Evidence map›Paper›PMID 39696223›Full record

ArticleBMC pulmonary medicine2024

Integrating genetic and clinical data to predict lung cancer in patients with chronic obstructive pulmonary disease.

Zhan Gu, Yonghui Wu, Fengzhi Yu, Jijia Sun, Lixin Wang

Abstract read
In one paragraph

Article in BMC pulmonary medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

2 citing papers in PubMed.

  1. Article
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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

5 authors.

Zhan GuDepartment of Integrative Medicine, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China.
Yonghui WuDepartment of Integrative Medicine, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China.
Fengzhi YuDepartment of Integrative Medicine, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China.
Jijia SunDepartment of Mathematics and Physics, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Lixin WangDepartment of Integrative Medicine, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China. 1701005@tongji.edu.cn.

Funding

National Natural Science Foundation of China 82004115National Natural Science Foundation of China 82374345Shanghai Key Discipline of Traditional Chinese Medicine Cross Innovation Category
6 · The paper itself

Abstract

backgroundChronic obstructive pulmonary disease (COPD) is closely linked to lung cancer (LC) development. The aim of this study is to identify the genetic and clinical risk factors for LC risk in COPD, according to which the prediction model for LC in COPD was constructed.

methodsThis is a case-control study in which patientis with COPD + LC as the case group, patientis with only COPD as the control group, and patientis with only LC as the second control group. A panel of clinical variables including demographic, environmental and lifestyle factors were collected. A total of 20 single nucleotide polymorphisms (SNPs) were genotyped. The univariate analysis, candidate gene study and multivariate analysis were applied to identify the independent risk factors, as well as the prediction model was constructed. The ROC analysis was used to evaluate the predictive ability of the model.

resultsA total of 503 patients were finally enrolled in this study, with 188 patients for COPD + LC group, 162 patients for COPD group and 153 patients for LC group. The univariate analysis of clincial data showed compared with the patients with COPD, the patients with COPD + LC tended to have significantly lower BMI, higher smoking pack-years, and higher prevalence of emphysema. The results of the candidate gene study showed the rs1489759 in HHIP and rs56113850 in CYP2A6 demonstrated significant differences between COPD and COPD + LC groups. By using multivariate logistic regression analysis, four variables including BMI, pack-years, emphysema and rs56113850 were identified as independent risk factors for LC in COPD and the prediction model integrating genetic and clinical data was constructed. The AUC of the prediction model for LC in COPD reached 0.712, and the AUC of the model for predicting LC in serious COPD reached up to 0.836.

conclusionThe rs56113850 (risk allele C) in CYP2A6, decrease in BMI, increase in pack-years and emphysema presence were independent risk factors for LC in COPD. Integrating genetic and clinical data for predicting LC in COPD demonstrated favorable predictive performance.

Indexed as

Lung NeoplasmsPolymorphism, Single NucleotidePulmonary Disease, Chronic ObstructiveAgedCase-Control StudiesFemaleGenetic Predisposition to DiseaseGenotypeHumansLogistic ModelsMaleMiddle AgedRisk FactorsROC CurveSmokingChronic obstructive pulmonary diseaseLung cancerPrediction modelRisk factorsSingle nucleotide polymorphisms

Identifiers

PMID39696223
PMCPMC11656926

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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.