The tumor-log odds of positive lymph nodes-metastasis staging system, a new staging system for gastric cancer after D2 resection in China.

2012 ◽  
Vol 30 (15_suppl) ◽  
pp. e14655-e14655
Author(s):  
Rui-hua Xu ◽  
Miao-zhen Qiu
Keyword(s):  
Gastric Cancer ◽  
Lymph Nodes ◽  
Cox Regression ◽  
Staging System ◽  
Tnm Staging ◽  
Cut Points ◽  
Tnm System ◽  
Prognostic Assessment ◽  
Log Odds ◽  
Positive Lymph Nodes

e14655 Background: In this study, we established a hypothetical tumor-lodds-metastasis (TLM) and tumor-ratio-metastasis (TRM) staging system. Moreover we compared them with the 7th edition of American Joint Committee on Cancer tumor-nodes-metastasis (AJCC TNM) staging system in gastric cancer patients after D2 resection. Methods: A total of 1000 gastric carcinoma patients receiving treatment in our center were selected for the analysis. Finally, 730 patients who received D2 resection were retrospectively studied. Patients were staged using the TLM, TRM and the 7th edition AJCC TNM system. Survival analysis was performed with a Cox regression model. We used two parameters to compare the TNM, TRM and TLM staging system, the -2log likelihood and the hazard ratio. Results: The cut points of lymph node ratio (LNR) were set as 0, 0-0.3, 0.3-0.6, 0.6-1.0. And for the log odds of positive lymph nodes (LODDS), the cut points were established as≤-0.5, -0.5-0, 0-0.5, >0.5. There were significant differences in survival among patients in different LODDS classifications for each pN or LNR groups. When stratified by the LODDS classifications, the prognosis was highly homologous between those in the according pN or LNR classifications. Multivariate analysis shown that TLM staging system was better than the TRM or TNM system for the prognostic evaluation. Conclusions: The TLM systems was superior to the TRM or TNM system for prognostic assessment of gastric adenocarcinoma patients after D2 resection.

scholarly journals The Tumor-Log Odds of Positive Lymph Nodes-Metastasis Staging System, a Promising New Staging System for Gastric Cancer after D2 Resection in China

PLoS ONE ◽  
2012 ◽  
Vol 7 (2) ◽  
pp. e31736 ◽  
Author(s):  
Miao-zhen Qiu ◽  
Hui-juan Qiu ◽  
Zhi-qiang Wang ◽  
Chao Ren ◽  
De-shen Wang ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Lymph Nodes ◽  
Staging System ◽  
Lymph Nodes Metastasis ◽  
System A ◽  
Log Odds ◽  
Positive Lymph Nodes

scholarly journals A Nomogram Based on the Log Odds of Positive Lymph Nodes Predicts the Prognosis of Patients With Distal Cholangiocarcinoma After Surgery

2021 ◽  
Vol 8 ◽  
Author(s):  
Rui Li ◽  
Zhenhua Lu ◽  
Zhen Sun ◽  
Xiaolei Shi ◽  
Zhe Li ◽  
...  
Keyword(s):  
Risk Factors ◽  
Lymph Node ◽  
Lymph Nodes ◽  
Staging System ◽  
Tnm Staging ◽  
Distal Cholangiocarcinoma ◽  
Tnm Staging System ◽  
Log Odds ◽  
Independent Risk Factors ◽  
Positive Lymph Nodes

Background: Lymph node (LN) metastasis is considered one of the most important risk factors affecting the prognosis of distal cholangiocarcinoma (DCC). This study aimed to demonstrate the superiority of log odds of positive lymph nodes (LODDS) compared with other LN stages, and to establish a novel prognostic nomogram to predict the cancer-specific survival (CSS) of DCC.Methods: From the Surveillance, Epidemiology and End Results (SEER) database, the data of 676 patients after DCC radical operation were screened, and patients were randomly divided into training (n = 474) and validation sets (n = 474). The prognostic evaluation performance of the LODDS and American Joint Commission on Cancer (AJCC) N stage and lymph node ratio (LNR) were compared using the Akaike information criteria, receiver operating characteristic area under the curve (AUC), and C-index. Multivariate Cox analysis was used to screen independent risk factors, and a LODDS-based nomogram prognostic staging model was established. The nomogram's precision was verified by C-index, calibration curves, and AUC, and the results were compared with those of the AJCC TNM staging system.Results:Compared with the other two stages of LN metastasis, LODDS was most effective in predicting CSS in patients with DCC. Multivariate analysis proved that LODDS, histologic grade, SEER historic stage, and tumor size were independent risk factors for DCC. The C-index of the nomogram, based on the above factors, in the validation set was 0.663. The 1-, 3-, and 5-y AUCs were 0.735, 0.679, and 0.745, respectively. Its good performance was also verified by calibration curves. In addition, the C-index and Kaplan-Meier analysis showed that the nomogram performed better than the AJCC TNM staging system.Conclusion:For postoperative patients with DCC, the LODDS stage yielded better prognostic efficiency than the AJCC N and LNR stages. Compared with the AJCC TNM staging system, the nomogram, based on the LODDS, demonstrated superior performance.

Rhabdomyosarcoma: the Stanford experience using a TNM staging system.

1986 ◽  
Vol 4 (3) ◽  
pp. 370-378 ◽  
Author(s):  
T J Pedrick ◽  
S S Donaldson ◽  
R S Cox
Keyword(s):  
Lymph Nodes ◽  
Staging System ◽  
Tnm Staging ◽  
Actuarial Survival ◽  
Entire Study ◽  
Histologic Subtype ◽  
Tnm System ◽  
T Stage ◽  
Tnm Staging System ◽  
Extent Of Disease

Seventy-four patients with rhabdomyosarcoma were initially staged according to the Intergroup Rhabdomyosarcoma Study (IRS) grouping classification and then retrospectively using a TNM staging system based on the initial clinical extent of disease. The TNM system includes T1, tumor confined to site or organ of origin; T2, regional extension beyond the site of origin; N0, normal lymph nodes; N1, lymph nodes containing tumor; M0, no evidence of metastases; and M1, distant metastases. All patients received combination chemotherapy, and more than 90% received radiation therapy as part of their initial treatment program with curative intent. Fifty-three of 74 patients (72%) were group III according to the IRS system, indicating unresectable or gross residual tumor. A more uniform distribution was achieved using the TNM system. Freedom from relapse (FFR) was 43% and the actuarial survival rate was 47% for the entire study group at 10 years. All but one relapse occurred within 3 years of initial diagnosis, and only three of 38 relapsed patients were salvaged. All TNM stage I patients are surviving disease free. Among patients having stages II, III, and IV disease by the TNM system, FFR was 53%, 26%, and 11%, and the survival rates were 47%, 36%, and 33%, respectively. Thirty-two of 74 patients (43%) had evidence of lymph node involvement at presentation, and 28 (88%) of these had primary lesions that extended beyond the site of origin (T2 primary). Histologic subtype and primary site had little impact on outcome in a multivariate analysis, and T stage was identified as the single most significant covariate correlated with survival; a model composed of both T stage and M stage was the best one for predicting relapse. The presented data support a study using a prospectively assigned TNM staging system based on the initial clinical extent of disease for use in future therapeutic trials.

scholarly journals Residual Volume of Lymph Nodes During Chemoradiotherapy Based Nomogram to Predict Survival of Nasopharyngeal Carcinoma Patient Receiving Induction Chemotherapy

2021 ◽  
Vol 11 ◽  
Author(s):  
Yan Li ◽  
Jian Zang ◽  
Jingyi Liu ◽  
Shanquan Luo ◽  
Jianhua Wang ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Nasopharyngeal Carcinoma ◽  
Lymph Nodes ◽  
Induction Chemotherapy ◽  
Cox Regression ◽  
Staging System ◽  
Tnm Staging ◽  
Residual Volume ◽  
Discriminative Ability ◽  
Cox Regression Analysis

PurposeTo accurately stratify nasopharyngeal carcinoma (NPC) patients who were benefit from induction chemotherapy (IC) followed by chemoradiotherapy (CCRT), we established residual volume of lymph nodes during chemoradiotherapy based nomogram to predict survival for NPC patients.MethodsCox regression analysis were used to evaluate predictive effects of tumor volume parameters. Multivariate Cox regression analysis was used to identify the prognostic factors, and nomogram models were developed to predict survival of NPC patients receiving IC followed by CCRT.ResultsCompared with other tumor volumetric parameters, midRT GTVnd was the best predictive factor for OS (HR: 1.043, 95%CI: 1.031-1.055), PFS (HR: 1.040, 95%CI: 1.030- 1.051), and DMFS (HR: 1.046, 95%CI: 1.034 – 1.059) according to the HR of Cox regression analysis. Based on multivariate analysis, three nomograms included midRT GTVnd were constructed to predict 4-year survival. The C-index of nomograms for each survival endpoints were as follow (training cohort vs. validation cohort): 0.746 vs. 0.731 for OS; 0.747 vs. 0.735 for PFS; 0.768 vs. 0.729 for DMFS, respectively. AUC showed a good discriminative ability. Calibration curves demonstrated a consistence between actual results and predictions. Decision curve analysis (DCA) showed that the nomograms had better clinical predictive effects than current TNM staging system.ConclusionWe identified the best volumetric indicator associated with prognosis was the residual volume of lymph nodes at the fourth week of chemoradiotherapy for patients receiving IC followed by CCRT. We developed and validated three nomograms to predict specific probability of 4-year OS, PFS and DMFS for NPC patient receiving IC followed by CCRT.

scholarly journals A nomogram based on Aspartate Aminotransferase/Alanine Aminotransferase (AST/ALT) ratio after surgery to predict the prognostic value in patients with gastric cancer

2020 ◽  
Author(s):  
Linfang Li ◽  
Shan Xing ◽  
Ning Xue ◽  
Miantao Wu ◽  
Yaqing Liang ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Aspartate Aminotransferase ◽  
Alanine Aminotransferase ◽  
Cox Regression ◽  
Staging System ◽  
Tnm Staging ◽  
Calibration Plot ◽  
Study Cohort ◽  
Tnm Staging System ◽  
Resectable Gastric Cancer

Abstract Background This study aimed to develop an effective nomogram for predicting overall survival (OS) in surgically treated gastric cancer. Methods We retrospectively evaluated 190 gastric cancer in this study. Cox regression analyses were performed to identify significant prognostic factors for OS in patients with resectable gastric cancer. The predictive accuracy of nomogram was assessed by calibration plot, concordance index (C-index) and decision curve, and then were compared with the traditional TNM staging system. Based on the total points (TPS) by nomogram, we further divided patients into different risk groups. Results On multivariate analysis of the 190 cohort, independent factors for survival were age, clinical stage and Aspartate Aminotransferase/Alanine Aminotransferase (SLR), which were entered into the nomogram. The calibration curve for the probability of OS showed that the nomogram-based predictions were in good agreement with actual observations. And the C-index of the established nomogram for predicting OS had a superior discrimination power compared with the TNM staging system [0.768 (95% CI: 0.725-0.810) vs 0.730 (95% CI: 0.688-0.772), p < 0.05]. Decision curve also demonstrated that the nomogram was better than TNM staging system. Based on the TPS of the nomogram, we further subdivided the study cohort into 3 groups: low risk (TPS ≤ 158), middle risk (158 < TPS ≤ 188), high risk (TPS > 188), the differences of OS rate were significant in the groups. Conclusions The established nomogram resulted in more accurate prognostic prediction for individual patient with resectable gastric cancer.

scholarly journals Nomogram Based on Log Odds of Positive Lymph Nodes Predicting Cancer-Specific Survival in Patients With T3 and T4 Gallbladder Cancer After Radical Resection

2021 ◽  
Vol 8 ◽  
Author(s):  
Chen Yuan ◽  
Qiaomeng Tao ◽  
Jian Wang ◽  
Kai Wang ◽  
Shubing Zou ◽  
...  
Keyword(s):  
Lymph Nodes ◽  
Gallbladder Cancer ◽  
Cox Regression ◽  
External Validation ◽  
Radical Resection ◽  
Cancer Specific Survival ◽  
Clinical Applicability ◽  
Log Odds ◽  
Advanced Gallbladder Cancer ◽  
Positive Lymph Nodes

Background: The aim of this study based on log odds of positive lymph nodes (LODDS) is to develop and validate an effective prognostic nomogram for patients with T3 and T4 gallbladder cancer (GBC) after resection.Patients and Methods: A total of 728 T3 and T4 gallbladder cancer patients after resection from the Surveillance, Epidemiology, and End Results (SEER) database, randomly divided into training cohort and validation cohort according to 7:3. Another 128 patients from The Second Affiliated Hospital of Nanchang University for external validation. The nomograms were built by the Cox regression model and the Fine and Grey's model. Concordance index (C-index), calibration curve and the area under receiver operating characteristic (ROC) curve (AUC) were used to evaluate the nomogram and internal verification. The decision curve analysis (DCA) was used to measure clinical applicability.Result: LODDS was independent prognostic predictor for overall survival (OS) and cancer-specific survival (CSS), and established the nomograms on this basis. The nomogram we have established has a good evaluation effect, with a C-index of 0.719 (95%CI, 0.707–0.731) for OS and 0.747 (95%CI, 0.733–0.760) for CSS. The calibration curves of OS and CSS both showed good calibration capability, and the AUC for predicting 1-, 2-, and 3-year 0.858, 0.848 were and 0.811 for OS, and 0.794, 0.793, and 0.750 for CSS. The DCA of nomograms both showed good clinical applicability.Conclusion: The nomogram can provide effective OS and CSS prediction for patients with advanced gallbladder cancer after surgery.

scholarly journals Nomogram to predict overall survival based on the log odds of positive lymph nodes for patients with endometrial carcinosarcoma after surgery

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Linzhi Gao ◽  
Jun Lyu ◽  
Xiaoya Luo ◽  
Dong Zhang ◽  
Guifang Jiang ◽  
...  
Keyword(s):  
Overall Survival ◽  
Lymph Nodes ◽  
Prediction Model ◽  
Classification System ◽  
Staging System ◽  
Seer Database ◽  
Figo Staging ◽  
Log Odds ◽  
Positive Lymph Nodes ◽  
Better Than

Abstract Purpose Aims to compare the prognostic performance of the number of positive lymph nodes (PLNN), lymph node ratio (LNR) and log odds of metastatic lymph nodes (LODDS) and establish a prognostic nomogram to predict overall survival (OS) rate for patients with endometrial carcinosarcoma (ECS). Methods Patients were retrospectively obtained from Surveillance, Epidemiology and End Results (SEER) database from 2004 to 2015. The prognostic value of PLNN, LNR and LODDS were assessed. A prediction model for OS was established based on univariate and multivariate analysis of clinical and demographic characteristics of ECS patients. The clinical practical usefulness of the prediction model was valued by decision curve analysis (DCA) through quantifying its net benefits. Results The OS prediction accuracy of LODDS for ECS is better than that of PLNN and LNR. Five factors, age, tumor size, 2009 FIGO, LODDS and peritoneal cytology, were independent prognostic factors of OS. The C-index of the nomogram was 0.743 in the training cohort. The AUCs were 0.740, 0.682 and 0.660 for predicting 1-, 3- and 5-year OS, respectively. The calibration plots and DCA showed good clinical applicability of the nomogram, which is better than 2009 FIGO staging system. These results were verified in the validation cohort. A risk classification system was built that could classify ECS patients into three risk groups. The Kaplan-Meier curves showed that OS in the different groups was accurately differentiated by the risk classification system and performed much better than FIGO 2009. Conclusion Our results indicated that LODDS was an independent prognostic indicator for ECS patients, with better predictive efficiency than PLNN and LNR. A novel prognostic nomogram for predicting the OS rate of ECS patients was established based on the population in the SEER database. Our nomogram based on LODDS has a more accurate and convenient value for predicting the OS of ECS patients than the FIGO staging system alone.

scholarly journals A novel pN3 gastric cancer staging system with superior prognostic utility based upon the examination of over 31 lymph nodes: a propensity score-matching analysis

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Qiantao Hu ◽  
Siwei Pan ◽  
Zijun Guo
Keyword(s):  
Gastric Cancer ◽  
Propensity Score ◽  
Lymph Nodes ◽  
Propensity Score Matching ◽  
Staging System ◽  
Tnm Staging ◽  
Survival Outcomes ◽  
The Novel ◽  
Risk Of Death ◽  
Tnm Staging System

Abstract Background Individuals with pN3 gastric cancer (GC) account for a large proportion of pN + GC, and exhibit poor survival outcomes. The pN3 stage is defined based upon the number of metastatic lymph nodes (mLNs), but the subclassification of pN3 patients based upon the number of examined LNs (eLNs) is rarely performed. Methods In total, 2894 pTxN3M0 GC patients in the Surveillance, Epidemiology, and End Results database that had undergone surgery from 2000 to 2016 were selected for analysis. The X-tile software was used to select the optimal cutoff values. Cox proportional regression analyses were used to evaluated hazard ratios corresponding to the risk of death. Selection bias was minimized via propensity score matching (PSM). Results As the number of eLNs rose, the risk of death for patients trended downwards. Survival analyses indicated that patients with ≤ 31 eLNs exhibited significantly poorer survival outcomes as compared to patients with > 31 eLNs (5-year OS: 18.4% vs. 24.7%), and this result remained significant when analyzing 857 pairs of patients following PSM analysis. Significant differences in prognosis were additionally observed when comparing pN3a and pN3b patients with ≤ 31 or > 31 eLNs under pT3/4a stage. For pT4b stage, pN3a patients with > 31 eLNs also exhibited a better prognosis than other patients. The novel TNM staging system designed exhibited excellent utility as a tool for the prognostic evaluation of this GC patient population. Conclusions These results suggest that in pN3 GC, a minimum of 32 LNs should be examined. The novel TNM staging system for pN3 patients described herein, which was developed based upon the number of eLNs, may thus be of value in clinical settings.

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