Evidence map›Paper›PMID 38760801›Full record

ArticleLipids in health and disease2024

Association between metabolic syndrome and kidney cancer risk: a prospective cohort study.

Lin Wang, Han Du, Chao Sheng, Hongji Dai, Kexin Chen

Abstract read
In one paragraph

Article in Lipids in health and disease, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 2 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

8 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
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  8. Review
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

5 authors.

Lin WangDepartment of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Human Major Diseases, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, 300060, China.
Han DuDepartment of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Human Major Diseases, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, 300060, China.
Chao ShengDepartment of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Human Major Diseases, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, 300060, China.
Hongji DaiDepartment of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Human Major Diseases, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, 300060, China. daihongji@tmu.edu.cn.
Kexin ChenDepartment of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Human Major Diseases, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, 300060, China. chenkexin@tmu.edu.cn.

Funding

the 14th five-year Special Project of Cancer Prevention and Treatment for the Youth Talents of Tianjin Cancer Institute and Hospital YQ-08Tianjin Key Medical Discipline (Specialty) Construction Project TJYXZDXK-009ATianjin Municipal Science and Technology Bureau 22JCYBJC01040
6 · The paper itself

Abstract

backgroundKidney cancer has become known as a metabolic disease. However, there is limited evidence linking metabolic syndrome (MetS) with kidney cancer risk. This study aimed to investigate the association between MetS and its components and the risk of kidney cancer.

methodsUK Biobank data was used in this study. MetS was defined as having three or more metabolic abnormalities, while pre-MetS was defined as the presence of one or two metabolic abnormalities. Hazard ratios (HRs) and 95% confidence intervals (CIs) for kidney cancer risk by MetS category were calculated using multivariable Cox proportional hazards models. Subgroup analyses were conducted for age, sex, BMI, smoking status and drinking status. The joint effects of MetS and genetic factors on kidney cancer risk were also analyzed.

resultsThis study included 355,678 participants without cancer at recruitment. During a median follow-up of 11 years, 1203 participants developed kidney cancer. Compared to the metabolically healthy group, participants with pre-MetS (HR= 1.36, 95% CI: 1.06-1.74) or MetS (HR= 1. 70, 95% CI: 1.30-2.23) had a significantly greater risk of kidney cancer. This risk increased with the increasing number of MetS components (P for trend < 0.001). The combination of hypertension, dyslipidemia and central obesity contributed to the highest risk of kidney cancer (HR= 3.03, 95% CI: 1.91-4.80). Compared with participants with non-MetS and low genetic risk, those with MetS and high genetic risk had the highest risk of kidney cancer (HR= 1. 74, 95% CI: 1.41-2.14).

conclusionsBoth pre-MetS and MetS status were positively associated with kidney cancer risk. The risk associated with kidney cancer varied by combinations of MetS components. These findings may offer novel perspectives on the aetiology of kidney cancer and assist in designing primary prevention strategies.

Indexed as

Kidney NeoplasmsMetabolic SyndromeAdultAgedDyslipidemiasFemaleHumansHypertensionMaleMiddle AgedObesity, AbdominalProportional Hazards ModelsProspective StudiesRisk FactorsCentral obesityDyslipidemiaHypertensionMetabolic syndromePolygenic risk scoreRenal cancer

Identifiers

PMID38760801
PMCPMC11100063

What Socratic 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 Socratic graph.