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NTRODUCTION
Measuring clinical disability in patients with MS
Clinical disability in patients with MS is typically evaluated using Kurtzke’s Expanded Disability Status Scale
( EDSS
), 1, 2 scores on which range from 0 (a normal neurological exam) to 10 (death due to MS). Scores from 0 to
3.5 reflect an individual’s increasing disability across the eight, mutually-exclusive Functional Systems that are assessed in order to determine an individual’s EDSS score [ i.e.
, (i) Pyramidal (ambulation), (ii) Cerebellar
(coordination), (iii) Brain stem (speech and swallowing), (iv) Sensory (touch and pain), (v) Bowel and bladder functions; (vi) Visual, (vii) Mental, and (viii) Other ( i.e.
, any other neurological findings due to MS)]. Importantly, however, scores of 4 or more are heavily weighted on ambulation: (i) scores from 4.0 to 5.5 indicating an increasingly-limited ability to walk; (ii) scores from 6.0 to 6.5 indicating the unilateral – and then the bilateral – need of a cane, crutch, or brace in order to walk; (iii) scores from 7.0 to 9.0 indicating an increasingly-disabled restriction to a wheelchair and then to a bed; and (iv) a score of 9.5 indicating a totally-helpless, bed-ridden patient who is unable to communicate or swallow. Furthermore, as reviewed by Goodin, 3 in addition to emphasizing ambulation and not adequately covering other functions ( e.g., cognition), the EDSS has been criticized for: (i) being subjective and complicated to score, (ii) having poor intra- and inter-rater reliability, and (iii) being ordinal and nonlinear with respect to disability. Nevertheless, despite these and other criticisms ( e.g., its non-linearity 4 and its
unresponsiveness 5, 6 ), the EDSS is still one of the most – if not the most – widely-used measures of clinical disability
in studies of patients with MS.
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ETHODS
Brain MRI
Determination of T2-LL and T1-LL values
The eFigure below illustrates the steps involved in segmenting each patient’s manually-corrected T
2
-hyperintense lesions ( cT2 ) and their manually-corrected T
1
-hypointense lesions ( cT1 ).
First, a Bayesian-tissue-classification approach 7 was used to automatically combine the normalized intensityinformation in each patient’s registered T
2
-, proton-density- ( PD ), and T
1
-weighted magnetic resonance images in order to generate an automatically-segmented T2 lesion ( aT2 ) mask for the cerebral white matter of that individual.
This aT2 mask (bottom left, automatically-segmented T2 lesions shown in yellow) was then verified and, if
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Clinical Disability and Lesion Load in Patients with MS – Online-Only Material page 4 of 11 necessary, corrected by one of seven well-trained readers in order to generate that patient’s cT2 lesion mask for each slice (bottom middle, manually-corrected T2 lesions shown in red).
The total volume of cT2 lesion masks across all slices in the patient’s cerebrum was calculated automatically and considered to be their total cerebral-white-matter T2-lesion-load ( T2-LL ). Cerebral-white-matter voxels in a patient’s T
1
-weighted image were considered to make up that patient’s cT1 lesion mask (bottom right, manuallycorrected T1 lesions shown in red) if they were both: (i) located within their cT2 lesion mask and (ii) had intensity values that were less than 75% of that of their cerebral-white-matter neighbours. The total volume of cT1 lesion masks across all slices in the patient’s cerebrum was calculated automatically and considered to be their total cerebral-white-matter T1-lesion-load ( T1-LL ). Based on these segmentations, T2-LL and T1-LL values were generated automatically for each patient.
Reader Inter- and Intra-Rater Reliability
The seven readers who generated the lesion labels in this study had previously undergone: (i) extensive training on similar MRI data from a large set of patients, and (ii) post-training testing on a “ Test ” set from 10 representative patients. As determined by their trainer (SJF), these Test scans had: (i) manually-corrected T2-LL values of between of 1.2 and 62.0 cc, and (ii) manually-corrected T1-LL values of between 0.2 and 12.9 cc. The readers’ manually-corrected Test-scan segmentations showed excellent inter-rater reliability relative to their trainer’s reference segmentations, both for: (i) T2 lesions [ Dice kappa values 8 across the 10 pairs of scans ( kappa ): mean
(range) = 0.94 (0.92 – 0.95); and intra-class correlations amongst the two sets of 10 scans ( ICC ): mean (range) =
0.99 (0.99 – 1.00)], and (ii) T1 lesions [ kappa = 0.88 (0.81 – 0.92); ICC = 0.99 (0.99 – 1.00)]. The readers’ manually-corrected Test-scan segmentations also showed excellent intra-rater reliability with a lag of about one week between reads, again both for (i) T2 lesions [ kappa : 0.94 (0.91 – 0.96); ICC : 0.99 (0.99 – 1.00)], and (ii) T1 lesions [ kappa : 0.89 (0.81 – 0.93); ICC : 0.99 (0.99 – 1.00)].
Statistical Analysis
Bivariate-Relationships: LOWESS Smoothers
A LOWESS smoother is created by running along the x-values and finding predicted values from a weighted average of nearby y-values – the surface being allowed to flex locally in order to better fit the data. In all of the plots shown in Figure 2, a tension of 0.5 was used, which means that a maximum of 50% of the points were included
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Clinical Disability and Lesion Load in Patients with MS – Online-Only Material page 5 of 11 in each running window used to generate a predicted value; please note, however, that practically identical results were obtained using tensions of 0.2, 0.3, 0.4, and 0.5).
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Bivariate relationships
The eTable below presents Pearson-product-moment-correlation matrices showing r -values (and associated p values) for all of the bivariate relationships amongst the patients’ demographic, clinical, and cube-rooted ( cr ) T2 and
T1 lesion-load ( LL ) data.
Spearman rank-order correlations were completely consistent with these and are not presented here. Correlations that are statistically significant at p < 0.05 are bolded, and those that are large ( i.e.
, r >
0.50) are underlined.
(n = 92; EDSS 0 - 6.0) r ( p ) Age Duration EDSS Score cr-T2-LL
Duration
EDSS Score cr-T2-LL cr-T1-LL
0.600 (< 0.00001)
0.254 (0.0147)
-
0.337 (0.00101)
0.033 (0.75692)
0.118 (0.26256)
0.324 (0.00164)
-
-
0.457 (< 0.00001)
-
-
-
0.346 (0.00072) 0.523 (< 0.00001) 0.890 (< 0.00001)
(n = 110; EDSS 0 - 9.5) r ( p ) Age Duration EDSS Score
Duration
EDSS Score cr-T2-LL cr-T1-LL
0.628 (< 0.00001) -
0.325 (0.00054) 0.456 (< 0.00001)
0.135 (0.16082)
-
-
0.393 (0.00002) 0.548 (< 0.00001) cr-T2-LL
-
-
-
0.230 (0.01579) 0.442 (< 0.00001) 0.619 (< 0.00001) 0.904 (< 0.00001)
Regardless of EDSS Subgroup ( i.e.
, Limited-EDSS vs. Full-EDSS), we found that: (i) even though the patients’ ages and symptom durations were strongly correlated, their symptom durations consistently showed larger correlations with both their cr-LL values and their EDSS scores than did their ages; and (ii) even though the patients’ cr-T2-LL values and cr-T1-LL values were strongly correlated, their cr-T1-LL values consistently showed
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Clinical Disability and Lesion Load in Patients with MS – Online-Only Material page 7 of 11 larger correlations with their EDSS scores than did their cr-T2-LL values. Together, these findings suggest that the patients’ symptom durations and T1-LL values are more clinically-relevant than their ages and T2-LL values.
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The benefits of decreasing variability while increasing statistical power and pathological specificity
In the present study, we attempted to minimize the amount of non-biological sources of variability that may have contributed to previous findings of highly-variable and, on average, only-moderate correlations between
EDSS-measured clinical disability and T2-LL in patients with MS.
3, 9, 10 Furthermore, we attempted to maximize
our statistical power by: (i) examining the entire range of the EDSS, and (ii) including data from a large sample of patients with MS. Finally, we tried to increase the pathological specificity of the patients’ MRI-measured cerebral-
WM-LL values by also quantifying their T1-LL, which has been shown to be more indicative of the extent of destructive lesional-pathology in patients with MS.
11 In so doing, we were able to find statistically-significant evidence for: (i) a large relationship between our patients’ EDSS scores and their T2-LL values, and (ii) an evenlarger relationship with their T1-LL values. Importantly, we were also able to show that consideration of scores across the entire range of the EDSS: (i) allows for a more-complete description of the relationship between patients’ clinical disability and their cerebral-WM-LL values, and (ii) suggests that this large relationship is maintained across the middle and the upper ranges of the EDSS scale.
Whereas we attempted to minimize any sources of non-biological and extra-patient variability, the data in the
Li et al.
12 study was associated with the many potential sources of increased variability that are present when data from many clinical trials are combined (as detailed in the Introduction). Importantly, it is not clear: (i) what the inclusion criteria were for the various clinical trials that contributed data to the Li et al.
12 analysis; or (ii) whether or not these may have resulted in any selection bias towards patients with clinical and imaging characteristics that were not representative of those from an unselected sample of patients with a similar range of scores on the EDSS.
Furthermore, as noted previously, Li et al.
12 only studied patients with EDSS scores limited to the range of 0–6.5, which – as suggested by our bsr findings – can lead to underestimating the true, overall relationship between EDSS scores and cr-T2-LL values in patients with MS. On the other hand, our sample of 110 patients with EDSS scores of
0–9.5 was representative of those seen in the MS Clinic of the Montreal Neurological Hospital and, we assume, representative of the untreated MS population in general.
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The impact of increasing statistical power and of reducing many of the aforementioned causes of variability can be seen not only in our findings, but also in the results of a recent study by Fisniku et al.
, 13 who studied the relationship between T2-LL and clinical disability in 74 patients who had presented with a clinically-isolated syndrome ( CIS ) suggestive of MS twenty years previously (of which 44 went on to have clinically-definite MS).
They found evidence for a large, non-plateauing relationship between T2-LL and disability at 20-year follow-up, both as measured by: (i) scores on the EDSS (

= 0.50, p < 0.001; n = 74, with EDSS scores >= 6 in 27 cases); and
(ii) scores on the Multiple Sclerosis Functional Composite scale (

= -0.53, p < 0.001; n
= 62), 14, 15 which provides a
quantitative measure of three key clinical dimensions of MS: ambulation, fine hand-motor coordination, and cognitive function. Importantly, in their study: (i) a reasonably-large sample size was studied, (ii) the entire range of
EDSS-measured clinical disability was sampled, (iii) all of the MRI data was collected on the same scanner, (iv) all of the lesions were identified by one experienced neuroradiologist who was blinded to clinical details, and (v) T2-LL was quantified using a semiautomatic local-threshold contour technique 16 that had been proven to have high inter- and intra-rater reliability 17
In conclusion, our findings have a number of important implications for future studies and clinical trials. First, they emphasize the importance of trying to minimize the effects of non-biological factors that influence variability in both the MRI measures and the clinical measures that are being studied: indeed, this is becoming more common in clinical trials 18 with the use of, for example: (i) central MRI-reading centers that are involved in the development of appropriate MRI protocols, as well as in the assurance that data from each of the contributing sites and scanners are acquired, processed, and analysed in a valid and reliable manner; 19 and (ii) the adoption of formal training and testing programs that ensure consistent clinical testing results from each of the contributing sites and testers ( e.g., the
Neurostatus program, www.neurostatus.net). Second, they emphasize the importance of quantifying not only the patients’ T2-LL (which is a relatively non-specific measure), but also their T1-LL (which seems to be more related to their degree of EDSS-measured clinical disability). Finally, the present findings point out the importance of: (i) studying patients with scores that span the entire range of the EDSS if the aim of a study is to understand what happens across the entire spectrum of disability that is found in MS, or (ii) remembering that findings in patients with EDSS scores of 0–6.0 are not necessarily representative of the entire course of the disease.
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