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Estimating time to disease progression comparing transition models and survival methods--an analysis of multiple sclerosis data.

ABSTRACT: This article reports an analysis that aims to quantify the effect of fingolimod, an oral treatment for relapsing remitting multiple sclerosis (MS), on disability progression. The standard approach utilizes survival analysis methods, which may be problematic for MS studies that assess disability at only a few time points and include as a cardinal feature both relapses and remissions. Instead, a Markov transition model, originally developed in the framework of longitudinal data, is fit, and its special probabilistic properties are used to estimate survival curves for time to disability progression. The transition approach models the whole disability process and uses all available transition data for inference, while survival methods concentrate on a single event of interest and use only time to event data. This article compares the transition model approach to survival analysis methods, and discusses the differences in the interpretations of the estimated parameters. It applies both models to data obtained from two phase 3 clinical trials and finds that both yield positive effects for the new treatment compared to placebo, and provide similar estimates for the probability of disability progression over time. The transition model enables calculation of covariate-specific transition matrices that describe the short-term effect of treatment and other covariates on the disability process.

SUBMITTER: Mandel M

PROVIDER: S-EPMC3909474 | biostudies-literature | 2013 Mar

REPOSITORIES: biostudies-literature

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Estimating time to disease progression comparing transition models and survival methods--an analysis of multiple sclerosis data.

Mandel Micha M Mercier Francois F Eckert Benjamin B Chin Peter P Betensky Rebecca A RA

Biometrics 20130214 1

This article reports an analysis that aims to quantify the effect of fingolimod, an oral treatment for relapsing remitting multiple sclerosis (MS), on disability progression. The standard approach utilizes survival analysis methods, which may be problematic for MS studies that assess disability at only a few time points and include as a cardinal feature both relapses and remissions. Instead, a Markov transition model, originally developed in the framework of longitudinal data, is fit, and its sp ...[more]

PMID: 23410536

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Project description:INTRODUCTION: Multiple sclerosis (MS) is a chronic disease of the central nervous system. Estimates of MS natural history (NH) disability progression speed from clinical observations vary worldwide. This may reflect, in part, variance in censoring-bias) (missing observations) and assumptions about when irreversible disability progression events occurred. We test whether estimates of progression speed which assume midpoint survival time at irreversible disability endpoints are significantly faster than estimates which assume maximum survival time, and are more stable across study groups and time periods. METHODS: Our Nova Scotia NH study population includes 2,240 definite relapsing-onset multiple sclerosis (R-MS) natural history patients with 18,078 Expanded Disability Status Scale (EDSS) clinical observations in study period 1979-2010. Progression speed is measured by rate-of-change in range EDSS 0-6 and by survival time at irreversible endpoints EDSS 1-9. Midpoint censoring-bias-reduction methods are applied to clinical observations. FINDINGS: Typical EDSS increase per year in range EDSS 0-6, assuming midpoint survival time, is estimated to be 0.168 for all R-MS, 0.204 for eventually-DMD-treated patients and 0.155 for never-DMD-treated patients. Estimates assuming midpoint rather than maximum survival time are significantly faster: 16% faster for all R-MS natural history patients, 6% faster for eventually-DMD-treated patients, and 21% faster for never-DMD-treated patients. The variability of estimates across study groups and time periods decreased when midpoint survival time was assumed. CONCLUSIONS: Estimates of typical disease progression speed from 1979-2010 Nova Scotia clinical observations are sensitive to censoring-bias and to analysts' survival time assumptions. Censoring-bias-adjusted estimates of typical natural history disability progression speed in relapsing-onset multiple sclerosis patients are significantly faster, and less variable within and across study groups and time periods, than unadjusted estimates, and are, arguably, more relevant for various stakeholders. The application of censoring-bias-reduction methods to other multiple sclerosis clinical databases may reduce variability in estimates of disability progression speed worldwide.

Dataset Information

Estimating time to disease progression comparing transition models and survival methods--an analysis of multiple sclerosis data.

Publications

Estimating time to disease progression comparing transition models and survival methods--an analysis of multiple sclerosis data.

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