Multiple Sclerosis Journal
2016, Vol. 22(8) 983–985
DOI: 10.1177/
1352458516655218
© The Author(s), 2016.
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MULTIPLE
SCLEROSIS MSJ
JOURNAL
http://msj.sagepub.com 983
The identification of temporal trends in the incidence
of disease or in the phenotypic characteristics of com-
plex diseases such as multiple sclerosis (MS) over
short time intervals may lead to the recognition of
contributing environmental factors. In recent years,
investigators have reported a rising incidence of MS
in some world regions, an increasing female:male sex
ratio, and a progressively earlier age of symptom
onset.
1
However, analyses of temporal trends can suf-
fer from multiple biases, leading to erroneous conclu-
sions as previously reported for age of onset.
2,3
In this issue of Multiple Sclerosis Journal, Westerlind
et al. examined temporal trends in the diagnosis of
primary progressive multiple sclerosis (PPMS). They
used the Swedish MS registry to identify 16,915
persons with MS, representing six birth cohorts
(1946–1975) and seven date of diagnosis cohorts
(1980–2014).
4
They found that the proportion of per-
sons with PPMS at onset decreased from 19.2% in the
1946–1950 birth cohort to 2.2% in the 1971–1975
birth cohort, a remarkable decline. The authors have
thoughtfully attempted to address many of the poten-
tial biases that might account for this result, including
survival bias, inadequate duration of follow-up in
younger birth cohorts, and the effects of changing
diagnostic criteria. Nevertheless, it remains difficult
to accept this rapid decline in the occurrence of
PPMS, and this may reflect incomplete control of
these biases, which work together in complex ways.
First, survival bias is probably operating as evi-
denced by the older average age of onset of 46.3 in
the persons with PPMS in the oldest birth cohort
consistent with frequently reported age at onset as
compared to 34.6 years in the youngest birth cohort.
The average age at onset also declined in the relaps-
ing-onset cohorts, from 38.4 in the oldest cohort to
29.8 in the youngest. This also illustrates a potential
survivorship bias that may or may not be the same
as that in the PPMS cohort.
Second, the exclusion of the large proportion of
unclassified patients (8.6%), a proportion nearly as
large as those identified with PPMS (8.6%), may
influence the results. This may have contributed dif-
ferentially to reducing the denominator over time,
impacting their findings. We note that one of the sen-
sitivity analyses combined the two groups which
greatly reduced the incidence rate ratio to 0.89.
Finally, and perhaps most importantly, the inadequate
and differential duration of follow-up by birth cohort
may lead to a substantial overestimate of the decline in
the proportion of PPMS. Consider the fact that the
mean age at diagnosis for the 1945 birth cohort was
46.3. The current maximum age for the youngest
cohort is 41–45 in 2016 showing that the younger birth
cohorts are missing the older persons who get diag-
nosed with MS because they have not been diagnosed
yet, thus the differential follow-up time truncates the
period over which to make the diagnosis within a birth
cohort, affecting the prevalence in the cohorts.
Consider a simple mathematical example to illustrate
the effect of these issues. Suppose we have 1000 MS
patients in each birth cohort and we estimate the pro-
portion with PPMS to be 10% for each of those birth
cohorts. Therefore, each birth cohort would include
100 PPMS and 900 relapsing-onset multiple sclerosis
(ROMS) patients. We will adjust these numbers for
deaths, which decline by birth cohort; for the follow-
up time, which reduces the prevalence of PPMS in the
cohort; and, finally, for the elimination of the unclas-
sified group from the ROMS population. The adjust-
ments have been informed by the literature, but are
only meant to illustrate how such assumptions and
estimates combine to produce remarkable declines in
the prevalence of PPMS as shown in Table 1 of the
Westerlind article.
We assumed that 30% of the 1946–1950 birth cohort
will have died by 2016, based on findings from the
Declines in the diagnosis of primary
progressive MS: A critical change in
phenotype or critical measurement error?
Gary R Cutter, Amber Salter and Ruth Ann Marrie
Correspondence to:
GR Cutter
Department of Biostatistics,
School of Public Health,
The University of Alabama
at Birmingham, 1665
University Boulevard, Ryals
Public Health Building,
Birmingham,
AL 35294-0022, USA.
cutterg@uab.edu
Gary R Cutter
Department of Biostatistics,
School of Public Health, The
University of Alabama at
Birmingham, Birmingham,
AL, USA
Amber Salter
Department of Biostatistics,
Washington University in St.
Louis, Saint Louis, MO, USA
Ruth Ann Marrie
Departments of Internal
Medicine and Community
Health Sciences, University
of Manitoba, Winnipeg, MB,
Canada; Multiple Sclerosis
Clinic, Winnipeg, MB,
Canada
655218MSJ 0 0 10.1177/1352458516655218Multiple Sclerosis JournalGR Cutter, A Salter
research-article 2016
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