Identifying and Predicting Diverse Patterns of Benign Nodule Growth.

Abstract

The natural history of benign thyroid nodules is typically characterized by slow growth and minimal risk of malignant transformation. Available data have, to date, been unable to elucidate the diversity of benign nodule growth patterns over time nor predictive of which patients follow which pattern. We aimed to better define the diverse patterns of benign nodule behavior and their predictors. We prospectively studied 389 consecutive patients with solitary, solid, cytologically benign thyroid nodules ≥1 cm and follow-up ultrasound for at least 4 years. Demographic, sonographic, biochemical data were collected at initial evaluation, and subsequent growth patterns were identified over the follow-up. Predictors of growth at initial evaluation and 3 years of follow-up were defined. The mean (±SD) follow-up was 7.7 (±2.7) years. Three distinct growth patterns were identified: A) stagnant nodules with average growth rate < 0.2 mm/year; B) slow-growing nodules with a rate 0.2 to 1.0 mm/year; and C) fast-growing nodules increasing > 1.0 mm/year. Fast-growing nodules represented 17.2% of the cohort, and were more frequent in patients younger than 50 years (OR 2.2 [1.2-4.1], P = 0.016), and in larger nodules (2.0-2.9 cm, OR 3.5 [1.7-7.1], P = 0.001; >3.0 cm, OR 4.4 [1.8-10.4], P = 0.001 vs reference 1-1.9 cm). In a multiple regression model, nodule growth at 3 years at an average growth rate over 0.2 mm/year over 3 years since initial evaluation was an independent predictor of longer-term fast nodule growth, even after adjusting for age, biological sex, TSH level, and nodule size (P < 0.001). The natural history of benign nodule growth is diverse, with over 80% of nodules demonstrating minimal to no growth long-term. Nearly 20% of cytologically benign nodules may exhibit a fast, continued growth pattern, which can be predicted by the 3-year growth rate pattern. These findings can help inform decision making for tailored benign nodule follow-up and monitoring.