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Record W6987758412

Treatment selection and experience in multiple sclerosis: survey of neurologists

2014· article· en· W6987758412 on OpenAlexaboutno aff

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2014
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsFingolimodGlatiramer acetateMultiple sclerosisMedical prescriptionNatalizumabAlternative medicineNeurologyGeneral practice
DOInot available

Abstract

fetched live from OpenAlex

Kristin A Hanson,1 Neetu Agashivala,2 Kathleen W Wyrwich,3 Karina Raimundo,2 Edward Kim,2 David W Brandes4 1UBC: An Express Scripts Company, Dorval, QC, Canada; 2Novartis Pharmaceuticals Corporation, East Hanover, NJ, USA; 3Evidera, Bethesda, MD, USA; 4Hope MS Center, Knoxville, TN, USA Background: Multiple sclerosis (MS) is a complex disease with many therapeutic options. Little is known about how neurologists select particular disease-modifying therapies (DMTs) for their patients. Objective: To understand how neurologists make decisions regarding the prescription of DMTs for patients with MS, and to explore neurologists' experiences with individual DMTs. Methods: From December 2012 to January 2013, members of a nationwide physician market research panel were sent an online study invitation with a link to a survey website. Eligible neurologists were included if they currently practice medicine in the United States, and if they treat ≥20 patients with MS. Results: A total of 102 neurologists (n=63 general neurologists; n=39 MS specialists; 81.4% male) completed the survey. The mean (standard deviation) number of years in practice since completing medical training was 16.4 (8.6) years. Overall, the most commonly prescribed DMTs were subcutaneous interferon (IFN) β -1a and glatiramer acetate; approximately 5.5% of patients were untreated. The most important attributes of DMT medication selection were (in order of importance) efficacy, safety, tolerability, patient preference, and convenience. The DMT with the highest neurologist-reported percentage of patients who were “Very/Extremely Satisfied” with their therapy was fingolimod (31.0%), followed by glatiramer acetate (13.9%; P=0.017). Compared with fingolimod (94.0%), significantly fewer (P<0.05) neurologists reported that “All/Most” of their patients were adherent to treatment with glatiramer acetate (78.0%), subcutaneous IFN ß-1a (84.0%), and IFN β-1b (75.0%); no significant differences were observed with intramuscular IFN β -1a (92.9%; P=0.75). Patients’ calls to neurologists’ offices were most commonly related to side effects for all self-injectable DMTs, whereas calls about fingolimod primarily involved insurance coverage issues. Conclusion: Our survey results showed that very few patients with MS did not received any DMT. Among the DMTs available at the time of the survey, neurologists reported that patients were most satisfied with, and adherent to, fingolimod, but these patients also faced more problems with insurance coverage when compared with those taking self-injectable DMTs. Keywords: multiple sclerosis, disease-modifying therapy, physician survey, treatment selection, treatment adherence, treatment satisfaction

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.582
GPT teacher head0.577
Teacher spread0.005 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2014
Admission routes1
Has abstractyes

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