Coping as a predictor of treatment outcome in people at clinical high risk of psychosis.

AIM: The concept of coping is relevant to recent models of psychosis, and people with established psychotic disorders have been found to predominately use maladaptive coping strategies. This study aimed to examine the general coping patterns of people at clinical high risk of psychosis (CHR) and to investigate whether pre-therapy coping behaviour plays a role in predicting responsiveness to early interventions. METHODS: One hundred twenty-eight help-seeking CHR outpatients were randomized into two treatment groups: either receiving integrated psychological intervention (IPI), including cognitive behaviour therapy, or supportive counselling (SC) for 12 months. Of those, 91 persons completed a Stress Coping Questionnaire (SCQ) at intake: 45 in the IPI group and 46 in the SC group. General coping behaviour in this sample was analysed and several regressions were conducted separately for each treatment group to examine coping as a predictor of outcome after 12 months of different forms of treatment. RESULTS: Participants relied significantly more on negative than on positive coping strategies, t(90) = -7.185, P < 0.001, and within the positive strategies, stress control was the most preferred one, t(90) = 10.979, P < 0.001. Several pre-therapy coping strategies significantly predicted improvement in symptomatic outcome in both treatment groups, explaining between 16% and 25% of variance. The predictive value of coping was higher in the SC group. CONCLUSIONS: Maladaptive coping behaviours were found to emerge in the early stages of psychosis and coping behaviour contributed significantly to the prediction of post-treatment symptom improvement. These findings indicate a need for psychosocial support and coping strategy enhancement in people at risk of psychosis.

Multivariate patterns of brain-cognition associations relating to vulnerability and clinical outcome in the at-risk mental states for psychosis.

BACKGROUND: Neuropsychological deficits are a core feature of established psychosis and have been previously linked to fronto-temporo-limbic brain alterations. Both neurocognitive and neuroanatomical abnormalities characterize clinical at-risk mental states (ARMS) for psychosis. However, structure-cognition relationships in the ARMS have not been directly explored using multivariate neuroimaging techniques. METHODS: Voxel-based morphometry and partial least squares were employed to study system-level covariance patterns between whole-brain morphological data and processing speed, working memory, verbal learning/IQ, and executive functions in 40 ARMS subjects and 30 healthy controls (HC). The detected structure-cognition covariance patterns were tested for significance and reliability using non-parametric permutation and bootstrap resampling. RESULTS: We identified ARMS-specific covariance patterns that described a generalized association of neurocognitive measures with predominantly prefronto-temporo-limbic and subcortical structures as well as the interconnecting white matter. In the conversion group, this generalized profile particularly involved working memory and verbal IQ and was positively correlated with limbic, insular and subcortical volumes as well as negatively related to prefrontal, temporal, parietal, and occipital cortices. Conversely, the neurocognitive profiles in the HC group were confined to working memory, learning and IQ, which were diffusely associated with cortical and subcortical brain regions. CONCLUSIONS: These findings suggest that the ARMS and prodromal phase of psychosis are characterized by a convergent mapping from multi-domain neurocognitive measures to a set of prefronto-temporo-limbic and subcortical structures. Furthermore, a neuroanatomical separation between positive and negative brain-cognition correlations may not only point to a biological process determining the clinical risk for disease transition, but also to possible compensatory or dysmaturational neural processes.

Early recognition and disease prediction in the at-risk mental states for psychosis using neurocognitive pattern classification.

BACKGROUND: Neuropsychological deficits predate overt psychosis and overlap with the impairments in the established disease. However, to date, no single neurocognitive measure has shown sufficient power for a prognostic test. Thus, it remains to be determined whether multivariate neurocognitive pattern classification could facilitate the diagnostic identification of different at-risk mental states (ARMS) for psychosis and the individualized prediction of illness transition. METHODS: First, classification of 30 healthy controls (HC) vs 48 ARMS individuals subgrouped into 20 "early," 28 "late" ARMS subjects was performed based on a comprehensive neuropsychological test battery. Second, disease prediction was evaluated by categorizing the neurocognitive baseline data of those ARMS individuals with transition (n = 15) vs non transition (n = 20) vs HC after 4 years of follow-up. Generalizability of classification was estimated by repeated double cross-validation. RESULTS: The 3-group cross-validated classification accuracies in the first analysis were 94.2% (HC vs rest), 85.0% (early at-risk subjects vs rest), and, 91.4% (late at-risk subjects vs rest) and 90.8% (HC vs rest), 90.8% (converters vs rest), and 89.0% (nonconverters vs rest) in the second analysis. Patterns distinguishing the early or late ARMS from HC primarily involved the verbal learning/memory domains, while executive functioning and verbal IQ deficits were particularly characteristic of the late ARMS. Disease transition was mainly predicted by executive and verbal learning impairments. CONCLUSIONS: Different ARMS and their clinical outcomes may be reliably identified on an individual basis by evaluating neurocognitive test batteries using multivariate pattern recognition. These patterns may have the potential to substantially improve the early recognition of psychosis.

Evaluation of a high resolving power time-of-flight mass spectrometer for drug analysis in terms of resolving power and acquisition rate.

Liquid chromatography time-of-flight mass spectrometry (LC-TOFMS) is applied increasingly to various fields of small molecule analysis. The moderate resolving power (RP) of standard TOFMS instruments poses a risk of false negative results when complex biological matrices are to be analyzed. In this study, the performance of a high resolving power TOFMS instrument (maXis by Bruker Daltonik, Bremen, Germany) was evaluated for drug analysis. By flow injection analysis of critical drug mixtures, including a total of 17 compounds with nominal masses of 212-415 Da and with mass differences of 8.8-23.5 mDa, RP varied from 34,400 to 51,900 (FWHM). The effect of acquisition rate on RP, mass accuracy, and isotopic pattern fit was studied by applying 1, 2, 5, 10, and 20 Hz acquisition rates in a 16 min gradient elution LC separation. All three variables were independent of the acquisition rate, with an average mass accuracy and isotopic pattern fit factor (mSigma) of 0.33 ppm and 5.9, respectively. The average relative standard deviation of RP was 1.8%, showing high repeatability. The performance was tested further with authentic urine extracts containing a co-eluting compound pair with a nominal mass of 296 Da and an 11.2 mDa mass difference. The authentic sample components were readily resolved and correctly identified by the automated data analysis. The average RP, mass accuracy, and isotopic pattern fit were 36,600, 0.9 ppm, and 7.3 mSigma, respectively.

Neuropsychological profiles in different at-risk states of psychosis: executive control impairment in the early--and additional memory dysfunction in the late--prodromal state.

Impairments in neuropsychological functioning have been described in subjects clinically at high risk for psychosis, but the specific cognitive deficits in different clinical high-risk groups remain to be elucidated. The German Research Network on Schizophrenia employs a heuristic 2-stage model: a putatively late prodromal state (LPS), characterized by the onset of attenuated positive or brief psychotic symptoms, and an early prodromal state (EPS), mainly characterized by the presence of basic symptoms, which are predictive for psychosis within the next 10 years. A total of 205 subjects met the criteria for either an EPS or an LPS of psychosis and were assessed with a comprehensive neuropsychological test battery. Neurocognitive profiles of high-risk groups were compared with data of 87 healthy controls comparable with regard to gender, age, and premorbid verbal IQ. Patients in the LPS were impaired in all neurocognitive domains (memory/learning, executive control/processing speed, and working memory) examined, with memory being the worst. Deficits were less pronounced in patients in the EPS, with a specific deficit in the executive control/processing speed domain. Consistent with a progressive neurodevelopmental disorder, some cognitive abilities were already impaired in patients in the EPS, followed by further deterioration in the LPS. Specifically, deficits in executive control functioning were related to the presence of basic symptoms, indicating a vulnerability for psychosis. Memory deficits were associated with the onset of psychotic symptoms indicating further disease progression in the trajectory to psychosis and, thus, may be useful in predicting psychosis and targeting early intervention.

Neuroanatomical correlates of executive dysfunction in the at-risk mental state for psychosis.

Deficits in executive functioning have been described as a core feature of schizophrenia and have been linked to patterns of fronto-temporo-limbic brain alterations. To date, such structure-cognition relationships have not been explored in a clinically defined at-risk mental state (ARMS) for psychosis using whole-brain neuroimaging techniques. Therefore, we used voxel-based morphometry in 40 ARMS and 30 matched healthy control (HC) individuals to investigate whether gray and white matter volumes (1) correlated with the performance in the Trail-Making Test B (TMT-B), an established measure of executive functioning, and (2) were volumetrically linked to the ventromedial prefrontal cortex (VMPFC), found to be associated with TMT-B in the ARMS during the first analysis step. We found the ARMS subjects to be specifically impaired in their TMT-B performance versus HC. Brain-cognition associations involving the insular cortices were observed in the HC, but not in the ARMS individuals. Conversely, TMT-B correlations in the VMPFC, the cerebellum, the fronto-callosal white matter were detected in the ARMS, but not the HC group. The VMPFC was linked to the temporo-limbic cortices in HC, whereas the connectivity pattern in the ARMS involved the left temporal and dorsolateral prefrontal cortex, the cerebellum, the right SMA and extended portions of the fronto-callosal white matter. These findings suggest that executive deficits are already present in the ARMS for psychosis and may be subserved by structurally altered networks of interconnected cortical and subcortical brain regions in line with the disconnectivity hypothesis of schizophrenia.

Use of neuroanatomical pattern regression to predict the structural brain dynamics of vulnerability and transition to psychosis.

BACKGROUND: The at-risk mental state for psychosis (ARMS) has been associated with abnormal structural brain dynamics underlying disease transition or non-transition. To date, it is unknown whether these dynamic brain changes can be predicted at the single-subject level prior to disease transition using MRI-based machine-learning techniques. METHODS: First, deformation-based morphometry and partial-least-squares (PLS) was used to investigate patterns of volumetric changes over time in 25 ARMS individuals versus 28 healthy controls (HC) (1) irrespective of the clinical outcome and (2) according to illness transition or non-transition. Then, the baseline MRI data were employed to predict the expression of these volumetric changes at the individual level using support-vector regression (SVR). RESULTS: PLS revealed a pattern of pronounced morphometric changes in ARMS versus HC that affected predominantly the right prefrontal, as well as the perisylvian, parietal and periventricular structures (p<0.011), and that was more pronounced in the converters versus the non-converters (p<0.010). The SVR analysis facilitated a reliable prediction of these longitudinal brain changes in individual out-of training cases (HC vs ARMS: r=0.83, p<0.001; HC vs converters vs non-converters: r=0.83, p<0.001) by relying on baseline patterns that involved ventricular enlargements, as well as prefrontal, perisylvian, limbic, parietal and subcortical volume reductions. CONCLUSIONS: Abnormal brain changes over time may underlie an elevated vulnerability for psychosis and may be most pronounced in subsequent converters to psychosis. Pattern regression techniques may facilitate an accurate prediction of these structural brain dynamics, potentially allowing for an early recognition of individuals at risk of developing psychosis-associated neuroanatomical changes over time.

Use of neuroanatomical pattern classification to identify subjects in at-risk mental states of psychosis and predict disease transition.

CONTEXT: Identification of individuals at high risk of developing psychosis has relied on prodromal symptomatology. Recently, machine learning algorithms have been successfully used for magnetic resonance imaging-based diagnostic classification of neuropsychiatric patient populations. OBJECTIVE: To determine whether multivariate neuroanatomical pattern classification facilitates identification of individuals in different at-risk mental states (ARMS) of psychosis and enables the prediction of disease transition at the individual level. DESIGN: Multivariate neuroanatomical pattern classification was performed on the structural magnetic resonance imaging data of individuals in early or late ARMS vs healthy controls (HCs). The predictive power of the method was then evaluated by categorizing the baseline imaging data of individuals with transition to psychosis vs those without transition vs HCs after 4 years of clinical follow-up. Classification generalizability was estimated by cross-validation and by categorizing an independent cohort of 45 new HCs. SETTING: Departments of Psychiatry and Psychotherapy, Ludwig-Maximilians-University, Munich, Germany. PARTICIPANTS: The first classification analysis included 20 early and 25 late at-risk individuals and 25 matched HCs. The second analysis consisted of 15 individuals with transition, 18 without transition, and 17 matched HCs. MAIN OUTCOME MEASURES: Specificity, sensitivity, and accuracy of classification. RESULTS: The 3-group, cross-validated classification accuracies of the first analysis were 86% (HCs vs the rest), 91% (early at-risk individuals vs the rest), and 86% (late at-risk individuals vs the rest). The accuracies in the second analysis were 90% (HCs vs the rest), 88% (individuals with transition vs the rest), and 86% (individuals without transition vs the rest). Independent HCs were correctly classified in 96% (first analysis) and 93% (second analysis) of cases. CONCLUSIONS: Different ARMSs and their clinical outcomes may be reliably identified on an individual basis by assessing patterns of whole-brain neuroanatomical abnormalities. These patterns may serve as valuable biomarkers for the clinician to guide early detection in the prodromal phase of psychosis.

Evaluation of the German WPA "program against stigma and discrimination because of schizophrenia--Open the Doors": results from representative telephone surveys before and after three years of antistigma interventions.

OBJECTIVES: In 2001, the World Psychiatric Association's global antistigma-program "Fighting stigma and discrimination because of schizophrenia--Open the Doors" was initiated in Germany. Several measures to tackle the stigma in certain target populations have been proven successful, but the effectiveness of the program on the general population level has not yet been examined. METHODS: Before the start of a number of antistigma interventions in 2001, a professional survey institute was commissioned to conduct a representative telephone survey in 6 German cities (N=7225). The cities were chosen with respect to the implementation of antistigma programs (Düsseldorf, Munich), awareness programs (Bonn, Cologne; with the aim to enhance early recognition of schizophrenia), and none of the programs (Berlin, Essen). A panel design follow-up survey (N=4622) was conducted in 2004. Stereotypes, beliefs and attitudes about schizophrenia and social distance--i.e. the distance between different groups of society--towards people with schizophrenia, and the knowledge of antistigma projects were assessed. RESULTS: Overall, social distance decreased significantly between 2001 and 2004 (p=0.001). At the city level, this effect was only significant in those cities where antistigma projects were implemented (p<0.001), although the observed attitude changes were small. In cities with antistigma projects, social distance primarily decreased in the social distance subscale "transient social relations" (p<0.001), but not in the subscale "closer social relations". Both subcales did not change significantly in cities without antistigma projects. DISCUSSION: The present study provides limited evidence for the efficacy of antistigma interventions on the population level in Germany. Further research is needed to separate direct effects of antistigma interventions from more general, indirect influences on social distance.

Randomized controlled multicentre trial of cognitive behaviour therapy in the early initial prodromal state: effects on social adjustment post treatment.

AIM: Improvement of social adjustment is a major aim of indicated prevention in young people at risk of developing psychosis. The present study explores the effect of specific cognitive behaviour therapy (CBT) as compared with supportive counselling (SC) on social adjustment in people in a potential early initial prodromal state of psychosis (EIPS) primarily defined by self-experienced cognitive thought and perception deficits (basic symptoms). METHODS: A total of 128 help-seeking outpatients in the EIPS were randomized to receive either specific CBT or SC for 12 months. Social adjustment was assessed with the Social Adjustment Scale II (SAS II) at baseline, time of transition or post treatment RESULTS: From 113 patients, who completed the SAS II at intake, 67 (59.3%) completed the SAS assessments at time of transition or post treatment. Both specific CBT and SC resulted in improvements in scales of SAS II, with no significant between-group differences post treatment. CONCLUSIONS: Although treatment in specially designed early detection and intervention centres improves functioning of people in the EIPS, specific CBT was not superior to SC. One could hypothesize that additional vocational rehabilitation, case management and involvement of multidisciplinary teams are needed to further improve short-term outcome of specific interventions on this dimension.