Is papillary thyroid microcarcinoma an indolent tumor?: A retrospective study on 280 cases treated with radioiodine

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Abstract

The increasing detection of papillary thyroid microcarcinoma (PTMC) has created management dilemmas. To clarify the clinical significance of postsurgery stimulated thyroglobulin (ps-Tg) in PTMC who undergo thyroidectomy and radioactive iodine (RAI), we retrospectively reviewed the 358 PTMC patients who were treated with RAI and followed up in our hospital. Those with an excessive anti-Tg antibody, ultrasound-detected residual were excluded, thereby resulting in the inclusion of 280 cases. Their clinical and histopathological information and clinical outcomes were collected and summarized. Tumor stages were classified according to the tumor, node, metastasis (TNM) staging system and the consensus of the European Thyroid Association (ETA) risk stratification system, respectively. Kaplan–Meier curves were constructed to compare the disease-free survival (DFS) rates of different risk-staging systems. By the end of follow-up, none of the patients died of the disease or relapsed. The 8-year DFS rate was 76.9%. Kaplan–Meier curves showed different DFS rates in TNM stages I versus IV, III versus IV, very low risk versus high risk, low risk versus high risk, respectively (P < 0.05), while they were not significantly different in stage I versus stage III, very low risk versus low risk (P > 0.05). Finally, 40 (14.3%) cases got a persistent disease. Five variables (male sex, nonconcurrent benign pathology, initial tumor size >5 mm, lymph node metastasis, and ps-Tg ≥ 10 μg/L) were associated with disease persistence by univariate regression analysis. Ps-Tg ≥ 10 μg/L was the only independent prognostic variable that predicted disease persistence by multivariate regression analysis (odds ratio: 36.057, P = 0.000). Therefore, PTMC with a small size of ≤1 cm does not always act as an indolent tumor. In conclusion, ps-Tg ≥ 10 μg/L is associated with increased odds of disease persistence. ETA risk stratification is more effective in predicting disease persistence than the TNM classification system.

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