Anti-thyroglobulin antibody levels post-thyroidectomy and papillary thyroid carcinoma recurrence

The global incidence of thyroid cancer, particularly papillary thyroid carcinoma (PTC), is rising due to more frequent incidental findings. Despite a high 10-year survival rate of 93%, up to 28% of PTC patients experience locoregional recurrence. Postoperative monitoring typically relies on serum thyroglobulin (Tg), but the presence of anti-thyroglobulin antibodies (TgAb) interferes with Tg measurement, necessitating reliable detection methods. This study aimed to assess the predictive value of postoperative TgAb levels for PTC recurrence and establish a TgAb threshold as a prognostic marker.

A retrospective analysis was conducted on 15,620 patients who underwent bilateral total thyroidectomies at Gangnam Severance Hospital between March 2004 and December 2022. After excluding patients with unmeasurable postoperative TgAb or other carcinoma types, the final cohort comprised 4,434 PTC patients (775 men and 3,659 women, median age 46 ± 11.68 years). Bilateral total thyroidectomy was performed on all patients. TgAb levels were measured 2 days post-surgery and annually, with the most recent levels used for analysis. The primary outcome was PTC recurrence, analyzed based on stratified TgAb levels.

Elevated TgAb levels were significantly associated with increased tumor size and recurrence rates (P < 0.001). Patients with TgAb levels above 440 IU/mL showed a higher recurrence rate (13.3%) compared to those with lower levels. A TgAb threshold of 440 IU/mL was identified as a novel recurrence marker, with an odds ratio of 6.0 (95% CI: 2.987-12.053, P < 0.0001). The disease-free survival (DFS) was shorter in patients with TgAb levels above this threshold.

Postoperative TgAb levels are a useful prognostic indicator for PTC recurrence, with a proposed threshold of 440 IU/mL serving as a predictive marker. This threshold provides valuable insight for monitoring patients, irrespective of test timing post-surgery, and may guide clinical decision-making for identifying high-risk patients.