Mortality associated with clozapine: what is the evidence?

While clozapine has risks, relative risk of fatality is overestimated. The UK pharmacovigilance programme is efficient, but comparisons with other drugs can mislead because of reporting variations. Clozapine actually lowers mortality, partly by reducing schizophrenia-related suicides, but preventable deaths still occur. Clozapine should be used earlier and more widely, but there should be better monitoring and better management of toxicity.

Academic psychiatry is everyone's business.

This editorial considers the value and nature of academic psychiatry by asking what defines the specialty and psychiatrists as academics. We frame academic psychiatry as a way of thinking that benefits clinical services and discuss how to inspire the next generation of academics.

Longitudinal changes in DNA methylation associated with clozapine use in treatment-resistant schizophrenia from two international cohorts.

The second-generation antipsychotic clozapine is used as a medication for treatment-resistant schizophrenia. It has previously been associated with epigenetic changes in pre-clinical rodent models and cross-sectional studies of treatment-resistant schizophrenia. Cross-sectional studies are susceptible to confounding, however, and cannot disentangle the effects of diagnosis and medication. We therefore profiled DNA methylation in sequential blood samples (n = 126) from two independent cohorts of patients (n = 38) with treatment-resistant schizophrenia spectrum disorders who commenced clozapine after study enrolment and were followed up for up to six months. We identified significant non-linear changes in cell-type proportion estimates derived from DNA methylation data - specifically B-cells - associated with time on clozapine. Mixed effects regression models were used to identify changes in DNA methylation at specific sites associated with time on clozapine, identifying 37 differentially methylated positions (DMPs) (p < 5 × 10-5) in a linear model and 90 DMPs in a non-linear quadratic model. We compared these results to data from our previous epigenome-wide association study (EWAS) meta-analysis of psychosis, finding evidence that many previously identified DMPs associated with schizophrenia and treatment-resistant schizophrenia might reflect exposure to clozapine. In conclusion, our results indicate that clozapine exposure is associated with changes in DNA methylation and cellular composition. Our study shows that medication effects might confound many case-control studies of neuropsychiatric disorders performed in blood.

Developing a validated methodology for identifying clozapine treatment periods in electronic health records.

BACKGROUND: Clozapine is the only recommended antipsychotic medication for individuals diagnosed with treatment-resistant schizophrenia. Unfortunately, its wider use is hindered by several possible adverse effects, some of which are rare but potentially life threatening. As such, there is a growing interest in studying clozapine use and safety in routinely collected healthcare data. However, previous attempts to characterise clozapine treatment have had low accuracy. AIM: To develop a methodology for identifying clozapine treatment dates by combining several data sources and implement this on a large clinical database. METHODS: Non-identifiable electronic health records from a large mental health provider in London and a linked database from a national clozapine blood monitoring service were used to obtain information regarding patients' clozapine treatment status, blood tests and pharmacy dispensing records. A rule-based algorithm was developed to determine the dates of starting and stopping treatment based on these data, and more than 10% of the outcomes were validated by manual review of de-identified case note text. RESULTS: A total of 3,212 possible clozapine treatment periods were identified, of which 425 (13.2%) were excluded due to insufficient data to verify clozapine administration. Of the 2,787 treatments remaining, 1,902 (68.2%) had an identified start-date. On evaluation, the algorithm identified treatments with 96.4% accuracy; start dates were 96.2% accurate within 15 days, and end dates were 85.1% accurate within 30 days. CONCLUSIONS: The algorithm produced a reliable database of clozapine treatment periods. Beyond underpinning future observational clozapine studies, we envisage it will facilitate similar implementations on additional large clinical databases worldwide.

Changes in immunoglobulin levels during clozapine treatment in schizophrenia.

BACKGROUND AND HYPOTHESIS: Use of clozapine in treatment-resistant schizophrenia is often limited due to risk of adverse effects. Cross-sectional associations between clozapine treatment and low immunoglobulin levels have been reported, however prospective studies are required to establish temporal relationships. We tested the hypothesis that reductions in immunoglobulin levels would occur over the first 6 months following initiation of clozapine treatment. Relationships between immunoglobulin levels and symptom severity over the course of clozapine treatment were also explored. DESIGN: This prospective observational study measured immunoglobulin (Ig) levels (A, M and G) in 56 patients with treatment-resistant schizophrenia at 6-, 12- and 24-weeks following initiation with clozapine. Clinical symptoms were also measured at 12 weeks using the positive and negative syndrome scale (PANSS). RESULTS: IgA, IgG and IgM all decreased during clozapine treatment. For IgA and IgG the reduction was significant at 24 weeks (IgA: ß = -32.66, 95% CI = -62.38, -2.93, p = 0.03; IgG: ß = -63.96, 95% CI = -118.00, -9.31, p = 0.02). For IgM the reduction was significant at 12 and 24 weeks (12 weeks: ß = -23.48, 95% CI = -39.56, -7.42, p = 0.004; 24 weeks: ß = -33.12, 95 %CI = -50.30, -15.94, p = <0.001). Reductions in IgA and IgG during clozapine treatment were correlated with reductions in PANSS-total over 12 weeks (n = 32, IgA r = 0.59, p = 0.005; IgG r = 0.48, p = 0.03). CONCLUSIONS: The observed reductions in immunoglobulin levels over six months of clozapine treatment add further evidence linking clozapine to secondary antibody deficiency. Associations between Ig reduction and symptom improvement may however indicate that immune mechanisms contribute to both desirable and undesirable effects of clozapine.

Treatment resistance NMDA receptor pathway polygenic score is associated with brain glutamate in schizophrenia.

Dysfunction of glutamate neurotransmission has been implicated in the pathophysiology of schizophrenia and may be particularly relevant in severe, treatment-resistant symptoms. The underlying mechanism may involve hypofunction of the NMDA receptor. We investigated whether schizophrenia-related pathway polygenic scores, composed of genetic variants within NMDA receptor encoding genes, are associated with cortical glutamate in schizophrenia. Anterior cingulate cortex (ACC) glutamate was measured in 70 participants across 4 research sites using Proton Magnetic Resonance Spectroscopy (1H-MRS). Two NMDA receptor gene sets were sourced from the Molecular Signatories Database and NMDA receptor pathway polygenic scores were constructed using PRSet. The NMDA receptor pathway polygenic scores were weighted by single nucleotide polymorphism (SNP) associations with treatment-resistant schizophrenia, and associations with ACC glutamate were tested. We then tested whether NMDA receptor pathway polygenic scores with SNPs weighted by associations with non-treatment-resistant schizophrenia were associated with ACC glutamate. A higher NMDA receptor complex pathway polygenic score was significantly associated with lower ACC glutamate (ß = -0.25, 95 % CI = -0.49, -0.02, competitive p = 0.03). When SNPs were weighted by associations with non-treatment-resistant schizophrenia, there was no association between the NMDA receptor complex pathway polygenic score and ACC glutamate (ß = 0.05, 95 % CI = -0.18, 0.27, competitive p = 0.79). These results provide initial evidence of an association between common genetic variation implicated in NMDA receptor function and ACC glutamate levels in schizophrenia. This association was specific to when the NMDA receptor complex pathway polygenic score was weighted by SNP associations with treatment-resistant schizophrenia.

Early neutrophil trajectory following clozapine may predict clozapine response - Results from an observational study using electronic health records.

BACKGROUND: Clozapine has unique effectiveness in treatment-resistant schizophrenia and is known to cause immunological side-effects. A transient spike in neutrophils commonly occurs in the first weeks of clozapine therapy. There is contradictory evidence in the literature as to whether neutrophil changes with clozapine are linked to treatment response. AIMS: The current study aims to further examine the neutrophil changes in response to clozapine and explore any association between neutrophil trajectory and treatment response. METHODS: A retrospective cohort study of patients undergoing their first treatment with clozapine and continuing for at least 2 years identified 425 patients (69% male/31% female). Neutrophil counts at baseline, 3 weeks and 1 month were obtained predominantly by linkage with data from the clozapine monitoring service. Clinical Global Impression- Severity (CGI-S) was rated from case notes at the time of clozapine initiation and at 2 years. Latent class growth analysis (LCGA) was performed to define distinct trajectories of neutrophil changes during the first month of treatment. Logistic regression was then conducted to investigate for association between the trajectory of neutrophil count changes in month 1 and clinical response at 2 years as well as between baseline neutrophil count and response. RESULTS: Of the original cohort, 397 (93%) patients had useable neutrophil data during the first 6 weeks of clozapine treatment. LCGA revealed significant differences in neutrophil trajectories with a three-class model being the most parsimonious. The classes had similar trajectory profiles but differed primarily on overall neutrophil count: with low, high-normal and high neutrophil classes, comprising 52%, 40% and 8% of the sample respectively. Membership of the high-normal group was associated with significantly increased odds of a positive response to clozapine, as compared to the low neutrophil group [Odds ratio (OR) = 2.10, p-value = 0.002; 95% confidence interval (95% CI) = 1.31-3.36]. Baseline neutrophil count was a predictor of response to clozapine at 2 years, with counts of ≥5 × 109/l significantly associated with positive response (OR = 1.60, p-value = 0.03; 95% CI = 1.03-2.49). CONCLUSIONS: Our data are consistent with the hypothesis that patients with low-level inflammation, reflected in a high-normal neutrophil count, are more likely to respond to clozapine, raising the possibility that clozapine exerts its superior efficacy via immune mechanisms.

The lived experience of clozapine discontinuation in patients and carers following suspected clozapine-induced neutropenia.

BACKGROUND: Clozapine is the treatment of choice in refractory psychosis. In most countries, clozapine must be stopped indefinitely if white blood cells fall below a defined threshold during routine monitoring. Despite evidence of severe adverse consequences of clozapine discontinuation, published accounts on the lived experiences and perspectives of patients and carers are scarce. METHOD: We completed semi-structured interviews with patients (n = 4) and family carers (n = 4) on experiences of clozapine cessation following suspected drug-induced neutropenia. Interviews were audio-recorded, transcribed and analysed thematically. RESULTS: The two overarching themes comprised:(i) stress of clozapine below threshold neutrophil results and (ii) patient and carer priorities. CONCLUSIONS: There is a suggested need for evidence-based pharmacological and psychological approaches to support patients and carers after clozapine cessation. Such approaches will minimise the potentially negative physical and emotional sequela in the aftermath of a below threshold neutrophil result and reduce the likelihood of experiencing additional health and social inequalities after clozapine discontinuation.

The association between peripheral inflammation, brain glutamate and antipsychotic response in Schizophrenia: Data from the STRATA collaboration.

Glutamate and increased inflammation have been separately implicated in the pathophysiology of schizophrenia and the extent of clinical response to antipsychotic treatment. Despite the mechanistic links between pro-inflammatory and glutamatergic pathways, the relationships between peripheral inflammatory markers and brain glutamate in schizophrenia have not yet been investigated. In this study, we tested the hypothesis that peripheral levels of pro-inflammatory cytokines would be positively associated with brain glutamate levels in schizophrenia. Secondary analyses determined whether this relationship differed according to antipsychotic treatment response. The sample consisted of 79 patients with schizophrenia, of whom 40 were rated as antipsychotic responders and 39 as antipsychotic non-responders. Brain glutamate levels were assessed in the anterior cingulate cortex (ACC) and caudate using proton magnetic resonance spectroscopy (1H-MRS) and blood samples were collected for cytokine assay on the same study visit (IL-6, IL-8, IL-10, TNF- α and IFN-γ). Across the whole patient sample, there was a positive relationship between interferon-gamma (IFN-γ) and caudate glutamate levels (r = 0.31, p = 0.02). In the antipsychotic non-responsive group only, there was a positive relationship between interleukin-8 (IL-8) and caudate glutamate (r = 0.46, p = 0.01). These findings provide evidence to link specific peripheral inflammatory markers and caudate glutamate in schizophrenia and may suggest that this relationship is most marked in patients who show a poor response to antipsychotic treatment.

Clinical impact of reducing the frequency of clozapine monitoring: controlled mirror-image cohort study.

BACKGROUND: To minimise infection during COVID-19, the clozapine haematological monitoring interval was extended from 4-weekly to 12-weekly intervals in South London and Maudsley NHS Foundation Trust. AIMS: To investigate the impact of this temporary policy change on clinical and safety outcomes. METHOD: All patients who received clozapine treatment with extended (12-weekly) monitoring in a large London National Health Service trust were included in a 1-year mirror-image study. A comparison group was selected with standard monitoring. The proportion of participants with mild to severe neutropenia and the proportion of participants attending the emergency department for clozapine-induced severe neutropenia treatment during the follow-up period were compared. Psychiatric hospital admission rates, clozapine dose and concomitant psychotropic medication in the 1 year before and the 1 year after extended monitoring were compared. All-cause clozapine discontinuation at 1-year follow-up was examined. RESULTS: Of 569 participants, 459 received clozapine with extended monitoring and 110 controls continued as normal. The total person-years were 458 in the intervention group and 109 in the control group, with a median follow-up time of 1 year in both groups. During follow-up, two participants (0.4%) recorded mild to moderate neutropenia in the intervention group and one (0.9%) in the control group. There was no difference in the incidence of haematological events between the two groups (IRR = 0.48, 95% CI 0.02-28.15, P = 0.29). All neutropenia cases in the intervention group were mild, co-occurring during COVID-19 infection. The median number of admissions per patient during the pre-mirror period remained unchanged (0, IQR = 0) during the post-mirror period. There was one death in the control group, secondary to COVID-19 infection. CONCLUSIONS: There was no evidence that the incidence of severe neutropenia was increased in those receiving extended monitoring.

Cognitive performance at first episode of psychosis and the relationship with future treatment resistance: Evidence from an international prospective cohort study.

BACKGROUND: Antipsychotic treatment resistance affects up to a third of individuals with schizophrenia, with recent research finding systematic biological differences between antipsychotic resistant and responsive patients. Our aim was to determine whether cognitive impairment at first episode significantly differs between future antipsychotic responders and resistant cases. METHODS: Analysis of data from seven international cohorts of first-episode psychosis (FEP) with cognitive data at baseline (N = 683) and follow-up data on antipsychotic treatment response: 605 treatment responsive and 78 treatment resistant cases. Cognitive measures were grouped into seven cognitive domains based on the pre-existing literature. We ran multiple imputation for missing data and used logistic regression to test for associations between cognitive performance at FEP and treatment resistant status at follow-up. RESULTS: On average patients who were future classified as treatment resistant reported poorer performance across most cognitive domains at baseline. Univariate logistic regressions showed that antipsychotic treatment resistance cases had significantly poorer IQ/general cognitive functioning at FEP (OR = 0.70, p = .003). These findings remained significant after adjusting for additional variables in multivariable analyses (OR = 0.76, p = .049). CONCLUSIONS: Although replication in larger studies is required, it appears that deficits in IQ/general cognitive functioning at first episode are associated with future treatment resistance. Cognitive variables may be able to provide further insight into neurodevelopmental factors associated with treatment resistance or act as early predictors of treatment resistance, which could allow prompt identification of refractory illness and timely interventions.

Anterior cingulate glutamate metabolites as a predictor of antipsychotic response in first episode psychosis: data from the STRATA collaboration.

Elevated brain glutamate has been implicated in non-response to antipsychotic medication in schizophrenia. Biomarkers that can accurately predict antipsychotic non-response from the first episode of psychosis (FEP) could allow stratification of patients; for example, patients predicted not to respond to standard antipsychotics could be fast-tracked to clozapine. Using proton magnetic resonance spectroscopy (1H-MRS), we examined the ability of glutamate and Glx (glutamate plus glutamine) in the anterior cingulate cortex (ACC) and caudate to predict response to antipsychotic treatment. A total of 89 minimally medicated patients with FEP not meeting symptomatic criteria for remission were recruited across two study sites. 1H-MRS and clinical data were acquired at baseline, 2 and 6 weeks. Response was defined as >20% reduction in Positive and Negative Syndrome Scale (PANSS) Total score from baseline to 6 weeks. In the ACC, baseline glutamate and Glx were higher in Non-Responders and significantly predicted response (P < 0.02; n = 42). Overall accuracy was greatest for ACC Glx (69%) and increased to 75% when symptom severity at baseline was included in the model. Glutamate metabolites in the caudate were not associated with response, and there was no significant change in glutamate metabolites over time in either region. These results add to the evidence linking elevations in ACC glutamate metabolites to a poor antipsychotic response. They indicate that glutamate may have utility in predicting response during early treatment of first episode psychosis. Improvements in accuracy may be made by combining glutamate measures with other response biomarkers.

Neuropsychological differences between treatment-resistant and treatment-responsive schizophrenia: a meta-analysis.

Antipsychotic treatment resistance affects up to a third of individuals with schizophrenia. Of those affected, 70-84% are reported to be treatment resistant from the outset. This raises the possibility that the neurobiological mechanisms of treatment resistance emerge before the onset of psychosis and have a neurodevelopmental origin. Neuropsychological investigations can offer important insights into the nature, origin and pathophysiology of treatment-resistant schizophrenia (TRS), but methodological limitations in a still emergent field of research have obscured the neuropsychological discriminability of TRS. We report on the first systematic review and meta-analysis to investigate neuropsychological differences between TRS patients and treatment-responsive controls across 17 published studies (1864 participants). Five meta-analyses were performed in relation to (1) executive function, (2) general cognitive function, (3) attention, working memory and processing speed, (4) verbal memory and learning, and (5) visual-spatial memory and learning. Small-to-moderate effect sizes emerged for all domains. Similarly to previous comparisons between unselected, drug-naïve and first-episode schizophrenia samples v. healthy controls in the literature, the largest effect size was observed in verbal memory and learning [dl = -0.53; 95% confidence interval (CI) -0.29 to -0.76; z = 4.42; p < 0.001]. A sub-analysis of language-related functions, extracted from across the primary domains, yielded a comparable effect size (dl = -0.53, 95% CI -0.82 to -0.23; z = 3.45; p < 0.001). Manipulating our sampling strategy to include or exclude samples selected for clozapine response did not affect the pattern of findings. Our findings are discussed in relation to possible aetiological contributions to TRS.

Clinical predictors of antipsychotic treatment resistance: Development and internal validation of a prognostic prediction model by the STRATA-G consortium.

INTRODUCTION: Our aim was to, firstly, identify characteristics at first-episode of psychosis that are associated with later antipsychotic treatment resistance (TR) and, secondly, to develop a parsimonious prediction model for TR. METHODS: We combined data from ten prospective, first-episode psychosis cohorts from across Europe and categorised patients as TR or non-treatment resistant (NTR) after a mean follow up of 4.18 years (s.d. = 3.20) for secondary data analysis. We identified a list of potential predictors from clinical and demographic data recorded at first-episode. These potential predictors were entered in two models: a multivariable logistic regression to identify which were independently associated with TR and a penalised logistic regression, which performed variable selection, to produce a parsimonious prediction model. This model was internally validated using a 5-fold, 50-repeat cross-validation optimism-correction. RESULTS: Our sample consisted of N = 2216 participants of which 385 (17 %) developed TR. Younger age of psychosis onset and fewer years in education were independently associated with increased odds of developing TR. The prediction model selected 7 out of 17 variables that, when combined, could quantify the risk of being TR better than chance. These included age of onset, years in education, gender, BMI, relationship status, alcohol use, and positive symptoms. The optimism-corrected area under the curve was 0.59 (accuracy = 64 %, sensitivity = 48 %, and specificity = 76 %). IMPLICATIONS: Our findings show that treatment resistance can be predicted, at first-episode of psychosis. Pending a model update and external validation, we demonstrate the potential value of prediction models for TR.

Clinical correlates of early onset antipsychotic treatment resistance.

BACKGROUND: There is evidence of heterogeneity within treatment-resistant schizophrenia (TRS), with some people not responding to antipsychotic treatment from illness onset and others becoming treatment-resistant after an initial response period. These groups may have different aetiologies. AIM: This study investigates sociodemographic and clinical correlates of early onset of TRS. METHOD: Employing a retrospective cohort design, we do a secondary analysis of data from a cohort of people with TRS attending the South London and Maudsley. Regression analyses were conducted to identify the correlates of the length of treatment to TRS. Predictors included the following: gender, age, ethnicity, problems with positive symptoms, problems with activities of daily living, psychiatric comorbidities, involuntary hospitalisation and treatment with long-acting injectable antipsychotics. RESULTS: In a cohort of 164 people with TRS (60% were men), the median length of treatment to TRS was 3 years and 8 months. We observed no cut-off on the length of treatment until TRS presentation differentiating between early and late TRS (i.e. no bimodal distribution). Having mild to very severe problems with hallucinations and delusions at the treatment start was associated with earlier TRS (~19 months earlier). In sensitivity analyses, including only complete cases (subject to selection bias), treatment with a long-acting injectable antipsychotic was additionally associated with later TRS (~15 months later). CONCLUSION: Our findings do not support a clear separation between early and late TRS but rather a continuum of the length of treatment before TRS onset. Having mild to very severe problems with positive symptoms at treatment start predicts earlier onset of TRS.

Gene set enrichment analysis of pathophysiological pathways highlights oxidative stress in psychosis.

Polygenic risk prediction remains an important aim of genetic association studies. Currently, the predictive power of schizophrenia polygenic risk scores (PRSs) is not large enough to allow highly accurate discrimination between cases and controls and thus is not adequate for clinical integration. Since PRSs are rarely used to reveal biological functions or to validate candidate pathways, to fill this gap, we investigated whether their predictive ability could be improved by building genome-wide (GW-PRSs) and pathway-specific PRSs, using distance- or expression quantitative trait loci (eQTLs)- based mapping between genetic variants and genes. We focused on five pathways (glutamate, oxidative stress, GABA/interneurons, neuroimmune/neuroinflammation and myelin) which belong to a critical hub of schizophrenia pathophysiology, centred on redox dysregulation/oxidative stress. Analyses were first performed in the Lausanne Treatment and Early Intervention in Psychosis Program (TIPP) study (n = 340, cases/controls: 208/132), a sample of first-episode of psychosis patients and matched controls, and then validated in an independent study, the epidemiological and longitudinal intervention program of First-Episode Psychosis in Cantabria (PAFIP) (n = 352, 224/128). Our results highlighted two main findings. First, GW-PRSs for schizophrenia were significantly associated with early psychosis status. Second, oxidative stress was the only significantly associated pathway that showed an enrichment in both the TIPP (p = 0.03) and PAFIP samples (p = 0.002), and exclusively when gene-variant linking was done using eQTLs. The results suggest that the predictive accuracy of polygenic risk scores could be improved with the inclusion of information from functional annotations, and through a focus on specific pathways, emphasizing the need to build and study functionally informed risk scores.

A predictor model of treatment resistance in schizophrenia using data from electronic health records.

OBJECTIVES: To develop a prognostic tool of treatment resistant schizophrenia (TRS) in a large and diverse clinical cohort, with comprehensive coverage of patients using mental health services in four London boroughs. METHODS: We used the Least Absolute Shrinkage and Selection Operator (LASSO) for time-to-event data, to develop a risk prediction model from the first antipsychotic prescription to the development of TRS, using data from electronic health records. RESULTS: We reviewed the clinical records of 1,515 patients with a schizophrenia spectrum disorder and observed that 253 (17%) developed TRS. The Cox LASSO survival model produced an internally validated Harrel's C index of 0.60. A Kaplan-Meier curve indicated that the hazard of developing TRS remained constant over the observation period. Predictors of TRS were: having more inpatient days in the three months before and after the first antipsychotic, more community face-to-face clinical contact in the three months before the first antipsychotic, minor cognitive problems, and younger age at the time of the first antipsychotic. CONCLUSIONS: Routinely collected information, readily available at the start of treatment, gives some indication of TRS but is unlikely to be adequate alone. These results provide further evidence that earlier onset is a risk factor for TRS.

Prevalence and Correlates of Obsessive-Compulsive Symptoms in Individuals With Schizophrenia, Schizoaffective Disorder, or Bipolar Disorder.

Objective: Although frequently reported in psychosis, obsessive-compulsive symptoms (OCS) are often not recognized and thus undertreated. We aimed to estimate the prevalence of OCS and obsessive-compulsive disorder (OCD) in patients with schizophrenia, schizoaffective disorder, or bipolar disorder in clinical records and identify clinical associations of OCS co-occurrence.Methods: Data were retrieved from the South London and Maudsley NHS Foundation Trust Biomedical Research Centre case register. The study population was restricted to individuals diagnosed with schizophrenia (ICD F20.x), schizoaffective disorder (ICD F25.x), or bipolar disorder (ICD F31.x) between 2007 and 2015. OCS and OCD were ascertained from structural fields and via Natural Language Processing software applied to free-text records. Clinical characteristics were obtained from Health of the Nation Outcome Scales for the analyses on associations between clinical characteristics and OCS/OCD status using logistic regressions with confounders considered.Results: 22,551 cases of schizophrenia, schizoaffective disorder, or bipolar disorder were identified in the observation window. Among these, 5,179 (24.0%) were identified as having OCS (including an OCD diagnosis) and 2,574 (11.9%) specifically with comorbid OCD. OCS/OCD was associated with an increased likelihood of recorded aggressive behavior (OR = 1.18; 95% CI, 1.10-1.26), cognitive problems (OR = 1.21; 95% CI, 1.13-1.30), hallucinations and delusions (OR = 1.11; 95% CI, 1.04-1.20), and physical problems (OR = 1.17; 95% CI, 1.09-1.26).Conclusions: OCS and OCD are frequently recorded for patients with schizophrenia, schizoaffective disorder, and bipolar disorder and are associated with more severe psychiatric clinical characteristics. Automated information extraction tools hold potential to improve recognition and treatment of co-occurring OCS/OCD for psychosis.