Competing-Risks Model for Predicting the Postoperative Prognosis of Patients with Papillary Thyroid Adenocarcinoma Based on The Surveillance, Epidemiology, and End Results (SEER) Database

Med Sci Monit. 2020 Jul 25:26:e924045. doi: 10.12659/MSM.924045.

Abstract

BACKGROUND The aim of this study was to identify accurate prognostic factors for postoperative papillary thyroid adenocarcinoma (PTAC) using a competing-risks model based on data from the Surveillance, Epidemiology, and End Results (SEER) database. MATERIAL AND METHODS Data on patients with PTAC who had received surgery between 2010 and 2015 in the SEER database were extracted. A univariate analysis was performed while considering competing risks using the cumulative incidence function, with Nelson-Aalen cumulative risk curves of the incidence function for PTAC-specific death were calculated and then compared between 2 groups using Gray's test. To identify the factors that affect the cumulative incidence of PTAC-specific death, a multivariate analysis using the Fine-Gray model was performed. RESULTS The 8324 eligible surgical PTAC patients included 101 patients who died from PTAC and 129 patients who died from other causes. The univariate Gray's test revealed that the cumulative incidence rate for events of interest was significantly affected (P<0.05) by age, sex, marital status, metastasis, differentiation grade, American Joint Committee on Cancer (AJCC) stage, radiation status, chemotherapy status, regional lymph nodes removal, and tumor size. Multivariate competing-risks analyses showed that age, sex, metastasis, differentiation grade, radiation status, chemotherapy status, and tumor size were independent risk factors for the postoperative prognosis of PTAC patients (P<0.05). The results of multivariate Cox regression were different, with marital status also appearing as an independent risk factor. CONCLUSIONS This study established a competing-risks analysis model to evaluate the risk factors of surgical PTAC patients. Our findings may be useful for improving patient prognoses and decision-making when providing individualized treatments.

MeSH terms

  • Adenocarcinoma / metabolism
  • Adenocarcinoma / mortality
  • Adult
  • Databases, Factual
  • Female
  • Humans
  • Incidence
  • Male
  • Middle Aged
  • Models, Statistical
  • Multivariate Analysis
  • Neoplasm Grading / methods
  • Neoplasm Staging / methods
  • Nomograms
  • Postoperative Period
  • Prognosis
  • Risk Assessment
  • Risk Factors
  • SEER Program
  • Thyroid Cancer, Papillary / diagnosis*
  • Thyroid Cancer, Papillary / metabolism
  • Thyroid Cancer, Papillary / mortality*
  • Thyroid Gland
  • Thyroid Neoplasms / metabolism