We thank Dr Platt and colleagues for their critical review of our work, especially of the methodology that we have used in this study. It is understandable that comparative studies of treatment effectiveness trigger constructive discussions among industry and academics. We also vehemently agree that rigorous methodology and cautious interpretation of results is mandatory, especially for analyses of observational data.1 2 Therefore, in this letter, we will provide additional clarifications in response to the concerns raised.
We appreciate that the categories that are underrepresented in multivariable logistic regression models may lead to inflation of estimates of the corresponding coefficients and their variance. Such inflation would, however, result in an overly conservative matching rather than the opposite. Due to the use of a caliper, patients with an extreme propensity score can not be matched to patients within the bulk of the distribution of the propensity scores. Such patients were excluded from the matched cohorts.
The issue of residual imbalance is important in any non-randomised comparative study. We acknowledge that the standardised mean difference in annualised relapse rates (ARR) between teriflunomide and fingolimod exceeded the nominal threshold of 20%. It is therefore reassuring that the sensitivity analyses, in which the residual imbalance fell below the accepted threshold of 20% (patients with prior on-treatment relapses, Cohen’s d 14%, and...
We thank Dr Platt and colleagues for their critical review of our work, especially of the methodology that we have used in this study. It is understandable that comparative studies of treatment effectiveness trigger constructive discussions among industry and academics. We also vehemently agree that rigorous methodology and cautious interpretation of results is mandatory, especially for analyses of observational data.1 2 Therefore, in this letter, we will provide additional clarifications in response to the concerns raised.
We appreciate that the categories that are underrepresented in multivariable logistic regression models may lead to inflation of estimates of the corresponding coefficients and their variance. Such inflation would, however, result in an overly conservative matching rather than the opposite. Due to the use of a caliper, patients with an extreme propensity score can not be matched to patients within the bulk of the distribution of the propensity scores. Such patients were excluded from the matched cohorts.
The issue of residual imbalance is important in any non-randomised comparative study. We acknowledge that the standardised mean difference in annualised relapse rates (ARR) between teriflunomide and fingolimod exceeded the nominal threshold of 20%. It is therefore reassuring that the sensitivity analyses, in which the residual imbalance fell below the accepted threshold of 20% (patients with prior on-treatment relapses, Cohen’s d 14%, and analysis with no MRI data included, Cohen’s d 16%) confirmed the results of the primary analysis. We have chosen not to explicitly report absolute differences in proportions reported in Table 1; this information is redundant as the absolute differences can easily be calculated from the proportions shown in the table.
Dr Platt and colleagues make an important point that the comparison of baseline patient characteristics should account for the weights used due to matching in a one-to-multiple variable ratio. We have recalculated the differences for the primary analysis and have observed that our original standardised mean differences overestimated the true weighted standardised mean differences present (see the Table below). Reassuringly, the compared groups are in reality more closely aligned than what the Table 1 in our article would suggest.
TABLE: Recalculated weighted standardised mean differences (Cohen’s d) for continuous baseline characteristics. (DMF, dimethyl fumarate)
DMF vs. teriflunomide fingolimod vs. DMF fingolimod vs. teriflunomide
age 0.006 0.01 0.02
disease duration 0.006 0.003 0.01
disability (EDSS) 0.04 0.002 0.026
relapses 12 months pre-baseline 0.05 0.015 0.03
Combining the results of multiple imputation is a standard procedure, inherent in multiple imputation methodology.3 We have calculated the mode in order to combine the 17 datasets into one. The resulting variable represents the combined result of the 17 imputed data sets and therefore reflects the values with the greatest support within the imputed data space.
Similar to our previous studies, we have chosen to match the studied patients on country.4 This is a conservative decision that aims to mitigate systematic differences in patient follow-up (modelled as the surrogate ‘country’ variable). However, there are methods that are considerably more effective in accounting for inter-centre heterogeneity. We have taken precautions to minimise the heterogeneity in the studied cohort directly – through adjusting for the length and the frequency of recorded follow-up as well as its consistency across the participating centres (the requirement of Neurostatus certification at each centre, adjustment for visit frequency, pairwise censoring, and the quality control process). In fact, differences in treating conventions access to therapies among centres and regions increase the chance that patients will be matched with comparable counterparts who were offered a different therapy for reasons unrelated to their disease severity.
We have calculated ARR in individual patients in order to derive point and interval estimates of the distributions of ARR. The estimates (mean and variance) were weighted for variable one-to-multiple matching and duration of pairwise-censored follow-up. The presented mean ARRs and their 95% confidence intervals are based on this method.
Individual estimation of ARR in a cohort where 75% of patients have a recorded, pairwise-censored follow up greater than 1 year (and the minimum required follow-up of 6 months) is subject to only a negligible risk of inflation due to short follow-up. Notionally, estimation of ARR of a population based on individual observed ARRs from a sample follows standard inferential reasoning within frequentist framework. It enables direct estimation of ARR in studied sample. As in our previous studies, we have used a negative binomial model to compare the incidence of relapse events throughout the pairwise-censored follow-up between the matched patients.4 5 Here, we have used the overall number of relapses from either treatment group and cumulative follow-up, as appropriate. As stated in the Methods, all analyses used weights to account for variable matching ratio and either ‘cluster’ or ‘frailty’ terms to account for the paired data structure. We agree that it would have been more accurate to use the term ‘incidence of relapses’ rather than ‘ARR’ in the description of the negative binomial model in the Methods section. Most importantly, all three methods that we have employed to evaluate relapse outcomes (the two methods described above and the survival model) showed consistent results in the primary analysis.
Appropriately, the authors have closely examined our estimates of variance for ARRs. Unfortunately, the table presented in their communication is difficult to understand. It is unclear what method for the back-calculation of standard deviations from the reported 95% confidence intervals was applied, given that it resulted in two divergent values for both our study and the given examples of randomised clinical trials – reported as ‘SD left’ and ‘SD right’. As described above, all of our analyses used weights to adjust for variable matching ratio, and these were also used to calculate interval estimates for the weighted mean ARRs. It is reasonable to observe variability in the error recorded in each sample, especially in observational studies, which naturally encapsulate more broadly defined cohorts in exchange for greater ecological validity. Furthermore, one would expect the variability in the error to be contingent on the specific selection of study samples, as a result of matching to other treatment groups. We agree that the implications of variable standard deviations across studies are of research interest, but it is not clear that their bench marking to a particular randomised control trial is justified.
We thank the authors for pointing out the inconsistency in the reported exposure to therapies between the groups before and after matching. Sixteen patients treated with dimethyl fumarate were previously exposed to teriflunomide as their highest-efficacy treatment, and the corresponding entry in Supplementary Table 6 should be 16 (2%). We apologise for the typographical error.
A well-powered analysis is not a weakness of a study. We are aware that a statistically significant difference and clinically meaningful difference are complementary but different concepts. Studies carried out within the frequentist framework are reliant on testing of significance of null hypotheses and are destined to provide binary answers – an arbitrary outcome that reflects its origin in randomised controlled trials. Therefore, a result that rejects a null hypothesis provides its reader with more certainty than a result that fails to do so, even when the difference may be of minimal clinical significance. The role of the clinical readership is to interpret clinical meaningfulness of the results. We refrained from attempting to develop cut-offs for what represents clinically meaningful difference and chose to leave this decision to the readers. More robust and intuitive answers to this problem lie in Bayesian methods. We are strong proponents of such methods, as the interpretation of their results is more intuitive for a clinical reader.
The title of their discussion point suggests that Dr Platt and colleagues consider reports that require further clarification of some of its concepts to be methodologically flawed. In the study under discussion, we have utilised the methodology previously used in several studies of comparative effectiveness in the MSBase data set, in particular the comparison of treatment escalation to fingolimod or natalizumab.4 We have systematically addressed the relevant sources of bias, in particular indication bias.1 We take great comfort in the fact that our previous comparative analyses have been highly convergent with the results of pivotal randomised controlled trials.5 6 We have now provided clarification of additional points in response to our colleagues’ review of our article. We value their constructive criticism and believe that our thorough response further strengthens the credibility of the reported results.
References
1. Kalincik T, Butzkueven H. Observational data: Understanding the real MS world. Mult Scler 2016;22(13):1642-48. doi: 10.1177/1352458516653667 [published Online First: 2016/06/09]
2. Trojano M, Tintore M, Montalban X, et al. Treatment decisions in multiple sclerosis - insights from real-world observational studies. Nat Rev Neurol 2017;13(2):105-18. doi: 10.1038/nrneurol.2016.188 [published Online First: 2017/01/14]
3. Heraud-Bousquet V, Larsen C, Carpenter J, et al. Practical considerations for sensitivity analysis after multiple imputation applied to epidemiological studies with incomplete data. BMC medical research methodology 2012;12:73. doi: 10.1186/1471-2288-12-73 [published Online First: 2012/06/12]
4. Kalincik T, Horakova D, Spelman T, et al. Switch to natalizumab vs fingolimod in active relapsing-remitting multiple sclerosis. Ann Neurol 2015;77:425-35. [published Online First: 2014/12/27]
5. Kalincik T, Brown JWL, Robertson N, et al. Comparison of alemtuzumab with natalizumab, fingolimod, and interferon beta for multiple sclerosis: a longitudinal study. Lancet Neurol 2017;16(4):271-81.
6. He A, Spelman T, Jokubaitis V, et al. Comparison of switch to fingolimod or interferon beta/glatiramer acetate in active multiple sclerosis. JAMA Neurol 2015;72(4):405-13. doi: 10.1001/jamaneurol.2014.4147 [published Online First: 2015/02/11]
We read with interest the article by Kalincik et al. [1] comparing fingolimod, dimethyl fumarate and teriflunomide in a cohort of relapsing-remitting multiple sclerosis (MS) patients. The authors investigated several endpoints and performed various sensitivity analyses, and we commend them for reporting technical details in the online supplementary material. We, however, have some concerns about the design, analysis and reporting of the study.
1. In the primary analyses, three separate propensity score models were developed to construct a matched cohort for each of the three pairwise comparisons. Supplementary Table 6 clearly indicates the existence of zero or low frequencies in some variables (e.g., most active previous therapy and magnetic resonance imaging [MRI] T2 lesions). Yet, those variables were used as covariates in the propensity score models, unsurprisingly resulting in extremely high point estimates and standard errors (SE; as reported in Supplementary Table 7). For example, teriflunomide was not the most active therapy for any patient in the dimethyl fumarate cohort (n=0 from Supplementary Table 6), but that category was nevertheless included in the propensity score model, leading to an unrealistic point estimate of 18.65 with SE of 434.5 (Supplementary Table 7). Even higher SEs (greater than 1000) are observed in the other propensity score models. Propensity scores estimated from these poorly constructed models were then used to cr...
We read with interest the article by Kalincik et al. [1] comparing fingolimod, dimethyl fumarate and teriflunomide in a cohort of relapsing-remitting multiple sclerosis (MS) patients. The authors investigated several endpoints and performed various sensitivity analyses, and we commend them for reporting technical details in the online supplementary material. We, however, have some concerns about the design, analysis and reporting of the study.
1. In the primary analyses, three separate propensity score models were developed to construct a matched cohort for each of the three pairwise comparisons. Supplementary Table 6 clearly indicates the existence of zero or low frequencies in some variables (e.g., most active previous therapy and magnetic resonance imaging [MRI] T2 lesions). Yet, those variables were used as covariates in the propensity score models, unsurprisingly resulting in extremely high point estimates and standard errors (SE; as reported in Supplementary Table 7). For example, teriflunomide was not the most active therapy for any patient in the dimethyl fumarate cohort (n=0 from Supplementary Table 6), but that category was nevertheless included in the propensity score model, leading to an unrealistic point estimate of 18.65 with SE of 434.5 (Supplementary Table 7). Even higher SEs (greater than 1000) are observed in the other propensity score models. Propensity scores estimated from these poorly constructed models were then used to create three matched cohorts, which are the basis for the primary analyses in this work. Readers need to be skeptical about any inference (estimated SE of the treatment effect, and consequently the confidence intervals/p-values) made from these cohorts, because of the instability in the propensity score models. Further, while teriflunomide was not the ‘most active previous therapy’ for any patient in the original (unmatched) dimethyl fumarate cohort (n=0 and 0% from Supplementary Table 6), Table 1 reported n=14 (2%) patients with this therapy after matching. Naturally the matched cohort should not produce more patients than originally present in the unmatched cohort for any category.
2. A threshold lower than 10% or 20% in absolute value for standardized mean differences (i.e. Cohen’s d) is normally considered to assess imbalances in baseline covariates. However, in this study, a standardized mean difference was reported to be equal to 26% for relapse activity prior to the baseline for the comparison of fingolimod vs. teriflunomide matched sample (Table 1). Neither the standardized or raw difference in proportions was reported for any of the categorical variables in Table 1, even though some of the percentages in matched cohorts were substantially different (e.g., relapse rate). Large residual differences observed in the distribution of the covariates (likely due to poorly built propensity score models) will contribute to bias in the resulting estimates. Furthermore, matching by country, a crucial variable which would allow minimizing outcome assessment bias [2] was not reported in Table 1, but as Supplementary Table 4 which clearly shows that matching by country is far from being obtained. Even more important, since the matching process was conducted in a variable ratio manner for the primary analyses, standardized differences in Table 1 should be replaced with weighted standardized means or proportion differences to obtain a correct check of residual baseline imbalances after matching [3].
3. In the primary analysis, missing baseline MRI values were imputed to generate 17 imputed datasets (MRI information was available for only 20-27% of the population as reported in Supplementary Table 6). In a propensity score analysis, multiple imputation (instead of single imputation) would substantially complicate the analysis due to the pooling of estimates from the 17 imputed datasets (using Rubin’s rules). Both Supplementary Tables 7 and 11 included one set of estimates from each stage of the analysis (propensity score analysis and primary analysis of the matched cohorts respectively), making it unclear how the results were pooled. If the results were not pooled and a single imputed dataset was used for the analysis (as suggested by Supplementary Tables 7 and 11), then such a process would fail to account for the uncertainty in the missing values, leading to SEs and p-values that are smaller than expected.
4. We applaud the authors for conducting a series of sensitivity analyses to evaluate the robustness of their findings. However, readers would have more confidence in the findings if the supplementary materials included more details of how those sensitivity analyses were done. For example, when 1:1 matching was done, it is not clear whether and how the authors have accounted for the matched-pairs designs. In particular, despite having almost identical sample sizes in some matched cohorts (e.g., comparing analyses of ‘no MRI data included’ vs. ‘matching on 2-year relapse rate’ for fingolimod vs. dimethyl fumarate in Supplementary Table 11), high variability in p-values in most cases deserve further explanation.
5. As for the PS adjusted treatment effect analyses, this work claims that individual ARRs were calculated and used in the assessment of primary endpoint analysis. This approach is controversial [4]. Furthermore, the use of individual ARRs is contradicted in the statistical analysis section in which the authors state that a weighted negative binomial accounting for matching has been used. It is unclear whether individual ARRs were fed into a negative binomial and it is important to note that, if they were, results may be biased. The authors do not make clear whether standard errors and p-values properly accounted both for matching and weighting in all assessed endpoints (they include a cluster term in the negative binomial model which only accounts for matching). Table 1 presented below reports a back-calculation of the standard deviation (SD) for ARRs, which should correspond to a stable population parameter, in particular the column ‘SD right’ which is less prone to rounding effects present the original ARRs confidence interval values. This standard deviation is benchmarked against a recent work on a new drug for MS [5]. For the studies OPERA I and II consistent and stable SD values are obtained (around 1), while highly inconsistent and underestimated SDs are obtained for the MSBASE study, especially when the weighting scheme should have been attributing within the matched group the weight of 1 to the treatment arm represented by one single patient. Our Table 1 shows that the reported estimated standard errors are incorrect (i.e. generally smaller) due to the use of a wrong weighting scheme or lack of accounting for weighting properly and, consequently, p-values significance has been inflated dramatically.
6. The large number of patients included made statistically significant a very small and perhaps not clinically meaningful difference, increasing the risk of overinterpretation of the results. From a clinical standpoint an ARR difference between 0.20 and 0.26, that is an ARR ratio of 0.80 or, more intuitively, 1 relapse over 5 years vs. 1 relapse over 4 years is close to negligible overall. This represents an effect size that no future trial would likely be powered or interested to detect, especially as it comes from an ARR threshold (0.20) quite prone to the presence of noise in detecting a relapse.
To recapitulate, we wish to highlight the need for caution while interpreting the findings of this paper. Real world evidence (RWE) is an important and necessary component of research to assess the effectiveness and safety of various therapies outside the context of randomized clinical trials. However, because RWE is prone to various sources of bias, rigorous and careful analysis, interpretation and reporting are needed to ensure that results are reliable, reproducible and useful to inform clinical decision making.
REFERENCES
[1] Kalincik T et al. Comparison of fingolimod, dimethyl fumarate and teriflunomide for multiple sclerosis. Journal of Neurology, Neurosurgery & Psychiatry. 2019: jnnp-2018-319831. doi:10.1136/jnnp-2018-31983.
[2] Bovis F et al. Expanded disability status scale progression assessment heterogeneity in multiple sclerosis according to geographical areas. Ann Neurol. 2018 Oct;84(4):621-625.
[3] Austin, Peter C. Assessing balance in measured baseline covariates when using many‐to‐one matching on the propensity‐score. Pharmacoepidemiology and drug safety 17.12 (2008): 1218-1225.
[4] Suissa S et al. Statistical Treatment of Exacerbations in Therapeutic Trials of Chronic Obstructive Pulmonary Disease. American Journal of Respiratory and Critical Care Medicine. 2006;173(8):842-846.
[5] Hauser SL, Bar-Or A, Comi G, Giovannoni G, Hartung HP, Hemmer B, Lublin F, Montalban X, Rammohan KW, Selmaj K, Traboulsee A, Wolinsky JS, Arnold DL, Klingelschmitt G, Masterman D, Fontoura P, Belachew S, Chin P, Mairon N, Garren H, Kappos L; OPERA I and OPERA II Clinical Investigators. Ocrelizumab versus Interferon Beta-1a in Relapsing Multiple Sclerosis. N Engl J Med. 2017 Jan 19;376(3):221-234.
Table 1 – Back-calculation of ARR standard deviation to benchmark flaws in the reported standard errors and p-values
Study Drug n ARR Lower ARR Upper ARR SD left SD right
OPERA I [5] Ocrelizumab 410 0.16 0.12 0.2 1.29 1.00
Interferon 411 0.29 0.24 0.36 0.85 0.97
OPERA II [5] Ocrelizumab 417 0.16 0.12 0.2 1.30 1.01
Interferon 418 0.29 0.23 0.36 1.05 0.98
ARR: Annualized relapse rate; SD: standard deviation; DMF: dimethyl fumarate
Correspondence to:
Robert W. Platt, Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, 1020 Pine Ave W, Montreal, Quebec H3A 1A2, Canada.
Email: robert.platt@mcgill.ca
Seizures and movement disorders : cortico-subcortical networks
Dr Aileen McGonigal
Aix Marseille Univ, Inserm, INS, Institut de Neurosciences des Systèmes, Marseille, France
APHM, Timone Hospital, Clinical Neurophysiology, Marseille, France
Corresponding author: Dr Aileen McGonigal, Service de Neurophysiologie Clinique, CHU Timone, AP-HM, Marseille, France
Email : aileen.mcgonigal@univ-amu.fr
Tel: 00 33 491384995
Fax:00 33 491385826
To the Editors
I was interested to read the recent review by Dr Freitas and colleagues1. This interesting article highlights diagnostic challenges, clinical overlap and possible shared pathophysiological processes in epileptic seizures and movement disorders. I would like to add a couple of points that seem important to acknowledge.
Firstly, in terms of clinical expression, the authors rightly mention that automatic movements occurring during focal epileptic seizures can sometimes resemble those seen in certain movement disorders, and they give the examples of orofacial automatisms (most often seen in temporal lobe seizures), as well as hyperkinetic behaviors. While the authors highlight sleep-related epilepsy as the main cause of hyperkinetic behavior, in fact hyperkinetic behavior may be seen in seizures from various cortical origins both in wakefulness and in sleep. It should be recognized that especially (though not exclusivel...
Seizures and movement disorders : cortico-subcortical networks
Dr Aileen McGonigal
Aix Marseille Univ, Inserm, INS, Institut de Neurosciences des Systèmes, Marseille, France
APHM, Timone Hospital, Clinical Neurophysiology, Marseille, France
Corresponding author: Dr Aileen McGonigal, Service de Neurophysiologie Clinique, CHU Timone, AP-HM, Marseille, France
Email : aileen.mcgonigal@univ-amu.fr
Tel: 00 33 491384995
Fax:00 33 491385826
To the Editors
I was interested to read the recent review by Dr Freitas and colleagues1. This interesting article highlights diagnostic challenges, clinical overlap and possible shared pathophysiological processes in epileptic seizures and movement disorders. I would like to add a couple of points that seem important to acknowledge.
Firstly, in terms of clinical expression, the authors rightly mention that automatic movements occurring during focal epileptic seizures can sometimes resemble those seen in certain movement disorders, and they give the examples of orofacial automatisms (most often seen in temporal lobe seizures), as well as hyperkinetic behaviors. While the authors highlight sleep-related epilepsy as the main cause of hyperkinetic behavior, in fact hyperkinetic behavior may be seen in seizures from various cortical origins both in wakefulness and in sleep. It should be recognized that especially (though not exclusively) in prefrontal seizures2, more elaborate automatic behaviors may include complex and often repetitive movements that tend to occur in a context of altered consciousness, including naturalistic movements such as hand tapping, rocking or leg movements. These may be associated with vocalization including verbal stereotypies, laughing or singing, and sometimes emotional signs. The seizure semiological pattern is typically similar for a given patient from one seizure to the next. These excessively repetitive movements occurring within a limited behavioral repertoire could indeed be characterised as stereotypies, according to the definition of this term3.
In cases of focal pharmacoresistant epilepsy, presurgical evaluation may require intracerebral electroencephalography (EEG). This offers a rich source of data for correlating clinical seizure expression with intracerebral electrical activity measured with millisecond resolution. The depth electrode methodology of stereoelectroencephalography (SEEG) allows sampling of widely distributed structures, through which signal analysis studies have helped to establish the network basis of epilepsy4.
In a series of frontal seizures recorded with SEEG, the clinical expression of ictal stereotyped movements was shown to correlate with a rostrocaudal gradient of seizure organisation within frontal cortex, notably whether movements involved predominantly proximal or distal body segments: more distal stereotypies were associated with more anterior prefrontal regions 5. Thus, while both cortical and subcortical structures seem likely to be involved in such complex seizure-related behavior4 6, it can be suspected that cortico-subcortical circuits are topographically organised in a way that directly influences clinical expression.
While most SEEG recording is from cortical structures, aimed at identifying a pathological zone for surgical resection, deeper subcortical structures including thalamus and caudate nucleus are sometimes also explored. In the context of Freitas and colleagues’ discussion of pathophysiology, it is of interest to note that in SEEG exploration of frontal lobe epilepsy, the caudate nucleus has been shown to be involved in generation of both spontaneous and stimulation-triggered seizures7. An SEEG study of temporal lobe seizures demonstrated an association between greater impairment of awareness and increased long-distance connectivity between thalamus and associative cortical structures 8. Lastly, in a separate and recent study of patients with temporal lobe epilepsy recorded with SEEG, direct stimulation of pulvinar during hippocampal seizures produced electroclinical change, with clinically less severe seizures9.
Thus, an exciting role of SEEG exploration of epilepsy is not only in defining a potential surgical excision for each patient, but also using the recorded data to pursue better understanding of organisation of pathophysiological networks, including in terms of interactions between their cortical and subcortical components. As well as the strong neuroscientific interest of such data, this could potentially advance therapeutic approaches, for example facilitating development of tailored deep brain stimulation methods according to anatomical and electrophysiological specificities of different cases. This is of direct clinical relevance to management of epilepsy but could eventually also open up therapeutic possibilities for some movement disorders.
1. Freitas ME, Ruiz-Lopez M, Dalmau J, et al. Seizures and movement disorders: phenomenology, diagnostic challenges and therapeutic approaches. 2019:jnnp-2018-320039.
2. Bonini F, McGonigal A, Trébuchon A, et al. Frontal lobe seizures: From clinical semiology to localization. Epilepsia 2014;55.2 264-77.
3. Edwards MJ, Lang AE, Bhatia KP. Stereotypies: a critical appraisal and suggestion of a clinically useful definition. Mov Disord 2012;27(2):179-85. doi: 10.1002/mds.23994
4. Bartolomei F, Lagarde S, Wendling F, et al. Defining epileptogenic networks: Contribution of SEEG and signal analysis. Epilepsia 2017
5. McGonigal A, Chauvel P. Prefrontal seizures manifesting as motor stereotypies. Movement Disorders 2013 doi: doi: 10.1002/mds.25718
6. Chauvel P, McGonigal A. Emergence of semiology in epileptic seizures. Epilepsy & Behavior 2014
7. Aupy J, Kheder A, Bulacio J, et al. Is the caudate nucleus capable of generating seizures? Evidence from direct intracerebral recordings. Clinical Neurophysiology 2018
8. Arthuis M, Valton L, Régis J, et al. Impaired consciousness during temporal lobe seizures is related to increased long-distance cortical-subcortical synchronization. Brain 2009;132(Pt 8):2091-101. doi: 10.1093/brain/awp086
9. Filipescu C, Lagarde S, Lambert I, et al. The effect of medial pulvinar stimulation on temporal lobe seizures. Epilepsia 2019
We applaud Suichi et al.[1] for proposing new diagnostic criteria for POEMS syndrome. There is clearly a need for simplified validated criteria that permit early diagnosis of this rare, elusive and devastating paraneoplastic disorder, especially because early local or systemic treatment of the underlying plasma cell malignancy can dramatically improve prognosis.[2] Our recent clinical experience[3] is in full agreement with the three proposed cardinal features of POEMS syndrome, namely polyneuropathy, vascular endothelial growth factor (VEGF) level elevation, and the presence of monoclonal protein. The authors argue that the triad alone may be insufficiently specific; therefore they propose the additional requirement of two of four secondary features, namely extravascular fluid accumulation, skin changes, organomegaly, and sclerotic bone lesion.
We would like to draw attention to clinical and methodological aspects that could further enhance or refine the diagnosis of POEMS syndrome. First, the process of diagnosis starts with clinical suspicion. Polyneuropathy is usually the earliest symptom of POEMS syndrome. POEMS syndrome should be considered in any patient with a severely progressive polyneuropathy of acute to subacute onset that is not otherwise explained, and VEGF level measurement should be offered. Routine screening for monoclonal protein (with immunofixation) and skeletal survey may be negative initially, and could remain negative for a long duration into...
We applaud Suichi et al.[1] for proposing new diagnostic criteria for POEMS syndrome. There is clearly a need for simplified validated criteria that permit early diagnosis of this rare, elusive and devastating paraneoplastic disorder, especially because early local or systemic treatment of the underlying plasma cell malignancy can dramatically improve prognosis.[2] Our recent clinical experience[3] is in full agreement with the three proposed cardinal features of POEMS syndrome, namely polyneuropathy, vascular endothelial growth factor (VEGF) level elevation, and the presence of monoclonal protein. The authors argue that the triad alone may be insufficiently specific; therefore they propose the additional requirement of two of four secondary features, namely extravascular fluid accumulation, skin changes, organomegaly, and sclerotic bone lesion.
We would like to draw attention to clinical and methodological aspects that could further enhance or refine the diagnosis of POEMS syndrome. First, the process of diagnosis starts with clinical suspicion. Polyneuropathy is usually the earliest symptom of POEMS syndrome. POEMS syndrome should be considered in any patient with a severely progressive polyneuropathy of acute to subacute onset that is not otherwise explained, and VEGF level measurement should be offered. Routine screening for monoclonal protein (with immunofixation) and skeletal survey may be negative initially, and could remain negative for a long duration into the disease course. In fact, in many patients with POEMS, the concentration of monoclonal protein in the serum or urine is conspicuously low. Lack of abnormality on one or these two tests is insufficient to exclude a diagnosis of POEMS syndrome.[3,4] It is important to emphasize that any patient with a severe polyneuropathy and a significantly elevated VEGF level (usually >200 pg/ml) should be subjected to an aggressive search for plasma cell malignancy with CT or CT-PET and possibly image-directed bone marrow biopsy. Second, searching for characteristics of the polyneuropathy may improve the specificity of the POEMS diagnosis and differentiate it from mimics, even in the absence of secondary features: sensorimotor polyneuropathy with mixed axonal and demyelinating features, notably a prior diagnosis of chronic inflammatory demyelinating polyradiculoneuropathy (CIDP) refractory to intravenous immunoglobulin and corticosteroids, severe axon loss in distal leg muscles together with diffuse demyelinating features on nerve conduction studies of the upper extremity, and evidence of proximal involvement in the form of root enhancement on imaging and elevated cerebrospinal protein.[3,5] Third, secondary features of edema, skin changes, and organomegaly develop as the disease advances, and may not be manifest in the earliest stages. As it is desirable to make an early diagnosis and prevent accumulation of impairment from this treatable condition, there should not be a delay in diagnosing due to a lack of secondary features.
Validation exercises of diagnostic criteria of clinical syndromes (that lack an objective diagnostic criterion) are by definition circular arguments that inflate the accuracy of criteria that match prevalent practice. It is possible that the reported 100% sensitivity and specificity are overestimates, and may be more applicable for patients in later stages.
Therefore we propose a designation of "possible POEMS" for any progressive/severe or "red flags" polyneuropathy with elevated VEGF level. The probability of POEMS syndrome in this group is sufficiently high that a rapid and aggressive diagnostic evaluation for plasma cell malignancy is warranted. Only after completion of such an evaluation and careful neurological and hematological follow-up can POEMS syndrome be excluded.
1 Suichi T, Misawa S, Sato Y, et al. Proposal of new clinical diagnostic criteria for POEMS syndrome. J Neurol Neurosurg Psychiatry 2019;90:133–7. doi:10.1136/jnnp-2018-318514
2 Dispenzieri A. POEMS syndrome: 2017 Update on diagnosis, risk stratification, and management. Am J Hematol 2017;92:814–29. doi:10.1002/ajh.24802
3 Li Y, Valent J, Soltanzadeh P, et al. Diagnostic challenges in POEMS syndrome presenting with polyneuropathy: A case series. J Neurol Sci 2017;378:170–4. doi:10.1016/j.jns.2017.05.019
4 He T, Zhao A, Zhao H, et al. Clinical characteristics and the long-term outcome of patients with atypical POEMS syndrome variant with undetectable monoclonal gammopathy. Ann Hematol 2019;98:735–43. doi:10.1007/s00277-018-03589-4
5 Mauermann ML, Sorenson EJ, Dispenzieri A, et al. Uniform demyelination and more severe axonal loss distinguish POEMS syndrome from CIDP. J Neurol Neurosurg Psychiatry 2012;83:480–6. doi:10.1136/jnnp-2011-301472
Komatsu et al. presented an interesting clinicopathological case of anti-myelin oligodendrocyte glycoprotein (MOG) demyelinating disease of the CNS. (1) Their patient had a rather unusual subacute encephalopathic presentation with extensive supratentorial fluid-attenuation inversion recovery white matter hyperintensities. The authors focused mainly on the conspicuous MRI punctuate and curvilinear enhancement pattern within the hemispheric lesions.
It is well established that intraparenchymal punctuate and curvilinear gadolinium enhancement may arise in the context of Moyamoya syndrome, various endotheliopathies and most commonly, in disorders causing small vessels blood-brain barrier disruption. (2)These entities are associated histologically with perivascular cellular infiltrates and include inflammatory autoimmune diseases (i.e. primary or secondary angiitis of the CNS, neurosarcoidosis, histiocytosis and demyelinating diseases of the CNS), pre-lymphoma states (i.e. sentinel lesions of primary CNS lymphoma), non-Hodgkin lymphoma (i.e. intravascular lymphoma) and CLIPPERS syndrome. (2) Notably, among demyelinating disorders, multiple sclerosis and aquaporin-4 antibody (AQP4-Ab) neuromyelitis optica spectrum disorders (NMOSD) manifest this specific neuroimaging pattern in rare cases. (2,3)
We agree with Komatsu et al. that their case is the first report of the perivascular enhancement in anti-MOG antibody disease. Indeed, gadolinium enhancement was observed in...
Komatsu et al. presented an interesting clinicopathological case of anti-myelin oligodendrocyte glycoprotein (MOG) demyelinating disease of the CNS. (1) Their patient had a rather unusual subacute encephalopathic presentation with extensive supratentorial fluid-attenuation inversion recovery white matter hyperintensities. The authors focused mainly on the conspicuous MRI punctuate and curvilinear enhancement pattern within the hemispheric lesions.
It is well established that intraparenchymal punctuate and curvilinear gadolinium enhancement may arise in the context of Moyamoya syndrome, various endotheliopathies and most commonly, in disorders causing small vessels blood-brain barrier disruption. (2)These entities are associated histologically with perivascular cellular infiltrates and include inflammatory autoimmune diseases (i.e. primary or secondary angiitis of the CNS, neurosarcoidosis, histiocytosis and demyelinating diseases of the CNS), pre-lymphoma states (i.e. sentinel lesions of primary CNS lymphoma), non-Hodgkin lymphoma (i.e. intravascular lymphoma) and CLIPPERS syndrome. (2) Notably, among demyelinating disorders, multiple sclerosis and aquaporin-4 antibody (AQP4-Ab) neuromyelitis optica spectrum disorders (NMOSD) manifest this specific neuroimaging pattern in rare cases. (2,3)
We agree with Komatsu et al. that their case is the first report of the perivascular enhancement in anti-MOG antibody disease. Indeed, gadolinium enhancement was observed in 6 out of 108 MRIs among adult patients with CNS MOG autoimmunity in a large French natiowide cohort. (4) Leptomeningeal enhancement, thought to indicate cortical encephalitis, was detected in only 3 scans. Most importantly, none of the patients in this study or other related publications, demonstrated punctuate or fine, linear-shaped enhancing lesions.
Intriguingly, the enhancement pattern in the case of Komatsu et al. shares many similarities with the imaging abnormalities seen in a recently described disorder, namely autoimmune glial fibrillary acidic protein (GFAP) astrocytopathy. This is a novel form of a steroid-responsive meningoencephalomyelitis associated with IgG binding to GFAP. A characteristic pattern on neuroimaging of brain linear, perivascular enhancement, oriented radially to the ventricles was identified in the seminal paper by Fang et al. (5) This striking abnormality was also observed in a substantial proportion of patients with the disorder in subsequent cohorts. (6)
Therefore, it would be useful to know the CSF status of GFAP-Ab of the forementioned patient. Besides, about 40% of individuals with GFAP antibody-positive meningoencephalomyelitis had coexisting neural autoantibodies. (5, 6)
Many questions regarding GFAP autoimmunity and, to a lesser extent, MOG-Ab–associated diseases remain to be answered in future studies. Overall, it seems that in the right clinical context, when perivascular enhancement on MRI is observed, one should be alert in making a differential diagnosis of GFAP astrocytopathy rather than anti-MOG antibody demyelinating disease.
1. Komatsu T, Matsushima S, Kaneko K, et al. Perivascular enhancement in anti-MOG antibody demyelinating disease of the CNS. J Neurol Neurosurg Psychiatry 2019;90:111-112.
2. Taieb, G., Duran-Peña, A., de Chamfleur, N.M. et al. Neuroradiology 2016; 58: 221-235 https://doi.org/10.1007/s00234-015-1629-y
3. Pekcevik Y, Izbudak I. Perivascular enhancement in a patient with neuromyelitis optica spectrum disease during an optic neuritis attack. J Neuroimaging 2015; 25:686–687
4. Cobo-Calvo I, Ruiz A, Maillart E, et al. Clinical spectrum and prognostic value of CNS MOG autoimmunity in adults. The MOGADOR study. Neurology 2018; 90 (21) e1858-e1869; DOI: 10.1212/WNL.0000000000005560
5. Fang B, McKeon A, Hinson SR, et al. Autoimmune Glial Fibrillary Acidic Protein Astrocytopathy: A Novel Meningoencephalomyelitis. JAMA Neurol. 2016;73(11):1297–1307. doi:10.1001/jamaneurol.2016.2549
6. Zarkali A, Cousins O, Athauda D, et al. Glial fibrillary acidic protein antibody-positive meningoencephalomyelitis. Practical Neurology 2018;18:315-319
Re: A unifying theory for cognitive abnormalities in functional neurological disorders, fibromyalgia and chronic fatigue syndrome
Viraj Bharambe Specialist registrar in neurology
John C Williamson Specialist registrar in neurology
Andrew J Larner Consultant Neurologist
Cognitive Function Clinic
Walton Centre for Neurology and Neurosurgery
Lower Lane
Fazakerley
Liverpool
L9 7LJ
UK
e-mail: a.larner@thewaltoncentre.nhs.uk
Teodoro et al. present evidence for shared cognitive symptoms in fibromyalgia, chronic fatigue syndrome, and functional neurological disorders, and hypothesize that functional cognitive disorders (FCD) may share similar symptoms.1 We present data which speak to this issue.
We have previously reported preliminary data examining performance on the mini-Addenbrooke’s Cognitive Examination (MACE) by patients diagnosed with fibromyalgia2 as part of a larger study of MACE.3 Here, we update these data for fibromyalgia patients (n = 17; F:M = 17:0; age range 33-56 years, median 49) and compare them to MACE performance by patients diagnosed with FCD (n = 43; F:M = 18:25; age range 28-82 years, median 58).4
There was no statistical difference (p > 0.1) in the proportions of patients scoring below the two cut-off scores (≤21/30, ≤25/30) defined in the index MACE report.5 Looking at MACE subscores (Attention, Registration,...
Re: A unifying theory for cognitive abnormalities in functional neurological disorders, fibromyalgia and chronic fatigue syndrome
Viraj Bharambe Specialist registrar in neurology
John C Williamson Specialist registrar in neurology
Andrew J Larner Consultant Neurologist
Cognitive Function Clinic
Walton Centre for Neurology and Neurosurgery
Lower Lane
Fazakerley
Liverpool
L9 7LJ
UK
e-mail: a.larner@thewaltoncentre.nhs.uk
Teodoro et al. present evidence for shared cognitive symptoms in fibromyalgia, chronic fatigue syndrome, and functional neurological disorders, and hypothesize that functional cognitive disorders (FCD) may share similar symptoms.1 We present data which speak to this issue.
We have previously reported preliminary data examining performance on the mini-Addenbrooke’s Cognitive Examination (MACE) by patients diagnosed with fibromyalgia2 as part of a larger study of MACE.3 Here, we update these data for fibromyalgia patients (n = 17; F:M = 17:0; age range 33-56 years, median 49) and compare them to MACE performance by patients diagnosed with FCD (n = 43; F:M = 18:25; age range 28-82 years, median 58).4
There was no statistical difference (p > 0.1) in the proportions of patients scoring below the two cut-off scores (≤21/30, ≤25/30) defined in the index MACE report.5 Looking at MACE subscores (Attention, Registration, Verbal fluency, Clock Drawing, Memory recall), the proportions scoring at ceiling were not statistically different (p > 0.1) in the fibromyalgia and FCD groups. Ranking performance in cognitive domains from worst to best showed the same pattern in both patient groups, namely Verbal fluency, Memory recall, Registration, Attention, and Clock drawing.
Although numbers are small and the cognitive testing relatively simple, and the group demographics differ (both gender and age p < 0.05), nevertheless we suggest this evidence supports the hypothesis of Teodoro et al. of shared cognitive symptoms in fibromyalgia and FCD.
References
1. Teodoro T, Edwards MJ, Isaacs JD. A unifying theory for cognitive abnormalities in functional neurological disorders, fibromyalgia and chronic fatigue syndrome: systematic review. J Neurol Neurosurg Psychiatry 2018; 89: 1308-19. doi: 10.1136/jnnp-2017-317823.
2. Williamson J, Larner AJ. Cognitive dysfunction in patients with fibromyalgia. Br J Hosp Med 2016; 77: 116. doi: 10.12968/hmed.2016.77.2.116.
3. Williamson J, Larner AJ. MACE for the diagnosis of dementia and MCI: 3-year pragmatic diagnostic test accuracy study. Dement Geriatr Cogn Disord 2018; 45: 300-7. doi: 10.1159/000484438.
4. Bharambe V, Larner AJ. Functional cognitive disorders: demographic and clinical features contribute to a positive diagnosis. Neurodegener Dis Manag 2018; 8: 377-83. doi: 10.2217/nmt-2018-0025.
5. Hsieh S, McGrory S, Leslie F, et al. The Mini-Addenbrooke’s Cognitive Examination: a new assessment tool for dementia. Dement Geriatr Cogn Disord 2015; 39: 1-11. doi: 10.1159/000366040.
Conflicts of interest
The authors declare no conflict of interest
Dear Editor,
We have read with great interest the work by Scarpazza et al that provided a longitudinal MRI evaluation of natalizumab-related Progressive Multifocal Leukoencephalopathy (NTZ-PML) lesions in Multiple Sclerosis (MS) patients (1).
Their central finding was the high percentage (78.1%) of patients, who eventually developed NTZ-PML, in whom highly suggestive lesions were already retrospectively detectable on pre-diagnostic MRI exams. Furthermore, the pre-diagnostic phase proved to be relatively long (150.8±74.9 days), with an estimated percentage increase of the lesions’ volume of 62.8% per month (1).
Given the widely recognized crucial role of a timely NTZ-PML identification in reducing mortality and residual disability (1), these results present the neurological and neuroradiological communities with an important clinical challenge, prompting a major effort to ensure an early diagnosis of this condition.
Although redefining the timing of MRI surveillance, with up to one brain MRI exam every 3-4 months for high-risk patients, appears as a justified strategy, we think that improving the accuracy of early identification of NTZ-PML is also mandatory.
In our opinion, such achievement should be pursued using two complementary approaches: (i) a specific training addressed to neuroradiologists working in the field of MS, who should be aware of the relevance of even very small asymptomatic PML lesions and how to differentiate them from new M...
Dear Editor,
We have read with great interest the work by Scarpazza et al that provided a longitudinal MRI evaluation of natalizumab-related Progressive Multifocal Leukoencephalopathy (NTZ-PML) lesions in Multiple Sclerosis (MS) patients (1).
Their central finding was the high percentage (78.1%) of patients, who eventually developed NTZ-PML, in whom highly suggestive lesions were already retrospectively detectable on pre-diagnostic MRI exams. Furthermore, the pre-diagnostic phase proved to be relatively long (150.8±74.9 days), with an estimated percentage increase of the lesions’ volume of 62.8% per month (1).
Given the widely recognized crucial role of a timely NTZ-PML identification in reducing mortality and residual disability (1), these results present the neurological and neuroradiological communities with an important clinical challenge, prompting a major effort to ensure an early diagnosis of this condition.
Although redefining the timing of MRI surveillance, with up to one brain MRI exam every 3-4 months for high-risk patients, appears as a justified strategy, we think that improving the accuracy of early identification of NTZ-PML is also mandatory.
In our opinion, such achievement should be pursued using two complementary approaches: (i) a specific training addressed to neuroradiologists working in the field of MS, who should be aware of the relevance of even very small asymptomatic PML lesions and how to differentiate them from new MS lesions on conventional brain MRI scans (2), and (ii) the identification of new MRI markers that could help in an early neuroradiological identification of PML.
It is noteworthy to mention that recent works described the presence of significant magnetic susceptibility changes, revealing a paramagnetic dipole, at the level of the subcortical U-fibers adjacent to PML lesions (3, 4). This paramagnetic effect, which has been speculatively attributed to iron accumulation inside macrophages and microglial cells following myelin degeneration, has been reported as an early and constant finding in this condition (3, 4).
Given the known absence of significant paramagnetic effects within new MS plaques (5), this sign, which still needs validation studies on larger patient cohorts, could potentially improve the accuracy of an early neuroradiological differential diagnosis between these two conditions, eventually leading to the implementation of susceptibility-weighted sequences in routine brain MRI exams of high-risk patients.
References
1. Scarpazza C, Signori A, Prosperini L, et al. Early diagnosis of progressive multifocal leucoencephalopathy: longitudinal lesion evolution. Journal of neurology, neurosurgery, and psychiatry 2018.
2. Wijburg MT, Witte BI, Vennegoor A, et al. MRI criteria differentiating asymptomatic PML from new MS lesions during natalizumab pharmacovigilance. Journal of neurology, neurosurgery, and psychiatry 2016;87(10):1138-45.
3. Hodel J, Outteryck O, Verclytte S, et al. Brain Magnetic Susceptibility Changes in Patients with Natalizumab-Associated Progressive Multifocal Leukoencephalopathy. AJNR American journal of neuroradiology 2015;36(12):2296-302.
4. Pontillo G, Cocozza S, Lanzillo R, et al. Brain Susceptibility Changes in a Patient with Natalizumab-Related Progressive Multifocal Leukoencephalopathy: A Longitudinal Quantitative Susceptibility Mapping and Relaxometry Study. Frontiers in neurology 2017;8:294.
5. Zhang Y, Gauthier SA, Gupta A, et al. Quantitative Susceptibility Mapping and R2* Measured Changes during White Matter Lesion Development in Multiple Sclerosis: Myelin Breakdown, Myelin Debris Degradation and Removal, and Iron Accumulation. AJNR American journal of neuroradiology 2016;37(9):1629-35.
Corresponding Author:
Giuseppe Pontillo, MD
Department of Advanced Biomedical Sciences
University “Federico II”, Via Pansini, 5, 80131 - Naples - Italy
E-mail: giuseppe.pon@gmail.com
We thank Abat et al. for re-emphasizing an important interpretation of our work, namely that sex-differences in life-expectancy likely influenced the presented lifetime risks [1]. Indeed, in our paper we repeatedly discussed in several sections (for instance in the methods) that differences in life-expectancy between men and women could differentially affect their lifetime risk. It was for this reason that we consequently decided to analyze the data in a sex-specific manner while taking the competing risk of death into account in order to prevent potential overestimation.
Abat et al. unfortunately also allege that we attributed the observed sex-differences in disease risk to sex-specific effects on a biological level. The authors have seemingly missed our discussion at length arguing that observed differences in lifetime risk may be primarily attributed to the effects of differences in life-expectancy between men and women: “Apart from a longer life-expectancy in general, these findings may be explained by smaller differences in life-expectancy between men and women in the Netherlands (1.8 years), compared with the USA (4.8 years). With longer life-expectancy, individuals in this study simply had more time to develop these diseases in a timeframe with high age-specific incidence rates.”
It seems thus that ours and Abat and co-authors’ interpretation of our findings is pretty much congruent, i.e. age, irrespective of sex, should be consid...
We thank Abat et al. for re-emphasizing an important interpretation of our work, namely that sex-differences in life-expectancy likely influenced the presented lifetime risks [1]. Indeed, in our paper we repeatedly discussed in several sections (for instance in the methods) that differences in life-expectancy between men and women could differentially affect their lifetime risk. It was for this reason that we consequently decided to analyze the data in a sex-specific manner while taking the competing risk of death into account in order to prevent potential overestimation.
Abat et al. unfortunately also allege that we attributed the observed sex-differences in disease risk to sex-specific effects on a biological level. The authors have seemingly missed our discussion at length arguing that observed differences in lifetime risk may be primarily attributed to the effects of differences in life-expectancy between men and women: “Apart from a longer life-expectancy in general, these findings may be explained by smaller differences in life-expectancy between men and women in the Netherlands (1.8 years), compared with the USA (4.8 years). With longer life-expectancy, individuals in this study simply had more time to develop these diseases in a timeframe with high age-specific incidence rates.”
It seems thus that ours and Abat and co-authors’ interpretation of our findings is pretty much congruent, i.e. age, irrespective of sex, should be considered as the main driver for the observed differences in lifetime risks of these diseases. Yet, in order not to rule out other interpretations prematurely, we also indicate that consideration should be given to potential sex-specific risk factors. For example, we observed a lower educational level for women compared to men which may have led to a lower resilience for dementia in women.
Reference
1 Licher S, Darweesh SKL, Wolters FJ, et al. Lifetime risk of common neurological diseases in the elderly population. J Neurol Neurosurg Psychiatry 2018;:jnnp-2018-318650.
To the Editor,
We read with interest the work from Licher et al. [1] in which the authors tried to quantify the burden of common neurological diseases (i.e. dementia, stroke and parkinsonism) in 12 102 individuals (6 982 women and 5 120 men) aged ≥ 45 years and free from these diseases at baseline. All these individuals were recruited between 1990 and 2016 into the prospective population-based Rotterdam Study. At the end of their analyzes, the authors concluded that one in two women and one in three men will develop dementia, stroke or parkinsonism during their lifetime, and that the risk for women to develop both stroke and dementia during their life is almost twice that of men [1].
By reading the article from Licher et al. [1], we were extremely surprised by the fact that the authors did not consider the impact of the difference in life expectancies between men and women on their results and conclusions. This is particularly well underlined by the fact that the authors did not clearly precise the age structures of the two populations they studied [1]. In our view, this information is critical as, although the reasons for this difference are still debated and may probably be multi-factorial [2], it is well known that women live longer than men. This trend is confirmed by the 2018 World Health Statistics report [3] that estimates that in 2016, the life expectancies of men and women at birth were respectively 69.8 and 74.2 years at the international level. The...
To the Editor,
We read with interest the work from Licher et al. [1] in which the authors tried to quantify the burden of common neurological diseases (i.e. dementia, stroke and parkinsonism) in 12 102 individuals (6 982 women and 5 120 men) aged ≥ 45 years and free from these diseases at baseline. All these individuals were recruited between 1990 and 2016 into the prospective population-based Rotterdam Study. At the end of their analyzes, the authors concluded that one in two women and one in three men will develop dementia, stroke or parkinsonism during their lifetime, and that the risk for women to develop both stroke and dementia during their life is almost twice that of men [1].
By reading the article from Licher et al. [1], we were extremely surprised by the fact that the authors did not consider the impact of the difference in life expectancies between men and women on their results and conclusions. This is particularly well underlined by the fact that the authors did not clearly precise the age structures of the two populations they studied [1]. In our view, this information is critical as, although the reasons for this difference are still debated and may probably be multi-factorial [2], it is well known that women live longer than men. This trend is confirmed by the 2018 World Health Statistics report [3] that estimates that in 2016, the life expectancies of men and women at birth were respectively 69.8 and 74.2 years at the international level. Therefore, knowing that stroke, dementia and parkinsonism are more prevalent in the elderly than in younger people [4], it is clear for us that what the authors attributed to sex is in fact the direct consequence of ageing, an aspect that was not studied by the authors. By not highlighting this factor, they led readers to misinterpretations, including general newspapers journalists that assume that this difference is a gender gap that should be filled.
To conclude, by not considering the impact of the difference in life expectancies between men and women on their study, the authors introduced an important bias in their study, leading them to draw erroneous conclusions. Age is the real culprit, not gender!
References
1 Licher S, Darweesh SKL, Wolters FJ, et al. Lifetime risk of common neurological diseases in the elderly population. J Neurol Neurosurg Psychiatry 2018;:jnnp-2018-318650.
2 Marais GAB, Gaillard J-M, Vieira C, et al. Sex gap in aging and longevity: can sex chromosomes play a role? Biol Sex Differ 2018;9:33.
3 World Health Organization. World Health Statistics 2018- Monitoring health for the Sustainable Development Goals. Available from http://apps.who.int/iris/bitstream/handle/10665/272596/9789241565585-eng.... Accessed on 2018/10/22.
4 GBD 2015 Neurological Disorders Collaborator Group. Global, regional, and national
burden of neurological disorders during 1990-2015: a systematic analysis for the
Global Burden of Disease Study 2015. Lancet Neurol 2017;16:877–97.
We thoroughly enjoyed reading the comment on our paper which analysed expert ratings of the movement disorder associated with NMDAR antibody-encephalitis.1 Thompson et al’s elegant pathophysiological explanation provides an excellent framework of the most plausible neural structures involved in NMDAR-antibody encephalitis. Further, they note these movements can occur in semi-conscious patients, and this concurs well with the previous description of anti-gravity movements in the context of ‘status dissociatus’.2 A review of our 76 videos, revealed Thompson et al’s account of “variable, complex jerky semi-rhythmic movements….in the obtunded state” in 45 (59%) of cases. Therefore, this complex description was not present in almost half of patients. Furthermore, our recent clinical experiences note some NMDAR-antibody patients with abnormal movements but without obtundation: perhaps, given the known stepwise progression of many cases, this is a function of increasingly early disease recognition.3
By contrast to Thompson et al, our published study design intentionally used conventional phenomenological terms to define the movement disorder associated with NMDAR antibody-encephalitis.1 This approach aimed to define a pragmatic method, available to all clinicians, which could identify and faithfully communicate this complex movement disorder, with the important aim of earlier disease recognition. The results identified a dominant set of recognised classifications – dyston...
We thoroughly enjoyed reading the comment on our paper which analysed expert ratings of the movement disorder associated with NMDAR antibody-encephalitis.1 Thompson et al’s elegant pathophysiological explanation provides an excellent framework of the most plausible neural structures involved in NMDAR-antibody encephalitis. Further, they note these movements can occur in semi-conscious patients, and this concurs well with the previous description of anti-gravity movements in the context of ‘status dissociatus’.2 A review of our 76 videos, revealed Thompson et al’s account of “variable, complex jerky semi-rhythmic movements….in the obtunded state” in 45 (59%) of cases. Therefore, this complex description was not present in almost half of patients. Furthermore, our recent clinical experiences note some NMDAR-antibody patients with abnormal movements but without obtundation: perhaps, given the known stepwise progression of many cases, this is a function of increasingly early disease recognition.3
By contrast to Thompson et al, our published study design intentionally used conventional phenomenological terms to define the movement disorder associated with NMDAR antibody-encephalitis.1 This approach aimed to define a pragmatic method, available to all clinicians, which could identify and faithfully communicate this complex movement disorder, with the important aim of earlier disease recognition. The results identified a dominant set of recognised classifications – dystonia, stererotypies and chorea – with a paucity of tremor. In agreement with Thompson et al’s observations, it revealed some additional under-represented features. These were within our ‘other’ classification category (Figure 1D), and included mutism, stupor, myorhythmia, myokymia, tics, opisthotonus, ataxia, dyskinesias, waxy flexibility, oculogyric crises, athetosis, agitation, startle and vocal perseveration. However, we noted in our discussion that even the expert raters found it difficult to accurately describe this movement disorder within the predictable constraints of preconceived and established categorisations, and much of their feedback reflected a dissatisfaction with the final category chosen. Quantitatively, and by comparison to the other mixed movement disorders they rated, this limitation was strikingly reflected by the appreciably poorer inter-rater variability and the significantly more descriptive terms used to capture the essence of this movement disorder (P<0.0001).
Indeed, our findings are best interpreted within the intrinsic framework of movement disorder nomenclature. By extension, and particularly to the expert eye, we agree with Thompson et al that the disorder is often even more distinctive than this rare combination would suggest. In fact, in some cases, it may be unique. Interestingly, use of the term ‘unique’ may only be inaccurate given some of the closest mimics include ketamine / phencyclidine use and GRIN1A mutations. Of course, all of these imply the targeted specific-NMDAR modulation is at the core of this network-based pathophysiology.
Overall, within inevitable contemporary nomenclature constraints, we anticipate that the constellation of dystonia, stereotypies and chorea, with limited tremor, will provide a comprehensive, clear and concise message to clinicians and alert them to the possibility of this highly-treatable disorder. Yet, in future, perhaps this multifaceted movement disorder merits its own nomenclature to better emphasise the distinctive nature of the clinical observations. However, a term such as NMDAR-antibody associated movement disorder would be self-fulfilling and perhaps divert from the aim of its accurate recognition. Therefore, a reliance on conventional terms will yet be necessary to communicate this entity.
References
1. Varley JA, Webb AJS, Balint B, et al. The Movement disorder associated with NMDAR antibody-encephalitis is complex and characteristic: an expert video-rating study. J Neuro Neurosurg Psychiatry 2018;
2. Stamelou M, Plazzi G, Lugaresi E, et al. The distinct movement disorder in anti‐NMDA receptor encephalitis may be related to status dissociatus: A hypothesis. Mov Disord. 2012;27(11):1360–1363.
3. Irani SR, Bera K, Waters P, et al. N-methyl-D-aspartate antibody encephalitis: temporal progression of clinical and paraclinical observations in a predominantly non-paraneoplastic disorder of both sexes. Brain 2010;133(Pt 6):1655–1667.
We thank Dr Platt and colleagues for their critical review of our work, especially of the methodology that we have used in this study. It is understandable that comparative studies of treatment effectiveness trigger constructive discussions among industry and academics. We also vehemently agree that rigorous methodology and cautious interpretation of results is mandatory, especially for analyses of observational data.1 2 Therefore, in this letter, we will provide additional clarifications in response to the concerns raised.
We appreciate that the categories that are underrepresented in multivariable logistic regression models may lead to inflation of estimates of the corresponding coefficients and their variance. Such inflation would, however, result in an overly conservative matching rather than the opposite. Due to the use of a caliper, patients with an extreme propensity score can not be matched to patients within the bulk of the distribution of the propensity scores. Such patients were excluded from the matched cohorts.
The issue of residual imbalance is important in any non-randomised comparative study. We acknowledge that the standardised mean difference in annualised relapse rates (ARR) between teriflunomide and fingolimod exceeded the nominal threshold of 20%. It is therefore reassuring that the sensitivity analyses, in which the residual imbalance fell below the accepted threshold of 20% (patients with prior on-treatment relapses, Cohen’s d 14%, and...
Show MoreDear Editor,
We read with interest the article by Kalincik et al. [1] comparing fingolimod, dimethyl fumarate and teriflunomide in a cohort of relapsing-remitting multiple sclerosis (MS) patients. The authors investigated several endpoints and performed various sensitivity analyses, and we commend them for reporting technical details in the online supplementary material. We, however, have some concerns about the design, analysis and reporting of the study.
1. In the primary analyses, three separate propensity score models were developed to construct a matched cohort for each of the three pairwise comparisons. Supplementary Table 6 clearly indicates the existence of zero or low frequencies in some variables (e.g., most active previous therapy and magnetic resonance imaging [MRI] T2 lesions). Yet, those variables were used as covariates in the propensity score models, unsurprisingly resulting in extremely high point estimates and standard errors (SE; as reported in Supplementary Table 7). For example, teriflunomide was not the most active therapy for any patient in the dimethyl fumarate cohort (n=0 from Supplementary Table 6), but that category was nevertheless included in the propensity score model, leading to an unrealistic point estimate of 18.65 with SE of 434.5 (Supplementary Table 7). Even higher SEs (greater than 1000) are observed in the other propensity score models. Propensity scores estimated from these poorly constructed models were then used to cr...
Show MoreSeizures and movement disorders : cortico-subcortical networks
Dr Aileen McGonigal
Aix Marseille Univ, Inserm, INS, Institut de Neurosciences des Systèmes, Marseille, France
APHM, Timone Hospital, Clinical Neurophysiology, Marseille, France
Corresponding author: Dr Aileen McGonigal, Service de Neurophysiologie Clinique, CHU Timone, AP-HM, Marseille, France
Email : aileen.mcgonigal@univ-amu.fr
Tel: 00 33 491384995
Fax:00 33 491385826
To the Editors
I was interested to read the recent review by Dr Freitas and colleagues1. This interesting article highlights diagnostic challenges, clinical overlap and possible shared pathophysiological processes in epileptic seizures and movement disorders. I would like to add a couple of points that seem important to acknowledge.
Show MoreFirstly, in terms of clinical expression, the authors rightly mention that automatic movements occurring during focal epileptic seizures can sometimes resemble those seen in certain movement disorders, and they give the examples of orofacial automatisms (most often seen in temporal lobe seizures), as well as hyperkinetic behaviors. While the authors highlight sleep-related epilepsy as the main cause of hyperkinetic behavior, in fact hyperkinetic behavior may be seen in seizures from various cortical origins both in wakefulness and in sleep. It should be recognized that especially (though not exclusivel...
We applaud Suichi et al.[1] for proposing new diagnostic criteria for POEMS syndrome. There is clearly a need for simplified validated criteria that permit early diagnosis of this rare, elusive and devastating paraneoplastic disorder, especially because early local or systemic treatment of the underlying plasma cell malignancy can dramatically improve prognosis.[2] Our recent clinical experience[3] is in full agreement with the three proposed cardinal features of POEMS syndrome, namely polyneuropathy, vascular endothelial growth factor (VEGF) level elevation, and the presence of monoclonal protein. The authors argue that the triad alone may be insufficiently specific; therefore they propose the additional requirement of two of four secondary features, namely extravascular fluid accumulation, skin changes, organomegaly, and sclerotic bone lesion.
We would like to draw attention to clinical and methodological aspects that could further enhance or refine the diagnosis of POEMS syndrome. First, the process of diagnosis starts with clinical suspicion. Polyneuropathy is usually the earliest symptom of POEMS syndrome. POEMS syndrome should be considered in any patient with a severely progressive polyneuropathy of acute to subacute onset that is not otherwise explained, and VEGF level measurement should be offered. Routine screening for monoclonal protein (with immunofixation) and skeletal survey may be negative initially, and could remain negative for a long duration into...
Show MoreKomatsu et al. presented an interesting clinicopathological case of anti-myelin oligodendrocyte glycoprotein (MOG) demyelinating disease of the CNS. (1) Their patient had a rather unusual subacute encephalopathic presentation with extensive supratentorial fluid-attenuation inversion recovery white matter hyperintensities. The authors focused mainly on the conspicuous MRI punctuate and curvilinear enhancement pattern within the hemispheric lesions.
Show MoreIt is well established that intraparenchymal punctuate and curvilinear gadolinium enhancement may arise in the context of Moyamoya syndrome, various endotheliopathies and most commonly, in disorders causing small vessels blood-brain barrier disruption. (2)These entities are associated histologically with perivascular cellular infiltrates and include inflammatory autoimmune diseases (i.e. primary or secondary angiitis of the CNS, neurosarcoidosis, histiocytosis and demyelinating diseases of the CNS), pre-lymphoma states (i.e. sentinel lesions of primary CNS lymphoma), non-Hodgkin lymphoma (i.e. intravascular lymphoma) and CLIPPERS syndrome. (2) Notably, among demyelinating disorders, multiple sclerosis and aquaporin-4 antibody (AQP4-Ab) neuromyelitis optica spectrum disorders (NMOSD) manifest this specific neuroimaging pattern in rare cases. (2,3)
We agree with Komatsu et al. that their case is the first report of the perivascular enhancement in anti-MOG antibody disease. Indeed, gadolinium enhancement was observed in...
Re: A unifying theory for cognitive abnormalities in functional neurological disorders, fibromyalgia and chronic fatigue syndrome
Viraj Bharambe Specialist registrar in neurology
John C Williamson Specialist registrar in neurology
Andrew J Larner Consultant Neurologist
Cognitive Function Clinic
Walton Centre for Neurology and Neurosurgery
Lower Lane
Fazakerley
Liverpool
L9 7LJ
UK
e-mail: a.larner@thewaltoncentre.nhs.uk
Teodoro et al. present evidence for shared cognitive symptoms in fibromyalgia, chronic fatigue syndrome, and functional neurological disorders, and hypothesize that functional cognitive disorders (FCD) may share similar symptoms.1 We present data which speak to this issue.
We have previously reported preliminary data examining performance on the mini-Addenbrooke’s Cognitive Examination (MACE) by patients diagnosed with fibromyalgia2 as part of a larger study of MACE.3 Here, we update these data for fibromyalgia patients (n = 17; F:M = 17:0; age range 33-56 years, median 49) and compare them to MACE performance by patients diagnosed with FCD (n = 43; F:M = 18:25; age range 28-82 years, median 58).4
There was no statistical difference (p > 0.1) in the proportions of patients scoring below the two cut-off scores (≤21/30, ≤25/30) defined in the index MACE report.5 Looking at MACE subscores (Attention, Registration,...
Show MoreDear Editor,
Show MoreWe have read with great interest the work by Scarpazza et al that provided a longitudinal MRI evaluation of natalizumab-related Progressive Multifocal Leukoencephalopathy (NTZ-PML) lesions in Multiple Sclerosis (MS) patients (1).
Their central finding was the high percentage (78.1%) of patients, who eventually developed NTZ-PML, in whom highly suggestive lesions were already retrospectively detectable on pre-diagnostic MRI exams. Furthermore, the pre-diagnostic phase proved to be relatively long (150.8±74.9 days), with an estimated percentage increase of the lesions’ volume of 62.8% per month (1).
Given the widely recognized crucial role of a timely NTZ-PML identification in reducing mortality and residual disability (1), these results present the neurological and neuroradiological communities with an important clinical challenge, prompting a major effort to ensure an early diagnosis of this condition.
Although redefining the timing of MRI surveillance, with up to one brain MRI exam every 3-4 months for high-risk patients, appears as a justified strategy, we think that improving the accuracy of early identification of NTZ-PML is also mandatory.
In our opinion, such achievement should be pursued using two complementary approaches: (i) a specific training addressed to neuroradiologists working in the field of MS, who should be aware of the relevance of even very small asymptomatic PML lesions and how to differentiate them from new M...
Dear Editor,
We thank Abat et al. for re-emphasizing an important interpretation of our work, namely that sex-differences in life-expectancy likely influenced the presented lifetime risks [1]. Indeed, in our paper we repeatedly discussed in several sections (for instance in the methods) that differences in life-expectancy between men and women could differentially affect their lifetime risk. It was for this reason that we consequently decided to analyze the data in a sex-specific manner while taking the competing risk of death into account in order to prevent potential overestimation.
Abat et al. unfortunately also allege that we attributed the observed sex-differences in disease risk to sex-specific effects on a biological level. The authors have seemingly missed our discussion at length arguing that observed differences in lifetime risk may be primarily attributed to the effects of differences in life-expectancy between men and women: “Apart from a longer life-expectancy in general, these findings may be explained by smaller differences in life-expectancy between men and women in the Netherlands (1.8 years), compared with the USA (4.8 years). With longer life-expectancy, individuals in this study simply had more time to develop these diseases in a timeframe with high age-specific incidence rates.”
It seems thus that ours and Abat and co-authors’ interpretation of our findings is pretty much congruent, i.e. age, irrespective of sex, should be consid...
Show MoreTo the Editor,
Show MoreWe read with interest the work from Licher et al. [1] in which the authors tried to quantify the burden of common neurological diseases (i.e. dementia, stroke and parkinsonism) in 12 102 individuals (6 982 women and 5 120 men) aged ≥ 45 years and free from these diseases at baseline. All these individuals were recruited between 1990 and 2016 into the prospective population-based Rotterdam Study. At the end of their analyzes, the authors concluded that one in two women and one in three men will develop dementia, stroke or parkinsonism during their lifetime, and that the risk for women to develop both stroke and dementia during their life is almost twice that of men [1].
By reading the article from Licher et al. [1], we were extremely surprised by the fact that the authors did not consider the impact of the difference in life expectancies between men and women on their results and conclusions. This is particularly well underlined by the fact that the authors did not clearly precise the age structures of the two populations they studied [1]. In our view, this information is critical as, although the reasons for this difference are still debated and may probably be multi-factorial [2], it is well known that women live longer than men. This trend is confirmed by the 2018 World Health Statistics report [3] that estimates that in 2016, the life expectancies of men and women at birth were respectively 69.8 and 74.2 years at the international level. The...
We thoroughly enjoyed reading the comment on our paper which analysed expert ratings of the movement disorder associated with NMDAR antibody-encephalitis.1 Thompson et al’s elegant pathophysiological explanation provides an excellent framework of the most plausible neural structures involved in NMDAR-antibody encephalitis. Further, they note these movements can occur in semi-conscious patients, and this concurs well with the previous description of anti-gravity movements in the context of ‘status dissociatus’.2 A review of our 76 videos, revealed Thompson et al’s account of “variable, complex jerky semi-rhythmic movements….in the obtunded state” in 45 (59%) of cases. Therefore, this complex description was not present in almost half of patients. Furthermore, our recent clinical experiences note some NMDAR-antibody patients with abnormal movements but without obtundation: perhaps, given the known stepwise progression of many cases, this is a function of increasingly early disease recognition.3
By contrast to Thompson et al, our published study design intentionally used conventional phenomenological terms to define the movement disorder associated with NMDAR antibody-encephalitis.1 This approach aimed to define a pragmatic method, available to all clinicians, which could identify and faithfully communicate this complex movement disorder, with the important aim of earlier disease recognition. The results identified a dominant set of recognised classifications – dyston...
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