TY - JOUR
AU - Bergström, Mats
AB - Abstract The use of oral fluid tests to detect drugs is of growing interest in various areas, including treatment centers, roadside and workplace testing. In this study, we investigated drug detection in oral fluid samples collected using a commercially available device, Oral Eze. Drug detection in oral fluid was compared to paired urine samples, which were simultaneously collected. We also evaluated the collection device by comparing A and B oral fluid samples. Finally, we studied the stability of various drugs in samples stored for at least 1 year. The drug profile was investigated by comparing the drugs detected in oral fluid samples with paired urine samples collected in a treatment center. A total of 113 paired oral fluid and urine samples were investigated for the presence of drugs in the following groups: amphetamines, benzodiazepines, opiates and opioids, cocaine and cannabis. A and B samples were collected from different workplaces through an uncontrolled sampling procedure (n = 76). The stability of drugs in A samples was assessed after storage at −20°C for 1 year. Generally, there was a good correlation between drugs detected in oral fluid samples and urine samples. The heroin metabolite, 6-MAM, was more frequently detected in oral fluid samples than in urine samples, while cannabis was better detected in urine samples. Drugs in oral fluid samples were stable when stored at −20°C for at least 1 year. However, in many positive A and B oral fluid samples, there was significant variation in the concentrations obtained. Hence, the collection device may need to be further standardized and improved. Introduction The use of oral fluid to detect drugs is an interesting alternative to other methods and is applicable for a variety of workplaces. Oral fluid sampling is a non-invasive and easily monitored technique, which can be performed in any environment by staff with little training. In comparison, urine sampling requires a special room with facilities, and blood samples must be collected by a trained person. The use of oral fluid as a test matrix has become increasingly interesting for monitoring drug intake in treatment centers, and this technique could also be applied in roadside testing to identify people who are driving under the influence of drugs (1–5). In workplaces, oral fluid testing is a valuable tool to identify employees with drug habits that may impair their working ability and also as an aid during rehabilitation (6). When monitoring the drug intake of individuals in treatment centers, many studies have compared oral fluid samples to simultaneously obtained urine samples. These investigations have led to several publications covering a wide range of different drugs in oral fluid samples and urine samples (7–12). The outcome of these studies has opened the possibility of using oral fluid tests instead of urine, blood and plasma samples. There are always some drawbacks associated with different sampling methods. Urine sampling is sometimes delayed, for instance, when the individual is not able to produce a sample during the time available. Urine samples can also be adulterated by substitution or sample dilution, representing another drawback. Oral fluid sampling using a collection device is not void of complications and may be difficult if the person being tested suffers from xerostomia. Despite this downside, the use of oral fluid as a test method in workplaces is increasing. Many workplaces apply a strict drug policy. The individual must be informed about what drugs will be tested, and refusal or inability to participate may have serious consequences. Oral fluid sampling of employees usually takes place unannounced and two samples are taken, known as A and B samples. When drugs are detected, the A sample is verified by a selective method usually on a liquid chromatography–mass spectrometry instrument (LC–MS-MS). The individual is always entitled to question the result obtained in the A sample. When this happens, the B sample is sent to another laboratory to confirm the result obtained for the A sample. The challenges are rare, and it is of course important that comparable results are achieved (13). It is not difficult to produce homogenous urine samples, as both A and B samples are taken from the same container. Ensuring homogeneity for A and B oral fluid samples using a collection device is more challenging because each sample is collected individually. The European Workplace Drug Testing Society (EWDTS) (14) provides a guideline that describes how to handle workplace samples, including pre-analytical sampling, the analytical procedure and post-analytical storage. Regarding the pre-analytical part, one important issue is the choice of sampling method, which allows the application of sensitive cut-off levels. Today, there are many different manufacturers of oral fluid sampling devices (15). Different sampling tools may have different recoveries and stabilities for drugs in oral fluid samples. Also, it is crucial to develop an analytical method that is sensitive enough to detect low concentrations of drugs in oral fluid samples. In our previous work, we established a sensitive multi-analyte (LC–MS-MS) method for the detection of drugs in oral fluid (16). The aim of the present work is to investigate the drug profile obtained using a commercially available collection device, Oral Eze, as a sampling tool, and to relate these findings to the results obtained from simultaneously collected urine samples. Oral fluid samples were taken from individuals at a treatment center by experienced staff. Additionally, using samples collected from individuals at different workplaces, the drug concentrations in A and B oral fluid samples collected using this device were compared. In this part of the study, sampling was uncontrolled in the sense that staff was taught how to obtain samples but had different levels of experience with the sampling device and worked at a variety of different locations. In this respect, the present study differs from other published methods. As a general principle concerning workplace testing, when a positive A sample is obtained, both the A and B samples are stored to make it possible to perform second-opinion tests. Hence, we also assessed the stability of drugs in oral fluid samples stored at −20°C for at least 1 year. Materials and Methods Participants Oral fluid samples and urine samples were collected from subjects at a treatment center close to the hospital in Eskilstuna, Sweden. At the same time as urine sample collection, the subject was also asked to provide an oral fluid sample. The individual was informed that the urine sample and the oral fluid sample were to be used for a statistical study on drug detection in urine compared to oral fluid matrix and that personal data were not going to be published or documented. A document providing their consent to participate in the study was signed by the individual. The procedure was approved by the Ethics Committee at Karolinska Institutet, Stockholm, Sweden. The A and B samples used in the current study were samples collected at different workplaces and these were sent to the laboratory for drug testing. The oral fluid samples were identified by serial numbers. Client records were available only to the reffering institution. Sample collection Collection of paired oral fluid and urine samples From December 2016 to October 2017, 113 paired oral fluid and urine samples were collected from 64 different individuals. Oral fluid samples were collected using a commercially available collection device (Oral Eze, Thermo Fisher, Vantaa, Finland). When 1 mL of oral fluid was collected onto the pad, an indicator on the stick attached to the pad turned blue. This procedure took 2–10 min. The pad with the oral fluid was then placed into a buffer solution. The oral fluid sampling procedure was validated in a previous study (16). For this part of the study, the oral fluid samples were collected at the same time as the urine samples. Both oral fluid and urine samples were stored at −20°C prior to analysis. Collection of A and B oral fluid samples A technician from the laboratory informed the responsible staff at the workplace how to use the Oral Eze pad to collect oral fluid samples. A written instruction on how to use the oral Eze pad is provided, and the laboratory instructor could always be contacted if needed. The A and B oral fluid samples were collected in series in the same session and sent to the laboratory for drug testing. At the laboratory, the A samples were analyzed. The B samples were left intact and were only used if the result of the A sample was challenged. Both A and B oral fluid samples were stored at −20°C for at least 1 year in the laboratory. The A and B samples are valid for 1 year; after this time, the samples are usually discarded by the laboratory. However, these samples were retained for the purpose of the current study. After 1 year of storage, A and B oral fluid samples were evaluated, and the stability of A samples was studied by retesting. Analytical methods Oral fluid analysis Oral fluid samples were analyzed according to the multi-analyte method published by Zheng et al. (16). It is a simple “dilute and shoot” principle. The most important steps were the centrifugations. Oral fluid samples were transferred to smaller 12 × 75 mm round bottom tubes and centrifuged at 10,000g for 10 min. Oral fluid samples (150 |$ {\mu}$|L) were added to Eppendorf tubes, and then internal standards and 100 |$ {\mu}$|L acetonitrile were added. The solutions were mixed before adding 200 |$ {\mu}$|L of methanol. After mixing the solutions again, the samples were centrifuged at 10,000g for 10 min. Urine analysis Urine samples were analyzed using routine laboratory methods with LC–MS-MS instruments. The conjugated forms of benzodiazepines, buprenorphine and cannabis in urine were hydrolyzed using β-glucuronidase enzyme from Helix pomatia. The hydrolysis steps for the conjugated glucuronide molecule in benzodiazepines, buprenorphine and cannabis were developed at the laboratory. Although the sample clean-up was similar, these substances were analyzed by three separate methods. Amphetamines, opioids, opiates and cocaine were analyzed by four separate methods. Urine samples were centrifuged then diluted (1:10) with deionized water containing internal standards prior to LC–MS-MS analysis following the “dilute and shoot” principle (17). All these methods were accredited and routinely used in the laboratory to detect drugs in urine samples. Drugs analyzed Table I summarizes the substances analyzed in this work and the cut-off values applied for oral fluid and urine samples. The drug concentrations represent the neat oral fluid. The sampling device collects 1 mL of oral fluid which is diluted in 2 mL of buffer solution. This dilution effect was corrected in the oral fluid samples. Table I The Cut–Off Values for Drugs in Oral Fluid and in Urine Drugs . Oral fluid (ng/mL) . EWDTS confirmation cut–offs for oral fluids (ng/mL) . Urine confirmation cut–offs analysis (ng/mL) . EWDTS confirmation cut–offs for urine analysis (ng/mL) . Amphetamine/methamphetamine (MDMA, MDA, MDEA) 15 15 200 200 Benzodiazepines (alprazolam, bromazepam, clonazepam, 7–aminoclonazepam, diazepam, phenazepam, flunitrazepam, 7–aminoflunitrazepam, lorazepam, midazolam, nordiazepam, nitrazepam, 7–aminonitrazepam, oxazepam, temazepam, triazolam)a 1 3 50 100 Cannabis–Δ9–THCb 2 2 10 15 Cocaine (benzoylecgonine) 2 8 100 100 Opiates (codeine, ethylmorphine, morphine, 6–MAM) 3 15 300 300 Opioids Buprenorphine 1 1 5 2 Norbuprenorphine 1 1 5 2 Fentanyl 2 – 0,5 – Norfentanyl – – 6 – Oxycodone 2 – 300 – Methadone 2 20 250 EDDP = 75 250/75 Tramadol 9 – 200 – O–Desmethyltramadol 9 – 200 – Phencyclidine (PCP) 2 – 25 25 Drugs . Oral fluid (ng/mL) . EWDTS confirmation cut–offs for oral fluids (ng/mL) . Urine confirmation cut–offs analysis (ng/mL) . EWDTS confirmation cut–offs for urine analysis (ng/mL) . Amphetamine/methamphetamine (MDMA, MDA, MDEA) 15 15 200 200 Benzodiazepines (alprazolam, bromazepam, clonazepam, 7–aminoclonazepam, diazepam, phenazepam, flunitrazepam, 7–aminoflunitrazepam, lorazepam, midazolam, nordiazepam, nitrazepam, 7–aminonitrazepam, oxazepam, temazepam, triazolam)a 1 3 50 100 Cannabis–Δ9–THCb 2 2 10 15 Cocaine (benzoylecgonine) 2 8 100 100 Opiates (codeine, ethylmorphine, morphine, 6–MAM) 3 15 300 300 Opioids Buprenorphine 1 1 5 2 Norbuprenorphine 1 1 5 2 Fentanyl 2 – 0,5 – Norfentanyl – – 6 – Oxycodone 2 – 300 – Methadone 2 20 250 EDDP = 75 250/75 Tramadol 9 – 200 – O–Desmethyltramadol 9 – 200 – Phencyclidine (PCP) 2 – 25 25 a Alpha-Hydroxyalprazolam, alpha-hydroxymidazolam and alpha-hydroxytriazolam were detected only in urine. b THC-COOH was measured in urine. Open in new tab Table I The Cut–Off Values for Drugs in Oral Fluid and in Urine Drugs . Oral fluid (ng/mL) . EWDTS confirmation cut–offs for oral fluids (ng/mL) . Urine confirmation cut–offs analysis (ng/mL) . EWDTS confirmation cut–offs for urine analysis (ng/mL) . Amphetamine/methamphetamine (MDMA, MDA, MDEA) 15 15 200 200 Benzodiazepines (alprazolam, bromazepam, clonazepam, 7–aminoclonazepam, diazepam, phenazepam, flunitrazepam, 7–aminoflunitrazepam, lorazepam, midazolam, nordiazepam, nitrazepam, 7–aminonitrazepam, oxazepam, temazepam, triazolam)a 1 3 50 100 Cannabis–Δ9–THCb 2 2 10 15 Cocaine (benzoylecgonine) 2 8 100 100 Opiates (codeine, ethylmorphine, morphine, 6–MAM) 3 15 300 300 Opioids Buprenorphine 1 1 5 2 Norbuprenorphine 1 1 5 2 Fentanyl 2 – 0,5 – Norfentanyl – – 6 – Oxycodone 2 – 300 – Methadone 2 20 250 EDDP = 75 250/75 Tramadol 9 – 200 – O–Desmethyltramadol 9 – 200 – Phencyclidine (PCP) 2 – 25 25 Drugs . Oral fluid (ng/mL) . EWDTS confirmation cut–offs for oral fluids (ng/mL) . Urine confirmation cut–offs analysis (ng/mL) . EWDTS confirmation cut–offs for urine analysis (ng/mL) . Amphetamine/methamphetamine (MDMA, MDA, MDEA) 15 15 200 200 Benzodiazepines (alprazolam, bromazepam, clonazepam, 7–aminoclonazepam, diazepam, phenazepam, flunitrazepam, 7–aminoflunitrazepam, lorazepam, midazolam, nordiazepam, nitrazepam, 7–aminonitrazepam, oxazepam, temazepam, triazolam)a 1 3 50 100 Cannabis–Δ9–THCb 2 2 10 15 Cocaine (benzoylecgonine) 2 8 100 100 Opiates (codeine, ethylmorphine, morphine, 6–MAM) 3 15 300 300 Opioids Buprenorphine 1 1 5 2 Norbuprenorphine 1 1 5 2 Fentanyl 2 – 0,5 – Norfentanyl – – 6 – Oxycodone 2 – 300 – Methadone 2 20 250 EDDP = 75 250/75 Tramadol 9 – 200 – O–Desmethyltramadol 9 – 200 – Phencyclidine (PCP) 2 – 25 25 a Alpha-Hydroxyalprazolam, alpha-hydroxymidazolam and alpha-hydroxytriazolam were detected only in urine. b THC-COOH was measured in urine. Open in new tab Statistical analysis For each analyte, positivity rates were computed along with test sensitivity and specificity. The sensitivity = (true positive OF)/(total positive UR) and specificity = (true negative OF)/(total negative UR). The percentage change, reported in Tables III and IV, was calculated as the difference between the A and B samples divided by the result obtained for the A sample. Test agreement, with the urine result as the reference, was calculated using Cohen’s kappa; MedCalc software version 19.0.3 (MedCalc Software, Ostend, Belgium) was utilized (18). Results Amphetamines, benzodiazepines, cannabis, cocaine, opiates and opioids were measured in 113 paired oral fluid and urine samples. Table I presents the cut-off values for drugs in the neat oral fluid and urine samples included in this work. Many of the substances in oral fluid, such as cocaine, opiates and methadone, had a much lower cut-off value than that recommended by the EWDTS. In general, the parent compounds are more abundant in oral fluid samples. In urine samples, the drugs are present at higher concentrations, and metabolites are primarily detected. Metabolites for some benzodiazepines, β-hydroxyalprazolam, β-hydroxymidazolam, β-hydroxytriazolam and EDDP (2-ethylidene-1,5-dimethyl-3,3-diphenylpyrrolidine) a metabolite for methadone, were measured only in urine samples. Cocaine and diazepam were only detected in oral fluid samples. In oral fluid samples, the parent molecule of cannabis, Δ9-tetrahydrocannabinol (THC), was measured instead of the metabolite THC-COOH, which was the substance detected in urine. Figure 1 summarizes the detection frequencies in oral fluid samples compared to urine samples. Only the drugs that tested positive in urine and/or oral fluid samples are presented. One sample was positive for fentanyl and methadone in urine and oral fluid samples; therefore, these results have not been included in Figure 1 or Table II. The result for ethylmorphine was also excluded from the data as only one sample was found positive in urine at a low concentration but negative in the paired oral fluid sample. Figure 1 Open in new tabDownload slide Frequencies of drugs detected in paired oral fluid (OF) and urine (UR) samples. Figure 1 Open in new tabDownload slide Frequencies of drugs detected in paired oral fluid (OF) and urine (UR) samples. Table II Statistical Evaluation of the Data Obtained in Oral Fluid Compared to Urine Samplesa Drugs . Sensitivity (%) . Specificity (%) . Kappa (%) . Amphetamines Amphetamine 100 100 100 Benzodiazepines Diazepam – 86 0 Nordiazepam 91 94 82 Oxazepam 6 100 8 Temazepam 6 100 9 Clonazepam 100 95 68 7–Aminoclonazepam 100 100 100 Alprazolam 100 98 87 Opiates Codeine 100 98 92 Morphine 61 100 73 6–MAM 100 93 47 Opioids Buprenorphine 85 95 80 Norbuprenorphine 56 100 66 Oxycodone 100 100 100 Tramadol 100 100 100 O–Desmethyltramadol 75 100 85 Other substances Cannabis 48 100 58 Cocaine – 94 0 Benzoylecgonine 83 100 90 Drugs . Sensitivity (%) . Specificity (%) . Kappa (%) . Amphetamines Amphetamine 100 100 100 Benzodiazepines Diazepam – 86 0 Nordiazepam 91 94 82 Oxazepam 6 100 8 Temazepam 6 100 9 Clonazepam 100 95 68 7–Aminoclonazepam 100 100 100 Alprazolam 100 98 87 Opiates Codeine 100 98 92 Morphine 61 100 73 6–MAM 100 93 47 Opioids Buprenorphine 85 95 80 Norbuprenorphine 56 100 66 Oxycodone 100 100 100 Tramadol 100 100 100 O–Desmethyltramadol 75 100 85 Other substances Cannabis 48 100 58 Cocaine – 94 0 Benzoylecgonine 83 100 90 aSensitivity and specificity with urine as reference. Agreement measured as Cohen’s Kappa. Open in new tab Table II Statistical Evaluation of the Data Obtained in Oral Fluid Compared to Urine Samplesa Drugs . Sensitivity (%) . Specificity (%) . Kappa (%) . Amphetamines Amphetamine 100 100 100 Benzodiazepines Diazepam – 86 0 Nordiazepam 91 94 82 Oxazepam 6 100 8 Temazepam 6 100 9 Clonazepam 100 95 68 7–Aminoclonazepam 100 100 100 Alprazolam 100 98 87 Opiates Codeine 100 98 92 Morphine 61 100 73 6–MAM 100 93 47 Opioids Buprenorphine 85 95 80 Norbuprenorphine 56 100 66 Oxycodone 100 100 100 Tramadol 100 100 100 O–Desmethyltramadol 75 100 85 Other substances Cannabis 48 100 58 Cocaine – 94 0 Benzoylecgonine 83 100 90 Drugs . Sensitivity (%) . Specificity (%) . Kappa (%) . Amphetamines Amphetamine 100 100 100 Benzodiazepines Diazepam – 86 0 Nordiazepam 91 94 82 Oxazepam 6 100 8 Temazepam 6 100 9 Clonazepam 100 95 68 7–Aminoclonazepam 100 100 100 Alprazolam 100 98 87 Opiates Codeine 100 98 92 Morphine 61 100 73 6–MAM 100 93 47 Opioids Buprenorphine 85 95 80 Norbuprenorphine 56 100 66 Oxycodone 100 100 100 Tramadol 100 100 100 O–Desmethyltramadol 75 100 85 Other substances Cannabis 48 100 58 Cocaine – 94 0 Benzoylecgonine 83 100 90 aSensitivity and specificity with urine as reference. Agreement measured as Cohen’s Kappa. Open in new tab The sensitivity, specificity and Cohen’s kappa are presented in Table II. The results for the urine samples were set as reference values. In general, positive compounds detected in oral fluid samples mirrored their detection in urine samples. The substances that were more frequently detected in urine samples were cannabis, morphine, oxazepam and temazepam. Cocaine, diazepam and 6-MAM, a heroin metabolite, were better detected in oral fluid samples than urine samples. A total of 76 paired A and B oral fluid samples collected at different workplaces were analyzed. Of these, 26 samples (34%) tested positive for drugs, and the results indicate that there were prominent differences between A and B samples (Table III). The percentage change was estimated by dividing the results for B samples by the results for A samples. The most common drugs detected in workplace samples were cannabis, amphetamines and benzodiazepines, followed by cocaine. About 38% of the positive samples collected from individuals at different workplaces displayed significant (~50%) variation between the A and B oral fluid samples. B samples showed a higher concentration than A samples. However, there were A samples that had higher concentrations than B samples. The A and B oral fluid samples were analyzed simultaneously in the same batch. Table III Evaluation of Drugs in A and B Samplesa (a) Sample ID Amphetamine Cannabis Cocaine Benzoylecgonine Codeine Ethylmorphine A sample (ng/mL) B sample (ng/mL) % Change A sample (ng/mL) B sample (ng/mL) % Change A sample (ng/mL) B sample (ng/mL) % Change A sample (ng/mL) B sample (ng/mL) % Change A sample (ng/mL) B sample (ng/mL) % Change A sample (ng/mL) B sample (ng/mL) % Change 1 10 16 +60% 2 25 42 +68% 3 372 240 –35% 4 7.2 29 +300% 1.0 2.3 +130% 5 60 28 –53% 6 45 33 –27% 7 47 44 –6% 15.9 12.6 –21% 8 9.6 5.4 –44% 9 10 690 330 –52% 11 3.9 3.9 0% 12 360 330 –8% 13 222 210 –5% 14 15 4.2 3.6 –14% 16 7.9 3.4 –57% 35 12.6 –64% 11.9 5.8 –51% 17 703 373 –47% 18 19 228 231 +1.3% 20 3.6 2.2 –39% 21 40 59 +48% 15 22 +50% 22 2.1 1.5 –29% 2.7 1.5 –44% 23 17 26 +53% 82 79 –4% 238 232 –3% 24 19 19 0% 25 26 11 15 +40% (b) Sample ID Oxycodone Tramadol O-Desmethyltramadol Alprazolam Diazepam Nordiazepam A sample (ng/mL) B sample (ng/mL) % Change A sample (ng/mL) B sample (ng/mL) % Change A sample (ng/mL) B sample (ng/mL) % Change A sample (ng/mL) B sample (ng/mL) % Change A sample (ng/mL) B sample (ng/mL) % Change A sample (ng/mL) B sample (ng/mL) % Change 9 63 47 –25% 16.8 12.3 –27% 14 2.7 3.3 +22% 11 8.7 –21% 18 2.1 2.0 –5% 3.9 3.7 –5% 20 231 348 +51% 23 31 +35% 23 3.6 5.1 42% 3.3 3.6 +9% 25 3.9 3.5 10% 16 14 –13% (a) Sample ID Amphetamine Cannabis Cocaine Benzoylecgonine Codeine Ethylmorphine A sample (ng/mL) B sample (ng/mL) % Change A sample (ng/mL) B sample (ng/mL) % Change A sample (ng/mL) B sample (ng/mL) % Change A sample (ng/mL) B sample (ng/mL) % Change A sample (ng/mL) B sample (ng/mL) % Change A sample (ng/mL) B sample (ng/mL) % Change 1 10 16 +60% 2 25 42 +68% 3 372 240 –35% 4 7.2 29 +300% 1.0 2.3 +130% 5 60 28 –53% 6 45 33 –27% 7 47 44 –6% 15.9 12.6 –21% 8 9.6 5.4 –44% 9 10 690 330 –52% 11 3.9 3.9 0% 12 360 330 –8% 13 222 210 –5% 14 15 4.2 3.6 –14% 16 7.9 3.4 –57% 35 12.6 –64% 11.9 5.8 –51% 17 703 373 –47% 18 19 228 231 +1.3% 20 3.6 2.2 –39% 21 40 59 +48% 15 22 +50% 22 2.1 1.5 –29% 2.7 1.5 –44% 23 17 26 +53% 82 79 –4% 238 232 –3% 24 19 19 0% 25 26 11 15 +40% (b) Sample ID Oxycodone Tramadol O-Desmethyltramadol Alprazolam Diazepam Nordiazepam A sample (ng/mL) B sample (ng/mL) % Change A sample (ng/mL) B sample (ng/mL) % Change A sample (ng/mL) B sample (ng/mL) % Change A sample (ng/mL) B sample (ng/mL) % Change A sample (ng/mL) B sample (ng/mL) % Change A sample (ng/mL) B sample (ng/mL) % Change 9 63 47 –25% 16.8 12.3 –27% 14 2.7 3.3 +22% 11 8.7 –21% 18 2.1 2.0 –5% 3.9 3.7 –5% 20 231 348 +51% 23 31 +35% 23 3.6 5.1 42% 3.3 3.6 +9% 25 3.9 3.5 10% 16 14 –13% aA set of 76 (paired A and B samples) were analyzed, of these 34% were detected positive in both A and the parallel B samples. About 38% of these positive samples had ~50% or higher concentration variation between A and B samples. There were more B samples with a higher concentration than A samples. However, some A samples had a higher concentration than B samples. Open in new tab Table III Evaluation of Drugs in A and B Samplesa (a) Sample ID Amphetamine Cannabis Cocaine Benzoylecgonine Codeine Ethylmorphine A sample (ng/mL) B sample (ng/mL) % Change A sample (ng/mL) B sample (ng/mL) % Change A sample (ng/mL) B sample (ng/mL) % Change A sample (ng/mL) B sample (ng/mL) % Change A sample (ng/mL) B sample (ng/mL) % Change A sample (ng/mL) B sample (ng/mL) % Change 1 10 16 +60% 2 25 42 +68% 3 372 240 –35% 4 7.2 29 +300% 1.0 2.3 +130% 5 60 28 –53% 6 45 33 –27% 7 47 44 –6% 15.9 12.6 –21% 8 9.6 5.4 –44% 9 10 690 330 –52% 11 3.9 3.9 0% 12 360 330 –8% 13 222 210 –5% 14 15 4.2 3.6 –14% 16 7.9 3.4 –57% 35 12.6 –64% 11.9 5.8 –51% 17 703 373 –47% 18 19 228 231 +1.3% 20 3.6 2.2 –39% 21 40 59 +48% 15 22 +50% 22 2.1 1.5 –29% 2.7 1.5 –44% 23 17 26 +53% 82 79 –4% 238 232 –3% 24 19 19 0% 25 26 11 15 +40% (b) Sample ID Oxycodone Tramadol O-Desmethyltramadol Alprazolam Diazepam Nordiazepam A sample (ng/mL) B sample (ng/mL) % Change A sample (ng/mL) B sample (ng/mL) % Change A sample (ng/mL) B sample (ng/mL) % Change A sample (ng/mL) B sample (ng/mL) % Change A sample (ng/mL) B sample (ng/mL) % Change A sample (ng/mL) B sample (ng/mL) % Change 9 63 47 –25% 16.8 12.3 –27% 14 2.7 3.3 +22% 11 8.7 –21% 18 2.1 2.0 –5% 3.9 3.7 –5% 20 231 348 +51% 23 31 +35% 23 3.6 5.1 42% 3.3 3.6 +9% 25 3.9 3.5 10% 16 14 –13% (a) Sample ID Amphetamine Cannabis Cocaine Benzoylecgonine Codeine Ethylmorphine A sample (ng/mL) B sample (ng/mL) % Change A sample (ng/mL) B sample (ng/mL) % Change A sample (ng/mL) B sample (ng/mL) % Change A sample (ng/mL) B sample (ng/mL) % Change A sample (ng/mL) B sample (ng/mL) % Change A sample (ng/mL) B sample (ng/mL) % Change 1 10 16 +60% 2 25 42 +68% 3 372 240 –35% 4 7.2 29 +300% 1.0 2.3 +130% 5 60 28 –53% 6 45 33 –27% 7 47 44 –6% 15.9 12.6 –21% 8 9.6 5.4 –44% 9 10 690 330 –52% 11 3.9 3.9 0% 12 360 330 –8% 13 222 210 –5% 14 15 4.2 3.6 –14% 16 7.9 3.4 –57% 35 12.6 –64% 11.9 5.8 –51% 17 703 373 –47% 18 19 228 231 +1.3% 20 3.6 2.2 –39% 21 40 59 +48% 15 22 +50% 22 2.1 1.5 –29% 2.7 1.5 –44% 23 17 26 +53% 82 79 –4% 238 232 –3% 24 19 19 0% 25 26 11 15 +40% (b) Sample ID Oxycodone Tramadol O-Desmethyltramadol Alprazolam Diazepam Nordiazepam A sample (ng/mL) B sample (ng/mL) % Change A sample (ng/mL) B sample (ng/mL) % Change A sample (ng/mL) B sample (ng/mL) % Change A sample (ng/mL) B sample (ng/mL) % Change A sample (ng/mL) B sample (ng/mL) % Change A sample (ng/mL) B sample (ng/mL) % Change 9 63 47 –25% 16.8 12.3 –27% 14 2.7 3.3 +22% 11 8.7 –21% 18 2.1 2.0 –5% 3.9 3.7 –5% 20 231 348 +51% 23 31 +35% 23 3.6 5.1 42% 3.3 3.6 +9% 25 3.9 3.5 10% 16 14 –13% aA set of 76 (paired A and B samples) were analyzed, of these 34% were detected positive in both A and the parallel B samples. About 38% of these positive samples had ~50% or higher concentration variation between A and B samples. There were more B samples with a higher concentration than A samples. However, some A samples had a higher concentration than B samples. Open in new tab Table IV The Stability of A Samples When Stored at –20°C for at least 1 yeara Sample ID Amphetamine Cannabis Cocaine Benzoylecgonine Codeine Ethylmorphine A sample (ng/mL) Reanalyzed A sample (ng/mL) % Change A sample (ng/mL) Reanalyzed A sample (ng/mL) % Change A sample (ng/mL) Reanalyzed A sample (ng/mL) % Change A sample (ng/mL) Reanalyzed A sample (ng/mL) % Change A sample (ng/mL) Reanalyzed A sample (ng/mL) % Change A sample (ng/mL) Reanalyzed A sample (ng/mL) % Change 1 16 10 –38% 2 16 25 +56% 3 ~1,000 372 Xa 4 7.3 7.2 –1% 5 64 60 –6% 6 33 45 +36% 7 58 47 –19% 36 16 –56% 8 13.1 9.6 –26% 9 10 576 690 +20% 11 3.9 3.9 0% 12 313 360 +15% 13 188 222 +18% 14 15 6.0 4.2 –30% 16 7.9 7.9 0% 44 35 –20% 11.7 11.9 2% 17 628 703 +12% 18 19 198 228 +15% 20 4.5 3.6 –20% 21 50 40 –20% 12 15 +25% 22 2.5 2.1 –16% 3.0 2.7 –10% 23 18 17 –6% 100 82 –18% 173 238 +38% 24 24 19 –21% 25 26 12 11 –8% Sample ID Oxycodone Tramadol O-Desmethyltramadol Alprazolam Diazepam Nordiazepam A sample (ng/mL) Reanalyzed A sample (ng/mL) % change A sample (ng/mL) Reanalyzed A sample (ng/mL) % change A sample (ng/mL) Reanalyzed A sample (ng/mL) % change A sample (ng/mL) Reanalyzed A sample (ng/mL) % change A sample (ng/mL) Reanalyzed A sample (ng/mL) % change A sample (ng/mL) Reanalyzed A sample (ng/mL) % change 9 59 63 –7% 17 17 0% 14 3.9 2.7 –31% 9 11 +22% 18 1.7 2.1 +24% 5.4 3.9 –28% 20 327 231 –29% 34 23 –32% 23 2.7 3.6 +33% 3.9 3.3 –15% 25 4.8 3.3 –31% 16.2 15.6 –4% Sample ID Amphetamine Cannabis Cocaine Benzoylecgonine Codeine Ethylmorphine A sample (ng/mL) Reanalyzed A sample (ng/mL) % Change A sample (ng/mL) Reanalyzed A sample (ng/mL) % Change A sample (ng/mL) Reanalyzed A sample (ng/mL) % Change A sample (ng/mL) Reanalyzed A sample (ng/mL) % Change A sample (ng/mL) Reanalyzed A sample (ng/mL) % Change A sample (ng/mL) Reanalyzed A sample (ng/mL) % Change 1 16 10 –38% 2 16 25 +56% 3 ~1,000 372 Xa 4 7.3 7.2 –1% 5 64 60 –6% 6 33 45 +36% 7 58 47 –19% 36 16 –56% 8 13.1 9.6 –26% 9 10 576 690 +20% 11 3.9 3.9 0% 12 313 360 +15% 13 188 222 +18% 14 15 6.0 4.2 –30% 16 7.9 7.9 0% 44 35 –20% 11.7 11.9 2% 17 628 703 +12% 18 19 198 228 +15% 20 4.5 3.6 –20% 21 50 40 –20% 12 15 +25% 22 2.5 2.1 –16% 3.0 2.7 –10% 23 18 17 –6% 100 82 –18% 173 238 +38% 24 24 19 –21% 25 26 12 11 –8% Sample ID Oxycodone Tramadol O-Desmethyltramadol Alprazolam Diazepam Nordiazepam A sample (ng/mL) Reanalyzed A sample (ng/mL) % change A sample (ng/mL) Reanalyzed A sample (ng/mL) % change A sample (ng/mL) Reanalyzed A sample (ng/mL) % change A sample (ng/mL) Reanalyzed A sample (ng/mL) % change A sample (ng/mL) Reanalyzed A sample (ng/mL) % change A sample (ng/mL) Reanalyzed A sample (ng/mL) % change 9 59 63 –7% 17 17 0% 14 3.9 2.7 –31% 9 11 +22% 18 1.7 2.1 +24% 5.4 3.9 –28% 20 327 231 –29% 34 23 –32% 23 2.7 3.6 +33% 3.9 3.3 –15% 25 4.8 3.3 –31% 16.2 15.6 –4% aThe measured A samples were stable when stored for at least 1 year at −20°C. Only two A samples varied significantly. The high variations were probably analytical differences. The quantified A sample result (1,000 ng/mL) for sample 3 for amphetamine was high and was not diluted at the time of testing. The reanalyzed value after 1 year of storage was 372 ng/mL. We did not include this result in the table since amphetamine was stable in all the other samples. Open in new tab Table IV The Stability of A Samples When Stored at –20°C for at least 1 yeara Sample ID Amphetamine Cannabis Cocaine Benzoylecgonine Codeine Ethylmorphine A sample (ng/mL) Reanalyzed A sample (ng/mL) % Change A sample (ng/mL) Reanalyzed A sample (ng/mL) % Change A sample (ng/mL) Reanalyzed A sample (ng/mL) % Change A sample (ng/mL) Reanalyzed A sample (ng/mL) % Change A sample (ng/mL) Reanalyzed A sample (ng/mL) % Change A sample (ng/mL) Reanalyzed A sample (ng/mL) % Change 1 16 10 –38% 2 16 25 +56% 3 ~1,000 372 Xa 4 7.3 7.2 –1% 5 64 60 –6% 6 33 45 +36% 7 58 47 –19% 36 16 –56% 8 13.1 9.6 –26% 9 10 576 690 +20% 11 3.9 3.9 0% 12 313 360 +15% 13 188 222 +18% 14 15 6.0 4.2 –30% 16 7.9 7.9 0% 44 35 –20% 11.7 11.9 2% 17 628 703 +12% 18 19 198 228 +15% 20 4.5 3.6 –20% 21 50 40 –20% 12 15 +25% 22 2.5 2.1 –16% 3.0 2.7 –10% 23 18 17 –6% 100 82 –18% 173 238 +38% 24 24 19 –21% 25 26 12 11 –8% Sample ID Oxycodone Tramadol O-Desmethyltramadol Alprazolam Diazepam Nordiazepam A sample (ng/mL) Reanalyzed A sample (ng/mL) % change A sample (ng/mL) Reanalyzed A sample (ng/mL) % change A sample (ng/mL) Reanalyzed A sample (ng/mL) % change A sample (ng/mL) Reanalyzed A sample (ng/mL) % change A sample (ng/mL) Reanalyzed A sample (ng/mL) % change A sample (ng/mL) Reanalyzed A sample (ng/mL) % change 9 59 63 –7% 17 17 0% 14 3.9 2.7 –31% 9 11 +22% 18 1.7 2.1 +24% 5.4 3.9 –28% 20 327 231 –29% 34 23 –32% 23 2.7 3.6 +33% 3.9 3.3 –15% 25 4.8 3.3 –31% 16.2 15.6 –4% Sample ID Amphetamine Cannabis Cocaine Benzoylecgonine Codeine Ethylmorphine A sample (ng/mL) Reanalyzed A sample (ng/mL) % Change A sample (ng/mL) Reanalyzed A sample (ng/mL) % Change A sample (ng/mL) Reanalyzed A sample (ng/mL) % Change A sample (ng/mL) Reanalyzed A sample (ng/mL) % Change A sample (ng/mL) Reanalyzed A sample (ng/mL) % Change A sample (ng/mL) Reanalyzed A sample (ng/mL) % Change 1 16 10 –38% 2 16 25 +56% 3 ~1,000 372 Xa 4 7.3 7.2 –1% 5 64 60 –6% 6 33 45 +36% 7 58 47 –19% 36 16 –56% 8 13.1 9.6 –26% 9 10 576 690 +20% 11 3.9 3.9 0% 12 313 360 +15% 13 188 222 +18% 14 15 6.0 4.2 –30% 16 7.9 7.9 0% 44 35 –20% 11.7 11.9 2% 17 628 703 +12% 18 19 198 228 +15% 20 4.5 3.6 –20% 21 50 40 –20% 12 15 +25% 22 2.5 2.1 –16% 3.0 2.7 –10% 23 18 17 –6% 100 82 –18% 173 238 +38% 24 24 19 –21% 25 26 12 11 –8% Sample ID Oxycodone Tramadol O-Desmethyltramadol Alprazolam Diazepam Nordiazepam A sample (ng/mL) Reanalyzed A sample (ng/mL) % change A sample (ng/mL) Reanalyzed A sample (ng/mL) % change A sample (ng/mL) Reanalyzed A sample (ng/mL) % change A sample (ng/mL) Reanalyzed A sample (ng/mL) % change A sample (ng/mL) Reanalyzed A sample (ng/mL) % change A sample (ng/mL) Reanalyzed A sample (ng/mL) % change 9 59 63 –7% 17 17 0% 14 3.9 2.7 –31% 9 11 +22% 18 1.7 2.1 +24% 5.4 3.9 –28% 20 327 231 –29% 34 23 –32% 23 2.7 3.6 +33% 3.9 3.3 –15% 25 4.8 3.3 –31% 16.2 15.6 –4% aThe measured A samples were stable when stored for at least 1 year at −20°C. Only two A samples varied significantly. The high variations were probably analytical differences. The quantified A sample result (1,000 ng/mL) for sample 3 for amphetamine was high and was not diluted at the time of testing. The reanalyzed value after 1 year of storage was 372 ng/mL. We did not include this result in the table since amphetamine was stable in all the other samples. Open in new tab Sample number 22 was positive for cocaine; the detected value was 2.1 ng/mL in the A sample and 1.4 ng/mL in the B sample. The cut-off value applied for cocaine was 2 ng/mL; therefore, the results for the A and B samples were positive and negative, respectively. This was the only workplace sample where the drug detected was at the cut-off level and the results for the A and B samples had contradictory results. The storage stability after 1 year was evaluated by calculating the percentage change in the reanalyzed A sample from the original value Table lV. There were no apparent indications of storage-related degradation of drugs in the A samples. One sample, number 7, had a high percentage change, with the previous result showing a lower value than the reanalyzed value 1 year later. However, as the other results for cannabis were within the acceptable range, we concluded that this result and the result for ethylmorphine in sample 2 were due to analytical variation. Discussion In general, the drugs detected in oral fluid were correlated with the drugs detected in urine samples (Table II). The concentrations of substances in oral fluid are dependent on the molecules physiological factors such as pH and protein binding ability (15, 19). The positive detection rates are also dependent on the cut-off values for the drugs (Table I). For some analytes such as morphine, the positive detection rate could be increased in oral fluid samples by using a more sensitive LC–MS-MS so that a lower cut-off value could be used. For oral fluid samples, the applied cut-off values are continuously reviewed and revised according to regulatory demands, guidelines and the performance of the analytical instrument. LC–MS-MS is able to detect substances at low concentrations; thus, a lower cut-off values can be applied (16, 20–22). In this work, the heroin metabolite 6-MAM was more frequently detected in oral fluid than in urine samples, and this is in accordance with other studies (23, 24). There was a poor correlation between cannabis detected in urine and oral fluid samples. The results from this study diverge from others in the literature, as the sensitivity and specificity for cannabis in oral fluid compared to urine samples has previously been reported to be as high as 80% (7), whereas it was 50% in this study. The correlation between cannabis in urine and oral fluid samples may be improved by using the metabolite THC-COOH in oral fluid, as this metabolite appears at lower concentrations but has a longer detection window than Δ9-THC (25). A possible explanation for the low detection frequencies in oral fluid compared to urine samples could be that the most recent intake for cannabis occurred more than 48 h prior to sampling in this study. However, the positive detection of Δ9-THC over a longer period among frequent cannabis users during recess has been reported, which complicates the interpretation of recent cannabis use (26, 27). Previously, a more extended detection for THCCOOH was also indicated in urine samples among frequent users during recess (28). Thus, the interpretation of a drug result obtained in oral fluid is of great importance (29). Generally, the positive detection of drugs in oral fluid samples indicates drug intake (30). A negative oral fluid sample could mean no intake of drugs or that drug intake occurred a few days prior. In situations where there is suspicion of drug use, an additional urine sample could complement a negative oral fluid sample. The detection windows are longer for urine samples, and metabolites are commonly detected (31, 32). Oral fluid samples offer detection of more recent drug intake and also detect the parent drugs that could affect the individual’s driving or working performance. Thus, the application of oral fluid testing could be more relevant for identifying drug intake with a potential effect on performance or accident risk. The oral fluid method has been implemented as a routine method in our laboratory since 2016 (16). In our experience, the drugs detected in urine samples, which is the traditional procedure, are the same as those found in oral fluid samples. The most common drugs in the opiate, opioid, amphetamine and benzodiazepine groups detected in urine samples are also detected in oral fluid samples. At the laboratory, we have noticed an increasing trend of positive urine samples for cannabis and cocaine, which is reflected in a greater number of positive findings for these substances in oral fluid samples. Most of the oral fluid samples (90%) sent to the laboratory come from different workplaces. Workplace samples are usually negative, but positive findings are not infrequent, with about 5–10% of workplace samples testing positive for drugs (results not shown here). Because the individual is tested at their workplace, and a positive drug result may have serious consequences; it is not surprising that a positive A sample is challenged by the employee, leading to evaluation of the B sample for a second opinion. Indeed, such a procedure does not usually change the original conclusion, except in the few cases where the values are very close to the cut-offs, or the second-opinion laboratory uses a different cut-off value. We demonstrated that the drugs collected on the pad are the same as to those detected in urine samples, and the drugs in A samples were stable for at least 1 year when stored at −20°C. The A and B samples were analyzed in the same batch to eliminate any analytical differences. In this study, there was a significant difference in the results obtained for the A and B oral fluid samples as the collection was performed at various sites, and it is possible that not all staff were familiar with the collection device. The collection of A and B oral fluid samples was supervised by different trained individuals at different workplaces. We did not inform them that these A and B samples were going to be included in a scientific study. Thus, the sampling procedures were uncontrolled. The neat oral fluid sampling volumes in A and B samples collected using the device were not measured. Thus, we relied on the sampling procedure having been correctly performed, and that sampling was ended when 1 mL of oral fluid was collected and the indicator turned blue, as specified by the manufacturer. When collecting oral fluid samples, sampling adulteration should be considered. There is a risk that an individual may have intentionally tried to tamper with their sample, for example, by sucking the device after the indicator has turned blue, leading to a smaller sample volume on the collection pad. Another possibility is that the different sample handling between A and B samples, where the later was opened for the first time after 1 year of storage could have an effect on concentrations. These two parameters were not investigated in the current study. There was no systematic variation in concentrations between A and B samples; therefore, it is less probable that these two factors may affect the sample results. The drug concentrations in A samples were generally lower than those in B samples, but this was sometimes reversed. Therefore, a more likely explanation for the concentration variation in A and B samples is that the pre-analytical sampling procedure for the Oral Eze pad is complicated. Thus, the drug variation in A and B samples, presented in Table III, is more likely a result from sampling differences, how the pad is positioned in the mouth, collection time, the collected volume or differences in drug recovery from the pad. There are a variety of different sampling devices, and the A and B samples should be evaluated using these devices in uncontrolled individuals at different workplace settings. In the literature, there have been controlled studies where A and B oral fluid samples were collected simultaneously and the drug concentrations were similar (25, 33). However, in the current study, there was a significant difference in the results obtained in uncontrolled A and B oral fluid samples sent to the laboratory for drug testing from different workplaces. Hence, our findings suggest that it may be preferable to collect a single oral fluid sample and then split it into two separate specimens. Conclusion In general, the drugs detected in oral fluid samples are comparable to those obtained in urine samples. When stored at −20°C, the oral fluid samples were stable for at least 1 year. The drug concentrations in A and B oral fluid samples collected from individuals at different workplaces using a collection device can differ significantly. Hence, the results for A and B samples do not always agree, and this could have consequences for samples where the concentrations are at low levels. It may be necessary to improve and further standardize the collection devices, in addition to improving training. References 1. Bosker , W.M. , Huestis , M.A. ( 2009 ) Oral fluid testing for drugs of abuse . Clinical Chemistry , 55 , 1910 – 1931 . Google Scholar Crossref Search ADS PubMed WorldCat 2. Drummer , O.H. ( 2006 ) Drug testing in oral fluid . Clinical Biochemist Reviews , 27 , 147 – 159 . Google Scholar OpenURL Placeholder Text WorldCat 3. Bogstrand , S.T. , Gjerde , H. ( 2014 ) Which drugs are associated with highest risk for being arrested for driving under the influence? A case–control study . Forensic Science International , 240 , 21 – 28 . Google Scholar Crossref Search ADS PubMed WorldCat 4. Chu , M. , Gerostamoulos , D., Beyer , J., Rodda , L., Boorman , M., Drummer , O.H. ( 2012 ) The incidence of drugs of impairment in oral fluid from random roadside testing . Forensic Science International , 215 , 28 – 31 . Google Scholar Crossref Search ADS PubMed WorldCat 5. Davey , J. , Armstrong , K., Martin , P. ( 2014 ) Results of the Queensland 2007–2012 roadside drug testing program: the prevalence of three illicit drugs . Accident Analysis and Prevention , 65 , 11 – 17 . Google Scholar Crossref Search ADS PubMed WorldCat 6. Caplan , Y.H. , Goldberger , B.A. ( 2001 ) Alternative specimens for workplace drug testing . Journal of Analytical Toxicology , 25 , 396 – 399 . Google Scholar Crossref Search ADS PubMed WorldCat 7. West , R. , Mikel , C., Hofilena , D., Guevara , M. ( 2018 ) Positivity rates of drugs in patients treated for opioid dependence with buprenorphine: a comparison of oral fluid and urine using paired collections and LC–MS/MS . Drug and Alcohol Dependence , 193 , 183 – 191 . Google Scholar Crossref Search ADS PubMed WorldCat 8. Conermann , T. , Gosalia , A.R., Kabazie , A.J., Moore , C., Miller , K., Fetsch , M., et al. ( 2014 ) Utility of oral fluid in compliance monitoring of opioid medications . Pain Physician , 17 , 63 – 70 . Google Scholar PubMed OpenURL Placeholder Text WorldCat 9. Dams , R. , Choo , R.E., Lambert , W.E., Jones , H., Huestis , M.A. ( 2007 ) Oral fluid as an alternative matrix to monitor opiate and cocaine use in substance-abuse treatment patients . Drug and Alcohol Dependence , 87 , 258 – 267 . Google Scholar Crossref Search ADS PubMed WorldCat 10. Miller , K.L. , Puet , B.L., Roberts , A., Hild , C., Carter , J., Black , D.L. ( 2017 ) Urine drug testing results and paired oral fluid comparison from patients enrolled in long-term medication-assisted treatment in Tennessee . Journal of Substance Abuse Treatment , 76 , 36 – 42 . Google Scholar Crossref Search ADS PubMed WorldCat 11. Heltsley , R. , Depriest , A., Black , D.L., Crouch , D.J., Robert , T., Marshall , L., et al. ( 2012 ) Oral fluid drug testing of chronic pain patients. II. Comparison of paired oral fluid and urine specimens . Journal of Analytical Toxicology , 36 , 75 – 80 . Google Scholar Crossref Search ADS PubMed WorldCat 12. Vindenes , V. , Yttredal , B., Oiestad , E.L., Waal , H., Bernard , J.P., Morland , J.G., et al. ( 2011 ) Oral fluid is a viable alternative for monitoring drug abuse: detection of drugs in oral fluid by liquid chromatography-tandem mass spectrometry and comparison to the results from urine samples from patients treated with methadone or buprenorphine . Journal of Analytical Toxicology , 35 , 32 – 39 . Google Scholar Crossref Search ADS PubMed WorldCat 13. Kadehjian , L. ( 2005 ) Legal issues in oral fluid testing . Forensic Science International , 150 , 151 – 160 . Google Scholar Crossref Search ADS PubMed WorldCat 14. Oral-fluid-2015-11-01-v2.0.pdf (2015). http://www.ewdts.org/ewdts-guidelines.html. 15. Desrosiers , N.A. , Huestis , M.A. ( 2019 ) Oral fluid drug testing: analytical approaches, issues and interpretation of results . Journal of Analytical Toxicology , 43 , 415 – 443 . Google Scholar Crossref Search ADS PubMed WorldCat 16. Zheng , Y. , Sparve , E., Bergstrom , M. ( 2018 ) A simple validated multi-analyte method for detecting drugs in oral fluid by ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) . Drug Testing and Analysis , 10 , 1001 – 1008 . Google Scholar Crossref Search ADS PubMed WorldCat 17. Andersson , M. , Stephanson , N., Ohman , I., Terzuoli , T., Lindh , J.D., Beck , O. ( 2014 ) Direct and efficient liquid chromatographic-tandem mass spectrometric method for opiates in urine drug testing—importance of 6-acetylmorphine and reduction of analytes . Drug Testing and Analysis , 6 , 317 – 324 . Google Scholar Crossref Search ADS PubMed WorldCat 18. Cohen , J.A. ( 1960 ) Coefficient of agreement for nominal scales . Educational and Psycological Measurement , 20 , 37 – 46 . Google Scholar Crossref Search ADS WorldCat 19. Drummer , O.H. ( 2005 ) Review: pharmacokinetics of illicit drugs in oral fluid . Forensic Science International , 150 , 133 – 142 . Google Scholar Crossref Search ADS PubMed WorldCat 20. Valen , A. , Leere Oiestad , A.M., Strand , D.H., Skari , R., Berg , T. ( 2017 ) Determination of 21 drugs in oral fluid using fully automated supported liquid extraction and UHPLC-MS/MS . Drug Testing and Analysis , 9 , 808 – 823 . Google Scholar Crossref Search ADS PubMed WorldCat 21. Di Rago , M. , Chu , M., Rodda , L.N., Jenkins , E., Kotsos , A., Gerostamoulos , D. ( 2016 ) Ultra-rapid targeted analysis of 40 drugs of abuse in oral fluid by LC-MS/MS using carbon-13 isotopes of methamphetamine and MDMA to reduce detector saturation . Analytical and Bioanalytical Chemistry , 408 , 3737 – 3749 . Google Scholar Crossref Search ADS PubMed WorldCat 22. Grabenauer , M. , Moore , K.N., Bynum , N.D., White , R.M., Mitchell , J.M., Hayes , E.D., et al. ( 2018 ) Development of a quantitative LC-MS-MS assay for codeine, morphine, 6-acetylmorphine, hydrocodone, hydromorphone, oxycodone and oxymorphone in neat oral fluid . Journal of Analytical Toxicology , 42 , 392 – 399 . Google Scholar Crossref Search ADS PubMed WorldCat 23. Bottcher , M. , Lierheimer , S., Peschel , A., Beck , O. ( 2019 ) Detection of heroin intake in patients in substitution treatment using oral fluid as specimen for drug testing . Drug and Alcohol Dependence , 198 , 136 – 139 . Google Scholar Crossref Search ADS PubMed WorldCat 24. Presley , L. , Lehrer , M., Seiter , W., Hahn , D., Rowland , B., Smith , M., et al. ( 2003 ) High prevalence of 6-acetylmorphine in morphine-positive oral fluid specimens . Forensic Science International , 133 , 22 – 25 . Google Scholar Crossref Search ADS PubMed WorldCat 25. Milman , G. , Barnes , A.J., Schwope , D.M., Schwilke , E.W., Goodwin , R.S., Kelly , D.L., et al. ( 2011 ) Cannabinoids and metabolites in expectorated oral fluid after 8 days of controlled around-the clock oral THC administration . Analytical and Bioanalytical Chemistry , 401 , 599 – 607 . Google Scholar Crossref Search ADS PubMed WorldCat 26. Swortwood , M.J. , Newmeyer , M.N., Andersson , M., Abulseoud , O.A., Scheidweiler , K.B., Huestis , M.A. ( 2017 ) Cannabinoid disposition in oral fluid after controlled smoked, vaporized, and oral cannabis administration . Drug Testing and Analysis , 9 , 905 – 915 . Google Scholar Crossref Search ADS PubMed WorldCat 27. Lee , D. , Milman , G., Barnes , A.J., Goodwin , R.S., Hirvonen , J., Huestis , M.A. ( 2011 ) Oral fluid cannabinoids in chronic, daily cannabis smokers during sustained, monitored abstinence . Clinical Chemistry , 57 , 1127 – 1136 . Google Scholar Crossref Search ADS PubMed WorldCat 28. Lowe , R.H. , Darwin , W.D., Herning , R., Cadet , J.L., Huestis , M.A. ( 2009 ) Extended urinary Delta9-tetrahydrocannabinol excretion in chronic cannabis users precludes use as a biomarker of new drug exposure . Drug and Alcohol Dependence , 105 , 24 – 32 . Google Scholar Crossref Search ADS PubMed WorldCat 29. Cone , E.J. , Huestis , M.A. ( 2007 ) Interpretation of oral fluid tests for drugs of abuse . Annals of the New York Academy of Sciences , 1098 , 51 – 103 . Google Scholar Crossref Search ADS PubMed WorldCat 30. Verstraete , A.G. ( 2004 ) Detection times of drugs of abuse in blood, urine, and oral fluid . Therapeutic Drug Monitoring , 26 , 200 – 205 . Google Scholar Crossref Search ADS PubMed WorldCat 31. Bruun , L.D. , Kjeldstadli , K., Temte , V., Birdal , M., Bachs , L., Langodegard , M., et al. ( 2019 ) Detection time of oxazepam and zopiclone in urine and oral fluid after experimental oral dosing . Journal of Analytical Toxicology , 43 , 369 – 377 . Google Scholar Crossref Search ADS PubMed WorldCat 32. Temte , V. , Kjeldstadli , K., Bruun , L.D., Birdal , M., Bachs , L., Karinen , R., et al. ( 2019 ) An experimental study of diazepam and alprazolam kinetics in urine and oral fluid following single oral doses . Journal of Analytical Toxicology , 43 , 104 – 111 . Google Scholar Crossref Search ADS PubMed WorldCat 33. Niedbala , R.S. , Kardos , K.W., Fritch , D.F., Kardos , S., Fries , T., Waga , J., et al. ( 2001 ) Detection of marijuana use by oral fluid and urine analysis following single-dose administration of smoked and oral marijuana . Journal of Analytical Toxicology , 25 , 289 – 303 . Google Scholar Crossref Search ADS PubMed WorldCat © The Author(s) 2020. Published by Oxford University Press. All rights reserved. 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TI - Detection of Drugs in Oral Fluid Samples Using a Commercially Available Collection Device: Agreement with Urine Testing and Evaluation of A and B Samples Obtained from Employees at Different Workplace Settings with Uncontrolled Sampling Procedures
JF - Journal of Analytical Toxicology
DO - 10.1093/jat/bkaa024
DA - 2021-01-21
UR - https://www.deepdyve.com/lp/oxford-university-press/detection-of-drugs-in-oral-fluid-samples-using-a-commercially-haPCxQwKkD
SP - 1004
EP - 1011
VL - 44
IS - 9
DP - DeepDyve
ER -