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Development and validation of a nomogram for predicting the early death of anaplastic thyroid cancer: a SEER population-based study.
Cui, Hanxiao; Wang, Ru; Zhao, Xuyan; Wang, Shuhui; Shi, Xianbiao; Sang, Jianfeng.
Afiliação
  • Cui H; Department of Oncology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
  • Wang R; Division of Thyroid Surgery, Department of General Surgery, Nanjing Drum Tower Hospital, The Affiliated Hospital of Medical School, Nanjing University, Nanjing, China.
  • Zhao X; Department of Oncology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
  • Wang S; Department of Oncology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
  • Shi X; Division of Thyroid Surgery, Department of General Surgery, Nanjing Drum Tower Hospital, The Affiliated Hospital of Medical School, Nanjing University, Nanjing, China. sxbnju0510@163.com.
  • Sang J; Division of Thyroid Surgery, Department of General Surgery, Nanjing Drum Tower Hospital, The Affiliated Hospital of Medical School, Nanjing University, Nanjing, China. drsangjianfeng@163.com.
J Cancer Res Clin Oncol ; 149(17): 16001-16013, 2023 Nov.
Article em En | MEDLINE | ID: mdl-37689588
BACKGROUND: Anaplastic thyroid cancer (ATC) is a highly aggressive malignancy with dismal prognosis. This study aimed to identify the independent risk factors and construct a readily-to-use nomogram to predict the probability of early death in ATC patients. METHOD: Patients diagnosed with ATC between 2004 and 2015 from the Surveillance, Epidemiology, and End Results (SEER) database were enrolled in this study for model development and internal validation. Univariate and multivariate logistic regression analyses were conducted to identify independent risk factors for early death of ATC. Nomograms for predicting the probability of all-cause early death (ACED) and cancer-specific early death (CSED) of ATC were subsequently developed. The performance of the nomograms was comprehensively evaluated and validated in an internal cohort. RESULT: A total of 696 ATC patients were included in this study, of which 488 patients in the training cohort and 208 patients in the validation cohort. The univariate and multivariate logistic regression analyses identified five independent factors (tumor size, M stage, surgery, radiotherapy and chemotherapy) in the ACED model and six variables in the CSED (gender, tumor size, M stage, surgery, radiotherapy and chemotherapy) model for the establishment of the nomograms. Calibration curves and receiver operating characteristic (ROC) curves showed satisfactory efficacy and consistency both in the training (ACED: AUC values: 0.814 (0.776-0.852); CSED: 0.778 (0.736-0.820)) and validation sets (ACED: 0.762 (0.696-0.827); CSED: 0.745 (0.678-0.812)). In addition, the decision curve analysis (DCA) demonstrated the favorable potential of the two nomograms in clinical application. CONCLUSION: The two nomograms assist clinicians to identify risk factors and predict the early death probability among ATC patients, thus guide individualized treatment to improve the prognosis.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias da Glândula Tireoide / Carcinoma Anaplásico da Tireoide Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias da Glândula Tireoide / Carcinoma Anaplásico da Tireoide Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article