Evidence map›Paper›PMID 34718769›Full record

ArticleNicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco2022

Optimal Cutoff Concentration of Urinary Cyanoethyl Mercapturic Acid for Differentiating Cigarette Smokers From Nonsmokers.

Deepak Bhandari, Luyu Zhang, Wanzhe Zhu, Víctor R De Jesús, Benjamin C Blount

Abstract read
In one paragraph

Article in Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 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

10 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Article
  4. Review
  5. Smoke exposure associated with higher urinary benzene biomarker muconic acid (MUCA) in Golestan Cohort Study participants.Biomarkers : biochemical indicators of exposure, response, and susceptibility to chemicals · 2023
    Article
  6. Article
  7. Validating Wave 1 (2014) Urinary Cotinine and TNE-2 Cut-points for Differentiating Wave 4 (2017) Cigarette Use from Non-use in the United States Using Data from the PATH Study.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2023
    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.

Deepak BhandariCenters for Disease Control and Prevention, Division of Laboratory Sciences, Tobacco and Volatiles Branch, Atlanta, GA, USA.ORCID 0000-0001-6059-2739
Luyu ZhangCenters for Disease Control and Prevention, Division of Laboratory Sciences, Tobacco and Volatiles Branch, Atlanta, GA, USA.
Wanzhe ZhuCenters for Disease Control and Prevention, Division of Laboratory Sciences, Tobacco and Volatiles Branch, Atlanta, GA, USA.
Víctor R De JesúsCenters for Disease Control and Prevention, Division of Laboratory Sciences, Tobacco and Volatiles Branch, Atlanta, GA, USA.
Benjamin C BlountCenters for Disease Control and Prevention, Division of Laboratory Sciences, Tobacco and Volatiles Branch, Atlanta, GA, USA.

Funding

Intramural CDC HHS CC999999
6 · The paper itself

Abstract

introductionCotinine is a widely used biomarker for classifying cigarette smoking status. However, cotinine does not differentiate between the use of combustible and noncombustible tobacco products. The increasing use of noncombustible tobacco drives the need for a complementary biomarker for distinguishing cigarette smokers from users of noncombustible tobacco products. AIMS AND

methodsWe evaluated the urinary acrylonitrile metabolite, 2CyEMA, as a biomarker of exposure to cigarette smoke in the US population-representative data from the National Health and Nutritional Examination Survey (NHANES). Smoking status was categorized based on the recent tobacco use questionnaire. The receiver operating characteristic (ROC) curve analysis was performed to identify optimal cutoff concentrations by maximizing Youden's J index. The area under the curve (AUC) was used to compare 2CyEMA effectiveness with respect to serum cotinine.

resultsThe overall cutoff concentration for the classification of cigarette smokers from nonsmokers was 7.32 ng/ml with high sensitivity and specificity (≥0.925). When stratified by demographic variables, the cutoff concentrations varied among subgroups based on age, sex, and race/Hispanic origin. Non-Hispanic Blacks had the highest cutoff concentration (15.3 ng/ml), and Hispanics had the lowest (4.63 ng/ml). Females had higher cutoff concentrations (8.80 ng/ml) compared to males (6.10 ng/ml). Among different age groups, the cutoff concentrations varied between 4.63 ng/ml (21-39 years old) and 10.6 ng/ml (for ≥60 years old). We also explored the creatinine adjusted cutoff values.

conclusions2CyEMA is an effective biomarker for distinguishing cigarette smokers from nonsmokers (users of noncombustible tobacco products or nonusers). IMPLICATIONS: Distinguishes smokers from noncombustible tobacco product users.

Indexed as

AcetylcysteineTobacco ProductsBiomarkersChild, PreschoolCotinineFemaleHumansMaleNon-SmokersNutrition SurveysSmokersAcetylcysteineBiomarkersCotinine

Identifiers

PMID34718769
PMCPMC8967795

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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.