Dataset Information

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

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.

SUBMITTER: Gui W

PROVIDER: S-EPMC7246027 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

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

Gui Weiwei W Zhu Weifen W Lu Weina W Shang Chengxin C Zheng Fenping F Lin Xihua X Li Hong H

PeerJ 20200521

<h4>Background</h4>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.<h4>Methods</h4>A total of 1,404 cases of ATC diagnosed between 1983 and 2013 were extracted from on the Surveillance, Epidemiology and End Re ...[more]

PMID: 32509460

Similar Datasets

Project description:ImportanceAnaplastic thyroid carcinoma (ATC) historically has a 4-month median overall survival (OS) from time of diagnosis, with disease-specific mortality approaching 100%. The association between recent major advancements in treatment and OS has yet to be evaluated.ObjectiveTo evaluate rates of OS in patients with ATC over the last 2 decades.Design, setting, and participantsRetrospective cohort study in a single tertiary care institution. Patients with histopathological confirmation of ATC from January 2000 to October 2019 were included and divided into 3 groups according to date of presentation: 2000-2013, 2014-2016, and 2017-2019.Main outcomes and measuresOverall survival compared among different treatment eras and differing therapies, including targeted therapy, immunotherapy, and surgery.ResultsOf 479 patients (246 men [51%]; median age, 65.0 [range, 21.1-92.6] years) with ATC evaluated, 52 (11%) were stage IVA, 172 (36%) stage IVB, and 255 (53%) stage IVC at presentation. The median OS of the entire cohort was 0.79 years (9.5 months), ranging from 0.01 to 16.63. The OS at 1 and 2 years was 35% (95% CI, 29%-42%) and 18% (95% CI, 13%-23%) in the 2000-2013 group (n = 227), 47% (95% CI, 36%-56%) and 25% (95% CI, 17%-34%) in the 2014-2016 group (n = 100), and 59% (95% CI, 49%-67%) and 42% (95% CI, 30%-53%) in the 2017-2019 group (n = 152), respectively (P < .001). The hazard ratio was 0.50 (95% CI, 0.38-0.67) for the 2017-2019 group compared with the 2000-2013 patients (P < .001). Factors associated with improved OS included targeted therapy (hazard ratio, 0.49; 95% CI, 0.39-0.63; P < .001), the addition of immunotherapy to targeted therapy (hazard ratio, 0.58; 95% CI, 0.36-0.94; P = .03), and surgery following neoadjuvant BRAF-directed therapy (hazard ratio, 0.29; 95% CI, 0.10-0.78; P = .02). Patients undergoing surgery following neoadjuvant BRAF-directed therapy (n = 20) had a 94% 1-year survival with a median follow-up of 1.21 years.Conclusion and relevanceIn this large single-institution cohort study spanning nearly 20 years, changes in patient management appear to be associated with significant increase in survival. The era of untreatable ATC is progressively being replaced by molecular-based personalized therapies, with integration of multidisciplinary therapies including surgery and radiation therapy.

Project description:Background Increasing evidence indicates that the pathology and the modified Kadish system have some influence on the prognosis of esthesioneuroblastoma (ENB). However, an accurate system to combine pathology with a modified Kadish system has not been established. Methods This study aimed to set up and evaluate a model to predict overall survival (OS) accurately in ENB, including clinical characteristics, treatment and pathological variables. We screened the information of patients with ENB between January 1, 1976, and December 30, 2016 from the National Cancer Institute Surveillance, Epidemiology, and End Results (SEER) program as a training cohort. The validation cohort consisted of patients with ENB at Sun Yat-sen University Cancer Center and The First Affiliated Hospital of Sun Yat-sen University in the same period, and 87 patients were included. The Pearson’s chi-squared test was used to assess significance of clinicopathological and demographic characteristics. We used the Cox proportional hazards model to examine univariate and multivariate analyses. The model coefficients were used to calculate the Hazard ratios (HR) with 95% confidence intervals (CI). Prognostic factors with a p-value < 0.05 in multivariate analysis were included in the nomogram. The concordance index (c-index) and calibration curve were used to evaluate the predictive power of the nomogram. Results The c-index of training cohort and validation cohort are 0.737 (95% CI, 0.709 to 0.765) and 0.791 (95% CI, 0.767 to 0.815) respectively. The calibration curves revealed a good agreement between the nomogram prediction and actual observation regarding the probability of 3-year and 5-year survival. We used a nomogram to calculate the 3-year and 5-year growth probability and stratified patients into three risk groups. Conclusions The nomogram provided the risk group information and identified mortality risk and can serve as a reference for designing a reasonable follow-up plan.

Project description:BackgroundUveal melanoma (UM) is a rare but aggressive cancer, which is the most common primary intraocular malignancy in adults. We aimed to develop and validate a competing risk nomogram to predict cancer-specific survival (CSS) of patients with UM, as well as compare its prognostic value with that of the American Joint Committee on Cancer (AJCC) staging system.MethodsData of patients diagnosed with UM from 2010 to 2015 were identified from the Surveillance, Epidemiology, and End Results (SEER) database. We extracted and integrated significant prognostic factors based on competing risk regression to build a nomogram. The nomogram with an online prediction version was also created. The performance of the nomogram was evaluated using Harrell's concordance index (C-index) and calibration plots. Receiver operating characteristic (ROC) curve was carried out to estimate clinical applicability of the model. Improvements in the predictive accuracy of our new model compared with AJCC staging system were estimated by calculating the relative integrated discrimination improvement (IDI) and the net reclassification improvement (NRI).ResultsA total of 839 eligible patients with primary UM were randomly assigned to a training cohort (588, 70%) and a validation cohort (251, 30%). Age, histological type, T stage and M stage were independent prognostic factors to predict CSS of UM and were incorporated in the nomogram. The calibration plots indicated that the 3- and 5-year CSS probabilities were consistent between the nomogram prediction and the actual observation. The C-index for this model was 0.778 (95% CI:0.756-0.800) and 0.786 (95% CI: 0.749-0.816) in the training cohort and validation cohort. Areas under the curve (AUCs) were 0.814, 0.771, and 0.792 in the training cohort, 0.788, 0.781 and 0.804 in the validation cohort, respectively. The NRI value in AJCC staging system was - 0.153 (95% CI -0.29 - - 0.041) for 3 years of follow-up and - 0.276 (95% CI -0.415 - - 0.132) for 5 years of follow-up. The IDI values for 3 and 5 years of follow-up in the AJCC staging system were - 0.021 (P = 0.076) and - 0.045 (P = 0.004), respectively.ConclusionsWe have developed and validated a competing risk nomogram to reliably predict cancer-specific survival of patients with UM. This convenient tool may be useful for evaluating cancer-specific prognosis.

Dataset Information

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

Publications

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

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets