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  • 1.
    Bejerot, Susanne
    et al.
    Örebro University, School of Medical Sciences. Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.
    Nilsonne, Gustav
    Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden; Stress Research Institute, Stockholm University, Stockholm, Sweden.
    Humble, Mats B.
    Örebro University, School of Medical Sciences. University Health Care Research Centre, Region Örebro County, Örebro, Sweden.
    Subcortical brain volume differences in participants with attention deficit hyperactivity disorder in children and adults2017In: Lancet psychiatry, ISSN 2215-0374, E-ISSN 2215-0366, Vol. 4, no 6, p. 437-437Article in journal (Refereed)
  • 2.
    Chang, Zheng
    et al.
    Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, UK; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
    Larsson, Henrik
    Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
    Lichtenstein, Paul
    Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
    Fazel, Seena
    Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, UK.
    Psychiatric disorders and violent reoffending: a national cohort study of convicted prisoners in Sweden2015In: Lancet psychiatry, ISSN 2215-0374, E-ISSN 2215-0366, Vol. 2, no 10, p. 891-900Article in journal (Refereed)
    Abstract [en]

    Background Reoffending and presence of psychiatric disorders are common in prisoners worldwide. However, whether psychiatric disorders are risk factors for reoffending is still unknown. We aimed to examine the association between psychiatric disorders, including substance use disorder, and violent reoffending.

    Methods: We did a longitudinal cohort study of 47,326 prisoners who were imprisoned since Jan 1, 2000, and released before Dec 31, 2009, in Sweden. We obtained data for diagnosed psychiatric disorders from both inpatient and outpatient registers, and sociodemographic and criminological factors from other population-based registers. We calculated hazard ratios (HRs) for violent reoffending with Cox regression. To control for potential familial confounding, we compared sibling prisoners with and without psychiatric disorders. We calculated population attributable fraction to assess the population effect.

    Findings: Diagnosed psychiatric disorders were associated with an increased hazard of violent reoffending in male (adjusted HR 1·63 [95% CI 1·57-1·70]) and female (2·02 [1·54-2·63]) prisoners, and these associations were independent of measured sociodemographic and criminological factors, and, in men, remained substantial after adjustment for unmeasured familial factors (2·01 [1·66-2·43]). However, findings differed between individual diagnoses and sex. We found some evidence of stronger effects on violent reoffending of alcohol and drug use disorders and bipolar disorder than of other psychiatric disorders. Alcohol use disorder seemed to have a greater effect in women than in men (women 2·08 [1·66-2·60]; men 1·63 [1·56-1·71]). The overall effects of psychiatric disorders did not differ with severity of crime. The hazard of violent reoffending increased in a stepwise way with the number of diagnosed psychiatric disorders. Assuming causality, up to 20% (95% CI 19-22) of violent reoffending in men and 40% (27-52) in women was attributable to the diagnosed psychiatric disorders that we investigated.

    Interpretation Certain psychiatric disorders are associated with a substantially increased hazard of violent reoffending. Because these disorders are prevalent and mostly treatable, improvements to prison mental health services could counteract the cycle of reoffending and improve both public health and safety. National violence prevention strategies should consider the role of prison health.

    Funding: Wellcome Trust, Swedish Research Council, and Swedish Research Council for Health, Working Life and Welfare.

  • 3.
    Chang, Zheng
    et al.
    Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, United Kingdom; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
    Lichtenstein, Paul
    Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
    Larsson, Henrik
    Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
    Fazel, Seena
    Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, United Kingdom.
    Substance use disorders, psychiatric disorders, and mortality after release from prison: a nationwide longitudinal cohort study2015In: Lancet psychiatry, ISSN 2215-0374, E-ISSN 2215-0366, Vol. 2, no 5, p. 422-430Article in journal (Refereed)
    Abstract [en]

    BACKGROUND: High mortality rates have been reported in people released from prison compared with the general population. However, few studies have investigated potential risk factors associated with these high rates, especially psychiatric determinants. We aimed to investigate the association between psychiatric disorders and mortality in people released from prison in Sweden.

    METHODS: We studied all people who were imprisoned since Jan 1, 2000, and released before Dec 31, 2009, in Sweden for risks of all-cause and external-cause (accidents, suicide, homicide) mortality after prison release. We obtained data for substance use disorders and other psychiatric disorders, and criminological and sociodemographic factors from population-based registers. We calculated hazard ratios (HRs) by Cox regression, and then used them to calculate population attributable fractions for post-release mortality. To control for potential familial confounding, we compared individuals in the study with siblings who were also released from prison, but without psychiatric disorders. We tested whether any independent risk factors improved the prediction of mortality beyond age, sex, and criminal history.

    FINDINGS: We identified 47,326 individuals who were imprisoned. During a median follow-up time of 5·1 years (IQR 2·6-7·5), we recorded 2874 (6%) deaths after release from prison. The overall all-cause mortality rate was 1205 deaths per 100,000 person-years. Substance use disorders significantly increased the rate of all-cause mortality (alcohol use: adjusted HR 1·62, 95% CI 1·48-1·77; drug use: 1·67, 1·53-1·83), and the association was independent of sociodemographic, criminological, and familial factors. We identified no strong evidence that other psychiatric disorders increased mortality after we controlled for potential confounders. In people released from prison, 925 (34%) of all-cause deaths in men and 85 (50%) in women were potentially attributable to substance use disorders. Substance use disorders were also an independent determinant of external-cause mortality, with population attributable fraction estimates at 42% in men and 70% in women. Substance use disorders significantly improved the prediction of external-cause mortality, in addition to sociodemographic and criminological factors.

    INTERPRETATION: Interventions to address substance use disorders could substantially decrease the burden of excess mortality in people released from prison, but might need to be provided beyond the immediate period after release.

  • 4.
    Cortese, Samuele
    et al.
    Center for Innovation in Mental Health, Academic Unit of Psychology, and Clinical and Experimental Sciences (CNS and Psychiatry), Faculty of Medicine, University of Southampton, Southampton, UK; Solent NHS Trust, Southampton, UK; New York University Child Study Center, New York NY, USA; Division of Psychiatry and Applied Psychology, School of Medicine, University of Nottingham, Nottingham, UK.
    Sun, Shihua
    Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
    Zhang, Junhua
    School of Education, Jiangsu Key Laboratory for Big Data of Psychology and Cognitive Science, Yancheng Teachers University, Yancheng, China.
    Sharma, Esha
    Psychiatric Epidemiology, Department of Public Health, Brown School, Washington University in St Louis, St Louis MO, USA.
    Chang, Zheng
    Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
    Kuja-Halkola, Ralf
    Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
    Almqvist, Catarina
    Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden; Pediatric Allergy and Pulmonology Unit at Astrid Lindgren Children's Hospital, Karolinska University Hospital, Stockholm, Sweden.
    Larsson, Henrik
    Örebro University, School of Medical Sciences. Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
    Faraone, Stephen V.
    State University of New York Upstate Medical University, Syracuse NY, USA.
    Association between attention deficit hyperactivity disorder and asthma: a systematic review and meta-analysis and a Swedish population-based study2018In: Lancet psychiatry, ISSN 2215-0374, E-ISSN 2215-0366, Vol. 5, no 9, p. 717-726Article, review/survey (Refereed)
    Abstract [en]

    Background: Several studies have assessed the possible association between attention deficit hyperactivity disorder (ADHD) and asthma. However, existing evidence is inconclusive as to whether this association remains after controlling for possible important confounders. To fill this knowledge gap, we did a systematic review and meta-analysis, followed by a population-based study.

    Methods: For the systematic review and meta-analysis, we searched PubMed, PsycINFO, Embase, Embase Classic, Ovid MEDLINE, and Web of Knowledge databases up to Oct 31, 2017, for observational studies allowing estimation of the association between asthma and ADHD. No restrictions to date, language, or article type were applied. Unpublished data were collected from authors of the identified studies. We extracted unadjusted and adjusted odds ratios (ORs) from the identified studies and calculated ORs when they were not reported. We assessed study quality using the Newcastle-Ottawa Scale and study heterogeneity using I (2) statistics. A random-effects model was used to calculate pooled ORs. The systematic review is registered with PROSPERO (CRD42017073368). To address the fact that the ORs obtained in the meta-analysis were adjusted for confounders that inevitably varied across studies, we did a population-based study of individuals in multiple national registers in Sweden. We calculated an unadjusted OR and an OR that was simultaneously adjusted for all confounders identified in a directed acyclic graph based on the studies of asthma and ADHD identified in our systematic review.

    Findings: We identified 2649 potentially eligible citations, from which we obtained 49 datasets including a total of 210 363 participants with ADHD and 3 115 168 without. The pooled unadjusted OR was 1.66 (95% CI 1.22-2.26; I-2 = 99.47) and the pooled adjusted OR was 1.53 (1.41-1.65; I-2 = 50.76), indicating a significant association between asthma and ADHD. Possible lack of representativeness of the study population was detected with the Newcastle-Ottawa Scale in 42 of 49 datasets. In the population-based study, we included 1 575 377 individuals born between Jan 1, 1992, and Dec 31, 2006, of whom 259 253 (16.5%) had asthma and 57 957 (3.7%) had ADHD. Asthma was significantly associated with ADHD (OR 1.60, 95% CI 1.57-1.63) in the crude model adjusting for sex and year of birth, and this association remained significant after simultaneous adjustment for all covariates (1.45, 1.41-10.48).

    Interpretation: The combined results of the meta-analysis and the population-based study support a significant association between asthma and ADHD, which remained even after simultaneously controlling for several possible confounders in the population-based study. Awareness of this association might help to reduce delay in the diagnosis of both ADHD and asthma.

  • 5.
    Cortese, Samuele
    et al.
    Centre for Innovation in Mental Health, Academic Unit of Psychology, University of Southampton, Southampton, UK; Clinical and Experimental Sciences (Central Nervous System and Psychiatry), Faculty of Medicine, University of Southampton, Southampton SO171BJ, UK; Solent NHS Trust, Southampton, UK; New York University Child Study Center, New York, NY, USA; Division of Psychiatry and Applied Psychology, School of Medicine, University of Nottingham, Nottingham, UK.
    Sun, Shihua
    Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
    Zhang, Junhua
    School of Education, Jiangsu Key Laboratory for Big Data of Psychology and Cognitive Science, Yancheng Teachers University, Yancheng, China.
    Sharma, Esha
    Psychiatric Epidemiology, Department of Public Health, Brown School, Washington University in St Louis, St Louis, MO, USA.
    Chang, Zheng
    Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
    Kuja-Halkola, Ralf
    Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
    Almqvist, Catarina
    Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden; Paediatric Allergy and Pulmonology Unit at Astrid Lindgren Children's Hospital, Karolinska University Hospital, Stockholm, Sweden.
    Larsson, Henrik
    Örebro University, School of Medical Sciences. Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
    Faraone, Stephen V.
    SUNY Upstate Medical University, Syracuse, NY, USA.
    Need for further analysis to explore the association between ADHD and asthma: Authors' reply2018In: Lancet psychiatry, ISSN 2215-0374, E-ISSN 2215-0366, Vol. 5, no 12, p. 963-964Article in journal (Refereed)
  • 6.
    Fazel, Seena
    et al.
    Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, United Kingdom.
    Chang, Zheng
    Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, United Kingdom; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
    Fanshawe, Thomas
    Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom.
    Långström, Niklas
    Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden; Research and Evaluation Department, Swedish Prison and Probation Administration, Norrköping, Sweden.
    Lichtenstein, Paul
    Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
    Larsson, Henrik
    Örebro University, School of Medical Sciences. Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
    Mallett, Susan
    School of Population and Health Sciences, University of Birmingham, Birmingham, United Kingdom.
    Prediction of violent reoffending on release from prison: derivation and external validation of a scalable tool2016In: Lancet psychiatry, ISSN 2215-0374, E-ISSN 2215-0366, Vol. 3, no 6, p. 535-543Article in journal (Refereed)
    Abstract [en]

    Background: More than 30 million people are released from prison worldwide every year, who include a group at high risk of perpetrating interpersonal violence. Because there is considerable inconsistency and inefficiency in identifying those who would benefit from interventions to reduce this risk, we developed and validated a clinical prediction rule to determine the risk of violent off ending in released prisoners.

    Methods: We did a cohort study of a population of released prisoners in Sweden. Through linkage of population-based registers, we developed predictive models for violent reoffending for the cohort. First, we developed a derivation model to determine the strength of prespecified, routinely obtained criminal history, sociodemographic, and clinical risk factors using multivariable Cox proportional hazard regression, and then tested them in an external validation. We measured discrimination and calibration for prediction of our primary outcome of violent reoffending at 1 and 2 years using cutoffs of 10% for 1-year risk and 20% for 2-year risk.

    Findings: We identified a cohort of 47 326 prisoners released in Sweden between 2001 and 2009, with 11 263 incidents of violent reoffending during this period. We developed a 14-item derivation model to predict violent reoffending and tested it in an external validation (assigning 37 100 individuals to the derivation sample and 10 226 to the validation sample). The model showed good measures of discrimination (Harrell's c-index 0.74) and calibration. For risk of violent reoffending at 1 year, sensitivity was 76% (95% CI 73-79) and specificity was 61% (95% CI 60-62). Positive and negative predictive values were 21% (95% CI 19-22) and 95% (95% CI 94-96), respectively. At 2 years, sensitivity was 67% (95% CI 64-69) and specificity was 70% (95% CI 69-72). Positive and negative predictive values were 37% (95% CI 35-39) and 89% (95% CI 88-90), respectively. Of individuals with a predicted risk of violent reoffending of 50% or more, 88% had drug and alcohol use disorders. We used the model to generate a simple, web-based, risk calculator (OxRec) that is free to use.

    Interpretation: We have developed a prediction model in a Swedish prison population that can assist with decision making on release by identifying those who are at low risk of future violent off ending, and those at high risk of violent reoffending who might benefit from drug and alcohol treatment. Further assessments in other populations and countries are needed.

  • 7.
    Fazel, Seena
    et al.
    Department of Psychiatry, University of Oxford, Oxford, United Kingdom.
    Wolf, Achim
    Department of Psychiatry, University of Oxford, Oxford, United Kingdom.
    Chang, Zheng
    Department of Psychiatry, University of Oxford, Oxford, UK.
    Larsson, Henrik
    Department of Psychiatry, University of Oxford, Oxford, United Kingdom.
    Goodwin, Guy M.
    Department of Psychiatry, University of Oxford, Oxford, United Kingdom.
    Lichtenstein, Paul
    Department of Psychiatry, University of Oxford, Oxford, United Kingdom.
    Depression and violence: a Swedish population study2015In: Lancet psychiatry, ISSN 2215-0374, E-ISSN 2215-0366, Vol. 2, no 3, p. 224-232Article in journal (Refereed)
    Abstract [en]

    Background: Depression increases the risk of a range of adverse outcomes including suicide, premature mortality, and self-harm, but associations with violent crime remain uncertain. We aimed to determine the risks of violent crime in patients with depression and to investigate the association between depressive symptoms and violent crime in a cohort of twins.

    Methods: We conducted two studies. The first was a total population study in Sweden of patients with outpatient diagnoses of depressive disorders (n=47,158) between 2001 and 2009 and no lifetime inpatient episodes. Patients were age and sex matched to general population controls (n=898,454) and risk of violent crime was calculated. Additionally, we compared the odds of violent crime in unaffected half-siblings (n=15,534) and full siblings (n=33,516) of patients with the general population controls. In sensitivity analyses, we examined the contribution of substance abuse, sociodemographic factors, and previous criminality. In the second study, we studied a general population sample of twins (n=23,020) with continuous measures of depressive symptoms for risk of violent crime.

    Findings: During a mean follow-up period of 3·2 years, 641 (3·7%) of the depressed men and 152 (0·5%) of the depressed women violently offended after diagnosis. After adjustment for sociodemographic confounders, the odds ratio of violent crime was 3·0 (95% CI 2·8–3·3) compared with the general population controls. The odds of violent crime in half-siblings (adjusted odds ratio 1·2 [95% CI 1·1–1·4]) and full siblings (1·5, 95% CI 1·3–1·6) were significantly increased, showing some familial confounding of the association between depression and violence. However, the odds increase remained significant in individuals with depression after adjustment for familial confounding, and in those without substance abuse comorbidity or a previous violent conviction (all p<0·0001). In the twin study, during the mean follow-up time of 5·4 years, 88 violent crimes were recorded. Depressive symptoms were associated with increased risk of violent crime and a sensitivity analysis identified little difference in risk estimate when all crimes (violent and non-violent) was the outcome.

    Interpretation: Risk of violent crime was increased in individuals with depression after adjustment for familial, sociodemographic and individual factors in two longitudinal studies. Clinical guidelines should consider recommending violence risk assessment in certain subgroups with depression.

    Funding: Wellcome Trust and the Swedish Research Council.

  • 8.
    Fazel, Seena
    et al.
    Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, UK .
    Wolf, Achim
    Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, UK .
    Larsson, Henrik
    Örebro University, School of Medical Sciences. Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
    Lichtenstein, Paul
    Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
    Mallett, Susan
    School of Population and Health Sciences, University of Birmingham, Birmingham, UK.
    Fanshawe, Thomas R.
    Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
    Identification of low risk of violent crime in severe mental illness with a clinical prediction tool (Oxford Mental Illness and Violence tool [OxMIV]): a derivation and validation study2017In: Lancet psychiatry, ISSN 2215-0374, E-ISSN 2215-0366, Vol. 4, no 6, p. 461-468Article in journal (Refereed)
    Abstract [en]

    Background: Current approaches to stratify patients with psychiatric disorders into groups on the basis of violence risk are limited by inconsistency, variable accuracy, and unscalability. To address the need for a scalable and valid tool to assess violence risk in patients with schizophrenia spectrum or bipolar disorder, we describe the derivation of a score based on routinely collected factors and present findings from external validation.

    Methods: On the basis of a national cohort of 75 158 Swedish individuals aged 15-65 years with a diagnosis of severe mental illness (schizophrenia spectrum or bipolar disorder) with 574 018 patient episodes between Jan 1, 2001, and Dec 31, 2008, we developed predictive models for violent offending (primary outcome) within 1 year of hospital discharge for inpatients or clinical contact with psychiatric services for outpatients (patient episode) through linkage of population-based registers. We developed a derivation model to determine the relative influence of prespecified criminal history and sociodemographic and clinical risk factors, which are mostly routinely collected, and then tested it in an external validation. We measured discrimination and calibration for prediction of violent offending at 1 year using specified risk cutoffs.

    Findings: Of the cohort of 75 158 patients with schizophrenia spectrum or bipolar disorder, we assigned 58 771 (78%) to the derivation sample and 16 387 (22%) to the validation sample. In the derivation sample, 830 (1%) individuals committed a violent offence within 12 months of their patient episode. We developed a 16-item model. The strongest predictors of violent offending within 12 months were conviction for previous violent crime (adjusted odds ratio 5 . 03 [95% CI 4.23-5.98]; p < 0.0001), male sex (2.32 [1.91-2.81]; p < 0.0001), and age (0.63 per 10 years of age [0.58-0.67]; p < 0.0001). In external validation, the model showed good measures of discrimination (c-index 0.89 [0.85-0.93]) and calibration. For risk of violent offending at 1 year, with a 5% cutoff, sensitivity was 62% (95% CI 55-68) and specificity was 94% (93-94). The positive predictive value was 11% and the negative predictive value was more than 99%. We used the model to generate a simple web-based risk calculator (Oxford Mental Illness and Violence tool [OxMIV]).

    Interpretation: We have developed a prediction score in a national cohort of patients with schizophrenia spectrum or bipolar disorder, which can be used as an adjunct to decision making in clinical practice by identifying those who are at low risk of violent offending. The low positive predictive value suggests that further clinical assessment in individuals at high risk of violent offending is required to establish who might benefit from additional risk management. Further validation in other countries is needed. Copyright (C) The Author(s). Published by Elsevier Ltd.

  • 9.
    Hollis, Chris
    et al.
    National Institute of Health Research (NIHR) MindTech MedTech Cooperative, NIHR Nottingham Biomedical Research Centre and Centre for ADHD and Neurodevelopmental Disorders Across the Lifespan, Institute of Mental Health, Division of Psychiatry and Applied Psychology, School of Medicine, University of Nottingham, Nottingham, United Kingdom.
    Chen, Qi
    Department of Medical Epidemiology and Biostatistics, Karolinska Instituet, Stockholm, Sweden.
    Chang, Zheng
    Department of Medical Epidemiology and Biostatistics, Karolinska Instituet, Stockholm, Sweden.
    Quinn, Patrick D.
    Department of Applied Health Science, School of Public Health, Indiana University, Bloomington IN, United States.
    Viktorin, Alexander
    Department of Medical Epidemiology and Biostatistics, Karolinska Instituet, Stockholm, Sweden.
    Lichtenstein, Paul
    Department of Medical Epidemiology and Biostatistics, Karolinska Instituet, Stockholm, Sweden.
    D'Onofrio, Brian
    Department of Medical Epidemiology and Biostatistics, Karolinska Instituet, Stockholm, Sweden; Department of Psychological and Brain Sciences, College of Arts and Sciences, Indiana University, Bloomington IN, USA.
    Landen, Mikael
    Department of Medical Epidemiology and Biostatistics, Karolinska Instituet, Stockholm, Sweden; Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, University of Gothenburg, Gothenburg, Sweden.
    Larsson, Henrik
    Örebro University, School of Medical Sciences. Department of Medical Epidemiology and Biostatistics, Karolinska Instituet, Stockholm, Sweden.
    Methylphenidate and the risk of psychosis in adolescents and young adults: a population-based cohort study2019In: Lancet psychiatry, ISSN 2215-0374, E-ISSN 2215-0366, Vol. 6, no 8, p. 651-658Article in journal (Refereed)
    Abstract [en]

    Background: There is a clinical concern that prescribing methylphenidate, the most common pharmacological treatment for attention-deficit hyperactivity disorder (ADHD), might increase the risk of psychotic events, particularly in young people with a history of psychosis. We aimed to determine whether the risk of psychotic events increases immediately after initiation of methylphenidate treatment or, in the longer term, 1 year after treatment initiation in adolescents and young adults with and without a previously diagnosed psychotic disorder.

    Methods: In this cohort study, we used population-based observational data from the Swedish Prescribed Drug Register, the National Patient Register, and the Total Population Register, three population-based registers containing data on all individuals in Sweden, to attain data on sex, birth, death, migration, medication use, and psychotic events for all eligible participants. We screened individuals on these registers to identify those receiving methylphenidate treatment, and who were aged 12-30 years at the start of treatment, for their inclusion in the study. We used a within-individual design to compare the incidence of psychotic events in these individuals during the 12-week periods immediately before and after methylphenidate initiation. Longer term risk was assessed by comparing the incidence of psychotic events 12 weeks before methylphenidate initiation and during a 12-week period one calendar year before the initiation of methylphenidate with the incidence of these events during the 12-week period one calendar year after methylphenidate initiation. We estimated the incidence rate ratios (IRR) and 95% CIs of psychotic events after the initation of methylphenidate treatment, relative to the events before treatment, which were defined as any hospital visit (inpatient admission or outpatient attendance, based on data from the National Patient Register) because of psychosis, using the International Classification of Diseases version 10 definition. Analyses were stratified by whether the individual had a history of psychosis.

    Findings: We searched the Swedish Prescribed Drug Register to find eligible individuals who had received methylphenidate between Jan 1, 2007 and June 30, 2012. 61 814 individuals were screened, of whom 23 898 (38.7%) individuals were assessed and 37 916 (61.3%) were excluded from the study because they were outside of the age criteria at the start of treatment, they had immigrated, emigrated, or died during the study period, or because they were administered other ADHD medications. The median age at methylphenidate initiation was 17 years, and a history of psychosis was reported in 479 (2.0%) participants. The IRR of psychotic events in the 12-week period after initiation of methylphenidate treatment relative to that in the 12-week period before treatment start was 1.04 (95% CI 0.80-1.34) in adolescents and young adults without a history of psychosis and 0.95 (0.69-1.30) among those with a history of psychosis.

    Interpretation: Contrary to clinical concerns, we found no evidence that initiation of methylphenidate treatment increases the risk of psychotic events in adolescents and young adults, including in those individuals with a history of psychosis. Our study should reassure clinicians considering initiating methylphenidate treatment for ADHD in adolescents and young adults, and it challenges the widely held view in clinical practice that methylphenidate should be avoided, or its use restricted, in individuals with a history of psychosis.

  • 10.
    Munk-Olsen, Trine
    et al.
    The National Center for Register-based Research, Department of Economics and Business Economics, Aarhus University, Aarhus, Denmark; Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark.
    Liu, Xiaoqin
    The National Center for Register-based Research, Department of Economics and Business Economics, Aarhus University, Aarhus, Denmark.
    Viktorin, Alexander
    Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
    Brown, Hilary K.
    Interdisciplinary Centre for Health and Society, Scarborough Campus, University of Toronto, Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada; Women's College Research Institute, Women's College Hospital, Toronto, ON, Canada; Institute for Clinical Evaluative Sciences, Toronto, ON, Canada.
    Di Florio, Arianna
    Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK; Department of Psychiatry, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC, USA.
    D'Onofrio, Brian M.
    Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden; Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA.
    Gomes, Tara
    Leslie Dan Faculty of Pharmacy, University of Toronto, Toronto, ON, Canada; Institute for Clinical Evaluative Sciences, Toronto, ON, Canada.
    Howard, Louise M.
    Section of Women's Mental Health/Women's Health Academic Centre, Department of Health Service and Population Research, King's College London, London, UK; Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
    Khalifeh, Hind
    Section of Women's Mental Health/Women's Health Academic Centre, Department of Health Service and Population Research, King's College London, London, UK; Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
    Krohn, Holly
    Department of Psychiatry, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC, USA.
    Larsson, Henrik
    Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
    Lichtenstein, Paul
    Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
    Taylor, Clare L.
    Section of Women's Mental Health/Women's Health Academic Centre, Department of Health Service and Population Research, King's College London, London, UK; Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
    Van Kamp, Inge
    Department of Obstetrics, Section of Perinatal Psychiatry, Leiden University Medical Center, Leiden, Netherlands.
    Wesseloo, Richard
    Department of Psychiatry, Erasmus Medical Centre, Rotterdam, Netherlands.
    Meltzer-Brody, Samantha
    Department of Psychiatry, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC, USA.
    Vigod, Simone N.
    Department of Psychiatry, University of Toronto, Toronto, ON, Canada; Women's College Research Institute, Women's College Hospital, Toronto, ON, Canada; Institute for Clinical Evaluative Sciences, Toronto, ON, Canada.
    Bergink, Veerle
    Department of Psychiatry, Erasmus Medical Centre, Rotterdam, Netherlands; Department of Psychiatry and Department of Obstetrics, Gynecology and Reproductive Science, Icahn School of Medicine at Mount Sinai, New York City, NY, USA.
    Maternal and infant outcomes associated with lithium use in pregnancy: an international collaborative meta-analysis of six cohort studies2018In: Lancet psychiatry, ISSN 2215-0374, E-ISSN 2215-0366, Vol. 5, no 8, p. 644-652Article in journal (Refereed)
    Abstract [en]

    BACKGROUND: Concerns about teratogenicity and maternal and offspring complications restrict the use of lithium during pregnancy for the treatment of mood disorders. We aimed to investigate the association between in-utero lithium exposure and risk of pregnancy complications, delivery outcomes, neonatal morbidity, and congenital malformations.

    METHODS: In this meta-analysis, primary data from pregnant women and their children from six international cohorts based in the community (Denmark, Sweden, and Ontario, Canada) and in clinics (the Netherlands, UK, and USA) were analysed. Pregnancies were eligible for analysis if the pregnancy resulted in a liveborn singleton between 1997 and 2015, if health-related information was available for both mother and infant, and if the mother had a mood disorder (bipolar disorder or major depressive disorder) or if she had been given lithium during pregnancy (at least two dispensations of lithium during pregnancy that were dispensed any time from 1 month before conception until the delivery, or a single lithium dispensation during pregnancy when there was at least one other lithium dispensation within 6 months before or after this date). Pregnancies during which the mother had been prescribed known teratogenic drugs were excluded. Pregnancies were grouped into a lithium-exposed group and a mood disorder reference group. The main outcome measures were pregnancy complications, delivery outcomes, neonatal readmission to hospital within 28 days of birth, and congenital malformations (major malformations and major cardiac malformations). Analyses were done at each site by use of a shared protocol. Adjusted odds ratios (aORs) and 95% CIs were calculated by use of logistic regression models, and site-specific prevalence rates and ORs were pooled by use of random-effects meta-analytical models.

    FINDINGS: 22   124 eligible pregnancies were identified across the six cohorts, of which 727 pregnancies were eligible for inclusion in the lithium-exposed group (557 [77%] from register-based cohorts and 170 [23%] from clinical cohorts). Lithium exposure was not associated with any of the predefined pregnancy complications or delivery outcomes. An increased risk for neonatal readmission within 28 days of birth was seen in the lithium-exposed group compared with the reference group (pooled prevalence 27·5% [95% CI 15·8-39·1] vs 14·3% [10·4-18·2]; pooled aOR 1·62, 95% CI 1·12-2·33). Lithium exposure during the first trimester was associated with an increased risk of major malformations (pooled prevalence 7·4% [95% CI 4·0-10·7] vs 4·3% [3·7-4·8]; pooled aOR 1·71, 95% CI 1·07-2·72) but for major cardiac malformations the difference was not significant (2·1% [0·5-3·7] vs 1·6% [1·0-2·1]; pooled aOR 1·54, 95% CI 0·64-3·70).

    INTERPRETATION: Considering both the effect sizes and the precision of the estimates in this meta-analysis, treatment decisions for pregnant women with mood disorders must weigh the potential for increased risks of lithium during pregnancy-in particular those associated with use of lithium during the first trimester-against its effectiveness at reducing relapse.

    FUNDING: None.

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