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Record W4280600583 · doi:10.1111/ene.15406

Confirmed disability progression as a marker of permanent disability in multiple sclerosis

2022· article· en· W4280600583 on OpenAlexaff
Sifat Sharmin, Francesca Bovis, Charles B. Malpas, Dana Horáková, Eva Havrdová, Guillermo Izquierdo, Sara Eichau, María Trojano, Alexandre Prat, Marc Girard, Pierre Duquette, Marco Onofrj, Alessandra Lugaresi, François Grand’Maison, Pierre Grammond, Patrizia Sola, Diana Ferraro, Murat Terzi, Oliver Gerlach, Raed Alroughani, Cavit Boz, Vahid Shaygannejad, Vincent Van Pesch, Elisabetta Cartechini, Ludwig Kappos, Jeannette Lechner‐Scott, Roberto Bergamaschi, Recai Türkoğlu, Claudio Solaro, Gerardo Iuliano, Franco Granella, Bart Van Wijmeersch, Daniele Spitaleri, Mark Slee, Pamela McCombe, Julie Prévost, Radek Ampapa, Serkan Özakbaş, José Luis Sánchez-Menoyo, Aysun Soysal, Steve Vucic, Thor Petersen, Koen de Gans, Ernest Butler, Suzanne Hodgkinson, Youssef Sidhom, Riadh Gouider, Edgardo Cristiano, Tamara Castillo‐Triviño, Maria Luisa Saladino, Michael Barnett, Fraser Moore, Csilla Rózsa, Bassem Yamout, Olga Skibina, Anneke van der Walt, Katherine Buzzard, Orla Gray, Stella Hughes, Ángel Pérez Sempere, Bhim Singhal, Yára Dadalti Fragoso, Cameron Shaw, Allan G. Kermode, Bruce Taylor, Magdolna Simó, Neil Shuey, Talal Al‐Harbi, Richard Macdonell, José Andrés Domínguez, Tünde Csépány, Carmen Adella Sîrbu, Maria Pia Sormani, Helmut Butzkueven, Tomáš Kalinčík

Bibliographic record

VenueEuropean Journal of Neurology · 2022
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsJewish General HospitalCegep de Saint JeromeCentre Hospitalier de l’Université de MontréalCentre intégré de santé et de services sociaux de Chaudière-AppalachesGreenfield Research (Canada)Université de MontréalHôpital Notre-Dame
FundersNational Health and Medical Research CouncilBiogenUniversity of MelbourneTeva Pharmaceutical IndustriesSanofi GenzymeUniversity of TasmaniaSanofi
KeywordsMedicineMultiple sclerosisPhysical medicine and rehabilitationPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND AND PURPOSE: The prevention of disability over the long term is the main treatment goal in multiple sclerosis (MS); however, randomized clinical trials evaluate only short-term treatment effects on disability. This study aimed to define criteria for 6-month confirmed disability progression events of MS with a high probability of resulting in sustained long-term disability worsening. METHODS: In total, 14,802 6-month confirmed disability progression events were identified in 8741 patients from the global MSBase registry. For each 6-month confirmed progression event (13,321 in the development and 1481 in the validation cohort), a sustained progression score was calculated based on the demographic and clinical characteristics at the time of progression that were predictive of long-term disability worsening. The score was externally validated in the Cladribine Tablets Treating Multiple Sclerosis Orally (CLARITY) trial. RESULTS: The score was based on age, sex, MS phenotype, relapse activity, disability score and its change from baseline, number of affected functional system domains and worsening in six of the domains. In the internal validation cohort, a 61% lower chance of improvement was estimated with each unit increase in the score (hazard ratio 0.39, 95% confidence interval 0.29-0.52; discriminatory index 0.89). The proportions of progression events sustained at 5 years stratified by the score were 1: 72%; 2: 88%; 3: 94%; 4: 100%. The results of the CLARITY trial were confirmed for reduction of disability progression that was >88% likely to be sustained (events with score ˃1.5). CONCLUSIONS: Clinicodemographic characteristics of 6-month confirmed disability progression events identify those at high risk of sustained long-term disability. This knowledge will allow future trials to better assess the effect of therapy on long-term disability accrual.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.054
Threshold uncertainty score0.650

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.083
GPT teacher head0.327
Teacher spread0.244 · 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 teacher head, 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

Citations15
Published2022
Admission routes1
Has abstractyes

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