Estimating typical multiple sclerosis disability progression speed from clinical observations

Murray G Brown1, Mark Asbridge2, Vern Hicks3

  • 1Department of Community Health and Epidemiology, Dalhousie University and Capital District Health Authority, Centre for Clinical Research, Halifax, Nova Scotia, Canada.

Plos One
|October 21, 2014
PubMed
Abstract

Insights

Adjusting for missing data in multiple sclerosis (MS) studies reveals faster disability progression. This method reduces variability in natural history estimates for relapsing-onset MS patients.

Area of Science:

  • Neurology
  • Clinical Epidemiology

Background:

  • Multiple sclerosis (MS) is a chronic central nervous system disease with variable natural history (NH) disability progression estimates.
  • Discrepancies in MS progression speed estimates may stem from censoring bias and assumptions about irreversible disability events.

Purpose of the Study:

  • To evaluate if midpoint survival time assumptions yield faster and more stable MS disability progression estimates compared to maximum survival time assumptions.
  • To assess the impact of censoring-bias-reduction methods on the variability of MS natural history progression estimates.

Main Methods:

  • Utilized data from 2,240 relapsing-onset MS (R-MS) patients in Nova Scotia (1979-2010) with 18,078 Expanded Disability Status Scale (EDSS) observations.
  • Measured progression speed via rate-of-change in EDSS (0-6) and survival time at irreversible endpoints (EDSS 1-9).
  • Applied midpoint censoring-bias-reduction methods to clinical observations.

Main Results:

  • Estimates assuming midpoint survival time were significantly faster (16-21% faster) than those assuming maximum survival time.
  • Typical EDSS increase per year was estimated at 0.168 for all R-MS patients.
  • Variability in progression speed estimates decreased across study groups and time periods when midpoint survival time was assumed.

Conclusions:

  • MS natural history disability progression speed estimates are sensitive to censoring bias and survival time assumptions.
  • Censoring-bias-adjusted estimates for R-MS patients are faster and less variable, offering potentially greater relevance.
  • Applying these bias-reduction methods to other MS databases could decrease worldwide variability in progression speed estimates.