ReviewInternational journal of molecular sciences2017
Molecular Signature of Indeterminate Thyroid Lesions: Current Methods to Improve Fine Needle Aspiration Cytology (FNAC) Diagnosis.
Review in International journal of molecular sciences, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04285476 (Study of the Predictive Value of a Signature of microRNA in Thyroid Cytologies of Undetermined Type), which is not on this map. Cited by 12 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Study of the Predictive Value of a Signature of microRNA in Thyroid Cytologies of Undetermined Type
Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Systematic Review and Meta-Analysis to Identify the Immunocytochemical Markers Effective in Delineating Benign from Malignant Thyroid Lesions in FNAC Samples.Endocrine pathology · 2022Pooled it
- Inside the Matrix: Integrated Cytology and Molecular Testing of Thyroid FNAC Samples Using a Commercial Synthetic 3D Scaffold.International journal of molecular sciences · 2025Article
- SWE, C-TIRADS and AI-assisted diagnostic systems in distinguishing thyroid nodules of different lesion size: Which has better diagnostic performance?Frontiers in endocrinology · 2025Article
- High-Resolution Tactile-Sensation Diagnostic Imaging System for Thyroid Cancer.Sensors (Basel, Switzerland) · 2023Article
- PAPPA Expression in Indeterminate Thyroid Nodules as Screening Test to Select Patients for Molecular Testing.International journal of molecular sciences · 2022Article
- Protein Signatures and Tissue Diagnosis of Pancreatic Cancer.Journal of the American College of Surgeons · 2020Article
- Cell and Molecular Biology of Thyroid Disorders.International journal of molecular sciences · 2019Article
- Therapeutic advances in anaplastic thyroid cancer: a current perspective.Molecular cancer · 2018Review
- Current controversies and future directions in the diagnosis and management of differentiated thyroid cancers.Gland surgery · 2018Review
- Current Knowledge in Thyroid Cancer-From Bench to Bedside.International journal of molecular sciences · 2017Article
- Molecular Testing forJournal of cytologyArticle
- Performance of European Thyroid Imaging Reporting and Data System in Stratifying Malignancy Risk of Thyroid Nodules: A Prospective Study.Journal of medical ultrasoundArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Fine needle aspiration cytology (FNAC) represents the gold standard for determining the nature of thyroid nodules. It is a reliable method with good sensitivity and specificity. However, indeterminate lesions remain a diagnostic challenge and researchers have contributed molecular markers to search for in cytological material to refine FNAC diagnosis and avoid unnecessary surgeries. Nowadays, several "home-made" methods as well as commercial tests are available to investigate the molecular signature of an aspirate. Moreover, other markers (i.e., microRNA, and circulating tumor cells) have been proposed to discriminate benign from malignant thyroid lesions. Here, we review the literature and provide data from our laboratory on mutational analysis of FNAC material and circulating microRNA expression obtained in the last 6 years.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.