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      Development and validation of a prognostic nomogram to predict overall survival and cancer-specific survival for patients with anaplastic thyroid carcinoma

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          Abstract

          Background

          Anaplastic thyroid carcinoma (ATC) is a rare malignant tumor with a poor prognosis. However, there is no useful clinical prognostic predictive tool for ATC so far. Our study identified risk factors for survival of ATC and created a reliable nomogram to predict overall survival (OS) and cancer-specific survival (CSS) of patients with ATC.

          Methods

          A total of 1,404 cases of ATC diagnosed between 1983 and 2013 were extracted from on the Surveillance, Epidemiology and End Results database based on our inclusion criteria. OS and CSS were compared among patients between each variable by Kaplan–Meier methods. The Cox proportional hazards model was used to evaluate multiple prognostic factors and obtain independent predictors. All independent risk factors were included to build nomograms, whose accuracy and practicability were tested by concordance index (C-index), calibration curves, ROC curves, DCA, net reclassification improvement (NRI) and integrated discrimination improvement (IDI).

          Results

          Historic stage, tumor size, surgery and radiotherapy were independent risk factors associated with ATC according to multivariate Cox regression analysis of OS. However, gender was also an important prognostic predictor in CSS besides the factors mentioned above. These characteristics were included in the nomograms predicting OS and CSS of patients with ATC. The nomograms predicting OS and CSS performed well with a C-index of 0.765 and 0.773. ROC curves, DCA, NRI and IDI suggested that the nomogram was superior to TNM staging and age.

          Conclusion

          The proposed nomogram is a reliable tool based on the prediction of OS and CSS for patients with ATC. Such a predictive tool can help to predict the survival of the patients.

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          Most cited references29

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          Anaplastic thyroid carcinoma: from clinicopathology to genetics and advanced therapies

          Although anaplastic thyroid carcinoma (ATC) is a rare form of thyroid cancer, the limited efficacy of conventional treatment options and challenges in histological diagnosis make this an almost invariably lethal disease. In this Review, the authors describe the clinical and pathological features of ATC, highlight recent advances in uncovering the genetics and molecular biology of this disease, and discuss both conventional and future treatment modalities.
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            In-depth mining of clinical data: the construction of clinical prediction model with R

            This article is the series of methodology of clinical prediction model construction (total 16 sections of this methodology series). The first section mainly introduces the concept, current application status, construction methods and processes, classification of clinical prediction models, and the necessary conditions for conducting such researches and the problems currently faced. The second episode of these series mainly concentrates on the screening method in multivariate regression analysis. The third section mainly introduces the construction method of prediction models based on Logistic regression and Nomogram drawing. The fourth episode mainly concentrates on Cox proportional hazards regression model and Nomogram drawing. The fifth Section of the series mainly introduces the calculation method of C-Statistics in the logistic regression model. The sixth section mainly introduces two common calculation methods for C-Index in Cox regression based on R. The seventh section focuses on the principle and calculation methods of Net Reclassification Index (NRI) using R. The eighth section focuses on the principle and calculation methods of IDI (Integrated Discrimination Index) using R. The ninth section continues to explore the evaluation method of clinical utility after predictive model construction: Decision Curve Analysis. The tenth section is a supplement to the previous section and mainly introduces the Decision Curve Analysis of survival outcome data. The eleventh section mainly discusses the external validation method of Logistic regression model. The twelfth mainly discusses the in-depth evaluation of Cox regression model based on R, including calculating the concordance index of discrimination (C-index) in the validation data set and drawing the calibration curve. The thirteenth section mainly introduces how to deal with the survival data outcome using competitive risk model with R. The fourteenth section mainly introduces how to draw the nomogram of the competitive risk model with R. The fifteenth section of the series mainly discusses the identification of outliers and the interpolation of missing values. The sixteenth section of the series mainly introduced the advanced variable selection methods in linear model, such as Ridge regression and LASSO regression.
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              Prognostic factors for thyroid carcinoma. A population-based study of 15,698 cases from the Surveillance, Epidemiology and End Results (SEER) program 1973-1991.

              A number of prognostic factors for thyroid carcinoma have been identified, including sociodemographic characteristics, such as age and gender, and tumor characteristics, such as histology and stage. The relative importance of these factors as independent predictors of survival for patients with papillary, follicular, anaplastic, and medullary thyroid carcinoma has been extensively studied but remains uncertain. The authors used data collected by the Surveillance, Epidemiology and End Results (SEER) program of the National Cancer Institute between 1973 and 1991 to investigate prognostic factors for each of the major histologic types of thyroid carcinoma in a population-based patient series and to assess the effect of these factors as predictors of survival. Both tumor and sociodemographic characteristics were independently associated with survival. Patients with papillary carcinoma had the highest 10-year relative survival (0.98), followed by those with follicular carcinoma (0.92) and medullary carcinoma (0.80). Anaplastic tumors had the lowest 10-year relative survival (0.13). Stage at diagnosis and differentiation status were strong independent prognostic factors for each histologic type. Advanced stage at diagnosis was a stronger prognostic factor for medullary carcinoma than for other histologic types. Increasing age was associated with lower relative survival for each histologic type. Gender, marital status, and ethnicity were significant, but weaker, predictors of survival. Survival varied markedly among patients with different histologic types of thyroid carcinoma. Stage at diagnosis and tumor differentiation were important prognostic factors for each histologic type. Age at diagnosis was a stronger predictor of survival for patients with follicular and medullary carcinoma than for patients with papillary carcinoma.
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                Author and article information

                Contributors
                Journal
                PeerJ
                PeerJ
                PeerJ
                PeerJ
                PeerJ
                PeerJ Inc. (San Diego, USA )
                2167-8359
                21 May 2020
                2020
                : 8
                : e9173
                Affiliations
                Department of Endocrinology, the Affiliated Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University , Hangzhou, Zhejiang, China
                Author information
                http://orcid.org/0000-0002-8537-4479
                Article
                9173
                10.7717/peerj.9173
                7246027
                32509460
                892b4bfa-9969-4168-b827-eafd36777e6f
                © 2020 Gui et al.

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.

                History
                : 24 October 2019
                : 21 April 2020
                Funding
                Funded by: Zhejiang Provincial Natural Science Foundation of China
                Award ID: NO.LQ18h070001
                This work was supported by the Zhejiang Provincial Natural Science Foundation of China (Grant No. LQ18h070001). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Bioinformatics
                Diabetes and Endocrinology
                Internal Medicine
                Metabolic Sciences

                anaplastic thyroid carcinoma,nomogram,overall survival,cancer-specific survival,seer

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