Protein Classifier for Thyroid Indeterminate Nodules
Study Details
Study Description
Brief Summary
In multi-center, prospective, double-blind cohorts, PCT-DIA/MS protein classifier supported by artificial neural networks will be validated to classify thyroid indeterminate nodules.
Condition or Disease | Intervention/Treatment | Phase |
---|---|---|
|
N/A |
Study Design
Arms and Interventions
Arm | Intervention/Treatment |
---|---|
Experimental: PCT-DIA/MS PCT-DIA/MS protein classifier supported by artificial neural networks will be validated to classify thyroid indeterminate nodules |
Diagnostic Test: PCT-DIA/MS
PCT-DIA/MS will be validated to classify FNA biopsy specimens
|
Outcome Measures
Primary Outcome Measures
- protein classifier [immediately after the procedure]
classify thyroid indeterminate nodules as Benign or Malignant
Eligibility Criteria
Criteria
Inclusion Criteria:
-
Patients with aged 18 to 70 years old;
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Patients with thyroid nodules who have not been treated with drugs;
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Patients who were diagnosed as Bethesda III and IV by cytology and pathology before operation;
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Patients who underwent total / partial thyroidectomy and had histopathological reports of corresponding cellular pathological punctured nodules;
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Patients voluntarily participate in the study after informed consent.
Exclusion Criteria:
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Patients without operation;
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Patients with insufficient FNA sample size (judged by the laboratory).
Contacts and Locations
Locations
Site | City | State | Country | Postal Code | |
---|---|---|---|---|---|
1 | Hangzhou First People's Hospital Affiliated to Zhejiang University Medical College | Hangzhou | Zhejiang | China | 317500 |
Sponsors and Collaborators
- Luo Dingcun
Investigators
- Principal Investigator: Dingcun Luo, First People's Hospital of Hangzhou
Study Documents (Full-Text)
None provided.More Information
Publications
None provided.- ZhejiangU20200701