Helse Stavanger HF, Stavanger
University of Oslo, Norway
Fjorden Hospital, Roskilde, Denmark
Helse Stavanger HF, Stavanger
University of Oslo, Norway
Fjorden Hospital, Roskilde, Denmark
University of Oslo, Norway
Yale Psychiatric Institute, New Haven, Connecticut, USA
Correspondence: Tor K. Larsen, MD, Helse Stavanger HF, Psychiatric Clinic, Armauer Hansensv. 20, PO Box 8100, N-4068 Stavanger, Norway. Tel: 47 51 51 51 51; fax: 47 51 51 50 50; e-mail: tklarsen{at}online.no
Funding detailed in Acknowledgements.
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ABSTRACT |
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Aims To identify and validate patterns of premorbid functioning in first-episode psychosis.
Method The Premorbid Adjustment Scale was used to examine 335 patients.
Results Social and academic function constituted fairly independent dimensions. Cluster analysis identified groups varying both in level and course. Patients with a stable social course compared with a deteriorating one had a shorter duration of untreated psychosis, were older, had more friends and less negative symptoms. Good childhood academic function correlated with more education, more meaningful activities and better working memory. Patients with a stable academic course were older at admission.
Conclusions Patterns of premorbid development suggest both neurodevelopmental and neuroregressive pathways to illness.
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INTRODUCTION |
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In this study we combined the PAS data from four samples of patients with first-episode non-affective psychosis, collected in Norway and Denmark between 1993 and 2001, and used cluster analysis to identify distinctive patterns of premorbid course. Our hypothesis was that some patterns would suggest a neurodevelopmental pathophysiology whereas others would suggest a neuroregressive process.
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METHOD |
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The exclusion criteria were a history of prior first psychosis, receiving adequate prior neuroleptic treatment, and organic or substance-induced psychosis. Written informed consent was obtained from all participants and the study was approved by the regional research ethics committees.
The mean age of the total sample of 335 patients was 27.9 years (s.d.=9.5), 59.1% were male and 84% were hospitalised at start of treatment. The majority had a diagnosis of schizophrenia spectrum disorder (34% schizophrenia, 19.4% schizophreniform, 11.9% schizoaffective disorder). The distribution of non-schizophrenia psychosis was 11.6% affective disorders with mood-incongruent psychosis, 6.3% delusional disorder, 6.3% brief psychosis and 10.4% other psychosis.
Measures
Premorbid Adjustment Scale
The Premorbid Adjustment Scale (PAS) comprises 36 items describing levels
of functioning before the onset of psychosis. These items cover sociability
and withdrawal, peer relationships, scholastic performance, adaptation to
school and capacity to establish socio-sexual relationships, assessed during
four periods in life: childhood (up to 11 years), early adolescence (12-15
years), late adolescence (16-18 years) and adulthood (19 years and beyond).
The rating is based on interviews with the patient and/or with family members.
The scoring range of each item is 0-6, with 0 indicating the best level of
functioning and 6 the worst. Onset of psychosis is defined by the presence of
delusions, hallucinations, thought disorder, inappropriate or bizarre
behaviour or gross psychomotor behaviour in which the symptoms are not
apparently due to organic causes
(Cannon-Spoor et al,
1982).
The PAS has been used in several studies, yet there is no consensus as to how to present the data. In several studies the mean scores for all four originally defined time periods have been presented (Haas et al, 1998; Robinson et al, 1999; Apiquian et al, 2002). Other studies report overall mean scores (Levitt et al, 1996), but most studies select items for certain dimensions. For example, Hien et al (1998) combined the items measuring social functioning to calculate an overall (mean) social dimension score. In another study the items for social withdrawal and peer relationships were summed to a single dimension (peers), and the same was done for school functioning and school performance (school) (Fennig et al, 1995). Three studies have carried out a principal component analysis with varimax rotation. In two of these a social and a school factor were identified (van Kammen et al, 1994; Cannon et al, 1997). Krauss et al (1998) identified two social factors, one for childhood/early adolescence and the other for late adolescence, and a separate factor for school (containing performance and adjustment). Allen and colleagues calculated a sum-score including all applicable age periods for each of the five items: sociability; peer relationships; school performance; school adaptation; and socio-sexual functioning (Allen et al, 2001). On the basis of the work by van Kammen and Cannon, they carried out confirmatory factor analysis and identified a social and an academic factor.
In some studies a change score has been used. Kelley et al (1992) and Cannon et al (1997) calculated this by subtracting childhood scores from early-adolescence scores. Haas & Sweeney defined three patterns of PAS in the following manner: deteriorating PAS was defined as a pattern of worsening scores from childhood over the remaining premorbid periods and the equivalent of a two-point change over four premorbid stages (Haas & Sweeney, 1992: p. 376); the remaining cases were divided into stable good and stable poor, split by the median score. The sample consisted of 71 patients and no statistical analysis was presented to support this subtyping. This study is the first to subtype premorbid functioning in a longitudinal manner. Hien et al (1998) used the median to split the sample into good and poor adjustment, but no longitudinal measure was considered.
In our own study of patients with a first episode of non-affective psychosis attending for treatment in Rogaland County, Norway, in 1993-1994, we calculated change scores as the difference between the mean score for one period and the mean score for the previous period (early adolescence minus childhood; late adolescence minus early adolescence; adulthood minus late adolescence; Larsen et al, 1996b). We thus identified a subgroup with deteriorating course. Like Haas et al (1998), we used the median scores to divide the remaining patients into stable good and stable poor subgroups.
Published research appears to identify two basic dimensions in the PAS: social and academic. The time patterns are much less clear. A major problem with using the median scores to separate the stable good and stable poor subgroups is that a skewed distribution of data may make one of the groups heterogeneous. Furthermore, such a procedure cannot identify groups of patients with a deteriorating course. The identification of such a group would be important, because a substantial neuroregressive element in schizophrenia should imply a deteriorating course, whereas a predominantly neurodevelopmental element would probably be expressed as a stable course, even if poor. In this study we aimed to replicate the identification of a social and an academic dimension, to identify clusters of patients with different time patterns for each of the dimensions, and to test the validity of the clusters by comparing them on characteristics at start of treatment.
Other instruments
The Structured Clinical Interview for DSM-IV (SCID;
Spitzer et al, 1992) was used for diagnostic purposes. Symptom levels were measured using the
Positive and Negative Syndrome Scale (PANSS;
Kay et al, 1987).
Eight neuropsychological tests were used for assessing neurocognitive
function, described in detail by Friis et al
(2002). We identified five
dimensions that explained 72% of the variance: working memory/fluency,
executive function, verbal learning, impulsivity and motor speed
(Friis et al, 2003; Rund et al,
2004).
Global functioning was measured by the Global Assessment of Functioning (GAF) scale (American Psychiatric Association, 1994); the scores were split into symptom scores (GAF-S) and function scores (GAF-F) to improve psychometric properties.
The duration of untreated psychosis was measured as the time from the first onset of positive psychotic symptoms (the first week with a PANSS score of 4 or more on at least one of the Positive Scale items 1, 3, 5, 6 or General Scale item 9) to the start of first adequate treatment of psychosis (i.e. admission to the study). Multiple sources, including personal interviews with patients and relatives, were used to ascertain the length of this period. Relatives were interviewed when the patient was unable to give reliable information.
Drug and alcohol misuse was measured with the Clinician Rating Scale (Drake et al, 1990). Social functioning (number of friends and participation in meaningful activities) during the year before start of treatment were measured with the Strauss-Carpenter scale (Strauss & Carpenter, 1974).
All raters were trained in the use of study instruments by rating pre-prepared case notes and audio/videotapes before joining the study assessment teams. We achieved good reliability for all major variables such as PANSS, GAF, duration of untreated psychosis, and diagnosis (see Friis et al, 2003). No specific reliability test was done for the PAS in the TIPS study, but a test-retest on a subsample of the patients (1993-1994) with a masked rater showed good reliability, with an intraclass coefficient of 0.84-0.87 (Larsen et al, 1996b).
Statistical analysis
Correlations were calculated as Pearson product moment coefficients, and
chisquared tests were used for relationships between categorical variables.
K-mean cluster analyses were used to identify groups. We chose to
include patients who, owing to early start of psychosis, had missing scores
for late adolescence and/or adulthood. (Technically, this was done by using
the delete cases pairwise option of the Statistical Package for
the Social Sciences. We explored the alternative option delete cases
likewise, which dropped all cases with one or more missing values: 65
for social function and 19 for academic. This option gave basically the same
clustering, but with a considerable number of patients lost to further
analysis.) To compare clusters we used t-tests or one-way analysis of
variance.
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RESULTS |
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Pearson correlations between social withdrawal and peer relationships were strongly correlated (childhood 0.64, early adolescence 0.70, late adolescence 0.66, adulthood 0.69). So, too, were the correlations between adaptation to school and school performance (childhood 0.58, early adolescence 0.60, late adolescence 0.54). Because of this we calculated two sum dimension variables for each age level - one social (combining the social withdrawal and peer relationship items) and one academic (combining adaptation to school and school performance). In the PAS, school functioning and adaptation to school are not rated during adulthood and therefore the academic sum variable could not be calculated for this period. In Table 2, correlations between the social and academic dimensions are shown. For both dimensions there were strong correlations with the nearest time period (Pearson correlations 0.67-0.74), and an almost 50% reduced correlation with the next period (0.52-0.54) and (for social) another 50% reduction to the adult period. The social and academic dimensions proved to be weakly intercorrelated.
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We carried out separate K-mean cluster analyses for the social and
academic dimensions. For both dimensions the analyses suggested four or five
clusters. We chose the four-cluster solutions as they seemed to give the
clearest picture (Figs 1 and
2). For both dimensions we
defined a starting level as good (<1.50), intermediate (1.50-2.99) or poor
(3.00). The courses were defined by change scores over the time periods as
clearly stable (<1.00), slightly deteriorating (1.00-1.99) and clearly
deteriorating (
2.00). Clusters were labelled according to this definition,
but as none of them occupied the slightly deteriorating
category, only the terms stable and deteriorating
are used to describe course. Even though we do not have a normal control
group, the PAS score of 0 is defined as normal. Furthermore, we feel confident
that the naming of the groups is reasonable, taking into consideration that
(for example) the good stable group on average had many friends
for all periods and the poor stable group per definition had almost no
friends for all periods.
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As seen in Table 3, there
was a significant relationship between social and academic levels
(2=23.3, d.f.=2; P<0.0005). However, for a
considerable proportion of patients there was a discrepancy between the
clusters of the two dimensions. For example, 12% of the patients with good
social functioning had poor academic functioning. Although none of the patient
groups had poor social functioning in childhood, nearly 17% of patients
already had poor academic functioning at that age.
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The distribution of course is given in
Table 4. There is a significant
relationship between the course of the two dimensions (2=6.75,
d.f.=1; P=0.009), but a considerable number of patients had a stable
course on one dimension and a deteriorating course on the other. It is worth
noting that a deteriorating course was much less common for the academic
dimension than for the social dimension, probably because many patients had a
poor academic functioning as children.
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The next step was to conduct separate analyses of childhood levels and course for the social and academic clusters with baseline demographic, clinical and neurocognitive variables. Since multiple comparisons were made (76 in number) we chose a Bonferroni correction of P=0.0006 as equivalent to an uncorrected P<0.05 (Tables 5, 6, 7, 8). In Table 5 the baseline variables are related to childhood social cluster levels; no significant relationship was found. In Table 6 the baseline variables are related to social cluster course; patients with a deteriorating course had longer duration of untreated psychosis, lower age, fewer friends and higher negative PANSS scores. Tables 7 and 8 show similar analyses for the academic dimension: patients with a poorer level had fewer years of education, less meaningful activity and poorer working memory; patients with a deteriorating course had a lower age at study entry.
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DISCUSSION |
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We postulate that these patterns might be the product of two different but developmentally linked neurobiological processes. Levels of social and academic functioning in childhood may be determined early in life, largely by neurodevelopmental processes related to genetics and perinatal forces (Murray & Lewis, 1987). Levels of social and academic functioning that decline later on, especially in adolescence, may be determined by neuroregressive processes such as developmentally determined reductions in cortical synaptic connectivity (McGlashan & Hoffman, 2000). The latter processes have traditionally been labelled as deterioration (dementia) and have been thought to arise from loss of brain neurons (neurodegeneration). We consider the latter term to be misleading, because more recent post-mortem studies have found loss of neuropil but no loss of neurons in the cortex of patients with schizophrenia (Selemon et al, 1995; Garey et al, 1998; Rajkowska et al, 1998; Harrison, 1999; Selemon & Goldman-Rakic, 1999); we therefore prefer the term neuroregression for this process.
Our results clearly illustrate that the heterogeneity of schizophrenia begins early, long before the onset of psychosis. The variety of longitudinal premorbid patterns is interesting from several points of view. In our fairly representative sample of patients with first-episode psychosis, as many as 40% reported good stable social functioning. This is an argument against seeing schizophrenia as an entirely neurodevelopmental disorder with social dysfunction being an obligatory early manifestation (Rund, 1998; Weinberger & McClure, 2002). Second, it seems that having social problems, especially when they worsen over time, is a risk factor for late detection of psychosis. It may be that the social network has adapted to the person having problems and thus does not react when the transition to psychosis is taking place, or it may be that the person's social network is so small that the likelihood of someone becoming worried is greatly reduced.
We postulate from the observed premorbid patterns that the academic dimension is the more neurodevelopmentally determined. More than three-quarters of patients are stable over time in their childhood level of functioning, especially when that level is either poor or intermediate. This is consistent with the repeated finding that neurocognitive deficits are present in people with first-episode schizophrenia by the time of onset, and do not change much with time and ongoing disorder - the so-called static encephalopathy (Hoff et al, 1992; Saykin et al, 1994; Rund, 1998; Fucetola et al, 2000). The strong relationship between poor childhood academic functioning and poor working memory at baseline assessment supports the validity of this hypothesis. On the other hand, it appears that social functioning is more neuroregressively determined. Only 57% of patients are stable at their original childhood level of social functioning. Deterioration describes a relatively high fraction of the sample and affects both levels of childhood social functioning (intermediate and good). This suggests that it is important to assess young adults displaying a marked drop in social functioning as soon as possible for signs of early psychosis. The specific nature of these neurobiological processes, both static and progressive, require further elucidation, but premorbid adjustment patterns may provide direction to the inquiry. For example, social functioning should be targeted if one wishes to track the process of neuroregression.
Regarding gender differences, we have previously reported that men have poorer premorbid functioning and more deterioration, especially closer to the onset of psychosis (Larsen et al, 1996b). This has also been reported by other research teams (e.g. van Mastrigt & Addington, 2002). We did not replicate these findings in a much larger sample and with a new method for describing patterns of premorbid functioning. Our conclusion must be that the gender differences in premorbid functioning are not significant.
Limitations of the study
A weakness of the study is the retrospective description of the premorbid
phase. Recall bias might be a problem insofar as the patients are experiencing
their first psychotic episode at the time of the interview. It is also
possible that the relatives will give a description of the premorbid period
coloured by the present experience with psychosis. Another possible confound
is the halo effect, in which the PAS rater's knowledge of the
scores of previous periods influences the current rating. In this study we had
no possibility of avoiding this problem.
In order to learn more about the validity of the premorbid dimensions and subtypes we describe, a follow-up is needed. We are conducting a follow-up study with 1-year, 2-year and 5-year assessment of all patients, and are also planning a 10-year follow-up. We report few significant correlations between the premorbid subtypes and both GAF and neurocognitive variables. Some of the correlations are on trend level, but we have avoided discussing trends because of the large number of analyses in the study. We also cannot rule out the possibility that the small size of some of the subgroups results in low statistical power.
Clinical implications
First and foremost, these data suggest that premorbid functioning is
extremely heterogeneous, and that two separate dimensions - social and
academic - should be considered. Most early intervention initiatives focus on
rapid changes in symptoms, such as sudden social withdrawal or problems at
school. Our findings emphasise the importance of considering the possibility
of psychotic development in people with long-lasting social or academic
dysfunction. Our study also supports the idea that schizophrenia is a
heterogeneous disorder with neurodevelopmental and neuroregressive pathways to
psychosis, processes that may be qualitatively distinct in their
neurobiological origins but interactive in their contribution to the
pathophysiology of schizophrenia.
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Clinical Implications and Limitations |
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LIMITATIONS
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ACKNOWLEDGMENTS |
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This paper is part of the Tidlig Intervensjon ved Psykoser (TIPS; Early Treatment Intervention in Psychosis) project with the following research group: Thomas McGlashan, MD (Principal Investigator), Per Vaglum, MD (Principal Investigator), Svein Friis, MD, Ulrik Haahr, MD, Jan Olav Johannessen, MD, Tor K. Larsen, MD, Ingrid Melle, MD, Stein Opjordsmoen, MD, Bjørn Rishovd Rund, PhD and Erik Simonsen, MD.
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Received for publication May 20, 2003. Revision received February 25, 2004. Accepted for publication March 2, 2004.
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