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Confounders in natural history of interferon-Цtreated relapsing multiple sclerosis.

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scores of 4 and 6 had to be confirmed at 6 months. This is
not the same as “irreversible” because one study has indicated
that worsening to Expanded Disability Status Scale score of
6, confirmed at 6 months, was not sustained after 2 years by
almost one-third of patients.4
1
Department of Neurology, University Medical Centre,
University of Groningen, Groningen, the Netherlands, 2Faculty
of Medicine (Neurology), University of British Columbia,
Vancouver, British Columbia, Canada, and 3Unità di
Neuroepidemiologia, Fondazione Istituto Neurologico “Carlo
Besta,” Milan, Italy
1. Trojano M, Pellegrini F, Fuiani A, et al. New natural history of
interferon-␤-treated relapsing multiple sclerosis. Ann Neurol
2007;61:300 –306.
2. Ebers G. Disease evolution in multiple sclerosis. J Neurol 2006;
253(suppl 6):vi3–vi8.
3. Kremenchutzky M, Rice G, Baskerville J, et al. The natural history of multiple sclerosis: a geographically based study 9: observations on the progressive phase of the disease. Brain 2006;129:
584 –594.
4. Liu C, Blumhardt LD. Disability outcome measures in therapeutic trials of relapsing-remitting multiple sclerosis: effects of heterogeneity of disease course in placebo cohorts. J Neurol Neurosurg Psychiatry 2000;68:450 – 457.
DOI: 10.1002/ana.21185
Confounders in Natural History of Interferon-␤–
Treated Relapsing Multiple Sclerosis
Olivier Gout, MD
Trojano and colleagues,1 based on their observational
study, suggest that interferon-␤ slows progression in
relapsing-remitting multiple sclerosis patients. They have
used propensity scores to correct significant differences between interferon-␤–treated and untreated control groups,
and then conducted a sensitivity analysis to detect how the
magnitude of an unmeasured binary confounder might affect the propensity score adjusted hazard ratios. In fact, several potential confounders, which are significant predictors
of disease progression,2– 4 have been excluded from the propensity score such as symptoms at onset, completeness of
recovery from initial attack, interval between first and second attack, number of relapses during the first 2 or 5 years,
T2 lesion load on first magnetic resonance image, and so
on. Taking account of these confounders may change the
result of their study.
Department of Neurology, Fondation Opthalmologique
Adolphe de Rothschild, Paris, France
References
1. Trojano M, Pellegrini F, Fuiani A, et al. New natural history of
interferon ␤-treated relapsing multiple sclerosis. Ann Neurol
2007;61:300 –306.
Annals of Neurology
DOI: 10.1002/ana.21186
Reply
References
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2. Runmarker B, Andersen O. Prognostic factors in a multiple sclerosis incidence cohort with twenty-five years of follow-up. Brain
1993;116:117–134.
3. Weinshenker BG, Bass B, Rice GPA, et al. The natural history
of multiple sclerosis: a geographically based study. 2. Predictive value of the early clinical course. Brain 1989;112:
1419 –1428.
4. Confavreux C, Vukusic S, Adeleine P. Early clinical predictors
and progression of irreversible disability in multiple sclerosis: an
amnesic process. Brain 2003;126:770 –782.
Vol 63
No 1
January 2008
Maria Trojano, MD,1 Fabio Pellegrini, MScStat,2
Aurora Fuiani, MD,1 Damiano Paolicelli, MD,1
Valentina Zipoli, MD,3 Giovanni B. Zimatore, MD,1
Elisabetta Di Monte, MD,1 Emilio Portaccio, MD,3
Vito Lepore, MD,1 Paolo Livrea, MD,1 and
Maria Pia Amato, MD3
We thank Dr Koch and colleagues and Dr Gout for their
attention to our article1 and for giving us the opportunity to
stress further the usefulness of appropriate statistical analyses
for enhancing the quality of observational studies.
Systematic bias is minimized when a propensity score
analysis is performed together with a sensitivity analysis.
We recognize that the treatment and control groups in our
study were imbalanced for all of the baseline covariates,
which meant that it was necessary to use appropriate statistical methods to adjust the comparisons. Propensity score
analysis, taking into consideration parameters of interest
that would likely affect the outcome, can create balanced
groups that have a similar likelihood of receiving a therapy
and resemble randomized cohorts of patients.2– 4
We agree that an important limitation of this approach
is that propensity scores cannot adjust for variables that are
not measured in a study (eg, concomitant diseases). Therefore, a sensitivity analysis5 was conducted to evaluate their
possible impact on the study outcome. This analysis
showed that even a small imbalance between treatment
arms in a parameter that doubled the risk for reaching the
end point would eliminate the statistical significance of
findings for Expanded Disability Status Scale outcomes.1
However, the results for secondary progression end point
were more robust. Therefore, statistical adjustment can indeed compensate for even major imbalances; furthermore,
sensitivity analysis can also help define to what extent a
potential residual imbalance could account for observed
outcomes. With regard to the baseline time point we used
for each group, the aim of a propensity score analysis is to
balance the two groups on measured covariates at their
baseline time point, so by its nature, differences between
groups at baseline are taken into account using this approach. Furthermore, a secondary progressive disease course
at baseline was an exclusion criterion for both groups, and
the control group showed a baseline mean Expanded Disability Status Scale score significantly lower than the treated
group (see Table 1 in our article1). Therefore, Koch and
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relapsing, цtreated, natural, history, sclerosis, multiple, confounders, interferon
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