A longitudinal model for disease progression was developed and applied to multiple sclerosis

Lawton, Michael, Tilling, Kate, Robertson, Neil ORCID: https://orcid.org/0000-0002-5409-4909, Tremlett, Helen, Zhu, Feng, Harding, Katharine, Oger, Joel and Ben-Shlomo, Yoav 2015. A longitudinal model for disease progression was developed and applied to multiple sclerosis. Journal of Clinical Epidemiology 68 (11) , pp. 1355-1365. 10.1016/j.jclinepi.2015.05.003

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Abstract

OBJECTIVES: To develop a model of disease progression using multiple sclerosis (MS) as an exemplar. STUDY DESIGN AND SETTINGS: Two observational cohorts, the University of Wales MS (UoWMS), UK (1976), and British Columbia MS (BCMS) database, Canada (1980), with longitudinal disability data [the Expanded Disability Status Scale (EDSS)] were used; individuals potentially eligible for MS disease-modifying drugs treatments, but who were unexposed, were selected. Multilevel modeling was used to estimate the EDSS trajectory over time in one data set and validated in the other; challenges addressed included the choice and function of time axis, complex observation-level variation, adjustments for MS relapses, and autocorrelation. RESULTS: The best-fitting model for the UoWMS cohort (404 individuals, and 2,290 EDSS observations) included a nonlinear function of time since onset. Measurement error decreased over time and ad hoc methods reduced autocorrelation and the effect of relapse. Replication within the BCMS cohort (978 individuals and 7,335 EDSS observations) led to a model with similar time (years) coefficients, time [0.22 (95% confidence interval {CI}: 0.19, 0.26), 0.16 (95% CI: 0.10, 0.22)] and log time [-0.13 (95% CI: -0.39, 0.14), -0.15 (95% CI: -0.70, 0.40)] for BCMS and UoWMS, respectively. CONCLUSION: It is possible to develop robust models of disability progression for chronic disease. However, explicit validation is important given the complex methodological challenges faced

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	MRC Centre for Neuropsychiatric Genetics and Genomics (CNGG) Medicine
Subjects:	R Medicine > R Medicine (General)
Uncontrolled Keywords:	Multiple sclerosis; Repeated measures model; Multilevel model; Fractional polynomials; Prognosis; Observational cohorts
Publisher:	Elsevier
ISSN:	0895-4356
Date of Acceptance:	5 May 2015
Last Modified:	31 Oct 2022 09:34
URI:	https://orca.cardiff.ac.uk/id/eprint/81545

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