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Validating Chronic Disease Ascertainment Algorithms for Use in the Canadian Longitudinal Study on Aging*

Published online by Cambridge University Press:  08 August 2013

Mark Oremus
Affiliation:
Department of Clinical Epidemiology and Biostatistics, McMaster University
Ronald Postuma
Affiliation:
Department of Neurology, McGill University and Montréal General Hospital
Lauren Griffith
Affiliation:
Department of Clinical Epidemiology and Biostatistics, McMaster University
Cynthia Balion
Affiliation:
Department of Pathology and Molecular Medicine, McMaster University
Christina Wolfson
Affiliation:
Department of Epidemiology and Biostatistics and Occupational Health, McGill University Research Institute, McGill University Health Centre
Susan Kirkland
Affiliation:
Department of Community Health and Epidemiology, Dalhousie University Department of Medicine, Dalhousie University
Christopher Patterson
Affiliation:
Geriatric Services, Hamilton Health Sciences and Division of Geriatric Medicine, McMaster University
Harry S. Shannon
Affiliation:
Department of Clinical Epidemiology and Biostatistics, McMaster University
Parminder Raina*
Affiliation:
Department of Clinical Epidemiology and Biostatistics, McMaster University
CLSA Algorithms Validation Group
Affiliation:
Jonathan D. Adachi, M.D. (McMaster University), Wade Elliot, M.D. (Regional Joint Assessment Centre, Hamilton, Ontario), Paul Hernandez, M.D. (Dalhousie University), Ally P.H. Prebtani, M.D. (McMaster University), Malcolm Sears, M.D. (McMaster University), Rolf J. Sebaldt, M.D. (McMaster University), Koon Teo, M.D. (McMaster University), Dale Williams, M.D. (McMaster University), James Williams, M.D. (Dundas Family Medical Group, Dundas, Ontario), Mitchell Winemaker, M.D. (McMaster University).
*
Correspondence and requests for offprints should be sent to / La correspondance et les demandes de tirés-à-part doivent être adressées à: Parminder Raina, Ph.D. McMaster University 1280 Main Street West MIP-309A Hamilton, ON L8S 4K1 ([email protected])

Abstract

We validated seven chronic disease ascertainment algorithms for use in the Canadian Longitudinal Study on Aging. The algorithms pertained to diabetes mellitus type 2, parkinsonism, chronic airflow obstruction (CAO), hand osteoarthritis (OA), hip OA, knee OA, and ischemic heart disease. Our target recruitment was 20 cases and controls per disease; some cases were controls for unrelated diseases. Participants completed interviewer-administered disease symptom and medication use questionnaires. Diabetes cases and controls underwent fasting glucose testing; CAO cases and controls underwent spirometry testing. For each disease, the appropriate algorithm was used to classify participants’ disease status (positive or negative for disease). We also calculated sensitivity and specificity using physician diagnosis as the reference standard. The final sample involved 176 participants recruited in three Canadian cities between 2009 and 2011. Most estimated sensitivities and specificities were 80 per cent or more, indicating that the seven algorithms correctly identified individuals with the target disease.

Résumé

Nous avons validé sept algorithmes d’évaluation de maladie chronique pour l’usage dans L’Étude longitudinale canadienne (ÉLCV) sur le vieillissement. Les algorithmes ont concerné le diabète type 2, parkinsonisme, obstruction chronique de flux d’air, ostéoarthrite de main, ostéoarthrite de hanche, ostéoarthrite de genou, et la maladie cardiaque ischémique. Notre recrutement de cible était 20 cas et contrôles par chaque maladie. Quelques cas ont été utilisés comme contrôles avec certaines maladies. Tous les participants ont répondu à des questionnaires au sujet des symptômes de la maladie et d’utilisation de médicaments. Les cas et les contrôles de diabète ont subi le test de jeûne de glucose et les cas et les contrôles de l’obstruction chronique de flux d’air ont subi le test de spirométrie. Pour chaque maladie, nous avons utilisé l’algorithme adapté pour classifier si les participants étaient positifs ou négatif pour la maladie. Nous avons également calculé la sensibilité et la spécificité utilisant le diagnostic de médecin comme norme. L’échantillon final a fait participer 176 participants, qui ont été recrutés dans trois villes canadiennes entre 2009 et 2011. La plupart des sensibilités et spécificités étaient 80% ou plus, indiquant que les sept algorithmes peuvent correctement identifier des personnes avec les maladies.

Type
Articles
Copyright
Copyright © Canadian Association on Gerontology 2013 

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Footnotes

*

The study was supported by the Canadian Institutes of Health Research (http://webapps.cihr-irsc.gc.ca/funding/detail_e?pResearchId=3993413&p_version=CIHR&p_language=E&p_session_id=1673456). Mark Oremus holds the McLaughlin Foundation Professorship in Population and Public Health and, during the course of the study, held a Career Scientist Award from the Ontario Ministry of Health and Long-term Care. Parminder Raina holds the Raymond and Margaret Labarge Chair in Research and Knowledge Application for Optimal Aging and a Canada Research Chair in GeroScience. The sponsors played no role in study design, methods, subject recruitment, data collection or analysis, and manuscript preparation.

The authors thank Rachel Morris, Kathryn Walker, Natasha Clayton, Sameer Rawal, Leena Taji, Mary Gauld, Wid Al-Qazwini, and Julianna Beckett for recruiting participants, conducting interviews, and coordinating the study. Conflict of interest: Paul Hernandez serves on the medical advisory boards of AstraZeneca, Boehringer Ingelheim, GlaxoSmithKlein, Merck, Novartis, Nycomed, and Pfizer, and has conducted contract research studies for these companies; he has also received payment for lectures and for development of educational presentations from AstraZeneca, Boehringer Ingelheim, GlaxoSmithKlein, Nycomed, and Pfizer. Christopher Patterson has received payment for lectures from the Alzheimer Society of Canada.

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