Use of an algorithm applied to urine drug screening to assess adherence to an OxyContin® regimen

Objective: This study examined the ability of an algorithm applied to urine drug levels of oxycodone in healthy adult volunteers to differentiate among low, medium, and high doses of OxyContin®.Participants and interventions: Thirty-six healthy volunteers were randomized to receive 80, 160, or 240 mg of daily OxyContin® to steady state while under a naltrexone blockade. During days 3 and 4 of the study, urine samples of all participants were collected, and oxycodone levels detected in the urine were obtained using a liquid chromatography-mass spectrometry (LC-MS-MS) assay.Outcome measures: The concordance was calculated for raw and adjusted LC-MS-MS urine oxycodone values within each study participant between their third and fourth day values. Also, an analysis of medians was calculated for each of the dosage groupings using Bonett-Price confidence intervals for both raw and adjusted LC-MS-MS values.Results: The concordance correlation coefficient for the raw LC-MS-MS values between days 3 and 4 was 0.689 (95% confidence intervals = 0.515, 0.864), whereas the concordance correlation coefficient for the LC-MS-MS values using the algorithm (ie, normalized values) was 0.882 (95% confidence intervals = 0.808, 0.956). Because of greater variability in the raw values, some overlap was observed in the confidence intervals of the various OxyContin® doses, whereas no overlap was observed in the normalized confidence intervals regardless of the application of a Bonferroni adjustment.Conclusions: In contrast to raw LC-MS-MS values, an algorithm that normalizes oxycodone urine drug levels for pH, specific gravity, and lean body mass discriminates well among all three of the daily doses of OxyContin® tested (80, 160, and 240 mg), even with correcting for multiple analyses.