Abstract / Summary
Background/Objectives: The management of Bethesda IV (follicular neoplasm) thyroid nodules remains controversial, in part due to wide variation in the reported risk of malignancy (ROM-BIV). Understanding this variability is essential for documenting systemic inconsistencies in ROM-BIV estimates and for developing more consistent risk-stratification strategies. This study aimed to quantify ROM-BIV variability across European centers and conduct an exploratory analysis of the trade-offs associated with hypothetical risk-based thresholds within a surgically selected cohort. Methods: We analyzed data from 15,251 patients with Bethesda IV thyroid nodules enrolled in the EUROCRINE registry. Multilevel logistic regression models were used to estimate ROM-BIV and assess variation across centers and countries, adjusting for patient- and nodule-level characteristics. Threshold analysis and decision curve analysis were employed as illustrative mappings of trade-off mechanisms within the surgically treated cohort to explore how varying risk levels affect classification outcomes. Results: Adjusted center-level ROM-BIV demonstrated marked variability, ranging from 5.5% to 65.5%. Intraclass correlation coefficients (ICCs) were 11.4% for institutions and 9.7% for countries, indicating meaningful clustering of ROM-BIV at both levels. The fixed component of the model showed limited-to-moderate discrimination (AUC-ROC 0.647; 95% CI, 0.637–0.656). Exploratory analysis illustrated the inherent trade-off between reducing potential overdiagnosis and maintaining sensitivity for malignancy detection. Decision curve analysis indicated a theoretical net benefit over default strategies, although no specific clinical threshold could be recommended based on these retrospective data. Conclusions: Substantial variability in ROM-BIV across European centers may reflect differences in institutional selection, diagnostic practices, clinical management, and reporting, rather than biological variance. These findings highlight the need for standardization of diagnostic and reporting pathways. Risk-based models must be positioned as supportive tools for individualized management and require rigorous prospective validation in unselected populations before any clinical implementation can be considered.