Evidence map›Paper›PMID 36811728›Full record

ReviewDiscover oncology2023

Metabolic syndrome and thyroid Cancer: risk, prognosis, and mechanism.

Ling-Rui Li, Jun-Long Song, Han-Qing Liu, Chuang Chen

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Discover oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

24 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  15. Thyroid cancer and insulin resistance.Reviews in endocrine & metabolic disorders · 2024
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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

4 authors.

Ling-Rui Li *Department of Breast and Thyroid Surgery, Renmin Hospital of Wuhan University, No. 238 Jieang Road, Wuchang District, Wuhan, 430060, Hubei, PR China.
Jun-Long Song *Department of Breast and Thyroid Surgery, Renmin Hospital of Wuhan University, No. 238 Jieang Road, Wuchang District, Wuhan, 430060, Hubei, PR China.
Han-Qing LiuDepartment of Breast and Thyroid Surgery, Renmin Hospital of Wuhan University, No. 238 Jieang Road, Wuchang District, Wuhan, 430060, Hubei, PR China.
Chuang ChenDepartment of Breast and Thyroid Surgery, Renmin Hospital of Wuhan University, No. 238 Jieang Road, Wuchang District, Wuhan, 430060, Hubei, PR China. chenc0678@126.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The increasing incidence of thyroid cancer (TC) cannot be fully explained by overdiagnosis. Metabolic syndrome (Met S) is highly prevalent due to the modern lifestyle, which can lead to the development of tumors. This review expounds on the relationship between Met S and TC risk, prognosis and its possible biological mechanism. Met S and its components were associated with an increased risk and aggressiveness of TC, and there were gender differences in most studies. Abnormal metabolism places the body in a state of chronic inflammation for a long time, and thyroid-stimulating hormones may initiate tumorigenesis. Insulin resistance has a central role assisted by adipokines, angiotensin II, and estrogen. Together, these factors contribute to the progression of TC. Therefore, direct predictors of metabolic disorders (e.g., central obesity, insulin resistance and apolipoprotein levels) are expected to become new markers for diagnosis and prognosis. cAMP, insulin-like growth factor axis, angiotensin II, and AMPK-related signaling pathways could provide new targets for TC treatment.

Indexed as

Biological mechanismMetabolic syndromePrognosisRisk factorThyroid cancer

Identifiers

PMID36811728
PMCPMC9947216

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Registered trials

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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.