Using biological indices to classify schizophrenia and other psychotic patients

Although classification of mental disorders using more than clinical description would be desirable, there is scant evidence that available laboratory tests (i.e. biological indices) would provide more valid classifications than current diagnostic systems (e.g. DSM-IV). We used cluster analysis of f...

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Published inSchizophrenia research Vol. 50; no. 3; pp. 139 - 150
Main Authors Sponheim, S.R, Iacono, W.G, Thuras, P.D, Beiser, M
Format Journal Article
LanguageEnglish
Published Amsterdam Elsevier B.V 01.07.2001
Elsevier Science
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Online AccessGet full text
ISSN0920-9964
1573-2509
DOI10.1016/S0920-9964(00)00160-2

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Abstract Although classification of mental disorders using more than clinical description would be desirable, there is scant evidence that available laboratory tests (i.e. biological indices) would provide more valid classifications than current diagnostic systems (e.g. DSM-IV). We used cluster analysis of four biological variables to classify 163 psychotic patients and 83 nonpsychiatric comparison subjects. Analyses revealed a three-cluster solution with the first cluster reflecting electrodermal deviance, the second cluster representing nondeviant biological function, and the third cluster reflecting increased nailfold plexus visibility and ocular motor dysfunction. To assess the construct validity of proband clusters we examined ocular motor performance in 156 first-degree relatives as a function of proband cluster membership. First-degree relatives of third cluster probands exhibited worse ocular motor performance than relatives of other cluster probands. Additionally, better classification sensitivity and specificity were obtained for the relatives when they were grouped by proband cluster than by proband DSM-IV diagnosis. When a single proband characteristic (i.e. eyetracking performance) was used to group relatives, classification sensitivity and specificity failed to significantly increase over grouping by proband DSM-IV diagnosis. Multivariate biologically defined clusters may offer an advantage over DSM-IV classification when examining nosology and etiology of psychotic disorders.
AbstractList Although classification of mental disorders using more than clinical description would be desirable, there is scant evidence that available laboratory tests (i.e. biological indices) would provide more valid classifications than current diagnostic systems (e.g. DSM-IV). We used cluster analysis of four biological variables to classify 163 psychotic patients and 83 nonpsychiatric comparison subjects. Analyses revealed a three-cluster solution with the first cluster reflecting electrodermal deviance, the second cluster representing nondeviant biological function, and the third cluster reflecting increased nailfold plexus visibility and ocular motor dysfunction. To assess the construct validity of proband clusters we examined ocular motor performance in 156 first-degree relatives as a function of proband cluster membership. First-degree relatives of third cluster probands exhibited worse ocular motor performance than relatives of other cluster probands. Additionally, better classification sensitivity and specificity were obtained for the relatives when they were grouped by proband cluster than by proband DSM-IV diagnosis. When a single proband characteristic (i.e. eyetracking performance) was used to group relatives, classification sensitivity and specificity failed to significantly increase over grouping by proband DSM-IV diagnosis. Multivariate biologically defined clusters may offer an advantage over DSM-IV classification when examining nosology and etiology of psychotic disorders.
Although classification of mental disorders using more than clinical description would be desirable, there is scant evidence that available laboratory tests (i.e. biological indices) would provide more valid classifications than current diagnostic systems (e.g. DSM-IV). We used cluster analysis of four biological variables to classify 163 psychotic patients and 83 nonpsychiatric comparison subjects. Analyses revealed a three-cluster solution with the first cluster reflecting electrodermal deviance, the second cluster representing nondeviant biological function, and the third cluster reflecting increased nailfold plexus visibility and ocular motor dysfunction. To assess the construct validity of proband clusters we examined ocular motor performance in 156 first-degree relatives as a function of proband cluster membership. First-degree relatives of third cluster probands exhibited worse ocular motor performance than relatives of other cluster probands. Additionally, better classification sensitivity and specificity were obtained for the relatives when they were grouped by proband cluster than by proband DSM-IV diagnosis. When a single proband characteristic (i.e. eyetracking performance) was used to group relatives, classification sensitivity and specificity failed to significantly increase over grouping by proband DSM-IV diagnosis. Multivariate biologically defined clusters may offer an advantage over DSM-IV classification when examining nosology and etiology of psychotic disorders.Although classification of mental disorders using more than clinical description would be desirable, there is scant evidence that available laboratory tests (i.e. biological indices) would provide more valid classifications than current diagnostic systems (e.g. DSM-IV). We used cluster analysis of four biological variables to classify 163 psychotic patients and 83 nonpsychiatric comparison subjects. Analyses revealed a three-cluster solution with the first cluster reflecting electrodermal deviance, the second cluster representing nondeviant biological function, and the third cluster reflecting increased nailfold plexus visibility and ocular motor dysfunction. To assess the construct validity of proband clusters we examined ocular motor performance in 156 first-degree relatives as a function of proband cluster membership. First-degree relatives of third cluster probands exhibited worse ocular motor performance than relatives of other cluster probands. Additionally, better classification sensitivity and specificity were obtained for the relatives when they were grouped by proband cluster than by proband DSM-IV diagnosis. When a single proband characteristic (i.e. eyetracking performance) was used to group relatives, classification sensitivity and specificity failed to significantly increase over grouping by proband DSM-IV diagnosis. Multivariate biologically defined clusters may offer an advantage over DSM-IV classification when examining nosology and etiology of psychotic disorders.
Author Iacono, W.G
Beiser, M
Thuras, P.D
Sponheim, S.R
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Issue 3
Keywords Psychosis
Schizophrenia
Nosology
Ocular motor function
Genetic vulnerability
Cluster analysis
Schizoaffective psychosis
Electrodermography
Electrophysiology
Bipolar disorder
First degree relatives
Electroencephalography
Electrodiagnosis
Criterion
Classification
Genetics
Diagnosis
Diagnostic and Statistical Manual IV
Mood disorder
Human
Family study
Biological indicator
Pursuit eye movement
Vision
Perception
Visibility
Schizophreniform disorder
Comparative study
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Snippet Although classification of mental disorders using more than clinical description would be desirable, there is scant evidence that available laboratory tests...
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StartPage 139
SubjectTerms Adolescent
Adult
Adult and adolescent clinical studies
Biological and medical sciences
Chronic Disease
Cluster Analysis
Electroencephalography
Female
Galvanic Skin Response - physiology
Genetic vulnerability
Humans
Male
Medical sciences
Middle Aged
Nosology
Nosology. Terminology. Diagnostic criteria
Ocular Motility Disorders - diagnosis
Ocular motor function
Other psychotic disorders
Psychiatric Status Rating Scales
Psychology. Psychoanalysis. Psychiatry
Psychopathology. Psychiatry
Psychoses
Psychosis
Psychotic Disorders - classification
Psychotic Disorders - diagnosis
Psychotic Disorders - genetics
Schizophrenia
Schizophrenia - classification
Schizophrenia - diagnosis
Schizophrenia - genetics
Severity of Illness Index
Techniques and methods
Title Using biological indices to classify schizophrenia and other psychotic patients
URI https://www.clinicalkey.com/#!/content/1-s2.0-S0920996400001602
https://dx.doi.org/10.1016/S0920-9964(00)00160-2
https://www.ncbi.nlm.nih.gov/pubmed/11439234
https://www.proquest.com/docview/70983831
Volume 50
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