scholarly journals Development and Validation of Prognostic Nomogram for Patients With Small Intestinal Neuroendocrine Carcinoma

2020 ◽  
Author(s):  
Guangrong Lu ◽  
Limin Wu ◽  
Jiajia Li ◽  
Yushan Xia ◽  
Xuchao Zhang ◽  
...  
Keyword(s):  
Treatment Strategies ◽  
Staging System ◽  
Tumor Grade ◽  
Tnm Staging ◽  
Calibration Plot ◽  
Seer Database ◽  
Cancer Specific Survival ◽  
Discrimination Power ◽  
Tnm Staging System ◽  
Small Intestinal

Abstract Small intestinal neuroendocrine carcinomas (SI NECs) are diagnosed very rarely, and the prognosis is extremely poor due to the metastatic disease of most patients at the time of diagnosis. This study aimed to establish nomogram models for prognostic evaluation of SI NEC in both overall survival (OS) and cancer-specific survival (CSS). Patients diagnosed with SI NEC between 2010 and 2015 were retrieved from the Surveillance, Epidemiology, and End Results (SEER) database and further randomly divided into the training and validating cohorts at a ratio of 7:3. Univariate and multivariate cox analysis was conducted to determine significant variables for construction of nomogram. The performance of the nomogram models were then assessed by concordance index (C-index), calibration plot and the area receiver operating characteristic (ROC) curve (AUC). A total of 1110 patients were retrospectively selected from the SEER database. Multivariate models revealed that age, tumor grade, American Joint Committee for Cancer (AJCC) stage, surgery and chemotherapy all showed a significant association with OS and CSS. The discrimination of nomogram for OS prediction was superior to that of the 7th AJCC Tumor-Node-Metastasis (TNM) staging system (C-index = 0.798, 95% CI, 0.762 - 0.833 vs 0.623, 95% CI, 0.580 - 0.666, P < 0.001). Similar results were also observed in CSS nomogram. Well-corresponded calibration plots were noticed using the nomograms. The comparisons of AUC values showed that the established nomograms exhibited better discrimination power than 7th TNM staging system for OS and CSS prediction. In conclusion, we have successfully established novel nomograms for predicting OS and CSS in patients with SI NEC, which can assist clinicians in making predictions about individual patient survival and provide improved treatment strategies.

Establishment and verification of a nomogram for predicting survival in patients with small intestinal gastrointestinal stromal tumors

2021 ◽  
Author(s):  
Guangrong Lu ◽  
Jiajia Li ◽  
Limin Wu ◽  
Yuning Shi ◽  
Xuchao Zhang ◽  
...  
Keyword(s):  
Tnm Staging ◽  
Calibration Plot ◽  
Survival Prediction ◽  
Imatinib Treatment ◽  
Seer Database ◽  
Training Set ◽  
Cancer Specific Survival ◽  
Discrimination Power ◽  
Ajcc Stage ◽  
Small Intestinal

Background: This study aimed to develop and validate nomograms for predicting overall survival (OS) and cancer-specific survival (CSS) in small intestinal gastrointestinal stromal tumours (SI GISTs). Methods: Patients diagnosed with SI GISTs were retrieved from the Surveillance, Epidemiology, and End Results (SEER) database and further randomly divided into the training and validating cohorts. Univariate and multivariate cox analyses were conducted in the training set to determine independent prognostic factors to build nomograms for predicting 3- and 5-year OS and CSS. The performance of the nomograms was assessed by concordance index (C-index), calibration plot and the area receiver operating characteristic (ROC) curve (AUC). Results: A total of 776 patients with SI GISTs were retrospectively collected from the SEER database. OS nomogram was constructed based on age, surgery, imatinib treatment and AJCC stage, while CSS nomogram incorporated age, surgery, tumor grade and AJCC stage. In the training set, C-index for the OS nomogram was 0.773 [95% confidence intervals (95% CI): 0.722–0.824], CSS nomogram 0.806 (95% CI: 0.757–0.855). In internal validation cohort, the C-index for the OS nomogram was 0.741, while for the CSS nomogram 0.819. Well-corresponded calibration plots both in OS and CSS nomogram models were noticed. The comparisons of AUC values showed that the established nomograms exhibited superior discrimination power than 7th TNM staging system. Conclusion: Our nomogram can effectively predict 3- and 5-year OS and CSS in patients with SI GISTs, and its use can help improve the accuracy of personalized survival prediction and facilitate to provide constructive therapeutic suggestions.

scholarly journals A modified TNM staging system for non-metastatic colorectal cancer based on nomogram analysis of SEER database

BMC Cancer ◽  
2018 ◽  
Vol 18 (1) ◽  
Author(s):  
Xiangxing Kong ◽  
Jun Li ◽  
Yibo Cai ◽  
Yu Tian ◽  
Shengqiang Chi ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Metastatic Colorectal Cancer ◽  
Staging System ◽  
Tnm Staging ◽  
Seer Database ◽  
Tnm Staging System

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 A Model for the Prediction of Survival in Patients With Upper Tract Urothelial Carcinoma After Surgery

Dose-Response ◽  
2019 ◽  
Vol 17 (4) ◽  
pp. 155932581988287
Author(s):  
Guang-lin Zhang ◽  
Wei Zhou
Keyword(s):  
Urothelial Carcinoma ◽  
Predictive Ability ◽  
Staging System ◽  
Tnm Staging ◽  
Upper Tract Urothelial Carcinoma ◽  
Cancer Specific Survival ◽  
Upper Tract ◽  
Tnm Staging System ◽  
Prediction Of Survival ◽  
Validation Set

Objective: We aimed to formulate and validate prognostic nomograms that can be used to predict the prognosis of patients with upper tract urothelial carcinoma (UTUC). Methods: By consulting the Surveillance, Epidemiology, and End Results (SEER) database, we identified patients who were surgically treated for UTUC between 2004 and 2013. Variables were analyzed in both univariate and multivariate analyses. Nomograms were constructed based on independent prognostic factors. The prognostic nomogram models were established and validated internally and externally to determine their ability to predict the survival of patients with UTUC. Results: A total of 4990 patients were collected and enrolled in our analyses. Of these, 3327 patients were assigned to the training set and 1663 to the validation set. Nomograms were effectively applied to predict the 3- and 5-year survivals of patients with UTUC after surgery. The nomograms exhibited better accuracy for predicting overall survival (OS) and cancer-specific survival (CSS) than the tumor-node-metastasis (TNM) staging system and the SEER stage in both the training and validation sets. Calibration curves indicated that the nomograms exhibited high correlation to actual observed results for both OS and CSS. Conclusions: The nomogram models showed stronger predictive ability than the TNM staging system and the SEER stage. Precise estimates of the prognosis of UTUC might help doctors to make better treatment decisions.

scholarly journals Molecular characterization of breast cancer: a potential novel immune-related lncRNAs signature

2020 ◽  
Vol 18 (1) ◽  
Author(s):  
Jianguo Lai ◽  
Bo Chen ◽  
Guochun Zhang ◽  
Xuerui Li ◽  
Hsiaopei Mok ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Risk Stratification ◽  
Cox Regression ◽  
Predictive Accuracy ◽  
Expression Profiles ◽  
Treatment Strategies ◽  
Staging System ◽  
Tnm Staging ◽  
The Cancer Genome Atlas ◽  
Tnm Staging System

Abstract Background Accumulating evidence has demonstrated that immune-related lncRNAs (IRLs) are commonly aberrantly expressed in breast cancer (BC). Thus, we aimed to establish an IRL-based tool to improve prognosis prediction in BC patients. Methods We obtained IRL expression profiles in large BC cohorts (N = 911) from The Cancer Genome Atlas (TCGA) database. Then, in light of the correlation between each IRL and recurrence-free survival (RFS), we screened prognostic IRL signatures to construct a novel RFS nomogram via a Cox regression model. Subsequently, the performance of the IRL-based model was evaluated through discrimination, calibration ability, risk stratification ability and decision curve analysis (DCA). Results A total of 52 IRLs were obtained from TCGA. Based on multivariate Cox regression analyses, four IRLs (A1BG-AS1, AC004477.3, AC004585.1 and AC004854.2) and two risk parameters (tumor subtype and TNM stage) were utilized as independent indicators to develop a novel prognostic model. In terms of predictive accuracy, the IRL-based model was distinctly superior to the TNM staging system (AUC: 0.728 VS 0.673, P = 0.010). DCA indicated that our nomogram had favorable clinical practicability. In addition, risk stratification analysis showed that the IRL-based tool efficiently divided BC patients into high- and low-risk groups (P < 0.001). Conclusions A novel IRL-based model was constructed to predict the risk of 5-year RFS in BC. Our model can improve the predictive power of the TNM staging system and identify high-risk patients with tumor recurrence to implement more appropriate treatment strategies.

Independent validation of the 2002 UICC TNM staging system for papillary renal cell carcinoma in a multicenter cohort

2009 ◽  
Vol 27 (15_suppl) ◽  
pp. 5092-5092
Author(s):  
C. Wulfing ◽  
E. Herrmann ◽  
L. Trojan ◽  
A. Schrader ◽  
F. Becker ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Multivariate Analysis ◽  
Metastatic Disease ◽  
Renal Cell ◽  
Papillary Renal Cell Carcinoma ◽  
Staging System ◽  
Tnm Staging ◽  
Cancer Specific Survival ◽  
Tnm Staging System

5092 Background: Papillary renal cell carcinoma (pRCC) is the second most malignant histologic subtype in nephrectomy specimens. To date, the most recognized staging system to stratify renal cancer patients is the 2002 UICC TNM classification system. Its accuracy for predicting patient outcome for pRCC is unknown. Methods: From ten urologic institutions in Germany follow-up data on 675 patients with pRCC were collected. In most cases histologic slides were available and central pathologic review was performed. The Kaplan-Meier method was used to derive the cumulative cancer-specific survival. For multivariate analysis of prognostic factors, a Cox regression analysis was performed. Results: 498 (74.1%) patients had organ-confined tumor stages (≤pT2). Synchronous distant metastases in the entire group occurred in 58 (8.7%) patients and 69 (11.2%) others developed metastatic disease during follow-up. Cancer-specific survival (CSS) was significantly related to TNM stage and histologic grading in univariate as well as in multivariate analysis (all p < 0.0001). 5-year CSS in pT1b tumors (90.0%) was significantly shorter compared to pT1a tumors (98.3%) (p = 0.017). Patients with ≥pT3 were at high risk for metastases (50.6%), while metastatic disease associated with ≤pT2 tumors occurred in 7.8% (p < 0.0001). Once metastatic disease was present, prognosis was poor (5-year CSS: 7.2%). Age was associated with a worse prognosis in the subgroup of ≥pT3 tumors in univariate (p = 0.026), but not in multivariate analysis. Conclusions: The 2002 UICC TNM staging system is applicable for pRCC. Clinical and radiologic follow-ups should be offered in frequent intervals to patients with venous thrombus and/or locally advanced disease. The role of age remains unclear, but should not be underestimated at risk stratification after tumor resection. No significant financial relationships to disclose.

A proposal for a novel and simple TNM staging for gastric cancer.

2017 ◽  
Vol 35 (4_suppl) ◽  
pp. 21-21 ◽  
Author(s):  
Taeil Son ◽  
Jiyu Sun ◽  
Hyoung-Il Kim ◽  
Jong Won Kim ◽  
Jae-Ho Cheong ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Metastatic Lymph Node ◽  
Stage Iv ◽  
Staging System ◽  
Tnm Staging ◽  
Rank Test ◽  
Discrimination Power ◽  
Tnm Staging System ◽  
N Classification ◽  
T Classification

21 Background: Current TNM staging system for gastric cancer has controversies regarding N classification. We aimed to develop a simple and novel TNM staging system for gastric cancer by re-grouping N classification. Methods: We retrospectively reviewed 14260 patients treated for gastric cancer. To develop simple combinations of TNM staging with similar weighted value between T and N classification, N classification was restructured with different cutoffs. The optimal cutoffs for the number of metastatic lymph node which maximize the x2 statistic of log-rank test for survival differences among patients were selected. C-statistic was used to compare the discriminating performance of the proposed N classification with the current N classification in the TNM staging system. We performed validation with 2 external datasets from a hospital in Korea (n = 1500) and SEER (n = 11324). Results: We identified the new cutoffs of N classification as 1~4, 5~10, 11~24, and 25 or more for N1, N2, N3a, and N3b, respectively. We found survival of the new N3b classification was similar to M1, regardless of T classification. Thus, we stratified these groups of N3b and M1 disease as stage IV, simultaneously. Our new TNM staging had similar weighted value between T and N classification resulting in simple combinations. (Table) Survival curves of subgroups in the new TNM staging had higher x2 value than current staging system (x2: 8239 vs. 7023, respectively) and homogeneity among subgroups in the same stage increased. However, C-statistics (0.801, 95%CI: 0.795, 0.807) of new model showed similar discrimination power than that (0.797, 95%CI: 0.791, 0.803) in 7th TNM staging system. C-statistics were also similar in other hospital in Korea (0.805 vs. 0.802, respectively) and SEER database (0.709 vs. 0.706, respectively). Conclusions: This novel staging system by recalculating cut-offs of N classification provides exceptionally simple and practical way to stratify substages in TNM staging for gastric cancer. [Table: see text]

scholarly journals Evaluation of the Eighth Edition of the American Joint Committee on Cancer TNM Staging System for Gastric Cancer: An Analysis of 7371 Patients in the SEER Database

2019 ◽  
Vol 2019 ◽  
pp. 1-9 ◽  
Author(s):  
Long-Long Cao ◽  
Jun Lu ◽  
Ping Li ◽  
Jian-Wei Xie ◽  
Jia-Bin Wang ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Survival Rates ◽  
Stage Iv ◽  
Staging System ◽  
Tnm Staging ◽  
Stage Migration ◽  
Seer Database ◽  
Tnm System ◽  
American Joint Committee ◽  
Tnm Staging System

Objective. To investigate the validity of the 8thedition of the American Joint Committee on Cancer (AJCC) TNM staging system for gastric cancer.Methods. The clinicopathologic data of 7371 patients who were diagnosed with gastric cancer and had 16 or more involved lymph nodes (LNs) were retrieved from the Surveillance, Epidemiology, and End Results (SEER) database and retrospectively reviewed.Results. Stage migration occurred primarily during stage III between the 7thand 8thedition TNM staging systems. Stages IIIB and IIIC in the 7thedition staging system were divided in the 8thedition and had obvious differences in survival rates (bothP<0.001). The 8thedition TNM stages IIIC and IV showed similar survival rates (P=0.101). The prognosis of patients with T4aN3bM0 was not different from that of patients with TxNxM1 (P=0.433), while the prognosis of patients with T4bN3bM0 was significantly poorer than that of patients with TxNxM1 (P=0.008). A revised TNM system with both T4aN3bM0 and T4bN3bM0 incorporated into stage IV was proposed. Multivariable regression analysis showed that the revised TNM system, but not the 7thand 8theditions, was an independent factor for disease-specific survival (DSS) in the third step of the analysis. Further analyses revealed that the revised TNM system had superior discriminatory ability to the 8thedition staging system, which was also an improvement over the 7thedition staging system.Conclusion. The 8thedition of the AJCC TNM staging system is superior to the 7thedition for predicting the DSS rates of gastric cancer patients. However, for better prognostic stratification, it might be more suitable for T4aN3bM0/T4bN3bM0 to be incorporated into stage IV in the 8thedition TNM staging system.

scholarly journals Clinical Validation of the Prognostic Stage Groups of the Eighth-Edition TNM Staging for Medullary Thyroid Carcinoma

2018 ◽  
Vol 103 (12) ◽  
pp. 4609-4616 ◽  
Author(s):  
So Young Park ◽  
Yoon Young Cho ◽  
Hye In Kim ◽  
Jun-Ho Choe ◽  
Jung-Han Kim ◽  
...  
Keyword(s):  
Thyroid Carcinoma ◽  
Medullary Thyroid Carcinoma ◽  
Staging System ◽  
Predictive Performance ◽  
Tnm Staging ◽  
Cancer Specific Survival ◽  
Prognostic Performance ◽  
Medullary Thyroid ◽  
Tnm Staging System ◽  
Eighth Edition

Abstract Context Despite advances in thyroid cancer staging systems, considerable controversy about the current staging system for medullary thyroid carcinoma (MTC) continues. Objective We aimed to evaluate the prognostic performance of the current eighth edition of the American Joint Committee on Cancer (AJCC)/Union for International Cancer Control TNM staging system (TNM-8) and the alternative proposed prognostic stage groups based on recursive partitioning analysis (TNM-RPA). Design, Setting, and Patients We retrospectively analyzed 182 patients with MTC treated at a single tertiary Korean hospital between 1995 and 2015. Interventions and Main Outcome Measures Survival analysis was conducted according to TNM-8 and TNM-RPA. The area under the receiver-operating characteristic curve (AUC), the proportion of variation explained (PVE), and the Harrell concordance index (C-index) were used to evaluate predictive performance. Results Under TNM-8, only two (1.1%) patients were downstaged compared with the seventh edition of the AJCC TNM staging system (TNM-7). The AUC at 10 years, PVE, and C-index were 0.679, 8.7%, and 0.744 for TNM-7 and 0.681, 8.9%, and 0.747 for TNM-8, respectively. Under TNM-RPA, 104 (57.14%) patients were downstaged compared with TNM-8. TNM-RPA had better prognostic performance with respect to cancer-specific survival (AUC at 10 years, 0.750; PVE, 20.9%; C-index, 0.881). Conclusions The predictive performance of the revised TNM-8 in patients with MTC has not changed despite its modification from TNM-7. The proposed changes in TNM-RPA were statistically valid and may present a more reproducible system that better estimates cancer-specific survival of individual patients.

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