scholarly journals Canadian Normative Data for Minimal Assessment of Cognitive Function in Multiple Sclerosis

2017 ◽  
Vol 44 (5) ◽  
pp. 547-555 ◽  
Author(s):  
Lisa A.S. Walker ◽  
David Marino ◽  
Jason A. Berard ◽  
Anthony Feinstein ◽  
Sarah A. Morrow ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Cognitive Function ◽  
Normative Data ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Demographic Variables ◽  
Data Sets ◽  
Demographic Differences ◽  
Canadian Population ◽  
Healthy Control

AbstractObjective: The Minimal Assessment of Cognitive Function in Multiple Sclerosis (MACFIMS) is a consensus-based collection of neuropsychological tests that evaluate cognitive functioning in individuals with multiple sclerosis (MS). The tests are typically scored using each respective published test manual, leaving the examiner to make interpretations from norms derived from different American populations. Given demographic differences, this may lead to misinterpretation of findings in Canadians. Our goal was to establish both discrete and regression-based normative data for the MACFIMS based on a largely co-normed Canadian population to allow for improved psychometric interpretation. Methods: MACFIMS data sets were aggregated from across three different Canadian cities (Ottawa, Toronto, and London), yielding a total of 330 healthy control participants from four different studies evaluating cognition in individuals with MS. Given the variety of contributing studies, there was variability in terms of the number of participants completing each measure. Results: Both age-based discrete normative data and demographically adjusted (sex, age, and education) regression-based formulae were established. The demographic variables varied in their contribution to each MACFIMS test in the regression models, predicting 0 to 18% of the variance. Conclusions: Provision of these regression-based formulae will allow for more accurate interpretation of Canadian-derived MACFIMS scores by allowing clinicians to correct for all relevant demographic variables simultaneously, leading to improved clinical decision making for individuals with multiple sclerosis.

scholarly journals Ethical use of off-label disease-modifying therapies for multiple sclerosis

2021 ◽  
pp. 135245852110302
Author(s):  
Joanna Laurson-Doube ◽  
Nick Rijke ◽  
Anne Helme ◽  
Peer Baneke ◽  
Brenda Banwell ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
World Health ◽  
World Federation ◽  
Off Label ◽  
Disease Modifying Therapies ◽  
The World ◽  
Disease Modifying ◽  
Health Organization

Background: Off-label disease-modifying therapies (DMTs) for multiple sclerosis (MS) are used in at least 89 countries. There is a need for structured and transparent evidence-based guidelines to support clinical decision-making, pharmaceutical policies and reimbursement decisions for off-label DMTs. Objectives/Results: The authors put forward general principles for the ethical use of off-label DMTs for treating MS and a process to assess existing evidence and develop recommendations for their use. Conclusion: The principles and process are endorsed by the World Federation of Neurology (WFN), American Academy of Neurology (AAN), European Academy of Neurology (EAN), Americas Committee for Treatment and Research in Multiple Sclerosis (ACTRIMS), European Committee for Treatment and Research in Multiple Sclerosis (ECTRIMS), Middle-East North Africa Committee for Treatment and Research in Multiple Sclerosis (MENACTRIMS) and Pan-Asian Committee for Treatment and Research in Multiple Sclerosis (PACTRIMS), and we have regularly consulted with the Brain Health Unit, Mental Health and Substance Use Department at the World Health Organization (WHO).

scholarly journals Treatment Discontinuation and Disease Progression with Injectable Disease-Modifying Therapies

2013 ◽  
Vol 15 (4) ◽  
pp. 194-201 ◽  
Author(s):  
Robert J. Fox ◽  
Amber R. Salter ◽  
Tuula Tyry ◽  
Jennifer Sun ◽  
Xiaojun You ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Disease Progression ◽  
Clinical Decision Making ◽  
Medication Compliance ◽  
Clinical Decision ◽  
Research Committee ◽  
The North ◽  
Disease Modifying Therapies ◽  
Patient Reported ◽  
Disease Modifying

Injectable first-line disease-modifying therapies (DMTs) for multiple sclerosis (MS) are generally prescribed for continuous use. Accordingly, the various factors that influence patient persistence with treatment and that can lead some patients to switch medications or discontinue treatment may affect clinical outcomes. Using data from the North American Research Committee on Multiple Sclerosis (NARCOMS) database, this study evaluated participants' reasons for discontinuation of injectable DMTs as well as the relationship between staying on therapy and sustained patient-reported disease progression and annualized relapse rates. Participants selected their reason(s) for discontinuation from among 16 possible options covering the categories of efficacy, safety, tolerability, and burden, with multiple responses permitted. Both unadjusted data and data adjusted for baseline age, disease duration, disability, and sex were evaluated. Discontinuation profiles varied among DMTs. Participants on intramuscular interferon beta-1a (IM IFNβ-1a) and glatiramer acetate (GA) reported the fewest discontinuations based on safety concerns, although GA was associated with reports of higher burden and lower efficacy than other therapies. Difficulties with tolerability were more often reported as a reason for discontinuing subcutaneous (SC) IFNβ-1a than as a reason for discontinuing IM IFNβ-1a, GA, or SC IFNβ-1b. In the persistent therapy cohort, less patient-reported disability progression was reported with IM IFNβ-1a treatment than with SC IFNβ-1a, IFNβ-1b, or GA. These findings have relevance to clinical decision making and medication compliance in MS patient care.

Complementing sparse vascular imaging data by physiological adaptation rules

2020 ◽  
Author(s):  
Maarten H.G. Heusinkveld ◽  
Robert J. Holtackers ◽  
Bouke P. Adriaans ◽  
Jos Op't Roodt ◽  
Theo Arts ◽  
...  
Keyword(s):  
Clinical Decision Making ◽  
Mechanical Load ◽  
Wall Stress ◽  
Clinical Decision ◽  
Physiological Adaptation ◽  
Patient Specific ◽  
Data Sets ◽  
Imaging Data ◽  
Artery Segment ◽  
Flow Waveforms

Introduction:Mathematical modeling of pressure and flow waveforms in blood vessels using pulse wave propagation (PWP)-models has tremendous potential to support clinical decision-making. For a personalized model outcome, measurements of all modeled vessel radii and wall thicknesses are required. In clinical practice, however, data sets are often incomplete. To overcome this problem, we hypothesized that the adaptive capacity of vessels in response to mechanical load could be utilized to fill in the gaps of incomplete patient-specific data sets. Methods:We implemented homeostatic feedback loops in a validated PWP model to allow adaptation of vessel geometry to maintain physiological values of wall stress and wall shear stress. To evaluate our approach, we gathered vascular MRI and ultrasound data sets of wall thicknesses and radii of central and arm arterial segments of ten healthy subjects. Reference models (i.e. termed RefModel, n=10) were simulated using complete data, whereas adapted models (AdaptModel, n=10) used data of one carotid artery segment only while the remaining geometries in this model were estimated using adaptation. We evaluated agreement between RefModel and AdaptModel geometries, as well as between pressure and flow waveforms of both models. Results:Limits of agreement (bias±2SD of difference) between AdaptModel and RefModel radii and wall thicknesses were 0.2±2.6 mm and -140±557 μm, respectively. Pressure and flow waveform characteristics of the AdaptModel better resembled those of the RefModels as compared to the model in which the vessels were not adapted.Conclusions:Our adaptation-based PWP-model enables personalization of vascular geometries even when not all required data is available.

scholarly journals Knowledge transfer to enhance the performance of deep learning models for automated classification of B-cell neoplasms

2021 ◽  
Author(s):  
Nanditha Mallesh ◽  
Max Zhao ◽  
Lisa Meintker ◽  
Alexander Höllein ◽  
Franz Elsner ◽  
...  
Keyword(s):  
Flow Cytometry ◽  
Deep Learning ◽  
Knowledge Transfer ◽  
Clinical Decision Making ◽  
Dimensional Space ◽  
Clinical Decision ◽  
Data Sets ◽  
Automated Classification ◽  
Learning Models ◽  
Hematological Disorders

AbstractMulti-parameter flow cytometry (MFC) is a cornerstone in clinical decision making for hematological disorders such as leukemia or lymphoma. MFC data analysis requires trained experts to manually gate cell populations of interest, which is time-consuming and subjective. Manual gating is often limited to a two-dimensional space. In recent years, deep learning models have been developed to analyze the data in high-dimensional space and are highly accurate. Such models have been used successfully in histology, cytopathology, image flow cytometry, and conventional MFC analysis. However, current AI models used for subtype classification based on MFC data are limited to the antibody (flow cytometry) panel they were trained on. Thus, a key challenge in deploying AI models into routine diagnostics is the robustness and adaptability of such models. In this study, we present a workflow to extend our previous model to four additional MFC panels. We employ knowledge transfer to adapt the model to smaller data sets. We trained models for each of the data sets by transferring the features learned from our base model. With our workflow, we could increase the model’s overall performance and more prominently, increase the learning rate for very small training sizes.

scholarly journals Performance of Regression-Based Norms for Cognitive Functioning of Persons With Multiple Sclerosis in an Independent Sample

2021 ◽  
Vol 11 ◽  
Author(s):  
Ruth Ann Marrie ◽  
Christiane E. Whitehouse ◽  
Ronak Patel ◽  
Chase R. Figley ◽  
Jennifer Kornelsen ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Relative Efficiency ◽  
Employment Status ◽  
Normative Data ◽  
Healthy Adults ◽  
Cognitive Tests ◽  
Healthy Controls ◽  
Control Groups ◽  
Z Scores ◽  
Healthy Control

Background: Cognitive impairment is common in multiple sclerosis (MS). Interpretation of neuropsychological tests requires the use of normative data. Traditionally, normative data have been reported for discrete categories such as age. More recently continuous norms have been developed using multivariable regression equations that account for multiple demographic factors. Regression-based norms have been developed for use in the Canadian population for tests included in the MACFIMS and BICAMS test batteries. Establishing the generalizability of these norms is essential for application in clinical and research settings.Objectives: We aimed to (i) test the performance of previously published Canadian regression-based norms in an independently collected sample of Canadian healthy controls; (ii) compare the ability of Canadian and non-Canadian regression-based norms to discriminate between healthy controls and persons with MS; and (iii) develop regression-based norms for several cognitive tests drawn from batteries commonly used in MS that incorporated race/ethnicity in addition to age, education, and sex.Methods: We included 93 adults with MS and 96 healthy adults in this study, with a replication sample of 104 (MS) and 39 (healthy adults). Participants reported their sociodemographic characteristics, and each was administered the oral Symbol Digit Modalities Test (SDMT), the California Verbal Learning Test (CVLT-II), and the Brief Visuospatial Memory Test-Revised (BVMT-R). From the healthy control data, we developed regression-based norms incorporating race, age, education and sex. We then applied existing discrete norms and regression-based norms for the cognitive tests to the healthy controls, and generated z-scores which were compared using Spearman rank and concordance coefficients. We also used receiver operating characteristic (ROC) curves to compare the ability of each set of norms to discriminate between participants with and without MS. Within the MS samples we compared the ability of each set of norms to discriminate between differing levels of disability and employment status using relative efficiency.Results: When we applied the published regression norms to our healthy sample, impairment classification rates often differed substantially from expectations (7%), even when the norms were derived from a Canadian (Ontario) population. Most, but not all of the Spearman correlations between z-scores based on different existing published norms for the same cognitive test exceeded 0.90. However, concordance coefficients were often lower. All of the norms for the SDMT reliably discriminated between the MS and healthy control groups. In contrast, none of the norms for the CVLT-II or BVMT-R discriminated between the MS and healthy control groups. Within the MS population, the norms varied in their ability to discriminate between disability levels or employment status; locally developed norms for the SDMT and CVLT-II had the highest relative efficiency.Conclusion: Our findings emphasize the value of local norms when interpreting the results of cognitive tests and demonstrate the need to consider and assess the performance of regression-based norms developed in other populations when applying them to local populations, even when they are from the same country. Our findings also strongly suggest that the development of regression-based norms should involve larger, more diverse samples to ensure broad generalizability.

scholarly journals Cognitive Impairment in Late-Life Depression: A Comparative Study of Healthy Older People, Late-Life Depression, and Mild Alzheimer's Disease Using Multivariate Base Rates of Low Scores

2021 ◽  
Vol 12 ◽  
Author(s):  
Caroline Masse ◽  
Pierre Vandel ◽  
Géraldine Sylvestre ◽  
Nicolas Noiret ◽  
Djamila Bennabi ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Older People ◽  
Clinical Decision Making ◽  
Late Life ◽  
Clinical Decision ◽  
Late Life Depression ◽  
Base Rates ◽  
Healthy Control

Late-Life Depression (LLD) is often associated with cognitive impairment. However, distinction between cognitive impairment due to LLD and those due to normal aging or mild Alzheimer's Disease (AD) remain difficult. The aim of this study was to present and compare the multivariate base rates of low scores in LLD, mild AD, and healthy control groups on a battery of neuropsychological tests. Participants (ages 60–89) were 352 older healthy adults, 390 patients with LLD, and 234 patients with mild AD (i.e., MMSE ≥ 20). Multivariate base rates of low scores (i.e., ≤ 5th percentile) were calculated for each participant group within different cognitive domains (verbal episodic memory, executive skills, mental processing speed, constructional praxis, and language/semantic memory). Obtaining at least one low score was relatively common in healthy older people controls (from 9.4 to 17.6%), and may thus result in a large number of false positives. By contrast, having at least two low scores was unusual (from 0.3 to 4.6%) and seems to be a more reliable criterion for identifying cognitive impairment in LLD. Having at least three low memory scores was poorly associated with LLD (5.9%) compared to mild AD (76.1%) and may provide a useful way to differentiate between these two conditions [χ(1)2 = 329.8, p < 0.001; Odds Ratio = 50.7, 95% CI = 38.2–77.5]. The multivariate base rate information about low scores in healthy older people and mild AD may help clinicians to identify cognitive impairments in LLD patients, improve the clinical decision-making, and target those who require regular cognitive and clinical follow-up.

The utility of regression-based norms in interpreting the minimal assessment of cognitive function in multiple sclerosis (MACFIMS)

2009 ◽  
Vol 16 (1) ◽  
pp. 6-16 ◽  
Author(s):  
BRETT A. PARMENTER ◽  
S. MARC TESTA ◽  
DAVID J. SCHRETLEN ◽  
BIANCA WEINSTOCK-GUTTMAN ◽  
RALPH H. B. BENEDICT
Keyword(s):  
Multiple Sclerosis ◽  
Cognitive Function ◽  
Sex Education ◽  
Reliability And Validity ◽  
Demographic Variables ◽  
Clinical Settings ◽  
Regression Analyses ◽  
Neuropsychological Battery ◽  
Data Set ◽  
Unique Data

AbstractThe Minimal Assessment of Cognitive Function in Multiple Sclerosis (MACFIMS) is a consensus neuropsychological battery with established reliability and validity. One of the difficulties in implementing the MACFIMS in clinical settings is the reliance on manualized norms from disparate sources. In this study, we derived regression-based norms for the MACFIMS, using a unique data set to control for standard demographic variables (i.e., age, age2, sex, education). Multiple sclerosis (MS) patients (n = 395) and healthy volunteers (n = 100) did not differ in age, level of education, sex, or race. Multiple regression analyses were conducted on the performance of the healthy adults, and the resulting models were used to predict MS performance on the MACFIMS battery. This regression-based approach identified higher rates of impairment than manualized norms for many of the MACFIMS measures. These findings suggest that there are advantages to developing new norms from a single sample using the regression-based approach. We conclude that the regression-based norms presented here provide a valid alternative to identifying cognitive impairment as measured by the MACFIMS. (JINS, 2010, 16, 6–16.)

Corticosteroids and Multiple Sclerosis: To Treat or Not to Treat?

2005 ◽  
Vol 138 (6) ◽  
pp. 1-13 ◽  
Author(s):  
Mike Namaka ◽  
Carol St-Laurent ◽  
Raelene Vandenbosch ◽  
Ranbir Gill ◽  
Dana Ruhlen ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Prevalence Rate ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Decision Making Process ◽  
High Dose ◽  
High Prevalence Rate ◽  
Autoimmune Pathology ◽  
High Prevalence ◽  
The Central Nervous System

Although a rare disease, multiple sclerosis (MS) has a high prevalence rate in Canada and affects many Canadians and their families. An autoimmune disease of the central nervous system, it results in the destruction of the myelin sheath that surrounds the nerve axons. High-dose IV steroid therapy is often used to treat an acute exacerbation in MS. Steroids have immunosuppressant effects that work to decrease the autoimmune pathology component of the disease and to reduce the inflammation around the nerve axon, thereby promoting closer contact of the damaged myelin and subsequently partially restoring adequate electrical nerve conduction to reduce symptoms. The high prevalence rate of MS in Canada makes it vital for pharmacists to become more aware of the different aspects of the disease and how these relate to therapy. The pharmacist should be aware of the adverse effects and impact of high-dose IV steroids in MS patients. The purpose of this review is threefold: 1) to provide a better understanding of MS pathology; 2) to contribute a systematic review of steroids; and 3) to assist in the clinical decision-making process and in the counselling requirements for patients on high-dose steroids.

Clinical Decision-Making in the Management of Multiple Sclerosis

2019 ◽  
pp. 159-177
Author(s):  
Syed A. Rizvi ◽  
Joshua A. Stone ◽  
Saima T. Chaudhry ◽  
Nichola Haddad ◽  
Brian Wong ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Decision Making ◽  
Clinical Decision Making ◽  
Clinical Decision

scholarly journals The role of natalizumab in the treatment of multiple sclerosis: benefits and risks

2017 ◽  
Vol 10 (9) ◽  
pp. 327-336 ◽  
Author(s):  
Barry A. Singer
Keyword(s):  
Multiple Sclerosis ◽  
Clinical Decision Making ◽  
Opportunistic Infections ◽  
Clinical Decision ◽  
Phase Iii ◽  
Effective Option ◽  
Natalizumab Treatment ◽  
The Central Nervous System ◽  
Infusion Reactions ◽  
Post Hoc

Natalizumab, a monoclonal antibody that blocks lymphocyte infiltration in the central nervous system, is a valuable tool in the treatment of relapsing forms of multiple sclerosis (MS). In a phase III clinical trial comparing natalizumab with placebo over 2 years, natalizumab reduced annualized relapse rate by 68%, 12-week confirmed disability progression by 42%, and reduced contrast-enhancing lesions by 92%. In post hoc analyses, natalizumab treatment was associated with 37% of patients achieving no evidence of disease activity ( versus 7% on placebo) and 30% achieving sustained disability improvement ( versus 19% on placebo). Natalizumab did not achieve a statistically significant primary composite disability outcome in a trial of 887 patients with secondary progressive MS, but it did demonstrate a benefit on a prespecified component of the 9-Hole Peg Test. The greatest risk of natalizumab treatment is progressive multifocal leukoencephalopathy (PML), with a 23% mortality rate. Risk stratification on the basis of immunosuppressant exposure, natalizumab treatment duration and anti-John Cunningham virus (JCV) antibody status and index has greatly improved clinical decision making. Other potential serious natalizumab-associated risks reported in clinical trials and postmarketing settings include infusion reactions, hepatotoxicity and rare, serious opportunistic infections. With more than a decade of continuous postmarketing experience, natalizumab remains a very effective option for patients with relapsing forms of MS. To optimize appropriate selection of natalizumab for patients with relapsing MS, however, a thorough understanding of individual patient risk factors for PML or other adverse events is also required.

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