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Pediatr Rheumatol Online J. 2017 Mar 29;15(1):18. doi: 10.1186/s12969-017-0148-2.

Methods for analyzing observational longitudinal prognosis studies for rheumatic diseases: a review & worked example using a clinic-based cohort of juvenile dermatomyositis patients.

Author information

1
Children's Hospital Research Institute of Manitoba, University of Manitoba, Winnipeg, Canada. llim@chrim.ca.
2
Department of Pediatrics, University of Manitoba, Winnipeg, Canada. llim@chrim.ca.
3
Institute of Health Policy Management and Evaluation, University of Toronto, Toronto, Canada. llim@chrim.ca.
4
The Child Health Evaluative Sciences Program, SickKids Research Institute, Toronto, Canada.
5
Department of Family and Community Medicine, University of Toronto, Toronto, Canada.
6
Department of Medicine, Toronto Western Research Institute, University of Toronto, Toronto, Canada.
7
Centre for Prognosis Studies, University Health Network, Toronto Western Hospital, Toronto, Canada.
8
Division of Rheumatology, SickKids, Toronto, Canada.
9
Physiology and Experimental Medicine Program, SickKids Research Institute, Toronto, Canada.
10
Department of Pediatrics and Immunology, University of Toronto, Toronto, Canada.
11
Institute of Health Policy Management and Evaluation, University of Toronto, Toronto, Canada.
12
The Dalla Lana School of Public Health, University of Toronto, Toronto, Canada.

Abstract

Most outcome studies of rheumatic diseases report outcomes ascertained on a single occasion. While single assessments are sufficient for terminal or irreversible outcomes, they may not be sufficiently informative if outcomes change or fluctuate over time. Consequently, longitudinal studies that measure non-terminal outcomes repeatedly afford a better understanding of disease evolution.Longitudinal studies require special analytic methods. Newer longitudinal analytic methods have evolved tremendously to deal with common challenges in longitudinal observational studies. In recent years, an increasing number of studies have used longitudinal design. This review aims to help readers understand and apply the findings from longitudinal studies. Using a cohort of children with juvenile dermatomyositis (JDM), we illustrate how to study evolution of disease activity in JDM using longitudinal methods.

KEYWORDS:

Biostatistics; Childhood-onset dermatomyositis; Epidemiology; Longitudinal study

PMID:
28356102
PMCID:
PMC5371187
DOI:
10.1186/s12969-017-0148-2
[Indexed for MEDLINE]
Free PMC Article

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