BACKGROUND: A good predictive model requires patients to attend consultations for prognosis and subsequent clinical follow up. The aim of the present study was to build a nomogram chart with independent prognostic factors for thyroid cancer (TC) patients with total thyroidectomy. METHODS: This was a retrospective, observational study. Data were collected from the Surveillance, Epidemiology, End Results (SEER) database and approved by the institutional review board of our institution. In total, 11,614 patients with TC after thyroidectomy were selected from 2010 to 2015. We divided the selected patients into a modeling group and a verification group at a ratio of 7:3. The effective factors were selected to establish the nomogram model through Cox analysis. Finally, internal verification was carried out through the testing group. RESULTS: Chi-squared analysis of various factors in the modeling group and the testing group had no significant statistical significance, indicating that random grouping was meaningful. Most of the TC patients were female patients. The following variables were selected through univariate and multivariate Cox analysis for overall-specific survival: age, histological type, grade, tumor size, stage TMN, and sex. These variables were used to establish predictions of 3- and 5-year survival rates using a nomogram. Both the modeling group and the verification group had good predictive ability with their C-index all greater than 0.8. CONCLUSIONS: We established the first postoperative prediction model of TC with total thyroidectomy through the variables selected via the Cox multivariate analysis, which laid the foundation for the prognostic prediction and postoperative follow up of each patient. 2021 Gland Surgery. All rights reserved.
BACKGROUND: A good predictive model requires patients to attend consultations for prognosis and subsequent clinical follow up. The aim of the present study was to build a nomogram chart with independent prognostic factors for thyroid cancer (TC) patients with total thyroidectomy. METHODS: This was a retrospective, observational study. Data were collected from the Surveillance, Epidemiology, End Results (SEER) database and approved by the institutional review board of our institution. In total, 11,614 patients with TC after thyroidectomy were selected from 2010 to 2015. We divided the selected patients into a modeling group and a verification group at a ratio of 7:3. The effective factors were selected to establish the nomogram model through Cox analysis. Finally, internal verification was carried out through the testing group. RESULTS: Chi-squared analysis of various factors in the modeling group and the testing group had no significant statistical significance, indicating that random grouping was meaningful. Most of the TC patients were female patients. The following variables were selected through univariate and multivariate Cox analysis for overall-specific survival: age, histological type, grade, tumor size, stage TMN, and sex. These variables were used to establish predictions of 3- and 5-year survival rates using a nomogram. Both the modeling group and the verification group had good predictive ability with their C-index all greater than 0.8. CONCLUSIONS: We established the first postoperative prediction model of TC with total thyroidectomy through the variables selected via the Cox multivariate analysis, which laid the foundation for the prognostic prediction and postoperative follow up of each patient. 2021 Gland Surgery. All rights reserved.
Entities:
Keywords:
Surveillance, Epidemiology, End Results database (SEER database); Thyroid cancer (TC); nomogram; overall survival (OS); thyroidectomy
Authors: Raymon H Grogan; Sharone P Kaplan; Hongyuan Cao; Roy E Weiss; Leslie J Degroot; Cassie A Simon; Omran M A Embia; Peter Angelos; Edwin L Kaplan; Rebecca B Schechter Journal: Surgery Date: 2013-09-26 Impact factor: 3.982
Authors: Katrin M Sjoquist; Lindsay A Renfro; R John Simes; Niall C Tebbutt; Stephen Clarke; Matthew T Seymour; Richard Adams; Timothy S Maughan; Leonard Saltz; Richard M Goldberg; Hans-Joachim Schmoll; Eric Van Cutsem; Jean-Yves Douillard; Paulo M Hoff; Joel Randolph Hecht; Christophe Tournigand; Cornelis J A Punt; Miriam Koopman; Herbert Hurwitz; Volker Heinemann; Alfredo Falcone; Rainer Porschen; Charles Fuchs; Eduardo Diaz-Rubio; Enrique Aranda; Carsten Bokemeyer; Ioannis Souglakos; Fairooz F Kabbinavar; Benoist Chibaudel; Jeffrey P Meyers; Daniel J Sargent; Aimery de Gramont; John R Zalcberg Journal: J Natl Cancer Inst Date: 2018-06-01 Impact factor: 13.506