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The aim of this study is to assess the results of inspections in the last three years of drug abuse testing in medical laboratories according to the latest regulations in Turkey. The on-site inspections of medical laboratories for drugs abuse testing performed in Alcohol and Drug Addiction Treatment Centers during 2014-2016 are described, and laboratory processes and performance evaluated. The performance of 35 laboratories in 2014, 62 laboratories in 2015, and 94 laboratories in 2016 were scored as the sum of the scores for all answers on the inspection form. An inspected laboratory was considered to have an unconformity if the total score was less than 2/3 of maximum score. The total scores of inspections and the number of laboratories with between years were compared using one-way analysis of variance and slope Chi-square for trend test, respectively. Total scores increased statistically significantly from 35.9 ± 16.2 in 2014, to 43.5 ± 16.3 in 2015 and 49.1 ± 1.3 in 2016 (p < 0.001). The laboratories with unconformities decreased statistically significantly from 57% in 2014 to 37% in 2015 and 22% in 2016 (p < 0.001). The published legislation and the inspections contributed to national standardization and improved quality of service in medical laboratories for drug abuse testing., (© 2018 John Wiley & Sons, Ltd.)

For many drugs, there is a poor correlation between the plasma and oral fluid (OF) concentrations, due to differences in OF pH, oral contamination, stimulation of OF flow and variability of the volume of sample taken. The aim of this study was to evaluate the OF/plasma ratio and variability in drug concentration in OF sampled by two commercially available collection systems: Saliva Collection System (SCS) and Quantisal. Blood and OF samples were collected from 12 volunteers after intake of 19.5 mg codeine phosphate. Six persons were sampled by SCS first, followed by Quantisal; six other participants used Quantisal before SCS. The OF content of SCS tubes was measured spectrophotometrically. The Quantisal devices were weighed to correct for the effectively obtained OF volume. Codeine was measured by gas chromatography-mass spectrometry. The mean codeine concentration at 1 h was 29.8 ± 18.8 μg/L in plasma, 72.8 ± 63.9 μg/L in SCS OF and 85.3 ± 72.6 μg/L in Quantisal OF. The mean OF/plasma ratio was 2.30 ± 0.77 (SCS) and 2.69 ± 1.94 (Quantisal). Pearson's correlation coefficient between OF and plasma codeine concentrations was statistically significantly (P = 0.005) higher for SCS (R(2) = 0.745) than for Quantisal (R(2) = 0.403). The variability in ratios with Quantisal was markedly reduced when used after SCS. Codeine concentrations measured in OF taken with SCS correlate better with plasma concentrations than in OF obtained with Quantisal, particularly when Quantisal was used first., (© The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Background: The aim of this study was to compare the usefulness of 3 different screening instruments (questionnaires) for the detection of cannabis use (CU) with biological markers in blood and hair., Methods: Ninety-four students were recruited in October 2013. Participants filled out the Severity of Dependence Scale (SDS), the CAGE-AID ("Cut down Annoyed Guilty Eye-opener"-Adapted to Include Drugs), and ProbCannabis-DT questionnaires concerning their possible CU. Blood and hair samples were taken and analyzed by gas chromatography-mass spectrometry. Logistic regression (Nagelkerke R(2)) and receiver operating characteristic (ROC) curve analyses were performed. THCCOOH (Δ(9)-tetrahydrocannabinoic acid) plasma of ≥5 ng/mL and THC (Δ(9)-tetrahydrocannabinol) hair concentrations of ≥0.1 and ≥0.02 ng/mg were used as the gold standard for CU. The questionnaire results were compared with different concentration ranges for THCCOOH in plasma (<5, 5-75, and >75 ng/mL, indicating the intensity of use) and THC in hair (≥0.02 ng/mg, ≥0.1 ng/mg)., Results: The Nagelkerke R(2) for comparing the SDS, CAGE-AID, and ProbCannabis-DT with THCCOOH in plasma was 0.350, 0.489, and 0.335, respectively. The area under the ROC curve (95% confidence interval) was 0.772 (0.662-0.882), 0.797 (0.710-0.884), and 0.769 (0.669-0.870), respectively. Corresponding sensitivity/specificity were 70%/84%, 100%/59%, and 87%/67%, respectively. These values were similar to those compared to a 0.02 ng/mg THC cutoff in hair., Conclusions: Moderate agreement was found between all questionnaires and biomarkers of CU. The CAGE-AID and probCannabis-DT questionnaires were very sensitive, but less specific. SDS was less sensitive, but more specific.

Aim: To assess whether analysis of oral fluid can be used to identify individual drivers with drug concentrations in blood above 25ng/mL for amphetamine and methamphetamine, 10ng/mL for cocaine and 1.0ng/mL for tetrahydrocannabinol (THC), which are the cut-off concentrations used in the European DRUID Project, by calculating the diagnostic accuracies when using the analytical cut-off concentrations in oral fluid as well as for the optimal cut-off concentrations., Methods: Paired samples of whole blood and oral fluid collected with the Statsure SalivaSampler were obtained from 4080 drivers in four European countries and analysed for amphetamine, methamphetamine, cocaine and THC using GC-MS or LC-MS. The vast majority (89%) were random drivers not suspected of drug-impaired driving. Receiver-Operating Characteristic analysis was used to evaluate the analytical results., Results: The prevalence of drug findings above the cut-off concentrations in blood was 1.3% for amphetamine, 1.0% for methamphetamine, 0.6% for cocaine and 1.3% for THC. The cut-off concentrations in oral fluid that gave the highest diagnostic accuracy were for amphetamine 130ng/mL (accuracy 99.8%), methamphetamine 280ng/mL (accuracy 99.9%), cocaine 570ng/mL (accuracy 99.6%), and THC 38ng/mL (accuracy 98.3%). The proportion of false positives were 0.2%, 0.1%, 0.1% and 0.9%; and the proportion of false negatives were 0.1%, 0.0%, 0.3% and 0.8%, respectively, when using those cut-offs. The positive predictive values were 87.9%, 92.9%, 84.6% and 35.7% for amphetamine, methamphetamine, cocaine and THC, respectively., Conclusions: Analysis of concentrations of illicit drugs in oral fluid could not be used to accurately identify drivers with drugs concentrations above the selected cut-offs in blood in a cohort of drivers with low prevalence of drugs., (Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.)

Background: Internationally, urine on-site testing has been used for detecting drivers under the influence of drugs (DUID) but more and more countries, such as Belgium, are switching to oral fluid screening., Objective: To compare the previous (published in 1999) and current (published 2009) enforcement procedures of DUID in Belgium. The two evaluated procedures differ in the way the drivers are screened by the police (signs of impairment versus signs of recent drug use), the matrix for screening (urine versus oral fluid) and the analytical cut-off concentrations in plasma., Methods: Data on positive screening and confirmation results were gathered from 1st April 2008 to 30th September 2010, when urine screening (Dipro Druglab panels test) was performed; and from 1st October 2010 to 31st March 2013, when an on-site oral fluid test (Securetec Drugwipe 5(+)) was used., Results: Approximately 4100 data sets related to urine screening and 3900 data sets related to oral fluid screening were studied. Eighty-eight percent of positive urine on-site tests yielded positive results in plasma for cannabis, 21% for cocaine, 20% for amphetamines and 7% for opiates. Sixty-six percent of the positive oral fluid on-site tests yielded positive results in plasma for cannabis, 30% for cocaine, 28% for amphetamines and 8% for opiates. For cannabis, opiates and amphetamines more negative results in plasma were observed in the period of urine screening., Conclusions: The percentage of plasma samples of tested drivers, in which none of the positive screened target drugs were present in a concentration above the legal cut-off value, has decreased from 17% to 8% since the introduction of the current legislation involving oral fluid screening., (Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.)

The relationship of drug concentrations between oral fluid and whole blood was evaluated by studying the linear correlation of concentrations and calculating the oral fluid to blood concentration ratios (OF/B) for different substances. Paired oral fluid and whole blood samples were collected from volunteers and persons suspected of drug use in four European countries. Oral fluid samples were collected with the Saliva∙Sampler™ device. All samples were analyzed for drugs of abuse and psychoactive medicines with validated gas and liquid chromatography-mass spectrometric methods. The median OF/B ratios were, for amphetamines 19-22, for opioids 1.8-11, for cocaine and metabolites 1.7-17, for tetrahydrocannabinol (THC) 14, for benzodiazepines 0.035-0.33, and for other psychoactive medicines 0.24-3.7. Most of the these results were close to theoretical values based on the physicochemical properties of the drugs and to values presented earlier, but there was a lot of inter-individual variation in the OF/B ratios. For all substances, except for lorazepam (R(2)  = 0.031) and THC (R(2)  = 0.030), a correlation between the oral fluid and whole blood concentrations was observed. Due to large variation seen here, drug findings in oral fluid should not be used to estimate the corresponding concentrations in whole blood (or vice versa). However, detection of drugs in oral fluid is a sign of recent drug use and oral fluid can be used for qualitative detection of several drugs, e.g. in epidemiological prevalence studies. By optimizing the sampling and the analytical cut-offs, the potential of oral fluid as a confirmation matrix could be enhanced., (Copyright © 2013 John Wiley & Sons, Ltd.)

Background: Analysis of samples of oral fluid (mixed saliva) is increasingly being used to detect recent drug use. The aim of this investigation was to assess the suitability of testing oral fluid as a biomarker for the presence of 4 benzodiazepines in blood and its possible application in clinical settings and in research on drug use., Methods: Paired samples of oral fluid and blood from 4080 individuals in 4 European countries were collected and analyzed for benzodiazepines using gas or liquid chromatography with mass spectroscopic detection., Results: Concentration data for the 4 most commonly detected benzodiazepines were studied: alprazolam, clonazepam, diazepam, and nordiazepam. Large variations in oral fluid to blood concentration ratios were observed for the studied benzodiazepines. The interquartile ranges for the oral fluid to blood concentrations ratios corresponded to 88%-197% of the median values. Selecting cutoff concentrations in oral fluid that gave the best accuracy in identifying individuals with benzodiazepine concentrations in blood above chosen thresholds produced accuracies of 74%-85% and the fraction of false negatives was 9%-23%., Conclusions: The concentration of the 4 studied benzodiazepines in oral fluid can neither be used to accurately estimate the concentrations in blood nor to correctly identify patients with blood drug concentrations below or above recommended therapeutic levels. When using analytical methods with limits of quantitation corresponding to concentrations less than 0.5 ng/mL in undiluted oral fluid, it may be used to confirm a recent intake of benzodiazepines. However, it is likely that some false negatives may occur.

Oral fluid is an easily available specimen for studying drug use in a cohort or population. The prevalence of drugs in samples of oral fluid is the same as the prevalence in blood if using equivalent cutoff concentrations. The cutoffs in oral fluid may be higher or lower than that in blood in accordance with the median oral fluid-to-blood (OF/B) concentration ratio, but it is also influenced by the skewness of the distribution of OF/B ratios. The aim of this study was to determine formulae for the estimation of equivalent cutoff concentrations in oral fluid and blood for 12 commonly used illegal and medicinal psychoactive drugs when oral fluid was collected with Statsure Saliva·Sampler™. Paired samples from 4,080 persons were collected and analyzed with chromatographic methods and mass spectroscopic detection. Regression formulae for the concentrations corresponding to selected percentiles in oral fluid versus the same concentration percentiles in blood were determined. The accuracy when multiplying the cutoff thresholds in blood with the average and median OF/B ratios to estimate equivalent cutoffs in oral fluid was also investigated. Prevalence regression gave the most accurate results. The regression formulae can be used to estimate equivalent cutoff concentrations in oral fluid and blood.

The objective of this paper is to compare concentrations of alcohol, illicit, and medicinal drugs in seriously injured drivers and drivers selected randomly at the roadside. Blood samples were analyzed for alcohol, 17 medicinal drugs and 8 illicit psychoactive substances and/or their metabolites by ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) and gas chromatography mass spectrometry (GC-MS) in injured drivers admitted to the emergency departments of five hospitals in Belgium between January 2008 and May 2010 and in drivers randomly selected between January 2008 and September 2009. Three hundred and seventy-seven seriously injured drivers and 2750 roadside respondents were selected. In the roadside survey, out of the 203 concentrations above DRUID (Driving Under the Influence of Drugs, Alcohol and Medicines) cut-offs for medicinal drugs, 51% were in the therapeutic range, 46% infratherapeutic, and 2.5% supratherapeutic. In the seriously injured drivers, out of the 78 concentrations above DRUID cut-offs for medicinal drugs, these percentages were respectively 63%, 33%, and 4%. Significant differences were found in the distribution of concentrations for opioids, benzodiazepines, and Z-drugs. For the latter, while in the seriously injured drivers study most concentrations were therapeutic, in the roadside survey most were infratherapeutic. The opposite was observed for the opioids. Eight and 41% of the roadside respondents and injured drivers, respectively, had an alcohol concentration above 0.1 g/L, with higher concentrations found in the injured drivers. For illicit drugs, significant differences were found for amphetamine and cocaine, for which respectively lower and higher concentrations were observed in the blood samples taken in the roadside survey., (Copyright © 2012 John Wiley & Sons, Ltd.)

Objective: To estimate the percentage of drivers involved in a traffic crash in Belgium who have alcohol and drugs in their blood., Methods: Blood samples of the drivers injured in a traffic crash and admitted to the emergency departments of 5 hospitals in Belgium between January 2008 and May 2010 were analyzed for ethanol (with an enzymatic method) and 22 other psychoactive substances (with ultra-performance liquid chromatography with tandem mass spectrometry or gas chromatography-mass spectrometry)., Results: One thousand seventy-eight drivers were included in the study. Alcohol (≥0.1 g/L) was the most common substance (26.2%). A large majority of the drivers (64%) who were positive for alcohol had a blood alcohol concentration (BAC) ≥1.3 g/L (legal limit in Belgium: 0.5 g/L). These high BACs were most frequent among male injured drivers. Cannabis was the most prevalent illicit drug (5.3%) and benzodiazepines (5.3%) were the most prevalent medicinal drugs. Approximately 1 percent of the drivers were positive for cocaine and amphetamines. No drivers tested positive for illicit opioids. Medicinal drugs were more likely to be found among female drivers and drivers older than 35 years, and alcohol and illicit drugs were more likely to be found among male drivers and drivers younger than 35 years., Conclusion: A high percentage of the injured drivers were positive for a psychoactive substance at the time of injury. Alcohol was the most common substance, with 80 percent of the positive drivers having a BAC ≥0.5 g/L. Compared to a roadside survey in the same area, drivers/riders with high BACs and combinations of drugs were overrepresented. Efforts should be made to increase alcohol and drug enforcement. The introduction of a categorization and labeling system might reduce driving under the influence of medicinal drugs by informing health care professionals and patients.

Objective: The purpose of this study was to compare the prevalence of psychoactive substances in general traffic in The Netherlands and Belgium., Method: Randomly selected car drivers and drivers of small vans in six police regions in The Netherlands and five police regions in Belgium were included between January 2007 and August 2009. Blood and oral fluid samples were analyzed for 23 substances, including ethanol (alcohol), by means of ultra performance liquid chromatography-tandem mass spectrometry or gas chromatography-mass spectrometry analysis. Samples were weighted according to the distribution of traffic over eight 6-hour periods. Substance groups were categorized in five mutually exclusive classes: single alcohol use, single illicit drug use, single medicinal drugs use, multiple drug use (including drugs from two or more separate substance groups but excluding alcohol), and drug use (either single or multiple) in combination with alcohol., Results: In total, 7,771 drivers (4,822 in The Netherlands and 2,949 in Belgium) were included in the study. In Belgium, the prevalence of single alcohol (6.4%) and single medicinal drugs (3.0%) was much higher than in The Netherlands (2.2% and 0.6%, respectively), whereas the single illicit drugs were more common in Dutch traffic (2.2%) than in Belgian traffic (0.6%). Compared with the estimated prevalence of psychoactive substances in the general driving public in Europe, the prevalence in Belgium (10.7%) was greater than the European average (7.4%), and the prevalence in The Netherlands was below the European average (5.5%)., Conclusions: The observed prevalence of psychoactive substances varies largely between The Netherlands and Belgium. Probable reasons for the differences are the higher level of alcohol enforcement in The Netherlands and nonresponse bias in the Belgian study (for illicit drugs in particular). Furthermore, cultural differences and variances in prescription policy could also be influential.

Previous research demonstrated that Methadone Maintenance Programs (MMP) and Methadone Maintenance Treatment/Therapy (MMT) could significantly reduce the mortality risk. However, in current forensic practice, methadone ingestion can still directly or indirectly be involved in fatalities. The objectives of this study were twofold. Firstly, referring to the wide range of blood levels reported in methadone-related fatalities, we aimed to provide insight into the interpretation of a quantitative post-mortem blood concentration. Secondly, to examine and discuss possible causes, mechanisms and manners of death. During a 30-year-period, all medico-legal files at the Department of Forensic Medicine (Ghent University) were searched through, to investigate whether methadone was involved in the fatal outcome. A significant increase in the methadone-related fatalities was found since 1995, which has also been noticed in other studies. In our study (n=48), the most frequent cause of death was intoxication: only one was due to a pure methadone intoxication, whereas in all other fatal intoxications, a poly-drug intoxication was found. In this study, cardiopulmonary failure, induced by depression of the vital centres in the brainstem, was--as expected--the most important mechanism of death. When we considered the post-mortem blood levels in our study group, we observed a wide range, namely between 0.10 and 4.13 microg/ml (median: 0.54 microg/ml, mean: 0.81 microg/ml, SD: 0.14). This was in line with previous reports, although the extreme values differed. We conclude that the interpretation of post-mortem methadone blood levels is still hazardous due to e.g. difficulties to assess the individual tolerance level, the variety of surviving periods after ingestion, interfering post-mortem redistribution and the combined ingestion of methadone with other drugs. Therefore, a close collaboration between the forensic pathologist and toxicologist is recommended in order to provide a well-grounded conclusion.

The objective of this study was to compare the number of drivers with drug concentrations above the legal cutoffs for driving under the influence of illicit substances in paired samples of blood and oral fluid. Between January 2008 and September 2009, 2,949 randomly selected drivers participated in a roadside survey. Each was asked to provide blood and oral fluid. Samples were analyzed for 11 illicit substances or metabolites by ultra-performance liquid chromatography-tandem mass spectrometry and gas chromatography-tandem mass spectrometry. Out of the 2,750 drivers who gave both blood and oral fluid, 28 (1.0%) had drug concentrations above the legal cutoff in blood and 71 (2.6%) were above the legal cutoff in oral fluid. Fifteen (7.5%) of the 199 drivers who gave an oral fluid sample but refused to provide blood tested positive, significantly more than drivers who provided both samples. Based on oral fluid analysis, 2.6 times more subjects tested positive for drugs compared to blood analysis. Those that refused to give a blood sample were 3 times more likely to test positive for drugs. Even in a survey that guaranteed total anonymity, people fearing a positive test result might have been more likely to refuse to give a blood sample.

The use of oral fluid (OF) as an alternative matrix for the detection of drugs of abuse has increased over the last decade, leading to the need for a rapid, simple, and reliable on-site OF testing device. Four on-site OF drug testing devices (Dräger DrugTest 5000, Cozart DDS, Mavand Rapid STAT, and Innovacon OrAlert) were evaluated on 408 volunteers at drug treatment centers. UPLC-MS-MS results were used as reference to determine sensitivity, specificity and accuracy for each device, applying Belgian legal confirmation cutoffs for benzoylecgonine, cocaine, and THC (10 ng/mL); morphine and 6-acetylmorphine (5 ng/mL); and amphetamine and 3,4-methylenedioxymethylamphetamine (25 ng/mL). Sensitivity for cocaine was 50%, 50%, 27%, and 11% for DrugTest, OrAlert, Rapid STAT, and DDS 806, respectively. For opiates, sensitivities were 84%, 73%, 77%, and 65%, respectively. For THC, the sensitivities were 81%, 23%, 43%, and 28%, respectively. For amphetamines, the sensitivities were 75%, 33%, 17%, and 67%, respectively. Specificity was >88% for opiates and THC, > 90% for amphetamines, and > 97% for cocaine. All tests showed good specificity. DrugTest had the highest sensitivity, although it was still low for some analytes.

Aim: To validate a method for determining equivalent drug cutoff concentrations for tetrahydrocannabinol and amphetamine in blood and oral fluid, which ensures that the drug prevalence in samples of blood and oral fluid taken simultaneously is equal., Methods: A method using regression analysis of drug concentrations for defined percentiles in blood and oral fluid was developed. The accuracy and precision of this technique was investigated. As study populations, 311 cannabis users and 197 amphetamine users from the Rosita-2 Project were used., Results: A total of 80 paired oral fluid and blood concentrations were needed to determine accurate regression formulae. When using the formulae to calculate drug cutoff concentrations in oral fluid corresponding to 2.0, 4.0, 6.0, 8.0 and 10.0 ng/ml tetrahydrocannabinol in blood and 200, 400, 600, 800 and 1000 ng/ml amphetamine in blood, the accuracy was better than 100 ± 20% compared to actual prevalence in blood with precision better than ± 20%., Conclusion: Prevalence regression may be a useful tool in estimating equivalent cutoff concentrations in blood and oral fluid., (Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.)

In recent years, the interest in the use of oral fluid as a biological matrix has increased significantly, particularly for detecting driving under the influence of drugs (DUID). In this study, the relationship between the oral fluid and the blood concentrations of drugs of abuse in drivers suspected of DUID is discussed. Blood and oral fluid samples were collected from drivers suspected of DUID or stopped during random controls by the police in Belgium, Germany, Finland, and Norway for the ROSITA-2 project. The blood samples were analyzed by gas chromatography-mass spectrometry (GC-MS) or liquid chromatography-mass spectrometry (LC-MS), sometimes preceded by immunoassay screening of blood or urine samples. The oral fluid samples were analyzed by GC-MS or LC-MS(/MS). Scatter plots and trend lines of the blood and oral fluid concentrations and the median, mean, range, and SD of the oral fluid to blood (OF:B) ratios were calculated for amphetamines, benzodiazepines, cocaine, opiates, and Delta(9)-2 tetrahydrocannabinol. The ratios found in this study were comparable with those that were published previously, but the range was wider. The OF:B ratios of basic drugs such as amphetamines, cocaine, and opiates were >1 [amphetamine: median (range) 13 (0.5-182), methylenedioxyamphetamine: 4 (1-15), methylenedioxymethamphetamine: 6 (0.9-88), methamphetamine: 5 (2-23), cocaine: 22 (4-119), benzoylecgonine: 1 (0.2-11), morphine: 2 (0.8-6), and codeine: 10 (0.8-39)]. The ratios for benzodiazepines were very low, as could be expected as they are highly protein bound and weakly acidic, leading to low oral fluid concentrations [diazepam: 0.02 (0.01-0.15), nordiazepam: 0.04 (0.01-0.23), oxazepam: 0.05 (0.03-0.14), and temazepam: 0.1 (0.06-0.54)]. For tetrahydrocannabinol, an OF:B ratio of 15 was found (range 0.01-569). In this study, the time of last administration, the dose, and the route of administration were unknown. Nevertheless, the data reflect the variability of the OF:B ratios in drivers thought to be under the influence of drugs. The wide range of the ratios, however, does not allow reliable calculation of the blood concentrations from oral fluid concentrations.

Aims: A major problem in assessing the true public health impact of drug-use on driving and overall traffic safety is that the variables being measured across studies vary significantly. In studies reported in a growing global literature, basic parameters assessed, analytical techniques and drugs tested are simply not comparable due to lack of standardization in the field. These shortcomings severely limit the value of this research to add knowledge to the field. A set of standards to harmonize research findings is sorely needed. This project was initiated by several international organizations to develop guidelines for research on drugged driving., Methods: A September 2006 meeting of international experts discussed the harmonization of protocols for future research on drugged driving. The principal objective of the meeting was to develop a consensus report setting guidelines, standards, core data variables and other controls that would form the basis for future international research. A modified Delphi method was utilized to develop draft guidelines. Subsequently, these draft guidelines were posted on the internet for global review, and comments received were integrated into the final document., Results: The Guidelines Document is divided into three major sections, each focusing upon different aspects of drugged driving research (e.g. roadside surveys, prevalence studies, hospital studies, fatality and crash investigations, etc.) within the critical issue areas of 'behavior', 'epidemiology' and 'toxicology'. The behavioral section contains 32 specific recommendations; (2) epidemiology 40 recommendations; and (3) toxicology 64 recommendations., Conclusions: It is anticipated that these guidelines will improve significantly the overall quality of drugged driving research and facilitate future cross-study comparisons nationally and globally.

In Belgium, the driving under the influence of drugs (DUID) procedure consists of three steps: observation of external signs of drug consumption by a police officer; an on-site urine test for amphetamines, cannabinoids, cocaine, and opiates; and blood sampling by a physician for gas chromatography-mass spectrometry analysis. The driver is sanctioned if THC is greater than 2 ng/mL, morphine is greater than 20 ng/mL, or amphetamine, methylenedioxymethamphetamine (MDMA), methylenedioxyethylamphetamine, N-methyl-1-(3.4-methylenedioxyphenyl)-2-butanamine, cocaine, or benzoylecgonine are greater than 50 ng/mL in plasma. We analyzed the results of 450 blood samples taken from May 2000 to February 2005. Cannabis was most often found above the cut-off (73.5% of the cases), followed by MDMA (20.4%), amphetamine (19.8%), benzoylecgonine (17.9%), cocaine (6.9%), and morphine (2.7%). One drug was found in 72.0% of the cases, two drugs in 22.6%, three drugs in 5.2%, and four drugs in 0.25%. In 10.7% of the plasma samples no target drugs were found above the legal cut-off. This percentage was 8.4% when urine was obtained and tested on-site and 21.2% when no urine was obtained (chi2 = 8.574, P = 0.0034). In 64.6% of these samples, a target drug (THC in 74.2%) was found under the legal cut-off. These data indicate that roadside urine testing significantly decreases the number of unnecessary blood analyses in DUID.

We analyzed 225 urine samples with FPIA (Abbott Amphetamine/Methamphetamine II on ADx and AxSYM), EMIT (Emit II Plus Monoclonal Amphetamine/Metamphetamine assay and EMIT II Plus Amphetamines assay, EMIT N), and KIMS (standard protocol and MDMA protocol, KIMS and KIMS X, respectively) immunoassays and compared their sensitivity and specificity. All assays were calibrated and used semi-quantitatively. All samples that screened positive by any amphetamine screening method and 15% of the negative samples were confirmed by liquid chromatography-tandem mass spectrometry (LC-MS-MS). A sample was considered positive for amphetamines if amphetamine, methamphetamine, methylenedioxymethamphetamine, methylenedio-xyethylamphetamine, or methylenedioxyamphetamine was present at 250 ng/mL. Ninety (40%) of the samples were positive by LC-MS-MS. The areas under the receiver operating characteristic curve varied between 0.972 (KIMS X) and 1.000 (ADx). The optimal cut-off concentrations varied between 271 ng/mL (EMIT N) and 723 ng/mL (AxSYM). The sensitivity was 100% for ADx and between 93 and 95% for the other assays. The specificity varied between 88% (KIMS) and 100% (EMIT N). Use of a 500 ng/mL screening cut-off would have resulted in identical or very similar results for ADx and KIMS X and large increases in the false positives for AxSYM and EMIT and the false negatives for EMIT N and KIMS.

In recent years the demand for drug testing in oral fluid in cases of driving under the influence has been increasing. The main advantages of saliva/oral fluid are the possibility for non-medical personnel to collect it without embarrassment and a better correlation between presence of drugs in oral fluid and impairment. Several surveys have been performed since the 1980s using saliva, and researchers encountered problems related to insufficient sample volume and insufficient sensitivity of the analytical methods. Steady progress has been shown in sample collection, knowledge of toxicokinetics in oral fluid, reliability of on-site and laboratory-based immunoassays and confirmation methods. In a few countries, legislation was passed that allows the use of saliva as a matrix for screening or confirmation. Despite this progress, some more work needs to be done, principally in the areas of the sensitivity and reliability of on-site screening devices, particularly for cannabis and benzodiazepines, knowledge about passive contamination and more generalised proficiency testing before oral fluid testing for DUID will have the reliability needed to be used forensically.

Data on the detection times of drugs of abuse are based on studies of controlled administration to volunteers or on the analysis of biologic samples of subjects who are forced to stop their (often chronic) use of drugs of abuse, eg, because of imprisonment or detoxification. The detection times depend mainly on the dose and sensitivity of the method used and also on the preparation and route of administration, the duration of use (acute or chronic), the matrix that is analyzed, the molecule or metabolite that is looked for, the pH and concentration of the matrix (urine, oral fluid), and the interindividual variation in metabolic and renal clearance. In general, the detection time is longest in hair, followed by urine, sweat, oral fluid, and blood. In blood or plasma, most drugs of abuse can be detected at the low nanogram per milliliter level for 1 or 2 days. In urine the detection time of a single dose is 1.5 to 4 days. In chronic users, drugs of abuse can be detected in urine for approximately 1 week after last use, and in extreme cases even longer in cocaine and cannabis users. In oral fluid, drugs of abuse can be detected for 5-48 hours at a low nanogram per milliliter level. The duration of detection of GHB is much shorter. After a single dose of 1 or 2 ng of flunitrazepam, the most sensitive methods can detect 7-aminoflunitrazepam for up to 4 weeks in urine.

Blood, urine, oral fluid (by spitting or with a Salivette), and sweat samples (by wiping the forehead with a fleece moistened with isopropanol) were obtained from 180 drivers who failed the field sobriety tests at police roadblocks. With quantitative GC-MS, the positive predictive value of oral fluid was 98, 92, and 90% for amphetamines, cocaine, and cannabis respectively. The prevalence of opiate positives was low. The proposed SAMHSA cut-off values for oral fluid testing at the workplace, proved their usefulness in this study. The positive predictive value of sweat wipe analysis with GC-MS was over 90% for cocaine and amphetamines and 80% for cannabis. The accuracy of Drugwipe was assessed by comparing the electronic read-out values obtained on-site after wiping the tongue and the forehead, with the corresponding GC-MS results in plasma, oral fluid, and sweat. The accuracy was always less than 90% except for the amphetamine-group in sweat.

Recently, certain studies have indicated that 2-oxo-3-hydroxy-LSD is present in urine at much higher concentrations than LSD. We determined LSD and 2-oxo-3-hydroxy-LSD in urine by GC-MS (Hewlett Packard 5970) after solid phase extraction on SPEC.PLUS MP1 disks (3 mL, 30 mg, Ansys, Irvine, CA, USA), using the method recommended for amphetamines and derivatisation with BSTFA. For 2-oxo-3-hydroxy-LSD-bis-TMS, the ions with m/z of 309 and 499 were used as quantification and confirmation ion respectively. In four samples containing between 561 and 7007 pg/mL of LSD, 2-oxo-3-hydroxy-LSD concentrations between 8021 and 28466 pg/mL were found, i.e. 4 to 41 times higher than the LSD concentrations. 2-oxo-3-hydroxy-LSD does not seem to be conjugated. These results indicate that 2-oxo-3-hydroxy-LSD, is present in urine in much higher concentrations than LSD, which could facilitate confirmation of positive screenings and increase detection times.

The precision and the diagnostic performance of the Boehringer Mannheim CEDIA DAU LSD assay was evaluated. The assay was performed in the semi-quantitative mode on a Hitachi 917 analyzer. Within-run coefficients of variation (CVs) of the semiquantitative values for 0.25 and 1.0 ng/mL were 11.2 and 6.2%, respectively. Day-to-day CVs for the same concentrations were 12.6 and 8.6%. We analyzed 318 urine samples by CEDIA, DPC Coat-A-Count RIA and Behring EMIT II. Confirmation was performed by GC-MS, after extraction on Bond Elut Certify columns. Two hundred sixty-three samples were negative by all methods. Twenty-five samples were positive by all immunoassays, 19 of which were confirmed by gas chromatography-mass spectrometry (GC-MS). One sample was falsely negative by CEDIA. Three samples were positive by EMIT and CEDIA, but negative by RIA and GC-MS. Twenty-six samples were positive by EMIT alone, but they were not confirmed by GC-MS. The LSD CEDIA assay seems to be less specific than DPC RIA but more specific than the EMIT LSD assay.