Diagnostic Performance of ACR and Kwak TI-RADS for Benign and Malignant Thyroid Nodules: An Update Systematic Review and Meta-Analysis

ABSTRACT:

Simple Summary

This meta-analysis determined the optimal cut-off value for differentiating benign and malignant thyroid nodules in two risk stratification systems (ACR and Kwak TI-RADS) and compared their diagnostic performance. Both systems showed good diagnostic performance. TR4 and 4B were estimated as optimal cut-off values for ACR and Kwak TI-RADS, respectively, but the cut-off values can be adjusted in consideration of changes in sensitivity and specificity.

Abstract

(1) Background: To determine the optimal cut-off values of two risk stratification systems to discriminate malignant thyroid nodules and to compare the diagnostic performance; (2) Methods: True and false positive and negative data were collected, and methodological quality was assessed for forty-six studies involving 39,085 patients; (3) Results: The highest area under the receiver operating characteristic (ROC) curve (AUC) of ACR and Kwak TI-RADS were 0.875 and 0.884. Based on the optimal sensitivity and specificity, the highest accuracy values of ROC curves or diagnostic odds ratios (DOR) were taken as the cut-off values for TR4 (moderate suspicious) and 4B. The sensitivity, specificity, DOR, and AUC by ACR (TR4) and Kwak TI-RADS (4B) for malignancy risk stratification of thyroid nodules were 94.3% and 96.4%; 52.2% and 53.7%; 17.5185 and 31.8051; 0.786 and 0.884, respectively. There were no significant differences in diagnostic accuracy in any of the direction comparisons of the two systems; (4) Conclusions: ACR and Kwak TI-RADS had good diagnostic performances (AUCs > 85%). Although we determined the best cut-off values in individual risk stratification systems based on statistical assessment, clinicians can adjust the optimal cut-off value according to the clinical purpose of the ultrasonography because raising or lowering cut-points leads to reciprocal changes in sensitivity and specificity.

SUBMITTER: Kang Y 

PROVIDER: S-EPMC9740871 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature