NGS-based Thyroscan Genomic Classifier in the Diagnosis of Thyroid Nodules

Thyroid Cancer Clinical Trial

Official title: Prospective, Blinded, Multi-center Clincal Study of NGS-based Thyroscan Genomic Classifier in the Diagnosis of Thyroid Nodules

Status Recruiting

Clinical Trial Summary

The purpose of this study is to evaluate the accuracy of Thyroscan in the differential diagnosis of benign and malignant thyroid nodules with suspecious ultrasound features

Clinical Trial Description

The prevalence of thyroid nodules by high-resolution ultrasound can be as high as 20%, though most of them are benign lesions, only about 5%~15% are malignant lesions. Based on 1.4 billion population in China, there are approximately 280 million thyroid nodule carriers, of which approximately 14~42 million are potential patients with thyroid cancer. Now thyroid cancer is the fastest growing cancer and the 4th most common cancer in women in China. Therefore, the key point in the evaluation of thyroid nodules is the differential diagnosis of benign and malignant nodules. At present, the commonly used imaging and cytological diagnostic techniques for thyroid nodules include ultrasound and ultrasound-guided fine needle aspiration biopsy (FNAB), as well as emerging molecular diagnostic techniques.

The purpose of this study is to evaluate the accuracy of Thyroscan in the diagnosis of benign and malignant thyroid nodules with suspecious ultrasound features. For patients who have signed an informed consent, the subjects undergo fine needle aspiration of thyroid nodules classified as C-TIRADS catagories 3 or 4a under the guidance of ultrasound or palpation before receiving surgical treatment. One needle is used to prepare cytological smear, and one needle is preserved and sent to Thyroscan detection. The histopathological is obtained as the "gold standerd" after surgical treatment. ;

Related Conditions & MeSH terms

• Thyroid Cancer
• Thyroid Diseases
• Thyroid Neoplasms
• Thyroid Nodule

• NCT number: NCT05025046
• Study type: Observational
• Source: Rigen Biotech
• Contact: Liang Hanzi
• Phone: +8613895604662
• Email: liang.hanzi@rigen-bio.com
• Status: Recruiting
• Start date: September 2021
• Completion date: June 2022