A Prediction Model for Assessing the Efficacy of Thermal Ablation in Treating Benign Thyroid Nodules ≥ 2 cm: A Multi-Center Retrospective Study

Objectives: To develop and validate a prediction model utilizing clinical and ultrasound (US) data for preoperative assessment of efficacy following US-guided thermal ablation (TA) in patients with benign thyroid nodules (BTNs) >= 2 cm. Materials and methods: We retrospectively assessed 962 patients with 1011 BTNs who underwent TA at four tertiary centers between May 2018 and July 2022. Ablation efficacy was categorized into therapeutic success (volume reduction rate [VRR] > 50%) and non-therapeutic success (VRR <= 50%). We identified independent factors influencing the ablation efficacy of BTNs >= 2 cm in the training set using multivariate logistic regression. On this basis, a prediction model was established. The performance of model was further evaluated by discrimination (area under the curve [AUC]) in the validation set. Results: Of the 1011 nodules included, 952 (94.2%) achieved therapeutic success at the 12-month follow-up after TA. Independent factors influencing VRR > 50% included sex, nodular composition, calcification, volume, and largest diameter (all p < 0.05). The prediction equation was established as follows: p = 1/1 + Exp & sum;[8.113 -2.720 x (if predominantly solid) -2.790 x (if solid) -1.275 x (if 10 mL < volume <= 30mL) -1.743 x (if volume > 30 mL) -1.268 x (if with calcification) -2.859 x (if largest diameter > 3 cm) +1.143 x (if female)]. This model showed great discrimination, with AUC of 0.908 (95% confidence interval [CI]: 0.868-0.947) and 0.850 (95% CI: 0.748-0.952) in the training and validation sets, respectively. Conclusions: A clinical prediction model was successfully developed to preoperatively predict the therapeutic success of BTNs larger than 2 cm in size following US-guided TA. This model aids physicians in evaluating treatment efficacy and devising personalized prognostic plans.