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      Nomogram individually predicts the overall survival of patients with gastroenteropancreatic neuroendocrine neoplasms

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          Abstract

          Background:

          The current study aimed to establish a novel nomogram to predict the overall survival of individual Chinese patients with gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs). Furthermore, this study sought to externally validate this nomogram using the Surveillance, Epidemiology, and End Results (SEER) database.

          Methods:

          The records of 1183 patients with GEP-NENs treated at five high-capacity institutions in China between 2005 and 2015 were retrospectively analysed. In addition, 10 236 GEP-NEN cases from the SEER database were included as an external validation set.

          Results:

          A multivariate analysis using Cox proportional hazards (PHs) regression was performed, and a nomogram was constructed. Discrimination, calibration, and external validation were performed using the SEER data set. The multivariate Cox model indicated that age, tumour size, differentiation, lymph node metastases, and distant metastases were independent covariates associated with survival. With respect to the training set, the nomogram exhibited better discrimination power than TNM classification (Harrell’s concordance index (C-index): 0.837 vs 0.784, P=0.006). Discrimination was also excellent and superior to that of TNM classification for the SEER-based validation set (C-index: 0.808 vs 0.717, P<0.001). The calibrated nomogram predicted a survival rate that closely corresponded to the actual survival rate.

          Conclusions:

          We developed a nomogram that predicted the 3- and 5-year overall survival rates of patients with GEP-NENs. Validation revealed excellent discrimination and calibration for this nomogram, suggesting that it exhibits satisfactory clinical utility that might improve individualised predictions of survival risks and lead to the creation of additional clinical therapies.

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          Most cited references14

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          Nomogram predicting long-term survival after d2 gastrectomy for gastric cancer.

          The aim of this study was to combine clinicopathologic variables associated with overall survival after gastric resection with D2 lymphadenectomy (D2 gastrectomy) for gastric cancer into a prediction nomogram. We retrospectively analyzed 7,954 patients who underwent D2 gastrectomy for gastric cancer at Seoul National University Hospital (SNUH) in Seoul, Korea. Two thirds of the patients were randomly assigned to the training set (n = 5,300), and one third were assigned to the validation set (n = 2,654). Multivariate analysis by Cox proportional hazards regression was performed using the training set, and the nomogram was constructed. Discrimination and calibration were performed using the SNUH validation set. Additional external validation was performed using the data set (n = 2,500) from Cancer Institute Ariake Hospital (CIAH) in Tokyo, Japan. The multivariate Cox model identified age at diagnosis, sex, location, depth of invasion, number of metastatic lymph nodes, and number of examined lymph nodes as covariates associated with survival. In the SNUH validation set, the nomogram exhibited superior discrimination power compared with the seventh American Joint Committee on Cancer TNM classification (Harrell's C-index, 0.78 v 0.69, respectively; P < .001). Calibration of the nomogram predicted survival corresponding closely with the actual survival. In the CIAH validation set, discrimination was good (C-index, 0.79), and the predicted survival was within a 10% margin of ideal nomogram. We developed a nomogram predicting 5- and 10-year overall survival after D2 gastrectomy for gastric cancer. Validation using the SNUH and CIAH data sets revealed good discrimination and calibration, suggesting good clinical utility. The nomogram improved individualized predictions of survival.
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            Individualized prediction of colon cancer recurrence using a nomogram.

            Estimates of recurrence after curative colon cancer surgery are integral to patient care, forming the basis of cancer staging and treatment planning. The categoric staging system of the American Joint Committee on Cancer (AJCC) is commonly used to convey risk by grouping patients based on anatomic elements. Although easy to implement, there remains significant heterogeneity within each stage grouping. In the era of multimodality treatment, a more refined tool is needed to predict recurrence. An institutional database of 1,320 patients with nonmetastatic colon cancer was used to develop a nomogram to estimate recurrence after curative surgery. Prognostic factors were assessed with multivariable analysis using Cox regression, whereas nonlinear continuous variables were modeled with cubic splines. The model was internally validated with bootstrapping, and performance was assessed by concordance index and a calibration curve. The colon cancer recurrence nomogram predicted relapse with a concordance index of 0.77, improving on the stratification provided by either the AJCC fifth or sixth staging scheme. Factors in the model included patient age, tumor location, preoperative carcinoembryonic antigen, T stage, numbers of positive and negative lymph nodes, lymphovascular invasion, perineural invasion, and use of postoperative chemotherapy. Using common clinicopathologic factors, the recurrence nomogram is better able to account for tumor and patient heterogeneity, thereby providing a more individualized outcome prognostication than that afforded by the AJCC categoric system. By identifying both the high- and low-risk patients within any particular stage, the nomogram is expected to aid in treatment planning and future trial design.
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              Prognostic nomogram and index for overall survival in previously untreated patients with chronic lymphocytic leukemia.

              The clinical course for patients with chronic lymphocytic leukemia is extremely heterogeneous. The Rai and Binet staging systems have been used to risk-stratify patients; most patients present with early-stage disease. We evaluated a group of previously untreated patients with chronic lymphocytic leukemia (CLL) at initial presentation to University of Texas M. D. Anderson Cancer Center to identify independent characteristics that predict for overall survival. Clinical and routine laboratory characteristics for 1674 previously untreated patients who presented for evaluation of CLL from 1981 to 2004 were included. Univariate and multivariate analyses identified several patient characteristics at presentation that predicted for overall survival in previously untreated patients with CLL. A multivariate Cox proportional hazards model was developed, including the following independent characteristics: age, beta-2 microglobulin, absolute lymphocyte count, sex, Rai stage, and number of involved lymph node groups. Inclusion of patients from a single institution and the proportion of patients younger than 65 years may limit this model. A weighted prognostic model, or nomogram, predictive for overall survival was constructed using these 6 characteristics for 5- and 10-year survival probability and estimated median survival time. This prognostic model may help patients and clinicians in clinical decision making as well as in clinical research and clinical trial design.
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                Author and article information

                Journal
                Br J Cancer
                Br. J. Cancer
                British Journal of Cancer
                Nature Publishing Group
                0007-0920
                1532-1827
                07 November 2017
                26 September 2017
                : 117
                : 10
                : 1544-1550
                Affiliations
                [1 ]Department of Gastric Surgery, Sun Yat-sen University Cancer Center , Guangzhou, People’s Republic of China
                [2 ]State Key Laboratory of Oncology in South China , Guangzhou, People’s Republic of China
                [3 ]Collaborative Innovation Center for Cancer Medicine , Guangzhou, People’s Republic of China
                [4 ]Department of General Surgery, Guangdong General Hospital , Guangzhou, People’s Republic of China
                [5 ]Guangdong Academy of Medical Science , Guangzhou, People’s Republic of China
                [6 ]Department of Biliopancreatic Surgery, Sun Yat-sen Memorial Hospital of Sun Yat-sen University , Guangzhou, People’s Republic of China
                [7 ]Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation , Guangzhou, People’s Republic of China
                [8 ]Department of Gastroenterology, First Affiliated Hospital of Sun Yat-sen University , Guangzhou, People’s Republic of China
                [9 ]Department of Gastrointestinal Surgery, Sun Yat-sen Memorial Hospital of Sun Yat-sen University , Guangzhou, People’s Republic of China
                [10 ]Department of Gastroenterology, Nanfang Hospital of Southern Medical University , Guangzhou, People’s Republic of China
                [11 ]Guangdong Provincial Key Laboratory of Gastroenterology, Guangzhou, People’s Republic of China
                [12 ]Department of Pathology, Sun Yat-sen University Cancer Center , Guangzhou, People’s Republic of China
                [13 ]Department of Colorectal Surgery, Sun Yat-sen University Cancer Center , Guangzhou, People’s Republic of China
                [14 ]Department of Hepatopancreatobiliary Surgery, Sun Yat-sen University Cancer Center , Guangzhou, People’s Republic of China
                Author notes
                [15]

                These authors contributed equally to this work.

                [16]

                These authors contributed equally to this work.

                Article
                bjc2017315
                10.1038/bjc.2017.315
                5680463
                28949958
                80d37ef2-acb5-4a30-91f0-d006b2f18a43
                Copyright © 2017 Cancer Research UK

                From twelve months after its original publication, this work is licensed under the Creative Commons Attribution-NonCommercial-Share Alike 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/4.0/

                History
                : 11 May 2017
                : 06 August 2017
                : 18 August 2017
                Categories
                Molecular Diagnostics

                Oncology & Radiotherapy
                nomogram,gastroenteropancreatic neuroendocrine neoplasms,predict,overall survival

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