Evidence map›Paper›PMID 36544708›Full record

ArticleFrontiers in oncology2022

Assessing the causality between thyroid and breast neoplasms: A bidirectional Mendelian randomization study.

Zhenqi Li, Lu Xia, Xiangzhi Li, Hongyang He

Open access · goldAbstract read
In one paragraph

Article in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.2field-weighted citation impact, top 11% 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

6 citing papers in PubMed, 10 citations in OpenAlex.

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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 at 3 institutions in 1 country.

Zhenqi LiSchool of Clinical Medicine, Dali University, Dali, China.
Lu XiaSchool of Clinical Medicine, Dali University, Dali, China.
Xiangzhi LiCollege of Life Science, Shaanxi Normal University, Xi'an, China.
Hongyang HeDepartment of General Surgery, The First Affiliated Hospital of Dali University, Dali, China.
Dali University · CNDalian Medical University · CNShaanxi Normal University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aim: This study aimed to evaluate the association between thyroid neoplasms (TN) and the risk of developing breast neoplasms (BN) by assessing data on single nucleotide polymorphisms (SNPs) obtained from the Deutsches Krebsforschungszentrum (DKFZ) and Breast Cancer Association (BCAC). Methods: Data on SNPs associated with TN and BN were obtained from DKFZ and BCAC, respectively. Secondary data analysis of all pooled data from genome-wide association studies (GWAS) was performed to identify the genetic loci closely associated with TN or BN as instrumental variables (IVs). To evaluate the causal relationship between TN and BN, a bidirectional Mendelian randomization (MR) analysis was performed using MR Egger regression, weighted median, inverse variance weighted (IVW) random effects model, simple mode, weighted mode, maximum likelihood, penalized weighted median, IVW radial, IVW fixed effects, and robust adjusted profile scores (RAPS) method. Results: The MR in this study demonstrated a modest reverse causal relationship between TN and BN but a significant positive causal relationship between BN and TN. Conclusions: The MR of this study provided genetic evidence suggesting an association between BN and TN; however, further research is warranted to explore the potential mechanism of interaction between these two malignancies. Moreover, general breast screening should be performed in individuals with TN, but TN screening should be reinforced in individuals with BN.

Indexed as

breast neoplasmsdatabasegeneticsMendelian randomization analysisthyroid neoplasms

Identifiers

PMID36544708
PMCPMC9760946
OpenAlexW4310675685

What OpenQuestion holds

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LicenceCC BY
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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.