Lack of robust meta‐analytic evidence to favour cognitive behavioural therapy for prevention of psychosis

Fusar‐Poli, Paolo; Raduà, Joaquim; Jauhar, Sameer

doi:10.1002/wps.20896

Cited by 7 publications

(5 citation statements)

References 9 publications

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“…Relatedly, future studies should aim to determine which interventions are most appropriate for different levels of risk and patterns of symptom progression (eg, conversion to psychosis, continuity of CHR-P symptoms, or symptom remission). The existing intervention literature is inconclusive as to whether psychosocial interventions may help to delay conversion to psychosis, but many are associated with reduction in prodromal symptom severity . This body of literature may benefit from parsing heterogeneity in assessing treatment outcomes by level of risk; however, calls for more precision in treatment selection in a manner that accounts for clinical heterogeneity within the CHR-P syndrome have largely remained unanswered .…”

Section: Discussionmentioning

confidence: 99%

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RETRACTED: Dynamic Prediction of Outcomes for Youth at Clinical High Risk for Psychosis

Worthington,

Addington,

Bearden

et al. 2023

JAMA Psychiatry

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ImportanceLeveraging the dynamic nature of clinical variables in the clinical high risk for psychosis (CHR-P) population has the potential to significantly improve the performance of outcome prediction models.ObjectiveTo improve performance of prediction models and elucidate dynamic clinical profiles using joint modeling to predict conversion to psychosis and symptom remission.Design, Setting, and ParticipantsData were collected as part of the third wave of the North American Prodrome Longitudinal Study (NAPLS 3), which is a 9-site prospective longitudinal study. Participants were individuals aged 12 to 30 years who met criteria for a psychosis-risk syndrome. Clinical, neurocognitive, and demographic variables were collected at baseline and at multiple follow-up visits, beginning at 2 months and up to 24 months. An initial feature selection process identified longitudinal clinical variables that showed differential change for each outcome group across 2 months. With these variables, a joint modeling framework was used to estimate the likelihood of eventual outcomes. Models were developed and tested in a 10-fold cross-validation framework. Clinical data were collected between February 2015 and November 2018, and data were analyzed from February 2022 to December 2023.Main Outcomes and MeasuresPrediction models were built to predict conversion to psychosis and symptom remission. Participants met criteria for conversion if their positive symptoms reached the fully psychotic range and for symptom remission if they were subprodromal on the Scale of Psychosis-Risk Symptoms for a duration of 6 months or more.ResultsOf 488 included NAPLS 3 participants, 232 (47.5%) were female, and the mean (SD) age was 18.2 (3.4) years. Joint models achieved a high level of accuracy in predicting conversion (balanced accuracy [BAC], 0.91) and remission (BAC, 0.99) compared with baseline models (conversion: BAC, 0.65; remission: BAC, 0.60). Clinical variables that showed differential change between outcome groups across a 2-month span, including measures of symptom severity and aspects of functioning, were also identified. Further, intra-individual risks for each outcome were more negatively correlated when using joint models (r = −0.92; P &lt; .001) compared with baseline models (r = −0.50; P &lt; .001).Conclusions and RelevanceIn this study, joint models significantly outperformed baseline models in predicting both conversion and remission, demonstrating that monitoring short-term clinical change may help to parse heterogeneous dynamic clinical trajectories in a CHR-P population. These findings could inform additional study of targeted treatment selection and could move the field closer to clinical implementation of prediction models.

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Section: Discussionmentioning

confidence: 99%

“…Model calibration was assessed using the Brier score and calibration slope. 38 For each model, the median likelihood of achieving each outcome was used as the cutoff for determining correct outcome prediction. Performance metrics for each joint model were averaged across the 10 folds.…”

Section: Model Validationmentioning

confidence: 99%

RETRACTED: Dynamic Prediction of Outcomes for Youth at Clinical High Risk for Psychosis

Worthington,

Addington,

Bearden

et al. 2023

JAMA Psychiatry

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“…Our findings also point to the value of preventive intervention research in CAMHS. There is intense interest in pharmacological and psychosocial treatments that might help to prevent psychosis and bipolar disorder 60 . CAMHS patients represent an ideal group for this research, since this population already receives a wide variety of interventions.…”

Section: Discussionmentioning

confidence: 99%

Potential for prediction of psychosis and bipolar disorder in Child and Adolescent Mental Health Services: a longitudinal register study of all people born in Finland in 1987

Lång

Ramsay

Yates³

et al. 2022

World Psychiatry

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Current strategies to predict psychosis identify only a small proportion of individuals at risk. Additional strategies are needed to increase capacity for pre diction and prevention of serious mental illness, ideally during childhood and adolescence. One possible approach would be to investigate systems in which psychosis risk factors are concentrated during childhood. One notable such system is represented by Child and Adolescent Mental Health Services (CAMHS). Although psychotic disorders are uncommon in CAMHS, many risk factors for psychosis are highly prevalent in young people who enter this system. We hypothesized, therefore, that youth attending CAMHS would be a highrisk group for psychosis if followed into adulthood and, furthermore, that CAMHS systems would capture a substantial proportion of future psychosis cases. We constructed a total population cohort study of all Finns born in 1987 (N=55,875), linking together extensive register data on health care contacts from birth through age 28 years. We identified all individuals diagnosed with a psychotic or bipolar disorder by age 28 (N=1,785). The risk of psychosis/bipolar disorder by age 28 years was 1.8% for individuals who had not attended CAMHS during childhood or adolescence, whereas it was 12.8% for those with a history of any outpatient CAMHS contact (odds ratio, OR=7.9, 95% CI: 7.28.7). Furthermore, the risk of psychosis/bipolar disorder by age 28 years was 2.3% for individuals without a history of inpatient CAMHS admission, whereas it was 24.0% for those with a history of inpatient CAMHS admission (OR=13.3, 95% CI: 11.914.9), and 36.5% for those with a history of inpatient CAMHS admission in adolescence (age 1317 years) (OR=24.2, 95% CI: 21.227.6). Individuals who attended CAMHS but received no mental disorder diagnosis had an equally high risk of subsequently developing a psychosis/bipolar disorder as individuals who did receive a diagnosis (OR=0.9, 99.5% CI: 0.71.1). Compared to other CAMHS attendees, individuals who developed psychosis or bipolar disorder were more likely to have had an initial CAMHS diagnosis of depressive or other mood disorder (OR=2.3, 99.5% CI: 1.63.0) and disruptive behaviour disorder (OR=1.7, 99.5% CI: 1.22.5). Of all psychosis/bipolar diagnoses by age 28 years, 50.2% occurred in individuals who had, at some point in childhood or adolescence, attended CAMHS, indicating that CAMHS represent not only a highrisk but also a highcapacity system for prediction of psychosis/bipolar disorder. These findings suggest an enormous, untapped potential for largescale psychosis/bipolar disorder prediction and prevention research within existing specialist CAMHS.

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“…Consequently, patients with BPE have several unmet needs that are not addressed by current mental health services. For example, only 3% of BLIPS engage with the minimum effective dose of cognitive behavioural therapy, which is also of questionable efficacy for this patient population (Fusar-Poli et al ., 2019a , 2019b , 2021a ).…”

Section: Discussionmentioning

confidence: 99%

Clinical outcomes in brief psychotic episodes: a systematic review and meta-analysis

Provenzani

Pablo

Arribas³

et al. 2021

Epidemiol Psychiatr Sci

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Aims Patients with brief psychotic episodes (BPE) have variable and fluctuating clinical outcomes which challenge psychiatric care. Our meta-analysis aims at providing a comprehensive summary of several clinical outcomes in this patient group. Methods A multistep systematic PRISMA/MOOSE-compliant literature search was performed for articles published from inception until 1st March 2021. Web of Science database was searched, complemented by manual search of original articles reporting relevant outcomes (psychotic recurrence, prospective diagnostic change or stability, remission, quality of life, functional status, mortality and their predictors) for patients diagnosed with acute and transient psychotic disorders (ATPD), brief psychotic disorders (BPD), brief intermittent psychotic symptoms (BIPS) and brief limited intermittent psychotic symptoms (BLIPS). Random-effects methods and Q-statistics were employed, quality assessment with Newcastle-Ottawa Scale, assessment of heterogeneity with I2 index, sensitivity analyses (acute polymorphic psychotic disorders, APPD) and multiple meta-regressions, assessment of publication bias with funnel plot, Egger's test and meta-regression (psychotic recurrence and sample size). Results A total of 91 independent articles (n = 94 samples) encompassed 37 ATPD, 24 BPD, 19 BLIPS and 14 BIPS samples, totalling 15 729 individuals (mean age: 30.89 ± 7.33 years, mean female ratio: 60%, 59% conducted in Europe). Meta-analytical risk of psychotic recurrence for all BPE increased from 15% (95% confidence interval (CI) 12–18) at 6 months, 25% (95% CI 22–30) at 12 months, 30% (95% CI 27–33) at 24 months and 33% (95% CI 30–37) at ⩾36 months follow-up, with no differences between ATPD, BPD, BLIPS and BIPS after 2 years of follow-up. Across all BPE, meta-analytical proportion of prospective diagnostic stability (average follow-up 47 months) was 49% (95% CI 42–56); meta-analytical proportion of diagnostic change (average follow-up 47 months) to schizophrenia spectrum psychoses was 19% (95% CI 16–23), affective spectrum psychoses 5% (95% CI 3–7), other psychotic disorders 7% (95% CI 5–9) and other (non-psychotic) mental disorders 14% (95% CI 11–17). Prospective diagnostic change within APPD without symptoms of schizophrenia was 34% (95% CI 24–46) at a mean follow-up of 51 months: 18% (95% CI 11–30) for schizophrenia spectrum psychoses and 17% (95% CI 10–26) for other (non-psychotic) mental disorders. Meta-analytical proportion of baseline employment was 48% (95% CI 38–58), whereas there were not enough data to explore the other outcomes. Heterogeneity was high; female ratio and study quality were negatively and positively associated with risk of psychotic recurrence, respectively. There were no consistent factor predicting clinical outcomes. Conclusions Short-lived psychotic episodes are associated with a high risk of psychotic recurrences, in particular schizophrenia spectrum disorders. Other clinical outcomes remain relatively underinvestigated. There are no consistent prognostic/predictive factors.

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Lack of robust meta‐analytic evidence to favour cognitive behavioural therapy for prevention of psychosis

Cited by 7 publications

References 9 publications

RETRACTED: Dynamic Prediction of Outcomes for Youth at Clinical High Risk for Psychosis

RETRACTED: Dynamic Prediction of Outcomes for Youth at Clinical High Risk for Psychosis

Potential for prediction of psychosis and bipolar disorder in Child and Adolescent Mental Health Services: a longitudinal register study of all people born in Finland in 1987

Clinical outcomes in brief psychotic episodes: a systematic review and meta-analysis

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