Table of Contents
ISRN Endocrinology
Volume 2012 (2012), Article ID 384707, 8 pages
Research Article

Sociodemographic Predictors of Survival in Differentiated Thyroid Cancer: Results from the SEER Database

1Department of Surgery, University of California San Diego, San Diego, CA 92103, USA
2Department of Surgery, Moores UCSD Cancer Center, 3855 Health Science Drive 0987, La Jolla, CA 92093-0987, USA

Received 9 March 2012; Accepted 26 June 2012

Academic Editors: C. Anderwald, R. V. García-Mayor, S. La Rosa, and Y. Tajiri

Copyright © 2012 Lily E. Johnston et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Background. Differentiated thyroid carcinoma (DTC) is prognosticated upon a combination of tumor characteristics, such as histology and stage, and patient age. DTC is also notable for having a strong female predominance. Using a nationwide database with long follow-up times, we explored the interplay between tumor biology and patient characteristics in predicting mortality. Methods. The Surveillance, Epidemiology, and End Results (SEER) registry data 1973–2005 was examined for patients with DTC as their only known malignancy. Cox multivariate analyses were used to generate mortality hazard ratios to evaluate the effects of age, gender, ethnicity, and marital status. Results. We identified 55,995 patients with DTC as their only malignancy. Consistent with the existing literature, the tumors are primarily diagnosed in women (77.5%), and predominantly affect Caucasians (78.3%). Female gender had a protective effect resulting in a 37% decrease in mortality. Age at diagnosis predicted mortality over age 40. Black ethnicity was associated with a 51% increase in mortality compared to Caucasians. Conclusion. Multiple demographic factors predict mortality in patients with DTC after adjusting for tumor characteristics, and they appear to have complex interactions. Recognizing the importance of these factors may enable clinicians to better tailor therapy.