Different types of childhood adversity and 5-year outcomes in a longitudinal cohort of first-episode psychosis patients

Little is known about the impact of different forms of childhood adversity on outcomes in first-episode psychosis (FEP) patients beyond the first year of treatment. We investigated associations between different types of childhood adversity and outcomes of FEP patients over the 5 years following their first contact with mental health services for psychosis. 237 FEP cases aged 18–65 years were followed on average for 5 years after first presentation to psychiatric services in South London, UK. Childhood adversity prior to 17 years of age was assessed at baseline using the Childhood Experience of Care and Abuse Questionnaire (CECA.Q). The results showed that exposure to at least one type of childhood adversity was significantly associated with a lower likelihood of achieving symptomatic remission, longer inpatient stays, and compulsory admission over the 5-year follow-up. There was no evidence though of a dose-response effect. Some specificity was evident. Childhood parental separation was associated with significantly greater likelihood of non-compliance with antipsychotic medications, compulsory admission, and substance dependence. Institutional care was significantly associated with longer total length of inpatient stays; and parental death was significantly associated with compulsory admissions. Clinicians should screen FEP patients for childhood adversity and tailor interventions accordingly to improve outcomes

The Maudsley environmental risk score for psychosis

Background Risk prediction algorithms have long been used in health research and practice (e.g. prediction of cardiovascular disease and diabetes). However, similar tools have not been developed for mental health. For example, for psychotic disorders, attempts to sum environmental risk are rare, unsystematic and dictated by available data. In light of this, we sought to develop a valid, easy to use measure of the aggregate environmental risk score (ERS) for psychotic disorders. Methods We reviewed the literature to identify well-replicated and validated environmental risk factors for psychosis that combine a significant effect and large-enough prevalence. Pooled estimates of relative risks were taken from the largest available meta-analyses. We devised a method of scoring the level of exposure to each risk factor to estimate ERS. Relative risks were rounded as, due to the heterogeneity of the original studies, risk effects are imprecisely measured. Results Six risk factors (ethnic minority status, urbanicity, high paternal age, obstetric complications, cannabis use and childhood adversity) were used to generate the ERS. A distribution for different levels of risk based on simulated data showed that most of the population would be at low/moderate risk with a small minority at increased environmental risk for psychosis. Conclusions This is the first systematic approach to develop an aggregate measure of environmental risk for psychoses in asymptomatic individuals. This can be used as a continuous measure of liability to disease; mostly relevant to areas where the original studies took place. Its predictive ability will improve with the collection of additional, population-specific data

Utilising symptom dimensions with diagnostic categories improves prediction of time to first remission in first-episode psychosis

There has been much recent debate concerning the relative clinical utility of symptom dimensions versus conventional diagnostic categories in patients with psychosis. We investigated whether symptom dimensions rated at presentation for first-episode psychosis (FEP) better predicted time to first remission than categorical diagnosis over a four-year follow-up. The sample comprised 193 FEP patients aged 18-65 years who presented to psychiatric services in South London, UK, between 2006 and 2010. Psychopathology was assessed at baseline with the Positive and Negative Syndrome Scale and five symptom dimensions were derived using Wallwork/Fortgang’s model; baseline diagnoses were grouped using DSM-IV codes. Time to start of first remission was ascertained from clinical records. The Bayesian Information Criterion (BIC) was used to find the best fitting accelerated failure time model of dimensions, diagnoses and time to first remission. Sixty percent of patients remitted over the four years following first presentation to psychiatric services, and the average time to start of first remission was 18.3 weeks (SD=26.0, median=8). The positive (BIC=166.26), excited (BIC=167.30) and disorganised/concrete (BIC=168.77) symptom dimensions, and a diagnosis of schizophrenia (BIC=166.91) predicted time to first remission. However, a combination of the DSM-IV diagnosis of schizophrenia with all five symptom dimensions led to the best fitting model (BIC=164.35). Combining categorical diagnosis with symptom dimension scores in FEP patients improved the accuracy of predicting time to first remission. Thus our data suggest that the decision to consign symptom dimensions to an annexe in DSM-5 should be reconsidered at the earliest opportunity

Interaction between cannabis consumption and childhood abuse in psychotic disorders:preliminary findings on the role of different patterns of cannabis use

Aim: Several studies have suggested that lifetime cannabis consumption and childhood abuse synergistically contribute to the risk for psychotic disorders. This study aimed to extend existing findings regarding an additive interaction between childhood abuse and lifetime cannabis use by investigating the moderating role of type and frequency of cannabis use. Methods: Up to 231 individuals presenting for the first time to mental health services with psychotic disorders and 214 unaffected population controls from South London, United Kingdom, were recruited as part of the Genetics and Psychosis study. Information about history of cannabis use was collected using the Cannabis Experiences Questionnaire. Childhood physical and sexual abuse was assessed using the Childhood Experience of Care and Abuse Questionnaire. Results: Neither lifetime cannabis use nor reported exposure to childhood abuse was associated with psychotic disorder when the other environmental variable was taken into account. Although the combination of the two risk factors raised the odds for psychosis by nearly three times (adjusted OR = 2.94, 95% CI: 1.44–6.02, P = 0.003), no evidence of interaction was found (adjusted OR = 1.46, 95% CI: −0.54 to 3.46, P = 0.152). Furthermore, the association of high-potency cannabis and daily consumption with psychosis was at least partially independent of the effect of childhood abuse. Conclusions: The heavy use of high-potency cannabis increases the risk of psychosis but, in addition, smoking of traditional resin (hash) and less than daily cannabis use may increase the risk for psychosis when combined with exposure to severe childhood abuse.</p

Development and Validation of Predictive Model for a Diagnosis of First Episode Psychosis Using the Multinational EU-GEI Case-control Study and Modern Statistical Learning Methods

Background and Hypothesis: It is argued that availability of diagnostic models will facilitate a more rapid identification of individuals who are at a higher risk of first episode psychosis (FEP). Therefore, we developed, evaluated, and validated a diagnostic risk estimation model to classify individual with FEP and controls across six countries. Study Design: We used data from a large multi-center study encompassing 2627 phenotypically well-defined participants (aged 18-64 years) recruited from six countries spanning 17 research sites, as part of the European Network of National Schizophrenia Networks Studying Gene-Environment Interactions study. To build the diagnostic model and identify which of important factors for estimating an individual risk of FEP, we applied a binary logistic model with regularization by the least absolute shrinkage and selection operator. The model was validated employing the internal-external cross-validation approach. The model performance was assessed with the area under the receiver operating characteristic curve (AUROC), calibration, sensitivity, and specificity. Study Results: Having included preselected 22 predictor variables, the model was able to discriminate adults with FEP and controls with high accuracy across all six countries (rangesAUROC=0.84-0.86). Specificity (range=73.9-78.0%) and sensitivity (range=75.6-79.3%) were equally good, cumulatively indicating an excellent model accuracy; though, calibration slope for the diagnostic model showed a presence of some overfitting when applied specifically to participants from France, the UK, and The Netherlands. Conclusions: The new FEP model achieved a good discrimination and good calibration across six countries with different ethnic contributions supporting its robustness and good generalizability.</p

The relationship between genetic liability, childhood maltreatment, and IQ: findings from the EU-GEI multicentric case-control study

This study investigated if the association between childhood maltreatment and cognition among psychosis patients and community controls was partially accounted for by genetic liability for psychosis. Patients with first-episode psychosis (N = 755) and unaffected controls (N = 1219) from the EU-GEI study were assessed for childhood maltreatment, intelligence quotient (IQ), family history of psychosis (FH), and polygenic risk score for schizophrenia (SZ-PRS). Controlling for FH and SZ-PRS did not attenuate the association between childhood maltreatment and IQ in cases or controls. Findings suggest that these expressions of genetic liability cannot account for the lower levels of cognition found among adults maltreated in childhood

The association between reasons for first using cannabis, later pattern of use, and risk of first-episode psychosis: the EU-GEI case-control study

BACKGROUND: While cannabis use is a well-established risk factor for psychosis, little is known about any association between reasons for first using cannabis (RFUC) and later patterns of use and risk of psychosis. METHODS: We used data from 11 sites of the multicentre European Gene-Environment Interaction (EU-GEI) case-control study. 558 first-episode psychosis patients (FEPp) and 567 population controls who had used cannabis and reported their RFUC.We ran logistic regressions to examine whether RFUC were associated with first-episode psychosis (FEP) case-control status. Path analysis then examined the relationship between RFUC, subsequent patterns of cannabis use, and case-control status. RESULTS: Controls (86.1%) and FEPp (75.63%) were most likely to report 'because of friends' as their most common RFUC. However, 20.1% of FEPp compared to 5.8% of controls reported: 'to feel better' as their RFUC (χ2 = 50.97; p < 0.001). RFUC 'to feel better' was associated with being a FEPp (OR 1.74; 95% CI 1.03-2.95) while RFUC 'with friends' was associated with being a control (OR 0.56; 95% CI 0.37-0.83). The path model indicated an association between RFUC 'to feel better' with heavy cannabis use and with FEPp-control status. CONCLUSIONS: Both FEPp and controls usually started using cannabis with their friends, but more patients than controls had begun to use 'to feel better'. People who reported their reason for first using cannabis to 'feel better' were more likely to progress to heavy use and develop a psychotic disorder than those reporting 'because of friends'