The use of clinical and biological characteristics to predict outcome following First Episode Psychosis

Abstract

Objective: Psychotic illnesses such as schizophrenia and other non-affective psychoses are heterogeneous in disease course and functional outcomes. We review evidence from investigations in clinical psychiatry, neuroimaging, neurocognition, and blood biomarker research suggesting that distinct bio-psycho-social patterns exist at the onset and during the early phase of a First Episode Psychosis (FEP), which can describe the risk of individual illness progression and functional trajectories.Method: A selective literature review was performed on articles drawn from Medline searches for relevant key words. A simulation model was constructed from data derived from two recent publications, selected as examples of studies that investigated multivariate predictors of long-term outcome following FEP. Results:We illustrate how illness trajectories following FEP could be described based on multimodal sociodemographic, clinical, psychological, and neurobiological information. A clinical modeling simulation shows that risk trajectories for achieving long-term favorable or unfavorable outcomes can differ significantly depending on baseline characteristics in combination with MRI and functional measurements within 6 months of disease onset. Conclusions:Multimodal trajectory modeling may be useful to describe longitudinal outcomes following FEP. Rich longitudinal data on predictors and outcomes, and better integration of multimodal (sociodemographic, clinical, psychological, biological) data, are required to operationalize this approach. This technique may improve our understanding of course of illness and help to provide a more personalized approach to the assessment and treatment of people presenting with FEP.

Predictors of functioning in people suffering from first‐episode psychosis 1 year into entering early intervention service in Hong Kong

“…Overall, our study found similar predictors of functioning levels in people suffering from first-episode psychosis as in western studies with younger cohorts of subjects, in which gender, 2,5-7 educational attainment, [6][7][8][9] psychopathology 2,4,5,7,12,13,16-20 and baseline functioning 21 were found to be important predictors of longer-term functioning. However, we failed to demonstrate any relationship between age and duration of untreated psychosis with functional outcomes, a finding shared by some overseas studies.…”

“…However, we failed to demonstrate any relationship between age and duration of untreated psychosis with functional outcomes, a finding shared by some overseas studies. 4,6,10,11,15 The lack of predictive value of duration of untreated psychosis in this sample and some other recent studies, was likely due to the fact that the duration of untreated psychosis had been shortened significantly with the introduction of early intervention service, making it less likely to detect a difference in functioning due to variations in the duration of untreated psychosis.…”

“…4,7,11 Premorbid adjustment was also well established to be associated with functional outcomes in people suffering from psychosis. 2,6,[8][9][10][11][12] Being diagnosed with schizophrenia remained a poor prognostic indicator of functioning. 8 Many studies argued that a longer duration of untreated psychosis was indicative of poorer functional outcomes, 7,13,14 yet negative studies existed.…”

“…10,15 While more severe positive, negative, depressive and cognitive symptoms were all indicative of poorer functional status, 2,4,5,7,12,13,[16][17][18][19][20] early symptomatic remission and functional recovery at 6-12 months after initiation of treatment appeared to be more predictive of longerterm functional outcomes. 6,9,[21][22][23][24] The early intervention service in Hong Kong was established in 2001, and was named EASY, that is, Early Assessment Service for Young people with early psychosis. The Service provided 2-year case management service for young people aged 15-25 suffering from first-episode psychosis.…”

A systematic review and checklist presenting the main challenges for health economic modeling in personalized medicine: towards implementing patient-level models

“…From these publications the full text was screened, resulting in five more exclusions from the sample for different reasons (i.e. papers presenting a biomedical model [32], a prediction model [33], or that did not include diagnostics or personalized risk estimations [34][35][36]). Analyzing the full text of the included articles resulted in an enrichment of the sample with 13 additional publications by cross-referencing.…”