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Cognitive function did not improve after initiation of natalizumab treatment in relapsing-remitting multiple sclerosis. A prospective one-year dual control group study

Multiple Sclerosis and Related Disorders, November 2016, Pages 36 - 43



Cognitive impairment in multiple sclerosis (MS) is common and has severe implications. Natalizumab (NZ) has documented effects on relapse rate and radiological disease activity in relapsing-remitting MS (RRMS) but studies regarding its specific effects on cognitive functioning are few. Previous studies have reported improvement, however, often lacking relevant control groups. The objective of the present study was to evaluate the cognitive effects of NZ treatment, compared to patients on stable first-line treatment and healthy control subjects.


MS patients starting NZ (MS-NZ), MS controls with stable interferon beta therapy (MS-C) and healthy control subjects (HC) were evaluated twice with one year interval, using a cognitive test battery covering six cognitive domains. The effects of NZ on levels of self-reported depression, fatigue, daytime sleepiness and perceived health were also examined.


MS patients (MS-NZ and MS-C) had significantly lower baseline cognitive performance compared to HC (global score, p=0.002), but there were no significant differences between MS-NZ and MS-C. At follow-up, both MS-NZ and MS-C had improved significantly in four and five cognitive domains, respectively, and in global score (p=0.013 and p<0.001, respectively). HC improved significantly in three cognitive domains but not in global score. A regression analysis including baseline cognitive z-score and z-score change showed that participants with lower baseline scores had a significantly greater improvement, compared to those with better initial performance (p=0.021). There were no significant changes in depression, fatigue, daytime sleepiness or perceived health in MS-NZ or MS-C.


Initiation of NZ therapy did not result in true cognitive improvement over one year. Presumably, the increased test performance in both MS groups was artificial and due to retest effects that were stronger in patients with lower baseline performance. Adequate control groups are essential when evaluating cognitive functioning in intervention trials among RRMS patients.


  • Initiation of natalizumab did not result in true cognitive improvement over one year.
  • Repeated cognitive testing may improve test results in patients and control subjects.
  • Retest effects are stronger in individuals with a lower initial test performance.

1. Introduction

Cognitive impairment in multiple sclerosis (MS) is common, and has major impact on quality of life (Amato et al, 2013 and Langdon, 2011). To date, there is no proven effective rehabilitation program or symptomatic treatment for MS-related cognitive dysfunction (Amato et al., 2013, Rosti-Otajarvi and Hamalainen, 2014).

During recent years the possibility to treat MS with different increasingly efficient disease modifying treatments (DMT) has expanded substantially (Piehl, 2014). One of the most effective DMT is natalizumab (NZ), which significantly reduces radiological disease activity, frequency of clinical relapses and the risk of sustained progression of physical disability in relapsing-remitting MS (RRMS) (Havrdova et al, 2009 and Polman et al, 2006). However, only few studies have specifically investigated the possible effects of NZ treatment on cognitive functioning in RRMS. Open-label or retrospective studies have reported cognitive improvement (Iaffaldano et al, 2012, Lang et al, 2012, Mattioli et al, 2015, Mattioli et al, 2011, Morrow et al, 2010, Svenningsson et al, 2013, Wilken et al, 2013, and Kunkel et al, 2015), or less cognitive deterioration (Portaccio et al., 2013), with NZ therapy. Reduced fatigue (Putzki et al., 2009; Iaffaldano et al, 2012, Lang et al, 2012, Svenningsson et al, 2013, and Wilken et al, 2013), depression (Lang et al, 2012, Svenningsson et al, 2013, and Kunkel et al, 2015) and daytime sleepiness (Svenningsson et al., 2013) have also been reported after start of NZ treatment. Importantly, only two of the above mentioned longitudinal studies included a comparator group of MS patients with another DMT (Mattioli et al, 2015 and Portaccio et al, 2013) and none of the studies used healthy control subjects (HC) for comparison.

Improvement in cognitive test scores in longitudinal studies due to retest effects are well known (Levine et al, 2004 and Lezak, 2004). Such effects are not restricted to healthy individuals, but have also been demonstrated in MS patients (Jasperse et al, 2007, Jonsson et al, 2006, and Solari et al, 2005) and may differ in magnitude between healthy individuals and subjects from clinical samples (Heaton et al., 2001).

1.1. Objectives

The primary aim was to examine the effects of the first year of NZ treatment on cognitive functioning in RRMS patients, with HC and MS disease controls, treated with another DMT, as comparators. In addition, we studied the effects of NZ on measures of self-assessed depression, fatigue, daytime sleepiness and perceived health.

2. Materials and methods

2.1. Patients and healthy control subjects

RRMS patients and HC subjects were examined twice, with a retest interval of one year. All patients were diagnosed with MS according to the McDonald criteria (Polman et al., 2005) and recruited from the Department of Neurology at the Karolinska University Hospital (Solna), Stockholm, between February 2010 and June 2012. Demographic and background clinical data were obtained from an interview, medical records and the Swedish Multiple Sclerosis Registry ( These data included age, sex, years of education, duration of MS, current DMT and other ongoing medications. The recruitment of MS patients was not randomized.

We examined eighteen RRMS-patients that were initiating NZ-treatment (300 mg IV monthly; MS-NZ) as second line DMT based on local and national guidelines, where a large majority switched from interferon beta (IFNb). One patient chose not to start NZ treatment and left the study. Another patient was excluded from the analysis after stopping NZ-treatment after seven months due to pregnancy. Yet another MS-NZ patient was excluded from the analysis after declining to come back for the follow-up testing. Due to study logistics all remaining MS-NZ patients (n=15) had the first infusion of NZ before the baseline evaluation. However, testing was always performed before the second infusion and in the majority within two weeks from the first infusion.

Fifteen RRMS-patients on stable first-line DMT were recruited as a non-intervention control group (MS-C). They were addressed after recommendation from their regular neurologists or other staff members involved in their routine care. Exclusion criteria for MS-NZ and MS-C were other neurological or medical conditions that could affect cognitive function, psychiatric disorders other than depression, and substance abuse. Previous exposure to NZ, or other second or third line DMTs, were additional exclusion criteria. All patients were at a minimum of four weeks from a previous relapse or steroid treatment at testing.

HC subjects (n=12) were recruited among individuals from a larger group (n=89) who had performed cognitive testing at an earlier occasion, intended for cross-sectional studies (Sundgren et al, 2013, Sundgren et al, 2015a, and Sundgren et al, 2015b). In order to match the demographics of the MS-groups, HC subjects approaching one year since the previous test session were contacted and selected based on their sex, age and years of education. All included HC subjects confirmed that they were healthy, and had not experienced major illness since the prior visit. Their previous test battery comprised the same cognitive tests as in the present study, and results were used as baseline data. The second evaluation was performed a year after the first examination, except for two HC subjects who performed their second testing after approximately 1.5 years.

The protocol was approved by the regional ethics committee (Regionala etikprövningsnämnden i Stockholm) and the study was conducted in accordance with Good Clinical Practice guidelines and the principles of the Declaration of Helsinki.

2.2. Clinical instruments

Physical disability was assessed by the Kurtzke Expanded Disability Status Scale (EDSS) (Kurtzke, 1983). The assessments were performed by the principal investigator (M.S.) or collected from the medical records if performed shortly prior to the study. Depression was assessed with the Beck Depression Inventory (BDI) (Beck et al., 1988) and the Center for Epidemiologic Studies Depression Scale (CES-D) (Radloff, 1977). Assessment of fatigue was done with the Fatigue Severity Scale (FSS) (Krupp et al., 1989) and the Fatigue Scale for Motor and Cognitive functions (FSMC) (Penner et al., 2009). Daytime sleepiness was assessed with the Epworth Sleepiness Scale (ESS) (Johns, 1991). Furthermore, perceived health (PH) was evaluated with the first item from the Health Related Quality of Life Short Form (SF-12®) (Ware et al., 1996). It was scored on a Likert scale (1–5) where 1 is “excellent” and 5 is “poor”.

The HC group had received the BDI and FSS at their first testing (Sundgren et al, 2013, Sundgren et al, 2015a, and Sundgren et al, 2015b) but not the CES-D, FSMC, ESS or PH. Thus, they were only given the BDI and FSS at the second evaluation.

The scores from BDI, CES-D and FSMC may additionally be reported as two (BDI and FSMC) or four (CES-D) subscales (Penner et al, 2009, Radloff, 1977, and Sundgren et al, 2013). Due to the limited sample size and in order to reduce the number of comparisons, we chose to include only the total scores.

2.3. Cognitive assessment

Premorbid verbal IQ was assessed with the Swedish Lexical Decision Test (Almkvist et al., 2007). The cognitive test battery included ten cognitive tests, several of which consist of subtests, resulting in a total of 20 cognitive scores. The individual test scores were grouped into cognitive domains (Table 1). Several test scores measure more than one cognitive ability and are thus included in more than one cognitive domain. The cognitive domains were attention, executive functions, memory, processing speed, verbal ability and visual perception/organization. For each participant, a global score including all 20 individual cognitive test scores was also constructed, and was calculated as the average of the 20 z-scores obtained.

Table 1

Cognitive tests and cognitive domains.


Cognitive domain Cognitive tests
Memory Benton Visual Retention Testa
Rey Auditory Verbal Learning Testb
Rey Auditory Verbal Learning Test – Recallb
Verbal ability Vocabulary Testc
Controlled Oral Word Association Testd
Attention Digit Span Test, Forwarde
Digit Span Test, Backwarde
Digit Span Test, Totale
Trail Making Test, condition 1,2,3 and 5d
Color-Word Interference Test, condition 1 and 2d
Executive functions Controlled Oral Word Association Testd
Color-Word Interference Test, condition 1–4d
Trail Making Test, condition 1–5d
Digit Span Test, Backwarde
Visual perception/organization Benton Visual Retention Testa
Block Design Teste
Digit Symbol Coding Teste
Symbol Search Teste
Processing speed Digit Symbol Coding Teste
Symbol Search Teste
Controlled Oral Word Association Testd
Global score All tests, including subtests

a BVRT-5, Form C, Administration A (Sivan, 1992).

b RAVLT (Schmidt, 1996).

d Delis-Kaplan Executive Function System (D-KEFS) (Delis et al., 2001).

e Wechsler Adult Intelligence Scale-Third Edition (WAIS-III) (Wechsler, 1997).

The included tests and test order were identical for MS-NZ and MS-C. HC performed the same tests, but were also given five additional tests intended for other studies (data not shown). The cognitive tests were administered according to standard protocols by the same investigator (M.S.) to all participants. All tests were given in Swedish. Session time was approximately 70 min for patients but longer (110 min) in HC due to their larger test battery. All participants were tested in a distraction-free and quiet environment.

2.4. Statistics

Cognitive test scores were adjusted for the effects of age, sex and years of education as identified in linear regression analysis of data from a large group of healthy control subjects (n=89) tested with the same cognitive tests (Sundgren et al., 2013). The data were expressed as z-scores, where z =(measured value – mean value of control subjects)/ S.D. of control subjects. Baseline group differences were analyzed with ANOVA (age, years of education and IQ) or Chi-square tests (sex). Other group comparisons at baseline were made with t-test or with Wilcoxon rank sum test in case of non-normal distributed data. Paired t-test was used to analyze changes in data between the first and second examination. To reduce the number of comparisons, cognitive test results were only analyzed on domain levels and as a global score. The alpha level was p<0.05. Calculations were performed with Matlab R2013b and Statistics Toolbox (Mathworks Inc.) and IBM SPSS Statistics version 20.0.

3. Results

3.1. Baseline characteristics

Demographic properties, clinical data and cognitive domain performance of the MS-NZ, MS-C and HC groups at baseline are summarized in Table 2. There were no significant differences in age, sex, years of education or premorbid IQ between the three groups. All patients in the MS-C group had ongoing IFNb-1a therapy, given as intramuscular injection once a week (Avonex ®). Three MS-NZ patients and one MS-C patient were treated with antidepressants. No HC subject had ongoing psychotropic medication.

Table 2

Demographic properties, clinical data and cognitive performance of the study population at baseline. Cognitive domain values are expressed in z-scores. P-values in left column show comparison between MS-NZ and MS-C. P-values in right column show comparison between all three groups (a) or comparison between all MS patients and HC (b). n.s. (non significant).


MS-NZ (n=15) MS-C (n=15) p-value HC (n=12) p-value
mean S.D. mean S.D. mean S.D.
Age (years) 34.6 10.3 36.1 9.2 32.1 8.6 n.s.a
Female sex (%) 87 80 75 n.s.a
Education (years) 13.5 2.2 13.5 2.3 14.0 2.1 n.s.a
Premorbid IQ 100.3 8.2 102.4 11.3 106.5 9.5 n.s.a
Disease duration (years) 5.7 5.5 4.6 4.4 n.s.
EDSS (0–10) 2.9 1.2 1.5 1.2 0.009
BDI (0−63) 13.0 10.9 6.4 5.4 0.044 3.2 3.1 0.005b
FSS (1–7) 4.6 1.4 3.1 1.5 0.013 2.9 0.9 0.044b
CES-D (0–60) 17.4 12.2 9.6 7.7 n.s.
FSMC (20–100) 64.2 22.6 43.6 20.0 0.015
ESS (0–24) 7.1 4.1 6.2 4.3 n.s.
PH (1–5) 3.2 1.0 2.5 1.0 n.s.
Memory −0.38 1.45 −0.70 1.09 n.s. 0.31 0.71 0.033b
Verbal ability −0.51 0.90 −0.45 0.80 n.s. 0.17 0.90 0.034b
Attention −0.77 2.57 −0.57 0.95 n.s. 0.28 0.45 0.040b
Executive function −1.27 3.32 −0.71 0.83 n.s. 0.24 0.35 0.002b
Visual percep./org. −0.45 1.29 −0.60 0.71 n.s. 0.47 0.72 0.004b
Processing speed −0.64 1.33 −0.97 0.75 n.s. 0.43 0.66 0.001b
Global score −0.92 2.27 −0.67 0.65 n.s. 0.30 0.44 0.002b

MS patients (MS-NZ+MS-C) had significantly higher self-assessed depression (BDI) and fatigue (FSS) scores than HC (p=0.005 and p=0.044, respectively). Furthermore, MS patients performed significantly worse than HC in all cognitive domains (memory, p=0.033; verbal ability, p=0.034; attention, p=0.040; executive function, p=0.002; visual perception and organization, p=0.004; processing speed, p=0.001) as well as in the global score (p=0.002).

MS-NZ had longer disease duration than MS-C (mean 5.6 and 4.6 years, respectively), but the difference was not significant. EDSS was 2.9 and 1.5 in MS-NZ and MS-C, respectively (p=0.009). Furthermore, MS-NZ had significantly more symptoms of fatigue (FSS, p=0.013 and FSMC, p=0.015) and depression (BDI, p=0.044) than MS-C. However, the difference in CES-D was not significant (p=0.052). There were no significant differences between the two MS groups in PH or ESS, but there was a trend for worse perceived health in MS-NZ (p=0.090). MS-NZ and MS-C did not differ significantly in any cognitive domain function or in the global score. HC had better baseline visual perception and organization (p=0.042) than the average of HC subjects from which they were recruited (n=89) (Sundgren et al., 2013), but were not significantly different from the average in the other domains, or in the global score.

3.2. Missing data and clinical events during the study period

Two MS-NZ patients had incomplete cognitive testing at baseline (six missing tests) and they were retested at follow up with the tests completed at baseline. One MS-NZ patient and two MS-C patients did not return all self-assessment questionnaires at the first examination. There were no missing data in the HC group. Missing data were not replaced. Only complete data (with both a T1 and T2 value) entered the paired t-test analysis.

One MS-NZ patient was pregnant in gestational week 7 at follow-up (NZ treatment interrupted 34 days prior to second test session) but had received NZ for a full year (13 infusions) and she was kept in the analysis. Furthermore, one MS-C patient became pregnant during the study and stopped IFN-1a treatment, but remained in the study. Two MS-NZ and two MS-C each reported a relapse during the study period. However, for one of the MS-NZ patients, the relapse was not verified by a physician. Two MS-NZ patients, with no antidepressants at inclusion, were introduced to sertraline by their regular neurologist during the study period. Another four MS-NZ patients had psychotherapy, but no antidepressant treatment during the study period. One MS-NZ patient had an uncomplicated foot fracture three months into the study, and another had uncomplicated hernia surgery at ten months. Two MS-NZ and two MS-C patients underwent physical rehabilitation programs during the study period and they were exposed to cognitive tests as part of those programs. However, none of the tests were the same as in the present study.

Following local guidelines, the MS-NZ patients may have been tested with the symbol digit modalities test (SDMT) at start and every 6 months, apart from our study protocol. The SDMT has resemblance with the digit symbol coding test included in the present study protocol. MS-NZ patients thus likely had additional exposure to a processing speed test during the study period.

3.3. Clinical variables and cognitive scores during one year

Change in clinical variables and the global cognitive score are illustrated in Fig. 1. There were no significant changes in EDSS, BDI, CES-D, FSS, FSMC, PH or ESS in the MS-NZ or the MS-C group. In the HC group BDI did not change but, interestingly, FSS improved significantly (p=0.031). The global cognitive z-score improved significantly in both MS groups, but not in HC. The effect was 0.58±0.79 in MS-NZ (p=0.013) and 0.29±0.24 in MS-C (p<0.001). One patient in MS-NZ was an outlier with a baseline global score -8.1 and a change in global score of 3.1. Excluding this patient from the paired t-test in the MS-NZ group made little difference (p=0.002).

Fig. 1.

Fig. 1

Change in physical disability (EDSS) depression (BDI, CES-D), fatigue (FSS, FSMC), daytime sleepiness (ESS), perceived health (PH) and global cognitive score in the study population. Blue and green columns represent first and second examination, respectively, and bars show S.D. Significant differences between first and second examination are indicated with p-values. Non-significant differences are not indicated. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)


Changes in the different cognitive domains are illustrated in Fig. 2. MS-NZ improved significantly in memory (p=0.015), verbal ability (p=0.005), visual perception and organization (p=0.030), and processing speed (p=0.003). MS-C improved significantly in memory (p=0.016), attention (p=0.030), executive function (p=0.016), visual perception and organization (p<0.001), and processing speed (p<0.001). The HC group improved significantly in verbal ability (p=0.035), visual perception and organization (p=0.002) and processing speed (p=0.021). HC did not improve in the other three cognitive domains. There were no significant differences in z-score change between the two MS groups for the six cognitive domains or in the global score (not illustrated).

Fig. 2.

Fig. 2

Change in cognitive performance in the study population. Same symbols and notations as in Fig. 1 are used. Significant differences between first and second examination are indicated with p-values. Non-significant differences are not indicated.


It was hypothesized that the improvement in global score, observed in both MS groups but not in the HC subjects, may be due to a stronger retest effect in subjects with low baseline performance (Salthouse and Tucker-Drob, 2008; Dikmen et al., 1999). A regression analysis involving baseline global z-score and z-score change was performed (Fig. 3). One outlier (see above) was excluded from the regression analysis. Indeed, patients with lower baseline performance had significantly greater improvement at the second examination (p=0.015). The regression line had a similar slope in HC, but the effect was not significant which may be due to the small material. When data from all participants were ranked, the correlation was -0.36 (Spearman's rho, p=0.021). The results indicated that the improved global score in both MS groups may be due to a stronger retest effect in subjects with lower initial test performance.

Fig. 3.

Fig. 3

Correlation between baseline global z-score and z-score change. Lines fitted to data with linear regression. Slopes of the lines were −0.17 (p=0.015) for patients (MS-NZ and MS-C) and −0.19 (n.s.) for HC.


4. Discussion

We performed a prospective study of cognitive functioning in two groups of RRMS patients and HC. Our results demonstrate that NZ treatment during one year did not significantly improve cognitive functioning in RRMS patients over and above what was seen in control patients on stable first-line treatment. Thus, we found that both MS groups improved in several cognitive domains, as well as in global cognitive score, and that both patients and HC improved in test performance, presumably due to learning effects. This effect was largest for those with poorest cognitive test performance at baseline, similar to previous findings (Salthouse and Tucker-Drob, 2008; Dikmen et al., 1999). In the present study, significant retest effects were seen in, for instance, processing speed, which is the domain of most interest in MS cognition research.

To our knowledge, there are no previous studies of the effects of NZ treatment on cognitive functions in RRMS that have included both an MS comparator group and a HC group. In the present study, both MS groups had, on average, mild physical disability and relatively mild cognitive impairment. Uncontrolled longitudinal studies evaluating the effects of NZ treatment on cognitive functioning have reported improvement upon starting therapy (Iaffaldano et al, 2012, Lang et al, 2012, Morrow et al, 2010, Svenningsson et al, 2013, and Wilken et al, 2013). In another recently published retrospective uncontrolled study of RRMS patients (n=24) on NZ therapy, results showed significant improvements in attention, executive function and episodic memory over 3 years. RRMS patients with EDSS<3.0 improved more than those with EDSS>3.0 and the cognitive improvement was most significant after the first year of treatment (Mattioli et al., 2015). Two previous studies have reported a superior cognitive effect in NZ treated patients compared to MS pseudo control groups receiving first-line treatments (Mattioli et al, 2011 and Portaccio et al, 2013). The study by Mattioli et al. (2011) reported an improvement in one of nine cognitive test scores among NZ-treated patients, that significantly exceeded that of the MS controls (p=0.049). In the study by Portaccio et al. (2013), using a reliable change index method, NZ-treated RRMS patients had, after 1.5 years, a lower mean number of deteriorating cognitive tests than patients receiving IFNb. The study also included MRI measures of brain atrophy, and NZ-treated subjects had significantly less brain volume change than the IFNb treated group. The relationship between change in cognitive performance and treatment disappeared in a multivariate analysis when brain volume change was included. The authors concluded that the beneficial effect of NZ may be mediated by a reduction in brain atrophy.

In general, there is a paucity of studies on the effects of DMT on cognitive functioning in MS. Improved cognitive test performance after IFNb treatment have also been reported (Amato et al, 2013, Barak and Achiron, 2002, Fischer et al, 2000, Kappos et al, 2009, Patti et al, 2010, and Pliskin et al, 1996). Furthermore, a subset of MS patients (n=16) on stable IFNb treatment over 16 years remained cognitively intact (Lacy et al., 2013).

In the present study, both MS-NZ and MS-C showed significant improvement in more cognitive domains than HC. The global score improved in both MS groups, but not in HC. The disease duration in the MS-C group was relatively short (mean 4.6 years) and many patients in this group had been exposed to IFNb-1a for only a comparably short time. Thus, it cannot be ruled out that IFNb-1a and NZ have similar effects on cognition. However, this is unlikely since MS-C and MS-NZ had similar levels of cognitive impairment at baseline. If the MS-C patients continued to gain in cognitive function some years after beginning the treatment, it follows that these patients would have had a very poor cognitive status at onset of treatment. This is contradicted by their low EDSS and stable clinical course. Normal retest effects are more likely to be the explanation for the improved test scores, with larger effects in patients with low scores and smaller in those with normal scores, and in HC. This is a likely explanation for the larger cognitive test improvement in both MS groups compared to HC. Artificial improvement due to repeated cognitive testing is a well-established phenomenon. It can be detected in several cognitive domains, and it is largest in young adults (Salthouse et al., 2004). It can occur even after long retest intervals, and is present in a variety of clinical samples (Lezak, 2004 and Salthouse, 2010) including MS patients (Jasperse et al, 2007, Jonsson et al, 2006, and Solari et al, 2005). In a study on patients with mild cognitive impairment, suggestive of early Alzheimer´s disease, human immunodeficiency virus infection or Huntington´s disease, the learning effects predicted long term cognitive outcomes above and beyond baseline cognitive performance (Duff et al., 2007).

The present study did not give evidence that NZ reduces depression, fatigue, sleepiness or perceived general health, but the number of patients was relatively small and this analysis was not included as a primary objective. E.g., in MS-NZ, there was improvement in FSS (−0.49), FSMC (−4.73) and ESS (−1.53). If considered relevant, these changes would have needed n=42 (FSS), n=52 (FSMC) and n=35 (ESS) to be statistically significant at alpha 0.05 and beta 0.20. Notably, HC showed significant improvement in FSS, which makes speculations regarding specific NZ effects on fatigue even more difficult. This further stresses the need for the inclusion of control subjects when evaluating change in behavioral variables in any clinical sample, including RRMS patients. There were expected and documented clinical differences regarding levels of EDSS, depression and fatigue between the two MS groups. Needless to say, the present study does not permit a direct comparison between NZ and IFNb-1a on cognitive functioning in RRMS. Thus, MS-NZ patients are likely to have a more active disease than the MS controls, and therefore it may still be a relative benefit of being on NZ therapy as compared to remaining on first line DMT with regard to future cognitive functioning. However, we can conclude that RRMS patients with mild cognitive dysfunction, on stable IFNb-1a treatment and without other signs of clinical deterioration are not likely to gain in cognitive functioning across one year by switching to NZ.

Some limitations deserve mentioning. The study sample was relatively small and the MS patients were not randomly selected. Randomization is, however, very difficult to achieve in a clinical setting. Thus, patients with a stronger motivation for cognitive testing may have been over-represented. Such patients may also hold a stronger belief in a positive cognitive effect of their treatment. This may have increased the retest effects. Further, MS-NZ patients had baseline evaluations after their first infusion. There were no significant cognitive baseline differences between MS-NZ and MS-C. However, an acute cognitive change within one or two weeks from start of NZ therapy is unlikely. In the study by Portaccio et al. (2013), there were similarly no significant baseline differences in cognitive performance between the NZ intervention and comparator groups. In the present study, a reduction of baseline levels of depression, fatigue and sleepiness after the first NZ infusion cannot be ruled out. However, mean FSMC in MS-NZ was 64.2 at the first assessment, which is above the suggested cut-off level (≥63) for “severe fatigue” (Penner et al., 2009). Similarly, the same MS group had a mean CES-D of 17.4 at baseline, which is above the commonly used cut-off (≥16) suggestive of clinically meaningful depression (Lewinsohn et al., 1997). Another limitation is that four of the self-assessment scales (CES-D, FSMC, ESS, PH) were not included in the HC group. The relatively limited sample size increased the risk of a type II error regarding possible changes in fatigue and daytime sleepiness. A final limitation is that the investigators could not be blinded for group allocation.

5. Conclusions

Initiation of NZ treatment in RRMS patients did not result in a treatment related cognitive improvement during the first year on therapy. Repeated cognitive testing after one year may show normal retest effects that are stronger in patients with an initial poor cognitive test performance, which may give a false impression of improvement. This finding is important in relation to prior studies reporting such improvements without relevant control groups. Adequate control groups are important to address cognitive effects of DMT in RRMS.

Conflict of interest

F.P. has received unrestricted academic research grants from Biogen and Novartis, and travel support and/or compensation for lectures and/or participation in advisory boards from Biogen, Novartis, Genzyme and Teva, which has been exclusively used for the support of research activities. M.S., Å.W. and T.B. declare no conflict of interest.

Role of funding source

The funding source did not participate in any aspect of this work.


This study was supported by research grants from Stockholm County Council.


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a Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden

b Institute of Gerontology, School of Health and Welfare, Jönköping University, Jönköping, Sweden

Correspondence to: Department of Neurology, Karolinska University Hospital (Solna), 17176 Stockholm, Sweden.

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    Timothy Vartanian, Professor at the Brain and Mind Research Institute and the Department of Neurology, Weill Cornell Medical College, Cornell...
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    Claire S. Riley, MD is an assistant attending neurologist and assistant professor of neurology in the Neurological Institute, Columbia University,...
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    Rebecca Farber, MD is an attending neurologist and assistant professor of neurology at the Neurological Institute, Columbia University, in New...

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