Gaurav Sharma1, Neal Oden2, Paul C VanVeldhuisen3, Michael P Bogenschutz4. 1. The Emmes Corporation, 401 North Washington Street Suite 700, Rockville, MD 20850, United States. Electronic address: gsharma@emmes.com. 2. The Emmes Corporation, 401 North Washington Street Suite 700, Rockville, MD 20850, United States. Electronic address: noden@emmes.com. 3. The Emmes Corporation, 401 North Washington Street Suite 700, Rockville, MD 20850, United States. Electronic address: pvanveldhuisen@emmes.com. 4. NYU School of Medicine, Bellevue Hospital Center, 462 First Avenue H Building, New York, NY 10016, United States. Electronic address: Michael.Bogenschutz@nyumc.org.
Abstract
BACKGROUND: Secondary analysis using data from the National Drug Abuse Treatment Clinical Trials Network randomized trial (NCT # 01207791), in which 1285 adult ED patients endorsing moderate to severe problems related to drug use were recruited from 6 US academic hospitals. OBJECTIVE: To investigate the utility of hair analysis in drug use disorder trials with infrequent visits, and its concordance with Timeline Follow Back (TLFB). METHODS: This study compared the self-reported drug use on the TLFB instrument with the biological measure of drug use from hair analysis for four major drug classes (Cannabis, Cocaine, Prescribed Opioids and Street Opioids). Both hair analysis and TLFB were conducted at 3, 6 and 12 month follow-up visit and each covered a 90-day recall period prior to the visit. RESULTS: The concordance between the hair sample results and the TLFB was high for cannabis and street opioids, but was low to moderate for cocaine and prescribed opioids. Under-reporting of drug use given the positive hair sample was always significantly lower for the drug the study participant noted as their primary drug of choice compared with other drugs the participant reported taking, irrespective of whether the drug of choice was cannabis, cocaine, street opioids and prescribed opioids. Over-reporting of drug use given the negative hair sample was always significantly higher for the drug of choice, except for cocaine. CONCLUSIONS: This study extends the literature on hair analysis supporting its use as a secondary outcome measure in clinical trials.
RCT Entities:
BACKGROUND: Secondary analysis using data from the National Drug Abuse Treatment Clinical Trials Network randomized trial (NCT # 01207791), in which 1285 adult ED patients endorsing moderate to severe problems related to drug use were recruited from 6 US academic hospitals. OBJECTIVE: To investigate the utility of hair analysis in drug use disorder trials with infrequent visits, and its concordance with Timeline Follow Back (TLFB). METHODS: This study compared the self-reported drug use on the TLFB instrument with the biological measure of drug use from hair analysis for four major drug classes (Cannabis, Cocaine, Prescribed Opioids and Street Opioids). Both hair analysis and TLFB were conducted at 3, 6 and 12 month follow-up visit and each covered a 90-day recall period prior to the visit. RESULTS: The concordance between the hair sample results and the TLFB was high for cannabis and street opioids, but was low to moderate for cocaine and prescribed opioids. Under-reporting of drug use given the positive hair sample was always significantly lower for the drug the study participant noted as their primary drug of choice compared with other drugs the participant reported taking, irrespective of whether the drug of choice was cannabis, cocaine, street opioids and prescribed opioids. Over-reporting of drug use given the negative hair sample was always significantly higher for the drug of choice, except for cocaine. CONCLUSIONS: This study extends the literature on hair analysis supporting its use as a secondary outcome measure in clinical trials.
Authors: Theresa M Winhusen; Eugene C Somoza; Bonita Singal; Sunme Kim; Paul S Horn; John Rotrosen Journal: Addiction Date: 2003-03 Impact factor: 6.526
Authors: Jan Gryczynski; Robert P Schwartz; Shannon Gwin Mitchell; Kevin E O'Grady; Steven J Ondersma Journal: Drug Alcohol Depend Date: 2014-05-17 Impact factor: 4.492
Authors: Theresa M Winhusen; Frankie Kropp; Robert Lindblad; Antoine Douaihy; Louise Haynes; Candace Hodgkins; Karen Chartier; Kyle M Kampman; Gaurav Sharma; Daniel F Lewis; Paul VanVeldhuisen; Jeff Theobald; Jeanine May; Gregory S Brigham Journal: J Clin Psychiatry Date: 2014-07 Impact factor: 4.384
Authors: Natalie S Levy; Joseph J Palamar; Stephen J Mooney; Charles M Cleland; Katherine M Keyes Journal: Ann Epidemiol Date: 2022-01-03 Impact factor: 6.996