The incidence of thyroid cancer has been rapidly increased in the past two decades [1]. Papillary thyroid cancer (PTC) is the most common subtype of thyroid cancer accounting for over 85% of cases [2]. Currently obstacles continue to exist in discriminating PTC from benign thyroid nodules (BTN).
Ultrasonic detection is widely accepted in diagnostic algorithm of thyroid nodules. But evidences proposed that evaluation bias and deviations were unavoidable due to sonographers’ subjective factors [3,4]. Fine needle aspiration cytology (FNAC) is recognized as golden standard for preoperative diagnosis of thyroid nodules [5]. However, FNAC fails to classify thyroid nodules in 37% of cases as indeterminate results[6]. Therefore, more precise and less invasive methods are urgently needed to discriminate PTC from thyroid nodules and aid the selection of optimal management.
We identified a novel metabolic biomarker signature for discrimination of PTC from BTN. A metabolic biomarker panel (17 differential metabolites) was identified to discriminate PTC from BTN with an AUC of 97.03%, 91.89% sensitivity and 92.63% specificity in discovery cohort. The panel had an AUC of 92.72%, 86.57% sensitivity and 92.50% specificity in validation cohort (Figure 1). The metabolic biomarker signature could correctly identify 84.09% patients whose nodules were histological benign but were suspected malignant by ultrasonography. Moreover, high accuracy of 87.88% for diagnosis of papillary thyroid microcarcinoma was displayed and showed significant improvement in accuracy, AUC and specificity when compared with ultrasound.
This study identified novel less invasive plasma metabolic biomarker panel for the diagnosis of patients with malignant thyroid nodules and the clinical use of this biomarker panel would have improved diagnosis stratification of thyroid microcarcinoma in comparison to ultrasound.
References
1Â Chen W, Zheng R, Baade PD, Zhang S, Zeng H, Bray F et al. Cancer statistics in China, 2015. CA Cancer J Clin 2016; 66: 115-132.
2 Cabanillas ME, McFadden DG, Durante C. Thyroid cancer. The Lancet 2016; 388: 2783-2795.
3 Brito JP, Gionfriddo MR, Al Nofal A, Boehmer KR, Leppin AL, Reading C et al. The accuracy of thyroid nodule ultrasound to predict thyroid cancer: systematic review and meta-analysis. J Clin Endocrinol Metab 2014; 99: 1253-1263.
4 Tessler FN, Middleton WD, Grant EG, Hoang JK, Berland LL, Teefey SA et al. ACR Thyroid Imaging, Reporting and Data System (TI-RADS): White Paper of the ACR TI-RADS Committee. J Am Coll Radiol 2017; 14: 587-595.
5 Haugen BR, Alexander EK, Bible KC, Doherty GM, Mandel SJ, Nikiforov YE et al. 2015 American Thyroid Association Management Guidelines for Adult Patients with Thyroid Nodules and Differentiated Thyroid Cancer: The American Thyroid Association Guidelines Task Force on Thyroid Nodules and Differentiated Thyroid Cancer. Thyroid 2016; 26: 1-133.
6 Manning AM, Yang H, Falciglia M, Mark JR, Steward DL. Thyroid Ultrasound-Guided Fine-Needle Aspiration Cytology Results: Observed Increase in Indeterminate Rate over the Past Decade. Otolaryngol Head Neck Surg 2017; 156: 611-615.