Dynamic Risk Stratification Integrated with ATA Risk System for Predicting Long-Term Outcome in Papillary Thyroid Cancer

Abstract

Background: In recent years, there has been a renewed interest in thyroid cancer management paradigms that use individualized risk assessments as the basis for treatment and follow-up recommendations. In this study, we assumed that the long-term follow-up of differentiated thyroid cancer patients might be better tailored by integrating the response to initial therapy with the America Thyroid Association (ATA) risk classes. Methods: This retrospective study included low- and intermediate-risk papillary thyroid cancer (PTC) patients followed up for a median time of 8 years and classified according to the response to initial therapy assessed 6–12 months after initial treatment. Results: After a median follow-up of 8 years, in the initial excellent response subgroup of PTC patients (n = 522), the rate of recurrent disease was significantly higher in intermediate-risk patients than in low-risk PTC patients (6.9% versus 1.2%, p = 0.0005). Similarly, in the initial biochemical incomplete response subgroup (n = 82), the rate of excellent response was significantly higher in low-risk PTC patients (58.0%) than in intermediate-risk PTC patients (33.3%) (p = 0.007). Finally, in the initial structural incomplete response subgroup (n = 66), the rate of excellent response was higher in low-risk patients (80.0%) than in intermediate-risk patients (46.4%) (p = 0.08). Moreover, all patients with initial indeterminate response had an excellent response at the last follow-up visit. ATA risk classes were independently associated with long-term outcome in each subgroup of patients classified dynamically after initial therapy and the overall prognostic performance, defined via ROC curve analysis, of response to initial therapy integrated with the ATA risk system (AUC: 0.89; 95% CI: 0.86–0.92) was significantly higher compared to the ATA risk stratification (AUC 0.69; 95% CI: 0.65–0.74, p < 0.001) or the dynamic risk stratification (DRS) systems alone (AUC: 0.86 95% CI: 0.82–0.90, p = 0.007). Conclusions: This study of a large cohort of PTC patients showed that the initial ATA risk criteria may be useful for improving the risk-adapted management of PTC patients based on the response to initial therapy.