Profiles of drug users in Switzerland and effects of early-onset intensive use of alcohol, tobacco and cannabis on other illicit drug use.

QUESTIONS UNDER STUDY / PRINCIPLES: The main aim of this study was to investigate profiles of drug users, with a particular focus on illicit drugs other than cannabis, and to explore the effect of early-onset intensive use (drunkenness, daily smoking, high on cannabis) on profiles of illicit drug use. METHODS: Baseline data from a representative sample of 5,831 young Swiss men in the ongoing Cohort Study on Substance Use Risk Factors were used. Substance use (alcohol, tobacco, cannabis and 15 types of other illicit drug) and age of onset of intensive use were assessed. The Item Response Theory (IRT) and prevalence rates at different ages of onset were used to reveal different profiles of illicit drug use. RESULTS: In addition to cannabis, there were two profiles of other illicit drug use: (a) "softer" drug users (uppers, hallucinogens and inhaled drugs), among which ecstasy had the highest discriminatory potential (IRT slope = 4.68, standard error (SE) = 0.48; p <0.001); and (b) "harder" drug users (heroin, ketamine, gamma-hydroxybutyrate/gamma-hydroxylactone, research chemicals, crystal meth and spice), among which ketamine had the highest discriminatory potential (slope = 4.05; SE = 0.63; p <0.001). Onset of intensive use at the age of 12 years or younger also discriminated between these two profiles. CONCLUSION: Both the IRT model and the effect of onset of intensive use enabled two groups of illicit drugs to be identified. In particular, very early onset (at 12 years or younger) intensive use of any substance was a marker for later use of the second group of drugs.

Monitoring de la problématique du cannabis en Suisse : étude sentinelle : panels 2008

A l'heure actuelle, le monitoring de la problématique du cannabis en Suisse constitue un ensemble de travaux qui permettent le suivi de la situation au niveau national et qui sont mis en oeuvre par un consortium d'instituts. Ce monitoring comprend l'étude présentée dans ce rapport, l'étude sentinelle. Elle s'intéresse à l'évolution de la situation en matière de cannabis ainsi qu'à la gestion de cette situation au niveau local. Ainsi, les observations relevées par des professionnels de terrain dans différents domaines (santé/social, école/formation professionnelle, police/justice) et dans quatre cantons suisses (St Gall, Tessin, Vaud, Zurich), dits "sentinelle", sont récoltées et analysées annuellement. [P. 5]

Challenging the "inoffensiveness" of regular cannabis use by its associations with other current risky substance use--a census of 20-year-old Swiss men.

3,537 men enrolling in 2007 for mandatory army recruitment procedures were assessed for the co-occurrence of risky licit substance use among risky cannabis users. Risky cannabis use was defined as at least twice weekly; risky alcohol use as 6+ drinks more than once/monthly, or more than 20 drinks per week; and risky tobacco use as daily smoking. Ninety-five percent of all risky cannabis users reported other risky use. They began using cannabis earlier than did non-risky users, but age of onset was unrelated to other risky substance use. A pressing public health issue among cannabis users stems from risky licit substance use warranting preventive efforts within this age group.

Smoked cannabis and doping control: looking for the wrong target analyte?

Introduction: Since 2004, cannabis is prohibited by the World Anti-Doping Agency (WADA) for all sports in competition. In the years since then, about half of all positive doping cases in Switzerland have been related to cannabis consumption. In most cases, the athletes plausibly claim to have consumed cannabis several days or even weeks before competition and only for recreational purposes not related to competition. In doping analysis, the target analyte in urine samples is 11-nor-delta-9-tetrahydrocannabinol- 9-carboxylic acid (THC-COOH), the reporting threshold for laboratories is 15 ng/mL. However, the wide detection window of this long-term THC metabolite in urine does not allow a conclusion concerning the time of consumption or the impact on the physical performance. Aim: The purpose of the present pharmacokinetic study on volunteers was to evaluate target analytes with shorter urinary excretion time. Subsequently, urines from athletes tested positive for cannabis should be reanalyzed including these analytes. Methods: In an one-session clinical trial (approved by IRB, Swissmedic, and Federal Office of Public Health), 12 healthy, male volunteers (age 26 ± 3 yrs, BMI 24 ± 2 kg/m2) with cannabis experience (> once/month) smoked a Cannabis cigarette standardized to 70 mg THC/cigarette (Bedrobinol® 7%, Dutch Office for Medicinal Cannabis) following a paced-puffing procedure. Plasma and urine was collected up to 8 h and 11 days, respectively. Total THC, 11-hydroxy-THC (THC-OH), and THC-COOH were determined after enzymatic hydrolyzation followed by SPE and GC/MS-SIM. The limit of quantitation (LOQ) for all analytes was 0.1 ng/mL. Visual analog scales (VAS) and vital functions were used for monitoring psychological and somatic side-effects at every timepoint of specimen collection (up to 480 min). Results: Eight puffs delivered a mean THC dose of 45 mg. Mean plasma levels of total THC, THC-OH and THC-COOH were measured in the range of 0.1-20.9, 0.1-1.8, and 1.8-7.5 ng/mL, respectively. Peak concentrations were observed at 5, 10, and 90 min. Mean urine levels were measured in the range of 0.1-0.7, 0.10-6.2, and 0.1-13.4 ng/mL, respectively. The detection windows were 2-8, 2-96, and 2-120 h. No or only mild effects were observed, such as dry mouth, sedation, and tachycardia. Besides high to very high THC-COOH levels (0-978 ng/mL), THC (0.1-24 ng/mL) and THC-OH (1-234 ng/mL) were found in 90 and 96% of the cannabis-positive urines from athletes. Conclusion: Instead of or in addition to THC-COOH, the pharmacologically active THC and THC-OH should be the target analytes for doping urine analysis. This would allow the estimation of more recent Cannabis consumption, probably influencing performance during competition. Keywords: cannabis, doping, clinical trial, plasma and urine levels, athlete's samples

Cannabis use as a means of socialization?: new consumption patterns among heavy users

Purpose: After tobacco and alcohol, cannabis is the most used substance among adolescents in Switzerland. Our aim is to assess whether cannabis use has become an ordinary means of socialization. We hypothesize that cannabis consumption has become a normative, although still illegal, behavior. Methods: As part of a larger qualitative study aimed at assessing new ways [patterns] of cannabis consumption, 16 daily cannabis consumers (11 males) and 2 former heavy consumers (both females), aged 15 to 20 years, participated in interviews and focus groups. Data were transcribed verbatim and analyzed using Atlas.ti qualitative analysis software. Results: Most consumers define the beginning of their consumption as a moment when they made new friends. They commonly use cannabis in group settings, which encourages the belief that all adolescents use cannabis. Thus, cannabis is mainly identified as an everyday social act. Joints are smoked like cigarettes: at all times of the day, during or after school or work with peers, often starting at lunch break, and mostly in public places. Friends offer a joint in a group setting, much like beer in a bar, as a means of making contact. Consumption invariably increases while socializing on vacation: "During vacation, we smoke up to 10-15 joints a day; at the end we're just dead." Additionally, in order to obtain cannabis, consumers have to be part of the right networks; they generally have several dealers to assure their supply, buy and sell themselves, or practice group-buying. As a result, all friends or acquaintances of consumers are themselves cannabis users. For instance, 4 boys, who say they are best friends, always smoke together and that, in order to quit, "All four of us should say to ourselves, 'Okay, now, let's all stop smoking'. That would be the only solution. . .but it would be impossible!" The 2 former consumers state that when they started using cannabis, "I found myself little by little in a vicious circle where I saw only people who also smoked". When they quit, they separated from their group of friends: "Either you make new friends who don't smoke or you smoke." Conclusions: Discussions with consumers demonstrate a normative facet of cannabis consumption as part of teenage socialization. Consequently, cannabis consumers develop a significant dependency since a majority of their friends use cannabis and their consumption involves most of their daily social life. Our study highlights the need for clear messages about the harmful aspects of using this substance while also suggesting that cessation efforts should include helping users separate from their consumption milieu. Sources of Support: Dept. of Public Health of the canton of Vaud.

Cannabis use trajectories among Swiss adolescents

Introduction: Swiss data indicate that one fifth of current 16-20 yearold cannabis users do not use tobacco and seem to do better than those smoking both substances. The aim of this research is to assess the substance use trajectories of cannabis users who do not use tobacco and those who use both substances from age 17 to age 23. Methods: Using data from the TREE longitudinal data base, 328 out of 1796 youth 18.3%; 45% females) who smoked cannabis only (Group CAN; N = 46; 36% females) or concurrently with tobacco (Group CANTAB; N = 284; 46% females) at T1 (2001; age 17) were followed at T4 (2004; age 20) and T7 (2007; age 23). Two additional outcome groups were included at T4 and T7: those using only tobacco (Group TOB) and those not using any of these substances (Group NONE). Data were analyzed separately by gender. Results: Females in group CAN at T1 were as likely to be in group TOB (35%) or NONE (35%) at T4 and the percentages increased to 41% and 47%, respectively, at T7. Males in group CAN at T1 were more likely to be in group TOB at T4 (33%) and T7 (61%) than in group NONE (23% and 15%, respectively). Females in group CANTOB at T1 were mainly in group TOB at T4 (52%) and T7 (61%), while males in CANTOB at T1 remained mainly in the same group at T4 (75%) and T7 (61%). Only 10% of females and 5% of males in group CANTOB at T1 were in group NONE at T4 and 15% and 12%, respectively, at T7. Conclusions: Adolescents using only cannabis are globally less likely to continue using cannabis in young adulthood than those using both substances, although a fair percentage (specially males) switch to tobacco use. This result confirms previous research indicating that nicotine dependence and persistent cigarette smoking may be the main public health consequences of cannabis use. A gender difference arises among those using tobacco and cannabis at age 17: while females become mainly tobacco smokers, the majority of males continue to use both substances. Although these results could be explained by a substitution effect, teenagers using both substances seem to have gone beyond the experimentation phase and should be a motive for concern.

Perception of tobacco, cannabis, and alcohol use of others is associated with one's own use.

BACKGROUND: Interventions have been developed to reduce overestimations of substance use among others, especially for alcohol and among students. Nevertheless, there is a lack of knowledge on misperceptions of use for substances other than alcohol. We studied the prevalence of misperceptions of use for tobacco, cannabis, and alcohol and whether the perception of tobacco, cannabis, and alcohol use by others is associated with one's own use. METHODS: Participants (n=5216) in a cohort study from a census of 20-year-old men (N=11,819) estimated the prevalence of tobacco and cannabis use among peers of the same age and sex and the percentage of their peers drinking more alcohol than they did. Using the census data, we determined whether participants overestimated, accurately estimated, or underestimated substance use by others. Regression models were used to compare substance use by those who overestimated or underestimated peer substance with those who accurately estimated peer use. Other variables included in the analyses were the presence of close friends with alcohol or other drug problems and family history of substance use. RESULTS: Tobacco use by others was overestimated by 46.1% and accurately estimated by 37.3% of participants. Cannabis use by others was overestimated by 21.8% and accurately estimated by 31.6% of participants. Alcohol use by others was overestimated by more than half (53.4%) of participants and accurately estimated by 31.0%. In multivariable models, compared with participants who accurately estimated tobacco use by others, those who overestimated it reported smoking more cigarettes per week (incidence rate ratio [IRR] [95% CI], 1.17 [range, 1.05, 1.32]). There was no difference in the number of cigarettes smoked per week between those underestimating and those accurately estimating tobacco use by others (IRR [95% CI], 0.99 [range, 0.84, 1.17]). Compared with participants accurately estimating cannabis use by others, those who overestimated it reported more days of cannabis use per month (IRR [95% CI], 1.43 [range, 1.21, 1.70]), whereas those who underestimated it reported fewer days of cannabis use per month (IRR [95% CI], 0.62 [range, 0.23, 0.75]). Compared with participants accurately estimating alcohol use by others, those who overestimated it reported consuming more drinks per week (IRR [95% CI], 1.57 [range, 1.43, 1.72]), whereas those who underestimated it reported consuming fewer drinks per week (IRR [95% CI], 0.41 [range, 0.34, 0.50]). CONCLUSIONS: Perceptions of substance use by others are associated with one's own use. In particular, overestimating use by others is frequent among young men and is associated with one's own greater consumption. This association is independent of the substance use environment, indicating that, even in the case of proximity to a heavy-usage group, perception of use by others may influence one's own use. If preventive interventions are to be based on normative feedback, and their aim is to reduce overestimations of use by others, then the prevalence of overestimation indicates that they may be of benefit to roughly half the population; or, in the case of cannabis, to as few as 20%. Such interventions should take into account differing strengths of association across substances.

Importance de l'exposition au tabac chez les jeunes consommateurs de cannabis: un cheval de Troie ?

Malgré une récente réduction, le tabagisme reste élevé et préoccupant parmi les jeunes. Les consommations de tabac et de cannabis sont, sur plusieurs aspects, fortement liées. Les preuves scientifiques tendent à démontrer que la dépendance à la nicotine et la consommation persistante de cigarettes seraient les deux principales conséquences néfastes de l'usage de cannabis pendant l'adolescence. Le phénomène du "mulling" (le fait de mélanger du tabac au cannabis pour sa consommation) représente l'une des hypothèses les plus plausibles du risque augmenté qu'ont les jeunes consommateurs de cannabis de devenir des futurs fumeurs de cigarettes. L'objectif principal de cette étude est de déterminer si les niveaux de nicotine retrouvés chez des fumeurs de cannabis sont suffisamment élevés pour prouver une exposition tabagique significative pouvant être expliquée par le phénomène du "mulling" plutôt que par l'environnement.

Is cannabis use a significant exposition to nicotine?

Purpose: Young cannabis users are at increased risk for cigarette initiation and later progression to nicotine dependence. The present study assesses to which extent cannabis users are exposed to nicotine through mulling, a widespread process consisting of mixing tobacco to cannabis for its consumption. Methods: Data are issued from an ongoing observational study taking place in Switzerland. A total of 267 eligible participants (mean age 19 years, 46.4% males) completed an anonymous self-administered questionnaire on their tobacco and cannabis intake in the previous 5 days. They also provided a urine sample that was blindly analyzed for cotinine (a key metabolite of nicotine) using liquid-chromatography coupled mass-spectrometry. After the exclusion of cannabis users not having smoked at least one joint/blunt in which tobacco had been mixed (n _ 2), and participants reporting other sources of nicotine exposition than cigarettes or mulling (n _37), four groups were created: cannabis and cigarette abstainers (ABS, n_ 69), cannabis only smokers (CAS; n _ 33), cigarette only smokers (CIS; n _ 62); and cannabis and cigarette smokers (CCS, n _ 64). Cotinine measures of CAS were compared to those of ABS, CIS and CCS. All comparisons were performed using ANCOVA, controlling for age, gender, ethnicity, BMI and environmental exposure to cigarette smoke in the past month (at home, in school/at work, in social settings). The number of mixed joints/blunts smoked in the previous 5 days was additionally taken into account when comparing CAS to CCS. Cotinine values (ng/ml) are reported as means with 95% confidence interval (95% CI). Results: In the previous 5 days, CAS had smoked on average 10 mixed joints/blunts, CIS 30 cigarettes, and CCS 8 mixed joints/ blunts and 41 cigarettes. Cotinine levels of participants considerably differed between groups. The lowest measure was found among ABS (3.2 [0.5-5.9]), followed in growing order by CAS (294.6 [157.1-432.0]), CIS (362.8 [258.4-467.3]), and CCS (649.9 [500.7-799.2]). In the multivariate analysis, cotinine levels of CAS were significantly higher than those of ABS (p _.001), lower than those of CCS (p _ .003), but did not differ from levels of CIS (p _ .384). Conclusions: Our study reveals cannabis users to be significantly exposed to nicotine through mulling, even after controlling for several possible confounders such as environmental exposure to cigarette smoke. Utmost, mixing tobacco to Poster cannabis can result in a substantial nicotine exposition as cotinine levels from cannabis only smokers were as high as those of moderate cigarette smokers. Our findings also suggest that mulling is adding up to the already important nicotine exposition of cigarettes smokers. Because of the addictiveness of nicotine, mulling should be part of a comprehensive assessment of substance use among adolescents and young adults, especially when supporting their cannabis and cigarette quitting attempts. Sources of Support: This study was funded by the Public Health Service of the Canton de Vaud. Dr. BÊlanger's contribution was possible through grants from the Royal College of Physicians and Surgeons of Canada, the CHUQ/CMDP Foundation and the Laval University McLaughlin program, QuÊbec, Canada.

Cannabis and tobacco use: where are the boundaries? A qualitative study on cannabis consumption modes among adolescents.

The purpose of this article is to identify tobacco and cannabis co-consumptions and consumers' perceptions of each substance. A qualitative research including 22 youths (14 males) aged 15-21 years in seven individual interviews and five focus groups. Discussions were recorded, transcribed verbatim and transferred to Atlas.ti software for narrative analysis. The main consumption mode is cannabis cigarettes which always mix cannabis and tobacco. Participants perceive cannabis much more positively than tobacco, which is considered unnatural, harmful and addictive. Future consumption forecasts thus more often exclude tobacco smoking than cannabis consumption. A substitution phenomenon often takes place between both substances. Given the co-consumption of tobacco and cannabis, in helping youths quit or decrease their consumptions, both substances should be taken into account in a global approach. Cannabis consumers should be made aware of their tobacco use while consuming cannabis and the risk of inducing nicotine addiction through cannabis use, despite the perceived disconnect between the two substances. Prevention programs should correct made-up ideas about cannabis consumption and convey a clear message about its harmful consequences. Our findings support the growing evidence which suggests that nicotine dependence and cigarette smoking may be induced by cannabis consumption.

Mult-class differentiation of cannabis seedlings in a forensic context

This article presents an experimental study about the classification ability of several classifiers for multi-classclassification of cannabis seedlings. As the cultivation of drug type cannabis is forbidden in Switzerland lawenforcement authorities regularly ask forensic laboratories to determinate the chemotype of a seized cannabisplant and then to conclude if the plantation is legal or not. This classification is mainly performed when theplant is mature as required by the EU official protocol and then the classification of cannabis seedlings is a timeconsuming and costly procedure. A previous study made by the authors has investigated this problematic [1]and showed that it is possible to differentiate between drug type (illegal) and fibre type (legal) cannabis at anearly stage of growth using gas chromatography interfaced with mass spectrometry (GC-MS) based on therelative proportions of eight major leaf compounds. The aims of the present work are on one hand to continueformer work and to optimize the methodology for the discrimination of drug- and fibre type cannabisdeveloped in the previous study and on the other hand to investigate the possibility to predict illegal cannabisvarieties. Seven classifiers for differentiating between cannabis seedlings are evaluated in this paper, namelyLinear Discriminant Analysis (LDA), Partial Least Squares Discriminant Analysis (PLS-DA), Nearest NeighbourClassification (NNC), Learning Vector Quantization (LVQ), Radial Basis Function Support Vector Machines(RBF SVMs), Random Forest (RF) and Artificial Neural Networks (ANN). The performance of each method wasassessed using the same analytical dataset that consists of 861 samples split into drug- and fibre type cannabiswith drug type cannabis being made up of 12 varieties (i.e. 12 classes). The results show that linear classifiersare not able to manage the distribution of classes in which some overlap areas exist for both classificationproblems. Unlike linear classifiers, NNC and RBF SVMs best differentiate cannabis samples both for 2-class and12-class classifications with average classification results up to 99% and 98%, respectively. Furthermore, RBFSVMs correctly classified into drug type cannabis the independent validation set, which consists of cannabisplants coming from police seizures. In forensic case work this study shows that the discrimination betweencannabis samples at an early stage of growth is possible with fairly high classification performance fordiscriminating between cannabis chemotypes or between drug type cannabis varieties.

Nicotine vaccines for smoking cessation.

BACKGROUND: By reducing the amount of nicotine that reaches the brain when a person smokes a cigarette, nicotine vaccines may help people to stop smoking or to prevent recent quitters from relapsing. OBJECTIVES: The aims of this review are to assess the efficacy of nicotine vaccines for smoking cessation and for relapse prevention, and to assess the frequency and type of adverse events associated with the use of nicotine vaccines. SEARCH METHODS: We searched the Cochrane Tobacco Addiction Review Group specialised register for trials, using the term 'vaccine' in the title or abstract, or in a keyword (date of most recent search April 2012). To identify any other material including reviews and papers potentially relevant to the background or discussion sections, we also searched MEDLINE, EMBASE, and PsycINFO, combining terms for nicotine vaccines with terms for smoking and tobacco use, without design limits or limits for human subjects. We searched the Annual Meeting abstracts of the Society for Research on Nicotine and Tobacco up to 2012, using the search string 'vaccin'. We searched Google Scholar for 'nicotine vaccine'. We also searched company websites and Google for information related to specific vaccines. We searched clinicaltrials.gov in March 2012 for 'nicotine vaccine' and for the trade names of known vaccine candidates. SELECTION CRITERIA: We included randomized controlled trials of nicotine vaccines, at Phase II and Phase III trial stage and beyond, in adult smokers or recent ex-smokers. We included studies of nicotine vaccines used as part of smoking cessation or relapse prevention interventions. DATA COLLECTION AND ANALYSIS: We extracted data on the type of participants, the dose and duration of treatment, the outcome measures, the randomization procedure, concealment of allocation, blinding of participants and personnel, reporting of outcomes, and completeness of follow-up.Our primary outcome measure was a minimum of six months abstinence from smoking. We used the most rigorous definition of abstinence, and preferred cessation rates at 12 months and biochemically validated rates where available. We have used the risk ratio (RR) to summarize individual trial outcomes. We have not pooled the current group of included studies as they cover different vaccines and variable regimens. MAIN RESULTS: There are no nicotine vaccines currently licensed for public use, but there are a number in development. We found four trials which met our inclusion criteria, three comparing NicVAX to placebo and one comparing NIC002 (formerly NicQbeta) to placebo. All were smoking cessation trials conducted by pharmaceutical companies as part of the drug development process, and all trials were judged to be at high or unclear risk of bias in at least one domain. Overall, 2642 smokers participated in the included studies in this review. None of the four included studies detected a statistically significant difference in long-term cessation between participants receiving vaccine and those receiving placebo. The RR for 12 month cessation in active and placebo groups was 1.35 (95% Confidence Interval (CI) 0.82 to 2.22) in the trial of NIC002 and 1.74 (95% CI 0.73 to 4.18) in one NicVAX trial. Two Phase III NicVAX trials, for which full results were not available, reported similar quit rates of approximately 11% in both groups. In the two studies with full results available, post hoc analyses detected higher cessation rates in participants with higher levels of nicotine antibodies, but these findings are not readily generalisable. The two studies with full results showed nicotine vaccines to be well tolerated, with the majority of adverse events classified as mild or moderate. In the study of NIC002, participants receiving the vaccine were more likely to report mild to moderate adverse events, most commonly flu-like symptoms, whereas in the study of NicVAX there was no significant difference between the two arms. Information on adverse events was not available for the large Phase III trials of NicVAX.Vaccine candidates are likely to undergo significant changes before becoming available to the general public, and those included in this review may not be the first to reach market; this limits the external validity of the results reported in this review in terms of both effectiveness and tolerability. AUTHORS' CONCLUSIONS: There is currently no evidence that nicotine vaccines enhance long-term smoking cessation. Rates of serious adverse events recorded in the two trials with full data available were low, and the majority of adverse events reported were at mild to moderate levels. The evidence available suggests nicotine vaccines do not induce compensatory smoking or affect withdrawal symptoms. No nicotine vaccines are currently licensed for use in any country but a number are under development.Further trials of nicotine vaccines are needed, comparing vaccines with placebo for smoking cessation. Further trials are also needed to explore the potential of nicotine vaccines to prevent relapse. Results from past, current and future research should be reported in full. Adverse events and serious adverse events should continue to be carefully monitored and thoroughly reported.

Assessment of driving capability through the use of clinical and psychomotor tests in relation to blood cannabinoids levels following oral administration of 20 mg dronabinol or of a cannabis decoction made with 20 or 60 mg Delta9-THC.

Delta(9)-Tetrahydrocannabinol (THC) is frequently found in the blood of drivers suspected of driving under the influence of cannabis or involved in traffic crashes. The present study used a double-blind crossover design to compare the effects of medium (16.5 mg THC) and high doses (45.7 mg THC) of hemp milk decoctions or of a medium dose of dronabinol (20 mg synthetic THC, Marinol on several skills required for safe driving. Forensic interpretation of cannabinoids blood concentrations were attempted using the models proposed by Daldrup (cannabis influencing factor or CIF) and Huestis and coworkers. First, the time concentration-profiles of THC, 11-hydroxy-Delta(9)-tetrahydrocannabinol (11-OH-THC) (active metabolite of THC), and 11-nor-9-carboxy-Delta(9)-tetrahydrocannabinol (THCCOOH) in whole blood were determined by gas chromatography-mass spectrometry-negative ion chemical ionization. Compared to smoking studies, relatively low concentrations were measured in blood. The highest mean THC concentration (8.4 ng/mL) was achieved 1 h after ingestion of the strongest decoction. Mean maximum 11-OH-THC level (12.3 ng/mL) slightly exceeded that of THC. THCCOOH reached its highest mean concentration (66.2 ng/mL) 2.5-5.5 h after intake. Individual blood levels showed considerable intersubject variability. The willingness to drive was influenced by the importance of the requested task. Under significant cannabinoids influence, the participants refused to drive when they were asked whether they would agree to accomplish several unimportant tasks, (e.g., driving a friend to a party). Most of the participants reported a significant feeling of intoxication and did not appreciate the effects, notably those felt after drinking the strongest decoction. Road sign and tracking testing revealed obvious and statistically significant differences between placebo and treatments. A marked impairment was detected after ingestion of the strongest decoction. A CIF value, which relies on the molar ratio of main active to inactive cannabinoids, greater than 10 was found to correlate with a strong feeling of intoxication. It also matched with a significant decrease in the willingness to drive, and it matched also with a significant impairment in tracking performances. The mathematic model II proposed by Huestis et al. (1992) provided at best a rough estimate of the time of oral administration with 27% of actual values being out of range of the 95% confidence interval. The sum of THC and 11-OH-THC blood concentrations provided a better estimate of impairment than THC alone. This controlled clinical study points out the negative influence on fitness to drive after medium or high dose oral THC or dronabinol.

Cannabis Use in Patients with Fibromyalgia: Effect on Symptoms Relief and Health-Related Quality of Life

Background: The aim of this study was to describe the patterns of cannabis use and the associated benefits reported by patients with fibromyalgia (FM) who were consumers of this drug. In addition, the quality of life of FM patients who consumed cannabis was compared with FM subjects who were not cannabis users. Methods: Information on medicinal cannabis use was recorded on a specific questionnaire as well as perceived benefits of cannabis on a range of symptoms using standard 100-mm visual analogue scales (VAS). Cannabis users and non-users completed the Fibromyalgia Impact Questionnaire (FIQ), the Pittsburgh Sleep Quality Index (PSQI) and the Short Form 36 Health Survey (SF-36). Results: Twenty-eight FM patients who were cannabis users and 28 non-users were included in the study. Demographics and clinical variables were similar in both groups. Cannabis users referred different duration of drug consumption; the route of administration was smoking (54%), oral (46%) and combined (43%). The amount and frequency of cannabis use were also different among patients. After 2 hours of cannabis use, VAS scores showed a statistically significant (p<0.001) reduction of pain and stiffness, enhancement of relaxation, and an increase in somnolence and feeling of well being. The mental health component summary score of the SF-36 was significantly higher (p<0.05) in cannabis users than in non-users. No significant differences were found in the other SF-36 domains, in the FIQ and the PSQI. Conclusions: The use of cannabis was associated with beneficial effects on some FM symptoms. Further studies on the usefulness of cannabinoids in FM patients as well as cannabinoid system involvement in the pathophysiology of this condition are warranted