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Paternal age related schizophrenia (PARS): Latent subgroups detected by k-means clustering analysis.

ABSTRACT: Paternal age related schizophrenia (PARS) has been proposed as a subgroup of schizophrenia with distinct etiology, pathophysiology and symptoms. This study uses a k-means clustering analysis approach to generate hypotheses about differences between PARS and other cases of schizophrenia.We studied PARS (operationally defined as not having any family history of schizophrenia among first and second-degree relatives and fathers' age at birth ? 35 years) in a series of schizophrenia cases recruited from a research unit. Data were available on demographic variables, symptoms (Positive and Negative Syndrome Scale; PANSS), cognitive tests (Wechsler Adult Intelligence Scale-Revised; WAIS-R) and olfaction (University of Pennsylvania Smell Identification Test; UPSIT). We conducted a series of k-means clustering analyses to identify clusters of cases containing high concentrations of PARS.Two analyses generated clusters with high concentrations of PARS cases. The first analysis (N=136; PARS=34) revealed a cluster containing 83% PARS cases, in which the patients showed a significant discrepancy between verbal and performance intelligence. The mean paternal and maternal ages were 41 and 33, respectively. The second analysis (N=123; PARS=30) revealed a cluster containing 71% PARS cases, of which 93% were females; the mean age of onset of psychosis, at 17.2, was significantly early.These results strengthen the evidence that PARS cases differ from other patients with schizophrenia. Hypothesis-generating findings suggest that features of PARS may include a discrepancy between verbal and performance intelligence, and in females, an early age of onset. These findings provide a rationale for separating these phenotypes from others in future clinical, genetic and pathophysiologic studies of schizophrenia and in considering responses to treatment.

SUBMITTER: Lee H

PROVIDER: S-EPMC3085629 | biostudies-literature | 2011 May

REPOSITORIES: biostudies-literature

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Paternal age related schizophrenia (PARS): Latent subgroups detected by k-means clustering analysis.

Lee Hyejoo H Malaspina Dolores D Ahn Hongshik H Perrin Mary M Opler Mark G MG Kleinhaus Karine K Harlap Susan S Goetz Raymond R Antonius Daniel D

Schizophrenia research 20110226 1-3

<h4>Background</h4>Paternal age related schizophrenia (PARS) has been proposed as a subgroup of schizophrenia with distinct etiology, pathophysiology and symptoms. This study uses a k-means clustering analysis approach to generate hypotheses about differences between PARS and other cases of schizophrenia.<h4>Methods</h4>We studied PARS (operationally defined as not having any family history of schizophrenia among first and second-degree relatives and fathers' age at birth ≥ 35 years) in a series ...[more]

PMID: 21353765

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Project description:ImportanceMedically complex patients are a heterogeneous group that contribute to a substantial proportion of health care costs. Coordinated efforts to improve care and reduce costs for this patient population have had limited success to date.ObjectiveTo define distinct patient clinical profiles among the most medically complex patients through clinical interpretation of analytically derived patient clusters.Design, setting, and participantsThis cohort study analyzed the most medically complex patients within Kaiser Permanente Northern California, a large integrated health care delivery system, based on comorbidity score, prior emergency department admissions, and predicted likelihood of hospitalization, from July 18, 2018, to July 15, 2019. From a starting point of over 5000 clinical variables, we used both clinical judgment and analytic methods to reduce to the 97 most informative covariates. Patients were then grouped using 2 methods (latent class analysis, generalized low-rank models, with k-means clustering). Results were interpreted by a panel of clinical stakeholders to define clinically meaningful patient profiles.Main outcomes and measuresComplex patient profiles, 1-year health care utilization, and mortality outcomes by profile.ResultsThe analysis included 104 869 individuals representing 3.3% of the adult population (mean [SD] age, 70.7 [14.5] years; 52.4% women; 39% non-White race/ethnicity). Latent class analysis resulted in a 7-class solution. Stakeholders defined the following complex patient profiles (prevalence): high acuity (9.4%), older patients with cardiovascular complications (15.9%), frail elderly (12.5%), pain management (12.3%), psychiatric illness (12.0%), cancer treatment (7.6%), and less engaged (27%). Patients in these groups had significantly different 1-year mortality rates (ranging from 3.0% for psychiatric illness profile to 23.4% for frail elderly profile; risk ratio, 7.9 [95% CI, 7.1-8.8], P < .001). Repeating the analysis using k-means clustering resulted in qualitatively similar groupings. Each clinical profile suggested a distinct collaborative care strategy to optimize management.Conclusions and relevanceThe findings suggest that highly medically complex patient populations may be categorized into distinct patient profiles that are amenable to varying strategies for resource allocation and coordinated care interventions.

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Paternal age related schizophrenia (PARS): Latent subgroups detected by k-means clustering analysis.

Publications

Paternal age related schizophrenia (PARS): Latent subgroups detected by k-means clustering analysis.

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