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      Nomograms forecasting long‐term overall and cancer‐specific survival of patients with oral squamous cell carcinoma

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          Abstract

          Our aim was to establish a “nomogram” model to forecast the overall survival ( OS) and cancer‐specific survival ( CSS) of oral squamous cell carcinoma ( OSCC) patients. The clinicopathological data for the 10,533 OSCC patients were collected from the Surveillance, Epidemiology and End Results ( SEER) database. We used a credible random split‐sample method to divide 10,533 patients into two cohorts: 7046 patients in the modeling cohort and 3487 patients in the external validation cohort (split‐ratio = 2:1). The median follow‐up period was 32 months (1–119 months). We developed nomograms to predict 5‐ and 8‐year OS and CSS of OSCC patients with a Cox proportional hazards model. The precision of the nomograms was assessed by the concordance index (C‐index) and calibration curves through internal and external validation. The C‐indexes of internal validation regarding 5‐ and 8‐year OS and CSS were 0.762 and 0.783, respectively. In addition, the external validation's C‐indexes were 0.772 and 0.800. Based on a large‐sample analysis targeting the SEER database, we established two nomograms to predict long‐term OS and CSS for OSCC patients successfully, which can assist surgeons in developing a more effective therapeutic regimen and conducting personalized prognostic evaluations.

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          Head and Neck cancers-major changes in the American Joint Committee on cancer eighth edition cancer staging manual.

          Answer questions and earn CME/CNE The recently released eighth edition of the American Joint Committee on Cancer (AJCC) Staging Manual, Head and Neck Section, introduces significant modifications from the prior seventh edition. This article details several of the most significant modifications, and the rationale for the revisions, to alert the reader to evolution of the field. The most significant update creates a separate staging algorithm for high-risk human papillomavirus-associated cancer of the oropharynx, distinguishing it from oropharyngeal cancer with other causes. Other modifications include: the reorganizing of skin cancer (other than melanoma and Merkel cell carcinoma) from a general chapter for the entire body to a head and neck-specific cutaneous malignancies chapter; division of cancer of the pharynx into 3 separate chapters; changes to the tumor (T) categories for oral cavity, skin, and nasopharynx; and the addition of extranodal cancer extension to lymph node category (N) in all but the viral-related cancers and mucosal melanoma. The Head and Neck Task Force worked with colleagues around the world to derive a staging system that reflects ongoing changes in head and neck oncology; it remains user friendly and consistent with the traditional tumor, lymph node, metastasis (TNM) staging paradigm. CA Cancer J Clin 2017;67:122-137. © 2017 American Cancer Society.
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            Assessing the generalizability of prognostic information.

            Physicians are often asked to make prognostic assessments but often worry that their assessments will prove inaccurate. Prognostic systems were developed to enhance the accuracy of such assessments. This paper describes an approach for evaluating prognostic systems based on the accuracy (calibration and discrimination) and generalizability (reproducibility and transportability) of the system's predictions. Reproducibility is the ability to produce accurate predictions among patients not included in the development of the system but from the same population. Transportability is the ability to produce accurate predictions among patients drawn from a different but plausibly related population. On the basis of the observation that the generalizability of a prognostic system is commonly limited to a single historical period, geographic location, methodologic approach, disease spectrum, or follow-up interval, we describe a working hierarchy of the cumulative generalizability of prognostic systems. This approach is illustrated in a structured review of the Dukes and Jass staging systems for colon and rectal cancer and applied to a young man with colon cancer. Because it treats the development of the system as a "black box" and evaluates only the performance of the predictions, the approach can be applied to any system that generates predicted probabilities. Although the Dukes and Jass staging systems are discrete, the approach can also be applied to systems that generate continuous predictions and, with some modification, to systems that predict over multiple time periods. Like any scientific hypothesis, the generalizability of a prognostic system is established by being tested and being found accurate across increasingly diverse settings. The more numerous and diverse the settings in which the system is tested and found accurate, the more likely it will generalize to an untested setting.
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              Events per variable (EPV) and the relative performance of different strategies for estimating the out-of-sample validity of logistic regression models

              We conducted an extensive set of empirical analyses to examine the effect of the number of events per variable (EPV) on the relative performance of three different methods for assessing the predictive accuracy of a logistic regression model: apparent performance in the analysis sample, split-sample validation, and optimism correction using bootstrap methods. Using a single dataset of patients hospitalized with heart failure, we compared the estimates of discriminatory performance from these methods to those for a very large independent validation sample arising from the same population. As anticipated, the apparent performance was optimistically biased, with the degree of optimism diminishing as the number of events per variable increased. Differences between the bootstrap-corrected approach and the use of an independent validation sample were minimal once the number of events per variable was at least 20. Split-sample assessment resulted in too pessimistic and highly uncertain estimates of model performance. Apparent performance estimates had lower mean squared error compared to split-sample estimates, but the lowest mean squared error was obtained by bootstrap-corrected optimism estimates. For bias, variance, and mean squared error of the performance estimates, the penalty incurred by using split-sample validation was equivalent to reducing the sample size by a proportion equivalent to the proportion of the sample that was withheld for model validation. In conclusion, split-sample validation is inefficient and apparent performance is too optimistic for internal validation of regression-based prediction models. Modern validation methods, such as bootstrap-based optimism correction, are preferable. While these findings may be unsurprising to many statisticians, the results of the current study reinforce what should be considered good statistical practice in the development and validation of clinical prediction models.
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                Author and article information

                Contributors
                13501258802@139.com
                weijianhuaprof@163.com
                Journal
                Cancer Med
                Cancer Med
                10.1002/(ISSN)2045-7634
                CAM4
                Cancer Medicine
                John Wiley and Sons Inc. (Hoboken )
                2045-7634
                07 March 2018
                April 2018
                : 7
                : 4 ( doiID: 10.1002/cam4.2018.7.issue-4 )
                : 943-952
                Affiliations
                [ 1 ] Department of stomatology The 316th Hospital of Chinese People's Liberation Army No. A2 Niangniangfu, Xiangshan Road Beijing Haidian District China
                [ 2 ] State Key Laboratory of Military Stomatology & National Clinical Research Center for Oral Diseases & Shaanxi Clinical Research Center for Oral Diseases Department of Oral and Maxillofacial Surgery School of Stomatology The Fourth Military Medical University Xi'an China
                [ 3 ] State Key Laboratory of Military Stomatology & National Clinical Research Center for Oral Diseases & Shaanxi Engineering Research Center for Dental Materials and Advanced Manufacture Department of Anesthesiology School of Stomatology The Fourth Military Medical University Xi'an China
                [ 4 ] State Key Laboratory of Military Stomatology & National Clinical Research Center for Oral Diseases & Shaanxi International Joint Research Center for Oral Diseases Department of Oral Histology and Pathology The Fourth Military Medical University Xi'an China
                [ 5 ] Department of oral and maxillofacial surgery The Second Hospital of Hebei Medical University Shijiazhuang China
                Author notes
                [*] [* ] Correspondence

                Xun Chen, Department of stomatology, The 316th Hospital of Chinese People's Liberation Army, No. A2 Niangniangfu, Xiangshan Road, Haidian District, Beijing, China. Tel: 010‐66320235; Fax: 010‐66778362; E‐mail: 13501258802@ 123456139.com

                Jianhua Wei, State Key Laboratory of Military Stomatology & National Clinical Research Center for Oral Diseases & Shaanxi Clinical Research Center for Oral Diseases, Department of Oral and Maxillofacial Surgery, School of Stomatology, The Fourth Military Medical University, No.145 West Changle Road, Xi'an, 710032, Shaanxi, China. Tel: 029‐84772502; Fax: 029‐84776097; E‐mail: weijianhuaprof@ 123456163.com

                Author information
                http://orcid.org/0000-0001-6505-4008
                Article
                CAM41216
                10.1002/cam4.1216
                5911576
                29512294
                0c9ebb56-8355-4e89-8e40-0e6ce6dc50d6
                © 2017 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 01 June 2017
                : 17 August 2017
                : 25 August 2017
                Page count
                Figures: 4, Tables: 3, Pages: 10, Words: 5839
                Categories
                Original Research
                Clinical Cancer Research
                Original Research
                Custom metadata
                2.0
                cam41216
                April 2018
                Converter:WILEY_ML3GV2_TO_NLMPMC version:version=5.3.4 mode:remove_FC converted:23.04.2018

                Oncology & Radiotherapy
                cancer‐specific survival,nomogram,oral squamous cell carcinoma,overall survival,seer

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