Evidence map›Paper›PMID 30937722›Full record

ReviewEndocrine2019

Advances in metabolomics of thyroid cancer diagnosis and metabolic regulation.

Raziyeh Abooshahab, Morteza Gholami, Maryam Sanoie, Fereidoun Azizi, Mehdi Hedayati

Registry-linked trialAbstract readReview
PubMed Publisher
In one paragraph

Review in Endocrine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06829043 (Utilizzo Della 18F-FDG PET/TC Per Stratificare il Rischio di malignità Dei Noduli Tiroidei a Citologia Indeterminata), which is not on this map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed
2.1field-weighted citation impact, top 13% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

NCT06829043 enrolling by invitationnot on this mapstarted 2022, after this paper: background citation

Utilizzo Della 18F-FDG PET/TC Per Stratificare il Rischio di malignità Dei Noduli Tiroidei a Citologia Indeterminata (TIR3A e TIR3B)

TypeobservationalSponsorIRCCS Azienda Ospedaliero-Universitaria di BolognaRan2022 to 2027Enrolled216ConditionsPET / CT, FDG PET/CT, Cytology, Thyroid NodulesArmsclinical practice drug treatment
3 · Its place in the literature

Who cites it

29 citing papers in PubMed, 45 citations in OpenAlex.

  1. Trial
  2. Review
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Review
  9. Article
  10. Article
  11. Toward Systems-Level Metabolic Analysis in Endocrine Disorders and Cancer.Endocrinology and metabolism (Seoul, Korea) · 2023
    Review
  12. Article
  13. Review
  14. Review
  15. Article
  16. Review
  17. Review
  18. Review
  19. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 1 country.

Raziyeh AbooshahabCellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Morteza GholamiCellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Maryam SanoieCellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Fereidoun AziziEndocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Mehdi HedayatiCellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran. hedayati47@gmail.com.
Research Institute for Endocrine Sciences · IRShahid Beheshti University of Medical Sciences · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Thyroid cancers (TCs) are the most frequent endocrine malignancy with an unpredictable fast-growing incidence, especially in females all over the world. Fine-needle aspiration biopsy (FNAB) analysis is an accurate diagnostic method for detecting thyroid nodules and classification of TC. Though simplicity, safety, and accuracy of FNAB, 15-30% of cases are indeterminate, and it is not possible to determine the exact cytology of the specimen. This demands the need for innovative methods capable to find crucial biomarkers with adequate sensitivity for diagnosis and prediction in TC researches. Cancer-based metabolomics is a vast emerging field focused on the detection of a large set of metabolites extracted from biofluids or tissues. Using analytical chemistry procedures allows for the potential recognition of cancer-based metabolites for the purposes of advancing the era of personalized medicine. Nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS) coupled with separation techniques e.g., gas chromatography (GC) and liquid chromatography (LC) are the main approaches for metabolic studies in cancers. The immense metabolite profiling has provided a chance to discover novel biomarkers for early detection of thyroid cancer and reduce unnecessary aggressive surgery. In this review, we recapitulate the recent advances and developed methods of diverse metabolomics tools and metabolic phenotypes of thyroid cancer, following a brief discussion of recent challenges in the thyroid cancer diagnosis.

Indexed as

MetabolomicsBiomarkers, TumorBiopsy, Fine-NeedleChromatography, LiquidHumansMagnetic Resonance SpectroscopyMass SpectrometryThyroid GlandThyroid NeoplasmsThyroid NoduleBiomarkers, TumorEarly detectionGC/MSLC/MSMetabolomicsNMRThyroid cancer diagnosis

Identifiers

PMID30937722
OpenAlexW2930319934

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.