Use of the Kwak Thyroid Image Reporting and Data System (K-TIRADS) in differential diagnosis of thyroid nodules: systematic review and meta-analysis

Abstract

Purpose

The purpose of this systematic literature review was to assess the usefulness of the Thyroid Image Reporting and Data System (K-TIRADS) classification proposed by Kwak for differentiation of thyroid nodules.

Material and methods

Four literature databases were searched for relevant articles through early January 2017. A meta-analysis was performed to calculate pooled sensitivity, specificity, positive likelihood ratio (LR+), negative likelihood ratio (LR-) and diagnostic odds ratio (DOR). The area under the curve (AUC) from the pooled receiver operating characteristic (ROC) was used to assess the usefulness of this classification for differentiation of thyroid nodules. Meta-analysis was conducted by using meta-analysis software.

Results

We analysed six publications describing 10,926 nodules. Pooled sensitivity, specificity, LR+, LR-, DOR, and AUC for pooled ROC were 0.983 (95 % CI 0.976–0.989), 0.552 (95 % CI 0.542–0.562), 2.666 (95 % CI 1.692–4.198), 0.05 (95 % CI 0.035–0.072), 51.020 (95 % CI 15.241–170.79) and 0.938, respectively.

Conclusions

Kwak TIRADS has high sensitivity and low specificity. Thus, it is very useful to discard the benign cases and to reduce the number of biopsies.

Key Points

• Routine, adequate standardization of thyroid nodules ultrasound classification is mandatory.

• Kwak TIRADS parameters are accurate for differentiating focal thyroid lesions.

• Kwak TIRADS system is simple to apply.

• Kwak TIRADS system may become a useful diagnostic tool.