A Novel, Integrative Approach for Evaluating Progression in Multiple Sclerosis: Development of a Scoring Algorithm.

SPMS algorithm disease progression multiple sclerosis, relapsing-remitting tool

Journal

JMIR medical informatics
ISSN: 2291-9694
Titre abrégé: JMIR Med Inform
Pays: Canada
ID NLM: 101645109

Informations de publication

Date de publication:
14 Apr 2020
Historique:
received: 23 12 2019
accepted: 22 02 2020
revised: 14 02 2020
entrez: 15 4 2020
pubmed: 15 4 2020
medline: 15 4 2020
Statut: epublish

Résumé

There is an unmet need for a tool that helps to evaluate patients who are at risk of progressing from relapsing-remitting multiple sclerosis to secondary progressive multiple sclerosis (SPMS). A new tool supporting the evaluation of early signs suggestive of progression in multiple sclerosis (MS) has been developed. In the initial stage, concepts relevant to progression were identified using a mixed method approach involving regression on data from a real-world observational study and qualitative research with patients and physicians. The tool was drafted in a questionnaire format to assess these variables. This study aimed to develop the scoring algorithm for the tool, using both quantitative and qualitative research methods. The draft scoring algorithm was developed using two approaches: quantitative analysis of real-world data and qualitative analysis based on physician interviews and ranking and weighting exercises. Variables that were included in the draft tool and regarded as most clinically relevant were selected for inclusion in a multiple logistic regression. The analyses were run using physician-reported data and patient-reported data. Subsequently, a ranking and weighting exercise was conducted with 8 experienced neurologists as part of semistructured interviews. Physicians were presented with the variables included in the draft tool and were asked to rank them in order of strength of contribution to progression and assign a weight by providing a percentage of the overall contribution. Physicians were also asked to explain their ranking and weighting choices. Concordance between physicians was explored. Multiple logistic regression identified age, MS disease activity, and Expanded Disability Status Scale score as the most significant physician-reported predictors of progression to SPMS. Patient age, mobility, and self-care were identified as the strongest patient-reported predictors of progression to SPMS. In physician interviews, the variables ranked and weighted as most important were stability or worsening of symptoms, intermittent or persistent symptoms, and presence of ambulatory and cognitive symptoms. Across all physicians, the level of concordance was 0.278 (P<.001), indicating a low to moderate, but statistically significant, level of agreement. Variables were categorized as high (n=8), moderate (n=8), or low (n=10) importance based on the findings from the different approaches described above. Accordingly, the respective questions in the tool were assigned a weight of "three," "two," or "one" to inform the draft scoring algorithm. This study further confirms the need for a tool to provide a consistent, comprehensive approach across physicians to support the early evaluation of signs indicative of progression to SPMS. The novel and comprehensive approach to develop the draft scoring algorithm triangulates data obtained from ranking and weighting exercises, qualitative interviews, and a real-world observational study. Variables that go beyond the clinically most obvious impairment in lower limbs have been identified as relevant subtle/sensitive signs suggestive of progressive disease.

Sections du résumé

BACKGROUND BACKGROUND
There is an unmet need for a tool that helps to evaluate patients who are at risk of progressing from relapsing-remitting multiple sclerosis to secondary progressive multiple sclerosis (SPMS). A new tool supporting the evaluation of early signs suggestive of progression in multiple sclerosis (MS) has been developed. In the initial stage, concepts relevant to progression were identified using a mixed method approach involving regression on data from a real-world observational study and qualitative research with patients and physicians. The tool was drafted in a questionnaire format to assess these variables.
OBJECTIVE OBJECTIVE
This study aimed to develop the scoring algorithm for the tool, using both quantitative and qualitative research methods.
METHODS METHODS
The draft scoring algorithm was developed using two approaches: quantitative analysis of real-world data and qualitative analysis based on physician interviews and ranking and weighting exercises. Variables that were included in the draft tool and regarded as most clinically relevant were selected for inclusion in a multiple logistic regression. The analyses were run using physician-reported data and patient-reported data. Subsequently, a ranking and weighting exercise was conducted with 8 experienced neurologists as part of semistructured interviews. Physicians were presented with the variables included in the draft tool and were asked to rank them in order of strength of contribution to progression and assign a weight by providing a percentage of the overall contribution. Physicians were also asked to explain their ranking and weighting choices. Concordance between physicians was explored.
RESULTS RESULTS
Multiple logistic regression identified age, MS disease activity, and Expanded Disability Status Scale score as the most significant physician-reported predictors of progression to SPMS. Patient age, mobility, and self-care were identified as the strongest patient-reported predictors of progression to SPMS. In physician interviews, the variables ranked and weighted as most important were stability or worsening of symptoms, intermittent or persistent symptoms, and presence of ambulatory and cognitive symptoms. Across all physicians, the level of concordance was 0.278 (P<.001), indicating a low to moderate, but statistically significant, level of agreement. Variables were categorized as high (n=8), moderate (n=8), or low (n=10) importance based on the findings from the different approaches described above. Accordingly, the respective questions in the tool were assigned a weight of "three," "two," or "one" to inform the draft scoring algorithm.
CONCLUSIONS CONCLUSIONS
This study further confirms the need for a tool to provide a consistent, comprehensive approach across physicians to support the early evaluation of signs indicative of progression to SPMS. The novel and comprehensive approach to develop the draft scoring algorithm triangulates data obtained from ranking and weighting exercises, qualitative interviews, and a real-world observational study. Variables that go beyond the clinically most obvious impairment in lower limbs have been identified as relevant subtle/sensitive signs suggestive of progressive disease.

Identifiants

pubmed: 32286236
pii: v8i4e17592
doi: 10.2196/17592
pmc: PMC7189255
doi:

Types de publication

Journal Article

Langues

eng

Pagination

e17592

Informations de copyright

©Chloe Tolley, Daniela Piani-Meier, Sarah Bentley, Bryan Bennett, Eddie Jones, James Pike, Frank Dahlke, Davorka Tomic, Tjalf Ziemssen. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 14.04.2020.

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Auteurs

Chloe Tolley (C)

Adelphi Values Ltd, Macclesfield, United Kingdom.

Daniela Piani-Meier (D)

Novartis Pharma AG, Basel, Switzerland.

Sarah Bentley (S)

Adelphi Values Ltd, Macclesfield, United Kingdom.

Bryan Bennett (B)

Adelphi Values Ltd, Macclesfield, United Kingdom.

Eddie Jones (E)

Adelphi Real World Ltd, Macclesfield, United Kingdom.

James Pike (J)

Adelphi Real World Ltd, Macclesfield, United Kingdom.

Frank Dahlke (F)

Novartis Pharma AG, Basel, Switzerland.

Davorka Tomic (D)

Novartis Pharma AG, Basel, Switzerland.

Tjalf Ziemssen (T)

Center of Clinical Neuroscience, Neurological University Clinic Carl Gustav Carus, TU Dresden, Dresden, Germany.

Classifications MeSH