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Record W2464491214 · doi:10.1093/brain/aww173

Defining secondary progressive multiple sclerosis

2016· article· en· W2464491214 on OpenAlexaff
Johannes Lorscheider, Katherine Buzzard, Vilija Jokubaitis, Tim Spelman, Eva Havrdová, Dana Horáková, María Trojano, Guillermo Izquierdo, Marc Girard, Pierre Duquette, Alexandre Prat, Alessandra Lugaresi, François Grand’Maison, Pierre Grammond, Raymond Hupperts, Raed Alroughani, Patrizia Sola, Cavit Boz, Eugenio Pucci, Jeannette Lechner‐Scott, Roberto Bergamaschi, Celia Oreja‐Guevara, Gerardo Iuliano, Vincent Van Pesch, Franco Granella, Cristina Ramo‐Tello, Daniele Spitaleri, Thor Petersen, Mark Slee, Freek Verheul, Radek Ampapa, Maria Pia Amato, Pamela McCombe, Steve Vucic, José Luis Sánchez-Menoyo, Edgardo Cristiano, Michael Barnett, Suzanne Hodgkinson, Javier Olascoaga, Maria Luisa Saladino, Orla Gray, Cameron Shaw, Fraser Moore, Helmut Butzkueven, Tomáš Kalinčík

Bibliographic record

VenueBrain · 2016
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsJewish General HospitalCégep de LévisHôpital Charles-Le MoyneHôpital Notre-Dame
FundersBiogenSanofi
KeywordsMultiple sclerosisExpanded Disability Status ScaleMedicineConfidence intervalPhysical therapyPediatricsCohortCohort studyPhysical medicine and rehabilitationInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

A number of studies have been conducted with the onset of secondary progressive multiple sclerosis as an inclusion criterion or an outcome of interest. However, a standardized objective definition of secondary progressive multiple sclerosis has been lacking. The aim of this work was to evaluate the accuracy and feasibility of an objective definition for secondary progressive multiple sclerosis, to enable comparability of future research studies. Using MSBase, a large, prospectively acquired, global cohort study, we analysed the accuracy of 576 data-derived onset definitions for secondary progressive multiple sclerosis and first compared these to a consensus opinion of three neurologists. All definitions were then evaluated against 5-year disease outcomes post-assignment of secondary progressive multiple sclerosis: sustained disability, subsequent sustained progression, positive disability trajectory, and accumulation of severe disability. The five best performing definitions were further investigated for their timeliness and overall disability burden. A total of 17 356 patients were analysed. The best definition included a 3-strata progression magnitude in the absence of a relapse, confirmed after 3 months within the leading Functional System and required an Expanded Disability Status Scale step ≥4 and pyramidal score ≥2. It reached an accuracy of 87% compared to the consensus diagnosis. Seventy-eight per cent of the identified patients showed a positive disability trajectory and 70% reached significant disability after 5 years. The time until half of all patients were diagnosed was 32.6 years (95% confidence interval 32-33.6) after disease onset compared with the physicians' diagnosis at 36 (35-39) years. The identified patients experienced a greater disease burden [median annualized area under the disability-time curve 4.7 (quartiles 3.6, 6.0)] versus non-progressive patients [1.8 (1.2, 1.9)]. This objective definition of secondary progressive multiple sclerosis based on the Expanded Disability Status Scale and information about preceding relapses provides a tool for a reproducible, accurate and timely diagnosis that requires a very short confirmation period. If applied broadly, the definition has the potential to strengthen the design and improve comparability of clinical trials and observational studies in secondary progressive multiple sclerosis.

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)0.016
metaresearch head score (Gemma)0.034
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.087

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.034
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.002
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.060
GPT teacher head0.312
Teacher spread0.252 · 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 designTheoretical or conceptual
Domainnot available
GenreMethods

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

Citations416
Published2016
Admission routes1
Has abstractyes

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