Association of comorbid-socioeconomic clusters with mortality in late onset epilepsy derived through unsupervised machine learning.


Journal

Seizure
ISSN: 1532-2688
Titre abrégé: Seizure
Pays: England
ID NLM: 9306979

Informations de publication

Date de publication:
Oct 2023
Historique:
received: 05 05 2023
revised: 20 07 2023
accepted: 22 07 2023
medline: 23 10 2023
pubmed: 4 8 2023
entrez: 3 8 2023
Statut: ppublish

Résumé

Late-onset epilepsy is a heterogenous entity associated with specific aetiologies and an elevated risk of premature mortality. Specific multimorbid-socioeconomic profiles and their unique prognostic trajectories have not been described. We sought to determine if specific clusters of late onset epilepsy exist, and whether they have unique hazards of premature mortality. We performed a retrospective observational cohort study linking primary and hospital-based UK electronic health records with vital statistics data (covering years 1998-2019) to identify all cases of incident late onset epilepsy (from people aged ≥65) and 1:10 age, sex, and GP practice-matched controls. We applied hierarchical agglomerative clustering using common aetiologies identified at baseline to define multimorbid-socioeconomic profiles, compare hazards of early mortality, and tabulating causes of death stratified by cluster. From 1,032,129 people aged ≥65, we identified 1048 cases of late onset epilepsy who were matched to 10,259 controls. Median age at epilepsy diagnosis was 68 (interquartile range: 66-72) and 474 (45%) were female. The hazard of premature mortality related to late-onset epilepsy was higher than matched controls (hazard ratio [HR] 1.73; 95% confidence interval [95%CI] 1.51-1.99). Ten unique phenotypic clusters were identified, defined by 'healthy' males and females, ischaemic stroke, intracerebral haemorrhage (ICH), ICH and alcohol misuse, dementia and anxiety, anxiety, depression in males and females, and brain tumours. Cluster-specific hazards were often similar to that derived for late-onset epilepsy as a whole. Clusters that differed significantly from the base late-onset epilepsy hazard were 'dementia and anxiety' (HR 5.36; 95%CI 3.31-8.68), 'brain tumour' (HR 4.97; 95%CI 2.89-8.56), 'ICH and alcohol misuse' (HR 2.91; 95%CI 1.76-4.81), and 'ischaemic stroke' (HR 2.83; 95%CI 1.83-4.04). These cluster-specific risks were also elevated compared to those derived for tumours, dementia, ischaemic stroke, and ICH in the whole population. Seizure-related cause of death was uncommon and restricted to the ICH, ICH and alcohol misuse, and healthy female clusters. Late-onset epilepsy is an amalgam of unique phenotypic clusters that can be quantitatively defined. Late-onset epilepsy and cluster-specific comorbid profiles have complex effects on premature mortality above and beyond the base rates attributed to epilepsy and cluster-defining comorbidities alone.

Sections du résumé

BACKGROUND AND OBJECTIVES OBJECTIVE
Late-onset epilepsy is a heterogenous entity associated with specific aetiologies and an elevated risk of premature mortality. Specific multimorbid-socioeconomic profiles and their unique prognostic trajectories have not been described. We sought to determine if specific clusters of late onset epilepsy exist, and whether they have unique hazards of premature mortality.
METHODS METHODS
We performed a retrospective observational cohort study linking primary and hospital-based UK electronic health records with vital statistics data (covering years 1998-2019) to identify all cases of incident late onset epilepsy (from people aged ≥65) and 1:10 age, sex, and GP practice-matched controls. We applied hierarchical agglomerative clustering using common aetiologies identified at baseline to define multimorbid-socioeconomic profiles, compare hazards of early mortality, and tabulating causes of death stratified by cluster.
RESULTS RESULTS
From 1,032,129 people aged ≥65, we identified 1048 cases of late onset epilepsy who were matched to 10,259 controls. Median age at epilepsy diagnosis was 68 (interquartile range: 66-72) and 474 (45%) were female. The hazard of premature mortality related to late-onset epilepsy was higher than matched controls (hazard ratio [HR] 1.73; 95% confidence interval [95%CI] 1.51-1.99). Ten unique phenotypic clusters were identified, defined by 'healthy' males and females, ischaemic stroke, intracerebral haemorrhage (ICH), ICH and alcohol misuse, dementia and anxiety, anxiety, depression in males and females, and brain tumours. Cluster-specific hazards were often similar to that derived for late-onset epilepsy as a whole. Clusters that differed significantly from the base late-onset epilepsy hazard were 'dementia and anxiety' (HR 5.36; 95%CI 3.31-8.68), 'brain tumour' (HR 4.97; 95%CI 2.89-8.56), 'ICH and alcohol misuse' (HR 2.91; 95%CI 1.76-4.81), and 'ischaemic stroke' (HR 2.83; 95%CI 1.83-4.04). These cluster-specific risks were also elevated compared to those derived for tumours, dementia, ischaemic stroke, and ICH in the whole population. Seizure-related cause of death was uncommon and restricted to the ICH, ICH and alcohol misuse, and healthy female clusters.
SIGNIFICANCE CONCLUSIONS
Late-onset epilepsy is an amalgam of unique phenotypic clusters that can be quantitatively defined. Late-onset epilepsy and cluster-specific comorbid profiles have complex effects on premature mortality above and beyond the base rates attributed to epilepsy and cluster-defining comorbidities alone.

Identifiants

pubmed: 37536152
pii: S1059-1311(23)00199-1
doi: 10.1016/j.seizure.2023.07.016
pii:
doi:

Types de publication

Observational Study Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

58-67

Informations de copyright

Copyright © 2023 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of Competing Interest C.B. Josephson has received grant support from Epilepsy Canada and unrestricted educational grants from UCB Pharma Inc. and Eisai Inc. for work unrelated to this project. A. Gonzalez-Izquierdo reports no disclosures relevant to the manuscript. J.D.T. Engbers reports no disclosures relevant to the manuscript. S. Denaxas reports no disclosures relevant to the manuscript. G. Delgado-Garcia reports no disclosures relevant to the manuscript. T.T. Sajobi reports no disclosures relevant to the manuscript. M. Wang reports no disclosures relevant to the manuscript. M.R. Keezer has received unrestricted educational grants, as well as grants for investigator-initiated studies, from UCB Pharma Inc. and Eisai Inc. for work unrelated to this project. S. Wiebe has received unrestricted educational grants from UCB Pharma, Eisai and Sunovion for work unrelated to this project.

Auteurs

Colin B Josephson (CB)

Department of Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada; Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, AB, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada; O'Brien Institute for Public Health, University of Calgary, Calgary, AB, Canada; Centre for Health Informatics, University of Calgary, Calgary, AB, Canada.

Arturo Gonzalez-Izquierdo (A)

UCL Institute of Health Informatics, London, UK; Health Data Research (HDR) UK, London, UK.

Jordan D T Engbers (JDT)

Desid Labs, Inc, Canada.

Spiros Denaxas (S)

UCL Institute of Health Informatics, London, UK; Health Data Research (HDR) UK, London, UK; Alan Turing Institute, London, UK.

Guillermo Delgado-Garcia (G)

Department of Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.

Tolulope T Sajobi (TT)

Department of Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada; Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, AB, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada; O'Brien Institute for Public Health, University of Calgary, Calgary, AB, Canada.

Meng Wang (M)

Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, AB, Canada.

Mark R Keezer (MR)

Department of Neurosciences, Université de Montreal, Montreal, Quebec, Canada.

Samuel Wiebe (S)

Department of Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada; Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, AB, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada; O'Brien Institute for Public Health, University of Calgary, Calgary, AB, Canada; Clinical Research Unit, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.

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