Evidence map›Paper›PMID 33924149›Full record

ArticleCancers2021

Associations of Variability in Metabolic Parameters with Lung Cancer: A Nationwide Population-Based Study.

In Young Cho, Kyungdo Han, Dong Wook Shin, Mi Hee Cho, Jung Eun Yoo, Jong Ho Cho

Abstract read
In one paragraph

Article in Cancers, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–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

9 citing papers in PubMed.

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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.

In Young ChoDepartment of Family Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul 03181, Korea.
Kyungdo HanDepartment of Statistics and Actuarial Science, Soongsil University, Seoul 06978, Korea.
Dong Wook ShinDepartment of Family Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Korea.
Mi Hee ChoSamsung C&T Medical Clinic, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul 03181, Korea.
Jung Eun YooDepartment of Family Medicine, Healthcare System Gangnam Center, Seoul National University Hospital, Seoul 06236, Korea.
Jong Ho ChoDepartment of Thoracic Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We investigated whether visit-to-visit variability in metabolic parameters is associated with lung cancer risk. We used nationally representative data from the Korean National Health Insurance System, and 8,011,209 lung-cancer-free subjects who underwent over three health examinations from 2005 to 2010 were followed until 2017. Variability of fasting blood glucose, total cholesterol, systolic blood pressure, and body weight were measured by the variability independent of the mean, assessed by quartiles. There were 44,982 lung cancer events. The hazard ratio (HR) and 95% confidence interval (CI) for lung cancer risk was 1.07 (1.04, 1.10) for fasting blood glucose in the highest quartile, 1.08 (1.05, 1.10) for systolic blood pressure, 1.04 (1.01, 1.07) for weight, and 1.11 (1.08, 1.14) for total cholesterol. When comparing ≥3 vs. 0 high-variability metabolic parameters, the HR for lung cancer was 1.18 (95% CI, 1.14, 1.22). However, while ≥3 high-variability parameters showed an increased lung cancer risk in men (HR 1.26, 95% CI 1.21, 1.31), women did not show increased risk (HR 0.99, 95% CI 0.92, 1.06). High variability in each metabolic parameter, and a higher number of high-variability parameters, were associated with increased lung cancer risk.

Indexed as

blood pressurebody weightcholesterolglucoselung cancerrisk factors

Identifiers

PMID33924149
PMCPMC8074362

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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.