Life expectancy in differentiated thyroid cancer: a novel approach to survival analysis

Abstract

In differentiated thyroid carcinoma 10-year survival rates amount to 80-95%. Because age at diagnosis varies widely, these survival rates strongly depend on age at presentation. The aim of the present study was to analyse the attributable risk factors, including therapy per se, on survival in thyroid cancer after proper adjustment for the baseline mortality rate in the general population and to elucidate the adverse treatment effects on survival. Initial treatment in 504 patients consisted of thyroidectomy and 131I ablation. High-dose 131I was administered for residual disease. Patients in complete remission underwent an annual physical examination and thyroglobulin measurements during TSH suppression. Survival time was studied after transformation to standardised survival time to adjust for the baseline mortality rate in the general population. Median follow-up since diagnosis was 9 years. The 10-year overall survival was 83% and disease-specific survival 91%. After initial treatment, persistent disease occurred in 75 patients (15%). In univariate analysis, T4, N1, M1 status and Hürthle cell type were prognostic for persistent and recurrent disease. Age was not prognostic for recurrent disease in multivariate analysis. The standardised survival time was not altered in disease-free patients. However, patients with persistent disease had a median standardised survival time of only 0.60 (95% confidence interval 0.47;0.72), ranging from 0 to above 1, independent of initial tumour status or age. The cumulative proportion of persistent disease was at least 20% of the whole group. Disease-free patients after thyroid carcinoma have a normal residual life span. In contrast, in cases of persistent disease the life expectancy ranges widely with its median being reduced to 60%. Overall, treatment including radioiodine is safe but unsuccessful in 20% of the patients. Age is not a disease-specific risk factor and should not be used as an independent factor in treatment algorithms.