INTRODUCTION: Cotinine 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 METHODS: We 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. RESULTS: The 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. CONCLUSIONS: 2CyEMA 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. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco 2021.
INTRODUCTION: Cotinine 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 METHODS: We 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. RESULTS: The 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. CONCLUSIONS: 2CyEMA 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. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco 2021.
Authors: Baoyun Xia; Benjamin C Blount; Tonya Guillot; Christina Brosius; Yao Li; Dana M Van Bemmel; Heather L Kimmel; Cindy M Chang; Nicolette Borek; Kathryn C Edwards; Charlie Lawrence; Andrew Hyland; Maciej L Goniewicz; Brittany N Pine; Yang Xia; John T Bernert; B Rey De Castro; John Lee; Justin L Brown; Stephen Arnstein; Diane Choi; Erin L Wade; Dorothy Hatsukami; Gladys Ervies; Angel Cobos; Keegan Nicodemus; Dana Freeman; Stephen S Hecht; Kevin Conway; Lanqing Wang Journal: Nicotine Tob Res Date: 2021-02-16 Impact factor: 4.244
Authors: Gideon St Helen; Evangelia Liakoni; Natalie Nardone; Newton Addo; Peyton Jacob; Neal L Benowitz Journal: Cancer Prev Res (Phila) Date: 2019-09-25
Authors: Neal L Benowitz; John T Bernert; Jonathan Foulds; Stephen S Hecht; Peyton Jacob; Martin J Jarvis; Anne Joseph; Cheryl Oncken; Megan E Piper Journal: Nicotine Tob Res Date: 2020-06-12 Impact factor: 4.244
Authors: Thomas B Starr; Christine Gause; Ada O Youk; Roslyn Stone; Gary M Marsh; James J Collins Journal: Risk Anal Date: 2004-06 Impact factor: 4.000
Authors: Denise S Tevis; Sharon R Flores; Brandon M Kenwood; Deepak Bhandari; Peyton Jacob; Jia Liu; Pawel K Lorkiewicz; Daniel J Conklin; Stephen S Hecht; Maciej L Goniewicz; Benjamin C Blount; Víctor R De Jesús Journal: Int J Hyg Environ Health Date: 2021-05-04 Impact factor: 7.401
Authors: Kristy Marynak; Margaret Mahoney; Kisha-Ann S Williams; Michael A Tynan; Elizabeth Reimels; Brian A King Journal: MMWR Morb Mortal Wkly Rep Date: 2020-02-21 Impact factor: 17.586
Authors: David L Ashley; Víctor R De Jesús; Osama A Abulseoud; Marilyn A Huestis; Daniel F Milan; Benjamin C Blount Journal: Int J Environ Res Public Health Date: 2020-09-04 Impact factor: 3.390
Authors: Kevin T Caron; Wanzhe Zhu; John T Bernert; Lanqing Wang; Benjamin C Blount; Kristin Dortch; Ronald E Hunter; Tia Harmon; J Ricky Akins; James Tsai; David M Homa; James L Pirkle; Connie S Sosnoff Journal: Int J Environ Res Public Health Date: 2022-05-11 Impact factor: 4.614