Comparison with published systems of a new staging system for papillary and follicular thyroid carcinoma

Several staging systems exist to estimate the prognosis for patients with thyroid carcinoma. Our goal was to develop a new staging system to predict cancer-specific survival (CSS) and evaluate it against published systems.

The Cedars-Sinai Medical Center (CSMC)'s staging system was derived using data from an adjusted analysis of 1622 patients with differentiated thyroid carcinomas (DTCs) from the CSMC Thyroid Cancer Center. Mean follow-up time was 11.8 years. There were 1180 female and 442 male patients with a mean age of 46. Staging systems reviewed include University of Alabama (Birmingham) and M.D. Anderson Cancer Center (UAB-MDACC); the Tumor-Node-Metastasis (TNM) 5th and 7th editions; Memorial Sloan-Kettering (MSK); the National Thyroid Cancer Treatment Cooperative Study (NTCTCS); Ohio State; Clinical Class; Metastases, Age, Completeness of resection, Invasion, and tumor Size (MACIS); Noguchi; and the Yildirim model for predicting outcomes. The proportion of variance explained (PVE) and the C-index were computed to rank and compare each staging system's ability to predict CSS with this patient population.

Adjusted hazard ratios revealed that age at surgery of >45 years, the presence of distant metastases, capsular invasion, and vascular invasion were the most significant predictors of CSS in this patient population. The final CSMC risk score consists of low-, moderate-, and high-risk groups. Among the well-differentiated thyroid carcinoma staging systems, the CSMC and NTCTCS ranked highest with PVE values of 5% and 4.3%, respectively, while the NTCTCS and CSMC staging systems were reversed using the C-index (0.77 and 0.76, respectively).

The PVE and C-index values were relatively low across all applicable staging systems and varied in each study reviewed. This suggests that no one staging system has been shown to be superior to another across different patient populations with DTC. In the future, additional factors, such as biological markers, added to the clinical and pathological characteristics may lead to the development of superior staging systems.