Monitoring Multiple Sclerosis Research Articles

Predictive value of individual serum neurofilament light chain levels in short-term disease activity in relapsing multiple sclerosis.

The assessment of serum neurofilament light chain (sNFL) has emerged as a diagnostic and prognostic tool in monitoring multiple sclerosis (MS). However, the application of periodic measurement in daily practice remains unclear. To evaluate the predictive value of individual sNFL levels in determining disease activity in patients with relapsing MS (RMS). In this two-year prospective study, 129 RMS patients underwent quarterly sNFL assessments and annual MRI scans. The study analyzed the correlation between individual NFL levels and past, current, and future disease activity. Group-level Z-scores were employed as a comparative measure. Among the 37 participants, a total of 61 episodes of disease activity were observed. sNFL levels proved valuable in distinct ways; they were confirmatory of previous and current clinical and/or radiological activity and demonstrated a high negative predictive value for future 90 days activity. Interestingly, Z-scores marginally outperformed sNFL levels in terms of predictive accuracy, indicating the potential for alternative approaches in disease activity assessment. In our cohort, sNFL cut-offs of 10.8 pg./mL (sensitivity 27%, specificity 90%) and 14.3 pg./mL (sensitivity 15%, specificity 95%) correctly identified 7 and 4 out of 26 cases of radiological activity within 90 days, respectively, with 14 and 15% false negatives. When using lower cut-off values, individuals with sNFL levels below 5 pg/mL (with a sensitivity of 92%, specificity of 25%, and negative predictive value of 94%) were less likely to experience radiological activity within the next 3 months. Individual sNFL levels may potentially confirm prior or current disease activity and predict short-term future radiological activity in RMS. These findings underscore its periodic measurement as a valuable tool in RMS management and decision-making, enhancing the precision of clinical evaluation in routine practice.

Longitudinal deep network for consistent OCT layer segmentation.

Retinal layer thickness is an important bio-marker for people with multiple sclerosis (PwMS). In clinical practice, retinal layer thickness changes in optical coherence tomography (OCT) are widely used for monitoring multiple sclerosis (MS) progression. Recent developments in automated retinal layer segmentation algorithms allow cohort-level retina thinning to be observed in a large study of PwMS. However, variability in these results make it difficult to identify patient-level trends; this prevents patient specific disease monitoring and treatment planning using OCT. Deep learning based retinal layer segmentation algorithms have achieved state-of-the-art accuracy, but the segmentation is performed on each individual scan without utilizing longitudinal information, which can be important in reducing segmentation error and reveal subtle changes in retinal layers. In this paper, we propose a longitudinal OCT segmentation network which achieves more accurate and consistent layer thickness measurements for PwMS.

Double inversion recovery to detect cervical spinal cord multiple sclerosis lesions.

Magnetic resonance imaging (MRI) plays a key role in diagnosing and monitoring multiple sclerosis (MS). Double inversion recovery (DIR) is a pulse sequence that has proven highly effective at detecting cortical lesions but is understudied in the spinal cord. We hypothesize that DIR images obtained during brain MRI can be of value in assessing the upper spinal cord of MS patients. We retrospectively examined brain MRI exams of 64 patients with established MS, who had also undergone cervical spine MRI. Two blinded MS expert readers, who assessed the scans for lesion numbers and rated lesion visibility and overall image quality, reviewed brain 3-dimensional DIR sagittal and coronal images. Standardized mean contrast-to-noise ratios (C/N) and standard deviation (SD) were calculated in representative lesions for each patient and compared to those of 3-dimensional FLAIR images. For the analysis of lesions categorized as "definite lesions," the sensitivity was 87%, specificity was 61%, and negative predictive value was 80%. On the other hand, for "definite" plus "probable" lesions, the sensitivity was 91%, the specificity was 54%, and negative predictive value was 86%. DIR demonstrated lesions with an average C/N of 7.56 with an SD of 1.77. FLAIR sequence demonstrated lesions with an average C/N of 0.67 and SD of 1.27. Sagittally acquired brain DIR can provide useful information on upper spinal cord lesions, with high C/N. In theory, this should facilitate the attainment of McDonald's or the Magnetic Resonance Imaging in MS (MAGNIMS) criteria in some cases, without a dedicated cervical spine MRI exam.

THUR 199 MS DMT monitoring according to abn guidelines & product specification

AimRetrospective audit monitoring Multiple Sclerosis (MS) patients on Disease Modifying Therapies (DMT’s) according to Association of British Neurologists (ABN) guidelines (2015) and product specifications. This requires blood tests prior and during treatment and reviews by MS professionals.MethodsMS nurse database identified patients, records were reviewed and data extracted including bloods, JC virus (JCV) testing, imaging, specialist tests and counselling. Analysis was presented to the MS team. Protocols and referral pathways were designed, and new patients were re-audited.ResultsThe first cycle comprised of 280 patients, representing 325 individual DMT regimens. Prior to commencing treatments 90.7% blood tests, 58% imaging, and 60% JCV testing was completed on average. At 12 months, this decreased to 88.7% bloods, 30% imaging, and 25% JCV testing. Electronic records revealed that counselling documentation was sometimes incomplete. The second cycle analysed 55 patients showing improvement in Progressive multifocal leukoencephalopathy counselling and annual imaging.ConclusionMonitoring of bloods is done at a high standard, imaging and JCV testing less frequently meet monitoring guidelines. Factors influencing this include rural locations, variation in practice, and changing guidelines. Further work will include yearly follow-up, documentation of stopping criteria and regular review of monitoring guidelines. Patient involvement should be considered.

Development and validation of a claims-based measure as an indicator for disease status in patients with multiple sclerosis treated with disease-modifying drugs

BackgroundAdministrative healthcare claims data provide a mechanism for assessing and monitoring multiple sclerosis (MS) disease status across large, clinically representative “real-world” populations. The estimation of MS disease status using administrative claims can be a challenge, however, due to a lack of detailed clinical information. Retrospective claims analyses in MS have traditionally used rates of MS relapses to approximate disease status. Healthcare costs may be alternate, broader claims-based indicators of disease activity because costs reflect multiple facets of care of patients with MS, and there is a strong correlation between quality of life of patients with MS and costs of the disease. This study developed, tested, and validated a healthcare cost-based measure to serve as an indicator of overall disease status in patients with MS treated with disease-modifying drugs (DMDs) utilizing administrative claims.MethodsUsing IMS Health Real World Data Adjudicated Claims – US data (January 2006–June 2013), a negative binomial regression predicted annual all-cause medical costs. Coefficients reaching statistical significance (p < 0.05) and increasing costs by ≥5% were selected for inclusion into an MS-specific severity score (scale of 0 to 100). Components of the score included rehabilitation services, altered mental state, pain, disability, stiffness, balance disorder, urinary incontinence, numbness, malaise/fatigue, and infections. Coefficient weights represented each predictor’s contribution. The predictive model was derived using 50% of a random sample and tested/validated using the remaining 50%.ResultsAverage overall predicted annual total medical cost was $11,134 (development sample, n = 11,384, vs. $10,528 actual) and $11,303 (validation sample, n = 11,385, vs. $10,620 actual). The model had consistent bias (approximately +$600 or +6% of actual costs) for both samples. In the validation sample, mean MS disease status scores were 0.24, 8.95, and 21.77 for low, medium, and high tertiles, respectively. Mean costs were most accurately predicted among less severe patients ($5243 predicted vs. $5233 actual cost for lowest tertile).ConclusionThe algorithm developed in this study provides an initial step to helping understand and potentially predict cost changes for a commercially insured MS population.

Functional plasticity in MS

MRI is an irreplaceable tool for diagnosing and monitoring multiple sclerosis (MS). Indeed, conventional MRI is very sensitive in detecting focal, macroscopic white matter lesions of the CNS. This has led to the formulation of diagnostic criteria, which rely not only on the neurologic assessment, but also on MRI markers. Similarly, conventional MRI is also used worldwide to monitor natural MS evolution, or to monitor specific treatment strategies. Recently, research has tried to broaden the horizon of MRI applications in MS beyond lesion detection.1 In this context, diffusion tensor imaging studies have shown that patients with MS experience microstructural tissue abnormalities that …

Zerebrale und spinale MRT-Untersuchung bei Patienten mit klinisch isoliertem Syndrom oder gesicherter Multipler Sklerose

Magnetic resonance imaging (MRI) has become a valuable tool for diagnosing and monitoring multiple sclerosis (MS). The high sensitivity for the detection of hyperintense lesions in T 2-weighted scans contributes substantially to diagnosis. The initial lesion number or lesion volume stands for an increased probability of further accumulation of lesion burden, an earlier conversion to clinically definite MS and progression of disability in the next 5 - 15 years. This diagnostic and prognostic information gained from MRI early in the disease course lead in 2001 to a revision of the diagnostic criteria. For the first time MRI criteria were defined in addition to the clinical and paraclinical criteria using the clinical terms for dissemination with respect to space and time. In particular, the defined MRI criteria are based on lesion number and location, the appearance of new lesions and lesion enhancement using contrast agent. Reliable detection and description of older and new lesions in the disease course by MRI represents subclinical disease activity which can substitute the clinical confirmation of a relapse leading to an earlier diagnosis. This places importance on the assessment of the subclinical disease activity in sequential MR scans requiring a standardized and reproducible approach to minimize variability despite different MR scanners. This review provides an updated proposal for the approach and management of cranial and spinal MR scans in patients with MS. We describe the influence of variables which cannot be standardized (scanner, field strength, manufacturer and software) and outline potential pitfalls of clinical MR imaging in MS resulting from a non-standardized approach. This updated proposal for slice positioning, sequences and documentation is a result of a consensus process targeting systematic and standardized use in clinical MR evaluations of MS.

Modelling new enhancing MRI lesion counts in multiple sclerosis.

Magnetic resonance imaging (MRI) has been established as the most relevant paraclinical tool for diagnosing and monitoring multiple sclerosis (MS). In this context, counting the number of new enhancing lesions on monthly MRI scans is widely used as a surrogate marker of MS activity when evaluating the effect of treatments. In this study, we investigated whether parametric models based on mixed Poisson distributions (the Negative Binomial (NB) and the Poisson-Inverse Gaussian (P-IG) distributions) were able to provide adequate fitting of new enhancing lesion counts in MS. We found that the NB model gave good approximations in relapsing-remitting and secondary progressive MS patients not selected for baseline MRI activity, whereas the P-IG distribution modelled better new enhancing lesion counts in relapsing-remitting MS patients selected for baseline activity. This study shows that parametric modelling for MS new enhancing lesion counts is feasible. This approach should provide more targeted tools for the design and the analysis of MRI monitored clinical trials in MS.