Effect of cannabis use on the course of schizophrenia in male patients: A prospective cohort study

Schizophrenia Research 137 (2012) 50–57

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Effect of cannabis use on the course of schizophrenia in male patients: A prospective cohort study Daniel van Dijk a, e,⁎, Maarten W.J. Koeter b, Ron Hijman c, René S. Kahn d, Wim van den Brink b a

General mental health institute ‘Duin en Bosch’, Duinenbosch 3, 1901AH, Castricum, The Netherlands Academic Medical Center, University of Amsterdam, the Netherlands Amsterdam Institute for Addiction Research, The Netherlands Neuroscience Division, University Medical Center Utrecht, The Netherlands d Neuroscience Division, University Medical Center Utrecht and Rudolf Magnus Institute for Neuroscience, The Netherlands e GGZ Friesland, The Netherlands b c

a r t i c l e

i n f o

Article history: Received 8 September 2011 Received in revised form 27 December 2011 Accepted 14 January 2012 Available online 6 February 2012 Keywords: Schizophrenia Cannabis Substance use Functional outcome

a b s t r a c t Background: Findings on the impact of cannabis use on the course of schizophrenia are inconsistent and not conclusive. Aims: To study the effect of cannabis use on the course of schizophrenia taking into account the effects of the quantity of cannabis use and important confounders. Methods: Prospective cohort study with assessments of symptoms, confounders and hospitalizations at baseline, 6 month and 12 month follow up. Results: In a representative cohort of 145 male patients with schizophrenia, 68 (46.9%) used cannabis. Mean age at onset of schizophrenia in cannabis using patients was significantly lower than in non-cannabis using patients. No other cross-sectional demographic or clinical differences were observed between users and non-users. In a series of longitudinal analyses, cannabis use was not associated with differences in psychopathology, but relapse in terms of the number of hospitalizations was significantly higher in cannabis using patients compared to non-cannabis using patients. Conclusions: Patients with schizophrenia using cannabis are more frequently hospitalized than non-cannabis using patients but do not differ with respect to psychopathology. Possible explanations for these findings are discussed. © 2012 Elsevier B.V. All rights reserved.

1. Introduction Reported prevalence of substance use disorders in people suffering from schizophrenia ranges from 10 to 70% (Regier et al., 1990; Dixon et al., 1991; Negrete, 2003; Swartz et al., 2006; Moore et al., 2007) depending on definitions of use and assessment methods (Swartz et al., 2008). Cannabis, the most frequently used illicit drug of the western world (Iversen, 2003; Di et al., 2007), is the preferred substance of patients with schizophrenia (Dixon, 1999; Green et al., 2007), and lifetime use is estimated to be at least twice as high as in the general population (Cantwell, 2003; Arseneault et al., 2004; Green et al., 2007; Swartz et al., 2008). Cannabis use is associated with an early age at onset of schizophrenia (Veen et al., 2004; Gonzalez-Pinto et al., 2008; Foti et al., 2010) and the use of cannabis is considered to be a major problem in treating this disease. Whether cannabis use is an etiological or precipitating factor of psychotic episodes or the result of converging genetic vulnerabilities is still in debate (Knudsen and Vilmar, 1984; Barnes et al., 2006; ⁎ Corresponding author at: Department Psychosis and Rehabilitation, GGZ Friesland, Sixmastraat 2, 8901BS, Leeuwarden, The Netherlands. Tel.: + 31 623940732. E-mail address: [email protected] (D. van Dijk). 0920-9964/$ – see front matter © 2012 Elsevier B.V. All rights reserved. doi:10.1016/j.schres.2012.01.016

Tandon et al., 2008; Welch et al., 2011; Zammit et al., 2011) but cannabis seems to be at least a component cause in the development of schizophrenia (Kuepper et al., 2010). The use of psychoactive substances such as cannabis could also be a form of self-medication in an attempt to mitigate existing symptoms or to reduce the side effects of the antipsychotic medication (Khantzian, 1985; Test et al., 1989; Khantzian, 1997). Altogether the role of cannabis use as a causal factor in the onset of schizophrenia remains an unresolved issue due to the methodological limitations of most studies (Macleod et al., 2004; Moore et al., 2007). This study does not address the role of cannabis in the development of schizophrenia but is focused on the effect of continued cannabis use on the course and outcome of patients already suffering from schizophrenia. In most longitudinal studies, cannabis using patients with schizophrenia reported more psychopathology and showed higher relapserates (Linszen et al., 1994; Johns, 2001; Swanson et al., 2007; Swartz et al., 2008). Cannabis use was also associated with reduced effectiveness of antipsychotics (Knudsen and Vilmar, 1984; Swartz et al., 2008), less access to non-pharmacological interventions (Regier et al., 1990; Wilk et al., 2006), problems in therapeutic alliance (Dixon, 1999; Wilk et al., 2006), early discharge from hospital independent of psychopathology (Brunette et al., 1997), and an increased need

D. van Dijk et al. / Schizophrenia Research 137 (2012) 50–57

for interventions and longer hospitalizations (Kivlahan et al., 1991). These negative effects of cannabis use in patients with schizophrenia were dose dependent (Andreasson et al., 1987; Linszen et al., 1994; Harrison, 1999; Rais et al., 2008; Weinstein et al., 2008; Yucel et al., 2008) with a narrow ‘therapeutic window’ (Iversen, 2003), even a small change in the amount of cannabis that was used could have an effect on the course of the disease. Indeed most studies have found a negative effect of cannabis use on the course of schizophrenia. However, some studies have shown contradictive findings. For example in one of the older cohort studies the cannabis-using group had significantly better cross-sectional scores on affective measurements (Peralta and Cuesta, 1992). A similar positive effect of cannabis on anxiety and depressive symptoms in schizophrenic patients was reported in a subgroup of ‘mild abusing’ subjects in a Dutch cohort that used cannabis less than once daily (Linszen et al., 1994). Other authors also reported less anxiety and fewer depressive symptoms in schizophrenic patients using cannabis (Johns, 2001), or were surprised by the lack of differences with respect to psychopathology between users and non-users at baseline (Zisook et al., 1992). Cannabis use in follow-up data of the CATIEcohort was even associated with higher or at least equal psychosocial functioning compared to abstinent patients (Swartz et al., 2006). Although cannabis use may have adverse consequences in psychosis-prone people (Iversen, 2003; Caspi et al., 2005; DeLisi, 2008), evidence of a persisting negative impact on the healthy brain is inconclusive (Iversen, 2003; Jager et al., 2006; Jager et al., 2007; DeLisi, 2008; Zullino et al., 2008). In a systematic review carried out in order to answer the question whether cannabis use has a negative effect on the course and outcome of psychotic disorders, relatively few longitudinal studies were found that examined this topic (Zammit et al., 2008). According to this review, prospective cohort studies and retrospective case–control studies showed that cannabis use was consistently associated with increased relapse and nonadherence, but associations with other clinical outcome measures were inconsistent. The authors concluded that these inconsistencies were probably due to differences between studies in the adjustment for confounders. They called for prospective studies with repeated measures of psychopathology and adjustment for relevant confounders such as baseline illness severity, length of illness period, gender, socioeconomic status and the use of alcohol and other drugs. In order to be able to compare the results of these new studies with existing data, the authors called for the simultaneous presentation of both crude and adjusted data (Zammit et al., 2008). A limitation of this review could be that it was not restricted to schizophrenic spectrum disorders but that the reviewed studies comprised a wide range of psychotic disorders. Other authors mention other methodological problems complicating the interpretation of the observed relation between cannabis use and the course of schizophrenia. For example the absence of an objective laboratory assessment of cannabis use in most studies may have led to an underestimation of cannabis-use and complicates the interpretation of some studies that addressed the impact of the use of cannabis on the course of the disease (Johns, 2001; Foti et al., 2010). Fortunately the reliability of anamnestic information on cannabis use seems to be fairly good (Gignac et al., 2005). Because of the liberal attitude and policy in the Netherlands toward cannabis use this reliability might be even better in Dutch cohort-studies (Veen et al., 2004). Although cannabis is an illegal substance in the Netherlands, the use of cannabis and the possession of small quantities are tolerated and the narcotic law is not enforced. Cannabis is sold in small quantities (b5 g) in so called ‘coffee shops’, with free and legal access to everyone older than 18 years. In most studies amongst patients suffering of schizophrenia a gender difference is seen in the prevalence of cannabis use, women use less cannabis. This difference is also seen in the general population. (Bardenstein and McGlashan, 1990; McGlashan and Bardenstein,

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1990; Brunette and Drake, 1997, 1998; Leung and Chue, 2000; Opler et al., 2001; Krakowski and Czobor, 2004; Veen et al., 2004; Morgan et al., 2008). In the current study regarding the effect of cannabis use on the course of schizophrenia, we addressed most of the methodological problems mentioned above. We used a prospective, comparative cohort design in which cannabis exposure levels were measured repeatedly and associated with repeated measures of psychopathology while controlling for important confounders. This design is suitable to test the four following hypotheses: 1) Cannabis-using patients with schizophrenia have an earlier onset of schizophrenia (cross sectional). 2) Cannabis-using patients with schizophrenia show more (severe) psychopathology at baseline than non-using patients (crosssectional). 3) The course of schizophrenia, assessed by the levels of psychopathology and the frequency of relapse, in cannabis-using patients is worse than the course of non-using patients, even after controlling for the most important confounders (longitudinal). 4) Effects of cannabis use are related to the amount of the cannabis that is used, even after controlling for the most important confounders (longitudinal). 2. Methods 2.1. Sample 2.1.1. Inclusion criteria To be eligible, patients had to be between 18 and 65 years of age, able to understand the informed consent procedure and meet DSM-IV criteria for schizophrenia, schizophreniform disorder or schizoaffective disorder. 2.1.2. Study design and recruitment The study was conducted in the Netherlands in a mixed rural and urban area, comprising approximately 700,000 inhabitants. All medical professionals of mental health institutes and all general practitioners were informed about the study by mailing and conferences. They were asked to refer patients, eligible for the study, to a clinical research team. This team consisted of trained psychiatrists, physicians, nurses, laboratory employees and a neuropsychologist. Recruitment covered a 3 year period (2000–2003). Mental health care in the Netherlands is primarily community based. Only when the behavior of a psychiatric patient is a risk factor for the safety of the patient or society, patients are hospitalized. Hospitalized patients are often people who rejected regular care and/or pharmacotherapy which is a common reason for relapse. Recruited patients included both patients already in treatment (prevalence sample) and relapsed patients who did not receive treatment at that time (incident sample). As a consequence all patients at baseline were in treatment or just started treatment. Of the 249 referred patients, 35 did not show up for the first visit. Of the remaining 214 patients, 2 had insufficient command of the Dutch language and 3 patients were unable to understand the study as a result of cognitive disabilities, according to the researcher in charge during the first contact. The remaining 209 patients were informed about the procedures of the study and subsequently they were interviewed in order to establish the diagnosis. A total of 12 patients were excluded from the study because they did not meet the diagnostic criteria for a schizophrenic disorder. Of the remaining 197 patients, 21 patients withdrew their informed consent after inclusion and two patients died by suicide. Of the 174 remaining subjects, 29 patients were female. Female patients were excluded post hoc as will be explained in the result section. As a consequence baseline data pertain to 145 male patients (t0).

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All included patients were invited for follow-up assessments at 6 (t1) and 12 (t2) months after baseline assessment. During the follow-up period 19 (13%) patients dropped-out. A total of 126 subjects (87%) had at least one follow up assessment and 90 subjects completed the study (62%). The planned follow-up periods exceeded the period of 6 and 12 months due to logistic factors that were not patient related. The mean follow-up period therefore was 410 days (range: 77–741 days). Time between baseline and the second visit (t1) was 335.6 days (range 77–613 days) and the mean period between t1 and the third visit (t2) 439.7 days (range 180–741 days). Follow-up data on (re)hospitalization were available for all patients including drop-outs, because after drop-out all patients agreed that already collected data and administrative data on hospitalization could be included in our data base (Fig. 1). 2.1.3. Instruments and procedure Diagnostic interviews, substance-use assessment scales, assessment of neurological side-effects and clinical symptom scales were administrated by psychiatrists or physicians. All raters received special training in the administration and scoring of the instruments. Interrater-reliability for PANSS, MADRS and CGI was good (kappa > 0.85). The assessment of the Quality of Life was carried out by trained nurses. Data were obtained in a four-year period (2000–2004). The design and research protocol was approved by the independent medical ethical committee of the Medical Centre Alkmaar (MCA), a non-affiliated hospital. 2.1.4. Inclusion procedure Diagnosis was confirmed with the Comprehensive Assessment of Symptoms and History (CASH); a semi-structured diagnostic interview. If necessary information could also be gathered from medical files related to psychiatric history of the patients (Andreasen et al.,

Referrals: n=249 No show: n=35 No CASH: n=5 CASH t0: n=209 Excluded: n=12 Included: n=197 Drop-out: n=23 Total cohort: n=174 Female: n=29(excl.) Baseline t0:n=145 Drop-out: n=19 Follow-up t1: n=126 Drop-out: n=36 Follow-up t2: n=90 Fig. 1. Number of referrals, inclusion, exclusion and drop-out total cohort (CASH=diagnostic interview).

1992). After explanation of the study procedures, written informed consent was obtained from all study participants. 2.2. Baseline assessment (t0) 2.2.1. Illness duration Illness duration was defined as the period between the onset of psychotic symptoms according to the CASH interview and the time of baseline assessment. 2.2.2. Symptoms Psychiatric symptoms were assessed with the Positive And Negative Symptom Scale (PANSS) (Kay et al., 1987, 1988) and the Montgomery-Asberg Depression Rating Scale (MADRS) (Montgomery and Asberg, 1979). Clinical symptom severity was measured with the Clinical Global Impression scale (CGI) (Berk et al., 2008). Special attention was given to the items of the PANSS measuring agitation, lack of cooperation with carers and aggression, the PANSS Excitement Component (PEC), since these items are important as a proxy for the therapeutic alliance. 2.2.3. Quality of life In order to get a better insight into the patients perceived satisfaction with life the Lancashire Quality of Life Scale, European version (QoLi-Eu) (Gaite et al., 2000), was administered. 2.2.4. Side effects Possible side effects of antipsychotic medication, important confounders when measuring quality of life and course of the disease, were assessed with the Unified Parkinson Disease Rating Scale, motor exam (UPDRS) (Martinez-Martin et al., 1994), the Barnes Akathisia Scale (BAS) (Barnes, 1989; Barnes, 2003) and the Abnormal Involuntary Movement Scale (AIMS) (Smith et al., 1979). 2.2.5. Sociodemographics Socioeconomic status was based on anamnestic data with respect to education, profession and salary of the patient and of his caretakers (mostly being parents). 2.2.6. Substance use The use of cannabis and other, non-prescribed, psychoactive substances was assessed with the Cannabis Assessment Scale (CAS) and the Assessment of Substance Use (ASU). These interviews were specially designed for the purposes of this study. The CAS, a semistructured interview, consists of two parts that assess the actual use, quantity and frequency of the use, money spent on cannabis and setting of use (part 1, 6 items) and the use of cannabis in the past (part 2, 4 items). Reliability of the CAS total score was high (Cronbach's alpha: .93). The Assessment of Substance Use (ASU), is a structured interview to assess the use, qualitative and quantitative, of all other, non-prescribed, psychotropic substances, including alcohol, coffee and tobacco (15 parts of 3 items each, Cronbach's alpha for the total score: .93). Other sources of information about the use of substances were interviews with relatives of the patients, caretakers, therapists and the CASH interview. Urine samples were collected during the interviews and semi-quantitative analyses were performed for cannabis, cocaine metabolites, amphetamine, ecstasy, benzodiazepines and opiates (including methadone). Two tests were used. The first assessed the actual use of all mentioned substances with a detection period of 3 days. The second test assessed the use of cannabis in the preceding month. When a patient mentioned the use of cannabis more than once in the month preceding the baseline assessment and/or the drug-screen was positive for cannabis use, we considered the patient to be a cannabis user. However, if patients were cannabis users at baseline but used less than four times during the follow-up period or less than

D. van Dijk et al. / Schizophrenia Research 137 (2012) 50–57

one time in the month preceding the follow-up assessments they were considered non-users for that follow-up period in agreement of earlier research in this field (Veen et al., 2004; Foti et al., 2010). Two patients with a positive drug-screen denied cannabis use at baseline but confirmed at follow-up the use of cannabis. Because of the supposed dose-effect correlation we focused not only on the dichotomous variable use/no use (qualitative), but also addressed quantitative variables. Cannabis exposure level was operationalized as the amount of cannabis used weekly, which was estimated by the product of the number of days a week a patient was using cannabis and the average number of cannabis-cigarettes (joints or reefers) that a patient used on a smoking day. 2.3. Follow-up assessments (t1, t2) 2.3.1. Follow-up visits At 6 and 12 months, all tests were repeated, except for the Quality of Life scale, which was only administered at the baseline visit (t0) and the last visit (t2). 2.3.2. Pharmacotherapy During each visit the patient was asked whether he used antipsychotic medication. Specific information about type, dosage and administration was also obtained. 2.3.3. Relapse Because hospitalization is a reliable and valid measure of relapse, the main outcome of this study, relapse of the psychotic disorder, was operationalized in 2 ways: number of hospitalizations during the study-period and the total duration of these hospitalization(s). When patients dropped-out, administrative data concerning (re)hospitalization, were obtained for the period of a year after baseline from all hospitals in the catchment area. Thus 12 month hospitalization data were available for all patients that completed baseline assessment (n = 145).

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Longitudinal outcomes include relapse (hospitalization) and changes in the level of psychopathology and quality of life over time. In the longitudinal analyses, the relation between current cannabis use (yes/no) and number of hospitalizations and mean duration of hospitalization, both count variables, were assessed with Poisson regression. Current cannabis use (yes/no) is the independent variable and age, years of illness, severity of illness, SES, use of alcohol and other drugs, length of follow-up period, and the PEC are covariates. The latter variable from the PANSS (PEC) was used as a potential confounder since continued cannabis use might be associated with patient-therapist tensions that may have a negative effect on course and outcome. The within person relation between the amount of cannabis used and changes in psychopathology was assessed with a repeated measures mixed model linear regression analysis. In order to separate the cross-sectional and longitudinal effects of the amount of cannabis use, we applied the following regression model proposed by Fitzmaurice (Fitzmaurice, 2004) for each of the psychopathology scores: Yt = b0 + b1(Xt − Xt = 0) + b2Xt = 0 +covariates. In this model, Yt is the psychopathology score at measurement occasion t (t0 = baseline, t1 = 6 months FU, t2 = 12 months FU) and Xt = 0 is the baseline score of X. In this model b1 can be interpreted as the longitudinal effect of the amount of cannabis used on pathology scores, i.e. the effect of changes of the amount of cannabis used over time on changes of psychopathology scores over time. b2 can be interpreted as the cross sectional effect of cannabis use on psychopathology, which is an answer to the question whether patients that use more cannabis than other patients show higher scores on psychopathology scales. The dependence between the longitudinal observations is modeled in this repeated measures regression analysis by an unstructured covariance matrix. The significance level is adjusted for the number of tests. However, setting alpha at a lower level decreases the power of the tests. For this reason we decided to be less conservative than Bonferoni correction and used an alpha of .005 For all analyses SPSS (17th version) was used. 3. Results

2.4. Statistical analysis

3.1. Baseline characteristics

Potential selection bias was assessed by comparing the baseline cohort with the patients that dropped out before and after the diagnostic CASH interview, on demographical characteristics using a ttest for continuous variables and chi-square tests for categorical variables. Both the cross-sectional relation between cannabis use and illness severity and the prospective relation between cannabis use and the course of illness were determined. The former assesses the between subject variation, i.e. whether patients that used cannabis were less well off than patients who did not use cannabis at baseline. The latter assesses the within subject variation, i.e. whether changes in cannabis use over time are related to changes in outcome for individual patients and for the group of cannabis users as a whole. Cross-sectional comparisons pertain to baseline measures and concern age at onset of schizophrenia, psychopathology, possible side effects of antipsychotic medication and quality of life. Crosssectional differences are tested with analyses of covariance (ANCOVA) with current cannabis use (yes/no) as independent variable and age, years of illness, severity of illness, use of alcohol and other drugs and socioeconomic status (SES) as covariates. The mean use of more than two glasses of alcohol daily as well as the regular (at least weekly) use of stimulants such as cocaine, amphetamine and ecstasy, were also considered to be potential confounders. Cross-sectional differences between cannabis users that were divided in ‘moderate use’ and ‘heavy use’ with different types of operationalization of these categories were tested with Analysis of Variance (ANOVA).

3.1.1. Initial cohort The initial cohort consisted of 174 patients: 29 females (16.7%) and 145 males (83.3%). Mean age was 33.7 years. Most subjects were Dutch (95.7%) and the vast majority was of Caucasian background (88.4%). No significant differences were found between the baseline cohort and the subjects that died or dropped out after the CASH interview but before baseline assessment (n = 23), with respect to demographic variables, schizophrenic disorder subtype or the use of cannabis (Fig. 1). Of the 174 patients, 73 (42.0%) used cannabis during the study period. As expected cannabis use was much more prevalent in males (n = 68/145; 46.9%) than in females (n = 5/29; 17.2%). Because the number of female patients was small (n = 29) and the pattern of referral, study-adherence (drop-out was more frequent in women; p = .034) and the use of cannabis was significantly different, combined with the fact that the course of schizophrenia might be different for the two genders (Bardenstein and McGlashan, 1990; McGlashan and Bardenstein, 1990; Brunette and Drake, 1997, 1998; Leung and Chue, 2000; Opler et al., 2001; Krakowski and Czobor, 2004; Morgan et al., 2008), we decided to restrict all further analyses to male patients (n = 145). 3.1.2. Male cohort As was stated before, cannabis was used by 68 patients (46.9%). Cocaine, the second illegal substance, was used by 12 patients (8.3%) and two of them also used cannabis. XTC was used by 10

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subjects (6.9%) and four of them also used cannabis. Amphetamine was used by four subjects (2.8%), of whom three patients used cannabis. The use of other illegal drugs (including heroin, lysergic acid, PCP) was very rare. The use of any kind of stimulant (cocaine, amphetamine, ecstasy) was 18% (26 subjects of whom 9 used also cannabis). In most of these cases stimulant use was incidental (once a week). Only 1 patient used stimulant drugs on a daily basis. Cannabis use was often more than once a week. The majority of the patients regularly used coffee (86.2%) and tobacco (78.6%). A total of 95 patients used alcohol (65.1%) and of those 24 (16.4%) were drinking more than 15 units/week. Binge drinking (>5 units/day) was seen in 6 patients (4.1%). In 13 patients data on the use of alcohol were missing (8.9%). There were no significant differences between the baseline group and the drop-out group (n= 28; 16.1%) with respect to age (p= .206), socioeconomic status (p= 1.000), cannabis use (p= .882), or the number of hospitalizations (p= .307). At baseline 78 patients were in outpatient treatment (53.8%), 61 were hospitalized (42.1%) and in six patients these data were missing (4.1%). No significant correlation between treatment setting and cannabis use was found (p= .486). No patients were homeless during the study-phase. High drop-out in the last phase of the study and the relative long period between baseline and follow-up moments were mostly not patient-related but due to unexpected circumstances caused by a reorganization of the mental health care services in the catchment area of the study.

However, in contrast to our second hypothesis, after adjustment for duration of illness, age, socioeconomic status, use of alcohol and other drugs, cannabis using and non-using patients did not significantly differ in symptom severity, illness severity, medication side effects and quality of life at baseline. Unadjusted data looked very similar and also did not reveal any significant differences between the two groups (Table 1).

3.2. Baseline comparison of cannabis users and non-users

3.4. Dose–effect relation between cannabis use and psychopathology

The results of the ANCOVA analysis in Table 1 confirm our first hypothesis: cannabis using patients had a lower age at onset of the disease than non-using patients (18.3 vs. 20.8 years; p = 0.006). Furthermore, the lower age at baseline (28.7 vs. 36.1 years; p b 0.001) resulted in a significantly shorter duration of the disease at baseline for the cannabis using group compared to the noncannabis using group (10.5 vs. 15.3 years; p = 0.003).

Table 3a shows the results of the mixed model regression analyses with both cross-sectional and longitudinal effect estimates. No significant associations between the mean number of days a week a patient used cannabis and psychopathology were found after adjustment for gender, age at onset, duration of illness and its severity, socioeconomic status, study adherence, use of other drugs and alcohol, neither cross-sectional nor longitudinal. Mean daily dose (mean number of joints used weekly) was also not related to (changes in) psychopathology scores and quality of life (Table 3b). Changes in the pattern of cannabis use during the study period were also not associated with outcome measures. When the cannabis use at baseline was divided in ‘low use’ and ‘high use’ no relevant differences could be seen either. Different kinds to operationalize the concept of ‘heavy use’ and ‘moderate use’ were carried out such as daily use versus non-daily use or depending on the number of joints used per day or per week and a composite score of both numbers. The subgroups' high and low use were relatively small. In summary no significant cross-sectional or longitudinal relationships between the amount of cannabis use and the level of

Table 1 Baseline characteristics, psychopathology, medication side effects and quality of life (Mean ± SD) in males (n = 145), ‘crude data’ and adjusted data. Cohort

No cannabis use Cannabis use Total (n = 77) (n = 68) (n = 145)

Clinical historya Age at baseline 36.1 ± 10.0 Age of onset 20.8 ± 5.9 Length of illness (yrs) 15.3 ± 10.8

28.7 ± 6.2 18.3 ± 4.0 10.5 ± 6.9

32.6 ± 9.2 19.6 ± 5.3 13.7 ± 10.0

Psychopathologyb PANSS Total PANSS Positive PANSS Negative PANSS General PANSS PEC MADRS CGI

72.1 ± 14.9 17.7 ± 5.5 18.5 ± 5.0 35.8 ± 8.0 9.5 ± 3.5 11.0 ± 7.5 3.9 ± 1.0

71.5 ± 16.5 17.3 ± 5.9 18.3 ± 5.3 35.8 ± 8.5 9.2 ± 3.3 10.5 ± 6.8 3.8 ± 1.0

70.9 ± 17.9 17.0 ± 6.3 18.1 ± 5.7 35.8 ± 9.0 9.0 ± 3.1 10.1 ± 6.2 3.6 ± 1.1

p

p***

b.001 .006 .003

.376 .482 .356 .606 .953 .530 .046

.676 .514 .653 .976 .280 .428 .061

3.3. Prospective comparison of cannabis using and non-using patients on hospitalization Table 2 shows the relationship between baseline cannabis use and the number of hospitalizations and the total length of these hospitalizations. Analysis of the duration of the hospitalization was restricted to all patients that were hospitalized for at least one night during de study period. These findings confirm our third hypothesis. After adjustment for potential confounders and length of follow-up period cannabis using patients were significantly more often hospitalized than non-using patients (1.2 versus 0.7 times; p = .035). Although the number of days in hospital in the cannabis-using group as a whole was higher, approximately 50 days longer hospitalization (p b .001), this was probably not directly related to the use of cannabis because after controlling for confounders the difference was no longer significant (p = .340). Of all confounders, any regular stimulant use at baseline had the strongest influence on the length of these hospitalizations (p = .097).

Table 2 Relation between cannabis use and relapse during follow-up, males (mean ± SD, n = 145). Exposition status

Side effectsb UPDRS BAS AIMS

11.1 ± 8.7 0.7 ± 0.9 14.8 ± 3.6

9.7 ± 6.3 0.7 ± 0.9 13.5 ± 3.2

10.5 ± 7.7 0.7 ± 0.9 14.2 ± 3.5

.869 .406 .428

.290 .769 .030

Quality of lifeb QoLi (Lancashire)

56.8 ± 26.7

51.5 ± 23.2

54.3 ± 25.1 .274

.260

p: adjusted p-value. p***: p-value when not adjusted for confounders as mentioned above (‘raw data’). a ANOVA. b ANCOVA with age, age of onset, baseline alcohol use (more than 14 glasses a week y/n), stimulant use (any use of cocaine, amphetamines or speed) and SES at baseline as covariates. All significance tests compare cannabis users with non-cannabis users.

No cannabis use Cannabis use (n = 77) (n = 68)

Clinical status/relapse Mean number of .7 ± 1.0 hospitalizationsd Number of 150.4 ± 155.7 hospitalization days a

1.2 ± 1.6

eβa

eβb

pc

1.64 1.69 .035

pb

.004

201.0 ± 156.4 0.98 1.34 .321 b.001

Adjusted effect estimate (ratio geometric means). Raw estimate, effect estimate (b). Poisson-regression, with propensity score based on age, duration of illness, SES, duration of follow-up, baseline alcohol use, baseline stimulant use and baseline illness severity as covariate. d Analyses restricted to subjects that were hospitalized for at least 1 day. b c

D. van Dijk et al. / Schizophrenia Research 137 (2012) 50–57 Table 3a (Changes in) number of days a week of cannabis use and (changes in) symptom severity (n= 145).

PANSS positive PANSS negative PANSS general PANSS total MADRS total QoLi (Lancashire)

Cross-sectional Longitudinal Cross-sectional Longitudinal Cross-sectional Longitudinal Cross-sectional Longitudinal Cross-sectional Longitudinal Cross-sectional Longitudinal

b

seb

df

t

p

.07 −.24 −.05 −.01 .07 −.39 .05 −.73 .18 −.22 −.19 1.48

.14 .18 .14 .17 .21 .27 .36 .50 .20 .25 .79 1.26

134.50 161.64 136.31 152.76 135.43 169.59 136.23 161.89 128.94 165.30 106.47 67.37

.50 − 1.31 −.38 −.03 .33 − 1.44 .14 − 1.46 .91 −.88 −.24 1.18

.617 .193 .706 .973 .740 .152 .893 .147 .364 .378 .812 .244

SPSS17: mixed model regression analysis with unstructured covariance matrix. Model Yj = b0 + b1C1 + b2(Cj − C1) + covariates Yj = symptoms at time j (e.g. PANSS positive symptoms at time j), Cj = cannabis use at tj {j = 0,1,2}, C1 = cannabis use at t0; time dependent covariates more than 14 glasses of alcohol a week at tj and any stimulant use at tj. Time independent covariates age, duration of illness, baseline illness severity, SES, and duration of follow-up.

psychopathology were observed, indicating that our fourth hypothesis was not confirmed.

4. Discussion 4.1. Differences in the course of the illness between cannabis-using and non-using patients The age at onset of the first psychotic episode occurred 2.5 years earlier in cannabis using patients compared to non-cannabis using patients as was hypothesized. This is consistent with almost all other studies currently available (see introduction). In contrast to our second hypothesis, no differences were found in the cross-sectional comparison between cannabis-using patients and non-using patients with respect to psychopathology, quality of life and side-effects of anti-psychotic medication. This was the case both with and without adjustment for important confounders such as age, length of illness period and baseline severity of illness. The use of cannabis, however, was an independent risk factor for relapse in terms of the number of hospitalizations during the 12 months follow-up of this cohort. A clinically relevant and statistically significant difference in the number of days of hospitalization was seen between cannabis using and non-cannabis using patients (difference: 50 days; p b .001), but this difference did not sustain after adjustment for the use of alcohol, illegal drugs and other confounders as was proposed by Zammit (Zammit et al., 2008). Finally our hypothesis with respect to dose-dependency had to be rejected: there was no significant dose–effect relation between (changes in) the amount of cannabis use and (changes in) different indicators of psychopathology (PANSS and MADRS) and quality of life (L-QoL). Division of the group in ‘no users’, ‘low users’ and ‘high users’ led to arbitrary concepts and to small groups with too low statistical power for conclusions. Together these findings are consistent with the data presented in the recent systemic review of (Zammit et al., 2008): a consistent relationship between cannabis use and relapse in terms of the number of hospitalizations, but no consistent relationship between cannabis use and psychopathology (also Brunette et al., 1997). From this combination of findings, the question arises whether the use of cannabis itself or the exacerbation of symptoms associated with cannabis use is the main reason for admission. Our findings, and most other studies, seem to support the first explanation, but the causal mechanism remains unknown.

55

The current study does not corroborate findings of studies reporting less anxiety and depression (Johns, 2001) and other positive outcomes in cannabis using patients with schizophrenia (Peralta and Cuesta, 1992; Test et al., 1989). Finally it was observed that the use of cannabis seemed to continue in the clinical setting, as could be shown with urine samples collected during hospitalization period. 4.2. Possible explanations The fact that this study, like some other studies, found no correlation between cannabis use and psychopathology, even when cannabis use was continued during admission, is surprising. It is even more surprising that cannabis use, despite the lack of an effect on psychopathology, was associated with more frequent hospitalizations. We propose several explanations for this phenomenon. Hospitalization may have had a positive effect on the course of schizophrenia. Increased psychopathology, due to cannabis use, could be masked by symptomatic improvement as a result of hospitalization. Second, it is possible that not the cannabis use in itself, but related factors, such as low treatment compliance and problems in the therapeutic alliance, are responsible for frequent psychotic relapses and hospitalizations. The fact that cannabis is an illegal substance, thus affiliated with a criminal subculture, could easily hamper therapeutic relationship and motivation for treatment. Non-compliance with current treatment modules, focused on abstinence, may create ineffective therapeutic relation-ships as patients argue that they have compelling reasons to use cannabis. However we could not find relevant differences with respect to the quality of the therapeutic relationship as was measured by the PEC subscale of the PANSS. Third, cannabis use may have a negative effect on neurocognitive functions resulting in more frequent relapses. Further research should, therefore, be focused on the reasons for use and the effects of the use of cannabis on neurocognitive variables. 4.3. Limitations and assets of the study Possible reasons for the lack of association between the extent of cannabis use and increased psychopathology are misclassification as a result of measurement errors (e.g. false negatives on cannabis use), selection bias due to loss of follow-up, insufficient adjustment for confounding, lack of power and too much heterogeneity with respect to diagnostic categories within the study cohort (Zammit et al., 2008). However, in the current study, the self-reported cannabis use status was confirmed with urine analysis and all statistical analyses were adjusted for a broad range of potential confounders. Moreover, loss to follow-up was not selective. Finally the generalizability of our Table 3b (Changes in) number of joints per week and (changes in) symptom severity (n = 145).

PANSS positive PANSS negative PANSS general PANSS total MADRS total QoLi (Lancashire)

Cross-sectional Longitudinal Cross-sectional Longitudinal Cross-sectional Longitudinal Cross-sectional Longitudinal Cross-sectional Longitudinal Cross-sectional Longitudinal

b

seb

df

t

p

.03 −.01 −.01 .03 .05 −.04 .07 −.01 .12 −.00 .07 −.04

.03 .04 .03 .03 .05 .05 .08 .10 .05 .05 .05 .09

131.92 155.10 140.91 154.86 133.29 175.81 132.18 158.84 135.42 170.87 125.87 91.38

.97 −.15 −.42 .92 1.00 −.74 .80 −.11 2.66 −.01 1.38 −.39

.333 .884 .679 .358 .320 .463 .427 .913 .009 .992 .169 .696

SPSS17: mixed model regression analysis with unstructured covariance matrix. Model Yj = b0 + b1C1 + b2(Cj-C1) + covariates Yj = symptoms at time j (e.g. PANSS positive symptoms at time j), Cj = cannabis use at tj {j = 0,1,2}, C1 = cannabis use at t0; time dependent covariates more than 14 glasses of alcohol a week at tj and any stimulant use at tj. Time independent covariates age, duration of illness, baseline illness severity, SES, and duration of follow-up.

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D. van Dijk et al. / Schizophrenia Research 137 (2012) 50–57

findings is enhanced by the fact that our cohort is representative for treatment seeking schizophrenic patients seen by mental health services in the Netherlands. The prevalence of cannabis use, demographic characteristics and psychopathology scores are comparable with those reported for other representative samples of schizophrenic patients. The mean severity of psychopathology, according to the PANSS was in the category mild to moderately severe in cannabis users and non-users alike (Kay et al., 1988). No indication for referral-based bias, with respect to severity of the disease or the use of substances, was found. However because no homeless patients were included in the study, the findings cannot be generalized to this specific population. It should also be noted that all analyses were restricted to males, and generalization to female patients with schizophrenia is not justified. A methodological problem that is rarely taken into account in previous studies is the complexity of cannabis as a psychotropic substance. Cannabis is a herbal compound that activates receptors of the endogenous cannabinoid signaling system, that is possibly involved in neuro-protective mechanisms (Marsicano et al., 2003; Witting et al., 2006; Bernard et al., 2005) and mood regulation (Pacher et al., 2006). The only randomized controlled trials that describe cannabis-induced psychotic symptoms were restricted to situations where relatively high doses of Δ-9-THC, were injected in a laboratory setting (D'Souza et al., 2004; D'Souza, 2007; D'Souza et al., 2008) or when cannabis was ingested, orally, in large doses (Negrete, 2003; Johns, 2001; Iversen, 2003). In the naturalistic setting however, most people that use cannabis make cigarettes that contain cannabis and tobacco, in differing compositions and of different strength, which are smoked (joints). Besides Delta-9-Tetra-Hydro-Cannabinol (Δ-9-THC), the component that may have psychotogenic properties, according to most studies (Kuepper et al., 2010), cannabis contains more than 60 other psychoactive substances some of which possibly interfere with or even antagonize each other. Some of these components (e.g. cannabidiol) even possess anxiolytic and antipsychotic properties (Pertwee, 1999; Pacher et al., 2006; Zuardi et al., 2006; Juckel et al., 2007; Morgan and Curran, 2008; Roser et al., 2008a, 2008b). In this cohort, most patients used Dutch cannabis (‘Nederwiet’), which is known to possess high levels of THC in comparison to cannabis from other sources (Pijlman et al., 2005). Future research should attempt to standardize the cannabis used. 5. Conclusion The current prospective study, including reliable measures of cannabis use and a broad range of possible confounders, confirms the findings of previous studies showing that in patients suffering from schizophrenia cannabis use is associated with an earlier age at onset. The actual use of cannabis is also associated with a negative effect on the course of the illness with more frequent relapses and subsequent hospitalization resulting in a substantial increase in the total number of days hospitalized. Therefore, patients with schizophrenia should be informed about the possible effects of cannabis and trained not to use cannabis or to reduce their cannabis use as much as possible. Declaration of interest This study was funded by Psychiatric Hospital Duin en Bosch, Later: General Mental Health Institute ‘Dijk en Duin’. Unrestricted grants were received from: Janssen-Cilag, Eli Lilly and AstraZeneca. General Mental Health Institute ‘Duin en Bosch’, facilitated the study in the catchment area and provided the research team. Role of funding source Funding for this study was provided by unrestricted grants of Janssen Cilag, Eli Lilly, Astra Zeneca (order correlates with the amount that was funded). These Sponsors

did not play a role in the choice of subject, design of the study, analysis of the data or publication procedure. Contributors Daniel van Dijk initiated this study and wrote the first draft of study protocol and article. Maarten W.J. Koeter designed partly the statistical model that was used and supervised the data analysis. Ron Hijman partly created the battery of neuropsychological outcome measures, critically advised the first author and trained the research team. René S. Kahn and Wim van den Brink were involved in all methodological aspects of the study and both were supervising the study. Case finding and data collection were performed by a research team including D.v.D. Conflict of interest The authors have no conflicts of interest to report. Acknowledgments We would like to thank the research subjects and their family for participating in our study. Also we have to thank participating researchers who chased the referring caretakers, the patients and their family and who collected data: A. van Amerongen, S. Berk, C.M. Jonkman, I. de Monchy, S. de Metz, P. de Baay, S. Groot, P. Veltman, J. Verbeek, L. Veld, E. Barkhof, M. Hasty, M. Willemse, A. Ferwerda. J. Camps, secretary. D. Lam, head of the institute during the study-period, facilitated naturalistic research in a non-academic setting.

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