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Sex as a determinant of relapse incidence and progressive course of multiple sclerosis

Tomas Kalincik, Vino Vivek, Vilija Jokubaitis, Jeannette Lechner-Scott, Maria Trojano, Guillermo Izquierdo, Alessandra Lugaresi, Francois Grand’Maison, Raymond Hupperts, Celia Oreja-Guevara, Roberto Bergamaschi, Gerardo Iuliano, Raed Alroughani, Vincent Van Pesch, Maria Pia Amato, Mark Slee, Freek Verheul, Ricardo Fernandez-Bolanos, Marcela Fiol, Daniele La Spitaleri, Edgardo Cristiano, Orla Gray, Jose Antonio Cabrera-Gomez, Vahid Shaygannejad, Joseph Herbert, Steve Vucic, Merilee Needham, Tatjana Petkovska-Boskova, Carmen-Adella Sirbu, Pierre Duquette, Marc Girard, Pierre Grammond, Cavit Boz, Giorgio Giuliani, Maria Edite Rio, Michael Barnett, Shlomo Flechter, Fraser Moore, Bhim Singhal, Elizabeth Alejandra Bacile, Maria Laura Saladino, Cameron Shaw, Eli Skromne, Dieter Poehlau, Norbert Vella, Timothy Spelman, Danny Liew, Trevor J. Kilpatrick, Helmut Butzkueven
DOI: http://dx.doi.org/10.1093/brain/awt281 3609-3617 First published online: 18 October 2013

Summary

The aim of this work was to evaluate sex differences in the incidence of multiple sclerosis relapses; assess the relationship between sex and primary progressive disease course; and compare effects of age and disease duration on relapse incidence. Annualized relapse rates were calculated using the MSBase registry. Patients with incomplete data or <1 year of follow-up were excluded. Patients with primary progressive multiple sclerosis were only included in the sex ratio analysis. Relapse incidences over 40 years of multiple sclerosis or 70 years of age were compared between females and males with Andersen-Gill and Tweedie models. Female-to-male ratios stratified by annual relapse count were evaluated across disease duration and patient age and compared between relapse-onset and primary progressive multiple sclerosis. The study cohort consisted of 11 570 eligible patients with relapse-onset and 881 patients with primary progressive multiple sclerosis. Among the relapse-onset patients (82 552 patient-years), 48 362 relapses were recorded. Relapse frequency was 17.7% higher in females compared with males. Within the initial 5 years, the female-to-male ratio increased from 2.3:1 to 3.3:1 in patients with 0 versus ≥4 relapses per year, respectively. The magnitude of this sex effect increased at longer disease duration and older age (P < 10−12). However, the female-to-male ratio in patients with relapse-onset multiple sclerosis and zero relapses in any given year was double that of the patients with primary progressive multiple sclerosis. Patient age was a more important determinant of decline in relapse incidence than disease duration (P < 10−12). Females are predisposed to higher relapse activity than males. However, this difference does not explain the markedly lower female-to-male sex ratio in primary progressive multiple sclerosis. Decline in relapse activity over time is more closely related to patient age than disease duration.

  • multiple sclerosis
  • sex
  • risk factors
  • MSBase
  • prediction

Introduction

Episodic exacerbations are defining phenomena for relapsing-remitting multiple sclerosis and can be directly associated with residual disability (Hirst et al., 2008). Even though the evidence remains inconclusive (Hutchinson, 2011), an association between high relapse rate in the first 2 years after disease onset and later accumulation of irreversible neurological impairment has been suggested (Scalfari et al., 2010; Kalincik et al., 2012). There have been only a limited number of studies delineating predictors of relapse activity, with only one study examining a large retrospective cohort (Held et al., 2005; Mowry et al., 2009; Tremlett et al., 2009). These studies suggested several predisposing factors, such as sex, age, ethnicity and time from multiple sclerosis onset. However, their outcomes, in particular those related to effect of sex on relapse incidence, have often been discordant.

There is a marked predominance of females among patients with multiple sclerosis with relapse-onset course. The sex ratios are 3:1 in relapsing-remitting and 3:2 in secondary progressive multiple sclerosis, but in primary progressive multiple sclerosis both sexes are represented equally (Runmarker and Andersen, 1993; Confavreux and Vukusic, 2006b; Alonso and Hernan, 2008; Koch-Henriksen and Sorensen, 2010).

We have used MSBase, a longitudinal, international, observational registry of patients with multiple sclerosis, to evaluate the effect of sex on relapse activity up to 40 years of multiple sclerosis duration or 70 years of age. We have directly compared the impacts of age and disease duration on relapse frequency in a predominantly contemporary multiple sclerosis cohort. We have also tested the hypothesis that the female-to-male ratio increases gradually with relapse activity and that the primary progressive disease represents a non-relapsing extreme along this continuum.

Patients and methods

Ethics statement

The MSBase registry (Butzkueven et al., 2006) was approved by the Melbourne Health Human Research Ethics Committee, and by the local ethics committees in all participating centres (or exemptions granted, according to applicable local laws and regulations). If required, written informed consent was obtained from enrolled patients, in accordance with the Declaration of Helsinki.

Patients and follow-up

Longitudinal clinical data from 18 885 patients from 55 multiple sclerosis centres in 25 countries were extracted from the MSBase registry in February 2012. Data recorded between the years 1951 and 2012 were used. The majority of the patients were enrolled in the MSBase registry in the year 2000 or later (75%), with 20% enrolled in years 1990–2000, 3% enrolled in years 1980–1990 and 0.9% of patients enrolled before 1980. The participating centres contributed between two and 1239 cases fulfilling the study inclusion criteria, with recorded annualized relapse rate (ARR) in relapse-onset multiple sclerosis, ranging from 0.1 to 2 and female-to-male ratio ranging from 0.9:1 to 4.4:1. The country-specific ranges were 2–3282 for the number of eligible patients, 0.2–2 for ARR in relapse-onset multiple sclerosis and 0.9–4.4:1 for female-to-male ratio. Patients with incomplete data (i.e. not fulfilling the minimal data set requirement, see below) or <1 year of recorded clinical follow-up were excluded. The minimal data set consisted of patient date of birth, sex, multiple sclerosis centre, dates of multiple sclerosis onset and clinical follow-up, disease course and disability (at inclusion and censoring), start and end dates of disease modifying treatment exposure and list of clinical relapses (including date of onset and relapse treatment status). Patients with relapse-onset multiple sclerosis (i.e. clinically isolated syndrome, relapsing-remitting multiple sclerosis, secondary progressive multiple sclerosis or relapsing-progressive multiple sclerosis) were included in all analyses. Patients with primary progressive multiple sclerosis were only included in the analyses comparing female-to-male ratios between relapse-onset and primary progressive multiple sclerosis (see below). Finally, patients with relapse-onset multiple sclerosis and at least 10 years of recorded follow-up, and all patients with primary progressive multiple sclerosis were included in a subgroup analysis of female-to-male ratios stratified by relapse activity.

The analysed data were recorded as part of routine clinical practice. The usual data entry practice at most centres was real time or near-real time data entry in relation to clinical visits. The MSBase protocol stipulates minimum annual updates of the minimum data set, but patients with less frequent visits were not excluded from the analyses. Data entry portal was either the iMed patient record system or the MSBase online data entry system.

A relapse was defined as occurrence of new symptoms or exacerbation of existing symptoms persisting for at least 24 h, in the absence of concurrent illness or fever, and occurring at least 30 days after a previous relapse (Schumacher et al., 1965). Date of onset was recorded for each clinical relapse. Formal scoring of relapse-associated disability was not required upon relapse entry. Disability was scored by accredited scorers (online Neurostatus certification was required at each centre) using the Expanded Disability Status Scale (EDSS). Duration of multiple sclerosis was calculated as the time from the patient-reported first clinical manifestation of the disease and relapsing/progressive onset of disease was assessed by participating neurologists. Primary progressive multiple sclerosis was defined as the disease with at least 1 year of progression from its first clinical manifestation and with zero recorded relapses. In each patient, unadjusted ARRs stratified by disease duration or patient age were calculated by including the initial relapse and the number of relapses for years for which clinical data were available. Censoring was defined to occur on the day of the last recorded clinical visit. Information about patient death and its relation to multiple sclerosis was not collected in the database.

To assure quality of the analysed data, only information from centres contributing at least 10 active records (i.e. cases with regular annual updates of clinical information) to the MSBase registry was used, as stipulated in the study protocol. A date of onset was required for all recorded events, including relapses, visits (with or without EDSS), changes in disease course and changes in treatment. Before the analysis the recorded data were verified using a series of automated procedures to identify any invalid or inconsistent entries.

Statistical analysis

Statistical analyses were carried out using Statistica 10 (Statsoft) and R (http://www.R-project.org). All hypotheses were tested at the two-tailed 0.05 level of statistical significance, after applying the Benjamini-Hochberg correction for multiple hypothesis testing. Two proportional hazards models with robust variance estimation (Andersen-Gill) and Efron approximation method, adjusted either for patient age or disease duration, were used to estimate cumulative hazard of relapses for each sex (cumulative hazard function is interpreted as the most probable count of repeatable events that would be expected for each individual by defined time, if the exposure to the risk started at Time 0). The outcome variable was time to relapse with multiple entries per patient allowed. The models were adjusted for pregnancy (proportion of time pregnant from the study enrolment or the previous recorded event to the next event/censoring, treated as time-varying variable) and immunomodulatory therapy, when any change in therapy with or without relapse was treated as a relapse (response) or non-relapse (censoring) event. The immunomodulatory agents considered were interferon β-1a 22 μg or 44 μg subcutaneous injection thrice weekly, interferon β-1a 30 μg intramuscular injection once weekly, interferon β-1b 250 μg subcutaneous injection every other day, glatiramer acetate 20 mg subcutaneous injection daily, natalizumab 300 mg intravenous infusion once monthly, fingolimod 0.5 mg orally once daily, dimethyl fumarate 240 mg orally twice or thrice daily, cladribine 10 mg orally once monthly for 2 months, and teriflunomide 7 mg or 14 mg orally once daily.

Two Tweedie models with index parameters 1.5 (i.e. compound Poisson-Gamma models) adjusted for sex, pregnancy and treatment (the latter two variables expressed as the proportion of time pregnant or treated with disease modifying agent throughout the recorded follow-up, respectively) were built to evaluate separately the effects of age and disease duration on ARR. Each patient contributed a single entry of overall ARR calculated as the number of relapses divided by the duration of the follow-up. A similar final Tweedie model including both age and disease duration was used to compare the effects of age and disease duration.

We evaluated the effect of relapse count on female-to-male ratio at any completed observational year using two logistic mixed effect models. The outcome in these models was the probability of being female (i.e. the female gender recorded in individual patients), with multiple entries per patient allowed (one entry per each completed year of follow-up/chronological age) and the random effect being the patient unique identifier. The predictors of interest were the number of relapses recorded in any completed follow-up year, patient age or multiple sclerosis duration (either age or multiple sclerosis duration was used in either model), and their interaction term. The models were adjusted for age at multiple sclerosis onset, disease course, pregnancy (proportion of time in any completed year) and immunomodulatory therapy (proportion of time in any completed year).

Results

Of the 18 885 patients in the MSBase registry (17 021 with relapse-onset multiple sclerosis, 1018 with primary progressive multiple sclerosis and 846 with the information about disease course missing), data from 11 570 relapse-onset and 881 (7%) primary progressive patients fulfilled the inclusion criteria (Fig. 1). The female-to-male ratio among the excluded patients (n = 6434) was 2.4:1 (4516 females, 1918 males, no missing data). Tables 1 and 2 show demographic and clinical characteristics of the included patients with relapse-onset and primary progressive multiple sclerosis, respectively. Patient characteristics were comparable between females and males, including visit frequency, with only marginally shorter disease duration and larger end-of-follow-up disability among males.

Figure 1

CONSORT flowchart of patient disposition. CIS = clinically isolated syndrome; MS = multiple sclerosis; PPMS = primary progressive multiple sclerosis; RPMS = relapsing-progressive multiple sclerosis; RRMS = relapsing-remitting multiple sclerosis; SPMS = secondary progressive multiple sclerosis.

View this table:
Table 1

Characteristics of the studied population with relapsing multiple sclerosis

FemalesMalesCohen’s d
Patients, n82953275
Age
    At inclusion, years37.0 ± 11.237.2 ± 11.20.02
    At censoring, years44.1 ± 11.744.4 ± 11.50.02
Ethnicity
    Caucasian, n (%)5102 (62)1992 (61)
    Hispanic, n (%)123 (2)64 (2)
    Asian, n (%)269 (3)7 (2)
    African, n (%)44 (0.5)12 (0.4)
    Other, n (%)227 (3)117 (4)
    Not specified, n (%)2530 (31)1023 (31)
Follow-up duration, years*5.8 (3–9.5)5.9 (3.1–9.7)0.01
Disease duration
    At inclusion, years*2.9 (0.4–9.3)2.5 (0.4–8.5)0.11
    At censoring, years*11.3 (6.2–18.1)10.8 (6.1–17.5)0.04
    Relapses, n35 72512 637
Disease course
 At inclusion
        CIS, n (%)2981 (36)1240 (38)
        RRMS, n (%)4731 (57)1721 (53)
        SPMS, n (%)412 (5)182 (6)
        RPMS, n (%)171 (2)132 (4)
 At censoring
        CIS, n (%)1521 (18)669 (20)
        RRMS, n (%)5488 (66)1984 (61)
        SPMS, n (%)1115 (13)490 (15)
        RPMS, n (%)171 (2)132 (4)
Disability
    At inclusion, EDSS*2 (1.5–3.5)2.5 (1.5–4)0.08
    At censoring, EDSS*2.5 (1.5–5)3 (1.5–6)0.14
    Received DMDs, n (%)3956 (48)1617 (49)
  • *Median (interquartile range); otherwise mean ± SD are shown.

  • CIS = clinically isolated syndrome; DMDs = disease-modifying drugs; RPMS = relapsing-progressive multiple sclerosis; RRMS = relapsing-remitting multiple sclerosis; SPMS = secondary progressive multiple sclerosis.

View this table:
Table 2

Characteristics of the group with primary progressive multiple sclerosis

Patients, n (females, %)881 (55)
Age
    At inclusion, years49.4 ± 11.0
    At censoring, years53.9 ± 11.2
    Follow-up duration, years*2.6 (0.5–7.0)
Disease duration
    At inclusion, years*5.8 (2.6–11.4)
    At censoring, years*10.8 (6.2–17.5)
Disability
    At inclusion, EDSS*5 (3.5–6.5)
    At censoring, EDSS*6 (4–7)
    Received DMDs, n (%)190 (22)
  • *Median (interquartile range); otherwise mean ± SD are shown.

  • DMDs = disease-modifying drugs.

Numbers of patients with relapse-onset multiple sclerosis included in the analysis stratified by disease duration and age are shown in Fig. 2A and B. In 82 552 patient-years of observation recorded among the relapse-onset patients, 48 362 relapses were recorded. Of these, 42% were concurrent with clinical visits. Figure 2C and D shows unadjusted ARR with respect to disease duration and age. Within the first year of multiple sclerosis, the relapse rate was relatively high (1.1 relapse/year), which was a result of its inflation by inclusion of the first recorded clinical event. Thereafter, the ARR gradually decreased from 0.5 at 2 years to 0.1 at 40 years. Also, a marked decline in ARR with age was seen, when ARR decreased from 0.9 at the age of 17 to 0.1 at the age of 70. Importantly, females tended to show higher unadjusted ARR during the initial 18 years of multiple sclerosis duration and between 27 and 49 years of age. These differences were further enhanced by adjusting the ARR for multiple sclerosis duration/patient age, pregnancy and treatment (Fig. 2E and F). Females showed consistently higher adjusted ARR [on average by 17.7%, 95% confidence interval (CI) = 15.1–20.3%] than males throughout the disease duration and at every chronological age (risk ratio = 1.08, 95% CI = 1.06–1.11, P ≤ 10−16, Tweedie models), with a relative decrease in this difference at long multiple sclerosis durations or at an older age. Accordingly, the cumulative hazard of relapses (Fig. 2G and H) was consistently higher among females and reached 9.3 (95% CI = 9.1–9.5) in females and 8.4 (95% CI = 8.1–8.7) in males at 40 years after multiple sclerosis onset (hazard ratio = 1.1, 95% CI = 1.05–1.14, P = 10−5, Andersen-Gill model). At the age of 70, the cumulative hazard reached 28.5 (95% CI = 26.6–30.7) in females and 26.7 (95% CI = 24.7–28.8) in males (hazard ratio = 1.1, 95% CI = 1.07–1.14, P < 10−12, Andersen-Gill model).

Figure 2

Incidence of relapses in females and males with relapse-onset disease course, stratified by disease duration and chronological age. Patient disposition (A and B) is only shown for patients with complete respective observational years. Annualized relapse rate unadjusted for other potential confounders (C and D) and adjusted for age (E) or disease duration (F), treatment and pregnancy using Tweedie models are shown (E and F). Each patient contributed a single ARR at censoring. P-values for effects of sex, disease duration and age are shown (Tweedie regression). Cumulative hazard functions for relapses in female and male subpopulations, adjusted for age (G) or disease duration (H), treatment and pregnancy using Andersen-Gill models (G and H), with each patient contributing multiple time-to-relapse entries. All results are stratified by disease duration (A, C, E, G) and patient age (B, D, F, H). Error bars and dashed lines show 95% CIs.

These observations in relapse-onset multiple sclerosis were further confirmed by the fact that the female-to-male ratio was higher among the patients with higher annual relapse count (Fig. 3, β = 0.03, P < 10−12, logistic mixed models). Within the initial 5 years of disease onset, the ratio increased from 2.3:1 in patients with no relapses to 3.3:1 in patients with at least four relapses per year. Interestingly, this effect was accentuated by longer disease duration, as the sex ratio among the frequently relapsing patients exceeded 4:1 (interaction term P < 10−12, logistic mixed model). A similar interaction effect was seen for age (P < 10−12, logistic mixed model). Overall, the sex ratios stratified by disease course were 2.1:1 for clinically isolated syndrome (as defined by the McDonald criteria; Polman et al., 2005), 2.8:1 for relapsing remitting multiple sclerosis, 2.2:1 for secondary progressive multiple sclerosis and 1.3:1 for relapsing progressive multiple sclerosis. Compared to the patients with relapse-onset multiple sclerosis, the population diagnosed with primary progressive disease showed a significantly lower female-to-male ratio across all disease durations or patient age groups: ∼1.2:1 (β = 1.13–1.16, P < 10−12, logistic mixed model; Fig. 3). In fact, the female-to-male ratio in patients with relapse-onset multiple sclerosis and zero relapses in any given year was 2:1 and therefore almost double that of the patients with primary progressive multiple sclerosis. In a subgroup analysis including 2969 patients with relapse-onset multiple sclerosis and data recorded over at least 10 years, the sex ratio increased from 2.2:1 in those with zero overall relapses to 3.2:1 in those with eight or more relapses captured during their 10-year follow-up (Fig. 4). In those with zero overall relapses, the start of the 10-year follow-up period did not coincide with their disease onset; the diagnosis of relapsing-remitting multiple sclerosis was based on their relapse activity preceding the recorded follow-up. In 881 patients with primary progressive multiple sclerosis (and therefore no recorded relapses) regardless of the duration of their follow-up, the female-to-male ratio was 1.2:1.

Figure 3

Female-to-male ratios stratified by disease duration and chronological age. Unadjusted distributions of the female-to-male (F:M) ratios by disease duration (A) and patient age (B) are shown for patients with relapse-onset multiple sclerosis (blue) stratified by annual relapse numbers and patients with primary progressive multiple sclerosis (yellow). Each point represents a female-to-male ratio among the patients with corresponding number of relapses in a completed observational year. Numbers of patients per timepoint are indicated. Patients were allowed to contribute entries at multiple years. Estimated mean is shown as distance-weighted least squares surface (relapse-onset multiple sclerosis) and red least squares line (primary progressive multiple sclerosis).The mean estimation does not extend beyond two relapses in patients with >20 years of multiple sclerosis duration or 50 years of age, as the amount of the corresponding data was insufficient.

Figure 4

Female-to-male ratios in relapse- versus progressive-onset multiple sclerosis. Female-to-male ratios (F:M) by total number of relapses recorded over a 10-year follow-up period. Patients with relapse-onset multiple sclerosis with 10-year followup data available (n = 2969) and those with primary progressive multiple sclerosis (n = 881) are compared. Circle sizes indicate number of patients within each stratum. MS = multiple sclerosis.

Among the patients with relapse-onset multiple sclerosis, the incidence of relapses declined with both multiple sclerosis duration (by 0.01 per year, 95% CI = 0.0001–0.03) and patient age (by 0.01 per year, 95% CI = 0.006–0.02). This was confirmed by the adjusted Andersen-Gill models (multiple sclerosis duration: hazard ratio = 0.87, 95% CI = 0.864–0.872, P < 10−12; age: hazard ratio = 0.95, 95% CI = 0.949–0.953, P < 10−12). The two separate Tweedie models (dispersion parameters = 0.52 and 0.51) further confirmed the significant effects of multiple sclerosis duration (rate ratio = 0.99, 95% CI = 0.992–0.996, P = 10−11) and age (rate ratio = 0.98, 95% CI = 0.982–0.985, P < 10−12) on ARR. Interestingly, in the final Tweedie model containing both multiple sclerosis duration and patient age (dispersion parameter = 0.51), only the patient age was found to have an independent negative association with ARR (rate ratio = 0.98, 95% CI = 0.979–0.983, P < 10−12).

Discussion

In a large, mostly contemporary population of patients followed in the MSBase registry, females have a higher relapse rate than males throughout the course of multiple sclerosis. The sex ratio in primary progressive multiple sclerosis is markedly different from that in relapse-onset multiple sclerosis and is discrete from the gradient determined by the relapse frequency. We have confirmed a strong inverse relationship between relapse frequency and either disease duration or age. Of these two collinear factors, chronological age is more closely related to the relapse incidence.

In the only available retrospective cohort study of predictors of relapse incidence, Tremlett et al. (2008) showed that females had 14.3% higher ARR than males. We have confirmed this observation by demonstrating a similar sex effect of 17.7%. Compared to Tremlett et al. (2008) our recorded ARR was approximately double (0.59 versus 0.23, range 0.1–0.9 versus 0.08–0.29 depending on patient age, respectively), despite the presumed higher proportion of patients receiving disease modifying treatment. This could be attributed to the inclusion of the first clinical episodes in the relapse count in our study and the near real-time data entry in the MSBase registry, which could have partially ameliorated the expected under-reporting of the relapses recorded retrospectively.

Other literature reporting incidence of relapses in multiple sclerosis only describes relatively short follow-up periods. A series of studies identified young age (West et al., 2006; Mowry et al., 2009) and short disease duration (Held et al., 2005) but not sex as being independently predictive of higher relapse incidence during 1-year observational periods. The discrepancies between these studies and our present analysis could be explained by the differences in statistical power determined by the size of the cohorts and the analytical designs. With respect to the low effect-to-noise ratio, the other studies were most probably underpowered to assess the effect of sex, as they only evaluated information derived from 105–727 patient-years.

We have seen that females are over-represented among patients with high relapse frequency, in particular later in the disease course and at older chronological age. This suggests that the attenuation of clinically apparent episodic inflammatory activity is delayed in females compared with males. In addition, higher mortality from multiple sclerosis-unrelated causes in males could potentially contribute to this phenomenon; however, the lack of detailed mortality data in the MSBase registry prevented the evaluation of this potential confounder. Importantly, the follow-up duration, which did not differ between the enrolled females and males, did not support sex-dependent study drop-out.

The difference in relapse risk associated with sex probably only plays a small role in explaining the reported differences in sex ratios between patients with relapse- and progressive-onset multiple sclerosis (Confavreux and Vukusic, 2006b; Kampman et al., 2013). As males show less frequent relapse activity throughout the disease course and lifespan, one could argue that their disease is more likely to be classified as progressive. However, the sex ratio among patients with primary progressive multiple sclerosis is still distinct from that among patients with relapse-onset multiple sclerosis and no relapse activity observed during the study period (Figs 3 and 4). Thus, we rejected the hypothesis that sex difference in propensity to relapses is fully accountable for the different sex ratios between relapse- and progressive-onset multiple sclerosis. From this perspective, primary progressive multiple sclerosis cannot be viewed as a mere extreme along the continuum of relapse activity in relapsing-remitting multiple sclerosis.

It is of further interest how the relapse incidence interacts with progression of disability. It has been previously suggested that early relapses may be associated with the development of permanent disability (Lublin et al., 2003; Hirst et al., 2008; Tremlett et al., 2009; Leray et al., 2010; Scalfari et al., 2010; Kalincik et al., 2012). There is also evidence both supporting (Confavreux et al., 2003; Confavreux and Vukusic, 2006a; Leray et al., 2010) and opposing (Trojano et al., 1995; Amato et al., 1999; Simone et al., 2002) the common view of faster disability accrual in males. Clearly, the associations between sex and disability warrant further clarification in observational studies, with the perspective of elucidating the complex interactions between sex, relapses and disability.

Multiple sclerosis duration and patient age are two largely collinear variables, whose effect on disease outcomes is difficult to differentiate. Whether the multiple sclerosis relapse activity is determined predominantly by the time from multiple sclerosis onset, or by patient age, is not known. Whereas some works identified disease duration as an independent predictor of relapse incidence (Held et al., 2005), others reported independent effect of age (Inusah et al., 2010). Tremlett et al. (2008) described a faster decline in ARR with disease duration in patients with later multiple sclerosis onset. It is possible that this interaction effect was in fact driven by the effect of age, but a direct statistical comparison between the effects of age and disease duration was not reported. In our present study, we have directly compared these two collinear variables using a multivariate Tweedie model. Our analysis indicates a dominant role of chronological age (∼2% per year decrease in ARR) over that of disease duration (∼1% per year decrease in ARR). This observation is complementary to previous works, which demonstrated that age at onset of progressive phase is remarkably similar between patients with primary progressive versus relapsing-remitting/secondary progressive disease course, suggesting that presence and duration of relapsing phase is, to a great extent, defined by patient age (Confavreux and Vukusic, 2006b; Leray et al., 2010; Scalfari et al., 2011).

Our analysis was carried out in a large international observational cohort: the MSBase registry. The studied population was representative of patient populations managed at large academic multiple sclerosis centres, which might limit generalization of our observations to a prevalent population. Inclusion in the MSBase might have posed a risk of recruitment bias; this was subject to the criteria for patient inclusion at the participating centres. Also, preferential data entry of patients with relapse-onset disease course at the study sites could have resulted in a relative under-representation of patients with primary progressive disease (which in our study was ∼7%). Selection bias was potentially introduced by the applied inclusion criteria. However, the fact that female-to-male ratios were comparable between the excluded and included populations rendered this situation unlikely. Survival bias could potentially have been introduced in case the patients with more pronounced disability were more often lost to follow-up. This hypothetical situation might favour the sex with slower disability accrual. On the other hand, given the parallel patient disposition of both sexes with respect to disease duration and patient age, the survival bias was improbable (Fig. 2A and B). The information before year 2000 represented data transferred from other clinical databases, and constituted only a small proportion of the evaluated data. The ARR and subsequently the differences studied in our analysis could have been underestimated by the possible relapse under-reporting. The differences in relapse reporting at the participating centres, as implied by the variability in the centre-specific ARRs, could have inflated the under-reporting error. On the other hand, the fact that only 42% of the recorded relapses were concurrent with a recorded clinical visit and that EDSS validation of relapses was not required indicates that relapse over-reporting could have occurred. For all of these potential confounders, we presume that their influence applied consistently across the studied population, regardless of patient sex, age or disease duration. It should be noted that our analysis contained remarkable statistical power provided by 82 552 patient-years from a longitudinal patient cohort with a mean follow-up period of 6 years. Overall, we were able to analyse ARR over 40 years of disease duration and 70 years of age.

In this study we evaluated the effect of sex on the incidence of multiple sclerosis relapses throughout the disease and lifespan and in the relapse-onset versus primary progressive course in a longitudinally followed large patient population. The outcomes help elucidate patterns of multiple sclerosis activity determined by sex and in the future might lead to our improved understanding of multiple sclerosis aetiopathogenesis.

Funding

The work was supported by the Multiple Sclerosis Research Australia Postdoctoral Fellowship to TK [11-054], NHMRC Career Development Award (Clinical) to H.B. [ID628856], NHMRC Project Grant [1032484], NHMRC Centre for Research Excellence [Grant ID 1001216] and the MSBase Foundation. The MSBase Foundation is a not-for-profit organization that receives support from Merck Serono, Biogen Idec, Novartis Pharma, Bayer-Schering, Sanofi-Aventis and BioCSL.

Acknowledgements

MSBase study group contributors: From MS-Centrum Nijmegen, The Netherlands, Dr Cees Zwanikken; from Francicus Ziekenhuis, The Netherlands, Ms Leontien den Braber-Moerland; from Jeroen Bosch Ziekenhuis, The Netherlands, Dr Erik van Munster; from Centre hospitalier del’Universite de Montreal, Hopital Notre-Dame, Canada, Dr Elaine Roger and Dr Pierre Despault; from the Royal Melbourne Hospital, Australia, Dr Mark Marriott, Dr Anneke Van der Walt, Dr John King, Dr Katherine Buzzard, Dr Jill Byron and Ms Lisa Morgan; from Box Hill Hospital, Monash University, Australia, Dr Olga Skibina and Ms Jodi Haartsen; from St Vincent’s Hospital, Australia, Dr Mark Paine; from Department of Neuroscience and Imaging, University ‘G. d’Annunzio’, Italy, Dr Giovanna De Luca, Dr Valeria Di Tommaso, Dr Daniela Travaglini, Dr Erika Pietrolongo, Dr Maria di Ioia and Dr Deborah Farina; from Hospital Italiano, Argentina, Dr Juan Ignacio Rojas and Dr Liliana Patrucco; from Consultorio Privado, Buenos Aires, Argentina, Dr Aldo Savino; from Hopital Tenon, Paris, France, Dr Etienne Roullet; from FLENI, Argentina, Dr Jorge Correale and Dr Celica Ysrraelit; from Ospedale di Macerata, Italy, Dr Elisabetta Cartechini and Mr Eugenio Pucci; from John Hunter Hospital, Australia, Dr David Williams and Dr Lisa Dark; from Sheba Medical Center, Tel Hashomer, Israel, Dr Joab Chapman; from Hospital Fernandez, Argentina, Dr Norma Deri; from Hospital Ecoville, Brazil, Dr Walter Oleschko Arruda; from HIGA Gral. San Martin La Plata, Argentina, Dr Santiago Vetere; from Jahn Ferenc Teaching Hospital, Hungary, Dr Csilla Rozsa and Dr Krisztian Kasa; and from Thomas Jefferson University, Philadelphia, USA, Dr Donald McCarren.

Footnotes

  • *These authors contributed equally to this work.

  • Contributing members of the MSBase Study Group are listed in the Acknowledgements section.

Abbreviations
ARR
annualized relapse rate
EDSS
Expanded Disability Status Scale

References

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