Evidence map›Paper›PMID 36014876›Full record

ArticleNutrients2022

Metabolic Obesity Phenotypes and Risk of Lung Cancer: A Prospective Cohort Study of 450,482 UK Biobank Participants.

Fang Shao, Yina Chen, Hongyang Xu, Xin Chen, Jiawei Zhou, Yaqian Wu, Yingdan Tang, Zhongtian Wang, Ruyang Zhang, Theis Lange and 7 more

Open access · goldAbstract read
In one paragraph

Article in Nutrients, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 3 pooled it
1.4field-weighted citation impact, top 18% 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

16 citing papers in PubMed, 3 syntheses or guidelines pooled it, 16 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

17 authors at 4 institutions in 3 countries.

Fang ShaoDepartment of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing 211166, China.ORCID 0000-0002-2551-2956
Yina ChenDepartment of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing 211166, China.
Hongyang XuDepartment of Critical Care Medicine, Wuxi People's Hospital Affiliated to Nanjing Medical University, Wuxi 214023, China.
Xin ChenDepartment of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing 211166, China.
Jiawei ZhouDepartment of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing 211166, China.
Yaqian WuDepartment of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing 211166, China.
Yingdan TangDepartment of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing 211166, China.
Zhongtian WangDepartment of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing 211166, China.
Ruyang ZhangDepartment of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing 211166, China.
Theis LangeSection of Biostatistics, Department of Public Health, Faculty of Health and Medical Sciences, University of Copenhagen, ØsterFarimagsgade 5, 1353 Copenhagen, Denmark.
Hongxia MaDepartment of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing 211166, China.
Zhibin HuDepartment of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing 211166, China.
Hongbing ShenDepartment of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing 211166, China.
David C ChristianiDepartment of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA.ORCID 0000-0002-0301-0242
Feng ChenDepartment of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing 211166, China.
Yang ZhaoDepartment of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing 211166, China.ORCID 0000-0003-1393-7567
Dongfang YouDepartment of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing 211166, China.
Nanjing Medical University · CNHarvard University · USUniversity of Copenhagen · DKWuxi People's Hospital · CN

Funding

Statistical Methods for Analysis of Massive Genetic and Genomic Data in Cancer ResearchR35CA197449 · NCI · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI XIHONG LIN · 2015 to 2026
$10.9M
Medical Research Council MC_PC_17228Medical Research Council MC_QA137853NCI NIH HHS R35 CA197449
6 · The paper itself

Abstract

(1) Background: The association between metabolic obesity phenotypes and incident lung cancer (LC) remains unclear. (2) Methods: Based on the combination of baseline BMI categories and metabolic health status, participants were categorized into eight groups: metabolically healthy underweight (MHUW), metabolically unhealthy underweight (MUUW), metabolically healthy normal (MHN), metabolically unhealthy normal (MUN), metabolically healthy overweight (MHOW), metabolically unhealthy overweight (MUOW), metabolically healthy obesity (MHO), and metabolically unhealthy obesity (MUO). The Cox proportional hazards model and Mendelian randomization (MR) were applied to assess the association between metabolic obesity phenotypes with LC risk. (3) Results: During a median follow-up of 9.1 years, 3654 incident LC patients were confirmed among 450,482 individuals. Compared with participants with MHN, those with MUUW had higher rates of incident LC (hazard ratio (HR) = 3.24, 95% confidence interval (CI) = 1.33-7.87,

Indexed as

Lung NeoplasmsMetabolic SyndromeObesity, Metabolically BenignBiological Specimen BanksBody Mass IndexHumansObesityOverweightPhenotypeProspective StudiesRisk FactorsThinnessUnited Kingdomlung cancerMendelian randomizationmetabolically healthy obesitymetabolic obesity phenotypes

Identifiers

PMID36014876
PMCPMC9414360
OpenAlexW4293065429

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.