Evidence map›Paper›PMID 36710862›Full record

SynthesisPeerJ2023

Body mass index and the risk of basal cell carcinoma: evidence from Mendelian randomization analysis.

Likui Lu, Bangbei Wan, Hongtao Zeng, Jun Guo, Min Li, Miao Sun

Open access · goldAbstract readMeta-Analysis
In one paragraph

Synthesis in PeerJ, 2023. 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
0.9field-weighted citation impact, top 26% 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, 6 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

6 authors at 3 institutions in 1 country.

Likui Lu *Institute for Fetology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China.
Bangbei Wan *Reproductive Medical Center, Hainan Women and Children's Medical Center, Haikou, Hainan, China.
Hongtao ZengInstitute for Fetology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China.
Jun GuoInstitute for Fetology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China.
Min LiDepartment of Dermatology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China.
Miao SunInstitute for Fetology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China.
First Affiliated Hospital of Soochow University · CNSoochow University · CNHainan Medical University · CN

Funding

Medical Research Council MC_PC_17228Medical Research Council MC_QA137853
6 · The paper itself

Abstract

Objective: We aim to test whether body mass index (BMI) is causally associated with the risk of basal cell carcinoma (BCC) using Mendelian randomization (MR) analysis. Methods: Single-nucleotide polymorphisms (SNPs) associated with four BMI-related traits were screened Results: Two-sample MR analysis showed inverse associations between genetically predicted BMI and BCC risk. Moreover, when exposure and outcome were switched to see if reverse causation was possible, there was no evidence of a cause-and-effect relationship from BCC to BMI. Finally, the meta-analysis also showed a strong negative causal relationship between BMI and BCC. Conclusion: Genetical predicted higher BMI were associated with lower BCC risk. Further research is required to comprehend the mechanisms underlying this putative causative association.

Indexed as

Basal Cell CarcinomaGenome-Wide Association StudyBody Mass IndexCausalityHumansMendelian Randomization AnalysisBasal cell carcinomaBody mass indexGenome-wide association studyMendelian randomizationSingle-nucleotide polymorphisms

Identifiers

PMID36710862
PMCPMC9881466
OpenAlexW4317829638

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.