Evidence map›Paper›PMID 31252407›Full record

ArticleEndocrine connections2019

Circulating adipokines and metabolic setting in differentiated thyroid cancer.

Chiara Mele, Maria Teresa Samà, Alessandro Angelo Bisoffi, Marina Caputo, Valentina Bullara, Stefania Mai, Gillian Elisabeth Walker, Flavia Prodam, Paolo Marzullo, Gianluca Aimaretti and 1 more

Open access · goldAbstract read
In one paragraph

Article in Endocrine connections, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 3 pooled it
1.8field-weighted citation impact, top 15% 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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed, 3 syntheses or guidelines pooled it, 19 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Review
  5. Article
  6. Review
  7. Article
  8. Article
  9. Obesity and Thyroid Cancer Risk: An Update.International journal of environmental research and public health · 2022
    Review
  10. Article
  11. Article
  12. Review
  13. 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

11 authors at 5 institutions in 1 country.

Chiara MeleDivision of Endocrinology, Department of Translational Medicine, University of Piemonte Orientale, Novara, Italy.
Maria Teresa SamàDivision of Endocrinology, University Hospital 'Maggiore della Carità', Novara, Italy.
Alessandro Angelo BisoffiDivision of Endocrinology, Department of Translational Medicine, University of Piemonte Orientale, Novara, Italy.
Marina CaputoDivision of Endocrinology, Department of Translational Medicine, University of Piemonte Orientale, Novara, Italy.
Valentina BullaraDivision of Endocrinology, University Hospital 'Maggiore della Carità', Novara, Italy.
Stefania MaiLaboratory of Metabolic Research, Istituto Auxologico Italiano, IRCCS, S. Giuseppe Hospital, Piancavallo di Oggebbio (VB), Italy.
Gillian Elisabeth WalkerDepartment of Health Sciences, University of Piemonte Orientale, Novara, Italy.
Flavia ProdamDepartment of Health Sciences, University of Piemonte Orientale, Novara, Italy.
Paolo MarzulloDivision of Endocrinology, Department of Translational Medicine, University of Piemonte Orientale, Novara, Italy.
Gianluca AimarettiDivision of Endocrinology, Department of Translational Medicine, University of Piemonte Orientale, Novara, Italy.
Loredana PaganoDivision of Endocrinology, Department of Translational Medicine, University of Piemonte Orientale, Novara, Italy.
Università degli Studi del Piemonte Orientale “Amedeo Avogadro” · ITAzienda Ospedaliero Universitaria Maggiore della Carita · ITIRCCS Istituto Auxologico Italiano · ITIstituti di Ricovero e Cura a Carattere Scientifico · ITUniversity of Turin · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The associative link relating insulin resistance (IR) and adipokines to the occurrence and phenotype of differentiated thyroid cancer (DTC) is unknown. The aim of this study was to evaluate the relationship between IR and adipokines in DTC patients, as compared with carriers of benign thyroid diseases (BTD) and healthy controls. This observational study enrolled 77 subjects phenotyped as DTC (N = 30), BTD (N = 27) and healthy subjects (N = 20). Each subject underwent preoperative analysis of anthropometric parameters, thyroid function and autoimmunity, insulin resistance (HOMA-IR) and levels of unacylated (UAG) and acylated ghrelin (AG), obestatin, leptin and adiponectin. Multivariate regression models were used to test the predictive role of metabolic correlates on thyroid phenotypes and DTC extension. The three groups showed similar age, gender distribution, smoking habit, BMI and thyroid parameters. Obestatin was significantly higher in DTC group compared to BTD (P < 0.05) and control subjects (P < 0.0001). DTC and BTD groups showed higher levels of UAG (P < 0.01) and AG (P < 0.05). Leptin levels were comparable between groups, whereas adiponectin levels were lower in DTC compared to BTD group (P < 0.0001) and controls (P < 0.01). In parallel, HOMA-IR was higher in DTC than BTD (P < 0.05) and control group (P < 0.01). Stepwise multivariable regression analysis showed that obestatin and UAG were independent predictors of DTC (P = 0.01 for both). In an analysis restricted to the DTC group, obestatin levels were associated with the absence of lymph node metastases (P < 0.05). Our results highlight a potential association between metabolic setting, circulating adipokines and thyroid cancer phenotype.

Indexed as

adipokineshistological phenotypeinsulin resistancethyroid cancer

Identifiers

PMID31252407
PMCPMC6652238
OpenAlexW2955501656

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.