Abstract

Background: Urine drug testing is used by health care providers to determine a patient’s compliance to their prescribed regimen and to detect non-prescribed medications and illicit drugs. However, the cutoff levels used by clinical labs are often arbitrarily set and may not reflect the urine drug concentrations of compliant patients. Objectives: Our aim was to test the hypothesis that commonly used cutoffs for many prescribed and illicit drugs were set too high, and methods using these cutoffs may yield a considerable number of false-negative results. The goals of this study were to outline the way to analyze patient results and estimate a more appropriate cutoff, develop and validate a high sensitivity analytical method capable of quantitating drugs and metabolites at lower than the commonly used cutoffs, and determine the number of true positive results that would have been missed when using the common cutoffs. Study Design: This was a retrospective study of urine specimens submitted for urine drug testing as part of the monitoring of prescription drug compliance described in chronic opioid therapy treatment guidelines. Setting: The study was set in a clinical toxicology laboratory, using specimens submitted for routine analysis by health care providers in the normal course of business. Methods: Lognormal distributions of test results were generated and fitted with a trendline to estimate the required cutoff level necessary to capture the normal distributions of each drug for the patient population study. A validated laboratory derived liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis capable of achieving the required cutoff levels was developed for each drug and/or metabolite. Results: The study shows that a lognormal distribution of patient urine test results fitted with a trendline is appropriate for estimating the required cutoff levels needed to assess medication adherence. The study showed a wide variation in the false-negative rate, ranging from 1.5% to 94.3% across a range of prescribed and illicit drugs. Limitations: The patient specimens were largely sourced from patients in either a long-term pain management program or in treatment for substance use disorder in the US. These specimens may not be representative of patients in other types of treatment or in countries with different approaches to these issues. Conclusions: The high-sensitivity method reduces false-negative results which could negatively impact patient care. Clinicians using less sensitive methods for detecting and quantifying drugs and metabolites in urine should exercise caution in assessing patient adherence using and changing the treatment plan based on those results. Key words: Urine drug testing, patient adherence, clinical toxicology, immunoassay, LC-MS, definitive drug testing, REMS, negative test results, false negative

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