Given the global burden of psychotic disorders, the identification of patients with early-onset psychosis (EOP; that is, onset before the age of 18) at higher risk of adverse outcome should be a priority. A systematic search of Pubmed, Embase, and PsycInfo (1980 through August 2014) was performed to identify longitudinal observational studies assessing correlates and/or predictors of clinical, functional, cognitive, and biological outcomes in EOP. Seventy-five studies were included in the review. Using multivariate models, the most replicated predictors of worse clinical, functional, cognitive, and biological outcomes in EOP were premorbid difficulties and symptom severity (especially of negative symptoms) at baseline. Longer duration of untreated psychosis (DUP) predicted worse clinical, functional, and cognitive outcomes. Higher risk of attempting suicide was predicted by greater severity of psychotic illness and of depressive symptoms at the first episode of psychosis. Age at onset and sex were not found to be relevant predictors of outcome in most multivariate models, whereas studies using bivariate analyses yielded inconsistent results. Lower intelligence quotient at baseline predicted lower insight at follow-up, worse functional outcomes, and a diagnostic outcome of schizophrenia. Biological predictors of outcome in EOP have been little studied and have not been replicated. Lower levels of antioxidants at baseline predicted greater brain volume changes and worse cognitive functioning at follow-up, whereas neuroimaging markers such as regional cortical thickness and gray matter volume at baseline predicted remission and better insight at follow-up, respectively. EOP patients with poorer premorbid adjustment and prominent negative symptoms at initial presentation are at risk of poor outcome. They should therefore be the target of careful monitoring and more intensive interventions to address whether the disease course can be modified in this especially severely affected group. Early intervention strategies to reduce DUP may also improve outcome in EOP.
Neuropsychiatric disorders are the greatest contributor to global burden of disease in adolescents and young adults worldwide.1 There has been growing interest in prevention and early intervention in psychiatry in recent years,2,3 as it has become increasingly evident that effective management of child and adolescent psychiatric disorders can help prevent the development of persistent mental health concerns in adulthood4,5 and that early intervention strategies can positively impact long-term outcome of severe mental disorders, especially in young people.6,
As neurodevelopmental disorders, schizophrenia and other psychoses usually show their first manifestations during childhood and adolescence, and 11–18% of patients present with their first episode of psychosis before age 18 (early-onset psychosis; EOP).10,11 Outcome in EOP is negatively affected by the impact of illness onset on individuals whose neurobiological and psychosocial development is not yet complete,12 leading to 50–60% of EOP patients with poor outcome.13 Although almost 40% of patients with schizophrenia will achieve social or functional recovery,14 and some will have a positive outcome even if medication is discontinued,15 there is still a large group of patients at risk of poor outcome. This group may constitute an even larger proportion in the population with an early-onset form of the illness, which makes identification of the risk factors associated with a poor outcome in this population especially valuable. This would facilitate more intensive and tailored interventions in those patients deemed to be at higher risk of having poor outcome, facilitating a rationalization of resources’ use and expectations.
Despite the interest of identifying predictors of outcome in this population, studies are still scarce and have shown contradictory results. One previous systematic review of predictors of outcome in adolescent first episode psychosis in papers published in 1989–1999 did not find any variable significantly predictive of diagnostic or overall outcome, except for (i) presence of abnormal premorbid personality traits, which was suggestive of a diagnostic outcome of schizophrenia, and (ii) lower functioning before and after the first episode of psychosis, which was associated both with a diagnostic outcome of schizophrenia and poorer overall outcome.16 Similarly, a more recent non-systematic review reported the following predictors of chronic long-term course in early-onset schizophrenia: younger age at illness onset, insidious onset, positive family history of non-affective psychosis, developmental delays, poor premorbid adjustment, longer duration of the first episode of psychosis, greater symptom severity and poorer psychosocial functioning at discharge, and higher number of relapses through follow-up.17
Given the potential clinical relevance of identifying predictors of outcome in children and adolescents with psychosis, we aimed to perform a comprehensive systematic review of the literature to date on predictors and correlates of clinical, functional, cognitive, and biological outcomes in EOP. We hypothesized that there would be a set of main predictors that overlap with those reported for adult-onset psychoses, and that those related to premorbid difficulties and developmental delays would play an especially important role in this population.
Materials and methods
A systematic two-step literature search was performed following the guidelines of the PRISMA statement.18 A Pubmed, Embase, and PsycInfo search (1980 through August 2014) was performed using the following search terms: (early-onset, childhood-onset, adolescent-onset, child*, adolescent*) combined with (psychosis, psychotic, schizophrenia, first-episode psychosis, first-episode psychotic, bipolar psychotic). In a second step, we manually reviewed the reference lists of the selected studies and previous reviews to identify any potentially relevant studies not identified by the computerized search.
The initial literature search yielded 3,750 studies and the manual search identified 47 additional studies. After removing duplicates, 2,293 potential studies were identified.
The abstracts of the 2,293 resulting studies were assessed for eligibility using the following hierarchical criteria:
Studies were peer-reviewed original articles published in English.
Studies had a longitudinal and observational design. As the main objective of this review was to assess predictors and correlates of the course of EOP and not specific therapeutic interventions, studies assessing predictive and outcome variables in the context of a clinical trial were not included.
Participants had a diagnosis of schizophrenia or other psychotic disorders according to the Diagnostic and Statistical Manual of Mental Disorders (DSM) criteria - DSM-III, DSM-III-R, DSM-IV, DSM-IV-TR, or to the International Classification of Diseases (ICD) criteria - ICD-9 or ICD-10. This limitation was applied since, before the DSM-III, the definition of categories such as childhood-onset schizophrenia included clinical pictures that would currently be classified under the diagnostic category of autism spectrum disorders.19
Onset of psychotic illness in childhood or adolescence (that is, either the upper limit of the range of age at onset was <18 years or the onset was defined by the authors as a ‘childhood onset’, ‘adolescence onset’, and/or ‘early-onset’). In four studies, the upper limit of the range of the age at onset was >18, but mean age at onset or at baseline was <18 and the authors referred to these as participants with EOP.20,
21,In two studies, the range of the age at onset or at baseline was not provided, but mean age at baseline was <18 and the authors referred to the sample as adolescent onset.24,25 22, 23
Studies assessed clinical, functional, cognitive, and/or biological (that is, neuroimaging, biochemical) outcome measures or suicide risk. This broad definition of outcome was used to provide a more comprehensive perspective on the issue and to increase the clinical applicability of the results.
Studies assessed the association between demographic, clinical, functional, cognitive, and/or biological baseline variables and follow-up outcome measures using bivariate (for example, Student’s t-tests, analysis of variance, χ 2-tests, correlations) or multivariate (for example, linear/logistic regression models or novel multivariate machine-learning methods) techniques.
When the Abstract did not provide sufficient information to assess study eligibility, the full text was consulted. In instances where the full text was not available, the authors were contacted by e-mail. Of the 2,293 assessed studies, 214 full-text articles were selected and further assessed for eligibility. Of those, 75 studies fulfilled all the inclusion criteria and were ultimately included in the review. Figure 1 shows the flowchart of the literature review process.
Data were extracted by two reviewers (CMD-C, AR-Q) and supervised by an external reviewer (LP-C). For each study, the following data were retrieved: author names, year of publication, name or acronym of the cohort, design (retrospective, prospective, or mixed), number of subjects, demographic variables (age at baseline, proportion of male subjects), clinical variables (age at onset, diagnosis distribution), length of follow-up, outcome measures, and predictors/correlates of outcome. Papers reporting on the same cohort were included as long as they provided additional information on any of the relevant outcome measures. Discrepancies were resolved by discussion.
Data synthesis and analysis
Studies were classified according to the type of outcome measures assessed (clinical, functional, cognitive, biological, or suicide risk), length of follow-up, and study cohort. For reporting purposes, findings are displayed (i) separately for studies using multivariate/regression models and those using bivariate analyses and (ii) only if associations/predictions reach a significance threshold of P<0.05.
Table 1 provides a summary of the reported significant predictors (in studies using multivariate/regression models) or correlates (in studies using bivariate approaches) for each outcome category. For further description of the characteristics and main findings of the reviewed articles (for example, sample size, design, statistical methods, outcomes assessed), see Supplementary Table 1.
Using multivariate models, premorbid difficulties (that is, poorer premorbid adjustment, history of developmental disorder) and greater symptom severity (especially negative symptoms) at baseline were consistently found to be significant predictors of worse outcome across all areas (clinical, functional, cognitive, and neuroimaging). This is also true for studies using bivariate analyses (Table 1). A diagnosis of schizophrenia was a significant predictor of greater disability, lower global functioning, and poorer quality of life at follow-up. Longer duration of untreated psychosis (DUP) was a significant predictor of worse clinical, functional, and cognitive outcomes in multivariate models (Table 1). However, the association between DUP and clinical or functional outcomes was not replicated in an EOP sample with longer DUP using a bivariate approach.26
Although sex has not been found to be a relevant predictor in most studies using regression models,27,
Lower age at onset has been found to predict worse quality of psychiatric care and poorer social, educational, and occupational functioning in multivariate models, but is not a consistently reported predictor of these and other outcomes in studies using regression models27,28,33 (Table 1). In bivariate studies, lower age at onset has been found to be associated with less likelihood of remission, worse global functioning, and greater disability, although there are also studies that do not find this association.31,34
Cognitive variables such as lower intelligence quotient (IQ) at baseline have been found to predict worse functional outcome, a diagnostic outcome of schizophrenia, or poorer insight at follow-up in multivariate models (Table 1).
Using multivariate models, biological predictors such as lower antioxidant levels at baseline have been found to predict greater brain volume changes and worse cognitive functioning at follow-up. Among neuroimaging markers, cortical thickness and GM volume at baseline in different brain regions have been found to predict remission and insight at follow-up, respectively (Table 1). However, other studies using multivariate techniques have not found significant associations/predictions between biological variables and outcomes such as diagnosis at follow-up in first-episode patients.35
In this systematic review, we found that the most replicated predictors of worse clinical, functional, cognitive, and/or biological outcomes in EOP are a positive history of premorbid difficulties (developmental delays and poor premorbid adjustment), greater symptom severity (especially of negative symptoms) at baseline and longer DUP. Greater initial symptom severity is also a good predictor of attempting suicide during follow-up, together with greater severity of depressive symptoms at baseline or at discharge after the first episode. Cognitive variables such as lower IQ at baseline predict poorer insight at follow-up, worse functional outcomes, and a diagnostic outcome of schizophrenia. Biochemical variables such as lower blood antioxidant levels at baseline predict greater brain volume changes and worse cognitive functioning at follow-up, whereas regional brain thickness and volume measures of different brain regions at baseline predict remission status and insight at follow-up, respectively. Age at psychosis onset and sex do not seem to be consistent predictors of any outcome in EOP samples.
It has been proposed that developmental continuity may exist from premorbid difficulties to primary negative symptoms in EOP.36 The coexistence of severe premorbid impairments and negative symptoms delineate a large subgroup of EOP individuals with higher neurodevelopmental load who are eventually at risk of a deleterious course.37 This would be consistent with our finding that poorer premorbid adjustment and more prominent negative symptoms at illness onset are core predictors of functional and clinical outcomes in EOP and would further support the neurodevelopmental nature of psychotic disorders,38 with early-onset forms at one extreme of the continuum of disease severity and genetic liability.39 Indeed, both negative symptoms and premorbid adjustment have also been found to be good predictors of outcome in adult-onset psychosis,40,
The fact that patients with early-onset schizophrenia spectrum disorders usually present with more severe premorbid impairments and initial negative symptoms than other types of EOP8,11,
Moreover, the association of a diagnosis of schizophrenia with worse outcome should also be appraised in light of the fact that most EOP studies use a follow-up diagnosis to categorize patients into diagnostic subgroups. This strategy can help more accurately define patient diagnosis as it minimizes the impact of diagnostic instability inherent in first episodes of EOP.57 However, if a follow-up diagnosis of schizophrenia is used as a predictor of outcome, there is a risk that those patients showing poorer outcome are also those more likely to receive this diagnosis during follow-up.
Insidious onset and longer DUP are well-replicated predictive factors of worse outcome in EOP in keeping with what has been found in adult-onset psychosis samples.58,
Sex and age at onset have yielded inconsistent associations with outcome in EOP, which contrasts with the classical assumption, based on adult-onset studies, that male sex and earlier age at onset are associated with poorer outcomes.70,71 The finding of a worse outcome in adult male patients is frequently contaminated by the fact that males usually have an earlier age at onset and insidious onset.71 In this review, being female was found to be a good predictor of better insight at follow-up and a higher number of readmissions, as well as a significant correlate (by bivariate analyses) of less regional GM loss through follow-up. The lack of a consistent association between sex and outcome in EOP could be due to the fact that females who develop a psychotic disorder during childhood or adolescence probably have a higher load of genetic, neurodevelopmental, or environmental factors leading to significantly earlier onset of the disease in spite of potential protective factors (for example, estrogens). In these individuals, outcome may already be impoverished by the presence of a more severe form of the disorder from the outset. Furthermore, it has also been proposed that prepubertal onset may preclude the protective effect of estrogens on development of the disorder, leading to a more severe course.71 In this review, lower age at onset was found to predict worse quality of psychiatric care and poorer social, educational, and occupational functioning in some multivariate models. However, it was not consistently reported as a significant predictor of functional and other outcomes in other studies using regression models, nor was it a good correlate in studies using bivariate approaches. A narrow age range in studies exclusively including adolescent-onset cases decreases the capability of detecting a significant effect of age at onset. The effect of age at onset (at least in studies using bivariate comparison) seems to be more marked in schizophrenia samples.63,64,72 This may be due to the fact that these are more homogeneous samples in which the contribution of age at onset would be more easily detected than in mixed samples with stronger differences in other relevant predictors (negative symptoms, premorbid functioning), which may obscure the predictive value of age at onset.
Among cognitive predictors of clinical outcomes, lower IQ at baseline was found to predict worse functional outcomes, a diagnostic outcome of schizophrenia, and poorer insight at follow-up in multivariate models, whereas its association with other outcomes such as disability was more inconsistent. Interestingly, higher baseline IQ was found to be a good predictor of functional outcome only for early-onset psychotic bipolar disorder patients in one cohort.56,73 This could be due to a specific effect of IQ in this diagnostic subgroup or to the fact that a higher developmental load in early-onset schizophrenia spectrum disorders may obscure the predictive value of this variable. Other cognitive variables (for example, baseline speed of processing) have been described as good predictors of functional outcomes, but more inconsistently, which highlights the complexity of the interaction between global cognition measures and outcome in EOP and the need to specifically assess the relationship between specific neurocognitive domains and specific dimensions of outcome17,74 or to develop complex predictive models by combining multiple clinical and neuropsychological variables.35 Furthermore, the finding of a strong association between cognition and functional outcome in this review is consistent with results in first episodes of adult-onset schizophrenia, in which cognitive variables and negative symptoms have been found to be the main predictors of long-term functional outcome,74 and points to the potential usefulness of cognitive remediation strategies for improving functional outcome in EOP.75
Although biomarker discovery efforts in psychiatry have gained priority in recent years,76 this review found few studies that focused on the predictive value of biological variables for outcomes in EOP. Lower baseline antioxidant status was found to predict greater loss of GM volume and worse cognitive functioning at follow-up in one cohort.77,78 These findings provide some support for the role of oxidative stress in EOP79 warranting further replication. These findings may also point to the potential applicability of antioxidant strategies to the treatment of EOP patients, as suggested by the promising results of a developmental animal model of schizophrenia indicating that the use of N-acetylcysteine can prevent the later expression of schizophrenia-like traits in adulthood.80 Among neuroimaging markers, cortical thickness and GM volume at baseline in different brain regions were reported to significantly predict remission81 and insight82 at follow-up, respectively, in studies using multivariate models. These are also findings with high potential for translational applicability warranting further replication. Even if implementation of biological predictors in psychiatric settings is still a way off, assessment of their predictive value is warranted by complex predictive models in combination with other relevant clinical, functional, and cognitive variables on a subject-by-subject basis using novel multivariate machine-learning methods. This could help design personalized medicine models by stratifying patients according to their risk of poor outcome or treatment response. These models would help determine whether more intensive interventions (for example, earlier initiation of clozapine treatment or more intensive psychosocial support) would be justified for a defined subset of EOP patients, an issue of great clinical and economic importance as this could improve quality of life in patients with EOP and reduce the burden of disease and cost to national health systems.
This work is subject to several caveats. First, differing outcome measures, length of follow-up, outcome measures, and designs make it difficult to compare studies. Many studies used a retrospective design, with retrospective identification of cases and use of clinical records for assessment of baseline variables. The lack of standardized data-recording methods may have led to inaccuracy or inconsistent reporting of different predictors. Furthermore, attrition rates were high in most of the studies, which may have affected the results to some extent, since it is usually difficult to establish whether discontinuation is due to factors such as lack of compliance or more severe course. Although many studies used appropriate statistical methods to identify predictors, most of the older studies provided only descriptive data and bivariate comparisons between potentially relevant variables, which precluded assessing the impact of potential covariates in the results. This is illustrated by studies finding significant results in bivariate comparisons that do not survive regression analyses.26 That being said, given the scarcity of studies on EOP and relevant outcomes, studies using traditional bivariate comparisons were ultimately included in this review so as to acquire a broader view of the issue. It should also be considered that our findings from multivariate models may have been influenced by the covariates introduced into the models, which differed among studies and were rarely selected systematically. Furthermore, the inclusion of studies using different diagnostic criteria (see Methods) may have also affected our findings to some extent. However, all patients included in this review were diagnosed or re-diagnosed with at least the DSM-III-R, whose diagnostic criteria for psychotic disorders are similar to those of current classification systems. Second, since findings on neurobiological predictors are mostly based on single studies, further replication would be needed to support their predictive value. Third, the exclusion of results based on clinical trials from this review may have prevented us from detecting some significant predictors of treatment response or short-term adherence. For example, data from a 6-month clinical trial found that a better attitude toward antipsychotic medication at a first lifetime psychiatric admission for a first early-onset psychotic episode was significantly related to lower all-cause antipsychotic treatment discontinuation.46 However, we decided not to include results from clinical trials to ascertain predictors of outcome over the course of EOP not related to specific therapeutic interventions.
These limitations notwithstanding, this is to the best of our knowledge the first systematic review to provide a comprehensive overview of recent studies on predictors of clinical, functional, cognitive, and neurobiological outcomes in EOP. Accurate research with potential for replication based on long-term longitudinal studies targeting the search for such predictors is needed.83 This could help identify subjects with EOP at higher risk of poor outcome in whom more intensive and earlier interventions would be warranted. Early intervention services in EOP should aim at shortening DUP and at carefully monitoring patients with poorer adjustment and more severe negative symptoms at first presentation. Novel therapeutic approaches targeting negative and cognitive symptoms are needed to improve the outcome of EOP.
This study was supported by the Spanish Ministry of Economy and Competitiveness, Instituto de Salud Carlos III (FIS PS09/01442 and PI12/1303), CIBERSAM, Madrid Regional Government (S2010/BMD-2422 AGES), European Union Structural Funds and European Union Seventh Framework Programme under grant agreements FP7-HEALTH-2009-2.2.1-2-241909 (Project EU-GEI), FP7-HEALTH-2009-2.2.1-3-242114 (Project OPTiMISE), FP7-HEALTH-2013-2.2.1-2-603196 (Project PSYSCAN), and FP7-HEALTH-2013-2.2.1-2-602478 (Project METSY); Fundación Alicia Koplowitz (FAK2012, FAK2013), Fundación Mutua Madrileña (FMM2009), and ERA-NET NEURON (Network of European Funding for Neuroscience Research) (PIM2010ERN-00642). CMD-C has previously held a Río Hortega grant, Instituto de Salud Carlos III, Spanish Ministry of Economy and Competitiveness, and a grant from Fundación Alicia Koplowitz. LP-C holds a grant from Fundación Alicia Koplowitz and has previously held a Río Hortega grant, Instituto de Salud Carlos III, Spanish Ministry of Economy and Competitiveness. AR-Q holds a Río Hortega grant, Instituto de Salud Carlos III, Spanish Ministry of Economy and Competitiveness.
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