Cannabis use and cognitive functioning in first-episode schizophrenia patients

Schizophrenia Research 124 (2010) 142–151

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Schizophrenia Research j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / s c h r e s

Cannabis use and cognitive functioning in first-episode schizophrenia patients José Manuel Rodríguez-Sánchez a,⁎, Rosa Ayesa-Arriola a, Ignacio Mata a, Teresa Moreno-Calle a, Rocío Perez-Iglesias a, César González-Blanch a, José Antonio Periañez b, José Luis Vazquez-Barquero a,c, Benedicto Crespo-Facorro a,c,⁎ a b c

Department of Psychiatry, CIBERSAM, University Hospital Marqués de Valdecilla, IFIMAV, Santander, Spain Department of Basic Psychology II, Complutense University of Madrid, Spain School of Medicine, University of Cantabria, Santander, Spain

a r t i c l e

i n f o

Article history: Received 5 March 2010 Received in revised form 27 July 2010 Accepted 10 August 2010 Available online 9 September 2010 Keywords: Psychosis Abuse Cognition Premorbid adjustment Cannabis

a b s t r a c t Cannabis is one of the most widely used illicit drugs in the world. In healthy individuals cannabis is associated with cognitive impairments. Research into the effect of cannabis use in schizophrenia has yielded contradictory findings. Our aim has been to explore the correlates of cannabis use in cognitive and psychopathological features, both cross-sectional and longitudinally, in early phases of schizophrenia. 104 patients with a first episode of non-affective psychosis and 37 healthy controls were studied. Patients were classified according to their use of cannabis prior to the onset of the illness (47 users vs. 57 non-users). They were cross-sectionally and longitudinally studied and compared on clinical and cognitive variables and also on their level of premorbid adjustment. Cannabis user patients had better attention and executive functions than non-cannabis user patients at baseline and after 1 year of treatment. Both groups showed similar improvement in their cognitive functioning during the 1-year follow-up period. We also found that users had a better social premorbid adjustment, particularly during the early periods of life. The amount of cannabis consumed and the length of time of consumption did not significantly relate to cognitive performance. The use of cannabis does not seem to be associated with a negative effect on cognition in a representative sample of first-episode schizophrenia patients. Cannabis user patients appear to comprise a subgroup of patients with a better premorbid adjustment and premorbid frontal cognitive functions. © 2010 Elsevier B.V. All rights reserved.

1. Introduction Cannabis is currently one of the most used illicit drugs worldwide (Wadsworth et al., 2006; Cohen et al., 2008). Studies in healthy individuals have established that acute (Solowij,

⁎ Corresponding authors. Hospital Universitario Marqués de Valdecilla, Department of Psychiatry, Planta 2a, Edificio 2 de Noviembre, Avda. Valdecilla s/n, 39008, Santander, Spain. Tel.: + 34 942 202537; fax: + 34 942 203447. E-mail addresses: [email protected] (J.M. Rodríguez-Sánchez), [email protected] (B. Crespo-Facorro). 0920-9964/$ – see front matter © 2010 Elsevier B.V. All rights reserved. doi:10.1016/j.schres.2010.08.017

1998) and chronic (Wadsworth et al., 2006) consumption of cannabis is associated with cognitive impairments (Pope et al., 2001, 2003; Pope and Yurgelun-Todd, 1996; Solowij, 1995; Solowij et al., 2002) and to transient schizophrenia-like positive, negative, and cognitive symptoms (D´Souza et al., 2009). In schizophrenia, cognitive dysfunction is a core feature already present at early stages, which should be considered as a potential endophenotype (Gonzalez-Blanch et al., 2007), still present long after treatment initiation (D'Souza et al., 2005). The relationship of cannabis consumption with these cognitive dysfunctions in schizophrenia is still obscure and research has brought forth contradictory findings. The use of

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cannabis has been related to memory impairments (D'Souza et al., 2005), to a better cognitive performance (JockersScherubl et al., 2007; Joyal et al., 2003), and to a long term sparing of cognitive functions (Stirling et al., 2005) and absence of associations has also been reported (Carey et al., 2003; Pencer and Addington, 2003). As regards clinical features, cannabis use has been associated with more severe positive symptoms (Caspari, 1999; Degenhardt et al., 2007; Grech et al., 2005) and earlier onset of the psychosis (Barnes et al., 2006; Gonzalez-Pinto et al., 2008). On the other hand, negative symptoms and difficulties in social skills have been proposed as risk factors for cannabis abuse (Mueser et al., 1998) and cannabis users have shown poorer clinical and social outcomes (Blanchard et al., 2000; Kavanagh et al., 2002). Consequently, it has been suggested that some patients would rely on cannabis consumption to alleviate their symptoms (D'Souza et al., 2005). Contrarily, cannabis user patients have also been described as having a lesser severity of negative symptoms and better social skills (Arndt et al., 1992; Kirkpatrick et al., 1996) and premorbid adjustment (Arndt et al., 1992; Sevy et al., 2001). Accordingly, Joyal et al. (2003) suggested that cannabis user patients with schizophrenia might comprise a differentiated subgroup of subjects characterized by more positive and less negative symptoms and who would also have better cognitive functioning and the social skills necessary to engage in behaviours related to drug consumption. The aim of the current article was to explore cognitive and psychopathological features, both cross-sectionally and longitudinally, of those first-episode schizophrenia patients that report using cannabis, as opposed to those that do not use this substance. We hypothesized that patients that report using cannabis would show a better cognition and premorbid adjustment and therefore would have to be considered as a specific subgroup of patients.

2. Method 2.1. Study setting and financial support The data for these analyses were taken from patients of a large epidemiological and longitudinal intervention program of first-episode psychosis (PAFIP), carried out at the University Hospital Marques de Valdecilla, Cantabria, Spain. A detailed description of the PAFIP methodology is available in earlier publications (Crespo-Facorro et al., 2007; PelayoTeran et al., 2008). Briefly, the study was conducted at the outpatient clinic and the inpatient unit at the University Hospital Marques de Valdecilla. This hospital serves an epidemiological catchment area population of 555,000 people. A divulgation process within all mental health outpatient units in Cantabria (5 outpatient clinics) and family physicians was thoroughly carried out during 3 months prior to starting the program to enhance referrals. Referrals to the PAFIP come from the inpatient unit and emergency room at the University Hospital Marques de Valdecilla, community mental health services and other community health care workers in the entire region of Cantabria. Thus, we do not think that there were biases in the way patients were referred.

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Consequently, all first episodes of psychosis declared in the region of Cantabria between 2001 and 2005 were referred to PAFIP. The age-corrected incidence rate for the schizophrenia spectrum disorder was of 1.38 per 10,000. The study, designed and directed by B C-F and JL V-B, conformed with international standards for research ethics and was approved by the local institutional review board that strictly adheres to the Charter of Fundamental Rights of the EU (Art. 3), and the Helsinki Declaration in its latest version. Among other requirements, all patients or their families were requested to sign informed consent to participate in the study. 2.2. Subjects From February 2001 to December 2007 all referrals to PAFIP were screened for patients who met the following criteria: 1) age 15–60 years; 2) living in the catchment area; 3) experiencing their first episode of psychosis; 4) no prior treatment with antipsychotic medication or, if previously treated, a total life time of adequate antipsychotic treatment of less than 6 weeks; 5) meeting DSM-IV criteria for schizophrenia, schizophreniform disorder, brief psychotic disorder, or schizoaffective disorder. Patients were excluded for any of the following reasons: 1) meeting DSM-IV criteria for drug dependence (except nicotine dependence). Therefore, consumption of substances (alcohol included) was not an exclusion criterion provided that patients did not meet the criteria for dependence. This also means that none of the patients studied met the criteria for dependence of cannabis (even though they were considered users of the substance), 2) meeting DSM-IV criteria for mental retardation, and 3) having a history of neurological disease or head injury. The diagnoses were confirmed, using the Structured Clinical Interview for DSM-IV (SCID-I) (First et al., 2001), by an independent psychiatrist 6 months on from the initial contact. All subjects were randomly assigned to one of three antipsychotic treatments: haloperidol, olanzapine, and risperidone. The proportion of cannabis users in each treatment group was similar (χ2 = 0.92; p = 0.63). Similarly, the proportion of subjects who received other medications (benzodiazepines, antidepressants, mood stabilizers and anticholinergics) did not differ between cannabis users and non-users patients (all p's N0.49). Our group has recently reported a lack of differential effect of antipsychotic treatments on cognitive functions in first-episode patients (Crespo-Facorro et al., 2009). Of the 174 consecutive patients who met inclusion criteria for program entry, 42 (21.1%) refused to participate in the cognitive protocol. Thus, a sample of 132 patients fulfilled baseline cognitive assessment. No significant differences were found in relevant variables such as age, gender distribution, illness duration, or clinical severity between those subjects who underwent cognitive evaluations and those who declined participation (all p-values N0.05). Of those 132 patients, 24 subjects who did not show up for the 1-year follow-up evaluation and 4 patients with a final diagnosis of schizoaffective disorder were excluded from the present study due to the fact that this diagnosis casts doubts as to its being considered as a schizophrenia spectrum disorder or as an affective disorder. There is actually some evidence to suggest that schizoaffective disorder may have a different

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neurocognitive profile from schizophrenia (Cheniaux et al., 2008). Even so, in order to assess whether excluding the schizoaffective patients would alter the present findings we reanalyzed the data set including them in it. This analysis yielded the same findings as the present analysis. So, a final set of 104 patients (68 schizophrenia, 24 schizophreniform disorder, 8 brief psychotic disorder and 4 psychotic disorder not otherwise specified) who had undergone both baseline and 1-year cognitive evaluations were analysed. No significant differences were found in relevant variables (age, gender distribution, illness duration, or clinical severity) between those patients finally included (N = 104) for whom baseline and follow-up data were available and those (N = 24) finally excluded, for whom only baseline data were available (all p-values N0.05). Therefore we consider the sample finally studied sufficiently representative of the patients referred to PAFIP. For the purposes of this report, patients were grouped according to the presence or absence of cannabis abuse prior to illness (psychosis) onset, as “users” or “non-users”. Classification of subjects as users or non-users was based on the verbal report by the patients taken during clinical interviews by the clinical team. Cannabis use was considered positive if there had been at least weekly use during the year previous to program entry. It was not possible to introduce a classification based on continued cannabis use throughout the first year due to the fact that 1-year consumption data for 15 patients were unavailable. 47 patients were considered cannabis users. They consumed a mean 24.45 (±21.19) joints per week and had started using the substance at a mean age of 16.80 (±3.35) years, with a duration of consumption at program entry of 6.72 (4.50) years. Since certain evidence suggests that cognitive deficits related to cannabis might disappear some time after consumption has ceased (Fried et al., 2005) we also wished to explore the results of those patients that had a sustained consumption during the first year. At 1 year we had consumption data available for only 32 subjects of those classified as cannabis users at illness onset. Of those, 23 had stopped consuming and only 9 continued to consume cannabis (13.89 ± 13.09 joints per week). Cannabis consumption may be associated with a concomitant use of other drugs. 21 patients (44.7% of cannabis users) regularly consumed other drugs (including alcohol, cocaine, hallucinogens amphetamine or heroine) in addition to cannabis in our sample. Finally a sample of healthy controls was also recruited from the local area through advertisements. Volunteers had no current or past history of psychiatric illness, including substance dependence, neurological or general medical disorders, as determined by using an abbreviated version of the Comprehensive Assessment of Symptoms and History (CASH) (Andreasen et al., 1992). All healthy subjects were non-users of substances and signed the informed consent. 2.3. Clinical assessment Specific clinical symptoms of psychosis were assessed by means of the Scale for the Assessment of Positive symptoms (SAPS) (Andreasen, 1984a) and Scale for the Assessment of Negative symptoms (SANS) (Andreasen, 1984b). For purposes

of the current study, baseline (visit one) and 1-year evaluations were considered. The same trained psychiatrist (BC-F) completed all clinical assessments. In order to rate functionality we used the global disability item from the Spanish version of Disability Assessment Schedule (DAS) (Janca et al., 1996). In addition data on the parental socioeducational status were also included (see Table 1).

2.4. Neuropsychological assessment All subjects underwent an extensive neuropsychological battery. Testing was divided into two sessions and took approximately 120 min. A detailed description of the cognitive battery has been reported elsewhere (Gonzalez-Blanch et al., 2007). Patients and controls received three cognitive assessments during the first year: at baseline, 6 months and 1 year after treatment initialization. In the current study only baseline and 1-year assessment were considered. Stabilization of psychotic symptoms and readiness for cognitive evaluation were decided by the clinical team after interviewing the patient and evaluating symptom severity. Cognitive baseline assessment was carried out when the clinical status

Table 1 Sociodemographics and treatment data. Users (N = 47) 23.62 (4.15) Age a Years of education b 9.53 (2.77) c IQ (WAIS III Vocabulary) 8.97 (2.81) d Sex (males) 38 (80.85%) Age of illness onset e 22.95 (4.06) DUP (months) 8.05 (9.85) DUI (months) 23.11 (23.44) Haloperidol 18 Olanzapine 12 Risperidone 17 Anticholinergics 5 Hypnotics 3 Benzodiazepines 17 Psychosocial function 0.49 (DAS) Parental socioeducative status Liberal professionals 2 High qualification work 20 Low qualification work 17 Unqualified 8 N of subjects that use concomitant drugs Amphetamines 3 Cocaine 4 Hallucinogens 2 Alcohol f 18

Non-users (N = 57)

Controls (N = 37)

30.04 (8.47) 11.47 (3.01) 9.95 (2.92) 27 (47.36%) 28.95 (8.08) 13.03 (23.03) 24.13 (30.90) 17 18 22 9 2 18 0.40

25.24 (7.87) 11.81 (2.29) 10.28 (2.24) 18 (48.64%)

4 19 15 19

0 7 5 0

9

Abbreviations: DAS = Disability Assessment Schedule; DUI = duration of untreated illness; DUP = duration of untreated psychosis; IQ = Premorbid IQ. a Users vs. non-users t = − 5.03; p b 0.001. b Users vs. non-users t = −3.39; p = 0.001. Patients vs. controls t = −2.52; p = 0.01. c Users vs. non-users t = − 2.58; p = 0.01. Patients vs. controls t = − 2.05; p = 0.04. d Users vs. non-users χ2 = 12.32; p b 0.001. e Users vs. non-users t = − 4.63; p b 0.001. f Users vs. non-users χ2 = 6.79; p b 0.009.

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of patients so permitted it in order to maximize collaboration, and this occurring at a mean of 10.5 (3.9) weeks after visit one. According to preceeding studies this moment was within the proper time to perform a baseline assessment for neurocognitive studies (Gonzalez-Blanch et al., 2006). A group of cognitive tests representative of the main cognitive domains were chosen as follows: for measuring verbal memory, the Rey Auditory Verbal Learning Test was used (Rey, 1964). Two measures were taken from this test: a learning measure consisting of the sum of the first five trials and a long term recall measure; the Rey Complex Figure test (long term recall) was used for visual memory (Rey, 1941); Motor Speed was measured by means of the Finger Tapping Test (Spreen and Strauss, 1991) using as the dependent variable the mean number of taps in ten seconds for the dominant hand; for motor coordination the Grooved Pegboard (Spreen and Strauss, 1991) was used, using seconds to complete the board with the dominant hand as the dependent variable. The Trail Making Test part B (TMT-B) was used for measuring executive functions (Lezak, 2005; Sanchez-Cubillo et al., 2009; Stuss et al., 2001). Time to complete the sheet was considered as a dependent variable; Backward Digits (WAIS III standard scores) for working memory (Weschler, 1999); Digit Symbol (WAIS III standard scores) for speed of processing (Rodriguez-Sanchez et al., 2007); FAS for verbal fluency (Lezak, 2005) and finally, the Continuous Performance Test (number of correct responses) for measuring attention were used (Gonzalez-Blanch et al., 2007). The WAIS III subtest of Vocabulary was used as a covariate to control the effect of premorbid IQ (Lezak, 2005; Yates, 1954). 2.5. Premorbid functioning assessment The Premorbid Adjustment Scale (PAS) was used to evaluate premorbid functioning (Cannon-Spoor et al., 1982). Four periods of age were considered as dependent variables: childhood (up to age 11), early adolescence (12– 15 years), late adolescence (16–18 years) and adulthood (19 and over). The general scale was not used because previous studies have raised concerns regarding its usefulness with first-episode samples (van Mastrigt and Addington, 2002). Social and academic premorbid adjustment dimensions were obtained (Allen et al., 2001) to study whether these specific aspects of premorbid adjustment were related to cannabis use. Academic and social scores were calculated for each age period and then averaged so that single scores for these two domains were obtained. On all variables obtained from this scale, higher scores indicate worse adjustment. 2.6. Statistical analyses Independent sample t-tests were used to compare patients and controls in age, years of education and premorbid IQ. Chi square tests were utilized to compare sex distribution. Differences in the number of subjects that completed certain tests (see Table 1) did not produce differences in sociodemographical variables, therefore the same sociodemographical variables were covaried in all analyses. A repeated measures analysis of covariance (repeated measures ANCOVA)

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was performed for each cognitive variable, total SAPS and total SANS with group (users vs. non-users) as the between subject factor and time (baseline vs. 1-year assessments) as the within subject factor. Effects of time (longitudinal dimension), group (cross-sectional dimension) and time by group (interaction effect) were examined. All post-hoc comparisons were Bonferroni corrected. In order to control the effect of baseline performance on cognitive and clinical changes a second set of analysis was performed. Both groups were compared by means of univariate ANCOVA in change scores. These change scores were calculated for each cognitive and clinical domain by substracting baseline scores from 1-year scores. In this analysis basal performance (in addition to the other relevant sociodemographic variables) was used as covariate. Multivariate Analysis of Covariance (MANCOVA) was used to study the four periods of age examined by the PAS (Childhood, Early adolescence, Late adolescence and Adulthood) and social and academic domains. Correlations and linear regression models were used to study the association between different continuous variables. The Statistical Package for Social Science (SPSS), version 12.0, was used for statistical analyses. All statistical tests were two-tailed, and significance was determined at the 0.05 level, but in the analysis of correlations. 3. Results Sociodemographic data for patients who consumed (users) and those who did not consume (non-users) are presented in Table 1. Cannabis user patients were younger, had fewer years of education, and a lower premorbid IQ. They had also an earlier age of illness onset than did non-users. Males were also significantly more represented in the group of cannabis users. The patients who used cannabis and other substances (N = 21) were compared with patients who only consumed cannabis (N = 26). The two groups did not differ in clinical, sociodemographic or cognitive variables. Therefore we believe that concomitant use of other substances in our sample was not of enough magnitude to bias the results. 3.1. Cognitive and clinical comparisons Descriptive data regarding the cognitive performance and psychopathology of both groups of patients and controls are provided in Table 2. Results of repeated measures ANCOVA comparing users and non-cannabis users are provided in Table 3. 3.1.1. Between-group effects The two groups of patients differed in TMT-B and CPT scores at baseline and at 1 year; with cannabis users outperforming non-users patients in both cognitive tasks (see Fig. 1). Given that TMT-B was affected by the concomitant consumption of other drugs we reanalysed this variable excluding the 13 patients that consumed other substances besides cannabis. Between-group effects continued between patients that consumed cannabis and patients that did not (F = 7.152; p = 0.009) at both moments (baseline p = 0.01;

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Table 2 Results on cognitive tests and clinical scales. Users RAVLT (Learning) N Baseline 1 year RAVTL (Long Term Recall) N Baseline 1 year Rey Complex Figure N Baseline 1 year Backward Digits N Baseline 1 year Digit Symbol N Baseline 1 year TMT-B a N Baseline 1 year FAS (verbal fluency) N Baseline 1 year CPT N Baseline 1 year Grooved Pegboard a N Baseline 1 year Finger tapping N Baseline 1 year SAPS N Baseline 1 year SANS N Baseline 1 year

Table 3 Repeated measures ANCOVA (cannabis users vs. non-users) without controls.* Non-users

Controls

47 57 37 38.21 (11.59) 43.32 (10.33) 52.46 (8.30) 45.13 (9.72) 48.14 (11.62) 58.97 (8.26) 47 6.60 (3.35) 8.51 (3.44)

57 7.54 (3.49) 9.26 (3.42)

37 10.84 (2.67) 12.24 (2.64)

47 18.74 (7.10) 23.86 (6.74)

55 18.46 (6.98) 23.58 (7.15)

37 24.16 (6.42) 26.31 (6.31)

47 5.51 (1.63) 6.32 (1.87)

56 5.79 (1.92) 6.25 (2.12)

36 7.47 (2.13) 7.67 (2.35)

47 6.40 (2.59) 8.43 (2.98)

55 7.64 (2.95) 9.23 (2.81)

37 10.59 (2.99) 12.37 (2.02)

47 57 37 89.21 (33.94) 99.82 (56.77) 58.03 (16.87) 65.36 (27.46) 79.77 (47.02) 49.62 (11.48) 47 56 37 28.79 (9.41) 31.12 (10.34) 38.76 (10.63) 33.02 (10.26) 33.82 (11.70) 42.92 (10.85) 38 73.63 (8.72) 75.82 (8.20)

45 25 70.73 (12.28) 78.20 (1.61) 71.82 (13.98) 78.84 (1.77)

42 48 36 71.52 (12.55) 72.68 (40.10) 57.97 (8.20) 63.11 (8.42) 67.27 (36.71) 55.15 (7.42) 41 45 21 48.18 (10.63) 45.90 (10.32) 53.26 (8.24) 50.31 (8.69) 47.26 (8.75) 53.83 (7.42)

13.89 (4.23) 1.83 (2.93)

12.11 (4.10) 1.05 (2.26)

7.49 (7.11) 4.70 (5.03)

7.54 (5.90) 5.54 (5.31)

Abbreviations: CPT = Continuous Performance Test; TMT-B = Trail Making Test-B; RAVTL = Rey Auditory Verbal Learning Test; SANS = Scale for the Assessment of Negative symptoms; SAPS = Scale for the Assessment of Positive symptoms. a This score is inverse: The higher the score, the worse the performance.

year p = 0.02); once again, patients that consumed performed better. We therefore consider that inclusion of patients that consume other drugs besides cannabis does not introduce a significant bias in the results. Users also had more positive symptoms at baseline (p = 0.04) although no overall between-group effect was observed (see Table 3). Additionally, a group of healthy controls were also included in the analysis (see Table 4). Healthy controls outperformed patients in all cognitive tests except for Finger Tapping and Grooved Pegboard. It is of note that in TMT-B and

RAVLT (Learning) RAVLT (LTM) RCF Backward Digits Digit Symbol TMT-B FAS CPT Grooved Pegboard Finger Tapping SAPS SANS

Within-group

Betweengroup

Group × time

F

P

F

P

F

P

43.89 47.26 78.39 14.25 76.65 47.02 16.38 4.33 49.78 5.53 564.58 9.64

b0.001 b0.001 b0.001 b0.001 a b0.001 b0.001 b0.001 0.04 c b0.001 0.021 e b0.001 0.002

0.02 0.002 0.11 1.46 0.53 7.10 1.55 4.82 1.45 0.64 3.46 2.71

0.89 0.97 0.74 0.23 0.47 0.01 b 0.22 0.03 d 0.23 0.43 0.07 f 0.10

2.02 b0.001 1.80 1.60 0.51 0.01 0.15 0.19 0.02 0.16 2.90 0.03

0.16 0.99 0.18 0.21 0.48 0.93 0.70 0.67 0.89 0.69 0.09 0.87

* Covariates were sex, age, years of study and IQ. Abbreviations: CPT = Continuous Performance Test; LTR = Long Term Recall; TMT-B = Trail Making Test-B; RAVTL = Rey Auditory Verbal Learning Test; RCF = Rey Complex Figure; SANS = Scale for the Assessment of Negative symptoms; SAPS = Scale for the Assessment of Positive symptoms. a Only users improve (F = 10.70; p = 0.001). b Users outperform non-users at both moments (baseline p = 0.03; year p = 0.007). c Considered separately, no group improves significantly (p ≥ 0.12). d Users outperform non-users at both moments (baseline p = 0.05; year p = 0.04). e Considered separately, no group improves significantly (p's ≥ 0.08). f Users have more positive symptoms only at baseline (F = 4.35; p = 0.04).

CPT healthy controls outperformed only non-user patients at the two time points (p's ≤ 0.002 and p's ≤ 0.03, respectively). No differences between non-users and users were found in these tasks. In addition, healthy controls outperformed only non-users at the basal assessment on the Grooved Pegboard (p = 0.04). 3.1.2. Within-group effects Both groups of patients showed a marked increase in score during the first year of treatment in all cognitive tasks (see Table 3). It is of note that post-hoc analyses showed that the increase in Backward Digits corresponded only to the group of users. Although the group of subjects as a whole showed a score increase in Finger Tapping and CPT, when cannabis users and non-cannabis users were considered separately no significant difference was observed. Regarding clinical symptomatology, both groups of patients also showed a significant reduction in the severity of positive and negative symptoms. The inclusion of controls in the analysis revealed that healthy subjects at 1 year improved in all cognitive scores except for Backward Digits, TMT-B, Grooved Pegboard, and Finger tapping (see Table 4). 3.1.3. Group-by-time effects The group-by-time effects of the repeated ANCOVA's (Table 3) and the direct comparison of cognitive changes (baseline minus 1-year scores) between groups (data available on request) revealed that cannabis and non-cannabis users did not differ in the degree of cognitive changes over time.

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Table 5 Comparison of both groups of patients on the age periods and specific domains of Premorbid Adjustment Scale (PAS).

Childhood Early adolescence Late adolescence Adulthood Social domain Academic domain

Users

Non-Users

F

p

5.03 7.49 9.79 3.67 0.75 2.91

6.33 8.09 8.64 4.29 1.14 2.46

8.37 6.26 1.38 4.66 11.44 0.25

0.005* 0.015* 0.244 0.034* 0.001* 0.62

(2.70) (3.14) (3.90) (3.93) (0.71) (0.86)

(3.48) (3.53) (4.25) (3.91) (0.88) (1.00)

Scores on the PAS are inverted: higher scores mean worse adjustment.

formed better) did not (p = 0.06), probably due to a ceiling effect in their performance. Therefore the group-by-time effect was significant (F = 6.12; p = 0.003). However, there were no differences between the two groups of patients. 3.2. Premorbid adjustment MANCOVA of the four periods of age of the PAS was significant (F = 3.05; p = 0.02). Post-hoc analysis showed that cannabis users had a better premorbid adjustment during childhood and early adolescence (see Table 5). As regards social and academic domains of the premorbid adjustment, MANCOVA showed a multivariate effect (F = 5.96; p = 0.004). Users had better adjustment in the social domain (F = 11.44; p = 0.001) but groups did not differ in the academic domain (F = 0.25; p = 0.62).

Fig. 1. Shows performance on TMT-B and CPT of both groups of patients (mean ± s.e. of the mean). Axis Y represents respectively seconds taken to perform the test and number of correct responses. The lower number of seconds in the TMT-B indicates better performance.

When controls were included in the analysis, only the performance on the Rey Complex Figure Test showed a significant difference between groups (see Table 4). This effect was caused by both groups of patients improving significantly over the first year, whereas controls (although they per-

Table 4 Repeated measures ANCOVA including healthy controls.*

RAVTL (Learning) RAVTL (LTM) RFC Backward Digits Digit Symbol TMT-B FAS CPT Grooved Pegboard Finger Tapping

Within-group

Between-group

Group × time

F

P

F

P

F

P

67.29 52.76 76.65 9.85 87.95 50.60 25.57 4.06 47.56 4.04

b 0.001 b 0.001 b 0.001 0.002 b 0.001 b 0.001 b 0.001 0.046 b 0.001 0.04

16.19 13.60 3.38 7.16 16.44 9.69 10.78 5.50 2.69 2.98

b0.001 b0.001 0.037 0.001 b0.001 b0.001 b0.001 0.005 0.07 0.056

1.13 0.78 6.12 1.21 1.81 2.27 0.19 0.74 4.16 0.32

0.33 0.46 0.003 0.30 0.17 0.11 0.83 0.48 0.02 0.73

* Covariates were sex, age, years of study and IQ. Abbreviations: CPT = Continuous Performance Test; LTR = Long Term Recall; TMT-B = Trail Making Test-B; RAVTL = Rey Auditory Verbal Learning Test; RCF = Rey Complex Figure.

3.3. Correlations and regression The amount of cannabis consumed, measured as the mean number of cannabis joints smoked per week during the year before baseline evaluation, correlated significantly with the years of education (r= −0.29; p = 0.003), the age of illness onset (r = − 0.335;p = 0.005), age (r = − 0.34; p b 0.001), premorbid IQ (r = −0.22; p = 0.02), baseline verbal fluency (r= −0.23; p = 0.02) and social domain of premorbid adjustment (−0.249; p = 0.01). Males smoked a significantly greater average number of cannabis joints per week (14.8 ± 20.3) than females (4.8± 13.8) (t= 2.98; p = 0.004). A linear regression model (enter method) with cannabis joints per week as the dependent variable and years of education, age of illness onset, sex, IQ, social domain of the PAS and verbal fluency as predictors was performed. Due to the fact that age and age of illness onset had a very strong positive correlation (r = 0.98) only the age of illness onset was introduced in the model. The model was significant (F = 4.94; p b 0.001) and explained 18.8% of the variance of the dependent variable. Interestingly, only the social domain of the PAS maintained a significant association with the dependent variable (β = − 0.25; t = − 2.76; p = 0.007): better social premorbid adjustment was related to a greater consumption of cannabis joints. The duration of consumption (defined as age of illness onset minus age of consumption onset) (mean 5.98 ± 4.21 years) was correlated to baseline SAPS (r = −0.29; r = 0.04). Due to the fact that there was no correlation with any cognitive variable, no further regression analyses were performed.

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4. Discussion Our research has shown that cannabis user schizophrenia patients have better attention and executive functions than non-user patients at baseline and after 1 year of treatment. Overall, both groups of patients showed a similar increase in their performance on cognitive tasks during the 1-year follow-up period. We also found that cannabis users had a better social premorbid adjustment, particularly during the early periods of life. The amount of cannabis consumed and the length of time of consumption did not significantly influence cognitive performance. Cognitive test scores increased during the follow-up periods in both groups of patients as well as controls. Previous research has found that improvements in cognitive tasks within the first year are similar in schizophrenia patients and healthy controls and can be attributable to learning effect due to repeated exposure to the tasks (Rodriguez-Sanchez et al., 2008). In addition, as already stated by previous reports with this sample, healthy controls showed a better cognitive functioning than patients in most of the cognitive variables, (Gonzalez-Blanch et al., 2007). Previous research into the role of cannabis on cognitive function in schizophrenia has already reported either a lack of association (Carey et al., 2003; Cleghorn et al., 1991; Pencer and Addington, 2003) or a better cognitive performance in patients who used cannabis. Jockers-Scherubl et al. (2007) found that cannabis users performed better on the Digit Symbol Test. Similarly, Stirling et al. (2005) reported that cannabis user patients had better cognitive functioning ten years after illness onset. In chronic (DeRosse et al., 2010) and early onset patients (de la Serna et al., 2010) the use of cannabis has also been related to a better performance in cognitive tasks known to be sensitive to frontal functioning. Similarly, our data here have revealed that cannabis user firstepisode patients performed better than non-users in the TMT-B, a task related to frontal lobe function (Stuss et al., 1998, 2001). It is of note that in a recent meta-analysis schizophrenic patients who consumed cannabis had revealed a better performance in the Trail Making Test (Potvin et al., 2008). Given that cannabis use in the non-schizophrenic population has been repeatedly related to those cognitive dysfunctions (Pope et al., 2001, 2003; Solowij et al., 2002) similar to those already present in schizophrenia (Solowij and Michie, 2007) the findings of our investigation might be somewhat counterintuitive. Different hypotheses could be taken into account to explain our results. First, it has been proposed that in schizophrenia, cannabis consumption would be a form of naïve pharmacotherapy due to its likely beneficial effects on cognitive or clinical variables (D'Souza et al., 2005; Dixon et al., 1991; Schneier and Siris, 1987; Test et al., 1989). In fact, a large number of investigations have stated that one of the major products of the marijuana plant, namely, cannabidiol might have, in contrast to delta-9-tetrahydrocannabinol, an antipsychotic effect, similar to that of atypical neuroleptics (Zuardi et al., 2006a,b). What is more, neuroimaging studies have shown that effects of cannabidiol in the brain are the opposite to those of delta-9-tetrahydrocannabinol (Bhattacharyya et al., 2010).

Additionally, the severity of negative symptoms has also been described as a risk factor for substance abuse in schizophrenia (Mueser et al., 1998). Thus, patients suffering from greater negative symptoms would start using cannabis to alleviate at least in part this symptomatology. Although the design of our study does not permit this question to be properly addressed, it might be expected that if cannabis alleviated the severity of negative symptoms, then this severity might increase once cannabis was no longer consumed. Contrary to this hypothesis, our results have shown (data not shown but available under request) that the subgroup of cannabis user patients who stopped using cannabis during the first year did not clinically differ either from those patients who continued using cannabis or from those who had never used cannabis. This lack of significant differences in negative symptoms occurred not only at baseline but also at 1-year assessment when the hypothetical beneficial effects of cannabis would be reversed after the consumption had ceased. What is more, patients who had given up the use of cannabis had fewer negative symptoms at 1-year assessment than any other group (3.44 ± 5.10 cannabis user patients who stopped using; 5.53 ± 5.32 cannabis non-user patients and 6.33 ± 6.06 cannabis user patients who kept using it). Regarding positive symptoms, the cannabis users had more severe positive symptoms at illness onset. Therefore, we might conclude that cannabis use does not seem to play a significant role in reducing symptomatology in first-episode psychotic patients. Previous investigations have already claimed against this hypothesis because of lack of sufficient support (Chambers et al., 2001) or because cannabis use generally starts before the onset of the illness, and not after (Løberg and Hugdahl, 2009). A second alternative hypothesis relies on the effect of cannabis on dopaminergic neurotransmission. It has been stated that acute administration of cannabinoid agonists might increase the frontal dopamine activity (Jentsch et al., 1997; Verrico et al., 2003). This means that if cannabis was used sporadically or in low doses it might improve frontal lobe related cognitive functioning (Cohen et al., 2008). In contrast, a repeated or chronic exposure to the substance might cause an adaptive reduction of dopamine release on the prefrontal cortex (Cohen et al., 2008; Jentsch et al., 1998; Verrico et al., 2003) and therefore a subsequent impairment in cognitive performance. If this hypothesis proves to be true it might be expected that a greater exposure to cannabis (lengthy duration and greater amount of cannabis consumption) might be associated with a lesser performance in cognition. In non-schizophrenic subjects an earlier age of cannabis use onset and a lengthy time of consumption have been related to a worse cognitive performance (Ehrenreich et al., 1999; Pope et al., 2003). However, we did not find any significant relationship between the amount of cannabis consumed and the duration of usage with any cognitive variable. As expected, according to previous studies (Andreasson et al., 1989; Arseneault et al., 2004; Henquet et al., 2005; Veen et al., 2004; Zammit et al., 2002) we observed that a greater exposure to cannabis was significantly related to an earlier age at the onset of the illness, and to a better social premorbid adjustment. Taken together, these results

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seem to indicate that the effects of cannabis on dopaminergic neurotransmission might not fully and uniquely explain our cognitive findings. We are also aware that our patients have been exposed to cannabis for a somewhat short time, which might not be a sufficient length of time to produce cognitive deleterious effects. Lastly, a third hypothesis might be considered to explain our results here. Some authors have stated that those schizophrenia patients who use illicit drugs might comprise a subgroup of patients with better social and planning abilities needed to engage in drug usage behaviours (Joyal et al., 2003). In accordance with this hypothesis we have found that cannabis user patients have a better performance on executive functions and attention tasks. It is of note that both cognitive functions are highly relevant to achieving a satisfactory adaptation to life's demands and have been related to general functioning and outcome in schizophrenia (Green, 1996). Accordingly, in our sample cannabis user patients showed a better social premorbid adjustment, particularly during childhood and early adolescence. The finding of better premorbid adjustment and better social skills in schizophrenia patients who use cannabis has been already reported (Arndt et al., 1992; Sevy et al., 2001) and some authors have suggested the better social adjustment to relate to a predominance of positive symptoms (Margolese et al., 2004). Similarly, in our study the post-hoc analyses revealed that cannabis users had significantly more positive symptoms at baseline. Therefore we suggest that the higher the presence of positive symptoms at baseline, the better the premorbid adjustment and the higher the performance on frontal related cognitive functions may represent a coherent picture of cannabis users as a specific subgroup of schizophrenia patients. Several limitations must be taken into account in the current investigation. First, most of the cannabis user patients at intake were abstinent at the time of the follow-up assessment (only 9 continued to use cannabis). This was due at least in part to the fact that as part of our clinical trial individual and group interventions were carried out during the follow-up period with the goal of reducing or stopping cannabis use among patients. Thus, the potential effects of cannabis might have vanished (Fried et al., 2005) and this might have introduced a bias in our results. To cope with this limitation subsequent analyses were performed upon those subjects for whom consumption data at one year were available (data not shown, available on request). Results of these complimentary analyses showed similar results to those obtained with the complete sample: no group-bytime effect was found and a group effect was seen in the TMTB (F = 5.44; P = 0.006) that was significant at both time points (p's ≤ 0.02). Interestingly, those patients who had given up cannabis obtained the best scores, with those that had never consumed performing worst and those that continued consuming performing between the other two groups. On the other hand, those that continued consuming had the best premorbid adjustment (F = 2.05; p = 0.046), which was particularly evident in the childhood period (F = 4.50; P = 0.015). These additional analyses showed a similar pattern of results to those we observed when the complete sample was analysed and therefore provided further support to our conclusions.

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A second limitation was the difficulty in providing an exact measurement of the exposure to cannabis by the subjects. The lack of control over the concentration of active components of the cannabis together with the difficulty in quantifying precisely the amount of substance used each time makes it impossible for cannabis exposure to be accurately assessed. Consequently, we tried to overcome this limitation by assessing the number of joints smoked each week, assuming that the amount of active components in each joint would be roughly similar. It can be argued that it cannot be ascertained if patients were telling the truth regarding their consumption. However, it has been stated somewhere else that information and self-reports given by subjects tend to be relatively accurate (Harrison et al., 1993; JockersScherubl et al., 2007; Pope et al., 2001). On many occasions self-reports are the only available way to ascertain if consumption has occurred, and this is especially so when large samples are studied. Nevertheless, self-reports are still able to provide quite interesting knowledge on this topic. It also has to be noted that patients enrolled in our clinical program were closely followed during three years and thorough clinical and behavioural information was gathered from patients and near relatives. So, we feel confident about the utility of self report measurement of substance use in our sample. A third limitation to be mentioned is the fact that all control subjects were non-cannabis users. A sample of healthy cannabis users would have offered us the chance to interpret our results better. However, we have to keep in mind that the main goal of this paper was not to study the effects of cannabis in schizophrenia, but rather to point out the cognitive features of those schizophrenia subjects who use cannabis. In conclusion, first-episode schizophrenia patients that use cannabis do not seem to show a worst cognitive performance with respect to patients that do not use the substance. On the contrary, they apparently perform better in certain cognitive functions. Cannabis user patients appear to comprise a subgroup of patients with a better premorbid adjustment and baseline frontal cognitive functions. Role of funding source The present study was performed under the following grant support: Instituto de Salud Carlos III PI020499, PI050427, and PI060507, Plan Nacional de Drogas Research Grant 2005-Orden sco/3246/2004, SENY Fundació Research Grant CI 2005-0308007 and Fundación Marqués de Valdecilla API07/011. These institutions had no other role in the study design, the data collection, data analysis, interpretation of the data, writing or decision to submit the paper.

Contributors All authors have contributed significantly to the current paper. All authors have approved to submit the paper.

Conflict of interest Prof. Vazquez-Barquero and Prof. Crespo-Facorro have received unrestricted research funding from AstraZeneca, Pfizer, Bristol-Myers Squibb, and Johnson & Johnson, which has been deposited into research accounts at the University of Cantabria. Prof. Vazquez-Barquero has received honoraria for his participation as a speaker at educational events from Johnson & Johnson. Prof. Crespo-Facorro has received honoraria for his participation as a speaker at educational events from Pfizer, Bristol-Myers Squibb, and Johnson & Johnson and consultant fees from Pfizer.

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Dr. Mata has received honoraria for his participation as a speaker at educational events from Johnson & Johnson. Dr. Perez-Iglesias has received honoraria for his participation as a speaker at educational events from Bristol-Myers Squibb-Otsuka. The remaining authors report no competing interests.

Acknowledgements The present study was performed at the Hospital Marqués de Valdecilla, University of Cantabria, Santander, Spain, under the following grant support: Instituto de Salud Carlos III PI020499, PI050427, and PI060507, Plan Nacional de Drogas Research Grant 2005-Orden sco/3246/2004, SENY Fundació Research Grant CI 2005-0308007 and Fundación Marqués de Valdecilla API07/011. No pharmaceutical company supplied any financial support towards it. The study, designed and directed by B C-F and JL V-B, conformed with international standards for research ethics and was approved by the local institutional review board. We wish to thank the PAFIP researchers who helped with data collection and specially acknowledge Obdulia Martinez, and Mrs. Gema Pardo for data collection. In addition, we acknowledge the participants and their families for enrolling in this study.

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