Helen Baldwin

BACKGROUND: The impact of precision psychiatry for clinical practice has not been systematically appraised. This study aims to provide a comprehensive review of validated prediction models to estimate the individual risk of being affected with a condition (diagnostic), developing outcomes (prognostic), or responding to treatments (predictive) in mental disorders. METHODS: PRISMA/RIGHT/CHARMS-compliant systematic review of the Web of Science, Cochrane Central Register of Reviews, and Ovid/PsycINFO databases from inception until July 21, 2019 (PROSPERO CRD42019155713) to identify diagnostic/prognostic/predictive prediction studies that reported individualized estimates in psychiatry and that were internally or externally validated or implemented. Random effect meta-regression analyses addressed the impact of several factors on the accuracy of prediction models. FINDINGS: Literature search identified 584 prediction modeling studies, of which 89 were included. 10.4% of the total studies included prediction models internally validated (n = 61), 4.6% models externally validated (n = 27), and 0.2% (n = 1) models considered for implementation. Across validated prediction modeling studies (n = 88), 18.2% were diagnostic, 68.2% prognostic, and 13.6% predictive. The most frequently investigated condition was psychosis (36.4%), and the most frequently employed predictors clinical (69.5%). Unimodal compared to multimodal models (β = .29, P = .03) and diagnostic compared to prognostic (β = .84, p < .0001) and predictive (β = .87, P = .002) models were associated with increased accuracy. INTERPRETATION: To date, several validated prediction models are available to support the diagnosis and prognosis of psychiatric conditions, in particular, psychosis, or to predict treatment response. Advancements of knowledge are limited by the lack of implementation research in real-world clinical practice. A new generation of implementation research is required to address this translational gap.

Background The clinical high‐risk state for psychosis (CHR‐P) paradigm has facilitated the implementation of psychosis prevention into clinical practice; however, advancements in adolescent CHR‐P populations are less established. Methods We performed a PRISMA/MOOSE‐compliant systematic review of the Web of Science database, from inception until 7 October 2019, to identify original studies conducted in CHR‐P children and adolescents (mean age &lt;18 years). Findings were systematically appraised around core themes: detection, prognosis and intervention. We performed meta‐analyses (employing Q statistics and I 2 test) regarding the proportion of CHR‐P subgroups, the prevalence of baseline comorbid mental disorders, the risk of psychosis onset and the type of interventions received at baseline. Quality assessment and publication bias were also analysed. Results Eighty‐seven articles were included ( n = 4,667 CHR‐P individuals). Quality of studies ranged from 3.5 to 8 (median 5.5) on a modified Newcastle–Ottawa scale. Detection : Individuals were aged 15.6 ± 1.2 years (51.5% males), mostly (83%) presenting with attenuated positive psychotic symptoms. CHR‐P psychometric accuracy improved when caregivers served as additional informants. Comorbid mood (46.4%) and anxiety (31.4%) disorders were highly prevalent. Functioning and cognition were impaired. Neurobiological studies were inconclusive. Prognosis : Risk for psychosis was 10.4% (95%CI: 5.8%–18.1%) at 6 months, 20% (95%CI: 15%–26%) at 12 months, 23% (95%CI: 18%–29%) at 24 months and 23.3% (95%CI: 17.3%–30.7%) at ≥36 months. Interventions : There was not enough evidence to recommend one specific treatment (including cognitive behavioural therapy) over the others (including control conditions) to prevent the transition to psychosis in this population. Randomised controlled trials suggested that family interventions, cognitive remediation and fish oil supplementation may improve cognition, symptoms and functioning. At baseline, 30% of CHR‐P adolescents were prescribed antipsychotics and 60% received psychotherapy. Conclusions It is possible to detect and formulate a group‐level prognosis in adolescents at risk for psychosis. Future interventional research is required.

Importance: The ENIGMA clinical high risk (CHR) for psychosis initiative, the largest pooled neuroimaging sample of individuals at CHR to date, aims to discover robust neurobiological markers of psychosis risk. Objective: To investigate baseline structural neuroimaging differences between individuals at CHR and healthy controls as well as between participants at CHR who later developed a psychotic disorder (CHR-PS+) and those who did not (CHR-PS-). Design, Setting, and Participants: In this case-control study, baseline T1-weighted magnetic resonance imaging (MRI) data were pooled from 31 international sites participating in the ENIGMA Clinical High Risk for Psychosis Working Group. CHR status was assessed using the Comprehensive Assessment of At-Risk Mental States or Structured Interview for Prodromal Syndromes. MRI scans were processed using harmonized protocols and analyzed within a mega-analysis and meta-analysis framework from January to October 2020. Main Outcomes and Measures: Measures of regional cortical thickness (CT), surface area, and subcortical volumes were extracted from T1-weighted MRI scans. Independent variables were group (CHR group vs control group) and conversion status (CHR-PS+ group vs CHR-PS- group vs control group). Results: Of the 3169 included participants, 1428 (45.1%) were female, and the mean (SD; range) age was 21.1 (4.9; 9.5-39.9) years. This study included 1792 individuals at CHR and 1377 healthy controls. Using longitudinal clinical information, 253 in the CHR-PS+ group, 1234 in the CHR-PS- group, and 305 at CHR without follow-up data were identified. Compared with healthy controls, individuals at CHR exhibited widespread lower CT measures (mean [range] Cohen d = -0.13 [-0.17 to -0.09]), but not surface area or subcortical volume. Lower CT measures in the fusiform, superior temporal, and paracentral regions were associated with psychosis conversion (mean Cohen d = -0.22; 95% CI, -0.35 to 0.10). Among healthy controls, compared with those in the CHR-PS+ group, age showed a stronger negative association with left fusiform CT measures (F = 9.8; P < .001; q < .001) and left paracentral CT measures (F = 5.9; P = .005; q = .02). Effect sizes representing lower CT associated with psychosis conversion resembled patterns of CT differences observed in ENIGMA studies of schizophrenia (ρ = 0.35; 95% CI, 0.12 to 0.55; P = .004) and individuals with 22q11.2 microdeletion syndrome and a psychotic disorder diagnosis (ρ = 0.43; 95% CI, 0.20 to 0.61; P = .001). Conclusions and Relevance: This study provides evidence for widespread subtle, lower CT measures in individuals at CHR. The pattern of CT measure differences in those in the CHR-PS+ group was similar to those reported in other large-scale investigations of psychosis. Additionally, a subset of these regions displayed abnormal age associations. Widespread disruptions in CT coupled with abnormal age associations in those at CHR may point to disruptions in postnatal brain developmental processes.

INTRODUCTION: Clinical trials involving patients with Alzheimer's disease (AD) continue to try to identify disease-modifying treatments. Although trials are designed to meet regulatory and registration requirements, many do not measure outcomes of the disease most relevant to key stakeholders. METHODS: A systematic review sought research that elicited information from people with AD, their caregivers, and health-care professionals on which outcomes of the disease were important. Studies published in any language between 2008 and 2017 were included. RESULTS: Participants in 34 studies described 32 outcomes of AD. These included clinical (memory, mental health), practical (ability to undertake activities of daily living, access to health information), and personal (desire for patient autonomy, maintenance of identity) outcomes of the disease. DISCUSSION: Evidence elicited directly from the people most affected by AD reveals a range of disease outcomes that are relevant to them but are not commonly captured in clinical trials of new treatments.