BACKGROUND: Ethyl glucuronide (EtG) in hair has emerged as a useful biomarker for detecting alcohol abuse and monitoring abstinence. However, there is a need to establish a reliable cutoff value for the detection of chronic and excessive alcohol consumption. METHODS: One hundred and twenty-five subjects were classified as teetotalers, low-risk drinkers, at-risk drinkers, or heavy drinkers. The gold standard for subjects' classifications was based on a prospective daily alcohol self-monitoring log. Subjects were followed for a 3-month period. The EtG diagnostic performance was evaluated and compared with carbohydrate-deficient transferring (CDT) and the activities of aspartate aminotransferase, alanine aminotransferase, and γ-glutamyl-transferase (γGT). RESULTS: A cutoff of >9 pg/mg EtG in hair, suggesting an alcohol consumption of >20/30 g (at-risk drinkers), and a cutoff of >25 pg/mg, suggesting a consumption of >60 g (heavy drinkers), were determined by receiver operating characteristic analysis. The EtG diagnostic performance was significantly better (P < 0.05) than any of the traditional biomarkers alone. EtG, as a single biomarker, yielded a stronger or similar diagnostic performance in detecting at-risk or heavy drinkers, respectively, than the best combination of traditional biomarkers (CDT and γGT). The combination of EtG with traditional biomarkers did not improve the diagnostic performance of EtG alone. EtG demonstrated a strong potential to identify heavy alcohol consumption, whereas the traditional biomarkers failed to do so. EtG was not significantly influenced by gender, body mass index, or age. CONCLUSION: Hair EtG definitively provides an accurate and reliable diagnostic test for detecting chronic and excessive alcohol consumption. The proposed cutoff values can serve as reference for future cutoff recommendations for clinical and forensic use.
BACKGROUND:Ethyl glucuronide (EtG) in hair has emerged as a useful biomarker for detecting alcohol abuse and monitoring abstinence. However, there is a need to establish a reliable cutoff value for the detection of chronic and excessive alcohol consumption. METHODS: One hundred and twenty-five subjects were classified as teetotalers, low-risk drinkers, at-risk drinkers, or heavy drinkers. The gold standard for subjects' classifications was based on a prospective daily alcohol self-monitoring log. Subjects were followed for a 3-month period. The EtG diagnostic performance was evaluated and compared with carbohydrate-deficient transferring (CDT) and the activities of aspartate aminotransferase, alanine aminotransferase, and γ-glutamyl-transferase (γGT). RESULTS: A cutoff of >9 pg/mg EtG in hair, suggesting an alcohol consumption of >20/30 g (at-risk drinkers), and a cutoff of >25 pg/mg, suggesting a consumption of >60 g (heavy drinkers), were determined by receiver operating characteristic analysis. The EtG diagnostic performance was significantly better (P < 0.05) than any of the traditional biomarkers alone. EtG, as a single biomarker, yielded a stronger or similar diagnostic performance in detecting at-risk or heavy drinkers, respectively, than the best combination of traditional biomarkers (CDT and γGT). The combination of EtG with traditional biomarkers did not improve the diagnostic performance of EtG alone. EtG demonstrated a strong potential to identify heavy alcohol consumption, whereas the traditional biomarkers failed to do so. EtG was not significantly influenced by gender, body mass index, or age. CONCLUSION: Hair EtG definitively provides an accurate and reliable diagnostic test for detecting chronic and excessive alcohol consumption. The proposed cutoff values can serve as reference for future cutoff recommendations for clinical and forensic use.
Authors: Hicham Kharbouche; Nadia Steiner; Marie Morelato; Christian Staub; Benjamin Boutrel; Patrice Mangin; Frank Sporkert; Marc Augsburger Journal: Alcohol Date: 2010-07-03 Impact factor: 2.405
Authors: Daniela Rinck; Helge Frieling; Anne Freitag; Thomas Hillemacher; Kristina Bayerlein; Johannes Kornhuber; Stefan Bleich Journal: Drug Alcohol Depend Date: 2007-01-17 Impact factor: 4.492
Authors: Jack Chen; Katherine M Conigrave; Petra Macaskill; John B Whitfield; Les Irwig Journal: Alcohol Alcohol Date: 2003 Nov-Dec Impact factor: 2.826
Authors: M Winkler; G Skopp; A Alt; E Miltner; Th Jochum; C Daenhardt; F Sporkert; H Gnann; W Weinmann; A Thierauf Journal: Int J Legal Med Date: 2012-12-29 Impact factor: 2.686
Authors: Alexandra Schröck; Annette Thierauf-Emberger; Stefan Schürch; Wolfgang Weinmann Journal: Int J Legal Med Date: 2016-09-05 Impact factor: 2.686
Authors: Nicolas Bertholet; Michael R Winter; Debbie M Cheng; Jeffrey H Samet; Richard Saitz Journal: Alcohol Alcohol Date: 2014-04-15 Impact factor: 2.826
Authors: Steven J Ondersma; Jessica R Beatty; Thomas G Rosano; Ronald C Strickler; Amy E Graham; Robert J Sokol Journal: Subst Use Misuse Date: 2016-01-15 Impact factor: 2.164
Authors: Martin Hastedt; Mara Büchner; Michael Rothe; René Gapert; Sieglinde Herre; Franziska Krumbiegel; Michael Tsokos; Thorsten Kienast; Andreas Heinz; Sven Hartwig Journal: Forensic Sci Med Pathol Date: 2013-03-17 Impact factor: 2.007
Authors: Hilda L Gutierrez; Lauren Hund; Shikhar Shrestha; William F Rayburn; Lawrence Leeman; Daniel D Savage; Ludmila N Bakhireva Journal: Alcohol Date: 2015-07-21 Impact factor: 2.405
Authors: Fritz Pragst; Franziska Krumbiegel; Denise Thurmann; Lena Westendorf; Maximilian Methling; André Niebel; Sven Hartwig Journal: Int J Legal Med Date: 2020-01-21 Impact factor: 2.686