Clinicopathological and prognostic features of early gastric cancer patients after surgery: a retrospective study

Clinicopathological and prognostic features of early gastric cancer patients after surgery: a retrospective study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Clinicopathological and prognostic features of early gastric cancer patients after surgery: a retrospective study Jing Qi, Congbo Zhu, Weihang Liu, Sheng Liu, Gaoqiang Cai, Guo-Qing Liao This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-46111/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: Despite the decline in the incidence of gastric cancer, the incidence of early gastric cancer has increased. Hence, understanding the clinicopathological and prognostic features of early gastric cancers could help us understand the development of gastric cancer and improve the prognosis of early gastric cancer. Methods : A total of 244 patients diagnosed with early gastric cancer after surgery at Xiangya Hospital Central South University were retrospectively analyzed. Results : General data showed that in patients with a mean age of 54.30±10.68 years (M:F = 1.6:1), the median tumor size was 2.203±1.245 cm. A total of 15.6% of patients had lymph node metastasis. By univariate analysis, the longest diameter of the tumor, T stage, total number of dissected lymph nodes, number of metastatic lymph nodes, metastatic-to-total dissected lymph node (LN) ratio, vascular invasion, NLRc, and MLRc were associated with disease-free survival; tumor size, invasive depths, vascular invasion, NLRc, MLRc, NWRc and LWRc were associated with lymph node metastasis. Additionally, the longest diameter of tumor and total number of dissected lymph nodes were independent factors for early gastric cancer patients; tumor size, invasive depths, vascular invasion and NLRc were independent risk factors for lymph node metastasis in EGC. Conclusion: The longest diameter of the tumor and total number of dissected LNs were independent prognostic factors for EGC patients. Additionally, the longest diameter of the tumor, tumor invasive depths, vascular invasion and NLRc were the independent risk factors for lymph node metastasis in EGC patients. Cancer Biology Oncology Early gastric cancer prognostic factors tumor diameter lymph node metastasis risk factors Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction In recent years, the incidence rates of gastric cancer (GC) have been declining steadily worldwide[ 1 ]. However, GC is still the fifth most common malignant tumor and the third leading cause of cancer-related mortality globally, with an estimated 1,033,701 new cases and 782,654 deaths in 2018[ 2 , 3 ]. This translates into a high fatality to new case rate of 75%, which is much higher than that of other prevalent solid cancers, including breast and prostate cancers[ 2 ]. The incidence of GC varies regionally, with approximately 70% occurring in Eastern Asia, Central and Eastern Europe and South America[ 4 ]. Approximately 50% of patients are diagnosed with advanced disease, with a 5-year cancer-specific survival rate lower than 30%[ 5 ]. However, the prognosis of GC markedly depends on the stage at diagnosis. In Western countries, including Europe and the United States, the 5-year survival rate does not exceed 25%[ 6 ], but in Japan, the 5-year cancer-specific survival rate is 90% with the diagnosis of early GC of up to 50%[ 7 ]. Similar to other common cancers, GC rarely occurs in children and young persons, with a peak incidence ranging from 55 to 80 years, and gastric cancer rates are twice as high in men as in women[ 8 ]. GC is divided into early gastric cancer (EGC) and advanced gastric cancer, with significant differences in recurrence and cancer-related survival rates. EGC is defined as a carcinoma invading the mucosa and/or submucosa with or without lymph node metastases[ 9 ]. Despite a decline in the incidence of total gastric cancer and the aging of the population, the incidence of early gastric cancer has been steadily increasing since the late 1980s[ 10 ]. Recent studies on EGC data remain incomplete and conflicting; with the growing incidence of early gastric cancer, it is essential to focus on the clinical and prognostic features of early gastric cancer, as they are controversial. We retrospectively examined patients with early gastric cancer in our center, aiming to achieve a better understanding of clinicopathologic features, the development of gastric cancer and prognostic factors in early gastric cancer and to improve the outcomes of gastric cancer. Patients And Methods Patient selection Data of patients who were diagnosed with EGC from January 2013 to December 2018 after surgery at Xiangya Hospital Central South University were collected through a pathology information system. The eligibility criteria in this study included (1) patients who were histopathologically diagnosed with early gastric cancer (carcinoma invading the mucosa and/or submucosa) after surgery; (2) no other synchronous malignant neoplasia; (3) no perioperative or postoperative chemotherapy or radiotherapy applied. This retrospective study was supported by the Medical Ethical Committee of Xiangya Hospital, Central South University, and due to the retrospective nature of the study, informed consent was waived. Data of routine blood collection All patients’ preoperative and postoperative peripheral routine blood tests were drawn within 7 days before the operation and 7 days after the operation. iNLR (initial preoperative neutrophil-to-lymphocyte ratio), iMLR(initial preoperative monocyte-to-lymphocyte ratio), iNWR (initial preoperative neutrophil-to-white blood cell ratio), iLWR (initial preoperative lymphocyte-to-white blood cell ratio), iPLR (initial preoperative platelet-to-lymphocyte ratio), iMWR (initial preoperative monocyte-to-white blood cell ratio), NLRc (postoperative change NLR), MLRc (postoperative change MLR), NWRc (postoperative change NWR), LWRc (postoperative change LWR), PLRc (postoperative change PLR), and MWRc (postoperative change NWR) were determined by ROC curve analysis. Follow-up data Patients who underwent surgery were followed every 3 months for the first 2 years, every 6 months between 2 and 5 years, and then every 12 months thereafter. We supplemented the follow-ups with our outpatient system or communicated with patients by telephone. We examined the postoperative EGC patients by chest scan, abdominal CT scan, magnetic resonance imaging (MRI) scan, abdominal ultrasound scan, endoscopy (including gastroscopy and colonoscopy) and positron emission tomography-computerized tomography (PET-CT) (if necessary) to evaluate tumor recurrence and distant metastasis. All patients were monitored until October 1, 2019, or death. Metastatic recurrence revealed by imaging and death were regarded as the endpoint events. X-tile and statistical analyses Patient characteristics between each group were compared by chi-square test. The values for the iNLR, iMLR, iPLR, iNWR, iLWR, iMWR, NLRc, MLRc, PLRc, NWRc, LWRc, MWRc, longest diameter of the tumor, total number of dissected lymph nodes (LNs), number of metastatic LNs, and ratio of metastatic-to-total dissected LNs were determined by receiver operating characteristic (ROC) curve, based on the results of the ROC curve, X-tile analyses were conducted to assess the optimal cutoff values based on the integral optic density (IOD). The disease-free survival (DFS) and overall survival (OS) were calculated by the Kaplan–Meier method, and differences between Kaplan–Meier curves were investigated by the log-rank test. Significant predictors for survival identified by univariate analysis were further assessed by multivariate analysis using a multivariate Cox proportional hazards regression model (forward stepwise method, conditional likelihood ratio). The significant predictors for lymph node metastasis by univariate analysis were further assessed by logistic regression. Statistical analyses were performed using SPSS V22.0 (SPSS Inc., USA).P value was considered statistically significant below the 5% level. Results Clinicopathologic features for EGC patients For our research, 244 patients were eventually enrolled as our study group (Fig. 1 ). As shown in Table 1 , the EGC group comprised 149 males and 95 females, and the male-to-female ratio was approximately 1.6:1, with a mean age of 54.30 ± 10.68 years, ranging from 24 to 82 years. All patients underwent D2 lymphadenectomy and curative gastrectomy (68.9% underwent the open method and 31.3% underwent the laparoscopy method). Most EGC patients underwent Billroth II reconstruction (71.7%), the tumor was most commonly located in the antrum and pylorus (61.9%), and the average size of the longest diameter of the tumor was 22.03 ± 12.45 mm, ranging from 3 to 85 mm. The most common pathological features included moderate-poor differentiation (58.2%), T1b (50.4%), N0 (84.4%), non-perineurium invasion invasion(99.2%), nonvascular invasion (90.6%), HER2-negative immunohistochemistry (81.6%) and TMN stage Ia (76.6%). More details are shown in Table 1 . Table 1 Characterization of the study group Quality N(%) or mean ± SD Mean Age[years](range) 54.30 ± 10.68(24–82) Gender Male 149 (61.1%) Female 95 (38.9%) Methods for operation Open method 168(68.9%) Laparoscopic method 76 (31.3%) Methods for reconstruction Billroth I 36 (14.8%) Billroth II 175(71.7%) Roux-en-Y 33 (13.5%) Localization Cardia 6(2.5%) Fundus 21(8.6%) Body of stomach 66(27.0%) Antrum and pylorus 151(61.9%) Tumor maximal dimension [mm] (range) 22.03 ± 12.45(3–85) Tumor differentiation Well 102(41.8%) Moderate-poor 142(58.2%) T stage Tis 17(7.0%) T1a 104(42.6%) T1b 123(50.4%) N stage N0 206(84.4%) N1 23(9.4%) N2 11(4.5%) N3a 4(1.6%) Numbers of lymph nodes dissection 20.92 ± 7.53(4–51) Metastatic numbers of lymph nodes dissection 0.45 ± 1.44(0–10) Perineuronal invasion Yes 2(0.08%) No 242(99.2%) vascular invasion Yes 23(9.4%) No 221(90.6%) Immunohistochemistry score for her-2 0 199(81.6%) + 26(10.7%) ++ 14(5.7%) +++ 5(2.0%) TNM stage* 0 17(7.0%) Ia 187(76.6%) Ib 25(10.2%) IIa 11(4.5%) IIb 4(1.6%) *according to the NCCN guidelines Gastric cancer(2019,Version 4) ROC analysis and X-tile analyses The values of iNLR, NLRc, iMLR, MLRc, iPLR, PLRc, iNWR, NWRc, iLWR LWRc, iMWR and MWRc were calculated by using ROC curves. Results showed the areas under the ROC curve for NLRc and MLRc were 0.632 (95% CI: 0.519–0.744; P = 0.046) and 0.659 (95% CI: 0.549–0.768; P = 0.016), respectively (Table 2 , Fig. 2 a-e). Besides, NLRc = 7.80 and MLRc = 1.40 were the optimal cutoff points determined by the X-tile program (Fig. 3 a-b). Table 2 Area under the curve(AUC) identified by Disease-free Survival Variable Area P value 95%CI iNLR 0.510 0.882 0.380–0.639 iMLR 0.543 0.516 0.420–0.666 iPLR 0.571 0.281 0.448–0.695 iNWR 0.512 0.859 0.381–0.643 iLWR 0.484 0.806 0.359–0.609 iMWR 0.508 0.898 0.369–0.648 NLRc 0.632 0.046 0.519–0.744 MLRc 0.659 0.016 0.549–0.768 PLRc 0.536 0.589 0.399–0.672 NWRc 0.566 0.315 0.441–0.692 LWRc 0.611 0.085 0.489–0.734 MWRc 0.524 0.714 0.397–0.652 Tumor maximal dimension 0.712 0.001 0.617–0.808 Total LN dissection numbers 0.690 0.003 0.573–0.807 Metastatic LN dissection numbers 0.764 ༜0.001 0.634–0.894 Metastatic-to-total LN dissection numbers ratio 0.770 ༜0.001 0.639–0.901 CI: Confidence interval; NLR: neutrophil-to-lymphocyte ratio; MLR: monocyte-to-lymphocyte ratio; PLR: platelet-to-lymphocyte ratio; NWR: neutrophil-to-white blood cell ratio; LWR: lymphocyte-to-white blood cell ratio; MWR: monocyte-to-white blood cell ratio;.LN: lymph node;LN: lymph node. In addition, results also indicated that the areas under the ROC curve for the longest diameter of the tumor, total number of dissected LNs, number of metastatic LNs and ratio of metastatic-to-total dissected LNs were 0.712 (95% CI: 0.617–0.808; P = 0.001), 0.690 (95% CI: 0.573–0.807; P = 0.003), 0.764 (95% CI: 0.634–0.894; P༜0.001), and 0.770 (95% CI: 0.639–0.901; P༜0.001), respectively (Table 2 , Fig. 2 f-i). Moreover, the best cutoff values were 2.0 cm for the diameter of the tumor, 13 for the total number of dissected LNs, 1 for the number of metastatic LNs, and 6% for the ratio of metastatic-to-total dissected LNs determined by X-tile program (Fig. 3 c-f). Risk factors for lymph node(LN) metastasis in EGC patient Since the LN metastasis plays a critical role for the selection of clinical treatment (EMR/ESD or surgery) in EGC patients, it is essential to identify the risk factors for LN metastasis in EGC patients. ROC curve was conducted to calculate the best cutoff points of each viriate for the LN metastasis. Results showed that the optimal cutoff points of NLRc, MLRc, NWRc, LWRc, and tumor maximal dimension were 5.29, 0.49, 0.70, 0.13 and 1.9, respectively(Table S1, Figure S1). Next, we investigated the risk factors for lymph node metastasis according to univariate analysis. As shown in Table 3 , tumor maximal dimension, T stage, vascular invasion, NLRc, MLRc, NWRc, and LWRc were associated with LN metastasis in EGC patients. Moreover, through multivariate analysis we found that tumor maximal dimension (≤ 1.9/༞1.9 cm) (RR:2.421, p = 0.044), T stage(Tis + T1a/T1b) (RR:3.807, p = 0.004), vascular invasion (yes/no) (RR:0.241, p = 0.006) and NLRc(≤ 5.29/༞5.29) (RR:8.500, p = 0.010) were the independent risk factors for LN metastasis in EGC patients (Table 4 ). Table 3 Risk Factors for LN metastasis in EGC patients according to univariate analysis Risk factors LN- LN+ 95% CI P value Age(years) ༜60 129 28 0.234–1.156 0.104 ≥ 60 77 10 Gender Male 129 20 0.751–3.026 0.246 Female 77 18 Methods for operation Open method 141 27 0.413–1.890 0.750 Laparoscopic method 65 11 Methods for reconstruction Billroth I 33 3 - 0.310 Billroth II 144 31 Roux-en-Y 29 4 Localization Cardia 5 1 - 0.752 Fundus 18 3 Body of stomach 53 13 Antrum and pylorus 130 21 Tumor maximal dimension [cm] ≤ 1.9 93 9 1.196–5.882 0.014 ༞1.9 113 29 Tumor differentiation Well 91 12 0.820–3.583 0.149 Moderate-poor 115 26 T stage Tis 17 0 - 0.005 T1a 94 10 T1b 95 28 Perineuronal invasion Yes 1 1 0.011–2.950 0.178 No 205 37 vascular invasion Yes 11 12 0.049–0.305 ༜0.001 No 195 26 Immunohistochemistry score (Her-2) 0 171 28 - 0.119 + 18 8 ++ 12 2 +++ 5 0 NLRc ≤ 5.29 93 7 1.535–8.655 0.002 ༞5.29 113 31 MLRc ≤ 0.49 50 2 1.341–24.819 0.009 ༞0.49 20 5 NWRc ≤ 0.70 70 5 1.270–9.086 0.011 ༞0.70 136 33 NLRc ≤ 0.13 106 27 0.203–0.916 0.026 ༞0.13 100 11 LN: lymph node; EGC: early gastric cancer; EGC: early gastric cancer; cm: centimetre; LN: lymph node; NLRc: postoperative neutrophil-to-lymphocyte ratio change; MLRc: postoperative monocyte-to-lymphocyte ratio change; NWRc: postoperative neutrophil-to-white blood cell ratio change; LWRc: postoperative lymphocyte -to-white blood cell ratio change. Table 4 Risk Factors for LN metastasis in EGC patients according to multivariate analysis Risk factors B SE RR 95% CI P value Tumor maximal dimension (≤ 1.9/༞1.9 cm) 0.884 0.440 2.421 1.023–5.799 0.044 T stage(Tis + T1a/T1b) 1.337 0.464 3.807 1.533–9.452 0.004 vascular invasion(yes/no) -1.423 0.515 0.241 0.088–0.661 0.006 NLRc(≤ 5.29/༞5.29) 2.140 0.826 8.500 1.683–42.914 0.010 MLRc (≤ 0.49/༞0.49) 1.178 0.828 3.246 0.642–16.453 0.154 MLRc (≤ 0.70/༞0.70) 0.286 0.661 1.331 0.364–4.865 0.665 MLRc (≤ 0.13/༞0.13) 1.347 0.699 3.844 0.978–15.117 0.054 LN: lymph node; EGC: early gastric cancer; EGC: early gastric cancer; cm: centimetre; LN: lymph node; NLRc: postoperative neutrophil-to-lymphocyte ratio change; MLRc: postoperative monocyte-to-lymphocyte ratio change; NWRc: postoperative neutrophil-to-white blood cell ratio change; LWRc: postoperative lymphocyte -to-white blood cell ratio change. Prognostic features for EGC We further investigated the relationship between the clinicopathologic features and prognosis of EGC patients according to univariate analysis. As shown in Table 5 , we found the longest diameter of the tumor > 2 cm, T1b, total number of dissected LNs ≤ 13, number of metastatic LNs ≥ 1, ratio of metastatic-to-total dissected LNs ≥ 6%, vascular invasion, NLRc > 7.80, MLRc > 1.40 were both associated with recurrence/metastasis and overall survival in EGC patients. Next, Cox proportional hazard models were performed to identify independent prognostic factors. Those identified as significant prognostic factors by univariate analysis were further assessed by a multivariate analysis. The multivariate analysis results showed that the longest diameter of the tumor (≤ 2/༞2 cm) (RR: 7.404, P = 0.001) and total number of dissected LNs (≤ 13/>13) (RR: 0.289, P = 0.015) were independent risk factors for recurrence/metastasis in EGC patients (Table 6 ), otherwise, longest diameter of tumor (≤ 2/༞2 cm) (RR: 4.109, P = 0.033) was the independent risk factors for overall survival in EGC patients(Table 7 ). The DFS and OS for the significant prognostic factors identified by the multivariate analysis is presented in Fig. 5 . Table 5 Prognostic Factors in EGC patients according to univariate analysis Prognostic factors Number DFS OS 95% CI P value 95% CI P value Age(years) ༜60 158 72.311–78.587 0.140 72.744–78.874 0.941 ≥ 60 86 64.002–74.879 70.292–78.258 Gender Male 149 69.120-75.992 0.700 72.373–77.898 0.263 Female 95 69.057–78.181 69.625–78.659 Methods for operation Open method 168 69.457–75.631 0.738 72.109–77.252 0.424 Laparoscopic method 76 65.962–78.996 67.532–79.906 Methods for reconstruction Billroth I 36 74.225–80.517 0.259 74.423–80.452 0.177 Billroth II 175 68.084–75.918 70.645–77.748 Roux-en-Y 33 62.928–77.358 69.810-77.904 Localization Cardia 6 - 0.583 - 0.909 Fundus 21 - - Body of stomach 66 - - Antrum and pylorus 151 - - Tumor maximal dimension[cm] ≤ 2 140 75.813–80.586 ༜0.001 76.621–80.909 0.004 ༞2 104 60.953–71.988 65.094–74.938 Tumor differentiation Well 103 68.198–76.818 0.964 70.182–77.897 0.809 Moderate-poor 141 70.358–77.545 72.973–79.132 T stage Tis + T1a 121 72.946–78.524 0.013 75.091–79.215 0.019 T1b 123 65.677–75.136 68.529–77.093 Total LN numbers ≤ 13 32 56.160-74.715 0.006 61.206–77.822 0.017 ༞13 212 71.386–76.631 73.116–77.687 Metastastic LN numers 0 206 41.107–56.570 ༜0.001 77.240-80.725 ༜0.001 ≥ 1 38 39.656–49.126 46.925–63.573 Metastastic-to-total LN ratio ༜6% 219 75.462–79.773 ༜0.001 77.487–80.744 ༜0.001 ≥ 6% 25 32.105–50.481 37.059–57.319 Perineuronal invasion Yes 2 - 0.656 - 0.682 No 242 - - vascular invasion Yes 23 33.024–54.850 ༜0.001 35.285–54.730 ༜0.001 No 221 73.715–78.722 76.566–80.299 Immunohistochemistry score for Her-2 0 199 - 0.410 - 0.369 + 26 - - ++ 14 - - +++ 5 - - NLRc ≤ 7.80 149 74.102–79.649 0.014 75.453–80.315 0.045 ༞7.80 95 60.067–71.073 64.168–73.808 MLRc ≤ 1.40 219 72.776–78.148 0.002 74.550-79.242 0.014 ༞1.40 25 43.446–64.243 49.086–68.157 EGC: early gastric cancer; DFS:disease-free survival; OS: overall survival; EGC: early gastric cancer; LN: lymph node; cm: centimetre; LN: lymph node; NLRc: postoperative neutrophil-to-lymphocyte ratio change; MLRc: postoperative monocyte-to-lymphocyte ratio change. Table 6 Prognostic Factors for DFS in EGC patients according to multivariate analysis Prognostic factors B SE RR 95% CI P value Tumor maximal dimension (≤ 2/༞2 cm) 2.002 0.604 7.404 2.265–24.196 0.001 T stage(Tis + T1a/T1b) 0.825 0.568 2.281 0.750–6.939 0.146 Total LN numbers (≤ 13/༞13) -1.242 0.513 0.289 0.106–0.789 0.015 Metastastic LN numers(0/≥1) 0.965 1.157 2.626 0.272–25.336 0.404 Metastastic-to-total LN ratio(≤ 6%/༞6%) 0.970 1.149 2.637 0.277–25.077 0.399 vascular invasion(yes/no) -0.517 0.571 0.596 0.195–1.824 0.365 NLRc(≤ 7.80/༞7.80) 0.764 0.544 2.148 0.740–6.235 0.160 MLRc (≤ 1.40/༞1.40) 0.872 0.564 2.392 0.792–7.228 0.122 DFS: Disease-free survival, EGC: Early gastric cancer, CI: confidence interval, RR: relative risk, LN: lymph node, cm: centimetre, NLRc = postoperative neutrophil-to-lymphocyte ratio change, MLRc = postoperative monocyte-to-lymphocyte ratio change. Table 7 Prognostic Factors for OS in EGC patients according to multivariate analysis Prognostic factors B SE RR 95% CI P value Tumor maximal dimension (≤ 2/༞2 cm) 1.413 0.665 4.109 1.117–15.121 0.033 T stage(Tis + T1a/T1b) 0.601 0.738 1.825 0.429–7.759 0.415 Total LN numbers (≤ 13/༞13) -0.952 0.606 0.386 0.118–1.266 0.116 Metastastic LN numers(0/≥1) -7.753 79.179 0.000 0.000-1.072E + 64 0.922 Metastastic-to-total LN ratio(≤ 6%/༞6%) 9.569 79.179 14315.765 0.000-3.570E + 71 0.904 vascular invasion(yes/no) -1.090 0.703 0.336 0.085–1.333 0.121 NLRc(≤ 7.80/༞7.80) 0.413 0.653 1.511 0.421–5.428 0.527 MLRc (≤ 1.40/༞1.40) 0.781 0.713 2.183 0.540–8.829 0.274 OS: overall survival, EGC: early gastric cancer, CI: confidence interval, RR: relative risk, LN: lymph node, cm: centimetre, NLRc = postoperative neutrophil-to-lymphocyte ratio change, MLRc = postoperative monocyte-to-lymphocyte ratio change. Discussion Gastric cancer (GC) has been a critical health burden due to its high morbidity and mortality worldwide, with approximately 1,033,701 new cases and 782,654 deaths in 2018[ 2 ]. Gastric cancer can be divided into early gastric cancer (EGC) and advanced gastric cancer, with significant differences in prognosis. Moreover, despite the declining incidence of GC and due to the advancement of early diagnostic techniques and health examinations, the incidence of EGC seems to have steadily increased since the late 1980s[ 10 – 11 ]. Many studies have indicated clinicopathologic features, multiple genes and molecules in advanced gastric cancer; however, there are limited studies focusing on the clinicopathologic and prognostic features of EGC. Our retrospective analysis of 244 patients with EGC found that the male-to-female ratio was 1.6:1, indicated that gastric cancer is a sex-related carcinoma regardless of whether early gastric cancer or overall gastric cancer patients were included, similar results were indicated by McGuire, S [ 8 ]. We further investigated the prognostic features in EGC and found no significant differences in age, sex, surgical methods, reconstruction methods, tumor location, tumor differentiation, perineurium invasion or immunohistochemistry score for HER2. As our previous study indicated that laparoscopic distal gastrectomy achieves the same degree of radicality and short-term prognosis as open distal gastrectomy[ 12 ], we now verified no significant difference between laparoscopic and open surgical methods in terms of long-term survival of GC patients. Additionally, we found that HER2 expression had no prognostic influence in EGC. However, some retrospective studies have suggested that HER2 positivity is the second worst prognostic factor[ 13 , 14 ], whereas other studies have suggested that HER2 status has no relationship with short- and long-term survival according to univariate and multivariate analyses[ 15 ]. We found that the longest diameter of the tumor = 2 cm were the best cutoff points for the prognosis factor in our large-scale group of EGC patients. Furthermore, the longest diameter of the tumor (≤ 2/༞2 cm) and total number of dissected LNs(≤ 13/༞13) were independent risk factors for EGC patients according to multivariate analysis, with RRs of 7.404 (P = 0.001) and 0.289 (P = 0.015), respectively. Li Y reported that lesions of over 2 cm might be more likely to have lymph node metastasis in EGC[ 17 ]. Similar results have been verified by Li H et al.[ 18 ]. Our research is the first to identify the relationship between the longest diameter of the tumor and disease-free survival rate by using X-tile software and ROC curves. The radical dissection of lymph nodes is a highly effective procedure in gastric cancer to improve the prognosis of GC and limit LN metastasis. Our study found that LN metastasis was 13.9% in EGC, which is higher than the LN metastasis rate of 2.5–8.6% in Japan[ 19 ]. In addition, NCCN guidelines indicated that the number of dissected LNs in GC should be greater than 15; due to the lower incidence of LN metastasis in EGC, lymphadenectomy is always applied with D1+, modified D2 or D2. However, Wu H et al, indicated that in EGC patients with unknown LN status, D2 dissection was the first choice, which could prolong the survival time for those patients[ 20 ]; a similar suggestion was given by Korean and Japanese investigators[ 21 , 22 ]. Our research also showed that the number of dissected LNs lower than 13 was associated with a poor prognosis of EGC patients, and this might be because limited LN dissection might lead to residual cancer, increasing the risk of recurrence or metastasis. Since lymph node metastasis remains a critical role in the therapeutic approach (EMR/ESD vs surgery) for EGC patients, it is important to identify the risk factors for EGC patients[ 23 ]. Our study demonstrated that longest diameter of the tumor (≤ 1.9/༞1.9 cm), T stage (Tis + T1a/T1b), vascular invasion (yes/no), and NLRc (≤ 5.29/༞5.29) were the independent risk factors for LN metastasis. Similarly, Japanese Gastric Cancer Association (JGCA) points that nonulcerated, well-differentiated and lesions diameter less than 2 cm are the indications for EMR/EDS approach in EGC patients[ 24 ]. Additionally, our study also found that the invasive depth of EGC(T stage) and vascular invasion were also associated with lymph node metastasis, Chu YN et al also found that submucosal invasion depth and LVI were the predictive factors for lymph node metastasis[ 25 ], hence, it is truely for the application of ultrasound gastroscope to identify the invasive depths in EGC patients, which could not only measured the lesion size, but also measured the invasive depths of EGC tumors[ 26 ]. In collaboration with previous studies, our research indicated that tumor size ≤ 1.9 cm, ultrasound gastroscope presents the non-submucosa invasion and non-vascular invasion might be the indications for ESD/EMR in EGC patients. There are several limitations in our study. Due to the retrospective nature of the study, some information(such as H.pylori infection, E.B virus infection et, al.) could not be collected; therefore, the analysable risk factors for those patients are still limited, and more data should be considered and collected. In addition, our findings should be verified by large-scale, multiple-center corhort. Moreover, our research retrospected from 2013 to 2018, which might be affected by the developments of practices and surgical expertise in different surgeons. Furthermore, adequate interventions should be applied to improve the EGC prognosis as patients have such poor prognostic factors. Conclusion The longest diameter of the tumor and total number of dissected LNs were independent prognostic factors for EGC patients. Additionally, the longest diameter of the tumor, tumor invasive depths, vascular invasion and NLRc were the independent risk factors for lymph node metastasis in EGC patients. Declarations Ethics approval and consent to participate The research was supported by the Medical Ethical Committee of Xiangya Hospital, Central South University (No. 202004082). Consent for publication Not applicable. Availability of data and materials The raw data underlying this paper are available upon request to the corresponding author due to ethical restrictions. Competing interests The authors declare that they have no competing interests. Funding Not applicable. Authors’ contributions Conceived and designed the experiments: Liao G Analyzed the data: Qi J. Performed the experiments: Qi J, Zhu C, Liu S, Liu W, Cai G. Wrote the paper: Qi J, Liao G. All authors read and approved the final manuscript. Acknowledgments Not applicable. References Pizzi M, Saraggi D, Fassan M, Megraud F, Di Mario F, Rugge M. Secondary prevention of epidemic gastric cancer in the model of Helicobacter pylori-associated gastritis. Dig Dis. 2014;32(3):265–74. Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2018;68(6):394–424. Parkin DM. The global health burden of infection-associated cancers in the year 2002. Int J Cancer. 2006;118(12):3030–44. Guggenheim DE, Shah MA. Gastric cancer epidemiology and risk factors. J Surg Oncol. 2013;107(3):230–6. Yamamoto H, Watanabe Y, Maehata T, Morita R, Yoshida Y, Oikawa R. An updated review of gastric cancer in the next-generation sequencing era: insights from bench to bedside and vice versa. World J Gastroenterol. 2014;20(14):3927–37. Verdecchia A, Francisci S, Brenner H, Gatta G, Micheli A, Mangone L, et al. Recent cancer survival in Europe: a 2000-02 period analysis of EUROCARE-4 data. Lancet Oncol. 2007;8(9):784–96. Luo M, Li L. Clinical utility of miniprobe endoscopic ultrasonography for prediction of invasion depth of early gastric cancer: A meta-analysis of diagnostic test from PRISMA guideline. Med (Baltim). 2019;98(6):e14430. McGuire S World Cancer Report 2014. Geneva, Switzerland: World Health Organization, International Agency for Research on Cancer, WHO Press, 2015. Adv Nutr. 2016; 7(2): 418-9. Hu B, El Hajj N, Sittler S, Lammert N, Barnes R, Meloni-Ehrig A. Gastric cancer: Classification, histology and application of molecular pathology. J Gastrointest Oncol. 2012;3(3):251–61. Bergquist JR, Leiting JL, Habermann EB, Cleary SP, Kendrick ML, Smoot RL, et al. Early-onset gastric cancer is a distinct disease with worrisome trends and oncogenic features. Surgery. 2019;166(4):547–55. Qi J, Liu S, Liu W, Cai G, Liao G. Identification of UAP1L1 as tumor promotor in gastric cancer through regulation of CDK6. Aging. 2020;12(8):6904–27. Ding J, Liao GQ, Liu HL, Liu S, Tang J. Meta-analysis of laparoscopy-assisted distal gastrectomy with D2 lymph node dissection for gastric cancer. J Surg Oncol. 2012;105(3):297–303. Park DI, Yun JW, Park JH, Oh SJ, Kim HJ, Cho YK. HER-2/neu amplification is an independent prognostic factor in gastric cancer. Dig Dis Sci. 2006;51(8):1371–9. Luo X, He Y, Tang H, Cao Y, Gao M, Liu B, et al. Effects of HER2 on the invasion and migration of gastric cancer. Am J Transl Res. 2019;11(12):7604–13. Grabsch H, Sivakumar S, Gray S, Gabbert HE, Müller W. HER2 expression in gastric cancer: Rare, heterogeneous and of no prognostic value - conclusions from 924 cases of two independent series. Cell Oncol. 2010;32(1–2):57–65. Janjigian YY, Werner D, Pauligk C, Steinmetz K, Kelsen DP, Jäger E, et al. Prognosis of metastatic gastric and gastroesophageal junction cancer by HER2 status: a European and USA International collaborative analysis. Ann Oncol. 2012;23(10):2656–62. Li Y, Zhao Q, Fan LQ, Tan BB, Zhang ZD, Liu Y. Analysis of lymph node dissection range-related factors for early gastric cancer operation. Hepatogastroenterology. 2013;60(125):971–4. Li H, Lu P, Lu Y, Liu C, Xu H, Wang S, et al. Predictive factors of lymph node metastasis in undifferentiated early gastric cancers and application of endoscopic mucosal resection. Surg Oncol. 2010;19(4):221–6. Gotoda T, Yanagisawa A, Sasako M, Ono H, Nakanishi Y, Shimoda T, et al. Incidence of lymph node metastasis from early gastric cancer: estimation with a large number of cases at two large centers. Gastric Cancer. 2000;3(4):219–25. Wu H, Wang L, He YL, Xu JB, Cai SR, Ma JP, et al. [Impact of clinicopathological features and extent of lymph node dissection on the prognosis in early gastric cancer patients]. Zhonghua Zhong Liu Za Zhi. 2013;35(7):509–13. Kasakura Y, Fujii M, Mochizuki F, Asaki H, Kobayashi M. Gastrectomy with D2 lymph node dissection in gastric cancer: a retrospective study at a single institution. Int Surg. 2001;86(1):50–6. Park SS, Park JM, Kim JH, Kim WB, Lee J, Kim SJ, et al. Prognostic factors for patients with node-negative gastric cancer: Can extended lymph node dissection have a survival benefit? J Surg Oncol. 2006;94(1):16–20. Abdelfatah MM, Barakat M, Othman MO, Grimm IS, Uedo N. The incidence of lymph node metastasis in submucosal early gastric cancer according to the expanded criteria: a systematic review. Surg Endosc. 2019;33(1):26–32. Ono H, Yao K, Fujishiro M, Oda I, Nimura S, Yahagi N, et al. Guidelines for endoscopic submucosal dissection and endoscopic mucosal resection for early gastric cancer. Dig Endosc. 2016;28(1):3–15. Chu YN, Yu YN, Jing X, Mao T, Chen YQ, Zhou XB, et al. Feasibility of endoscopic treatment and predictors of lymph node metastasis in early gastric cancer. World J Gastroenterol. 2019;25(35):5344–55. Zhao B, Zhang J, Zhang J, Luo R, Wang Z, Xu H, Huang B. Risk Factors Associated with Lymph Node Metastasis for Early Gastric Cancer Patients Who Underwent Non-curative Endoscopic Resection: a Systematic Review and Meta-analysis. J Gastrointest Surg. 2019;23(7):1318–28. Supplementary Files tableS1.docx FigureS1.tif Receiver operating characteristic (ROC) curves for predicting lymph node metastasis among 244 early gastric cancer patients. 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-46111","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research","associatedPublications":[],"authors":[{"id":953294,"identity":"bc19eba5-66d5-4e66-8f02-4a9fe8c9dfc6","order_by":0,"name":"Jing Qi","email":"","orcid":"","institution":"Xiangya Hospital Central South University","correspondingAuthor":false,"prefix":"","firstName":"Jing","middleName":"","lastName":"Qi","suffix":""},{"id":953295,"identity":"5e51404f-1f8c-4256-8c4f-5afb852583e7","order_by":1,"name":"Congbo Zhu","email":"","orcid":"","institution":"The First People’s Hospital of Yueyang","correspondingAuthor":false,"prefix":"","firstName":"Congbo","middleName":"","lastName":"Zhu","suffix":""},{"id":953296,"identity":"33ea1e4b-27f6-4873-b972-371a64fa7ee0","order_by":2,"name":"Weihang Liu","email":"","orcid":"","institution":"Xiangya Hospital Central South University","correspondingAuthor":false,"prefix":"","firstName":"Weihang","middleName":"","lastName":"Liu","suffix":""},{"id":953297,"identity":"0dcbc77b-2a02-41c7-844f-50dec2b78c76","order_by":3,"name":"Sheng Liu","email":"","orcid":"","institution":"Xiangya Hospital Central South University","correspondingAuthor":false,"prefix":"","firstName":"Sheng","middleName":"","lastName":"Liu","suffix":""},{"id":953298,"identity":"c3c17aff-d8e6-4ce4-8423-0ae58c3ef85e","order_by":4,"name":"Gaoqiang Cai","email":"","orcid":"","institution":"Xiangya Hospital Central South University","correspondingAuthor":false,"prefix":"","firstName":"Gaoqiang","middleName":"","lastName":"Cai","suffix":""},{"id":953299,"identity":"8ac15a3c-cf20-4c7e-aa4a-e23048af3dad","order_by":5,"name":"Guo-Qing Liao","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABC0lEQVRIiWNgGAWjYBACPmYog42BgfEBAwOQy8zcgFcLG5IWZgOIFkYCWpDZEmAtDIS0sDM/fPi1zUa2T7r9WtWNCuto/naglh8V2xj4Z2PXysbMZmws25Zm3CZzpux2zpn03BmHGRsYe87cZpC4cwCXX8ykJdsOJ7ZJ5KTdzm07nNsA1MLM2HabwUAiAYcW9m9wLcW5/w7nzieshcdM8iNYS/oxZqAVuRuI0FJszHAO6BeJHGbpnGPpuRuBWg4C/cIjcQO7Fn7+4xsf/iizkZ0/I/3h55wa69x55w8ffPCj4rYc/wzsWkCAmQccFzwGcJEDQMyDUz0QMP4Aa2F/gE/RKBgFo2AUjGAAACdTXE5w4GoOAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0002-5967-0282","institution":"Xiangya Hospital Central South University","correspondingAuthor":true,"prefix":"","firstName":"Guo-Qing","middleName":"","lastName":"Liao","suffix":""}],"badges":[],"createdAt":"2020-07-20 11:46:00","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-46111/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-46111/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":1674115,"identity":"2a399ec9-210f-4469-b551-ef6990c79835","added_by":"auto","created_at":"2020-07-24 14:37:58","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":19554,"visible":true,"origin":"","legend":"The study profile of patients enrolled in our study.","description":"","filename":"figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-46111/v1/figure1.png"},{"id":1674116,"identity":"fc038c02-42a0-4a6e-b09e-b65e0c72ed26","added_by":"auto","created_at":"2020-07-24 14:37:58","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":2638312,"visible":true,"origin":"","legend":"Receiver operating characteristic (ROC) curves for predicting disease-free survival among 244 early gastric cancer patients. (a) Preoperative parameters of routine blood analysis showed no significant prediction of DFS; (b) partial postoperative parameters (including PLRc, NWRc, and MWRc) of routine blood analysis showed no significant prediction of DFS; (c-i) in addition, ROC curves of LWRc, NLRc, MLRc, the longest diameter of the tumor, total number of dissected lymph nodes, number of metastatic lymph nodes, and ratio of metastatic-to-total dissected lymph nodes were used to predict disease-free survival.","description":"","filename":"figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-46111/v1/figure2.jpg"},{"id":1674117,"identity":"6e1fc40c-1912-4199-8f23-a6360a9a5413","added_by":"auto","created_at":"2020-07-24 14:37:58","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":3155196,"visible":true,"origin":"","legend":" X-tile analysis of prognosis based on integral optic density (IOD). X-tile plots showing DFS among 244 EGC patients. (a-f) The data are stratified by NLRc, MLRc, the longest diameter of the tumor, total number of dissected lymph nodes, number of metastatic lymph nodes, and ratio of metastatic-to-total dissected lymph node.","description":"","filename":"figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-46111/v1/figure3.jpg"},{"id":1674118,"identity":"1808307b-dcc7-4f95-907b-08c0911b402a","added_by":"auto","created_at":"2020-07-24 14:37:59","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":4337294,"visible":true,"origin":"","legend":"Disease-free survival and overall survival for 244 early gastric cancer patients. The data are stratified (a-i) by the longest diameter of the tumor (≤2 cm vs \u003e2 cm), total number of dissected lymph nodes (≤13 vs \u003e13), number of metastatic lymph nodes (0 vs ≥1), ratio of metastatic-to-total dissected lymph nodes (\u003c6% vs ≥6%), T stage (Tis+T1a vs T1b), vascular invasion (yes vs no), NLRc (≤7.80 vs \u003e7.80), and MLRc (≤1.40 vs \u003e1.40) based on the univariate analyses.","description":"","filename":"figure4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-46111/v1/figure4.jpg"},{"id":1674119,"identity":"08ac7a5c-aa76-460a-84e5-0f567b62f093","added_by":"auto","created_at":"2020-07-24 14:37:59","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":252327,"visible":true,"origin":"","legend":"Disease-free survival and overall survival for 244 early gastric cancer patients according to multivariate analysis. The data are stratified by (a) the longest diameter of the tumor (≤2 cm vs \u003e2 cm) for recurrence/metastasis in EGC patients; (b)total number of dissected lymph nodes (≤13 vs \u003e13) for recurrence/metastasis in EGC patients; (c)the longest diameter of the tumor (≤2 cm vs \u003e2 cm) for overall survival in EGC patients.","description":"","filename":"figure5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-46111/v1/figure5.jpg"},{"id":13559388,"identity":"8412fac0-6a25-4121-a9e1-0f548c9686dd","added_by":"auto","created_at":"2021-09-17 03:00:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1211805,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-46111/v1/84dfc724-5b58-40b5-b723-518347646be2.pdf"},{"id":1674121,"identity":"07c7e58c-2986-40bf-8a74-90034bd75ed9","added_by":"auto","created_at":"2020-07-24 14:37:59","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":15076,"visible":true,"origin":"","legend":"","description":"","filename":"tableS1.docx","url":"https://assets-eu.researchsquare.com/files/rs-46111/v1/tableS1.docx"},{"id":1674122,"identity":"4824ccd7-2505-461c-92dc-0e5a6d6405f3","added_by":"auto","created_at":"2020-07-24 14:37:59","extension":"tif","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":1279685,"visible":true,"origin":"","legend":"Receiver operating characteristic (ROC) curves for predicting lymph node metastasis among 244 early gastric cancer patients.","description":"","filename":"FigureS1.tif","url":"https://assets-eu.researchsquare.com/files/rs-46111/v1/FigureS1.tif"}],"financialInterests":"","formattedTitle":"Clinicopathological and prognostic features of early gastric cancer patients after surgery: a retrospective study","fulltext":[{"header":"Introduction","content":" \u003cp\u003eIn recent years, the incidence rates of gastric cancer (GC) have been declining steadily worldwide[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. However, GC is still the fifth most common malignant tumor and the third leading cause of cancer-related mortality globally, with an estimated 1,033,701 new cases and 782,654 deaths in 2018[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. This translates into a high fatality to new case rate of 75%, which is much higher than that of other prevalent solid cancers, including breast and prostate cancers[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The incidence of GC varies regionally, with approximately 70% occurring in Eastern Asia, Central and Eastern Europe and South America[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Approximately 50% of patients are diagnosed with advanced disease, with a 5-year cancer-specific survival rate lower than 30%[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. However, the prognosis of GC markedly depends on the stage at diagnosis. In Western countries, including Europe and the United States, the 5-year survival rate does not exceed 25%[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], but in Japan, the 5-year cancer-specific survival rate is 90% with the diagnosis of early GC of up to 50%[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSimilar to other common cancers, GC rarely occurs in children and young persons, with a peak incidence ranging from 55 to 80 years, and gastric cancer rates are twice as high in men as in women[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. GC is divided into early gastric cancer (EGC) and advanced gastric cancer, with significant differences in recurrence and cancer-related survival rates. EGC is defined as a carcinoma invading the mucosa and/or submucosa with or without lymph node metastases[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Despite a decline in the incidence of total gastric cancer and the aging of the population, the incidence of early gastric cancer has been steadily increasing since the late 1980s[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eRecent studies on EGC data remain incomplete and conflicting; with the growing incidence of early gastric cancer, it is essential to focus on the clinical and prognostic features of early gastric cancer, as they are controversial. We retrospectively examined patients with early gastric cancer in our center, aiming to achieve a better understanding of clinicopathologic features, the development of gastric cancer and prognostic factors in early gastric cancer and to improve the outcomes of gastric cancer.\u003c/p\u003e "},{"header":"Patients And Methods","content":" \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePatient selection\u003c/h2\u003e \u003cp\u003eData of patients who were diagnosed with EGC from January 2013 to December 2018 after surgery at Xiangya Hospital Central South University were collected through a pathology information system. The eligibility criteria in this study included (1) patients who were histopathologically diagnosed with early gastric cancer (carcinoma invading the mucosa and/or submucosa) after surgery; (2) no other synchronous malignant neoplasia; (3) no perioperative or postoperative chemotherapy or radiotherapy applied.\u003c/p\u003e \u003cp\u003eThis retrospective study was supported by the Medical Ethical Committee of Xiangya Hospital, Central South University, and due to the retrospective nature of the study, informed consent was waived.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eData of routine blood collection\u003c/h2\u003e \u003cp\u003eAll patients\u0026rsquo; preoperative and postoperative peripheral routine blood tests were drawn within 7 days before the operation and 7 days after the operation. iNLR (initial preoperative neutrophil-to-lymphocyte ratio), iMLR(initial preoperative monocyte-to-lymphocyte ratio), iNWR (initial preoperative neutrophil-to-white blood cell ratio), iLWR (initial preoperative lymphocyte-to-white blood cell ratio), iPLR (initial preoperative platelet-to-lymphocyte ratio), iMWR (initial preoperative monocyte-to-white blood cell ratio), NLRc (postoperative change NLR), MLRc (postoperative change MLR), NWRc (postoperative change NWR), LWRc (postoperative change LWR), PLRc (postoperative change PLR), and MWRc (postoperative change NWR) were determined by ROC curve analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eFollow-up data\u003c/h2\u003e \u003cp\u003ePatients who underwent surgery were followed every 3\u0026nbsp;months for the first 2 years, every 6\u0026nbsp;months between 2 and 5 years, and then every 12\u0026nbsp;months thereafter. We supplemented the follow-ups with our outpatient system or communicated with patients by telephone. We examined the postoperative EGC patients by chest scan, abdominal CT scan, magnetic resonance imaging (MRI) scan, abdominal ultrasound scan, endoscopy (including gastroscopy and colonoscopy) and positron emission tomography-computerized tomography (PET-CT) (if necessary) to evaluate tumor recurrence and distant metastasis. All patients were monitored until October 1, 2019, or death. Metastatic recurrence revealed by imaging and death were regarded as the endpoint events.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eX-tile and statistical analyses\u003c/h2\u003e \u003cp\u003ePatient characteristics between each group were compared by chi-square test. The values for the iNLR, iMLR, iPLR, iNWR, iLWR, iMWR, NLRc, MLRc, PLRc, NWRc, LWRc, MWRc, longest diameter of the tumor, total number of dissected lymph nodes (LNs), number of metastatic LNs, and ratio of metastatic-to-total dissected LNs were determined by receiver operating characteristic (ROC) curve, based on the results of the ROC curve, X-tile analyses were conducted to assess the optimal cutoff values based on the integral optic density (IOD). The disease-free survival (DFS) and overall survival (OS) were calculated by the Kaplan\u0026ndash;Meier method, and differences between Kaplan\u0026ndash;Meier curves were investigated by the log-rank test. Significant predictors for survival identified by univariate analysis were further assessed by multivariate analysis using a multivariate Cox proportional hazards regression model (forward stepwise method, conditional likelihood ratio). The significant predictors for lymph node metastasis by univariate analysis were further assessed by logistic regression. Statistical analyses were performed using SPSS V22.0 (SPSS Inc., USA).P value was considered statistically significant below the 5% level.\u003c/p\u003e \u003c/div\u003e "},{"header":"Results","content":" \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eClinicopathologic features for EGC patients\u003c/h2\u003e \u003cp\u003eFor our research, 244 patients were eventually enrolled as our study group (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). As shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, the EGC group comprised 149 males and 95 females, and the male-to-female ratio was approximately 1.6:1, with a mean age of 54.30\u0026thinsp;\u0026plusmn;\u0026thinsp;10.68 years, ranging from 24 to 82\u0026nbsp;years. All patients underwent D2 lymphadenectomy and curative gastrectomy (68.9% underwent the open method and 31.3% underwent the laparoscopy method). Most EGC patients underwent Billroth II reconstruction (71.7%), the tumor was most commonly located in the antrum and pylorus (61.9%), and the average size of the longest diameter of the tumor was 22.03\u0026thinsp;\u0026plusmn;\u0026thinsp;12.45\u0026nbsp;mm, ranging from 3 to 85\u0026nbsp;mm. The most common pathological features included moderate-poor differentiation (58.2%), T1b (50.4%), N0 (84.4%), non-perineurium invasion invasion(99.2%), nonvascular invasion (90.6%), HER2-negative immunohistochemistry (81.6%) and TMN stage Ia (76.6%). More details are shown in Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCharacterization of the study group\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eQuality\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN(%) or mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eMean Age[years](range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54.30\u0026thinsp;\u0026plusmn;\u0026thinsp;10.68(24\u0026ndash;82)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e149 (61.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95 (38.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMethods for operation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOpen method\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e168(68.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLaparoscopic method\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e76 (31.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eMethods for reconstruction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBillroth I\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36 (14.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBillroth II\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e175(71.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRoux-en-Y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33 (13.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eLocalization\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCardia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6(2.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFundus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21(8.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBody of stomach\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66(27.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAntrum and pylorus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e151(61.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eTumor maximal dimension [mm] (range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.03\u0026thinsp;\u0026plusmn;\u0026thinsp;12.45(3\u0026ndash;85)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTumor differentiation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWell\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e102(41.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModerate-poor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e142(58.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eT stage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17(7.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT1a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e104(42.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT1b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e123(50.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eN stage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e206(84.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23(9.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11(4.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN3a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4(1.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumbers of lymph nodes dissection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.92\u0026thinsp;\u0026plusmn;\u0026thinsp;7.53(4\u0026ndash;51)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMetastatic numbers of lymph nodes dissection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.45\u0026thinsp;\u0026plusmn;\u0026thinsp;1.44(0\u0026ndash;10)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePerineuronal\u0026nbsp;invasion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2(0.08%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e242(99.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003evascular invasion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23(9.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e221(90.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eImmunohistochemistry score for her-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e199(81.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26(10.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e++\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14(5.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e+++\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5(2.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eTNM stage*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17(7.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e187(76.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIb\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25(10.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIIa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11(4.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIIb\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4(1.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e*according to the NCCN guidelines Gastric cancer(2019,Version 4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eROC analysis and X-tile analyses\u003c/h2\u003e \u003cp\u003eThe values of iNLR, NLRc, iMLR, MLRc, iPLR, PLRc, iNWR, NWRc, iLWR LWRc, iMWR and MWRc were calculated by using ROC curves. Results showed the areas under the ROC curve for NLRc and MLRc were 0.632 (95% CI: 0.519\u0026ndash;0.744; P\u0026thinsp;=\u0026thinsp;0.046) and 0.659 (95% CI: 0.549\u0026ndash;0.768; P\u0026thinsp;=\u0026thinsp;0.016), respectively (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea-e). Besides, NLRc\u0026thinsp;=\u0026thinsp;7.80 and MLRc\u0026thinsp;=\u0026thinsp;1.40 were the optimal cutoff points determined by the X-tile program (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea-b).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eArea under the curve(AUC) identified by Disease-free Survival\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eArea\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e95%CI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eiNLR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.510\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.882\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.380\u0026ndash;0.639\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eiMLR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.543\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.516\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.420\u0026ndash;0.666\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eiPLR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.571\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.281\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.448\u0026ndash;0.695\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eiNWR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.512\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.859\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.381\u0026ndash;0.643\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eiLWR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.484\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.806\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.359\u0026ndash;0.609\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eiMWR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.508\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.898\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.369\u0026ndash;0.648\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNLRc\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.632\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.046\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.519\u0026ndash;0.744\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMLRc\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.659\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.016\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.549\u0026ndash;0.768\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePLRc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.536\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.589\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.399\u0026ndash;0.672\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNWRc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.566\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.315\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.441\u0026ndash;0.692\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLWRc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.611\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.085\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.489\u0026ndash;0.734\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMWRc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.524\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.714\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.397\u0026ndash;0.652\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTumor maximal dimension\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.712\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.617\u0026ndash;0.808\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal LN dissection numbers\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.690\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.003\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.573\u0026ndash;0.807\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMetastatic LN dissection numbers\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.764\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e༜0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.634\u0026ndash;0.894\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMetastatic-to-total LN dissection numbers ratio\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.770\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e༜0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.639\u0026ndash;0.901\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eCI: Confidence interval; NLR: neutrophil-to-lymphocyte ratio; MLR: monocyte-to-lymphocyte ratio; PLR: platelet-to-lymphocyte ratio; NWR: neutrophil-to-white blood cell ratio; LWR: lymphocyte-to-white blood cell ratio; MWR: monocyte-to-white blood cell ratio;.LN: lymph node;LN: lymph node.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn addition, results also indicated that the areas under the ROC curve for the longest diameter of the tumor, total number of dissected LNs, number of metastatic LNs and ratio of metastatic-to-total dissected LNs were 0.712 (95% CI: 0.617\u0026ndash;0.808; P\u0026thinsp;=\u0026thinsp;0.001), 0.690 (95% CI: 0.573\u0026ndash;0.807; P\u0026thinsp;=\u0026thinsp;0.003), 0.764 (95% CI: 0.634\u0026ndash;0.894; P༜0.001), and 0.770 (95% CI: 0.639\u0026ndash;0.901; P༜0.001), respectively (Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ef-i). Moreover, the best cutoff values were 2.0\u0026nbsp;cm for the diameter of the tumor, 13 for the total number of dissected LNs, 1 for the number of metastatic LNs, and 6% for the ratio of metastatic-to-total dissected LNs determined by X-tile program (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec-f).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eRisk factors for lymph node(LN) metastasis in EGC patient\u003c/h2\u003e \u003cp\u003eSince the LN metastasis plays a critical role for the selection of clinical treatment (EMR/ESD or surgery) in EGC patients, it is essential to identify the risk factors for LN metastasis in EGC patients. ROC curve was conducted to calculate the best cutoff points of each viriate for the LN metastasis. Results showed that the optimal cutoff points of NLRc, MLRc, NWRc, LWRc, and tumor maximal dimension were 5.29, 0.49, 0.70, 0.13 and 1.9, respectively(Table S1, Figure S1). Next, we investigated the risk factors for lymph node metastasis according to univariate analysis. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, tumor maximal dimension, T stage, vascular invasion, NLRc, MLRc, NWRc, and LWRc were associated with LN metastasis in EGC patients. Moreover, through multivariate analysis we found that tumor maximal dimension (\u0026le;\u0026thinsp;1.9/༞1.9\u0026nbsp;cm) (RR:2.421, p\u0026thinsp;=\u0026thinsp;0.044), T stage(Tis\u0026thinsp;+\u0026thinsp;T1a/T1b) (RR:3.807, p\u0026thinsp;=\u0026thinsp;0.004), vascular invasion (yes/no) (RR:0.241, p\u0026thinsp;=\u0026thinsp;0.006) and NLRc(\u0026le;\u0026thinsp;5.29/༞5.29) (RR:8.500, p\u0026thinsp;=\u0026thinsp;0.010) were the independent risk factors for LN metastasis in EGC patients (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRisk Factors for LN metastasis in EGC patients according to univariate analysis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eRisk factors\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLN-\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLN+\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAge(years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e༜60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e129\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.234\u0026ndash;1.156\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.104\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e129\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.751\u0026ndash;3.026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.246\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMethods for operation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOpen method\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e141\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.413\u0026ndash;1.890\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.750\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLaparoscopic method\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eMethods for reconstruction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBillroth I\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.310\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBillroth II\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRoux-en-Y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eLocalization\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCardia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.752\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFundus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBody of stomach\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAntrum and pylorus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e130\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eTumor maximal dimension\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e[cm]\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e\u0026le;\u0026thinsp;1.9\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e93\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e9\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e1.196\u0026ndash;5.882\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.014\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e༞1.9\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e113\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e29\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTumor differentiation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWell\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.820\u0026ndash;3.583\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.149\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModerate-poor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eT stage\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e17\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.005\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eT1a\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e94\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e10\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eT1b\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e95\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e28\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePerineuronal\u0026nbsp;invasion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.011\u0026ndash;2.950\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.178\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e205\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003evascular invasion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eYes\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e11\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e12\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.049\u0026ndash;0.305\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e༜0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eNo\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e195\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e26\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eImmunohistochemistry score\u003c/p\u003e \u003cp\u003e(Her-2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e171\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.119\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e++\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e+++\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNLRc\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e\u0026le;\u0026thinsp;5.29\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e93\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e7\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e1.535\u0026ndash;8.655\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e༞5.29\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e113\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e31\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMLRc\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e\u0026le;\u0026thinsp;0.49\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e50\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e1.341\u0026ndash;24.819\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.009\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e༞0.49\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e20\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eNWRc\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e\u0026le;\u0026thinsp;0.70\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e70\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e1.270\u0026ndash;9.086\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.011\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e༞0.70\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e136\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e33\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eNLRc\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e\u0026le;\u0026thinsp;0.13\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e106\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e27\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.203\u0026ndash;0.916\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.026\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e༞0.13\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e100\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e11\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eLN: lymph node; EGC: early gastric cancer; EGC: early gastric cancer; cm: centimetre; LN: lymph node; NLRc: postoperative neutrophil-to-lymphocyte ratio change; MLRc: postoperative monocyte-to-lymphocyte ratio change; NWRc: postoperative neutrophil-to-white blood cell ratio change; LWRc: postoperative lymphocyte -to-white blood cell ratio change.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRisk Factors for LN metastasis in EGC patients according to multivariate analysis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRisk factors\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTumor maximal dimension (\u0026le;\u0026thinsp;1.9/༞1.9\u0026nbsp;cm)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.884\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.440\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e2.421\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e1.023\u0026ndash;5.799\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.044\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eT stage(Tis\u0026thinsp;+\u0026thinsp;T1a/T1b)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e1.337\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.464\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e3.807\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e1.533\u0026ndash;9.452\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.004\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003evascular invasion(yes/no)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e-1.423\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.515\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.241\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.088\u0026ndash;0.661\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.006\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNLRc(\u0026le;\u0026thinsp;5.29/༞5.29)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e2.140\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.826\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e8.500\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e1.683\u0026ndash;42.914\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.010\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMLRc (\u0026le;\u0026thinsp;0.49/༞0.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.178\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.828\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.246\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.642\u0026ndash;16.453\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.154\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMLRc (\u0026le;\u0026thinsp;0.70/༞0.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.286\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.661\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.331\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.364\u0026ndash;4.865\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.665\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMLRc (\u0026le;\u0026thinsp;0.13/༞0.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.347\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.699\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.844\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.978\u0026ndash;15.117\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.054\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eLN: lymph node; EGC: early gastric cancer; EGC: early gastric cancer; cm: centimetre; LN: lymph node; NLRc: postoperative neutrophil-to-lymphocyte ratio change; MLRc: postoperative monocyte-to-lymphocyte ratio change; NWRc: postoperative neutrophil-to-white blood cell ratio change; LWRc: postoperative lymphocyte -to-white blood cell ratio change.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003ePrognostic features for EGC\u003c/h2\u003e \u003cp\u003eWe further investigated the relationship between the clinicopathologic features and prognosis of EGC patients according to univariate analysis. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, we found the longest diameter of the tumor\u0026thinsp;\u0026gt;\u0026thinsp;2\u0026nbsp;cm, T1b, total number of dissected LNs\u0026thinsp;\u0026le;\u0026thinsp;13, number of metastatic LNs\u0026thinsp;\u0026ge;\u0026thinsp;1, ratio of metastatic-to-total dissected LNs\u0026thinsp;\u0026ge;\u0026thinsp;6%, vascular invasion, NLRc\u0026thinsp;\u0026gt;\u0026thinsp;7.80, MLRc\u0026thinsp;\u0026gt;\u0026thinsp;1.40 were both associated with recurrence/metastasis and overall survival in EGC patients. Next, Cox proportional hazard models were performed to identify independent prognostic factors. Those identified as significant prognostic factors by univariate analysis were further assessed by a multivariate analysis. The multivariate analysis results showed that the longest diameter of the tumor (\u0026le;\u0026thinsp;2/༞2\u0026nbsp;cm) (RR: 7.404, P\u0026thinsp;=\u0026thinsp;0.001) and total number of dissected LNs (\u0026le;\u0026thinsp;13/\u0026gt;13) (RR: 0.289, P\u0026thinsp;=\u0026thinsp;0.015) were independent risk factors for recurrence/metastasis in EGC patients (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e), otherwise, longest diameter of tumor (\u0026le;\u0026thinsp;2/༞2\u0026nbsp;cm) (RR: 4.109, P\u0026thinsp;=\u0026thinsp;0.033) was the independent risk factors for overall survival in EGC patients(Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). The DFS and OS for the significant prognostic factors identified by the multivariate analysis is presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePrognostic Factors in EGC patients according to univariate analysis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e \u003cp\u003ePrognostic factors\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNumber\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eDFS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eOS\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAge(years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e༜60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e158\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e72.311\u0026ndash;78.587\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e72.744\u0026ndash;78.874\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.941\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e64.002\u0026ndash;74.879\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e70.292\u0026ndash;78.258\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e149\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e69.120-75.992\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.700\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e72.373\u0026ndash;77.898\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.263\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e69.057\u0026ndash;78.181\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e69.625\u0026ndash;78.659\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMethods for\u003c/p\u003e \u003cp\u003eoperation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOpen method\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e168\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e69.457\u0026ndash;75.631\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.738\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e72.109\u0026ndash;77.252\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.424\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLaparoscopic method\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e65.962\u0026ndash;78.996\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e67.532\u0026ndash;79.906\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eMethods for\u003c/p\u003e \u003cp\u003ereconstruction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBillroth I\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e74.225\u0026ndash;80.517\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.259\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e74.423\u0026ndash;80.452\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.177\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBillroth II\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e175\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e68.084\u0026ndash;75.918\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e70.645\u0026ndash;77.748\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRoux-en-Y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e62.928\u0026ndash;77.358\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e69.810-77.904\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eLocalization\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCardia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.583\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.909\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFundus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBody of stomach\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAntrum and pylorus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e151\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eTumor maximal\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003edimension[cm]\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e\u0026le;\u0026thinsp;2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e140\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e75.813\u0026ndash;80.586\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e༜0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e76.621\u0026ndash;80.909\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.004\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e༞2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e104\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e60.953\u0026ndash;71.988\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e65.094\u0026ndash;74.938\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTumor differentiation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWell\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e68.198\u0026ndash;76.818\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.964\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e70.182\u0026ndash;77.897\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.809\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModerate-poor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e141\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e70.358\u0026ndash;77.545\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e72.973\u0026ndash;79.132\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eT stage\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTis\u0026thinsp;+\u0026thinsp;T1a\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e121\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e72.946\u0026ndash;78.524\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.013\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e75.091\u0026ndash;79.215\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.019\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eT1b\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e123\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e65.677\u0026ndash;75.136\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e68.529\u0026ndash;77.093\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eTotal LN numbers\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e\u0026le;\u0026thinsp;13\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e32\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e56.160-74.715\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.006\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e61.206\u0026ndash;77.822\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.017\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e༞13\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e212\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e71.386\u0026ndash;76.631\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e73.116\u0026ndash;77.687\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eMetastastic\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eLN numers\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e206\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e41.107\u0026ndash;56.570\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e༜0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e77.240-80.725\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e༜0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e\u0026ge;\u0026thinsp;1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e38\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e39.656\u0026ndash;49.126\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e46.925\u0026ndash;63.573\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eMetastastic-to-total\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eLN ratio\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e༜6%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e219\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e75.462\u0026ndash;79.773\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e༜0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e77.487\u0026ndash;80.744\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e༜0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e\u0026ge;\u0026thinsp;6%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e25\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e32.105\u0026ndash;50.481\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e37.059\u0026ndash;57.319\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePerineuronal\u003c/p\u003e \u003cp\u003einvasion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.656\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.682\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e242\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003evascular\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003einvasion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eYes\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e23\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e33.024\u0026ndash;54.850\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e༜0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e35.285\u0026ndash;54.730\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e༜0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eNo\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e221\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e73.715\u0026ndash;78.722\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e76.566\u0026ndash;80.299\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eImmunohistochemistry\u003c/p\u003e \u003cp\u003escore for Her-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e199\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.410\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.369\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e++\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e+++\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eNLRc\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e\u0026le;\u0026thinsp;7.80\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e149\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e74.102\u0026ndash;79.649\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.014\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e75.453\u0026ndash;80.315\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.045\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e༞7.80\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e95\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e60.067\u0026ndash;71.073\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e64.168\u0026ndash;73.808\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eMLRc\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e\u0026le;\u0026thinsp;1.40\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e219\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e72.776\u0026ndash;78.148\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e74.550-79.242\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.014\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e༞1.40\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e25\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e43.446\u0026ndash;64.243\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e49.086\u0026ndash;68.157\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003eEGC: early gastric cancer; DFS:disease-free survival; OS: overall survival; EGC: early gastric cancer; LN: lymph node; cm: centimetre; LN: lymph node; NLRc: postoperative neutrophil-to-lymphocyte ratio change; MLRc: postoperative monocyte-to-lymphocyte ratio change.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePrognostic Factors for DFS in EGC patients according to multivariate analysis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrognostic factors\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTumor maximal dimension (\u0026le;\u0026thinsp;2/༞2\u0026nbsp;cm)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e2.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.604\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e7.404\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e2.265\u0026ndash;24.196\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT stage(Tis\u0026thinsp;+\u0026thinsp;T1a/T1b)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.825\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.568\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.281\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.750\u0026ndash;6.939\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.146\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal LN numbers (\u0026le;\u0026thinsp;13/༞13)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e-1.242\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.513\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.289\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.106\u0026ndash;0.789\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.015\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMetastastic LN numers(0/\u0026ge;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.965\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.157\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.626\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.272\u0026ndash;25.336\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.404\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMetastastic-to-total LN ratio(\u0026le;\u0026thinsp;6%/༞6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.970\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.149\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.637\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.277\u0026ndash;25.077\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.399\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003evascular invasion(yes/no)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.517\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.571\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.596\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.195\u0026ndash;1.824\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.365\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNLRc(\u0026le;\u0026thinsp;7.80/༞7.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.764\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.544\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.148\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.740\u0026ndash;6.235\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.160\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMLRc (\u0026le;\u0026thinsp;1.40/༞1.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.872\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.564\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.392\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.792\u0026ndash;7.228\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.122\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eDFS: Disease-free survival, EGC: Early gastric cancer, CI: confidence interval, RR: relative risk, LN: lymph node, cm: centimetre, NLRc\u0026thinsp;=\u0026thinsp;postoperative neutrophil-to-lymphocyte ratio change, MLRc\u0026thinsp;=\u0026thinsp;postoperative monocyte-to-lymphocyte ratio change.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePrognostic Factors for OS in EGC patients according to multivariate analysis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrognostic factors\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTumor maximal dimension (\u0026le;\u0026thinsp;2/༞2\u0026nbsp;cm)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e1.413\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.665\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e4.109\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e1.117\u0026ndash;15.121\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.033\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT stage(Tis\u0026thinsp;+\u0026thinsp;T1a/T1b)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.601\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.738\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.825\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.429\u0026ndash;7.759\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.415\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal LN numbers (\u0026le;\u0026thinsp;13/༞13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.952\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.606\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.386\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.118\u0026ndash;1.266\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.116\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMetastastic LN numers(0/\u0026ge;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-7.753\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e79.179\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000-1.072E\u0026thinsp;+\u0026thinsp;64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.922\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMetastastic-to-total LN ratio(\u0026le;\u0026thinsp;6%/༞6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.569\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e79.179\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14315.765\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000-3.570E\u0026thinsp;+\u0026thinsp;71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.904\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003evascular invasion(yes/no)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-1.090\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.703\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.336\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.085\u0026ndash;1.333\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.121\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNLRc(\u0026le;\u0026thinsp;7.80/༞7.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.413\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.653\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.511\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.421\u0026ndash;5.428\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.527\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMLRc (\u0026le;\u0026thinsp;1.40/༞1.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.781\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.713\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.183\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.540\u0026ndash;8.829\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.274\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eOS: overall survival, EGC: early gastric cancer, CI: confidence interval, RR: relative risk, LN: lymph node, cm: centimetre, NLRc\u0026thinsp;=\u0026thinsp;postoperative neutrophil-to-lymphocyte ratio change, MLRc\u0026thinsp;=\u0026thinsp;postoperative monocyte-to-lymphocyte ratio change.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e "},{"header":"Discussion","content":" \u003cp\u003eGastric cancer (GC) has been a critical health burden due to its high morbidity and mortality worldwide, with approximately 1,033,701 new cases and 782,654 deaths in 2018[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Gastric cancer can be divided into early gastric cancer (EGC) and advanced gastric cancer, with significant differences in prognosis. Moreover, despite the declining incidence of GC and due to the advancement of early diagnostic techniques and health examinations, the incidence of EGC seems to have steadily increased since the late 1980s[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Many studies have indicated clinicopathologic features, multiple genes and molecules in advanced gastric cancer; however, there are limited studies focusing on the clinicopathologic and prognostic features of EGC.\u003c/p\u003e \u003cp\u003eOur retrospective analysis of 244 patients with EGC found that the male-to-female ratio was 1.6:1, indicated that gastric cancer is a sex-related carcinoma regardless of whether early gastric cancer or overall gastric cancer patients were included, similar results were indicated by McGuire, S [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. We further investigated the prognostic features in EGC and found no significant differences in age, sex, surgical methods, reconstruction methods, tumor location, tumor differentiation, perineurium invasion or immunohistochemistry score for HER2. As our previous study indicated that laparoscopic distal gastrectomy achieves the same degree of radicality and short-term prognosis as open distal gastrectomy[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], we now verified no significant difference between laparoscopic and open surgical methods in terms of long-term survival of GC patients. Additionally, we found that HER2 expression had no prognostic influence in EGC. However, some retrospective studies have suggested that HER2 positivity is the second worst prognostic factor[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], whereas other studies have suggested that HER2 status has no relationship with short- and long-term survival according to univariate and multivariate analyses[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWe found that the longest diameter of the tumor\u0026thinsp;=\u0026thinsp;2\u0026nbsp;cm were the best cutoff points for the prognosis factor in our large-scale group of EGC patients. Furthermore, the longest diameter of the tumor (\u0026le;\u0026thinsp;2/༞2\u0026nbsp;cm) and total number of dissected LNs(\u0026le;\u0026thinsp;13/༞13) were independent risk factors for EGC patients according to multivariate analysis, with RRs of 7.404 (P\u0026thinsp;=\u0026thinsp;0.001) and 0.289 (P\u0026thinsp;=\u0026thinsp;0.015), respectively. Li Y reported that lesions of over 2\u0026nbsp;cm might be more likely to have lymph node metastasis in EGC[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Similar results have been verified by Li H et al.[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Our research is the first to identify the relationship between the longest diameter of the tumor and disease-free survival rate by using X-tile software and ROC curves.\u003c/p\u003e \u003cp\u003eThe radical dissection of lymph nodes is a highly effective procedure in gastric cancer to improve the prognosis of GC and limit LN metastasis. Our study found that LN metastasis was 13.9% in EGC, which is higher than the LN metastasis rate of 2.5\u0026ndash;8.6% in Japan[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. In addition, NCCN guidelines indicated that the number of dissected LNs in GC should be greater than 15; due to the lower incidence of LN metastasis in EGC, lymphadenectomy is always applied with D1+, modified D2 or D2. However, Wu H et al, indicated that in EGC patients with unknown LN status, D2 dissection was the first choice, which could prolong the survival time for those patients[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]; a similar suggestion was given by Korean and Japanese investigators[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Our research also showed that the number of dissected LNs lower than 13 was associated with a poor prognosis of EGC patients, and this might be because limited LN dissection might lead to residual cancer, increasing the risk of recurrence or metastasis.\u003c/p\u003e \u003cp\u003eSince lymph node metastasis remains a critical role in the therapeutic approach (EMR/ESD vs surgery) for EGC patients, it is important to identify the risk factors for EGC patients[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Our study demonstrated that longest diameter of the tumor (\u0026le;\u0026thinsp;1.9/༞1.9\u0026nbsp;cm), T stage (Tis\u0026thinsp;+\u0026thinsp;T1a/T1b), vascular invasion (yes/no), and NLRc (\u0026le;\u0026thinsp;5.29/༞5.29) were the independent risk factors for LN metastasis. Similarly, Japanese Gastric Cancer Association (JGCA) points that nonulcerated, well-differentiated and lesions diameter less than 2\u0026nbsp;cm are the indications for EMR/EDS approach in EGC patients[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Additionally, our study also found that the invasive depth of EGC(T stage) and vascular invasion were also associated with lymph node metastasis, Chu YN et al also found that submucosal invasion depth and LVI were the predictive factors for lymph node metastasis[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], hence, it is truely for the application of ultrasound gastroscope to identify the invasive depths in EGC patients, which could not only measured the lesion size, but also measured the invasive depths of EGC tumors[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. In collaboration with previous studies, our research indicated that tumor size\u0026thinsp;\u0026le;\u0026thinsp;1.9\u0026nbsp;cm, ultrasound gastroscope presents the non-submucosa invasion and non-vascular invasion might be the indications for ESD/EMR in EGC patients.\u003c/p\u003e \u003cp\u003eThere are several limitations in our study. Due to the retrospective nature of the study, some information(such as H.pylori infection, E.B virus infection et, al.) could not be collected; therefore, the analysable risk factors for those patients are still limited, and more data should be considered and collected. In addition, our findings should be verified by large-scale, multiple-center corhort. Moreover, our research retrospected from 2013 to 2018, which might be affected by the developments of practices and surgical expertise in different surgeons. Furthermore, adequate interventions should be applied to improve the EGC prognosis as patients have such poor prognostic factors.\u003c/p\u003e "},{"header":"Conclusion","content":" \u003cp\u003eThe longest diameter of the tumor and total number of dissected LNs were independent prognostic factors for EGC patients. Additionally, the longest diameter of the tumor, tumor invasive depths, vascular invasion and NLRc were the independent risk factors for lymph node metastasis in EGC patients.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eEthics approval and consent to participate\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe research was supported by the Medical Ethical Committee of Xiangya Hospital, Central South University (No. 202004082).\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eConsent for publication\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAvailability of data and materials\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe raw data underlying this paper are available upon request to the corresponding author due to ethical restrictions.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCompeting interests\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eFunding\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAuthors\u0026rsquo; contributions\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceived and designed the experiments: Liao G\u003c/p\u003e\n\u003cp\u003eAnalyzed the data: Qi J. Performed the experiments: Qi J, Zhu C, Liu S, Liu W, Cai G.\u003c/p\u003e\n\u003cp\u003eWrote the paper: Qi J, Liao G. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAcknowledgments\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e \u003cspan\u003ePizzi M, Saraggi D, Fassan M, Megraud F, Di Mario F, Rugge M. Secondary prevention of epidemic gastric cancer in the model of Helicobacter pylori-associated gastritis. Dig Dis. 2014;32(3):265\u0026ndash;74.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eBray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2018;68(6):394\u0026ndash;424.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eParkin DM. The global health burden of infection-associated cancers in the year 2002. Int J Cancer. 2006;118(12):3030\u0026ndash;44.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eGuggenheim DE, Shah MA. Gastric cancer epidemiology and risk factors. J Surg Oncol. 2013;107(3):230\u0026ndash;6.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eYamamoto H, Watanabe Y, Maehata T, Morita R, Yoshida Y, Oikawa R. An updated review of gastric cancer in the next-generation sequencing era: insights from bench to bedside and vice versa. World J Gastroenterol. 2014;20(14):3927\u0026ndash;37.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eVerdecchia A, Francisci S, Brenner H, Gatta G, Micheli A, Mangone L, et al. Recent cancer survival in Europe: a 2000-02 period analysis of EUROCARE-4 data. Lancet Oncol. 2007;8(9):784\u0026ndash;96.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eLuo M, Li L. Clinical utility of miniprobe endoscopic ultrasonography for prediction of invasion depth of early gastric cancer: A meta-analysis of diagnostic test from PRISMA guideline. Med (Baltim). 2019;98(6):e14430.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eMcGuire S World Cancer Report 2014. Geneva, Switzerland: World Health Organization, International Agency for Research on Cancer, WHO Press, 2015. Adv Nutr. 2016; 7(2): 418-9.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eHu B, El Hajj N, Sittler S, Lammert N, Barnes R, Meloni-Ehrig A. Gastric cancer: Classification, histology and application of molecular pathology. J Gastrointest Oncol. 2012;3(3):251\u0026ndash;61.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eBergquist JR, Leiting JL, Habermann EB, Cleary SP, Kendrick ML, Smoot RL, et al. Early-onset gastric cancer is a distinct disease with worrisome trends and oncogenic features. Surgery. 2019;166(4):547\u0026ndash;55.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eQi J, Liu S, Liu W, Cai G, Liao G. Identification of UAP1L1 as tumor promotor in gastric cancer through regulation of CDK6. Aging. 2020;12(8):6904\u0026ndash;27.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eDing J, Liao GQ, Liu HL, Liu S, Tang J. Meta-analysis of laparoscopy-assisted distal gastrectomy with D2 lymph node dissection for gastric cancer. J Surg Oncol. 2012;105(3):297\u0026ndash;303.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003ePark DI, Yun JW, Park JH, Oh SJ, Kim HJ, Cho YK. HER-2/neu amplification is an independent prognostic factor in gastric cancer. Dig Dis Sci. 2006;51(8):1371\u0026ndash;9.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eLuo X, He Y, Tang H, Cao Y, Gao M, Liu B, et al. Effects of HER2 on the invasion and migration of gastric cancer. Am J Transl Res. 2019;11(12):7604\u0026ndash;13.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eGrabsch H, Sivakumar S, Gray S, Gabbert HE, M\u0026uuml;ller W. HER2 expression in gastric cancer: Rare, heterogeneous and of no prognostic value - conclusions from 924 cases of two independent series. Cell Oncol. 2010;32(1\u0026ndash;2):57\u0026ndash;65.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eJanjigian YY, Werner D, Pauligk C, Steinmetz K, Kelsen DP, J\u0026auml;ger E, et al. Prognosis of metastatic gastric and gastroesophageal junction cancer by HER2 status: a European and USA International collaborative analysis. Ann Oncol. 2012;23(10):2656\u0026ndash;62.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eLi Y, Zhao Q, Fan LQ, Tan BB, Zhang ZD, Liu Y. Analysis of lymph node dissection range-related factors for early gastric cancer operation. Hepatogastroenterology. 2013;60(125):971\u0026ndash;4.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eLi H, Lu P, Lu Y, Liu C, Xu H, Wang S, et al. Predictive factors of lymph node metastasis in undifferentiated early gastric cancers and application of endoscopic mucosal resection. Surg Oncol. 2010;19(4):221\u0026ndash;6.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eGotoda T, Yanagisawa A, Sasako M, Ono H, Nakanishi Y, Shimoda T, et al. Incidence of lymph node metastasis from early gastric cancer: estimation with a large number of cases at two large centers. Gastric Cancer. 2000;3(4):219\u0026ndash;25.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eWu H, Wang L, He YL, Xu JB, Cai SR, Ma JP, et al. [Impact of clinicopathological features and extent of lymph node dissection on the prognosis in early gastric cancer patients]. Zhonghua Zhong Liu Za Zhi. 2013;35(7):509\u0026ndash;13.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eKasakura Y, Fujii M, Mochizuki F, Asaki H, Kobayashi M. Gastrectomy with D2 lymph node dissection in gastric cancer: a retrospective study at a single institution. Int Surg. 2001;86(1):50\u0026ndash;6.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003ePark SS, Park JM, Kim JH, Kim WB, Lee J, Kim SJ, et al. Prognostic factors for patients with node-negative gastric cancer: Can extended lymph node dissection have a survival benefit? J Surg Oncol. 2006;94(1):16\u0026ndash;20.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eAbdelfatah MM, Barakat M, Othman MO, Grimm IS, Uedo N. The incidence of lymph node metastasis in submucosal early gastric cancer according to the expanded criteria: a systematic review. Surg Endosc. 2019;33(1):26\u0026ndash;32.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eOno H, Yao K, Fujishiro M, Oda I, Nimura S, Yahagi N, et al. Guidelines for endoscopic submucosal dissection and endoscopic mucosal resection for early gastric cancer. Dig Endosc. 2016;28(1):3\u0026ndash;15.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eChu YN, Yu YN, Jing X, Mao T, Chen YQ, Zhou XB, et al. Feasibility of endoscopic treatment and predictors of lymph node metastasis in early gastric cancer. World J Gastroenterol. 2019;25(35):5344\u0026ndash;55.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eZhao B, Zhang J, Zhang J, Luo R, Wang Z, Xu H, Huang B. Risk Factors Associated with Lymph Node Metastasis for Early Gastric Cancer Patients Who Underwent Non-curative Endoscopic Resection: a Systematic Review and Meta-analysis. J Gastrointest Surg. 2019;23(7):1318\u0026ndash;28.\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":"Early gastric cancer, prognostic factors, tumor diameter, lymph node metastasis, risk factors","lastPublishedDoi":"10.21203/rs.3.rs-46111/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-46111/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eDespite the decline in the incidence of gastric cancer, the incidence of early gastric cancer has increased. Hence, understanding the clinicopathological and prognostic features of early gastric cancers could help us understand the development of gastric cancer and improve the prognosis of early gastric cancer. \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: A total of 244 patients diagnosed with early gastric cancer after surgery at Xiangya Hospital Central South University were retrospectively analyzed. \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: General data showed that in patients with a mean age of 54.30±10.68 years (M:F = 1.6:1), the median tumor size was 2.203±1.245 cm. A total of 15.6% of patients had lymph node metastasis. By univariate analysis, the longest diameter of the tumor, T stage, total number of dissected lymph nodes, number of metastatic lymph nodes, metastatic-to-total dissected lymph node (LN) ratio, vascular invasion, NLRc, and MLRc were associated with disease-free survival; tumor size, invasive depths, vascular invasion, NLRc, MLRc, NWRc and LWRc were associated with lymph node metastasis. Additionally, the longest diameter of tumor and total number of dissected lymph nodes were independent factors for early gastric cancer patients; tumor size, invasive depths, vascular invasion and NLRc were independent risk factors for lymph node metastasis in EGC. \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e The longest diameter of the tumor and total number of dissected LNs were independent prognostic factors for EGC patients. Additionally, the longest diameter of the tumor, tumor invasive depths, vascular invasion and NLRc were the independent risk factors for lymph node metastasis in EGC patients.\u003c/p\u003e","manuscriptTitle":"Clinicopathological and prognostic features of early gastric cancer patients after surgery: a retrospective study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2020-07-24 14:37:57","doi":"10.21203/rs.3.rs-46111/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":"975a1ac6-fa0f-493a-9aa3-8e055792bb82","owner":[],"postedDate":"July 24th, 2020","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":197827,"name":"Cancer Biology"},{"id":197828,"name":"Oncology"}],"tags":[],"updatedAt":"2020-08-10T20:02:12+00:00","versionOfRecord":[],"versionCreatedAt":"2020-07-24 14:37:57","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-46111","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-46111","identity":"rs-46111","version":["v1"]},"buildId":"2u56kwukJI3zHK-uzyFNs","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}