scholarly journals Analysis of Predictors for Lymph Node Metastasis in Patients with Superficial Esophageal Carcinoma

2016 ◽  
Vol 2016 ◽  
pp. 1-6 ◽  
Author(s):  
Ruzhen Jia ◽  
Qinsong Luan ◽  
Jing Wang ◽  
Dongsheng Hou ◽  
Shulei Zhao
Keyword(s):  
Risk Factors ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Prediction Model ◽  
Esophageal Carcinoma ◽  
Tumor Size ◽  
Depth Of Invasion ◽  
Node Metastasis ◽  
Superficial Esophageal Carcinoma ◽  
Independent Risk Factors

In order to predict related risk factors for lymph node metastasis (LNM) in patients with superficial esophageal carcinoma (SEC) and provide reference for endoscopic minimally invasive treatment, we included a total of 93 patients with superficial esophageal carcinoma who have underwent esophagectomy and lymph node dissection from 2010 to 2015. The depth of invasion was remeasured and classified into 6 groups according to their wall penetration. The prediction model was founded based on the independent risk factors. The results shows that lymph node metastasis of m1, m2, m3, sm1, sm2, and sm3 of superficial esophageal carcinoma was 0%, 0%, 5.3%, 8.7%, 17.6%, and 37.5%, respectively. The tumor size, differentiation, and lymphvascular invasion were also significantly related to lymph node metastasis by univariate analysis. Multivariate analysis showed that the depth of invasion and lymphovascular invasion were independent risk factors of lymph node metastasis. A prediction model for lymph node metastasis was established as follows: p=ex/(1+ex), and x = −5.469 + 0.839 × depth of invasion + 1.992 × lymphavascular metastasis. The area under ROC curve was 0.858 (95% CI: 0.757–0.959). It was also shown that the depth of invasion was related to tumor differentiation, macroscopic type, and tumor size.

scholarly journals Nomograms for Predicting the Lymph Node Metastasis in Early Gastric Cancer by Gender: A Retrospective Multicentric Study

2021 ◽  
Vol 11 ◽  
Author(s):  
Wannian Sui ◽  
Zhangming Chen ◽  
Chuanhong Li ◽  
Peifeng Chen ◽  
Kai Song ◽  
...  
Keyword(s):  
Risk Factors ◽  
Gastric Cancer ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Depth Of Invasion ◽  
Male And Female ◽  
Node Metastasis ◽  
Independent Risk Factors ◽  
Medical University ◽  
Training Sets

BackgroundLymph node metastasis (LNM) has a significant impact on the prognosis of patients with early gastric cancer (EGC). Our aim was to identify the independent risk factors for LNM and construct nomograms for male and female EGC patients, respectively.MethodsClinicopathological data of 1,742 EGC patients who underwent radical gastrectomy and lymphadenectomy in the First Affiliated Hospital, Second Affiliated Hospital, and Fourth Affiliated Hospital of Anhui Medical University between November 2011 and April 2021 were collected and analyzed retrospectively. Male and female patients from the First Affiliated Hospital of Anhui Medical University were assigned to training sets and then from the Second and Fourth Affiliated Hospitals of Anhui Medical University were enrolled in validation sets. Based on independent risk factors for LNM in male and female EGC patients from the training sets, the nomograms were established respectively, which was also verified by internal validation from the training sets and external validation from the validation sets.ResultsTumor size (odd ratio (OR): 1.386, p = 0.030), depth of invasion (OR: 0.306, p = 0.001), Lauren type (OR: 2.816, p = 0.000), lymphovascular invasion (LVI) (OR: 0.160, p = 0.000), and menopause (OR: 0.296, p = 0.009) were independent risk factors for female EGC patients. For male EGC patients, tumor size (OR: 1.298, p = 0.007), depth of invasion (OR: 0.257, p = 0.000), tumor location (OR: 0.659, p = 0.002), WHO type (OR: 1.419, p = 0.001), Lauren type (OR: 3.099, p = 0.000), and LVI (OR: 0.131, p = 0.000) were independent risk factors. Moreover, nomograms were established to predict the risk of LNM for female and male EGC patients, respectively. The area under the ROC curve of nomograms for female and male training sets were 87.7% (95% confidence interval (CI): 0.8397–0.914) and 94.8% (95% CI: 0.9273–0.9695), respectively. For the validation set, they were 92.4% (95% CI: 0.7979–1) and 93.4% (95% CI: 0.8928–0.9755), respectively. Additionally, the calibration curves showed good agreements between the bias-corrected prediction and the ideal reference line for both training sets and validation sets in female and male EGC patients.ConclusionsNomograms based on risk factors for LNM in male and female EGC patients may provide new insights into the selection of appropriate treatment methods.

scholarly journals Early Gastric Cancer Lymph Node Metastasis Model and Prognostic Survival Prediction Model in Western Population

2020 ◽  
Author(s):  
Huakai Tian ◽  
Zuo Zhang ◽  
Zitao Liu ◽  
Cegui Hu ◽  
Jiang Liu ◽  
...  
Keyword(s):  
Risk Factors ◽  
Gastric Cancer ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Early Gastric Cancer ◽  
Prediction Model ◽  
Tumor Size ◽  
Western Population ◽  
Node Metastasis ◽  
Cox Analysis

Abstract Objective This study analyzed the characteristics of early gastric cancer lymph node metastasis and survival prognosis after surgical resection in western population, and established a predictive model.MethodsPatients with stage T1a and T1b gastric cancer from 2010 to 2015 were screened from the surveillance, epidemiology and final outcome databases. Patients with multiple in situ tumors, distant metastases, and incomplete data were excluded. The risk factors for lymph node metastasis in early gastric cancer were analyzed by binary logistic regression and the chi-square test. Multivariate Cox analysis and the Kaplan-Meier test were used to evaluate the prognostic factors and survival rates of patients with early gastric cancer after surgical resection. The prediction model of lymph node metastasis and survival rate of early gastric cancer was established and verified by R software.ResultsIn 2294 patients, the lymph node metastasis rate was 14.5% (333/2294). Binary logistic multivariate regression analysis showed that tumor size (>2cm), tumor grade (III/IV), and stage T1b were risk factors for lymph node metastasis of early gastric cancer. Area under the curve (AUC) is 0.782.A predictive model was developed based on risk factors, and the model C index was 0.771, indicating that the model has good predictive ability. In addition, survival analysis of 2294 patients showed that the 5-year OS and CSS (75.4% and 88.7%) in patients without EGC were significantly higher than those with lymph node metastasis (64.3% and 72.8%) (P<0.05). Multivariate COX analysis showed that age, sex, race, tumor size, submucosal invasion and lymph node metastasis were independent factors influencing the prognosis of early gastric cancer. A cancer-specific survival (CSS) prediction model was constructed based on prognostic risk factors. The 3-year area under the CSS curve (AUC) was 0.706, and the 5-year area under the CSS curve (AUC) was 0.710. The prediction model is more consistent with the actual situation.ConclusionsWe established a reliable prediction model for lymph node metastasis of early gastric cancer and a prognostic model for early gastric cancer, which provided a good basis for clinical treatment decision.

scholarly journals The Characteristics, Prognosis, and Risk Factors of Lymph Node Metastasis in Early Gastric Cancer

2018 ◽  
Vol 2018 ◽  
pp. 1-7 ◽  
Author(s):  
Xuan Li ◽  
Shiyu Liu ◽  
Jin Yan ◽  
Lei Peng ◽  
Meihong Chen ◽  
...  
Keyword(s):  
Risk Factors ◽  
Gastric Cancer ◽  
Multivariate Analysis ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Early Gastric Cancer ◽  
Depth Of Invasion ◽  
Node Metastasis ◽  
Independent Risk Factors ◽  
Male Sex

Background. Lymph node metastasis (LNM) is the most important risk factor for endoscopic treatment in early gastric cancer (EGC) patients. We aimed to investigate the rate of LNM, the risk factors, and the prognosis of EGC patients with LMN. Methods. A total of 10,039 patients who underwent gastrectomy with lymphadenectomy were reviewed between January 2010 and December 2015 at Jiangsu Province Hospital in China. Among them, we identified 1004 (10%) EGCs. First, endoscopic and clinicopathological features related to LNM were analyzed, and then risk factors for LNM were identified using univariate and multivariate analysis. Finally, the short- and long-term outcomes were compared between the groups. Results. LNM occurred in 123 (12.3%) EGCs. Most of EGCs were male (n=720, 71.7%) and mean age was 59.65 ± 11.09 years. The rate of H. pylori infection was 78.0% (783/1004). LNM was significantly associated with age, sex, location, lesion size, macroscopic type, depth of invasion, differentiation type, histological morphology, lymphovascular invasion (LVI), and TMN stage. By multivariate analysis, significant independent risk factors for LNM in EGC were identified as following: male sex (OR 2.365, P=0.035), age ≦ 40 (OR 0.055, P=0.012), depressed type (OR 2.721, P=0.013), submucosa invasion (OR 2.987, P=0.032), LVI (OR 5.186, P=0.003), tumor located in corpora (OR 8.904, P=0.047), and in angle (OR 12.998, P=0.024). 86.5% were successfully followed up for 3 years. The overall 1- and 3-year survival rates in LNM group were 100% and 91.1%, respectively, and those with no LNM were 100% and 100%, respectively. Conclusion. EGCs were investigated in 10.0% of gastric cancer, which LNM occurred in 12.3% of EGC. Independent risk factors of LNM included male sex, age (>40), the depth of invasion, LVI, and tumor located in corpora or angle. The 3-year overall survival rate was greater in EGC patients without LNM.

scholarly journals Development of Nomograms for Predicting Lymph Node Metastasis and Distant Metastasis in Newly Diagnosed T1-2 Non-Small Cell Lung Cancer: A Population-Based Analysis

2021 ◽  
Vol 11 ◽  
Author(s):  
Yiming Qi ◽  
Shuangshuang Wu ◽  
Linghui Tao ◽  
Yunfu Shi ◽  
Wenjuan Yang ◽  
...  
Keyword(s):  
Risk Factors ◽  
Lung Cancer ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Small Cell Lung Cancer ◽  
Distant Metastasis ◽  
Tumor Size ◽  
Small Cell ◽  
Small Cell Lung ◽  
Node Metastasis

BackgroundFor different lymph node metastasis (LNM) and distant metastasis (DM), the diagnosis, treatment and prognosis of T1-2 non-small cell lung cancer (NSCLC) are different. It is essential to figure out the risk factors and establish prediction models related to LNM and DM.MethodsBased on the surveillance, epidemiology, and end results (SEER) database from 1973 to 2015, a total of 43,156 eligible T1-2 NSCLC patients were enrolled in the retrospective study. Logistic regression analysis was used to determine the risk factors of LNM and DM. Risk factors were applied to construct the nomograms of LNM and DM. The predictive nomograms were discriminated against and evaluated by Concordance index (C-index) and calibration plots, respectively. Decision curve analysis (DCAs) was accepted to measure the clinical application of the nomogram. Cumulative incidence function (CIF) was performed further to detect the prognostic role of LNM and DM in NSCLC-specific death (NCSD).ResultsEight factors (age at diagnosis, race, sex, histology, T-stage, marital status, tumor size, and grade) were significant in predicting LNM and nine factors (race, sex, histology, T-stage, N-stage, marital status, tumor size, grade, and laterality) were important in predicting DM(all, P&lt; 0.05). The calibration curves displayed that the prediction nomograms were effective and discriminative, of which the C-index were 0.723 and 0.808. The DCAs and clinical impact curves exhibited that the prediction nomograms were clinically effective.ConclusionsThe newly constructed nomograms can objectively and accurately predict LNM and DM in patients suffering from T1-2 NSCLC, which may help clinicians make individual clinical decisions before clinical management.

scholarly journals Indications of Lymph Node Metastasis and Survival Analysis in T1N+M0 Gastric Cancer: a Population-Based Study

2020 ◽  
Author(s):  
Peng Jin ◽  
Yang Li ◽  
Shuai Ma ◽  
Wenzhe Kang ◽  
Hao Liu ◽  
...  
Keyword(s):  
Risk Factors ◽  
Gastric Cancer ◽  
Survival Analysis ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Tumor Size ◽  
Multivariate Analyses ◽  
Invasion Depth ◽  
Node Metastasis ◽  
Definition Of

Abstract Background Since the definition of early gastric cancer (EGC) was first proposed in 1971, the treatment of gastric cancer with or without lymph node metastasis (LNM) has changed a lot. The present study aims to identify risk factors for LNM and prognosis, and to further evaluate the indications for adjuvant chemotherapy (AC) in T1N + M0 gastric cancer. Methods A total of 1291 patients with T1N + M0 gastric cancer were retrieved from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate analyses were performed to identify risk factors for LNM. The effect of LNM on overall survival (OS) and cancer-specific survival (CSS) was compared with patients grouped into T1N0-1 and T1N2-3, as the indications for AC. Results The rate of LNM was 19.52%. Multivariate analyses showed age, tumor size, invasion depth, and type of differentiation and retrieved LNs were associated with LNM (p < 0.05). Cox multivariate analyses indicated age, sex, tumor size, N stage were independent predictors of OS and CSS (p < 0.05), while race was indicator for OS (HR 0.866; 95%CI 0.750–0.999, p = 0.049), but not for CSS (HR 0.878; 95% CI 0.723–1.065, p = 0.187). In addition, survival analysis showed the proportion of patients in N+/N0 was better distributed than N0-1/N2-3b. There were statistically significant differences in OS and CSS between patients with and without chemotherapy in pT1N1M0 patients (p༜0.05). Conclusions Both tumor size and invasion depth are associated with LNM and prognosis. LNM is an important predictor of prognosis. pT1N + M0 may be appropriate candidates for AC. Currently, the treatment and prognosis of T1N0M0/T1N + M0 are completely different. An updated definition of EGC, taking into tumor size, invasion depth and LNM, may be more appropriate in an era of precision medicine.

Comparative study of preoperative prediction scores for lymph node metastasis in gastric and colon cancer patients

2020 ◽  
Author(s):  
Xiangjian Zheng ◽  
Xiaodong Chen ◽  
Min Li ◽  
Chunmeng Li ◽  
Xian Shen
Keyword(s):  
Risk Factors ◽  
Colon Cancer ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Cancer Patients ◽  
Serum Markers ◽  
Tumor Characteristics ◽  
Node Metastasis ◽  
Preoperative Prediction ◽  
Independent Risk Factors

Abstract Background: Surgery combined with chemo-radiotherapy is a recognized model for the treatment of gastric and colon cancers. Lymph node metastasis determines the patient's surgical or comprehensive treatment plan. This analytical study aims to compare preoperative prediction scores to better predict lymph node metastasis in gastric and colon cancer patients.Methods: This study comprised 768 patients, which included 312 patients with gastric cancer and 462 with colon cancer. Preoperative clinical tumor characteristics, serum markers, and immune indices were evaluated using single-factor analysis. Logistic analysis was designed to recognize independent predictors of lymph node metastasis in these patients. The independent risk factors were integrated into preoperative prediction scores, which were accurately assessed using receiver operating characteristic (ROC) curves.Results: Results showed that serum markers (CA125, hemoglobin, albumin), immune indices (S100, CD31, d2–40), and tumor characteristics (pathological type, size) were independent risk factors for lymph node metastasis in patients with gastric and colon cancer. The preoperative prediction scores reliably predicted lymph node metastasis in gastric and colon cancer patients with a higher area under the ROC curve (0.901). The area was 0.923 and 0.870 in gastric cancer and colon cancer, respectively. Based on the ROC curve, the ideal cutoff value of preoperative prediction scores to predict lymph node metastasis was established to be 287. Conclusion: The preoperative prediction scores is a useful indicator that can be applied to predict lymph node metastasis in gastric and colon cancer patients.

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