RESUMEN
Objective To compare diagnostic values of the 2015 American Thyroid Association (ATA) Management Guidelines for Adult Patients with Thyroid Nodules and Differentiated Thyroid Cancer with the thyroid imaging reporting and data system (TI-RADS) for sonographic malignancy risk stratification of thyroid nodules.Methods From November 2011 to December 2015,485 thyroid nodules in 331 patients (mean age,42.9 years± 10.4)were included in this study.Characteristics includingsize,composition,shape(nonparallel or parallel),margin,echogenicity,calcifications and extrathyroidal extension of thyroid nodules were evaluated.Every nodule was stratificated by criteria set by TI-RADS and ATA guidelines,and malignant rate of each risk stratification were calculated and analysed.With pathology as the gold standard,different cutoff were taken to diagnose malignant nodules,and the sensitivity,specifity,positive predictive value,negativepredictive value and accuracy of the two methodologies were calculated at each cutoff.And the two methodologies were evaluated and measured by ROC curve.Finally their Kappa value were calculated at the best cutoff.Results Of the 485 thyroid nodules,96 were benign and 389 were malignant.The malignancy rates under TI-RADS category 2,3,4a,4b,4c,and 5 nodules were 0,12.0％ (3/25),22.2％ (10/45),29.8％ (14/47),99.2％ (261/363) and 100％ (101/101).Malignancy rates under ATA guidelines of benign,very low,low,intermediate,and high suspicion for malignancy were 0,12.5％ (1/8),16.1％ (10/62),27.7％ (13/47),and 99.2％ (365/368).There were significant differences inside each patterns (P ＜ 0.01) respectively and high correlation between risk stratification with TI-RADS (r=0.70) and ATA guidelines (r=0.83).Areas under the ROC curve of the TI-RADS and ATA guidelines classifications were 0.966 and 0.959.Best cut-off point for diagnosing malignant by TI-RADS and ATA guideline classifications were ≥ 4c and ≥ high suspicion,and at that point,diagnostic value of TI-RADS and ATA guidelines were nearly the same(sensitivity,93.1％vs 93.8％;specificity,97.9％ vs 96.9％;PPV,99.5％ vs 99.2％;NPV,75.7％vs 79.5％;and accuracy,94.0％vs94.4％),and there was no significant differences (P=0.50,P=0.50,P=0.50,P=0.53,P=0.55),Kappa=0.97.Conclusions Both TI-RADS and the ATA guidelinesprovide effective malignancy risk stratification for thyroid nodules.The diagnosticvalue of TI-RADS when considering ≥ 4c and ATA guidelines when considering ≥ high-suspicion nodules as malignant were nearly the same and both high.
RESUMEN
To compare the diagnostic value between the thyroid imaging reporting and data system ( TIRADS) and ultrasound ( US ) patterns of 2015 American Thyroid Association ( ATA ) guidelines in the differentiation of benign and malignant thyroid nodules. 639 patients in Jiangsu province who were scheduled for ultrasound-guided fine-needle aspiration biopsy or thyroidectomy were recruited for the retrospective study. All of them were categorized based on TIRADS and ultrasound patterns of ATA ( 2015 ) guidelines. The receiver operating characteristic curve was established to assess and compare the diagnostic value of the two models. Results:( 1 ) 639 patients with 847 thyroid nodules were included in this study, 510 females and 129 males. The mean age was (46. 77 ±12.98)yearsold. (2)818nodulescouldbeclassifiedaccordingtoTIRADS. ThemalignancyratesofTIRADS2,3, 4A, 4B, 5 were 0, 15. 9%, 49. 1%, 78. 8% ,and 100%, respectively. (3) Ultrasound patterns of ATA could be assigned to 793 nodules. The malignancy rates of nodules with very low, low, intermediate, high suspicion for malignancy were 6. 2%, 10. 3%, 24. 9% and 70. 1%, respectively. (4) Ultrasound patterns of ATA had higher specificity (77. 9%) compared to TIRADS. The sensitivity and area under curve of ultrasound patterns of ATA were lower than those of TIRADS, though, not significant. Ultrasound patterns of ATA(2015) guidelines may yield higher specificity in the differential diagnosis of benign and malignant thyroid nodules, while TIRADS classification may offer a relatively higher sensitivity and area under curve.