Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ASCO Annual Meeting 2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress
Clinical Collections
Advances in Alzheimer’s

2024 ASCO Annual Meeting

Keep up to date with all the top stories and latest evidence with our hub page, including official congress videos and expert takeaways.
ADVANCED SEARCH
Log in
Top
BMC Neurology
Published in: BMC Neurology 1/2024

Open Access 01-12-2024 | Multiple Sclerosis | Study Protocol

Don’t be late! Timely identification of cognitive impairment in people with multiple sclerosis: a study protocol

Authors: Pauline T. Waskowiak, Brigit A. de Jong, Bernard M. J. Uitdehaag, Shalina R. D. Saddal, Jip Aarts, Aïda A. M. Roovers, Pim van Oirschot, Vincent de Groot, Frederieke G. Schaafsma, Karin van der Hiele, Marit F. L. Ruitenberg, Menno M. Schoonheim, Guy A. M. Widdershoven, Sabina van der Veen, Esther C. F. Schippers, Martin Klein, Hanneke E. Hulst, Don’t be late! Consortium

Published in: BMC Neurology | Issue 1/2024

Login to get access

Abstract

Background

Cognitive impairment occurs in up to 65% of people with multiple sclerosis (PwMS), negatively affecting daily functioning and health-related quality of life. In general, neuropsychological testing is not part of standard MS-care due to insufficient time and trained personnel. Consequently, a baseline assessment of cognitive functioning is often lacking, hampering early identification of cognitive decline and change within a person over time. To assess cognitive functioning in PwMS in a time-efficient manner, a BICAMS-based self-explanatory digital screening tool called the Multiple Screener©, has recently been developed. The aim of the current study is to validate the Multiple Screener© in a representative sample of PwMS in the Netherlands. Additionally, we aim to investigate how cognitive functioning is related to psychological factors, and both work and societal participation.

Methods

In this cross-sectional multicentre study, 750 PwMS (aged 18–67 years) are included. To obtain a representative sample, PwMS are recruited via 12 hospitals across the Netherlands. They undergo assessment with the Minimal Assessment of Cognitive Functioning in MS (MACFIMS; reference-standard) and the Multiple Screener©. Sensitivity, specificity, and predictive values for identifying (mild) cognitive impairment are determined in a subset of 300 participants. In a second step, the identified cut-off values are tested in an independent subset of at least 150 PwMS. Moreover, test–retest reliability for the Multiple Screener© is determined in 30 PwMS. Information on psychological and work-related factors is assessed with questionnaires.

Discussion

Validating the Multiple Screener© in PwMS and investigating cognition and its determinants will further facilitate early identification and adequate monitoring of cognitive decline in PwMS.
Literature
1.
Katz Sand I. Classification, diagnosis, and differential diagnosis of multiple sclerosis. Curr Opin Neurol. 2015;28(3):193–205.PubMedCrossRef
2.
Campbell J, Rashid W, Cercignani M, Langdon D. Cognitive impairment among patients with multiple sclerosis: associations with employment and quality of life. Postgrad Med J. 2017;93(1097):143–7.PubMedCrossRef
3.
4.
Eijlers AJC, et al. Predicting cognitive decline in multiple sclerosis: a 5-year follow-up study. Brain. 2018;141(9):2605–18.PubMed
5.
Wojcik C, et al. Staging and stratifying cognitive dysfunction in multiple sclerosis. Mult Scler. 2022;28(3):463–71.PubMedCrossRef
6.
Benedict RH, et al. Negative work events and accommodations in employed multiple sclerosis patients. Mult Scler. 2014;20(1):116–9.PubMedCrossRef
7.
Kordovski VM, et al. Identifying employed multiple sclerosis patients at-risk for job loss: when do negative work events pose a threat? Mult Scler Relat Disord. 2015;4(5):409–13.PubMedCrossRef
8.
van der Hiele K, et al. Work participation and executive abilities in patients with relapsing-remitting multiple sclerosis. PLoS ONE. 2015;10(6):e0129228.PubMedPubMedCentralCrossRef
9.
van Gorp DAM, et al. Cognitive functioning as a predictor of employment status in relapsing-remitting multiple sclerosis: a 2-year longitudinal study. Neurol Sci. 2019;40(12):2555–64.PubMedPubMedCentralCrossRef
10.
Global MS Employment Report 2016. 2016, MS International Federation: msif.org.
11.
Uitdehaag B, et al. New insights into the burden and costs of multiple sclerosis in Europe: results for the Netherlands. Multiple Sclerosis J. 2017;23(2_suppl):117–29.CrossRef
12.
Meide HVD, Gorp DV, Van Der Hiele K, Visser L. “Always looking for a new balance”: toward an understanding of what it takes to continue working while being diagnosed with relapsing-remitting multiple sclerosis. Disabil Rehabil. 2018;40(21):2545–52.PubMedCrossRef
13.
14.
Prouskas SE, et al. A randomized trial predicting response to cognitive rehabilitation in multiple sclerosis: Is there a window of opportunity? Mult Scler. 2022:13524585221103134.
15.
Fuchs TA, et al. Response heterogeneity to home-based restorative cognitive rehabilitation in multiple sclerosis: an exploratory study. Mult Scler Relat Disord. 2019;34:103–11.PubMedCrossRef
16.
Fuchs TA, et al. Functional connectivity and structural disruption in the default-mode network predicts cognitive rehabilitation outcomes in multiple sclerosis. J Neuroimaging. 2020;30(4):523–30.PubMedCrossRef
17.
Taylor LA, et al. Understanding who benefits most from cognitive rehabilitation for multiple sclerosis: a secondary data analysis. Mult Scler. 2023;29(11–12):1482–92.PubMedPubMedCentralCrossRef
18.
19.
Klein OA, das Nair R, Ablewhite J, Drummond A. Assessment and management of cognitive problems in people with multiple sclerosis: a National Survey of Clinical Practice. Int J Clin Pract. 2018:e13300.
20.
van Dongen L, et al. Introducing multiple screener: an unsupervised digital screening tool for cognitive deficits in MS. Mult Scler Relat Disord. 2019;38:101479.PubMedCrossRef
21.
22.
Smith A. Symbol digit modalities test. 1973: Western Psychological Services Los Angeles.
23.
Delis D, et al. Neuropsychological assessment of learning and memory. Cortex. 1989;10(3):308–17.
24.
Woods SP, et al. The California Verbal Learning Test–second edition: Test-retest reliability, practice effects, and reliable change indices for the standard and alternate forms. Arch Clin Neuropsychol. 2006;21(5):413–20.PubMedCrossRef
25.
Mulder JL, Dekker R, Dekker PH. Verbale Leer en Geheugen Test. Lisse: Swets & Zeitlinger; 1996.
26.
Rao SM. Cognitive Function Study Group, N. A Manual for the Brief Repeatable Battery of Neuropsychological Tests in Multiple Sclerosis., N.M.S. Society, Editor. 1990: New York.
27.
Zigmond AS, Snaith RP. The hospital anxiety and depression scale. Acta Psychiatr Scand. 1983;67(6):361–70.PubMedCrossRef
28.
Kos D, et al. Assessing fatigue in multiple sclerosis: Dutch modified fatigue impact scale. Acta Neurol Belg. 2003;103(4):185–91.PubMed
29.
Benedict RH, et al. Screening for multiple sclerosis cognitive impairment using a self-administered 15-item questionnaire. Mult Scler. 2003;9(1):95–101.PubMedCrossRef
30.
Benedict RH, et al. Validity of the minimal assessment of cognitive function in multiple sclerosis (MACFIMS). J Int Neuropsychol Soc. 2006;12(4):549–58.PubMedCrossRef
31.
32.
33.
Thompson AJ, et al. Diagnosis of multiple sclerosis: 2017 revisions of the McDonald criteria. Lancet Neurol. 2018;17(2):162–73.PubMedCrossRef
34.
Kurtzke JF. Rating neurologic impairment in multiple sclerosis: an expanded disability status scale (EDSS). Neurology. 1983;33(11):1444–52.PubMedCrossRef
35.
Benedict RH, et al. Revision of the Brief visuospatial memory test: studies of normal performance, reliability, and validity. Psychol Assess. 1996;8(2):145.CrossRef
36.
Gronwall D. Paced auditory serial-addition task: a measure of recovery from concussion. Percept Mot Skills. 1977;44(2):367–73.PubMedCrossRef
37.
Benton AL, Sivan AB, Hamsher K, Varney NR, Spreen O. Contributions to Neuropsychological Assessment. 2nd ed. New York: Oxford University Press; 1994.
38.
Delis DC, Kaplan E, Kramer JH. Delis-Kaplan executive function system. 2001.
39.
Schagen S, Schmand B, de Sterke S, Lindeboom J. Amsterdam Short-Term Memory test: a new procedure for the detection of feigned memory deficits. J Clin Exp Neuropsychol. 1997;19(1):43–51.PubMedCrossRef
40.
Nauta IM et al. Performance validity in outpatients with multiple sclerosis and cognitive complaints. Mult Scler. 2021:13524585211025780.
41.
Lee GP, Loring DW, Martin RC. Rey’s 15-item visual memory test for the detection of malingering: normative observations on patients with neurological disorders. Psychol Assess. 1992;4(1):43–6.
42.
Baron-Cohen S, et al. The “Reading the Mind in the Eyes” Test revised version: a study with normal adults, and adults with Asperger syndrome or high-functioning autism. J Child Psychol Psychiatry Allied Disciplines. 2001;42(2):241–51.CrossRef
43.
Rothlind J, Dukarm P, Kraybill M. Assessment of self-awareness of cognitive function: correlations of self-ratings with actual performance ranks for tests of processing speed, memory and executive function in non-clinical samples. Arch Clin Neuropsychol. 2017;32(3):316–27.PubMed
44.
45.
Hobart J, et al. The multiple sclerosis impact scale (MSIS-29) a new patient-based outcome measure. Brain. 2001;124(5):962–73.PubMedCrossRef
46.
Soldatos CR, Dikeos DG, Paparrigopoulos TJ. Athens Insomnia Scale: validation of an instrument based on ICD-10 criteria. J Psychosom Res. 2000;48(6):555–60.PubMedCrossRef
47.
Soldatos CR, Dikeos DG, Paparrigopoulos TJ. The diagnostic validity of the Athens Insomnia Scale. J Psychosom Res. 2003;55(3):263–7.PubMedCrossRef
48.
Connor KM. Assessment of resilience in the aftermath of trauma. J Clin Psychiatry. 2006;67(Suppl 2):46–9.PubMed
49.
Pearlin LI, Schooler C. The structure of coping. J Health Soc Behav. 1978:2–21.
50.
Costa Jr PT, McCrae RR. The Revised Neo Personality Inventory (neo-pi-r). 2008: Sage Publications, Inc.
51.
Schwartz ES, et al. The NEO-FFI in multiple sclerosis: internal consistency, factorial validity, and correspondence between self and informant reports. Assessment. 2011;18(1):39–49.PubMedCrossRef
52.
Donnellan MB, Oswald FL, Baird BM, Lucas RE. The mini-IPIP scales: tiny-yet-effective measures of the Big Five factors of personality. Psychol Assess. 2006;18(2):192.PubMedCrossRef
53.
Brugha TS, Cragg D. The list of threatening experiences: the reliability and validity of a brief life events questionnaire. Acta Psychiatr Scand. 1990;82(1):77–81.PubMedCrossRef
54.
Reilly MC, Zbrozek AS, Dukes EM. The validity and reproducibility of a work productivity and activity impairment instrument. Pharmacoeconomics. 1993;4(5):353–65.PubMedCrossRef
55.
Honan CA, Brown RF, Hine DW. The multiple sclerosis work difficulties questionnaire (MSWDQ): development of a shortened scale. Disabil Rehabil. 2014;36(8):635–41.PubMedCrossRef
56.
van Egmond E et al. A Dutch validation study of the Multiple Sclerosis Work Difficulties Questionnaire in relapsing remitting multiple sclerosis. Disabil Rehabil. 2019:1–10.
57.
Benedict RH, et al. Negative work events and accommodations in employed multiple sclerosis patients. Mult Scler J. 2014;20(1):116–9.CrossRef
58.
Foley T, McKinlay A, Warren N, Stolwyk RJ. Assessing the sensitivity and specificity of cognitive screening measures for people with Parkinson’s disease. NeuroRehabilitation. 2018;43(4):491–500.
59.
Dusankova JB, Kalincik T, Havrdova E, Benedict RH. Cross cultural validation of the Minimal Assessment of Cognitive Function in Multiple Sclerosis (MACFIMS) and the Brief International Cognitive Assessment for Multiple Sclerosis (BICAMS). Clin Neuropsychol. 2012;26(7):1186–200.PubMedCrossRef
60.
Amato MP, Ponziani G, Siracusa G, Sorbi S. Cognitive dysfunction in early-onset multiple sclerosis: a reappraisal after 10 years. Arch Neurol. 2001;58(10):1602–6.PubMedCrossRef
61.
Bujang M, Adnan TH. Requirements for minimum sample size for sensitivity and specificity analysis. J Clin Diagn Res. 2016;10(10):Ye01–ye06.PubMedPubMedCentral
62.
63.
RStudio. TeamRStudio: Integrated Development for R. RStudio. Boston: PBC; 2020.
64.
Corp I. IBM SPSS Statistics for Windows, Version 28.0. Armonk: IBM Corp; 2021.
65.
Eijlers AJ, et al. Increased default-mode network centrality in cognitively impaired multiple sclerosis patients. Neurology. 2017;88(10):952–60.PubMedCrossRef
66.
Koo TK, Li MY. A Guideline of selecting and reporting intraclass correlation coefficients for reliability research. J Chiropr Med. 2016;15(2):155–63.PubMedPubMedCentralCrossRef
67.
Akoglu H. User’s guide to correlation coefficients. Turk J Emerg Med. 2018;18(3):91–3.
Metadata
Title
Don’t be late! Timely identification of cognitive impairment in people with multiple sclerosis: a study protocol
Authors
Pauline T. Waskowiak
Brigit A. de Jong
Bernard M. J. Uitdehaag
Shalina R. D. Saddal
Jip Aarts
Aïda A. M. Roovers
Pim van Oirschot
Vincent de Groot
Frederieke G. Schaafsma
Karin van der Hiele
Marit F. L. Ruitenberg
Menno M. Schoonheim
Guy A. M. Widdershoven
Sabina van der Veen
Esther C. F. Schippers
Martin Klein
Hanneke E. Hulst
Don’t be late! Consortium
Publication date
01-12-2024
Publisher
BioMed Central
Published in
BMC Neurology / Issue 1/2024
Electronic ISSN: 1471-2377
DOI
https://doi.org/10.1186/s12883-023-03495-x

Other articles of this Issue 1/2024

BMC Neurology 1/2024 Go to the issue

Research

Clinical variables influencing the perception of fatigue in people with multiple sclerosis: a cross-sectional study using FSIQ-RMS

Study Protocol

Exploring vascular contributions to cognitive impairment and dementia (ENIGMA): protocol for a prospective observational study

Research

Designing and validating of a questionnaire measuring perceived self-care ability (PSCA) in chronic stroke patients at home

Study Protocol

Sustained effort network for treatment of status epilepticus/European academy of neurology registry on adult refractory status epilepticus (SENSE-II/AROUSE)

Case Report

Aneurysmal subarachnoid hemorrhage complicating spinal subarachnoid hematoma causing acute cauda equina syndrome: a case report

Case Report

Spontaneous development of myasthenia gravis and myositis following treatment with pembrolizumab: a case report