Evidence map›Paper›PMID 36339468›Full record

ArticleJournal of geriatric cardiology : JGC2022

Inflammation-based different association between anatomical severity of coronary artery disease and lung cancer.

Ya-Wei Zhao, Kai-Xin Yan, Ming-Zhuang Sun, Yi-Hao Wang, Yun-Dai Chen, Shun-Ying Hu

Open access · greenAbstract read
In one paragraph

Article in Journal of geriatric cardiology : JGC, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
1.2field-weighted citation impact, top 19% 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

12 citing papers in PubMed, 12 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 2 institutions in 1 country.

Ya-Wei ZhaoDepartment of Cardiology, Chinese PLA General Hospital, Beijing, China.
Kai-Xin YanDepartment of Cardiology, Chinese PLA General Hospital, Beijing, China.
Ming-Zhuang SunDepartment of Cardiology, Chinese PLA General Hospital, Beijing, China.
Yi-Hao WangDepartment of Cardiology, Chinese PLA General Hospital, Beijing, China.
Yun-Dai ChenDepartment of Cardiology, Chinese PLA General Hospital, Beijing, China.
Shun-Ying HuDepartment of Cardiology, Chinese PLA General Hospital, Beijing, China.
Chinese PLA General Hospital · CNPLA Academy of Military Science · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCoronary artery disease (CAD) is associated with cancer. The role of inflammation in the association of CAD with cancer remains unclear. The study investigated whether inflammation could impact the relationship between CAD and lung cancer.

methodsThe study involved 96 newly diagnosed lung cancer patients without receiving anti-cancer therapy and 288 matched non-cancer patients. All the patients underwent coronary angiography and were free from previous percutaneous coronary intervention or coronary artery bypass grafting. SYNTAX score (SXscore) were used to assess severity of CAD. High SXscore (SXhigh) grade was defined as SXscore > 16 (highest quartile). Neutrophil-to-lymphocyte ratio (NLR) served as an inflammatory biomarker. NLR-high grade referred to NLR > 2.221 (median).

resultsAmong 384 study patients, 380 patients (98.96%) had NLR value (median: 2.221, interquartile range: 1.637-3.040). Compared to non-cancer patients, lung cancer patients had higher rate of SXhigh among total study patients (

conclusionsInflammation could lead different association between anatomical severity of CAD and lung cancer. Severity of CAD was significantly associated with increased risk of lung cancer among patients with high inflammation rather than among patients with low inflammation.

Identifiers

PMID36339468
PMCPMC9630004
OpenAlexW4308549323

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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.