Nomograms for Differentiated Thyroid Carcinoma Patients Based on the Eighth AJCC Staging and Competing Risks Model

Author:

Li Chengzhuo12,Xu Fengshuo12,Huang Qiao3,Han Didi12ORCID,Zheng Shuai14,Wu Wentao2,Zhao Fanfan12,Feng Xiaojie12,Lyu Jun12ORCID

Affiliation:

1. Department of Clinical Research, The First Affiliated Hospital of Jinan University, Guangdong Province, China

2. School of Public Health, Xi’an Jiaotong University Health Science Center, Shaanxi Province, China

3. Center for Evidence-Based and Translational Medicine, Zhongnan Hospital of Wuhan University, Hubei Province, China

4. School of Public Health, Shaanxi University of Chinese Medicine, Shaanxi Province, China

Abstract

Abstract Background Differentiated thyroid carcinoma (DTC) patients have a long survival period and good prognosis, so they are easily affected by competing risk events. The purpose of this study was to use the competing risks model to identify prognostic factors for cause-specific death (CSD) and death due to other causes (DOC) in patients with DTC. Methods Our screening process identified 34 585 DTC patients in the Surveillance, Epidemiology, and End Results database and randomly divided them into a training cohort and a validation cohort. We used the Fine and Gray subdistribution hazards model to establish the CSD and DOC nomograms. The distinguishing ability and consistency of the nomograms were evaluated using the consistency indexes and calibration plots. Results Our analysis of a competing risks model revealed that pathological grade, tumor size, histological type, American Joint Committee on Cancer (AJCC)–8 stage, surgery status, adjuvant radiotherapy status, adjuvant chemotherapy status, and log odds of positive lymph nodes are prognostic factors for CSD, and age at diagnosis, year of diagnosis, sex, pathological grade, tumor size, AJCC-8 stage, surgery status, adjuvant radiotherapy status, and lymph node ratio are prognostic factors for DOC. The 1-year, 3-year, and 5-year concordance indexes in the validation cohorts were 0.942, 0.931, and 0.913 for the CSD nomogram and 0.813, 0.746, and 0.776 for the DOC nomogram. The calibration plots showed good consistency in both nomograms. Conclusions Our nomograms can be used as a tool to help clinicians individually predict the probability of CSD and DOC in DTC patients at 1 year, 3 years, and 5 years, which has certain guiding value in clinical applications.

Funder

National Social Science Foundation of China

Publisher

Oxford University Press (OUP)

Subject

Cancer Research,Oncology

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