Purpose

A clinical trial is proposed, to clinically validate, in a US population, the diagnostic performance of a new genetic test (ThyroidPrint). It will determine the nature of thyroid nodules that have been informed as indeterminate by cytology through a fine needle aspiration (FNA). The Genetic Classifier for Indeterminate Thyroid Nodules is a test that determines the expression of a panel of 10 biomarkers (CXCR3, CCR3, CXCl10, CK19, TIMP1, CLDN1, CAR, XB130, HO-1 and CCR7). Gene expression data is analyzed through an algorithm that generates a composite score that predicts the risk of malignancy. It´s intended use is for patients with thyroid cytology as indeterminate (Bethesda III and IV, according to The Bethesda System for Reporting Thyroid Cytopathology). This test uses a fine needle aspiration (FNA) sample.

Condition

Eligibility

Eligible Ages
Over 18 Years
Eligible Genders
All
Accepts Healthy Volunteers
No

Inclusion Criteria

  1. Patients undergoing FNA of a thyroid nodule. 2. Thyroid nodule greater 1cm 3. Age greater 18 years old.

Exclusion Criteria

  1. Thyroid nodule greater 1cm 2. Patients less than 18 years old, 3. Previous history of coagulation disorders and patients. 4. Ultrasound evidence of malignant cervical adenopathy.

Study Design

Phase
Study Type
Observational
Observational Model
Cohort
Time Perspective
Prospective

Recruiting Locations

Tulane University
New Orleans, Louisiana
Contact:
Emad Kandil, MD

More Details

Status
Unknown status
Sponsor
Pontificia Universidad Catolica de Chile

Study Contact

Hernan E Gonzalez, MD, PhD
+56999734312
hgonzale@med.puc.cl

Detailed Description

Thyroid nodules are a very frequent condition reaching up to 30-40% of the adult population. Although most thyroid nodules have little clinical significance, in many cases a fine needle aspirate (FNA) biopsy will be performed to determine its nature. In 70% of cases, a FNA will be reported as benign and in 10% of cases as cancer. However, the remaining 20% of cases the thyroid nodule will be reported as indeterminate. The latter patients have a risk of malignancy ranging from 15 to 25%, and in most cases the patient will undergo thyroid lobectomy or total thyroidectomy to determine the final pathology, resulting in an unacceptable number of unnecessary surgeries. This has a major health impact, including surgical risks and permanent hormonal supplementation, as well as unwarranted health costs estimated at 1.6 billion USD. Therefore, there is a need for diagnostic tools in order to improve the diagnostic accuracy of the FNA and avoidance of the high rate of unnecessary surgeries. GeneproDx has developed a gene expression signature to improve the diagnostic accuracy of FNA biopsy of thyroid nodules reported as indeterminate. The ThyroidPrint diagnostic measures the expression of 10 genes in a FNA sample. It combines the results of the 10 biomarkers using a proprietary algorithm to predict benign thyroid nodules. This assay is classified as multi-analyte algorithm assays (MAAA). The biomarkers consist of multiplex TaqMan® gene expression assays run on Qiagen's Rotor-Gene Q MDx RT-PCR IVD Platform instrument, which is a FDA cleared instrument. The following 10 genes comprise the biomarker panel: CXCR3, CCR3, CXCL10, CK19, TIMP1, CLDN1, CAR, XB130, HO-1 and CCR7. Each gene run in a multiplex configuration with two reference genes. Each assay is performed with Research Use Only (RUO) kits and reagents on a FDA cleared instrument. ThyroidPrint has been developed using two different cohorts of samples, a training set and a testing set. Using linear discriminant analysis, the training set identified the final biomarker panel including; CXCR3, CCR3, CXCL10, CK19, TIMP1, CLDN1, CAR, XB130, HO-1 and CCR7. In brief, the biomarkers have the following significance. CCR3 and CCR7 are chemokine receptors that are highly expressed in papillary thyroid cancer tumor cells. CXCR3 is also a chemokine receptor and along with its receptor, CXCL10, are detected in thyroid autoimmune disease. CAR is a G-couple receptor and has been shown to be involved in cancer and has decreased expression in parathyroid adenoma. CK19 is a keratin and has been used in thyroid tumors to recognize papillary carcinomas. CLDN1 is a structural protein and has been shown to be differentially expressed in tumors compared to normal tissue and has increased mRNA levels in papillary thyroid carcinoma. XB130 is also a structural protein and its expression has been demonstrated in papillary thyroid carcinoma. TIMP1 is a protease inhibitor with mRNA levels increased in advanced stages of thyroid carcinoma. HO- 1 is an oxygenase and its expression has correlates with tumor aggressiveness in thyroid cancer. In the final classifier, the expression of each gene was ̈weighted ̈ based on its individual relative classifying ability. The cutoff score was chosen in the ROC curve generated in the training set based on a minimum Sensitivity of 92% to guarantee a high Negative Predictive Value (>95%). This cutoff score offered a Specificity of 83%.An independent testing set of samples reproduced the diagnostic performance observed in the training set and showed consistent results in FNA samples. The assay has proven to accurately predict benign nodules in thyroid FNA samples with a Negative Predictive Value of 96% and Specificity of 83% in both cohorts. The definitive validation of an MAAA requires a final validation set, which analyzes samples that will be used in the routine clinical setting; in this case indeterminate thyroid nodules samples. In addition, in order to show clinical validity, the validation set must be performed, as a statistically powered multi-institutional trial to assure that the data is applicable to a broad population spectrum and has appropriate confidence intervals. A first, statistically powered, multi-institutional trial is currently underway in Chile to prove Clinical Validity. This trial includes 8 sites and will recruit approximately 3000 FNA to be completed by December 2017.

Notice

Study information shown on this site is derived from ClinicalTrials.gov (a public registry operated by the National Institutes of Health). The listing of studies provided is not certain to be all studies for which you might be eligible. Furthermore, study eligibility requirements can be difficult to understand and may change over time, so it is wise to speak with your medical care provider and individual research study teams when making decisions related to participation.