NCT06969768

Brief Summary

This study aims to refine the molecular classification of thyroid cancer (TC) using a multi-omics approach. By identifying a novel gene set and applying decision-tree modeling, the study seeks to improve diagnostic accuracy and predict tumor progression in BRAFV600E-like and RAS-like TC subtypes. Protein biomarkers were validated via immunohistochemistry (IHC), with findings confirmed across external datasets.

Trial Health

87
On Track

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Enrollment
275

participants targeted

Target at P75+ for all trials

Timeline
Completed

Started Feb 2018

Longer than P75 for all trials

Geographic Reach
1 country

1 active site

Status
completed

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

Study Start

First participant enrolled

February 21, 2018

Completed
3 years until next milestone

Primary Completion

Last participant's last visit for primary outcome

February 21, 2021

Completed
3 years until next milestone

Study Completion

Last participant's last visit for all outcomes

February 28, 2024

Completed
1.2 years until next milestone

First Submitted

Initial submission to the registry

April 30, 2025

Completed
14 days until next milestone

First Posted

Study publicly available on registry

May 14, 2025

Completed
Last Updated

May 14, 2025

Status Verified

May 1, 2025

Enrollment Period

3 years

First QC Date

April 30, 2025

Last Update Submit

May 12, 2025

Conditions

Thyroid Cancer

Keywords

Thyroid cancerProteogenomics

Outcome Measures

Primary Outcomes (1)

  • Classification Accuracy of Gene-Based Model

    The accuracy of the decision-tree model using specific gene set to classify thyroid cancer into BRAFV600E-like, RAS-like, and NT (normal thyroid) -like subtypes. Model performance will be evaluated using accuracy, sensitivity, specificity, and Cohen's kappa.

    1 year

Study Arms (1)

Thyroid cancer

All patients diagnosed with thyroid cancer who underwent thyroidectomy at Seoul National University Hospital

Eligibility Criteria

Age18 Years+
Sexall
Healthy VolunteersNo
Age GroupsAdult (18-64), Older Adult (65+)
Sampling MethodNon-Probability Sample
Study Population

All patients diagnosed with thyroid cancer

You may qualify if:

  • Patients with a confirmed clinical diagnosis of thyroid cancer
  • Availability of surgically resected thyroid tissue suitable for omics analysis

You may not qualify if:

  • \- Patients who have received chemotherapy for other malignancies

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (1)

Seoul National University Hospital

Seoul, South Korea

Location

Biospecimen

Retention: SAMPLES WITHOUT DNA

Surgical specimen

MeSH Terms

Conditions

Thyroid Neoplasms

Condition Hierarchy (Ancestors)

Endocrine Gland NeoplasmsNeoplasms by SiteNeoplasmsHead and Neck NeoplasmsEndocrine System DiseasesThyroid Diseases

Study Design

Study Type
observational
Observational Model
COHORT
Time Perspective
RETROSPECTIVE
Sponsor Type
OTHER
Responsible Party
PRINCIPAL INVESTIGATOR
PI Title
Professor

Study Record Dates

First Submitted

April 30, 2025

First Posted

May 14, 2025

Study Start

February 21, 2018

Primary Completion

February 21, 2021

Study Completion

February 28, 2024

Last Updated

May 14, 2025

Record last verified: 2025-05

Locations

KR(1)