Abstinence phenomena of chronic cannabis-addicts prospectively monitored during controlled inpatient detoxification: Cannabis withdrawal syndrome and its correlation with delta-9-tetrahydrocannabinol and -metabolites in serum

Drug and Alcohol Dependence 143 (2014) 189–197

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Abstinence phenomena of chronic cannabis-addicts prospectively monitored during controlled inpatient detoxification: Cannabis withdrawal syndrome and its correlation with delta-9-tetrahydrocannabinol and -metabolites in serum U. Bonnet a,∗ , M. Specka b , U. Stratmann a , R. Ochwadt c , N. Scherbaum b a Department of Psychiatry, Psychotherapy and Psychosomatics, Evangelisches Krankenhaus Castrop-Rauxel, Academic Teaching Hospital of the University of Duisburg/Essen, Castrop-Rauxel, Germany b Department of Addictive Behavior and Addiction Medicine, LVR-Klinikum Essen, University of Duisburg/Essen, Essen, Germany c MVZ synlab Leverkusen GmbH, Leverkusen, Germany

a r t i c l e

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Article history: Received 9 January 2014 Received in revised form 19 July 2014 Accepted 21 July 2014 Available online 1 August 2014 Keywords: Chronic cannabis addicts Cannabis-withdrawal syndrome Serum -9-tetrahydrocannabinol Serum THC-OH Serum THC-COOH

a b s t r a c t Objective: To investigate the course of cannabis withdrawal syndrome (CWS) within a controlled inpatient detoxification setting and to correlate severity of CWS with the serum-levels of delta9-tetrahydrocannabinol (THC) and its main metabolites 11-hydroxy-delta-9-tetrahydrocannabinol (THC-OH) and 11-nor-delta-9-tetrahydrocannabinol-9-carboxylic acid (THC-COOH). Methods: Thirty-nine treatment-seeking chronic cannabis dependents (ICD-10) were studied on admission and on abstinent days 2, 4, 8 and 16, using a CWS-checklist (MWC) and the Clinical Global Impression-Severity scale (CGI-S). Simultaneously obtained serum was analysed to its concentration of THC, THC-OH and THC-COOH. Results: MWC peaked on day 4 (10.4 ± 4.6 from 39 points) and declined to 2.9 ± 2.4 points on day 16. Women had a significantly stronger CWS than men. The CWS was dominated by craving > restlessness > nervousness > sleeplessness. CGI-S peaked with 5 out of 7 points. On admission, THC and its metabolites did negatively correlate with the severity of CWS. There was no significant correlation afterwards, no matter if CWS was medicated or not. THC-OH in serum declined most rapidly below detection limit, on median at day 4. At abstinence day 16, the THC-levels of 28.2% of the patients were still above 1 g/ml (range: 1.3 to 6.4 ng/ml). Conclusions: CWS increased and then decreased without any correlation between its severity and the serum-levels of THC or its main metabolites after admission. According to the CGI-S, most patients achieved the condition of ‘markedly ill’. Serum THC-OH was most clearly associated with recent cannabis use. Residual THC was found in the serum of almost one-third of the patients at abstinence day 16. © 2014 Elsevier Ireland Ltd. All rights reserved.

1. Introduction Cannabis is a psychotropic substance with widespread use worldwide, surpassed only by nicotine and alcohol (UNDOC, 2013). In Germany, for example, the12-month prevalence for cannabis use amounts to 4.5% for adults in general, with highest rates in the age groups of 18–20 years (16.2%) and 21–24 years (13.7%; Pabst et al., 2013). 12-month prevalence for cannabis dependence

∗ Corresponding author. Tel.: +4923051022858. E-mail address: [email protected] (U. Bonnet). http://dx.doi.org/10.1016/j.drugalcdep.2014.07.027 0376-8716/© 2014 Elsevier Ireland Ltd. All rights reserved.

(DSM-IV) was recently estimated as 0.5% in all German adults (Pabst et al., 2013). Retrospective studies on larger clinical (Wiesbeck et al., 1996; Levin et al., 2010) and epidemiological (Agrawal et al., 2008; Hasin et al., 2008) populations have shown that discontinuation of regular cannabis use is frequently followed by one or more symptoms like anxiety, irritability, craving for cannabis, or sleeping problems, which are associated with distress and impairment of daily activities and with relapse to cannabis use (Budney et al., 2004; Allsop et al., 2011). Starting from various definitions the existence of a clinical cannabis withdrawal syndrome (CWS) was validated in prospective studies with outpatients or untreated subjects supervised after cessation of cannabis use (Budney et al., 1999; Kouri

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and Pope, 2000; Budney et al., 2004; Arendt et al., 2007; Allsop et al., 2011) and by inpatient laboratory studies (Haney et al., 2008, 2010). On this basis diagnostic criteria for CWS have been recently operationalized and newly included in DSM-5 (American Psychiatric Association, 2013). In ICD-10, the CWS is still vaguely defined (Dilling et al., 2004). The CWS emerges most pronounced after stopping a lengthy and heavy cannabis intake and in treated samples its intensity is associated with a patient’s motivation for detoxification and with characteristics of the treatment setting (Budney et al., 2004). In most cases, the syndrome reaches its peak between the 2nd and 6nd day after cessation of cannabis inhalation and usually lasts for about 14 days (Kielholz and Ladewig, 1970; Wiesbeck et al., 1996; Budney et al., 2004). Some symptoms such as ‘sleeplessness’, ‘irritability’, or ‘strange dreams’, however, may last for longer (Budney et al., 2004; Vandrey et al., 2011; Lee et al., 2014). It is interesting to note in this context that down-regulated cannabinoid CB1 receptors return to normal functioning after about 4 weeks of abstinence (Hirvonen et al., 2012), which would constitute a physiological time frame for the occurrence of abstinence symptoms. Studies on the CWS carried out within clinical inpatient settings provide further evidence for the validity of this syndrome, but are still rare (Preuss et al., 2010; Lee et al., 2014). In a controlled inpatient environment, the CWS is expected to be less influenced by relapse-associated cues than in an everyday environment (Budney et al., 2004). Moreover, inpatient conditions provide improved relapse prevention and easier detection of relapses (Dasgupta, 2007). In the inpatient study of Preuss et al. (2010) with treatmentseeking white adolescents and young adults (n = 73) who were observed for 10 days, the intensity of most self-reported symptoms peaked on the first day in treatment and then decreased nearly linearly. Intensity of most symptoms ranged between low and moderate (Preuss et al., 2010). The symptom rated as ‘strong’ or ‘very strong’ most frequently (37.9%) was craving (Preuss et al., 2010). Since the CWS in animal experiments and human studies can be alleviated by the administration of -9-tetrahydrocannabinol (THC; Budney et al., 2007; Haney et al., 2008; Vandrey et al., 2013), which is mainly responsible for the euphoric and reinforcing effects of cannabis (Cone and Huestis, 1993; Mechoulam, 1999), it is likely that a decrease in THC levels in the extracellular brain fluid is crucially involved in the formation of the syndrome. In 2006, to the time when our study started, there was only one small study available, which had investigated the course of plasma cannabinoids after initiation of abstinence in chronic cannabis users (8 men were followed for 10–15 days; Johansson et al., 1989). Because that study revealed high inter-individual variability in the elimination halflives of THC (Johansson et al., 1989), the question arises whether THC-levels in the peripheral blood-compartment are associated with severity of cannabis withdrawal symptoms. The first study that addressed this question was published most recently; in nontreatment seeking, African–American chronic cannabis dependent patients, an overarching correlation between CWS and serum THC had not been found (Lee et al., 2014). In addition to THC, which is highly lipophilic with a long terminal elimination half-life of up to 12.6 days in blood from chronic cannabis users (Johansson et al., 1989), two major metabolites are of interest in the present context: the hydrophilic and also psychoactive metabolite 11-hydroxy-9-tetrahydrocannabinol (THC-OH) and the lipophilic, but no longer psychoactive metabolite 11-nor--9-tetrahydrocannabinol-9carboxylic acid (THC-COOH) (Mechoulam, 1999; Grotenhermen, 2003; Musshoff and Madea, 2006). The present study had therefore two objectives. First, to describe – under controlled inpatient conditions – the course of the CWS from shortly after cessation of chronic cannabis inhalation to up to 16 days, and second, to relate the CWS-severity to serum levels of THC and its metabolites.

2. Methods 2.1. Sample The study was conducted in 2006–2011 in an inpatient ward for detoxification from alcohol, medical drugs, and cannabis at the Psychiatric University-Hospital in Essen, Germany. Patients could be included into the study if they (a) were diagnosed as cannabis dependent according to ICD-10 (Dilling et al., 2004), (b) had consumed cannabis by inhalation daily or almost daily during the 6 months before admission, (c) had consumed cannabis within 24 h before admission, (d) had used no other psychotropic substances (except tobacco) or medication during 4 weeks before admission, and (e) had no active comorbid psychiatric or somatic disorder which could noticeably affect the course of cannabis detoxification treatment. Furthermore, patients had to be able to understand the explanation of the study and to voluntarily give their informed consent. Patients were excluded who during detoxification treatment exhibited a comorbidity requiring additional treatment, or showed positive results in their alcohol or drug screenings (see below) during treatment, or discontinued treatment within the first 48 h. Also those patients were excluded from the study who used cannabis during their inpatient treatment, as evidenced by self-report or by clinical observation or by indisputable urine screening results. In addition, patients were to be excluded who reduced their tobacco use for more than one quarter, in order to prevent interference of tobacco withdrawal symptoms with the study results. 2.2. Inpatient detoxification treatment Treatment usually was scheduled for up to 16 days, but could be extended if necessary. The multimodal treatment program consisted of medical visits; single and group therapeutic sessions which contained motivational enhancement, cognitivebehavioral treatment elements (Benyamina et al., 2008) and psycho-education; movement therapy and occupational therapy; and social counseling. Also, referral to subsequent long-term rehabilitation programs was offered. Parts of the routine treatment were randomized breath alcohol analyses and semi-quantitative drug screenings for cannabis, barbiturates, benzodiazepines, opiates, cocaine, amphetamines, methadone, and ethyl-glucuronide in urine. The patients agreed not to leave the ward without being accompanied by staff members and not to receive unchecked visitors. On ethical grounds, CWS could be medicated if needed in this prospective cohort-study. When patients showed distressing withdrawal symptoms such as anxiety, dysphoria, restlessness or sleep disturbance, nursing staff could administer escalating doses of gabapentin (up to 600 mg q.i.d.), or if this was not sufficiently effective, chlorprothixene (up to 50 mg q.i.d.; Bonnet and Scherbaum, 2010; Mason et al., 2012). The treatment was considered as completed when the psychiatric and somatic condition of patients had improved so far that rehabilitation treatment became possible. 2.3. Assessments After admission to treatment an interview based on the European Addiction Severity Index (Gsellhofer et al., 1997) was performed in order to obtain socio-demographic, addiction-specific, psychiatric and other relevant medical information. Substance use during the previous 6 months was assessed using a timeline follow-back interview (TLFB; Fals-Stewart et al., 2000). Furthermore, the body mass index (BMI) was determined on day 1. Additional information about previous psychiatric diagnoses was obtained by review of discharge letters and/or by contacting the referring physicians. During detoxification treatment the severity of the CWS was measured by a modified version of the Marijuana Withdrawal Checklist (MWC; Budney et al., 1999). In its original version the MWC consists of 10 symptoms (craving for cannabis, irritability, nervousness/anxiety, restlessness/tension, depression, anger/aggression, sleeplessness, strange dreams, loss of appetite, headache), which are rated on a 4-point scale (0 = not at all, 1 = mild, 2 = moderate, 3 = heavy; Budney et al., 1999). We added two symptoms (‘sweating’ and ‘nausea’; Allsop et al., 2011; Vandrey et al., 2008) to the original MWC (Budney et al., 1999). In contrast to other studies, the MWC was not handed out to be filled in by the patients, but was used as an interview. Simultaneously with the MWC, the Clinical Global Impression-Severity scale (CGI-S; Busner and Targum, 2007) was carried out in order to classify the general severity of the CWS. Ratings of the CGI-S range from 1 = normal to 7 = extremely ill (Busner and Targum, 2007). In addition, at day 1 and at the end of the scheduled study observation period (day 16) or before premature discharge the Brief Psychiatric Rating Scale (BPRS; Overall and Gorham, 1962) was used to assess the psychiatric burden of our study population. All instruments were performed in the late morning by the principal investigator (U.B.). At day 16 or before discharge the screening questionnaire from the Structured Clinical Interview for DSM-IV Axis II (SCID-II) (Wittchen et al., 1997) was completed by the patients. Blood and urine samples were scheduled for 9 a.m. on days 1, 2, 4, 8, 12 and 16. Blood was centrifuged, plasma separated and the samples were frozen at −20 ◦ C. On the same day, the material was sent to commercial clinical chemistry laboratories, which performed quantitative measures in serum by

U. Bonnet et al. / Drug and Alcohol Dependence 143 (2014) 189–197 gas chromatography–mass spectrometry (GC–MS) in Laboratory Laser (Cologne, Germany) and semi-quantitative measures in urine by enzyme immunoassay (EIA) in LVR-Laboratory (Dusseldorf, Germany). All patients were informed about the background and procedures and gave written consent for this study, which was approved by the local ethics committee. 2.4. Clinical chemistry in the commercial laboratories For quantitative GC–MS analysis (all made by R.O.), 1 ml of serum (centrifuged supernatant) was stirred with the corresponding deuterated standards and acidified with acetic acid. The solid phase extraction (SPE) columns are washed with methanol and conditioned with dilute phosphoric acid. Thereafter, the sample/controlstandards were given on the SPE columns and run through the column without vacuum. Then, the probes were washed with 0.5 ml of dilute acetic acid before eluting the cannabinoids with a mixture of chlorobutane and ethyl acetate. The obtained eluate was taken up in a sealable vial and dried under nitrogen at about 40 ◦ C. Subsequently, the derivatizing reagents were added, after which the sealed vials were transferred into microwaves, where they reacted at 500 W for 5 min. The samples/controls-standards were then dried again at about 40 ◦ C under nitrogen, then taken up in ethyl-acetate and measured by GC–MS (here QP2010 plus of Shimadzu (Shimadzu Europe) in SIM mode. The evaluation was carried out by means of the Shimadzu GC–MS Solution software (Shimadzu). Reference levels in serum were ≥1.0 ng/ml (THC and THC-OH) and ≥2.0 ng/ml (THC-COOH). For semiquantitative analysis, urine was investigated by Microgenics CEDIA DAU Multi-Level THC-assay (Microgenics) using a valid measurement range between 150 and 50 ng THC-COOH/ml urine (Grauwiler et al., 2008). 2.5. Statistics Group comparisons regarding MWC-scores over time were made using repeated measures (mixed) analysis of variance with multivariate criteria. Associations between amount of rescue medication received and MWC-scores were performed for each study day using multiple linear regression, taking into account confounding variables. Associations between MWC scores and laboratory parameters over more than one point in time were analyzed using generalized estimating equations (GEE). Associations at single time points were analyzed using Spearman’s rho, which is robust against skewed distributions. Two-group comparisons regarding laboratory parameters were performed using the Mann–Whitney U-test. For all of these tests, p < 5% as significance criterion was used. The software used for the statistical analysis was SPSS 21.

3. Results 3.1. Sample description Forty-three patients were eligible for the study and gave their informed consent. Four of them terminated treatment within the first 36 h after admission. No patient showed comorbid symptoms requiring additional treatment during the study. We did not find any evidence that a patient had used cannabis, alcohol or other psychotropic drugs during our supervised inpatient treatment. Five patients had reduced their usual daily tobacco use at the end of the study, but none of them by more than a quarter, so that he had to be excluded from the study (c.f. 2.1). Therefore, 39 patients were analyzed. Thirty-eight patients (97.4%) were white, 8 patients (20.5%) were female. Most lived alone (51.3%), were unemployed (69.2%) and had a moderate education level (76.9%; Table 1). Marijuana was used by 65.7% of the subjects, 15.4% used hashish and 17.9% both. All patients met at least 4 of the 6 ICD-10 criteria for cannabis dependence (including 15.4% who fulfilled 5 criteria). The majority (n = 26, 66.7%) of patients reported that they had consumed cannabis daily or nearly daily throughout the previous 12 months, 11 (28.2%) reported of periods of abstinence not longer than 10 days in the previous 12 months, and 2 patients (5.1%) reported to have once achieved 20 days of abstinence. Three (7.7%) patients had a history of inpatient withdrawal treatment and 2 (5.1%) of long-term rehabilitation treatment. Additional characteristics of cannabis misuse and sociodemography within this sample are given in Table 1. No patient reported of previous seizures or delirium. All were dependent from tobacco (ICD-10) and smoked cigarettes daily. Twelve patients (30.8%) reported of no experiences with other drugs, 25 (64.1%) had a past history of alcohol abuse

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or dependence, 20 (51.3%) patients reported of previous stimulant (except cocaine) abuse or dependence, 14 (35.9%) had abused hallucinogens, 10 (25.6%) cocaine, 5 (12.8%) sedatives and 3 (7.6%) opiates (tilidine). Three patients (7.6%) reported that they have tried out so-called ‘legal highs’ in their history. Twelve patients (30.8%) had a history of comorbid psychiatric disorders. The diagnoses included borderline personality disorder (4 patients), panic disorder (n = 3), unipolar depression (n = 2), paranoia (n = 2), and attention deficit/hyperactivity disorder (n = 1). Regarding the screening for personality disorders according to SKID-II, 3 patients (8.6% of 35 patients screened) showed no indication of a personality disorder, while 6 patients (17.1%) showed signs for 1 disorder, and 74.3% for 2 or more disorders. Most frequent were indications of a conduct disorder (n = 25, 71.4%) and borderline (n = 20, 47.1%), paranoid (n = 19, 54.3%), passive-aggressive (n = 17, 48.6%), or obsessive-compulsive (n = 16, 45.7%) personality disorders.

3.2. Treatment characteristics and attrition rate Most (n = 34, 87.1%) patients completed treatment regularly, while 5 (12.8%, all male) discontinued the inpatient treatment prematurely: 2 on day 9, the others on days 10, 12, and 13, respectively. The mean inpatient treatment lasted 18.5 ± 6.2 days. During detoxification, 19 patients (48.8%) received medication for withdrawal symptoms; all of them gabapentin and 7 of them additionally chlorprothixene The mean number of study days with gabapentin medication was 1.7 ± 2.0 for the whole sample and 3.4 ± 1.5 for those medicated; mean daily dose of gabapentin was 824.5 ± 569.5 mg, mean peak dose was 945 mg ± 619.4 mg. Mean number of days with chlorprothixene was 0.5 ± 1.2 for the whole sample and 2.9 ± 1.1 for those with chlorprothixene medication; mean daily dose of chlorprothixene was 76.2 ± 23.9 mg, mean peak dose was 92.9 ± 34.5 mg. The cumulative gabapentin and chlorprothixene doses were 5512 ± 9411 mg (range 0 to 36,000 mg) and 137 ± 347 mg (range 0 to 1500 mg), respectively (n = 39). Most treatment completers (n = 29, 74.3% of all patients) were referred to an outpatient treatment program at the same clinic (Hölscher et al., 2008), the remaining (n = 5, 12.8%) were referred to a specialized long-term rehabilitation ward.

3.3. Course of CWS For the sample as a whole the intensity of the CWS as measured by the MWC and the CGI-S peaked at day 4 and decreased afterwards (Fig. 1). The intra-individual peak was first observed on day 1 in 3 patients (7.7%), on day 2 in 12 patients (30.8%), on day 4 in 20 patients (51.3%), and on day 8 in 4 patients (10.3%). The maximum withdrawal severity according to CGI-S was 4 (‘moderately ill’) in 7 patients (17.9%), 5 (‘markedly ill’) in 16 patients (41%), and 6 (‘severely ill’) in 16 patients (41.1%).

3.4. Course of single withdrawal symptoms The profiles of the single withdrawal symptoms are displayed in Fig. 2. The mean intensity of irritability, nervousness, restlessness and anger increased until day 4 and then decreased. Craving and sleeplessness peaked on day 2. Strange, i.e. vivid and lucid dreams reached its maximum not until day 4. All these symptoms showed mild to moderate intensity, on average. The intra-individual peak for craving, the most intensive symptom, was first reached already on day 1 in 19 patients (48.7%), and on day 2 in 8 patients (20.5%). The other symptoms showed very low intensity throughout the course of the study.

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Table 1 History of cannabis use and sociodemography (n = 39). Cannabis history

MW ± SD

Median

Minimum

Maximum

Age (years) Daily cannabis (g) Duration of the current daily consumption (months) Duration of dependence (years) Age of the first consumption (years) Daily number of cigarettes Sociodemography Living alone Living with a partner or family Married Unemployed School drop out Completed 9 years of schooling Completed 10 years of schooling Completed 13 years of schooling High school Detention history

28.6 ± 7.5 2.5 ± 1.2 54.2 ± 62.5 9.9 ± 6.7 15.3 ± 2.4 22.6 ± 7.0 n 20 12 6 27 6 17 13 3 0 6

27.0 2.5 36 7.0 15 20.0 % 51.3 30.8 15.4 69.2 15.4 43.6 33.3 7.7 0 15.4

18 1.5 6 3 9 10

52 6.0 360 32 22 40

Fig. 1. Means and standard deviations of the CWS-checklist (MWC Score, top) and the Clinical Global Impression Scale (CGI-S Score, below) during the course of the study.

Fig. 2. Mean rating of single symptoms of the MWC. 4-point scale (0 = none, 1 = mild, 2 = moderate, 3 = heavy).

3.5. Internal consistency of the MWC Cronbach’s ˛ coefficients were only 0.49 and 0.55 on days 1 and 2. Coefficients were 0.67, 0.78, and 0.73 on days 4, 8, and 12, respectively. The scale used here therefore achieved ˛ coefficients comparable to that of the CWS-criteria proposed for DSM-5 (0.75; Gorelick et al., 2012) and of the original MWC of Budney (2004; 0.77). The items ‘sweating’ and ‘nausea’, which had been added to the original scale, did not improve internal consistency of the scale. In addition, ‘strange dreams’ and ‘loss of appetite’ showed only small (<0.2) item-scale correlations in our sample. 3.6. Influences on severity of the CWS In repeated measures (mixed) analyses of variance no significant (all p > 0.3) main or interaction effect on MWC scores was found with regard to the body-mass-index (BMI), self-reported

duration of cannabis dependence, duration of current consumption period or daily amount of cannabis consumption. The latter, however, was positively correlated with daily doses of rescue medication (rho = .422, p = 0.008). Furthermore, MWC scores were not significantly associated with history of psychiatric comorbidity (p = 0.31), indications for personality disorders (p > 0.12), or selfreported number of daily smoked cigarettes (p > 0.2). At the end of treatment the number of cigarettes consumed had increased slightly in the mean, but not significantly (p = 0.082). There was a gender effect, with women showing a more severe withdrawal syndrome than men (p = 0.018, Fig. 3). This gender effect did not disappear when BMI, duration and amount of daily cannabis intake, duration of dependence, age of first use, number of withdrawal treatments or indications of personality disorders were included into the analysis (p ≥ 0.19 for all of these covariates). Associations between BPRS scales at baseline and MWC scores during treatment

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Fig. 3. Significant influence of gender on MWC.

Fig. 4. Medians of MWC and serum cannabinoid-levels relative to individual baseline (day 1 = 100).

were generally low and not significant, although there was a tendency for baseline anxiety/depression to be associated with higher MWC scores on day 2 (rho = 0.43, p = 0.05). Amount of rescue medication showed no statistically significant correlation with MWC score on the respective study days 2 to 16 (p = 0.09–0.43). Linear regression analysis with gender and BMI as covariates, however, revealed a significant positive association of medication dose with MWC scores on days 8 (standardized beta = 0.41, p = 0.01), and 16 (beta = 0.62, p = 0.001), but not on days 2, 4, and 12 (p = 0.56, 0.073, and 0.34, respectively). 3.7. Course of THC and its metabolites, and correlation with the MWC At baseline, all patients had THC-levels ≥1.0 ng/ml (range: 2.7 to 139.7 ng/ml, n = 35) and THC-COOH-levels ≥2.0 ng/ml (range: 18 to 741.4 ng/ml, n = 35) in serum. THC-OH was in 77.1% (n = 27) above the reference level (range: <1.0 to 50 ng/ml, n = 35) to that time. Thereafter, the cannabinoid-levels decreased steadily over time (Table 2, Fig. 4). Serum THC-OH decreased the fastest and its median was below the reference level on day 4 (Fig. 4). Serum-THC levels were still above 1 ng/ml (range: 1.3 to 6.4 ng/ml) in 11 (55%) out of available 20 samples on day 16. A decrease of median urinary THCCOOH was seen first on day 8 when it decreased below the upper measurement range (150 ng/ml). At day 16 of abstinence, when the clinical cannabis withdrawal syndrome in most patients had subsided, many patients still had significant values of THC-COOH in their urine: from 23 available urines were 16 (70%) contaminated with THC-COOH >50 ng/ml (range: 51 to 141 ng/ml). Spearman rank correlations between the MWC and the 3 serum parameters were significant only on day 1 (admission): MWC/THC rho = −0.38 (p = 0.025); MWC/THC-OH: rho = −0.41(p = 0.016); MWC/TCOOH: rho = −0.63 (p < 0.001), i.e. the lower the level of the

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cannabinoids, the higher the CWS score. After day 1, correlation coefficients were small and not statistically significant. MWC scores on the respective days were also not significantly correlated with baseline-adjusted laboratory values. In addition, we analyzed the associations between the respective metabolites and MWC scores across all time points using Generalized Estimating Equations (GEE) with an AR-1 covariance structure and robust estimate of standard errors. Results now showed no statistically significant association of MWC scores with levels of THC (p = 0.16), but again statistically significant associations with THC-OH (p = 0.016) and THC-COOH (p = 0.013) in serum. All parameters had a negative sign, i.e. metabolite levels were inversely related with MWC score. Separate correlation analyses for each time point showed marked associations at day 1 only (r < −0.3), while there were near-zero correlations at day 2 to day 16. MWC and CGI measures of withdrawal on the respective days were not significantly correlated with metabolites’ rates of change from baseline (p = 0.18–0.8). Concerning the single withdrawal symptoms only for ‘strange dreams’ a significant correlation with serum THC was found at day 4 (rho = −0.55, p < 0.001). The BMI-correction of the laboratory values did not change the described relationships. Additional analyses comparing laboratory values of men versus women did not uncover significant gender effects for any laboratory measure on any day (all p > 0.05). 48.8% of study participants (n = 19) received medication for withdrawal symptoms, which is a potential confounding factor in the analysis of the association between withdrawal symptoms and levels of THC and metabolites. Therefore, we compared the medicated (n = 19) with the non-medicated group (n = 20) to this aspect. In patients without medication there was no significant correlation between MWC-scores and THC or its metabolites at days 2, 4, 8, 12 and 16 (p = 0.10–0.97). The same was true for patients with medication (p = 0.14–0.73). In comparison, there were also no significant differences between both groups with regards to associations between MWC-scores and cannabinoid levels (p = 0.07–0.83). 4. Discussion 4.1. What is new about this study? The study presents data on CWS from a white and treatmentseeking population of chronic cannabis dependent patients during inpatient detoxification about 16 days. It revealed a gender effect on CWS-severity and related CWS-severity to CGI-S, thus making the intensity of CWS comparable to other disorders. Negative correlations between CWS-severity and serum levels of THC and, more robustly, of THC-OH and THC-COOH were found at baseline, which extended recently published results that described a negative relationship between serum THC and two single withdrawal symptoms (‘difficulty getting off to sleeping’ and ‘anxious’) (Lee et al., 2014). Among the single withdrawal symptoms in our study, only for ‘strange dreams’ a significant correlation with serum THC was found. 4.2. Sample The patient population investigated here consisted of long-term cannabis users, with daily or nearly daily use for the previous 6 months or longer. Their cannabis consumption was in the upper range compared with other clinical studies on CWS (Budney et al., 2004; Arendt et al., 2007; Levin et al., 2010; Allsop et al., 2011; Lee et al., 2014). In contrast to other prospective studies (Budney et al., 1999, 2004; Arendt et al., 2007; Preuss et al., 2010; Lee et al., 2014), all patients developed a CWS in our study.

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Table 2 Course of CWS in relation to cannabinoids. Day 1

2

4

8

12

16

Mean (SD) Median n Mean (SD) Median n Mean (SD) Median n Mean (SD) Median n Mean (SD) Median n Mean (SD Median n

MWC (points)**

THC i.s. (ng/ml)

THC-OH i.s. (ng/ml)

THC-COOH i.s (ng/ml)

6.3 (2.7) 6.0 39 8.7 (3.5) 10.0 39 10.4 (4.6) 11.0 39 7.4 (5.0) 8.0 39 4.8 (3.3) 4.0 35 2.9 (2.4) 2.5 28

13.1 (23.8) 6.9 35*** 6.5 (5.8) 4.6 23 3.8 (3.0) 3.3 33 2.6 (4.0) 1.7 32 2.3 (3.9) 1.4 27 1.6 (2.0) .7 20

4.3 (8.6) 2.1 35*** 2.8 (4.1) 1.5 23 .8 (1.9) .0 33 .4 (1.5) .0 32 .3 (1.0) .0 26 .3 (.9) .0 20

146.4 (149.9) 102.5 35*** 119.7 (127.1) 99.3 23 39.6 (58.2) 19.5 34 17.9 (26.1) 10.2 32 15.7 (19.2) 10.2 26 9.1 (7.0) 7.0 21

THC-COOH i.u. (ng/ml)* >150 38*** >150 33 >150 38 144.0 35 92.0 31 95.0 23

Note: Values below the reference levels were treated as 0. * Means and standard deviations were not meaningful computable because of the values >150 ng/ml included in the sample due to the semi-quantitative test method. THC-COOH in urine (i.u.) was measured by semi-quantitative EIA, the other cannabinoids in serum (i.s.) with GC–MS (c.f. 2.4.). ** MWC (CWS-Checklist). *** 4 baseline samples have been lost on the way from the venipuncture, centrifugation, freezing and sending to the laboratory.

4.3. Course and characteristics of the CWS Similar to former prospective studies from U.S.A. (Budney et al., 2004) the intensity of CWS reached its climax on day 4 post cessation (mean 10.4 ± −4.6 points, median 11 points from possible 36 points, estimated in CGI-S as ‘markedly ill’ on average). Thereafter, the intensity gradually decreased over the next 12 days. The waxing and waning of the CWS could be caused by an overlap of a subsiding intoxication with lipophilic THC and the beginning withdrawal syndrome, which would explain the found negative correlation between serum THC and CWS-intensity on admission (c.f. 3.7.). Although we added the two items ‘nausea’ and ‘sweating’ to the original MWC (Budney et al., 1999), the mean total score in our inpatient setting did not reach the peak found in outpatient populations (Budney et al., 1999, 2004). This supports the notion that the CWS may in part be modulated by treatment setting (Budney et al., 2004), since an inpatient setting excludes external cues which may trigger conditioned withdrawal effects in patients’ everyday environments. Therefore the CWS observed in inpatient should be less severe than in outpatient settings (Budney et al., 2004). The increasing-decreasing course of CWS and the dominance of psychological withdrawal symptoms such as craving, restlessness, nervousness, irritability and sleeplessness are quite consistent across studies, regardless of whether retrospective or prospective in design, whether in inpatient or outpatient settings, whether with adult or adolescent populations (Budney et al., 2004; Arendt et al., 2007; Milin et al., 2008; Vandrey et al., 2008; Levin et al., 2010; Allsop et al., 2011). However, two inpatient studies on CWS found no increase of the CWS after admission (Preuss et al., 2010; Lee et al., 2014). The study of Preuss et al. (2010) included younger white patients (mean 19.7 years), a larger sample (n = 118), and had a shorter (10 days) observation period than the present study (Preuss et al., 2010). Furthermore, this study showed a higher dropout rate (40%, compared to 12.8% in the present study) and reported of a larger number of patients who developed little or no symptoms (Preuss et al., 2010). Recent cannabis intake (30% of patients had not consumed cannabis during the last 24 h before admission) and the amount of cannabis consumed the last time predicted higher symptom intensity (Preuss et al., 2010). The study of Lee et al. (Lee et al., 2014) included male adult predominantly African–Americans with lower median plasma THC-levels (4.1 ng/ml) on admission

than found in the present study (6.9 ng/ml) with predominantly white patients. This study has also a higher drop-out rate (55% at week 3) and only 56% of the participants developed a CWS at all (Lee et al., 2014; vs. 100% in the present study). Furthermore, the participants did not seek treatment and were studied in a more luxurious environment (Lee et al., 2014) than our patients. At first sight, the quantity of patients, who developed no CWS, and the temporal distance to the last consumption might have the biggest impact on the shape of the mean CWS-curve (linearly decreasing or waxing and waning) of the whole population included. In accordance with the results of Lee et al. (2014) we also did not find any significant correlation between CWS-severity and self-reported consumption parameters. Perhaps these were too homogeneous because, i.e. all patients reported to have consumed at least 6 months almost daily and at least 1.5 g cannabis during the last 24 h before admission (Table 1). Moreover, the CWS-severity appeared to be independent from indications for personality disorders and largely independent from the level of psychiatric symptoms of our population (c.f. 3.6). To the best of our knowledge, the present study is the first one relating CWS to CGI-S, thus permitting comparisons with withdrawal syndromes related to other substances. The average peak CWS in our sample (‘markedly ill’, 5) is comparable to the average intensity of an untreated alcohol withdrawal syndrome in an inpatient detoxification setting (Bonnet et al., 2011). For further comparison, patients with acute schizophrenic episodes in inpatient setting (Haro et al., 2003) and acute depressive episodes in outpatient settings (Freed et al., 1999; Khan et al., 2002) have been rated in the majority to be ‘severely ill’ (6) and ‘moderately ill’(4) according to CGI-S, respectively. A small outpatient study found CWS to be of similar severity as the tobacco withdrawalsyndrome, as measured with a special withdrawal and craving checklist (Vandrey et al., 2008). Women had a significantly stronger CWS than men. This gender effect was independent from the THC-levels, BMI, withdrawalmedication received, duration of cannabis-dependence, or consumption parameters. It could have simply reflected the baseline differences in symptom severity, as the magnitude of change from baseline and the time course of withdrawal among females looks to be identical to males (c.f. Fig. 3). Other studies had not discovered a “gender-effect” (Wiesbeck et al., 1996; Budney

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et al., 1999, 2004; Vandrey et al., 2008; Preuss et al., 2010; Allsop et al., 2011). Cannabinoid CB1 receptor density and physiology were assumed to be different in women’s and men’s brain (Fattore, 2013) which could explain the gender effect found in our study.

4.4. Influence of THC or its metabolites on CWS The present study is the second investigating possible associations between the levels of THC and its metabolites in serum and the intensity of the CWS. Only on admission day there were significant (negative) correlations between THC-levels and CWSintensity. This means, the lower the THC-level the stronger the CWS. The relatively homogeneous cannabis use in our sample without acutely intoxicated patients at baseline (c.f. 4.5: low plasma THC and THC-OH levels) might be the reason why no correlation was observed between serum cannabinoids and withdrawal severity afterwards, thus confirming recent results (Lee et al., 2014) On symptom-level there was a significant negative correlation between THC in serum and the ‘strange dreams’ at day 4, i.e. the less THC in serum the more strange dreams. This may support a specific affiliation of this symptom in the orchestra of the CWSsymptoms (Budney et al., 2004; Allsop et al., 2011; Lee et al., 2014), even if it occurred with mild intensity. Modulating effects of THC or withdrawal of THC on sleep stages have long been known (Feinberg et al., 1975). Beyond this we found no further correlation between the intensity of the CWS or its single symptoms and the measured THC metabolites. Their course through the biological compartments from the brain cells (Mura et al., 2005) toward blood and the influence of context and experience on the magnitude of symptoms seem to be too complex to unmask overarching significant correlations.

4.5. Interpretation of the levels of THC and its metabolites at baseline There are frequent data on the magnitude of rapid increase in serum cannabinoids immediately after acute cannabis inhalation available (c.f. Grotenhermen, 2003; Musshoff and Madea, 2006). The study which challenged recreational cannabis users (n = 24) to a THC-concentration (a joint with nearly 70 mg THC) resembling best the inhaled amounts reported from our patients found the following serum kinetics: following inhalation THC peaked at 12.3 ± 8.8 min with 231.0 ± 108.5 ng/ml, THC-OH peaked at 25.0 ± 15.5 min with 15.8 ± 8.8 ng/ml and THC-COOH peaked at 38.8 ± 18.5 min with 59.7 ± 56.9 ng/ml (Hunault et al., 2008). Subsequently, THC- and THC-OH-levels decreased within 8 h to equilibria (Hunault et al., 2008) comparable to the baseline values in the present study. Once equilibrium had been reached the intensity of psychoactive effect of cannabis was demonstrated to be proportional to serum concentrations of THC (Cone and Huestis, 1993). It might be assumed that THC-concentrations further decreasing from that level promote a CWS as demonstrated in the present and a recent study (Lee et al., 2014). A similar relationship could exist for CWS and serum THC-OH, which is psychoactive (Mechoulam, 1999), too, and did correlate negatively with the CWSseverity at baseline in our study, too. THC-COOH is not psychactive (Mechoulam, 1999) and showed higher levels in our study than in the study of Hunault (Hunault et al., 2008), reflecting a higher level of cannabis use in our study population (Musshoff and Madea, 2006; Grotenhermen, 2003).

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4.6. Course of THC and its metabolites and the resulting implications THC-OH in serum was the laboratory marker that had fallen fastest among the detection limit, which is supported by the findings of another group, who investigated THC-elimination in chronic cannabis users (Karschner et al., 2009; Bergamaschi et al., 2013; Lee et al., 2014). Remarkably, 28.2% (n = 11) of the chronic cannabis-dependents showed serum THC-levels still above 1 ng/ml on day 16 of their abstinence in our study. Karschner et al. (2009), Bergamaschi et al. (2013), and Lee et al. (2014) described similar results after 7,12 and 14 days of abstinence after chronic cannabis use, respectively. Recently, Bosker et al. (2013) found THC at abstinence days 14–16 (0.8 ± 0.2 ng/ml) and 21–23 (0.4 ± 0.2 ng/ml) in the serum of 84.2% and 67.7% of 19 chronic cannabis abusers, respectively. Because in the German traffic regulations drivers lose their license at THC-levels above 1 ng/ml in their serum (Oberlandesgericht Brandenburg, 2007) almost 30% of our patients would have lost their driving-license after more than 2 weeks of controlled abstinence. The question arises whether to that time found residual THC-levels, which were in the range 1.3 to 6.4 ng/ml (n = 11), are sufficient enough to induce impairments of neurocognitive or psychomotor performances. It is hypothesized that this residual THC is responsible for impairments in those performances (Karschner et al., 2009; Bergamaschi et al., 2013; Bosker et al., 2013), which were found even after 3 weeks of abstinence in chronic cannabis users (Bolla et al., 2002; Bosker et al., 2013). It is a sustaining debate whether the performance of chronic cannabis users can ever fully recover with increasing abstinence (Bolla et al., 2002; Crean et al., 2011). Nevertheless, serum THC concentrations of 2–5 ng/ml were associated with impairments on the critical tracking task, a skill important to driving performance (Raemakers et al., 2006). On the other hand according to epidemiological data, THC serum concentrations below 10 ng/ml are not associated with an elevated accident risk (Grotenhermen et al., 2007). Moreover, experimental studies on the impairment of driving-relevant skills by alcohol or cannabis suggests that a THC concentration in the serum of 7–10 ng/ml is correlated with an impairment comparable to that caused by a blood alcohol concentration (BAC) of 0.05% (Grotenhermen et al., 2007). On day 16 of abstinence, as the CWS in most patients had already subsided, yet a significant load with THC-COOH was found in the urines (median 95 ng/ml). The median urine THC-COOH decreased only slowly (144 ng/ml, 92 ng/ml, 95 ng/ml at day 8, 12 and 16, respectively). Therefore, the usefulness of the semi-quantitative urine-test was clearly limited in our population. In particular, useful creatinine normalization (Musshoff and Madea, 2006) was not possible because the measurements were too often above the quantitative measurement range (>150 ng/ml). Our data support the utility of serum THC-OH as a biomarker of recent cannabis inhalation in chronic cannabis users (Karschner et al., 2009; Bergamaschi et al., 2013; Lee et al., 2014). Urinary THCOH had been found to be not suited for this purpose (Lowe et al., 2009). But there are first promising data for the measure of cannabinoids, such as THC-glucuronide, in oral fluid to this objective (Lee et al., 2014). 4.7. Influence of the rescue medication Surprisingly, there were no significant differences between the CWS-severity of patients with and without rescue medication. One might speculate that the medication already given by nurse staff had relieved withdrawal symptoms to a degree that in the scores no longer difference between groups could be observed. In fact, effectiveness of gabapentin on the intensity of the CWS has recently been demonstrated (Mason et al., 2012). Linear regression analysis

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with gender and BMI as covariates, however, revealed a significant positive association of medication dose with CWS on its late (days 8 and 16) but not on its early part (days 2 and 4). Remarkable was a positive correlation between the medication and the amount of cannabis consumption prior to treatment (c.f. 3.6), which may indicate that expectation and attitude were more relevant for the usage of medication than the severity of the CWS itself. Both, in patients with medication and in patients without medication, there were always no significant associations between CWS-severity and levels of THC or its metabolites after admission. This could limit the importance of the medication to be a strong confounding factor in the correlation between CWS-severity and laboratory results of this study. 4.8. Strengths and limitations This study on human CWS has some strengths in that it was carried out under controlled inpatient conditions and had a comparatively long prospective observation time, a low dropout rate, multiple assessment of CWS complaints (using the MWC and the CGI-S), and analyzed associations between CWS and level of THC and metabolites in the body system. Most importantly, the analysis of the latter, however, could be considerably restricted by the not definitively regulated administration of the rescue medication. Further limitations were a small number of patients, semi-quantitative urine-screening on THC not always allowing creatinine-normalization, and measurement of THC and its metabolites not under forensic conditions, but in a wellequipped commercial clinical chemistry laboratory. 5. Conclusion CWS of an adult population of chronic cannabis-dependent patients was studied under controlled inpatient abstinent conditions. It declined within 16 days and peaked on abstinent day 4. At this time the patients were markedly sick. The CWS was dominated by psychological withdrawal symptoms in the order craving > restlessness > nervousness > sleeplessness. The first three of these symptoms scored higher than the rest already at baseline. MWC scores for women were significantly higher than for men from baseline on. Controlling for gender and BMI, higher dose of rescue medication was significantly associated with higher CWS severity on days 8 and 16. No overarching correlation was found between CWS-severity or its single symptoms and THC (and its metabolites THC-OH und THC-COOH) in serum. On day 16 of abstinence the THC level in the serum of almost 30% patients was still above 1 ng/ml. At this time, the urine of most patients was still substantially contaminated with THC-COOH. Author disclosure Role of funding source Nothing declared. Contributors Conception and design: U.B.; collection, analysis and interpretation of data: M.S., U.B., R.O., U.S.; drafting the article: U.B.; revising it critically for important intellectual content: N.S, M.S. All authors have read and approved the final version of the manuscript. Conflict of interest statement U.B. received fees for lectures and the organization of training courses by the following pharmaceutical companies: Actelion,

Boehringer-Ingelheim, Bristol-Myers Squibb, esparma, GlaxoSmithKline, Janssen-Cilag, Lilly, Lundbeck, Merz, and Servier. N.S. received fees for lectures, development of educational presentations and board memberships from Lundbeck, Jassen-Cilag, Reckitt-Benckiser and a grant from Roche. M.S., R.O. and U.S. had no conflict of interest. Acknowledgements The authors thank Ms. Raga Qasem and Mr. Markus Kudla as well as the staff of the detoxification ward ‘Station S1’ (LVR-Klinikum Essen, Germany) for their help with conducting the study. We are grateful to all participants for study support. References Agrawal, A., Pergadia, M.L., Lynskey, M.T., 2008. Is there evidence for symptoms of cannabis withdrawal in the national epidemiologic survey of alcohol and related conditions? Am. J. Addict. 17, 199–208. Allsop, D.J., Norberg, M.M., Copeland, J., Fu, S., Budney, A.J., 2011. The cannabis withdrawal scale development: patterns and predictors of cannabis withdrawal and distress. Drug Alcohol Depend. 119, 123–129. American Psychiatric Association, 2013. Diagnostic and Statistical Manual of Mental Disorders, Fifth ed. (DSM-5TM ). American Psychiatric Association, Washington, DC. Arendt, M., Rosenberg, R., Foldager, L., Sher, L., Munk-Jørgensen, P., 2007. Withdrawal Symptoms do not predict relapse among subjects treated for cannabis dependence. Am. J. Addict. 16, 461–467. Benyamina, A., Lecacheux, M., Blecha, L., Reynaud, M., Lukasiewcz, M., 2008. Pharmacotherapy and psychotherapy in cannabis withdrawal and dependence. Expert Rev. Neurother. 8, 479–491. Bergamaschi, M.M., Karschner, E.L., Goodwin, R.S., Scheidweiler, K.B., Hirvonen, J., Queiroz, R.H.C., Huestis, M.A., 2013. Impact of prolonged cannabis smokers‘blood on per se drugged driving laws. Clin. Chem. 59, 519–526. Bolla, K.I., Brown, K., Eldreth, D., Tate, K., Cadet, J.L., 2002. Dose-related neurocognitive effects of marijuana use. Neurology 59, 1337–1343. Bonnet, U., Scherbaum, N., 2010. Cannabis use disorders. Part II: Psychiatric and somatic sequelae and comorbidities. Fortschr. Neurol. Psychiat. 78, 360–367. Bonnet, U., Lensing, M., Specka, M., Scherbaum, N., 2011. Comparison of two oral symptom-triggered pharmacological inpatient treatments of acute alcohol withdrawal: clomethiazole vs. clonazepam. Alcohol Alcohol. 46, 68–73. Bosker, W., Karschner, E.L., Lee, D., Goodwin, R.S., Hirvonen, J., Innis, R.B., Theunissen, E.L., Kuypers, K.P.C., Huestis, M.A., Raemaekers, J.G., 2013. Psychomotor function in chronic daily cannabis smokers during sustained abstinence. PLoS One 8, e53127. Budney, A.J., Novy, P., Hughes, J.R., 1999. Marijuana withdrawal among adults seeking treatment for marijuana dependence. Addiction 94, 1311–1322. Budney, A.J., Hughes, J.R., Moore, B.A., Vandrey, R., 2004. Review of the validity and significance of cannabis withdrawal syndrome. Am. J. Psychiatry 161, 1967–1977. Budney, A.J., Vandrey, R.G., Hughes, J.R., Moore, B.A., Bahrenburg, B., 2007. Oral delta-9-tetrahydrocannabinol suppresses cannabis withdrawal symptoms. Drug Alcohol Depend. 86, 22–29. Busner, J., Targum, S.D., 2007. The clinical global impression scale: applying a research tool in clinical practice. Psychiatry (Edgemont) 4, 28–37. Crean, R.D., Crane, N.A., Mason, B.J., 2011. An evidence based review of acute and long-term effects of cannabis use on executive cognitive functions. J. Addict. Med. 5, 1–8. Cone, E.J., Huestis, M.A., 1993. Relating blood concentrations of terahydrocannabinol and metabolites to pharmacologic effects and time of marijuana usage. Ther. Drug Monit. 15, 527–532. Dasgupta, A., 2007. The effects of adulterants and selected ingested compounds on drugs-of-abuse testing in urine. Am. J. Clin. Pathol. 128, 491–503. Dilling, H., Mombour, W., Schmidt, M.H., 2004. Internationale Klassifikation psychischer Störungen. ICD-10 Kapitel V (F). Diagnostische Kriterien für Forschung und Praxis. Huber, Bern. Fals-Stewart, W., O’Farrell, T.J., Freitas, T.T., McFarlin, S.K., Rutigliano, P., 2000. The timeline followback reports of psychoactive substance use by drug-abusing patients: psychometric properties. J. Consult. Clin. Psychol. 68, 134–144. Fattore, L., 2013. Considering gender in cannabinoid research: a step towards personalized treatment of marijuana addicts. Drug Test. Anal. 5, 57–61. Feinberg, I., Jones, R., Walker, J.M., Cavness, C., March, J., 1975. Effects of high dosage delta-9-tetrahydrocannabinol on sleep patterns in man. Clin. Pharmacol. Ther. 17, 458–466. Freed, E., Goldney, G., Lambert, T., Tiller, J., Johnston, R., 1999. A double-blind, multicenter study to assess the tolerability and efficacy of paroxetine compared with amitriptyline in the treatment of depressed patients in Australian general practice. Aust. N. Z. J. Psychiatry 33, 416–421. Gorelick, D.A., Levin, K.H., Copersino, M.L., Heishman, S.J., Liu, F., Boggs, D.L., Kelly, D.L., 2012. Diagnostic criteria for cannabis withdrawal syndrome. Drug Alcohol Depend. 123, 141–147.

U. Bonnet et al. / Drug and Alcohol Dependence 143 (2014) 189–197 Grotenhermen, F., 2003. Pharmacokinetics and pharmacodynamics of cannabinoids. Clin. Pharmacokinet. 42, 327–360. Grauwiler, S.B., Drewe, J., Scholer, A., 2008. Sensitivity and specifity of urinary cannabinoid detection with two immunoassays after controlled oral administration of delta-9-tetrahydrocannabinol to humans. Ther. Drug Monit. 30, 1114–1124. Grotenhermen, F., Leson, G., Berghaus, G., Drummer, O.H., Krüger, H.P., Longo, M., Moskowitz, H., Perrine, B., Ramaekers, J.G., Smiley, A., Tunbridge, R., 2007. Developing limits for driving under cannabis. Addiction 102, 1910–1917. Gsellhofer, B., Fahrner, E.-M., Weiler, D., Vogt, M., Hron, U., Platt, J., 1997. Deutsche Version des ‘European Addiction Severity Index, http://www.emcdda.europa. eu/attachements.cfm/att 23587 DE ASI FB deutsch%20060629%20final.pdf (accessed on 01/04/14). Haney, M., Hart, C.L., Vosburg, S.K., Comer, S.D., Reed, S.C., Foltin, R.W., 2008. Effects of THC and lofexidine in a human laboratory model of marijuana withdrawal and relapse. Psychopharmacology 197, 157–168. Haney, M., Hart, C.L., Vosburg, S.K., Comer, S.D., Reed, S.C., Cooper, Z.D., Foltin, R.W., 2010. Effects of baclofen and mirtazapine on a laboratory model of marijuana withdrawal and relapse. Psychopharmacology 211, 233–234. Haro, J.M., Kamath, S.A., Ochoa, S., Novick, D., Rele, K., Fargas, A., Rodrı’guez, M.J., Rele, R., Orta, J., Kharbeng, A., Araya, S., Gervin, M., Alonso, J., Mavreas, V., Lavrentzou, E., Liontos, N., Gregor, K., Jones, P.B., On behalf of the SOHO Study Group, 2003. The Clinical Global Impression-Schizophrenia scale: a simple instrument to measure the diversity of symptoms present in schizophrenia. Acta Psychiatry Scand. 107 (Suppl. 416), 16–23. Hasin, D.S., Keyes, K.M., Alderson, D., Wang, S., Aharonovich, E., Grant, B.F., 2008. Cannabis withdrawal in the United States: results from NESARC. J. Clin. Psychiatry 69, 1354–1363. Hirvonen, J., Goodwin, R.S., Li, C.-T., Terry, G.E., Zoghbi, S.S., Morse, C., Pike, V.W., Huestis, M.A., Innis, R.B., 2012. Reversible and regionally selective downregulation of brain cannabinoid CB1-receptors in chronic daily cannabis smokers. Mol. Psychiatry 17, 642–649. Hölscher, F., Bonnet, U., Scherbaum, N., 2008. Use of an outpatient treatment center for cannabis abuse. Nervenarzt 79, 571–576. Hunault, C.C., Mensinga, T.T., de Vries, I., Kelholt-Dijkman, H.H., Hoek, J., Kridenier, M., Leenders, M.E.C., Meulenbelt, J., 2008. Delta-9-Tetrahydrocannabinol (THC) serum concentrations and pharmacological effects in males after smoking a combination of tobacco and cannabis containing 69 mg THC. Psychopharmacology 201, 171–181. Johansson, E., Halldin, M.M., Argurell, S., Hollister, L.E., Gillespie, H.K., 1989. Terminal elimination plasma half-life of 1-tetrahydrocannabinol (1-THC) in heavy users of marijuana. Eur. J. Clin. Pharmacol. 37, 273–277. Karschner, E.L., Schwilke, E.W., Lowe, H.R., Darwin, W.D., Herning, R.I., Cadet, J.L., Huestis, M.A., 2009. Implications of plasma 9-tetrahydrocannabinol, 11Hydroxy-THC, and 11-nor-9-Carboxy-THC concentrations in chronic cannabis smokers. J. Anal. Toxicol. 33, 469–477. Khan, A., Khan, S.R., Shankles, E.B., Polissar, N.L., 2002. Relative sensitivity of the Montgomery-Asberg Depression Rating Scale, the Hamilton Depression rating scale and the Clinical Global Impressions rating scale in antidepressant clinical trials. Int. Clin. Psychopharmacol. 17, 281–285. Kielholz, P., Ladewig, D., 1970. Drug addiction among juveniles with special consideration of hashish smoking. Dtsch. Med. Wochenschr. 95, 101–105. Kouri, E.M., Pope Jr., H.G., 2000. Abstinence symptoms during withdrawal from chronic marijuana use. Exp. Clin. Psychopharmacol. 8, 483–492. Lee, D., Schroeder, J.R., Karschner, E.L., Goodwin, R.S., Hirvonen, J., Gorelick, D., Huestis, M.A., 2014. Cannabis withdrawal in chronic, frequent smokers during

197

sustained abstinence within a closed residental environment. Am. J. Addict. 23, 234–242. Levin, K.H., Copersino, M.L., Heishman, S.J., Liu, F., Kelly, D.L., Boggs, D.L., Gorelick, D.A., 2010. Cannabis withdrawal symptoms in non-treatment-seeking adult cannabis smokers. Drug Alcohol Depend. 111, 120–127. Lowe, R.H., Abraham, T.T., Darwin, W.D., Herning, R., Cadet, J.L., Huestis, M.A., 2009. Extended urinary 9-tetrahydrocannabinol excretion in chronic cannabis users precludes use as a biomarker of new drug exposure. Drug Alcohol Depend. 105, 24–32. Mason, B.J., Crean, R., Goodell, V., Light, J.M., Quello, S., Shadan, F., Buffkins, K., Kyle, M., Adusumalli, M., Begovic, A., Rao, S., 2012. A proof-of-concept randomized controlled study of gabapentin: effects on cannabis use, withdrawal and executive function deficits in cannabis-dependent adults. Neuropsychopharmacology 37, 1689–1698. Mechoulam, R., 1999. Recent advantages in cannabinoid research. Forsch Komplementarmed. 6 (Suppl. 3), 16–20. Milin, R., Manion, I., Dare, G., Walker, S., 2008. Prospective assessment of cannabis withdrawal in adolescents with cannabis dependence: a pilot study. J. Am. Acad. Child Adolesc. Psychiatry 47, 174–179. Mura, P., Kintz, P., Dumestre, V., Raul, S., Hauet, T., 2005. THC can be detected in brain while absent in blood. J. Anal. Toxicol. 29, 842–843. Musshoff, F., Madea, B., 2006. Review of biologic matrices (urine, blood, hair) as indicators of recent or ongoing cannabis use. Ther. Drug Monit. 28, 155–163. Oberlandesgericht Brandenburg, 2007. Fahrverbot und THC—Mindestgrenzwert. Az: 1 Ss (OWi) 291 B/06. Beschluss vom 30.03.2007, http://verkehrsrechts forum.de/urteilsdatenbank/fahrverbot/teil-1/fahrverbot-thc— mindestgrenzwert.htm (accessed on 01/04/14). Overall, J.E., Gorham, D.R., 1962. The brief psychiatric rating scale. Psychol. Rep. 10, 799–812. Pabst, A., Kraus, L., Gomes de Matos, E., Piontek, D., 2013. Substanzkonsum und substanzbezogene Störungen in Deutschland im Jahr 2012. Sucht 59, 321–331. Preuss, U.W., Watzke, A.B., Zimmermann, J., Wong, J.W., Schmidt, C.O., 2010. Cannabis withdrawal severity and short-term course among cannabisdependent adolescent and young adult inpatients. Drug Alcohol Depend. 106, 133–134. Raemakers, J.C., Moeller, M.R., van Ruitenbeek, P., Theunissen, E.L., Schneider, E., Kauert, G., 2006. Cognition and motor control as a function of -9-THC concentration in serum and oral fluid: limits of impairment. Drug Alcohol Depend. 85, 114–122. United Nations Office on Drugs and Crime, 2013. World Drug Report 2013. United Nations Publications, www.undoc.org (accessed on 01/04/14). Vandrey, R.G., Budney, A.J., Hughes, J.R., Liguori, A., 2008. A within-subject comparison of withdrawal symptoms during abstinence from cannabis, tobacco, and both substances. Drug Alcohol Depend. 92, 48–54. Vandrey, R., Smith, M.T., McCann, D.U., Budney, A.J., Curran, E.M., 2011. Sleep disturbance and the effects of extend-release zolpidem during cannabis withdrawal. Drug Alcohol Depend. 117, 38–44. Vandrey, R., Stitzer, M.L., Mintzer, M.Z., Huestis, M.A., Murray, J.A., Lee, D., 2013. The dose effects of short-term dronabinol (oral THC) maintenance in daily cannabis users. Drug Alcohol Depend. 128, 64–70. Wiesbeck, G.A., Schuckit, M.A., Jelger, A., Tipp, J.E., Bucholz, K.K., Smith, T., 1996. An evaluation of the history of a marijuana withdrawal syndrome in a large population. Addiction 91, 1469–1478. Wittchen, H.-U., Zaudig, M., Fydrich, T., 1997. Strukturiertes Klinisches Interview für DSM-IV. Achse II: Persönlichkeitsstörungen. Hogrefe, Göttingen.