Author Of 1 Presentation

Neuromyelitis Optica and Anti-MOG Disease Oral Presentation

PS15.03 - Optical coherence tomography in aquaporin-4-IgG positive neuromyelitis optica spectrum disorders: a collaborative multi-center study

Abstract

Background

Optic neuritis (ON) is a frequent manifestation in aquaporin-4 antibody (AQP4-IgG) seropositive neuromyelitis optica spectrum disorders (NMOSD). Due to limited samples, existing optical coherence tomography (OCT) studies are inconsistent regarding retinal changes in eyes with a history of ON (NMO-ON) and without a history of ON (NMO-NON), and their functional relevance.

Objectives

The CROCTINO (Collaborative Retrospective Study on retinal OCT in Neuromyelitis Optica) project aims to reveal correlates of retinal pathology and to generate hypotheses for prospective OCT studies in NMOSD. The objective of this study was to analyze retinal changes of AQP4-IgG seropositive NMO-ON and NMO-NON eyes in an international cross-sectional OCT dataset.

Methods

Of 656 subjects, we enrolled 283 AQP4-IgG seropositive NMOSD patients and 72 healthy controls (HC) from 22 international expert centers. OCT data was acquired with Spectralis SD-OCT, Cirrus HD-OCT and Topcon 3D OCT-1. Mean thickness for the combined ganglion cell and inner plexiform layer (GCIP) and inner nuclear layer (INL) were calculated from macular volume scans. Clinical, functional and laboratory testing were performed at discretion of each center.

Results

We compared NMO-ON eyes (N = 260), NMO-NON eyes (N = 241) and HC eyes (N = 136). GCIP was reduced in NMO-ON (57.4 ± 12.2 µm) compared with NMO-NON (75.9 ± 7.7 µm; p < 0.001) and HC (81.4 ± 5.7 µm; p < 0.001). NMO-NON had thinner GCIP (p < 0.001) compared with HC. INL was thicker in NMO-ON (40.3 ± 3.9 µm) compared with NMO-NON (38.6 ± 3.9µm; p < 0.001), but not HC (39.4 ± 2.6 µm). Microcystic macular edema were visible in 6.6 % of NMOSD eyes.

Conclusions

AQP4-IgG seropositive NMOSD is characterized by a functionally relevant loss of retinal neuroaxonal content and a - probably inflammatory - increase of INL after ON. Our study further supports the existence of attack-independent damage in the visual system of patients with AQP4-IgG seropositive NMOSD.

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Author Of 3 Presentations

Imaging Poster Presentation

P0567 - Diffusion-based Structural connectivity abnormalities in MS phenotypes. (ID 1271)

Abstract

Background

People with MS present disruption of structural brain networks, but the differential characteristics of such changes among MS phenotypes and their clinical impact are not well elucidated.

Objectives

To characterize diffusion-based brain connectivity abnormalities in different MS phenotypes and their relation with disability in a large cohort of patients.

Methods

In this multicenter, retrospective, cross-sectional study, we collected clinical and brain MRI data from 344 patients with MS [median Expanded Disability Status Scale, EDSS 2.0 (range 0-7.0)] and 91 healthy volunteers (HV) from four MAGNIMS centers. Cognition was assessed with the Paced Auditory Serial Addition Test (PASAT) and Symbol Digits Modalities Test (SDMT) in 298 patients. We collected 3D-T1, FLAIR, diffusion-weighted images (DWI) and T2 or field maps acquisitions. FSL and ANTs packages were used to carry out DWI preprocessing and MRtrix software to generate connectivity matrices based on fractional anisotropy values. We computed six network measures (strength, global and local efficiency, clustering coefficient, assortativity and transitivity), and applied the ComBat tool to reduce inter-site variability. We calculated age-adjusted differences in graphs between groups using Mann-Whitney with FDR correction or Kruskal-Wallis with Dunn’s Test when necessary. Associations with clinical features were explored with Spearman’s rank correlation.

Results

Thirty-eight (11%) patients presented a clinically isolated syndrome (CIS), 262 (76%) had relapsing-remitting (RR) and 44 (13%) secondary progressive (SP) MS. CIS patients showed reduced global and local efficiency, clustering coefficient and transitivity compared to HV (corrected p<0.001), whilst RRMS did not differ from CIS patients. Compared with CIS and RRMS, patients with SPMS showed larger changes for the same previous graphs measures (corrected p<0.05), and lower strength than RRMS (corrected p=0.019).

In patients, reduced measures of strength, global and local efficiency, clustering and transitivity correlated with higher EDSS (rho:-0.12–-0.16, corrected p<0.034), lower PASAT (rho:0.26–0.30, corrected p<0.001) and worse SDMT scores (rho:0.28–0.32, corrected p<0.001).

Conclusions

Structural network integrity at the whole brain level is already widely reduced in people with MS from the earliest phases of the disease and becomes more abnormal in SPMS. Network modifications may contribute to the clinical manifestations of the disease.

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Neuropsychology and Cognition Poster Presentation

P0805 - Dynamics of cognitive decline along the disease course in multiple sclerosis (ID 897)

Abstract

Background

Cognitive decline is frequent in patients with multiple sclerosis (MS). The cognitive trajectory is not well understood and a global overview throughout the disease course needs to be elucidated. Besides, predictors of future cognitive decline are still needed.

Objectives

We aim to (a) assess the temporal dynamics of cognitive function through disease course, and (b) explore different clinical and MRI predictors of cognitive decline in a large cohort of patients with MS.

Methods

Longitudinal study with 212 MS patients who performed a total of 605 neurological, cognitive and MRI examinations at different times of the disease [examinations per patient: 3 (IQR:2-3); baseline age: 40.2 (IQR:34.5-47.6) years; baseline disease duration: 8.2 (IQR:2.3-13.9) years]. A z-score for global cognition (z-BRB) and for each cognitive domain was obtained from the Rao's Battery, and a 3D-structural MRI was acquired to calculate regional gray matter (GM) volumes. We modelled the dynamics of cognition throughout the MS course using age at MS onset, education and sex adjusted mixed-effects linear spline models with knots at 5 and 15 years. An age and sex adjusted multivariate regression model was performed to determine which factors at the first examination best predict cognitive performance at last follow-up in the entire sample.

Results

In the first 5 years of MS, we detected an increase in z-BRB (β=0.050, p=0.004) and z-attention (β=0.048, p=0.013), followed by a decline in z-BRB (β=-0.029, p=0.005) and z-verbal memory (β=-0.049, p=0.001) between the 5-15 years of the disease. During the 15-30 years of MS course, the cognitive decline was maintained, but also involved z-attention (β=-0.035, p=0.012). Lower education, higher EDSS and volumetric changes at right parahippocampus, left parsorbitalis, left superior, left middle and right inferior temporal, and right superior parietal areas at the first examination were associated with worse z-BRB at the last follow-up (adjR2=0.48, β=-0.652–0.863, p=<0.001–0.024).

Conclusions

In MS, cognition deteriorates after the first 5 years of the disease, with a steady decline over the next 25 years. The verbal memory is affected earlier and more markedly, followed by involvement of attention and information processing speed. Moreover, education, clinical disability and GM volume at baseline are associated with future cognitive outcomes.

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Invited Presentations Invited Abstracts

TC14.03 - Propensity Score: Neither a Black Box nor a Magic Bullet (ID 631)

Presentation Number
TC14.03
Presentation Topic
Invited Presentations

Abstract

Abstract

There is a trend in the medical literature towards the use of real-world data to inform aspects related with efficacy and safety in people living with MS. Indeed, there are some key aspects, mostly related with safety (e.g. rare and life-threatening adverse effects), for which the use of real-world data is the most convenient approach (if not the only feasible). However, we should carefully deal with confounding as a key issue for achieving causal inference, and thereof, getting real-world (unbiased) evidence through the use of real-world data from non-randomized study designs.

(1) To describe the use of propensity-score (PS)-based methods as an attempt for controlling for confounding.

(2) To learn the advantages, limitations and assumptions of these approaches to interpret the results from studies using these methods based on our own judgement

After a brief introduction on different available methods for controlling for confounding, we will narrow the lecture on propensity-score (PS)-based methods, particularly on PS-matching, a frequent approach in studies using observational data in MS.

In this course, we will explain the key concepts of PS-methods including the methodology of use, advantages, limitations and assumptions of these approaches.

A PS is a continuous variable that defines the probability of exposition (e.g. “use of a given DMD”) conditional (“as a function”) on the confounders. In this session, we will explain how to build a valid logistic regression model to estimate a PS. Then, we will describe different uses of PS with especial emphasis on PS-matching for which the estimation will be described step-by-step. We will explain the concept of caliper (the most commonly-used criterion for matching) and the assumptions derived from the bias-variance trade off. We will explain how standardized variable differences and Love Plots can help us to judge whether the matching on PS has been successfully performed in a study.

After the completion, the attendees will be able to better interpret the results coming from studies using PS-based methods. They shall use their own judgement to assess whether the reported analyses may or may not provide be reliable, unbiased findings.

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Presenter Of 1 Presentation

Invited Presentations Invited Abstracts

TC14.03 - Propensity Score: Neither a Black Box nor a Magic Bullet (ID 631)

Presentation Number
TC14.03
Presentation Topic
Invited Presentations

Abstract

Abstract

There is a trend in the medical literature towards the use of real-world data to inform aspects related with efficacy and safety in people living with MS. Indeed, there are some key aspects, mostly related with safety (e.g. rare and life-threatening adverse effects), for which the use of real-world data is the most convenient approach (if not the only feasible). However, we should carefully deal with confounding as a key issue for achieving causal inference, and thereof, getting real-world (unbiased) evidence through the use of real-world data from non-randomized study designs.

(1) To describe the use of propensity-score (PS)-based methods as an attempt for controlling for confounding.

(2) To learn the advantages, limitations and assumptions of these approaches to interpret the results from studies using these methods based on our own judgement

After a brief introduction on different available methods for controlling for confounding, we will narrow the lecture on propensity-score (PS)-based methods, particularly on PS-matching, a frequent approach in studies using observational data in MS.

In this course, we will explain the key concepts of PS-methods including the methodology of use, advantages, limitations and assumptions of these approaches.

A PS is a continuous variable that defines the probability of exposition (e.g. “use of a given DMD”) conditional (“as a function”) on the confounders. In this session, we will explain how to build a valid logistic regression model to estimate a PS. Then, we will describe different uses of PS with especial emphasis on PS-matching for which the estimation will be described step-by-step. We will explain the concept of caliper (the most commonly-used criterion for matching) and the assumptions derived from the bias-variance trade off. We will explain how standardized variable differences and Love Plots can help us to judge whether the matching on PS has been successfully performed in a study.

After the completion, the attendees will be able to better interpret the results coming from studies using PS-based methods. They shall use their own judgement to assess whether the reported analyses may or may not provide be reliable, unbiased findings.

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Moderator Of 1 Session

Teaching Course Fri, Sep 11, 2020
Session Type
Teaching Course
Date
Fri, Sep 11, 2020

Invited Speaker Of 1 Presentation

Invited Presentations Invited Abstracts

TC14.03 - Propensity Score: Neither a Black Box nor a Magic Bullet (ID 631)

Presentation Number
TC14.03
Presentation Topic
Invited Presentations

Abstract

Abstract

There is a trend in the medical literature towards the use of real-world data to inform aspects related with efficacy and safety in people living with MS. Indeed, there are some key aspects, mostly related with safety (e.g. rare and life-threatening adverse effects), for which the use of real-world data is the most convenient approach (if not the only feasible). However, we should carefully deal with confounding as a key issue for achieving causal inference, and thereof, getting real-world (unbiased) evidence through the use of real-world data from non-randomized study designs.

(1) To describe the use of propensity-score (PS)-based methods as an attempt for controlling for confounding.

(2) To learn the advantages, limitations and assumptions of these approaches to interpret the results from studies using these methods based on our own judgement

After a brief introduction on different available methods for controlling for confounding, we will narrow the lecture on propensity-score (PS)-based methods, particularly on PS-matching, a frequent approach in studies using observational data in MS.

In this course, we will explain the key concepts of PS-methods including the methodology of use, advantages, limitations and assumptions of these approaches.

A PS is a continuous variable that defines the probability of exposition (e.g. “use of a given DMD”) conditional (“as a function”) on the confounders. In this session, we will explain how to build a valid logistic regression model to estimate a PS. Then, we will describe different uses of PS with especial emphasis on PS-matching for which the estimation will be described step-by-step. We will explain the concept of caliper (the most commonly-used criterion for matching) and the assumptions derived from the bias-variance trade off. We will explain how standardized variable differences and Love Plots can help us to judge whether the matching on PS has been successfully performed in a study.

After the completion, the attendees will be able to better interpret the results coming from studies using PS-based methods. They shall use their own judgement to assess whether the reported analyses may or may not provide be reliable, unbiased findings.

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