Nomogram-Based New Recurrence Predicting System in Early-Stage Papillary Thyroid Cancer

Background and Objectives. The clinicopathological risk factors to predict recurrence of papillary thyroid cancer (PTC) patients remain controversial. Methods. PTC patients treated with thyroidectomy between January 1997 and December 2011 at the First Affiliated Hospital of Zhejiang University (Zhej...

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Main Authors: Yongfeng Ding, Zhuochao Mao, Jiaying Ruan, Xingyun Su, Linrong Li, Thomas J. Fahey, Weibin Wang, Lisong Teng
Format: Article
Language:English
Published: Wiley 2019-01-01
Series:International Journal of Endocrinology
Online Access:http://dx.doi.org/10.1155/2019/1029092
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author Yongfeng Ding
Zhuochao Mao
Jiaying Ruan
Xingyun Su
Linrong Li
Thomas J. Fahey
Weibin Wang
Lisong Teng
author_facet Yongfeng Ding
Zhuochao Mao
Jiaying Ruan
Xingyun Su
Linrong Li
Thomas J. Fahey
Weibin Wang
Lisong Teng
author_sort Yongfeng Ding
collection DOAJ
description Background and Objectives. The clinicopathological risk factors to predict recurrence of papillary thyroid cancer (PTC) patients remain controversial. Methods. PTC patients treated with thyroidectomy between January 1997 and December 2011 at the First Affiliated Hospital of Zhejiang University (Zhejiang cohort) were included. Multivariate Cox regression analysis was conducted to identify independent recurrence predictors. Then, the nomogram model for predicting probability of recurrence was built. Results. According to Zhejiang cohort (N = 1,697), we found that the 10-year event-free survival (EFS) rates of PTC patients with early-stage (TNM stages I, II, and III) were not well discriminated (91.6%, 89.0%, and 90.7%; P=0.768). The multivariate Cox model identified age, bilaterality, tumor size, and nodal status as independent risk factors for tumor recurrence in PTC patients with TNM stages I–III. We then developed a nomogram with the C-index 0.70 (95% CI, 0.64 to 0.76), which was significantly higher (P<0.0001) than the AJCC staging system (0.52). In the validation group, the C-index remained at a similar level. Conclusions. In this study, we build up a new recurrence predicting system and establish a nomogram for early-stage PTC patients. This prognostic model may better predict individualized outcomes and conduct personalized treatments.
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spelling doaj-art-b034a3048bb6424e823e86af85a884212025-08-20T02:19:18ZengWileyInternational Journal of Endocrinology1687-83371687-83452019-01-01201910.1155/2019/10290921029092Nomogram-Based New Recurrence Predicting System in Early-Stage Papillary Thyroid CancerYongfeng Ding0Zhuochao Mao1Jiaying Ruan2Xingyun Su3Linrong Li4Thomas J. Fahey5Weibin Wang6Lisong Teng7Cancer Center, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, ChinaCancer Center, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, ChinaCancer Center, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, ChinaCancer Center, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, ChinaDepartment of Orthopedics, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, ChinaDepartment of Surgery, New York Presbyterian Hospital-Weill Cornell Medical College, New York, NY, USACancer Center, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, ChinaCancer Center, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, ChinaBackground and Objectives. The clinicopathological risk factors to predict recurrence of papillary thyroid cancer (PTC) patients remain controversial. Methods. PTC patients treated with thyroidectomy between January 1997 and December 2011 at the First Affiliated Hospital of Zhejiang University (Zhejiang cohort) were included. Multivariate Cox regression analysis was conducted to identify independent recurrence predictors. Then, the nomogram model for predicting probability of recurrence was built. Results. According to Zhejiang cohort (N = 1,697), we found that the 10-year event-free survival (EFS) rates of PTC patients with early-stage (TNM stages I, II, and III) were not well discriminated (91.6%, 89.0%, and 90.7%; P=0.768). The multivariate Cox model identified age, bilaterality, tumor size, and nodal status as independent risk factors for tumor recurrence in PTC patients with TNM stages I–III. We then developed a nomogram with the C-index 0.70 (95% CI, 0.64 to 0.76), which was significantly higher (P<0.0001) than the AJCC staging system (0.52). In the validation group, the C-index remained at a similar level. Conclusions. In this study, we build up a new recurrence predicting system and establish a nomogram for early-stage PTC patients. This prognostic model may better predict individualized outcomes and conduct personalized treatments.http://dx.doi.org/10.1155/2019/1029092
spellingShingle Yongfeng Ding
Zhuochao Mao
Jiaying Ruan
Xingyun Su
Linrong Li
Thomas J. Fahey
Weibin Wang
Lisong Teng
Nomogram-Based New Recurrence Predicting System in Early-Stage Papillary Thyroid Cancer
International Journal of Endocrinology
title Nomogram-Based New Recurrence Predicting System in Early-Stage Papillary Thyroid Cancer
title_full Nomogram-Based New Recurrence Predicting System in Early-Stage Papillary Thyroid Cancer
title_fullStr Nomogram-Based New Recurrence Predicting System in Early-Stage Papillary Thyroid Cancer
title_full_unstemmed Nomogram-Based New Recurrence Predicting System in Early-Stage Papillary Thyroid Cancer
title_short Nomogram-Based New Recurrence Predicting System in Early-Stage Papillary Thyroid Cancer
title_sort nomogram based new recurrence predicting system in early stage papillary thyroid cancer
url http://dx.doi.org/10.1155/2019/1029092
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