75d4","order_by":1,"name":"Haodi Yu","email":"","orcid":"","institution":"Zhengzhou University People's Hospital","correspondingAuthor":false,"prefix":"","firstName":"Haodi","middleName":"","lastName":"Yu","suffix":""},{"id":311614660,"identity":"ad95a4ab-ac9a-4fca-bec5-101d75985e62","order_by":2,"name":"Qingyu Zhang","email":"","orcid":"","institution":"Henan Provincial People's Hospital","correspondingAuthor":false,"prefix":"","firstName":"Qingyu","middleName":"","lastName":"Zhang","suffix":""},{"id":311614663,"identity":"5f489822-e3f8-4d17-b3c1-47c0a6bccaf7","order_by":3,"name":"Shundong Cang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2klEQVRIiWNgGAWjYLACxgYgcQCIPxjY2JGmhXFGQVoyaVqYeT4cArPxAv72s4df/txxOI/veO/h1zYGB5gZ2A8f3YBPi8SZvDRr3jOHiyXPnEuzzjG4w8fAk5Z2A58WA4YcM2PGtsOJG24AGTkGz5gZJHjM8Gvhf2Nm+BOmxcLgMGMDQS0SOcYPeCFajB8zEKNF4sYbM2betvTEmWfOmDH2GKQlsxHyC39/jvHHn23WiX3He4w//PhjY8fPfvgYXi1AwCaBwmAjoBwEmD+gM0bBKBgFo2AUoAAA8RZRPJIHM6gAAAAASUVORK5CYII=","orcid":"","institution":"Henan Provincial People's Hospital","correspondingAuthor":true,"prefix":"","firstName":"Shundong","middleName":"","lastName":"Cang","suffix":""}],"badges":[],"createdAt":"2024-05-25 12:21:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4476751/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4476751/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":58229416,"identity":"21897416-0843-40a4-97ed-a8436031353b","added_by":"auto","created_at":"2024-06-12 19:15:19","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":268150,"visible":true,"origin":"","legend":"\u003cp\u003eThe flowchart for this study population selection.\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4476751/v1/5c2b64c9217bed564c0a5a76.jpg"},{"id":58229417,"identity":"11ff786e-7af0-4c55-8783-6d45139aa552","added_by":"auto","created_at":"2024-06-12 19:15:19","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1380743,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan-Meier survival analysis to evaluate differences based on the number of lymph nodes resected, the sequencing of radiotherapy, and the types of surgical intervention for adenocarcinomas in the distal esophagus, gastroesophageal junction, and gastric fundus, respectively\u003c/p\u003e\n\u003cp\u003eAEC:adenocarcinomas;\u003c/p\u003e\n\u003cp\u003eOS:overall survival\u003c/p\u003e\n\u003cp\u003eNo-RT: No radiation and/or cancer-directed surgery\u003c/p\u003e\n\u003cp\u003eSRT: Radiation after surgery\u003c/p\u003e\n\u003cp\u003eRST: Radiation prior to surgery\u003c/p\u003e\n\u003cp\u003eRSRT: Radiation before and after surgery\u003c/p\u003e\n\u003cp\u003eG1(Gastrectomy1): Surgery Codes:A300-A500(Not include A500); A300:Gastrectomy, NOS (A310: partial, A320: subtotal, A330:hemi-); A400 Near-total or total gastrectomy, NOS; A410 Near-total gastrectomy; A420 Total gastrectomy\u003c/p\u003e\n\u003cp\u003eG2(Gastrectomy2):A500-A800(Not include A800); (A500-A520 are used for gastrectomy resection when only portions of esophagus are included in procedure); (A600-A630 are used for gastrectomy resections with organs other than esophagus. Portions of esophagus may or may not be included in the resection)\u003c/p\u003e\n\u003cp\u003eE1(Esophagectomy1): Surgery Codes:A300-A500(Not include A500)(A300:Partial esophagectomy A400:Total esophagectomy, NOS)\u003c/p\u003e\n\u003cp\u003eE2(Esophagectomy2): Surgery Codes:A500-A800(Not include A800)(esophagectomy, NOS WITH laryngectomy and/or gastrectomy, NOS), Codes A500-A550 include partial esophagectomy, total esophagectomy, or esophagectomy, NOS.\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4476751/v1/1fe45736de75d9bc3cb35246.jpg"},{"id":58231145,"identity":"201d795a-47ca-4150-b427-7f1cacd3c581","added_by":"auto","created_at":"2024-06-12 19:23:19","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":188169,"visible":true,"origin":"","legend":"\u003cp\u003eNomogram of gastric cancer patients in 1, 3, 5 years.\u003c/p\u003e\n\u003cp\u003eRST: Radiation prior to surgery\u003c/p\u003e\n\u003cp\u003eSRT: Radiation after surgery\u003c/p\u003e\n\u003cp\u003eNoRT: No radiation\u003c/p\u003e","description":"","filename":"Figure4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4476751/v1/9622c6ff834aaddb68d8c839.jpg"},{"id":58229421,"identity":"af4c5486-8aaf-4d8d-8ffc-f3d34ec823de","added_by":"auto","created_at":"2024-06-12 19:15:19","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":347513,"visible":true,"origin":"","legend":"\u003cp\u003eA. The 1 year, 3 years and 5 years calibration of the nomogram in training set. B. The 1 year, 3 years and 5 years calibration of the nomogram in validation set.\u003c/p\u003e","description":"","filename":"Figure5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4476751/v1/6d7b45708c762202cc1542ab.jpg"},{"id":58229418,"identity":"2267c055-70ad-4eba-9ff6-68336253ee98","added_by":"auto","created_at":"2024-06-12 19:15:19","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":330888,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of area under the receiver operating characteristic curves between training set(A) and validation set(B).\u003c/p\u003e","description":"","filename":"Figure6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4476751/v1/d8d338d41aed2fa91421a34c.jpg"},{"id":58229422,"identity":"e5c4b65b-8ced-41c5-8391-fccd75b257d7","added_by":"auto","created_at":"2024-06-12 19:15:19","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":394377,"visible":true,"origin":"","legend":"\u003cp\u003eThe decision curve analysis of the nomogram for 1 year, 3 years, 5 years in the training set(A) and validation set(B).\u003c/p\u003e","description":"","filename":"Figure7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4476751/v1/bab1a3c82ab5ae1c0273c966.jpg"},{"id":58229424,"identity":"92119b39-3e4a-4e19-88d1-12e3bd9e1003","added_by":"auto","created_at":"2024-06-12 19:15:19","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":438242,"visible":true,"origin":"","legend":"\u003cp\u003eCumulative incidences of gastric cancer and esophageal adenocarcinoma.\u003c/p\u003e\n\u003cp\u003eA. The cumulative risk of death analysis on the number of lymph node resections, surgical methods, and the sequence of radiotherapy for gastric cancer.\u003c/p\u003e\n\u003cp\u003eB. The cumulative risk of death analysis on the surgical methods, and the sequence of radiotherapy for esophageal cancer.\u003c/p\u003e","description":"","filename":"Figure8.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4476751/v1/febcf44738604609dd33960e.jpg"},{"id":58231146,"identity":"f589b9f3-8211-4986-9a65-e525225d6225","added_by":"auto","created_at":"2024-06-12 19:23:19","extension":"jpg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":238674,"visible":true,"origin":"","legend":"\u003cp\u003eRestricted Cubic Splines (RCS) curves of the number of lymph node dissections and metastatic lymph nodes rafto(MLR) of mortality risk in gastric cancer and esophageal adenocarcinoma.\u003c/p\u003e\n\u003cp\u003eA. Relationship Between the number of lymph node dissections and the risk of death in gastric cancer.\u003c/p\u003e\n\u003cp\u003eB. Relationship Between the metastatic lymph nodes rafto and the risk of death in gastric cancer.\u003c/p\u003e\n\u003cp\u003eC. Relationship Between the number of lymph node dissections and the risk of death in esophagealcancer.\u003c/p\u003e\n\u003cp\u003eD. Relationship Between the metastatic lymph nodes rafto and the risk of death in esophageal cancer.\u003c/p\u003e","description":"","filename":"Figure9.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4476751/v1/a85d3d009dd3b3a76e1574db.jpg"},{"id":58229425,"identity":"39b214b6-852e-456a-90d0-5278d62a0558","added_by":"auto","created_at":"2024-06-12 19:15:20","extension":"jpg","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":280799,"visible":true,"origin":"","legend":"\u003cp\u003eSlope of the curve of the number of lymph nodes removed in gastric and esophageal adenocarcinoma.\u003c/p\u003e\n\u003cp\u003eA. In gastric adenocarcinoma, after the removal of 36 lymph nodes, patients may not gain significant additional benefits.\u003c/p\u003e\n\u003cp\u003eB. In esophageal adenocarcinoma, after the removal of 28-29 lymph nodes, patients may not gain significant additional benefits.\u003c/p\u003e","description":"","filename":"Figure10.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4476751/v1/2b1cd013b06842d12cdc8c33.jpg"},{"id":59699233,"identity":"fb474d6c-374e-4406-8867-c31ddfe9e6b9","added_by":"auto","created_at":"2024-07-05 04:04:05","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4919404,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4476751/v1/625a1dc7-5b89-4195-a063-f2b67ab5db93.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Comparative Analysis of Adjuvant Radiotherapy, Lymph Node Dissection, and Metastatic Positive Rate on Prognosis in T3-4N+ Gastroesophageal Junction Cancer: A Study Based on SEER Database and External Validation in China","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe management of GEJ cancers presents a significant clinical challenge, leading to active debate over the optimal treatment approach. Recent research has focused on clarifying the role of ART in conjunction with chemotherapy. The CROSS trial(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) provided foundational evidence supporting neoadjuvant chemoradiotherapy(NCRT) while the FLOT4-AIO trial(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) highlighted the benefits of neoadjuvant chemotherapy(NCT), contributing to the current body of literature informing clinical practice. Several studies have compared survival outcomes in patients treated with perioperative CT(POC) alone versus those receiving radiation before surgery(RST) indicating that adding radiation can improve survival outcomes for patients with gastric and GEJ adenocarcinomas(\u003cspan additionalcitationids=\"CR4 CR5\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). The advantages of RST could downstage T2-3 gastric cancer, increase the likelihood of a complete R0 resection, and offer better tolerability(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). TOPGEAR (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e) examined the incremental benefits of adding RST to chemotherapy. While radiotherapy has been associated with better local disease management, as noted by Reynolds et al.(\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e), it also increases the higher risk of toxicity. An Randomized Controlled Trial(RCT) demonstrated that the addition of RST to POC appears to be associated with an increased risk of death in patients with resectable stage IB to stage IIIC gastric and GEJ cancers(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Besides, in the Asian population, the ARTIST trial which focused on Asian patients with post-D2 lymph node dissection, did not show positive results in stage IA or IB gastric cancers, but subgroup analysis suggested that ART could potentially benefit a subset of patients with nodal involvement or intestinal histology type(\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Additionally, the decision to add radiotherapy depends on tumor staging, patient health status, RNE(\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e), and potential response to treatment. Currently, the evidence remains unclear about the advantages of using NRT or ART for those with resectable, locally advanced tumors at the GEJ(\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). Therefore, the safety and feasibility of RST in GEJ cancers need more research. In this study, we aimed to compare the survival differences among ART, surgical methods, RNE, and MLR in patients with T3-4N\u0026thinsp;+\u0026thinsp;GEJ, and to establish a prognostic model for gastric cancer.\u003c/p\u003e "},{"header":"Methods","content":" \u003cp\u003eDatabase and Participants\u003c/p\u003e \u003cp\u003ePatients diagnosed with GEJ cancer were extracted from 18 registries of the Surveillance, Epidemiology, and End Results database (SEER database 2000\u0026ndash;2019) and Henan Provincial People's Hospital (HPPH 2015\u0026ndash;2019) clinical message. In the SEER database, the primary cancer sites were coded according to the \"Primary site label\". We included tumors from five regions at the GEJ: C15.5 Lower third of the esophagus, C15.9 Esophagus NOS, C16.0 Cardia, C16.1 Fundus of the stomach, C16.9 Stomach NOS. For each patient, the following information was collected: Age, Sex, Race recode, Grade, RX Summ\u0026ndash;Surg/Rad Seq, Chemotherapy recode (yes, no/unknown), Radiation recode, RX Summ\u0026ndash;Systemic/Sur Seq, AJCC 7th TNM stage, SEER other cause of death classification, SEER cause-specific death classification, Survival months, Vital.status.recode.study.cutoff.used, Histology.recode-broad.groupings, COD to site rec KM, COD to site recode, Regional.nodes.examined.(1988+), CS.tumor.size. (2004\u0026ndash;2015), Regional nodes examined (1988+), Regional nodes positive (1988+), and positive rate of lymph node metastasis. In the HPPH set, the following information included: Age, Sex, Grade, Primary site, Chemotherapy, Radiation, Surgery, AJCC 7th TNM stage, Survival months, Status, the number of lymph node dissections, and Histology. Patients from the SEER database received chemotherapy, but it is not known whether it was administered before or after surgery.\u003c/p\u003e \u003cdiv id=\"Sec2\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eAll statistical analyses in this study were used by R software version (4.3.1) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.rproject.org/\u003c/span\u003e\u003cspan address=\"http://www.rproject.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). We utilized the \"survminer\" and \"survival\" packages to create Kaplan-Meier (KM) survival curves. A multivariable Cox hazard model was constructed, including variables that had a two-sided p-value of less than 0.05. To identify significant variables, we applied forward and backward selection methods. Using the \"rms\" package, we developed a nomogram for gastric cancer to predict 1-year, 3-year, and 5-year survival probabilities. We expressed the model's results in terms of hazard ratios (HRs) with 95% confidence intervals (CIs). To assess the accuracy of the nomogram, we plotted calibration curves, using a bootstrap method with 1000 resamples. We evaluated the model's discriminative ability by calculating the AUC. DCA was also used to appraise the clinical usefulness of nomogram. The packages \"tidycmprsk,\" \"gtsummary,\" \"ggsurvfit,\" and \"ggprism\" were employed to construct cumulative incidence curves for competing risks, which helped us analyze the impact of radiotherapy and surgery, as well as RNE, on the overall mortality risk associated with different surgical methods. Additionally, we utilized RCS curves to investigate any nonlinear relationship between RNE and the mortality risk.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003col\u003e\n \u003cli\u003e\u003cspan\u003e\n \u003cp\u003eBaseline Characteristics of the Study Population\u003c/p\u003e\n \u003c/span\u003e\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eA total of 7,709 patients with GEJ cancers were identified from the SEER database. Among them 3,176 patients (1,380 with cardia cancer, 1,522 with esophagus cancer, and 274 with gastric cancer) were selected for further analysis. Additionally, we included 312 patients with gastric cancer from HPPH. All patients underwent chemotherapy, although it remains unclear whether these chemotherapy were conducted preoperatively or postoperatively. The flowchart illustrating the selection process for the study population is presented in Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. Clinical and demographic characteristics of GEJ cancer patients from the SEER database are summarized in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\u0026nbsp;\u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eBaseline Characteristics of the Study Population\u003c/span\u003e\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eCardia\u003c/span\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eEsophagus\u003c/span\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eStomach\u003c/span\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eOverall\u003c/span\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003e(N\u0026thinsp;=\u0026thinsp;1380)\u003c/span\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003e(N\u0026thinsp;=\u0026thinsp;1522)\u003c/span\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003e(N\u0026thinsp;=\u0026thinsp;274)\u003c/span\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003e(N\u0026thinsp;=\u0026thinsp;3176)\u003c/span\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eAge\u003c/span\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"4\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e\u0026lt;\u0026thinsp;50\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e151 (10.9%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e138 (9.1%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e32 (11.7%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e321 (10.1%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e\u0026gt;=60\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e900 (65.2%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e1008 (66.2%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e183 (66.8%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e2091 (65.8%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e50\u0026ndash;60\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e329 (23.8%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e376 (24.7%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e59 (21.5%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e764 (24.1%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003eSex\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003eFemale\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e235 (17.0%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e185 (12.2%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e106 (38.7%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e526 (16.6%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003eMale\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e1145 (83.0%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e1337 (87.8%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e168 (61.3%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e2650 (83.4%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003eRace\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003eBlack\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e64 (4.6%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e39 (2.6%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e39 (14.2%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e142 (4.5%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003eOther\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e107 (7.8%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e63 (4.1%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e58 (21.2%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e228 (7.2%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003eWhite\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e1209 (87.6%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e1420 (93.3%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e177 (64.6%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e2806 (88.4%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003eGrade\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003eG1\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e71 (5.1%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e73 (4.8%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e11 (4.0%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e155 (4.9%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003eG2\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e542 (39.3%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e680 (44.7%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e77 (28.1%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e1299 (40.9%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003eG3\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e749 (54.3%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e756 (49.7%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e179 (65.3%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e1684 (53.0%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003eG4\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e18 (1.3%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e13 (0.9%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e7 (2.6%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e38 (1.2%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003eHistology\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003eAEC\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e1366 (99.0%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e1358 (89.2%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e272 (99.3%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e2996 (94.3%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003eSECC\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e14 (1.0%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e164 (10.8%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e2 (0.7%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e180 (5.7%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003eTstage\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003eT1\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e126 (9.1%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e165 (10.8%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e17 (6.2%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e308 (9.7%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003eT2\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e196 (14.2%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e265 (17.4%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e33 (12.0%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e494 (15.6%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003eT3\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e965 (69.9%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e1024 (67.3%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e127 (46.4%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e2116 (66.6%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003eT4\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e93 (6.7%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e68 (4.5%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e97 (35.4%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e258 (8.1%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003eNstage\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003eN0\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e364 (26.4%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e458 (30.1%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e67 (24.5%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e889 (28.0%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003eN1\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e590 (42.8%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e703 (46.2%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e71 (25.9%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e1364 (42.9%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003eN2\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e278 (20.1%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e275 (18.1%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e56 (20.4%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e609 (19.2%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003eN3\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e148 (10.7%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e86 (5.7%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e80 (29.2%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e314 (9.9%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003eRNE\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e\u0026lt;\u0026thinsp;15\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e596 (43.2%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e782 (51.4%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e93 (33.9%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e1471 (46.3%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e\u0026ge;\u0026thinsp;15\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e784 (56.8%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e740 (48.6%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e181 (66.1%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e1705 (53.7%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003eRad.saq\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003eNo radiation and/or cancer-directed surgery\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e333 (24.1%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e181 (11.9%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e141 (51.5%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e655 (20.6%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003eRadiation after surgery\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e212 (15.4%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e113 (7.4%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e127 (46.4%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e452 (14.2%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003eRadiation before and after surgery\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e34 (2.5%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e51 (3.4%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e0 (0%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e85 (2.7%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003eRadiation prior to surgery\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e794 (57.5%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e1162 (76.3%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e6 (2.2%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e1962 (61.8%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003eSurgery both before and after radiation\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e7 (0.5%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e15 (1.0%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e0 (0%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e22 (0.7%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003eTumor.size\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e\u0026le;\u0026thinsp;1mm\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e3 (0.2%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e2 (0.1%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e0 (0%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e5 (0.2%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e\u0026ge;\u0026thinsp;989mm\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e15 (1.1%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e10 (0.7%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e1 (0.4%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e26 (0.8%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e2-988mm\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e1362 (98.7%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e1510 (99.2%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e273 (99.6%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldSmallCaps\" class=\"BoldSmallCaps\" name=\"Emphasis\"\u003e3145 (99.0%)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003eRNE: number of lymph nodes removed; Rad.saq: sequence of radiotherapy and surgery\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cspan\u003e\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003e2. Survival Outcome of GEJ Cancers\u003c/p\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003cp\u003eThe KM survival analysis focused on assessing the impact of the number of resected lymph nodes, the timing of radiotherapy, and the type of surgical procedure on survival outcomes in adenocarcinomas of the lower esophagus, GEJ and upper part of the stomach. Our findings revealed that in T3-4N\u0026thinsp;+\u0026thinsp;gastric cancers, patients who underwent RST did not exhibit a significant survival advantage compared to those who did not (29 months vs. 26 months; p\u0026thinsp;=\u0026thinsp;0.6). Similarly, the choice of surgical approach, ranging from limited excision to full resection, did not result in significantly different survival rates (32 months vs. 22 months; p\u0026thinsp;=\u0026thinsp;0.092). However, patients who had more than 15 lymph nodes removed experienced notebly better survival than those with fewer than 15 lymph nodes removed (31 months vs. 18.5 months; p\u0026thinsp;=\u0026thinsp;0.003). In esophageal adenocarcinoma cases, RST significantly improved median overall survival(mOS) than those who received radiation after surgery(SRT) (34 months vs. 18 months; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Additionally, cardia adenocarcinoma patients with more extensive lymph node removal enjoyed longer mOS(33 months vs. 27 months; p\u0026thinsp;=\u0026thinsp;0.006) (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cspan\u003e\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003e3. Prognostic factors for gastric cancer patients and nomogram validation\u003c/p\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003cp\u003eIn patients with esophageal adenocarcinoma, stages N2 and N3 are significantly associated with a poor prognosis. Similarly, for individuals with cardia adenocarcinoma, age exceeding 60 years and the presence of N2 or N3 cancer stages are correlate with an adverse prognosis. Conversely, the dissection of 15 or more lymph nodes is associated with a more faborable prognosis. An analysis of 175 patients with advanced (T3-4N+) gastric cancer was conducted to identify prognostic factors affecting OS. Using forward and backward selection methods, significant variables were determined. For patients with gastric cancer, advanced age (\u0026gt;\u0026thinsp;60 years) or the manifestation of N2 or N3 stage disease portend a poorer prognosis. However, the prognosis is more favorable for patients with 15 or more local lymph nodes removed. (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ea, b, c). Based on the identified prognostic factors, a nomogram was developed to forecast the 1-year, 3-year, and 5-year survival probabilities (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). The calibration curves showed high consistencies between the predicted and actual survival rates both in the training and validation cohorts(Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e). Subsequent ROC analysis of the nomogram, assessing the likelihood of 1-year, 3-year, and 5-year OS, yielded AUC values of 0.766, 0.785, and 0.766 for the training set, and 0.752, 0.827, and 0.859 for the validation set, respectively. These results underscored a robust agreement between the predicted OS and actual outcomes in both the training and validation cohorts (Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e). Additionally, DCA curves further corroborated the nomogram\u0026apos;s efficacy in clinical practice, affirming its favorable performance (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003ea Multivariable prognostic factors for gastric cancer patients\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eGastric\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHR\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCI95\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;50\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026gt;=60\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.48\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.29\u0026ndash;4.77\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0064\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e50\u0026ndash;60\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.38\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.66\u0026ndash;2.87\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.3962\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eFemale\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eReference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMale\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.04\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.68\u0026ndash;1.59\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.8621\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eRace\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eBlack\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eReference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eOther\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.87\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.46\u0026ndash;1.64\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.6701\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eWhite\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.96\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.56\u0026ndash;1.62\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.8686\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eGrade\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eG1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eReference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eG2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.93\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.21\u0026ndash;4.12\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.9201\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eG3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.02\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.48\u0026ndash;8.6\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.3397\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eG4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.72\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.29\u0026ndash;10.11\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.5465\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eNstage\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eN1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eReference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eN2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.92\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.12\u0026ndash;3.29\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.017\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eN3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.78\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.22\u0026ndash;6.43\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eRad.saq\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo radiation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eReference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eRadiation after surgery\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.67\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.44\u0026ndash;1.02\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0623\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eRadiation prior to surgery\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.48\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.13\u0026ndash;1.75\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.2691\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSurgery\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eGastrectomy1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eReference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eGastrectomy2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.43\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.97\u0026ndash;2.09\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0702\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTumor.size\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026le;\u0026thinsp;1mm\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eReference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e2-988mm\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.72\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.23\u0026ndash;13.11\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.6006\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eRNE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;15\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eReference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026ge;\u0026thinsp;15\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.26\u0026ndash;0.62\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\"\u003eRNE: number of lymph nodes removed; Rad.saq: sequence of radiotherapy and surgery\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"char\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\u0026nbsp;\u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eb Multivariable prognostic factors for esophagus cancer patients\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eEsophagus\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHR\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCI95\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;50\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026gt;=60\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.31\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.94\u0026ndash;1.81\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.1112\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e50\u0026ndash;60\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.23\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.87\u0026ndash;1.75\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.2398\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eFemale\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eReference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMale\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.24\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.92\u0026ndash;1.69\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.1628\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eRace\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eBlack\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eReference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eOther\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.63\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.27\u0026ndash;1.47\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.286\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eWhite\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.87\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.45\u0026ndash;1.7\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.6877\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eGrade\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eG1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eReference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eG2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.97\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.6\u0026ndash;1.59\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.9081\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eG3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.11\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.68\u0026ndash;1.79\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.6802\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eG4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.67\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.68\u0026ndash;4.14\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.2659\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eNstage\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eN1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eReference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eN2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.24\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.02\u0026ndash;1.52\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0335\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eN3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.91\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.41\u0026ndash;2.59\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eRad.saq\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo radiation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eReference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eRadiation after surgery\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.44\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.94\u0026ndash;2.21\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0947\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eRadiation before and after surgery\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.17\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.68\u0026ndash;2.02\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.5667\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eRadiation prior to surgery\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.06\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.78\u0026ndash;1.44\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.7055\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSurgery both before and after radiation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.87\u0026ndash;5.58\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0951\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSurgery\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEsophagectomy1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eReference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEsophagectomy2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.16\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.94\u0026ndash;1.44\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.176\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTumor.size\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026le;\u0026thinsp;1mm\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eReference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026ge;\u0026thinsp;989mm\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.26\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.02\u0026ndash;4.24\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.3469\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e2-988mm\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.41\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.06\u0026ndash;2.94\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.3745\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eRNE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;15\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eReference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026ge;\u0026thinsp;15\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.83\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.69\u0026ndash;1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0552\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\"\u003eRNE: number of lymph nodes removed; Rad.saq: sequence of radiotherapy and surgery\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cspan\u003e\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003e4. Cumulative Incidences of GEJ Cancers and RCS.\u003c/p\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003cp\u003eWe performed an analysis to assess the cumulative risk of mortality about lymph node dissection count, surgical approaches, and radiotherapy sequencing across gastric, cardia, and esophageal adenocarcinomas. For esophageal adenocarcinoma, RST significantly reduced the cumulative mortality risk compared to SRT (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). However, in gastric cancer, there was no significant difference in mortality risk between patients receiving SRT and those who did not undergo any form of radiation therapy (p\u0026thinsp;=\u0026thinsp;0.7) (Fig. \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e). Additionally, we assessed the link between the quantity of lymph node dissections, MLR, and the risk of death using RCS curves. The analysis revealed a decrease in mortality risk with an increased RNE. Nonetheless, an MLR of over 10% raised the mortality risk for both gastric and esophageal adenocarcinoma patients (Fig. \u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003e). In addition, our analysis of the specific number of lymph nodes resected showed that the benefit for gastric cancer patients who had more than 36\u0026ndash;37 lymph nodes resected may be marginal. Similarly, the benefit for patients with esophageal adenocarcinoma who had more than 28\u0026ndash;29 lymph nodes resected may also be marginal(Fig. \u003cspan class=\"InternalRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eGEJ cancers rank among the most prevalent gastrointestinal malignancies worldwide.(\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Clinicians have long been focused on optimizing treatment approaches for these tumors. While various strategies, such as chemotherapy alone or in combination with radiotherapy, have been employed, it remains unclear which approach yields superior patient outcomes. A meta-analysis comparing neoadjuvant chemotherapy (NCT) and radiotherapy demonstrated a significant benefit of concurrent chemoradiotherapy (CRT) (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) and chemotherapy alone (p\u0026thinsp;=\u0026thinsp;0.005) over surgical intervention alone. However, the superiority of CRT over chemotherapy alone was marginal and not statistically significant (p\u0026thinsp;=\u0026thinsp;0.07). Previous evidence supported both NCRT and NCT preceding surgery(\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). While several studies have focused on the benefits of adjuvant CRT in addition to surgical intervention, there is a notable lack of research that specifically investigates the prognostic implications of RNE and MLR respectively in advanced tumors at the GEJ(\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Therefore, our research contributes to the current understanding of adjuvant therapies by examining the impact of lymph node dissection on the outcomes of advanced GEJ cancers.\u003c/p\u003e \u003cp\u003eFor patients with T3-4N\u0026thinsp;+\u0026thinsp;gastric cancer, the performance of postoperative radiation therapy did not show a difference in prognosis (P\u0026thinsp;=\u0026thinsp;0.57). It was noteworthy that according to the data collected from the SEER database, only 3 cases received radical surgical treatment (RST), while 87 received standard radiation therapy (SRT). Therefore, we were unable to conduct a more precise analysis of RST and SRT. In our hospital's patient data, postoperative ART was not administered to patients with T3-4N\u0026thinsp;+\u0026thinsp;gastric cancer. Notably, RST exhibited a pronounced benefit in esophageal adenocarcinoma, in contrast to SRT (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), while the trend was not observed in cardia cancer (p\u0026thinsp;=\u0026thinsp;0.07). The current consensus and guidelines tend to favor the RST or chemotherapy for advanced stages. For example, the NCCN guidelines point out that for T3-4N\u0026thinsp;+\u0026thinsp;tumors at the bottom of the stomach in the GEJ area, where surgery fails to meet the D2 standard or R1 resection(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e), SRT is more suitable for patients with high-risk factors. Consideration should be given to incorporating additional radiation therapy based on chemotherapy. Previous studies have indicated potential benefits of postoperative radiation therapy, particularly in cases of suboptimal surgical resection or absence of D2 lymph node dissection.(\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). However, for patients who have undergone D2 resection, postoperative radiotherapy may not be necessary, especially considering treatment toxicity.(\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e) Currently, the majority of research conclusions on gastric cancer are more inclined toward RST rather than SRT(\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eRST has been shown to reduce the size of locally advanced esophageal tumors and confer a survival benefit(\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e), although it also affects the physiological status of adjacent normal lymph node tissue(\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). Giugliano et al. pointed out that RNE in specimens from patients who had undergone previous radiotherapy was relatively diminished. This phenomenon may be attributed to local fibrosis and structural loss of lymph nodes induced by radiotherapy, leading to inadequate lymph node excision. It was found that the RNE(\u0026lt;\u0026thinsp;15 and \u0026ge;\u0026thinsp;15) was not significantly associated with prognosis(P\u0026thinsp;=\u0026thinsp;0.87)(\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e) while Hui-Ju Ho provided a different conclusion(\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). Conversely, our findings, as revealed by RCS curves, suggest that the removal of 15 lymph nodes might not serve as the optimal prognostic indicator for both esophageal and gastric cancer. Instead, our results indicate that a higher number of lymph nodes removed (RNE) correlates with a reduction in mortality. Furthermore, analysis of the change in slope of the curve revealed that the benefits to patients may not significantly increase beyond an RNE exceeding 36\u0026ndash;37 during gastric cancer surgery. Similarly, in esophageal adenocarcinoma, patients may not derive significant additional benefits after the removal of 28\u0026ndash;29 lymph nodes. Additionally, further analysis of the MLR showed a positive rate greater than 10% increases the risk of mortality(\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). MLR appears to offer a more accurate and objective assessment of prognosis in T3N3 gastric cancer compared to traditional pN staging(\u003cspan additionalcitationids=\"CR30 CR31\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e) and it might be a significant independent risk factor for OS and recurrence free survival(\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). Moreover, radiotherapy was associated with prolonged mOS in patients with MLR ranging from 10\u0026ndash;25% (P\u0026thinsp;=\u0026thinsp;0.002) and those with MLR\u0026thinsp;\u0026gt;\u0026thinsp;25% (P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). However, no significant difference was observed between concurrent CRT and chemotherapy alone among patients with 0% MLR (P\u0026thinsp;=\u0026thinsp;0.16) and those with MLR ranging from 1\u0026ndash;9% (P\u0026thinsp;=\u0026thinsp;0.088)(\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Nonetheless, current research on the impact of MLR staging on the prognosis of gastric cancer is inconsistent, with most studies indicating that a higher ratio correlates with a worse prognosis(\u003cspan additionalcitationids=\"CR36\" citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e). This variability may be due to the use of different cutoff values, potentially introducing bias in the measured survival prognosis. Consequently, further research is needed to elucidate the relationship between MLR and radiotherapy.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThe study revealed that SRT might not necessary for gastric cancer patients, whereas RST was found to be advantageous for those with esophageal adenocarcinoma. In cases of cardia adenocarcinoma, the addition of radiation, either before or after surgery, did not alter the prognosis. Notably, the removal of more than 15 lymph nodes was associated with superior prognosis compared to cases with fewer than 15 nodes removed, and this benefit increased with the removal of even more nodes. Additionally, a higher MLR was correlated with a better prognosis. The nomogram for T3-4N\u0026thinsp;+\u0026thinsp;gastric cancer provides a valuable predictive tool for estimating 5-year survival probability.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eART \u0026nbsp; \u0026nbsp; adjuvant radiotherapy\u003c/p\u003e\n\u003cp\u003eRST \u0026nbsp; \u0026nbsp; radiation before surgery\u003c/p\u003e\n\u003cp\u003eSRT \u0026nbsp; \u0026nbsp; radiation after surgery\u003c/p\u003e\n\u003cp\u003eRCS \u0026nbsp; \u0026nbsp;restricted cubic spline\u003c/p\u003e\n\u003cp\u003eRNE \u0026nbsp; regional.nodes.examined\u003c/p\u003e\n\u003cp\u003eNCRT \u0026nbsp; neoadjuvant chemoradiotherapy\u003c/p\u003e\n\u003cp\u003eROC \u0026nbsp; receiver operating characteristic\u003c/p\u003e\n\u003cp\u003eDCA \u0026nbsp; decision curve analysis\u003c/p\u003e\n\u003cp\u003ePOC \u0026nbsp; \u0026nbsp;perioperative chemotherapy\u003c/p\u003e\n\u003cp\u003eMLR \u0026nbsp; \u0026nbsp;metastatic lymph node ratio\u003c/p\u003e\n\u003cp\u003eGEJ \u0026nbsp; \u0026nbsp; \u0026nbsp;gastroesophageal junction cancer\u003c/p\u003e\n\u003cp\u003eSEER \u0026nbsp; \u0026nbsp; \u0026nbsp;Surveillance, Epidemiology, and End Results database\u003c/p\u003e\n\u003cp\u003eHPPH \u0026nbsp; \u0026nbsp;Henan Provincial People\u0026rsquo;s Hospital\u003c/p\u003e\n\u003cp\u003eOS \u0026nbsp; \u0026nbsp; \u0026nbsp; overall survival \u0026nbsp;\u003c/p\u003e\n\u003cp\u003emOS \u0026nbsp; \u0026nbsp; median overall survival\u003c/p\u003e\n\u003cp\u003eCRT \u0026nbsp; \u0026nbsp; chemoradiotherapy\u003c/p\u003e\n\u003cp\u003eNCT \u0026nbsp; \u0026nbsp;neoadjuvant chemotherapy\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eCompeting interests\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe authors report no conflict of interest.\u003c/p\u003e\n\u003cp\u003eAuthor\u0026rsquo;s contributions\u003c/p\u003e\n\u003cp\u003eT.C.R and Z.Q.Y designed the study. T.C.R and Y.H.D. collected the data. T.C.R and Y.H.D. analyzed the data. T.C.R and Z.Q.Y organized and revised the manuscript. C.S.D supervised the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials\u003c/p\u003e\n\u003cp\u003eThe dataset was abstracted from the SEER database (https://seer.cancer.gov/). The name of the dataset we abstracted was \u0026quot;Incidence-SEER Research Data Plus,17 Registries, Nov 2021 Sub (2000-2019)\u0026quot;. The data from HPPH used and analyzed during the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eThis work was supported by grants from the Key Research and Development Project of Henan Province (231111311900) and Henan scientific and technological project (242102310029).\u003c/p\u003e\n\u003cp\u003eEthics approval and consent to participate\u003c/p\u003e\n\u003cp\u003eThe patients in the Henan Provincial People\u0026apos;s Hospital and SEER database could not be identified, so the analyses and reporting of the data in our study were exempt from review by the Ethics Board of Henan Provincial People\u0026apos;s Hospital Affiliated to Zhengzhou University. The requirement for written informed consent to participate was also waived.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConsent for publication\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eShapiro J, van Lanschot JJB, Hulshof M, van Hagen P, van Berge Henegouwen MI, Wijnhoven BPL, et al. Neoadjuvant chemoradiotherapy plus surgery versus surgery alone for oesophageal or junctional cancer (CROSS): long-term results of a randomised controlled trial. Lancet Oncol. 2015;16(9):1090\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAl-Batran SE, Homann N, Pauligk C, Goetze TO, Meiler J, Kasper S, et al. Perioperative chemotherapy with fluorouracil plus leucovorin, oxaliplatin, and docetaxel versus fluorouracil or capecitabine plus cisplatin and epirubicin for locally advanced, resectable gastric or gastro-oesophageal junction adenocarcinoma (FLOT4): a randomised, phase 2/3 trial. Lancet. 2019;393(10184):1948\u0026ndash;57.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMiccio JA, Oladeru OT, Yang J, Xue Y, Choi M, Zhang Y, et al. Neoadjuvant vs. adjuvant treatment of Siewert type II gastroesophageal junction cancer: an analysis of data from the surveillance, epidemiology, and end results (SEER) registry. J Gastrointest Oncol. 2016;7(3):403\u0026ndash;10.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStahl M, Walz MK, Riera-Knorrenschild J, Stuschke M, Sandermann A, Bitzer M, et al. Preoperative chemotherapy versus chemoradiotherapy in locally advanced adenocarcinomas of the oesophagogastric junction (POET): Long-term results of a controlled randomised trial. Eur J Cancer. 2017;81:183\u0026ndash;90.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGreally M, Agarwal R, Ilson DH. Optimal management of gastroesophageal junction cancer. Cancer. 2019;125(12):1990\u0026ndash;2001.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCellini F, Morganti AG, Di Matteo FM, Mattiucci GC, Valentini V. Clinical management of gastroesophageal junction tumors: past and recent evidences for the role of radiotherapy in the multidisciplinary approach. Radiat Oncol. 2014;9:45.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAjani JA, Winter K, Okawara GS, Donohue JH, Pisters PW, Crane CH, et al. Phase II trial of preoperative chemoradiation in patients with localized gastric adenocarcinoma (RTOG 9904): quality of combined modality therapy and pathologic response. J Clin Oncol. 2006;24(24):3953\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLeong T, Smithers BM, Haustermans K, Michael M, Gebski V, Miller D, et al. TOPGEAR: A Randomized, Phase III Trial of Perioperative ECF Chemotherapy with or Without Preoperative Chemoradiation for Resectable Gastric Cancer: Interim Results from an International, Intergroup Trial of the AGITG, TROG, EORTC and CCTG. Ann Surg Oncol. 2017;24(8):2252\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePower DG, Reynolds JV. Localized adenocarcinoma of the esophagogastric junction\u0026ndash;is there a standard of care? Cancer Treat Rev. 2010;36(5):400\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTian S, Jiang R, Madden NA, Ferris MJ, Buchwald ZS, Xu KM, et al. Survival outcomes in patients with gastric and gastroesophageal junction adenocarcinomas treated with perioperative chemotherapy with or without preoperative radiotherapy. Cancer. 2020;126(1):37\u0026ndash;45.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLee J, Lim DH, Kim S, Park SH, Park JO, Park YS, et al. Phase III trial comparing capecitabine plus cisplatin versus capecitabine plus cisplatin with concurrent capecitabine radiotherapy in completely resected gastric cancer with D2 lymph node dissection: the ARTIST trial. J Clin Oncol. 2012;30(3):268\u0026ndash;73.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJabo B, Selleck MJ, Morgan JW, Lum SS, Bahjri K, Aljehani M, et al. Role of lymph node ratio in selection of adjuvant treatment (chemotherapy vs. chemoradiation) in patients with resected gastric cancer. J Gastrointest Oncol. 2018;9(4):708\u0026ndash;17.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYuan M, Bao Y, Ma Z, Men Y, Wang Y, Hui Z. The Optimal Treatment for Resectable Esophageal Cancer: A Network Meta-Analysis of 6168 Patients. Front Oncol. 2021;11:628706.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShah MA, Kennedy EB, Alarcon-Rozas AE, Alcindor T, Bartley AN, Malowany AB, et al. Immunotherapy and Targeted Therapy for Advanced Gastroesophageal Cancer: ASCO Guideline. J Clin Oncol. 2023;41(7):1470\u0026ndash;91.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSjoquist KM, Burmeister BH, Smithers BM, Zalcberg JR, Simes RJ, Barbour A, et al. Survival after neoadjuvant chemotherapy or chemoradiotherapy for resectable oesophageal carcinoma: an updated meta-analysis. Lancet Oncol. 2011;12(7):681\u0026ndash;92.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi N, Xiang X, Zhao D, Wang X, Tang Y, Chi Y, et al. Preoperative versus postoperative chemo-radiotherapy for locally advanced gastric cancer: a multicenter propensity score-matched analysis. BMC Cancer. 2022;22(1):212.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXiang M, Chang DT, Heestand GM, Pollom EL. Survival after neoadjuvant approaches to gastroesophageal junction cancer. Gastric Cancer. 2020;23(1):175\u0026ndash;83.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStiekema J, Trip AK, Jansen EP, Aarts MJ, Boot H, Cats A, et al. Does adjuvant chemoradiotherapy improve the prognosis of gastric cancer after an r1 resection? Results from a dutch cohort study. Ann Surg Oncol. 2015;22(2):581\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSmyth EC, Nilsson M, Grabsch HI, van Grieken NC, Lordick F. Gastric cancer. Lancet. 2020;396(10251):635\u0026ndash;48.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePark SH, Lim DH, Sohn TS, Lee J, Zang DY, Kim ST, et al. A randomized phase III trial comparing adjuvant single-agent S1, S-1 with oxaliplatin, and postoperative chemoradiation with S-1 and oxaliplatin in patients with node-positive gastric cancer after D2 resection: the ARTIST 2 trial(☆). Ann Oncol. 2021;32(3):368\u0026ndash;74.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhou YJ, Lu XF, Meng JL, Wang XY, Zhang QW, Chen JN, et al. Neo-adjuvant radiation therapy provides a survival advantage in T3-T4 nodal positive gastric and gastroesophageal junction adenocarcinoma: a SEER database analysis. BMC Cancer. 2021;21(1):771.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang N, Fei Q, Gu J, Yin L, He X. Progress of preoperative and postoperative radiotherapy in gastric cancer. World J Surg Oncol. 2018;16(1):187.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSolomon N, Zhuge Y, Cheung M, Franceschi D, Koniaris LG. The roles of neoadjuvant radiotherapy and lymphadenectomy in the treatment of esophageal adenocarcinoma. Ann Surg Oncol. 2010;17(3):791\u0026ndash;803.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBollschweiler E, Besch S, Drebber U, Schroder W, Monig SP, Vallbohmer D, et al. Influence of neoadjuvant chemoradiation on the number and size of analyzed lymph nodes in esophageal cancer. Ann Surg Oncol. 2010;17(12):3187\u0026ndash;94.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGiugliano DN, Berger AC, Pucci MJ, Rosato EL, Evans NR, Meidl H, et al. Comparative Quantitative Lymph Node Assessment in Localized Esophageal Cancer Patients After R0 Resection With and Without Neoadjuvant Chemoradiation Therapy. J Gastrointest Surg. 2017;21(9):1377\u0026ndash;84.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHo HJ, Chen HS, Hung WH, Hsu PK, Wu SC, Chen HC, et al. Survival Impact of Total Resected Lymph Nodes in Esophageal Cancer Patients With and Without Neoadjuvant Chemoradiation. Ann Surg Oncol. 2018;25(13):3820\u0026ndash;32.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eErgenc M, Uprak TK, Akin MI, Hekimoglu EE, Celikel CA, Yegen C. Prognostic significance of metastatic lymph node ratio in gastric cancer: a Western-center analysis. BMC Surg. 2023;23(1):220.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTopcu R, Sahiner IT, Kendirci M, Erkent M, Sezikli I, Tutan MB. Does lymph node ratio (metastasis/total lymph node count) affect survival and prognosis in gastric cancer? Saudi Med J. 2022;43(2):139\u0026ndash;45.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKutlu OC, Watchell M, Dissanaike S. Metastatic lymph node ratio successfully predicts prognosis in western gastric cancer patients. Surg Oncol. 2015;24(2):84\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang X, Chen Y, Gao Y, Zhang H, Guan Z, Dong Z, et al. Predicting gastric cancer outcome from resected lymph node histopathology images using deep learning. Nat Commun. 2021;12(1):1637.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhu J, Xue Z, Zhang S, Guo X, Zhai L, Shang S, et al. Integrated analysis of the prognostic role of the lymph node ratio in node-positive gastric cancer: A meta-analysis. Int J Surg. 2018;57:76\u0026ndash;83.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBilici A, Selcukbiricik F, Seker M, Oven BB, Olmez OF, Yildiz O, et al. Prognostic Significance of Metastatic Lymph Node Ratio in Patients with pN3 Gastric Cancer Who Underwent Curative Gastrectomy. Oncol Res Treat. 2019;42(4):209\u0026ndash;16.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKano K, Yamada T, Yamamoto K, Komori K, Watanabe H, Takahashi K, et al. Evaluation of Lymph Node Staging Systems as Independent Prognosticators in Remnant Gastric Cancer Patients with an Insufficient Number of Harvested Lymph Nodes. Ann Surg Oncol. 2021;28(5):2866\u0026ndash;76.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKano K, Yamada T, Komori K, Watanabe H, Takahashi K, Fujikawa H, et al. The Prognostic Value of Lymph Node Ratio in Locally Advanced Esophageal Cancer Patients Who Received Neoadjuvant Chemotherapy. Ann Surg Oncol. 2021;28(13):8464\u0026ndash;72.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen Y, Li C, Du Y, Xu Q, Ying J, Luo C. Prognostic and predictive value of metastatic lymph node ratio in stage III gastric cancer after D2 nodal dissection. Oncotarget. 2017;8(41):70841\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eErstad DJ, Blum M, Estrella JS, Das P, Minsky BD, Ajani JA, et al. Benchmarks for nodal yield and ratio for node-positive gastric cancer. Surgery. 2021;170(4):1231\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlatengbaolide, Lin D, Li Y, Xu H, Chen J, Wang B, et al. Lymph node ratio is an independent prognostic factor in gastric cancer after curative resection (R0) regardless of the examined number of lymph nodes. Am J Clin Oncol. 2013;36(4):325\u0026ndash;30.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Gastroesophageal Junction Cancer, Adjuvant radiotherapy, Overall survival, Lymph Node Excision, Metastatic lymph node ratio, Surgery","lastPublishedDoi":"10.21203/rs.3.rs-4476751/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4476751/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBackground\u003c/p\u003e\n\u003cp\u003eAdjuvant radiotherapy (ART) is recognized as a pivotal therapeutic modality capable of augmenting the overall survival(OS) outcomes in patients afflicted with gastroesophageal junction cancer (GEJ) at the T3-4N+ stage. However, there remains a need for comprehensive investigations into the optimal timing of radiotherapy administration relative to surgery. Furthermore, the number of regional nodes examined(RNE) and the metastasis lymph node ratio (MLR) exert discernible impacts on the prognosis of such patients. Our study endeavors to delve deeper into elucidating the interplay between ART and surgical interventions, while assessing the prognostic significance of RNE and MLR, with the ultimate goal of developing a nomogram to accurately predict the 5-year survival rate for T3-4N+ gastric cancer patients.\u003c/p\u003e\n\u003cp\u003ePatients and Methods\u003c/p\u003e\n\u003cp\u003e7,709 patients with GEJ cancer were involved from the Surveillance, Epidemiology, and End Results (SEER) database, spanning 2010 to 2019. 335 gastric cancer patients were involved from the Henan Provincial People's Hospital (HPPH), spanning 2015 to 2019. OS was analyzed using the log-rank test and multivariate analysis. The Cox regression models were valuable in predicting outcomes for these cancers. Receiver operating characteristic curve (ROC) and Decision Curve Analysis (DCA) were used to validate predictive model. Restricted cubic splines (RCS) were employed to analyze the potential nonlinear relationship between RNE and prognosis. Additionally, the relationship between MLR and prognosis was examined using the same method.\u003c/p\u003e\n\u003cp\u003eRESULTS\u003c/p\u003e\n\u003cp\u003eWe found that esophageal adenocarcinoma exhibited a superior response to preoperative radiotherapy(p\u0026lt;0.001). However, the timing of radiotherapy for gastric adenocarcinoma post-operation did not significantly affect outcomes (p=0.6). Age, tumor grade, lymph node stage, RNE, type of surgery, and timing of radiotherapyrelative to surgery emerged as crucial prognostic factors for T3-4N+ gastric cancers. Additionally, the analysis showed no significant nonlinear relationship between RNE (with a threshold of 15) and patient survival in esophageal and gastric adenocarcinomas (p\u0026gt;0.05), suggesting consistent findings across varying levels of lymph node removal.\u003c/p\u003e\n\u003cp\u003eCONCLUSIONS\u003c/p\u003e\n\u003cp\u003eEsophageal adenocarcinoma demonstrates a greater therapeutic response to preoperative radiotherapy. Our nomogram provides an effective tool for predicting the 5-year prognosis of T3-4N+ gastric adenocarcinoma. Moreover, our analysis suggests that the removal of 15 lymph nodes may not represent the optimal strategy for lymph node dissection. Additionally, MLR emerges as a significant prognostic factor influencing outcomes in patients with both esophageal and gastric cancer.\u003c/p\u003e","manuscriptTitle":"Comparative Analysis of Adjuvant Radiotherapy, Lymph Node Dissection, and Metastatic Positive Rate on Prognosis in T3-4N+ Gastroesophageal Junction Cancer: A Study Based on SEER Database and External Validation in China","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-12 19:15:15","doi":"10.21203/rs.3.rs-4476751/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"802b110b-1edb-4fff-b277-e0d709403009","owner":[],"postedDate":"June 12th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-07-10T13:36:48+00:00","versionOfRecord":[],"versionCreatedAt":"2024-06-12 19:15:15","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4476751","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4476751","identity":"rs-4476751","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}