Schizophrenia Bulletin Advance Access published March 7, 2014 Schizophrenia Bulletin doi:10.1093/schbul/sbu025
A Stratified Model for Psychosis Prediction in Clinical Practice
Chantal Michel*,1,3, Stephan Ruhrmann2,3, Benno G. Schimmelmann1, Joachim Klosterkötter2, Frauke Schultze-Lutter1 University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland; 2Department of Psychiatry and Psychotherapy, University of Cologne, Cologne, Germany
1
Shared first authorship
3
Objective: Impaired cognition is an important dimension in psychosis and its at-risk states. Research on the value of impaired cognition for psychosis prediction in at-risk samples, however, mainly relies on study-specific sample means of neurocognitive tests, which unlike widely available general test norms are difficult to translate into clinical practice. The aim of this study was to explore the combined predictive value of at-risk criteria and neurocognitive deficits according to test norms with a risk stratification approach. Method: Potential predictors of psychosis (neurocognitive deficits and at-risk criteria) over 24 months were investigated in 97 at-risk patients. Results: The final prediction model included (1) at-risk criteria (attenuated psychotic symptoms plus subjective cognitive disturbances) and (2) a processing speed deficit (digit symbol test). The model was stratified into 4 risk classes with hazard rates between 0.0 (both predictors absent) and 1.29 (both predictors present). Conclusions: The combination of a processing speed deficit and at-risk criteria provides an optimized stratified risk assessment. Based on neurocognitive test norms, the validity of our proposed 3 risk classes could easily be examined in independent at-risk samples and, pending positive validation results, our approach could easily be applied in clinical practice in the future. Key words: prediction/psychosis/neurocognition/ processing speed/at-risk criteria/risk estimation Introduction Neurocognitive disturbances are regarded as a core component of psychosis;1,2 with a recent meta-analysis reporting global cognitive impairments in schizophrenia patients being consistently present in studies over decades and around the world.3 Neurocognitive deficits mainly develop and intensify in the prodrome and early years following diagnosis before settling into a stable pattern of pronounced
deficit.4 Thus, the first years of psychosis are critical—with regard to cognitive decline and also with regard to many other domains that show a similar pattern, such as psychosocial and occupational functioning.5 Yet, psychoses often remain untreated for extended periods.6 As the duration of untreated psychosis (DUP) or illness (DUI; including the prodrome) is associated with worse functioning, more symptoms, cognitive impairments, and lower quality of life,7–10 increasing efforts have been undertaken to shorten DUP and DUI by early detection and intervention. Ideally, early detection and intervention would prevent the onset of frank psychosis and would be early and efficient enough to counteract the cognitive and psychosocial deficits that develop during the prodromal phase.11,12 Patients symptomatically at risk of psychosis exhibit lower neurocognitive test performance in several domains including general intelligence, processing speed, attention, executive function, and memory.12–16 At the mean group level, these deficits are mostly intermediate between the performance of healthy individuals and those diagnosed with schizophrenia.12–14 Furthermore, they are more pronounced in patients considered in a late risk stage (mainly by attenuated psychotic symptoms) than in those considered in an early stage (predominately by subjectively reported cognitive and perceptive basic symptoms).17,18 In converters, baseline performance is even lower than in nonconverters.13–16 Thus, neurocognitive baseline deficits are promising candidates for an estimation of risk of conversion. Furthermore, even beyond conversion, cognitive functioning is an important factor for understanding and predicting functional status in at-risk patients19 and patients with the full-blown disorder.20 “Impaired cognition” was therefore introduced as one of 8 dimensions of psychosis symptom severity proposed in Section III (ie, “Emerging Measures and Models”) of the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5).21,22
© The Author 2014. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: [email protected]
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*To whom correspondence should be addressed; University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, Bolligenstr 111, 3000 Bern 60, Switzerland; tel: +41-(0)31-932-8564, fax: +41-(0)31-932-8569, e-mail: [email protected]
C. Michel et al
Page 2 of 10
individual risk classification, sample-dependent subscale mean scores of negative or positive symptoms and neurocognitive tests scores were used as predictors.24,25 Therefore, our aim was to develop an easy-to-apply risk stratification model26,27 based on 24-month follow-up data of patients symptomatically at risk for psychosis for routine clinical use. Such a model should allow an estimation of conversion risk for individual patients based on the combination of baseline neurocognitive deficits (defined as more than 1 SD according to test norms) and single or combined at-risk criteria. Method Sample The sample consisted of 97 primarily adult patients aged between 16 and 40 years seeking help for mental problems at the Cologne Early Recognition and Intervention Centre for mental crisis (FETZ). All patients fulfilled either ultrahigh-risk (UHR) criteria including (1) “attenuated psychotic symptoms” (APS), (2) “brief limited intermittent psychotic symptoms” (BLIPS), and (3) a “state-trait criterion” according to the Structured Interview for Prodromal Symptoms (SIPS)28 or the basic symptom criterion “cognitive disturbances” (COGDIS) according to the Schizophrenia Proneness Instrument, Adult version (SPI-A).29 The SPI-A, SIPS, and a battery of neurocognitive tests (see below) are routinely administered as part of the clinical diagnostic protocol of the FETZ;30 raters were initially trained (concordance rate with expert rating after 10 training sessions was 91%) and supervised by Frauke Schultze-Lutter in the SPI-A and SIPS assessments. All patients provided informed written consent for participation in the study. Exclusion criteria for all patients were current or past diagnosis of any psychotic disorder according to DSM-IV criteria; diagnosis of delirium, dementia, amnestic or other cognitive disorder, mental retardation, mental disorders due to a general medical condition or substance-related disorder according to DSM-IV; alcohol or substance use disorders within the past 3 months according to DSM-IV (assessed with the Structured Clinical Interview of DSM-IV (SCID),31 no toxicology screen conducted); and diseases of the central nervous system (inflammatory, traumatic, epileptic). Patients were monitored for a conversion to psychosis according to the SIPS over a mean duration of 15.80 months (SD = 8.37; range = 1–37). In case of a conversion, the type of psychotic disorder was assessed with the psychosis section of the SCID.31 Fifty-three (54.6%) patients did not convert to psychosis over a mean time of 19.96 months (SD = 6.18; range = 3–37). Forty-four patients (45.4%) converted to a psychotic disorder according to DSM-IV criteria within 10.80 months on average (SD = 7.96; range = 1–24): 36 (81.8%) developed schizophrenia, 2 (4.5%) delusional disorder, 1 (2.3%) schizophreniform disorder, 1 (2.3%)
Downloaded from http://schizophreniabulletin.oxfordjournals.org/ at Universite Laval on July 13, 2014
Therein, severity of impaired cognition is defined on a 5-point Likert scale (scores between 0 and 4) using SDs from the age-adjusted mean on neurocognitive tests, with 1 SD or more below mean indicating moderate-to-severe impairment (see supplementary table S1).21 Generally, in neurocognitive and other psychological tests, the normal range is defined as ±1 SD from the mean and encompasses 68.26% of people if test scores are normally distributed in the population (see supplementary figure S1). The use of normative scales allows the clinician to determine if an individual differs from the majority of the reference population, defined, eg, by age, gender, education, or socioeconomic status. Such norms are readily available for most neurocognitive tests commonly used in psychosis research. To date, however, studies have predominately reported mean performances, which were calculated based on the raw scores of their sample. These group means generally differ between studies, sometimes considerably. Furthermore, neurocognitive group differences, eg, between converters and nonconverters, can become significant even if both group means still lie within the normal range of the general population (see supplementary figure S2). Consequently, such data provide little information on the presence of actual neurocognitive performance deficits according to norms. Yet, clinicians need this information to be able to classify individual test performances in their daily practice, eg, into estimates of risk for conversion. Despite the potential benefit that the use of test norms would provide for clinical practice, cognitive deficits based on such norms have been understudied in psychosis research. One exception is a study on at-risk patients that explored potential neurocognitive predictors not of conversion to psychosis, but of functional outcome.23 In addition to group mean analysis, this study also defined deficits in verbal performance, IQ, and verbal memory by standardized IQ scores ≤ 85. Deficient performance was found in 57.9% of the poor outcome group, but only in 26.5% of the good outcome group.23 Reviews and meta-analyses of other prediction studies based on group means generally reported heterogeneous findings with regard to neurocognitive predictors of conversion.12 The most promising predictors, however, seem to be a lower performance in processing speed, verbal fluency, visual and verbal memory, and working memory.12–16,19,23–25 These studies, however, rarely considered potentially important interactions between at-risk criteria and neurocognitive performance. Only 2 studies so far have studied both psychopathological and neurocognitive predictors.24,25 Although both studies differed considerably in the selection of predictors and, consequently, in the generated prediction models, each reported a benefit from combining neurocognitive and psychopathological predictors. However, rather than using at-risk criteria and norm-related neurocognitive deficits, which would allow
A Clinical Prediction Model for Psychosis
period, however, converters more frequently received antipsychotic medication (this includes medication for frank psychosis after conversion) and, expectedly, still more frequently took antipsychotic medication at followup. The rate of psychotherapy did not differ between converters and nonconverters (for treatment details see supplementary table S2). Assessments The neurocognitive test battery, previously described in detail,33 examines the following domains: 1. Attention: Continuous Performance Test, identical pairs version (CPT-IP)34,35 2. Memory: verbal memory with the Auditory Verbal Learning Test (AVLT);36,37 visual memory with the Rey-Ostrieth Complex Figure Test (ROFT);38,39 spatial working memory with the Subject Ordered Pointing Task (SOPT)39,40
Table 1. Characteristics of Sample
Age (y) Mean (±SD) Median (range) Gender, % male Partnership, % Single Married/steady partner Separated Graduationb, % None Certificate of secondary education (10 y) O-level (10 y) Vocational baccalaureate diploma (12 y) A-level (13 y) Still in school Vocational education, % None Apprenticeship or similar Master craftsman or similar College of higher education University Still in school/training Current occupation, % No work/education Regular occupation including education Any current, nonpsychotic DSM-IV axis-I disorderc, % Premorbid IQ by MWTd Mean (±SD) Median (range) Deficit according to norms
Converters (n = 44)
Nonconverters (n = 53)
Pa
24.1 (±5.7) 22.8 (16.3-39.3) 65.9
25.3 (±5.3) 24.7 (17.1-37.1) 64.2
0.200
93.2 4.5 2.3
92.5 7.5 0
0.459
7.0 9.3 20.9 7.0 37.2 18.6
0 3.8 13.2 13.2 58.5 11.3
0.086
25.0 11.4 2.3 2.3 6.8 52.3
9.4 22.6 0 0 7.5 60.4
0.157
22.7 77.3 65.9
17.6 82.4 59.6
0.537
27.8 (±4.5) 28.0 (15-35) 1
29.9 (±3.6) 30.0 (20-36) 0
0.018
0.857
0.526
0.274
Notes: MWT, German version of the Multiple Choice Vocabulary Test.32 a U-test and 2xk-χ test, respectively. b Translated into British graduations (minimum years of school education required to receive the respective graduation). c As assessed with the German version of the Structured Clinical Interview of DSM-IV axis I disorders.31 d MWT is a measure of verbal IQ highly correlated with total IQ; MWT values of 6-20 correspond to IQ values of 73–90, of 21–30 to 91–109, of 31–33 to 110–127 and of 34–37 to ≥128.
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psychosis not otherwise specified, 1 (2.3%) schizoaffective disorder, 1 (4.5%) major depressive disorder with psychotic features, and 1 (2.3%) bipolar disorder with psychotic features. Altogether, the majority of patients (86.4%) developed a schizophrenia spectrum disorder (n = 38) and only 6.8% developed an affective (n = 3) or other psychosis (n = 3). Converters and nonconverters did not differ at baseline in sociodemographic characteristics or the presence of any nonpsychotic DSM-IV axis I disorder although converters had more frequently reported recurrent brief depressive disorder (table 1; for more details on distribution of axis-I disorders see supplementary table S2). Furthermore, the frequency of deficits in estimated premorbid IQ did not differ between converters and nonconverters although a small-to-moderate effect of group on the mean estimated premorbid IQ was present in favor of nonconverters (Rosenthal’s r = .242; table 1). At baseline, all participants had never been treated with an antipsychotic. During the follow-up
C. Michel et al
3. Executive functions: Wisconsin Card Sorting Test (WCST);41 verbal executive functions with the verbal fluency task42 4. Processing speed: Digit Symbol Test (DST)43 and Trail-Making Test (TMT) A and B39,44
Table 2. Neuropsychological Measures and Definition of ‘Neurocognitive Deficits’ Neuropsychological Domain Attention
Memory Verbal memory
Visual memory
Working memory Spatial working memory
Executive functions Set shifting and problem solving Verbal executive functions
Processing speed
Test Description
Definition of Neurocognitive Deficit; Adjustment of Norms
The Continuous Performance Test (identical pairs version; CPT-IP)34 provided a measure of sustained attention. The signal detection parameter d' was calculated across 300 trials.
CPT-IP—d' (more than 1 SD below mean); norms unadjusted for age.35
The Auditory Verbal Learning Test (AVLT)36 provided a verbal memory measure for immediate and delayed recall after one to 5 learning trials of word lists.
AVLT immediate recall—no. correct after 1st trial (PR < 16); norms adjusted for age.37 AVLT trials 1–5—sum no. correct (PR < 16); norms adjusted for age.37 AVLT delayed recall—no. correct after 30 min (PR < 16); norms adjusted for age.37 ROFT—delayed recall (more than 1 SD below mean); norms adjusted for age.39(p827)
A measure of visual memory was provided by the Rey-Osterrieth Complex Figure Test (ROFT).38 The delayed recall performance was scored according to L.B. Taylor’s criteria. During each trial of a computerized version of the Subject Ordered Pointing Task (SOPT)40 subjects had to point to 1 of 12 objects, and the relative positions of the objects varied randomly across trials. Across 3 sessions of 12 trials the number of errors (pointing to an object already chosen on a previous trial) was calculated.
SOPT—no. errors (more than 1 SD below mean); norms adjusted for age.39(p475)
The percentage of perseverative and nonperseverative errors made in the Wisconsin Card Sorting Test (WCST)41 provided a measure of set shifting and problem solving. Verbal executive functions were measured by a verbal fluency task (a lexical and a semantic category task).42 For lexical verbal fluency as many words as possible beginning with a S and for semantic verbal fluency as many animal names as possible had to be produced within 1 min. The digit symbol test (DST)43 and trail-making test (TMT) A and B44 provided measures for the speed of visual information-processing and visuomotor coordination.
WCST—% errors (T
A Stratified Model for Psychosis Prediction in Clinical Practice
Chantal Michel*,1,3, Stephan Ruhrmann2,3, Benno G. Schimmelmann1, Joachim Klosterkötter2, Frauke Schultze-Lutter1 University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland; 2Department of Psychiatry and Psychotherapy, University of Cologne, Cologne, Germany
1
Shared first authorship
3
Objective: Impaired cognition is an important dimension in psychosis and its at-risk states. Research on the value of impaired cognition for psychosis prediction in at-risk samples, however, mainly relies on study-specific sample means of neurocognitive tests, which unlike widely available general test norms are difficult to translate into clinical practice. The aim of this study was to explore the combined predictive value of at-risk criteria and neurocognitive deficits according to test norms with a risk stratification approach. Method: Potential predictors of psychosis (neurocognitive deficits and at-risk criteria) over 24 months were investigated in 97 at-risk patients. Results: The final prediction model included (1) at-risk criteria (attenuated psychotic symptoms plus subjective cognitive disturbances) and (2) a processing speed deficit (digit symbol test). The model was stratified into 4 risk classes with hazard rates between 0.0 (both predictors absent) and 1.29 (both predictors present). Conclusions: The combination of a processing speed deficit and at-risk criteria provides an optimized stratified risk assessment. Based on neurocognitive test norms, the validity of our proposed 3 risk classes could easily be examined in independent at-risk samples and, pending positive validation results, our approach could easily be applied in clinical practice in the future. Key words: prediction/psychosis/neurocognition/ processing speed/at-risk criteria/risk estimation Introduction Neurocognitive disturbances are regarded as a core component of psychosis;1,2 with a recent meta-analysis reporting global cognitive impairments in schizophrenia patients being consistently present in studies over decades and around the world.3 Neurocognitive deficits mainly develop and intensify in the prodrome and early years following diagnosis before settling into a stable pattern of pronounced
deficit.4 Thus, the first years of psychosis are critical—with regard to cognitive decline and also with regard to many other domains that show a similar pattern, such as psychosocial and occupational functioning.5 Yet, psychoses often remain untreated for extended periods.6 As the duration of untreated psychosis (DUP) or illness (DUI; including the prodrome) is associated with worse functioning, more symptoms, cognitive impairments, and lower quality of life,7–10 increasing efforts have been undertaken to shorten DUP and DUI by early detection and intervention. Ideally, early detection and intervention would prevent the onset of frank psychosis and would be early and efficient enough to counteract the cognitive and psychosocial deficits that develop during the prodromal phase.11,12 Patients symptomatically at risk of psychosis exhibit lower neurocognitive test performance in several domains including general intelligence, processing speed, attention, executive function, and memory.12–16 At the mean group level, these deficits are mostly intermediate between the performance of healthy individuals and those diagnosed with schizophrenia.12–14 Furthermore, they are more pronounced in patients considered in a late risk stage (mainly by attenuated psychotic symptoms) than in those considered in an early stage (predominately by subjectively reported cognitive and perceptive basic symptoms).17,18 In converters, baseline performance is even lower than in nonconverters.13–16 Thus, neurocognitive baseline deficits are promising candidates for an estimation of risk of conversion. Furthermore, even beyond conversion, cognitive functioning is an important factor for understanding and predicting functional status in at-risk patients19 and patients with the full-blown disorder.20 “Impaired cognition” was therefore introduced as one of 8 dimensions of psychosis symptom severity proposed in Section III (ie, “Emerging Measures and Models”) of the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5).21,22
© The Author 2014. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: [email protected]
Page 1 of 10
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*To whom correspondence should be addressed; University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, Bolligenstr 111, 3000 Bern 60, Switzerland; tel: +41-(0)31-932-8564, fax: +41-(0)31-932-8569, e-mail: [email protected]
C. Michel et al
Page 2 of 10
individual risk classification, sample-dependent subscale mean scores of negative or positive symptoms and neurocognitive tests scores were used as predictors.24,25 Therefore, our aim was to develop an easy-to-apply risk stratification model26,27 based on 24-month follow-up data of patients symptomatically at risk for psychosis for routine clinical use. Such a model should allow an estimation of conversion risk for individual patients based on the combination of baseline neurocognitive deficits (defined as more than 1 SD according to test norms) and single or combined at-risk criteria. Method Sample The sample consisted of 97 primarily adult patients aged between 16 and 40 years seeking help for mental problems at the Cologne Early Recognition and Intervention Centre for mental crisis (FETZ). All patients fulfilled either ultrahigh-risk (UHR) criteria including (1) “attenuated psychotic symptoms” (APS), (2) “brief limited intermittent psychotic symptoms” (BLIPS), and (3) a “state-trait criterion” according to the Structured Interview for Prodromal Symptoms (SIPS)28 or the basic symptom criterion “cognitive disturbances” (COGDIS) according to the Schizophrenia Proneness Instrument, Adult version (SPI-A).29 The SPI-A, SIPS, and a battery of neurocognitive tests (see below) are routinely administered as part of the clinical diagnostic protocol of the FETZ;30 raters were initially trained (concordance rate with expert rating after 10 training sessions was 91%) and supervised by Frauke Schultze-Lutter in the SPI-A and SIPS assessments. All patients provided informed written consent for participation in the study. Exclusion criteria for all patients were current or past diagnosis of any psychotic disorder according to DSM-IV criteria; diagnosis of delirium, dementia, amnestic or other cognitive disorder, mental retardation, mental disorders due to a general medical condition or substance-related disorder according to DSM-IV; alcohol or substance use disorders within the past 3 months according to DSM-IV (assessed with the Structured Clinical Interview of DSM-IV (SCID),31 no toxicology screen conducted); and diseases of the central nervous system (inflammatory, traumatic, epileptic). Patients were monitored for a conversion to psychosis according to the SIPS over a mean duration of 15.80 months (SD = 8.37; range = 1–37). In case of a conversion, the type of psychotic disorder was assessed with the psychosis section of the SCID.31 Fifty-three (54.6%) patients did not convert to psychosis over a mean time of 19.96 months (SD = 6.18; range = 3–37). Forty-four patients (45.4%) converted to a psychotic disorder according to DSM-IV criteria within 10.80 months on average (SD = 7.96; range = 1–24): 36 (81.8%) developed schizophrenia, 2 (4.5%) delusional disorder, 1 (2.3%) schizophreniform disorder, 1 (2.3%)
Downloaded from http://schizophreniabulletin.oxfordjournals.org/ at Universite Laval on July 13, 2014
Therein, severity of impaired cognition is defined on a 5-point Likert scale (scores between 0 and 4) using SDs from the age-adjusted mean on neurocognitive tests, with 1 SD or more below mean indicating moderate-to-severe impairment (see supplementary table S1).21 Generally, in neurocognitive and other psychological tests, the normal range is defined as ±1 SD from the mean and encompasses 68.26% of people if test scores are normally distributed in the population (see supplementary figure S1). The use of normative scales allows the clinician to determine if an individual differs from the majority of the reference population, defined, eg, by age, gender, education, or socioeconomic status. Such norms are readily available for most neurocognitive tests commonly used in psychosis research. To date, however, studies have predominately reported mean performances, which were calculated based on the raw scores of their sample. These group means generally differ between studies, sometimes considerably. Furthermore, neurocognitive group differences, eg, between converters and nonconverters, can become significant even if both group means still lie within the normal range of the general population (see supplementary figure S2). Consequently, such data provide little information on the presence of actual neurocognitive performance deficits according to norms. Yet, clinicians need this information to be able to classify individual test performances in their daily practice, eg, into estimates of risk for conversion. Despite the potential benefit that the use of test norms would provide for clinical practice, cognitive deficits based on such norms have been understudied in psychosis research. One exception is a study on at-risk patients that explored potential neurocognitive predictors not of conversion to psychosis, but of functional outcome.23 In addition to group mean analysis, this study also defined deficits in verbal performance, IQ, and verbal memory by standardized IQ scores ≤ 85. Deficient performance was found in 57.9% of the poor outcome group, but only in 26.5% of the good outcome group.23 Reviews and meta-analyses of other prediction studies based on group means generally reported heterogeneous findings with regard to neurocognitive predictors of conversion.12 The most promising predictors, however, seem to be a lower performance in processing speed, verbal fluency, visual and verbal memory, and working memory.12–16,19,23–25 These studies, however, rarely considered potentially important interactions between at-risk criteria and neurocognitive performance. Only 2 studies so far have studied both psychopathological and neurocognitive predictors.24,25 Although both studies differed considerably in the selection of predictors and, consequently, in the generated prediction models, each reported a benefit from combining neurocognitive and psychopathological predictors. However, rather than using at-risk criteria and norm-related neurocognitive deficits, which would allow
A Clinical Prediction Model for Psychosis
period, however, converters more frequently received antipsychotic medication (this includes medication for frank psychosis after conversion) and, expectedly, still more frequently took antipsychotic medication at followup. The rate of psychotherapy did not differ between converters and nonconverters (for treatment details see supplementary table S2). Assessments The neurocognitive test battery, previously described in detail,33 examines the following domains: 1. Attention: Continuous Performance Test, identical pairs version (CPT-IP)34,35 2. Memory: verbal memory with the Auditory Verbal Learning Test (AVLT);36,37 visual memory with the Rey-Ostrieth Complex Figure Test (ROFT);38,39 spatial working memory with the Subject Ordered Pointing Task (SOPT)39,40
Table 1. Characteristics of Sample
Age (y) Mean (±SD) Median (range) Gender, % male Partnership, % Single Married/steady partner Separated Graduationb, % None Certificate of secondary education (10 y) O-level (10 y) Vocational baccalaureate diploma (12 y) A-level (13 y) Still in school Vocational education, % None Apprenticeship or similar Master craftsman or similar College of higher education University Still in school/training Current occupation, % No work/education Regular occupation including education Any current, nonpsychotic DSM-IV axis-I disorderc, % Premorbid IQ by MWTd Mean (±SD) Median (range) Deficit according to norms
Converters (n = 44)
Nonconverters (n = 53)
Pa
24.1 (±5.7) 22.8 (16.3-39.3) 65.9
25.3 (±5.3) 24.7 (17.1-37.1) 64.2
0.200
93.2 4.5 2.3
92.5 7.5 0
0.459
7.0 9.3 20.9 7.0 37.2 18.6
0 3.8 13.2 13.2 58.5 11.3
0.086
25.0 11.4 2.3 2.3 6.8 52.3
9.4 22.6 0 0 7.5 60.4
0.157
22.7 77.3 65.9
17.6 82.4 59.6
0.537
27.8 (±4.5) 28.0 (15-35) 1
29.9 (±3.6) 30.0 (20-36) 0
0.018
0.857
0.526
0.274
Notes: MWT, German version of the Multiple Choice Vocabulary Test.32 a U-test and 2xk-χ test, respectively. b Translated into British graduations (minimum years of school education required to receive the respective graduation). c As assessed with the German version of the Structured Clinical Interview of DSM-IV axis I disorders.31 d MWT is a measure of verbal IQ highly correlated with total IQ; MWT values of 6-20 correspond to IQ values of 73–90, of 21–30 to 91–109, of 31–33 to 110–127 and of 34–37 to ≥128.
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psychosis not otherwise specified, 1 (2.3%) schizoaffective disorder, 1 (4.5%) major depressive disorder with psychotic features, and 1 (2.3%) bipolar disorder with psychotic features. Altogether, the majority of patients (86.4%) developed a schizophrenia spectrum disorder (n = 38) and only 6.8% developed an affective (n = 3) or other psychosis (n = 3). Converters and nonconverters did not differ at baseline in sociodemographic characteristics or the presence of any nonpsychotic DSM-IV axis I disorder although converters had more frequently reported recurrent brief depressive disorder (table 1; for more details on distribution of axis-I disorders see supplementary table S2). Furthermore, the frequency of deficits in estimated premorbid IQ did not differ between converters and nonconverters although a small-to-moderate effect of group on the mean estimated premorbid IQ was present in favor of nonconverters (Rosenthal’s r = .242; table 1). At baseline, all participants had never been treated with an antipsychotic. During the follow-up
C. Michel et al
3. Executive functions: Wisconsin Card Sorting Test (WCST);41 verbal executive functions with the verbal fluency task42 4. Processing speed: Digit Symbol Test (DST)43 and Trail-Making Test (TMT) A and B39,44
Table 2. Neuropsychological Measures and Definition of ‘Neurocognitive Deficits’ Neuropsychological Domain Attention
Memory Verbal memory
Visual memory
Working memory Spatial working memory
Executive functions Set shifting and problem solving Verbal executive functions
Processing speed
Test Description
Definition of Neurocognitive Deficit; Adjustment of Norms
The Continuous Performance Test (identical pairs version; CPT-IP)34 provided a measure of sustained attention. The signal detection parameter d' was calculated across 300 trials.
CPT-IP—d' (more than 1 SD below mean); norms unadjusted for age.35
The Auditory Verbal Learning Test (AVLT)36 provided a verbal memory measure for immediate and delayed recall after one to 5 learning trials of word lists.
AVLT immediate recall—no. correct after 1st trial (PR < 16); norms adjusted for age.37 AVLT trials 1–5—sum no. correct (PR < 16); norms adjusted for age.37 AVLT delayed recall—no. correct after 30 min (PR < 16); norms adjusted for age.37 ROFT—delayed recall (more than 1 SD below mean); norms adjusted for age.39(p827)
A measure of visual memory was provided by the Rey-Osterrieth Complex Figure Test (ROFT).38 The delayed recall performance was scored according to L.B. Taylor’s criteria. During each trial of a computerized version of the Subject Ordered Pointing Task (SOPT)40 subjects had to point to 1 of 12 objects, and the relative positions of the objects varied randomly across trials. Across 3 sessions of 12 trials the number of errors (pointing to an object already chosen on a previous trial) was calculated.
SOPT—no. errors (more than 1 SD below mean); norms adjusted for age.39(p475)
The percentage of perseverative and nonperseverative errors made in the Wisconsin Card Sorting Test (WCST)41 provided a measure of set shifting and problem solving. Verbal executive functions were measured by a verbal fluency task (a lexical and a semantic category task).42 For lexical verbal fluency as many words as possible beginning with a S and for semantic verbal fluency as many animal names as possible had to be produced within 1 min. The digit symbol test (DST)43 and trail-making test (TMT) A and B44 provided measures for the speed of visual information-processing and visuomotor coordination.
WCST—% errors (T
