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Record W4310523139 · doi:10.3899/jrheum.220459

One-Third of European Patients With Axial Spondyloarthritis Reach Pain Remission With Routine Care Tumor Necrosis Factor Inhibitor Treatment

2022· article· en· W4310523139 on OpenAlexvenueno aff
Lykke Midtbøll Ørnbjerg, Kathrine Rugbjerg, Stylianos Georgiadis, Simon Horskjær Rasmussen, Ulf Lindström, Karel Pavelká, Neslihan Yılmaz, Ennio Giulio Favalli, Michael J. Nissen, Brigitte Michelsen, Elsa Vieira‐Sousa, Gareth T. Jones, Ruxandra Ionescu, Heikki Relas, Carlos Sánchez‐Piedra, Matija Tomšič, Árni Jón Geirsson, Irene van der Horst‐Bruinsma, Johan Askling, Anne Gitte Loft, Lucie Nekvindová, Haner Di̇reskeneli̇, Florenzo Iannone, Adrian Ciurea, K. M. Fagerli, María José Santos, Gary J. Macfarlane, Cătălin Codreanu, Kari K. Eklund, Manuel Pombo‐Suárez, Žiga Rotar, Björn Guðbjörnsson, Tamara Rusman, Mikkel Østergaard, Merete Lund Hetland

Bibliographic record

VenueThe Journal of Rheumatology · 2022
Typearticle
Languageen
FieldMedicine
TopicSpondyloarthritis Studies and Treatments
Canadian institutionsnot available
FundersNovartis PharmaCelgeneBiogenAmgenPfizerEli Lilly and Company
KeywordsMedicineAxial spondyloarthritisTumor necrosis factor αTumor necrosis factor alphaInternal medicineAnkylosing spondylitisSurgeryPhysical therapy

Abstract

fetched live from OpenAlex

OBJECTIVE: To investigate the distribution of patient-reported outcomes (PROs) in patients with axial spondyloarthritis (axSpA) initiating a tumor necrosis factor inhibitor (TNFi), to assess the proportion reaching PRO "remission" across registries and treatment series, and to compare patients registered to fulfill the modified New York (mNY) criteria for ankylosing spondylitis (AS) vs patients with nonradiographic axSpA (nr-axSpA). METHODS: Fifteen European registries contributed PRO scores for pain, fatigue, patient global assessment (PtGA), Bath Ankylosing Spondylitis (AS) Disease Activity Index (BASDAI), Bath AS Functional Index (BASFI), and Health Assessment Questionnaire (HAQ) from 19,498 patients with axSpA. Changes in PROs and PRO remission rates (definitions: ≤ 20 mm for pain, fatigue, PtGA, BASDAI, and BASFI; ≤ 0.5 for HAQ) were calculated at 6, 12, and 24 months of treatment. RESULTS: Heterogeneity in baseline characteristics and outcomes between registries were observed. In pooled data, 6 months after the start of a first TNFi, pain score was reduced by approximately 60% (median at baseline/6/12/24 months: 65/25/20/20 mm) in patients on treatment. Similar patterns were observed for fatigue (68/32/30/25 mm), PtGA (66/29/21/20 mm), BASDAI (58/26/21/19 mm), BASFI (46/20/16/16 mm), and HAQ (0.8/0.4/0.2/0.2). Patients with AS (n = 3281) had a slightly better response than patients with nr-axSpA (n = 993). The Lund Efficacy Index (LUNDEX)-adjusted remission rates at 6 months for pain/fatigue/PtGA/BASDAI/BASFI/HAQ were 39%/30%/38%/34%/35%/48% for the AS cohort and 30%/21%/26%/24%/33%/47% for the nr-axSpA cohort. Better PRO responses were seen with a first TNFi compared to a second and third TNFi. CONCLUSION: Patients with axSpA starting a TNFi achieved high PRO remission rates, most pronounced in those fulfilling the mNY criteria and for the first TNFi.

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)0.003
metaresearch head score (Gemma)0.006
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 score0.003
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.010
GPT teacher head0.220
Teacher spread0.210 · 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

Citations11
Published2022
Admission routes1
Has abstractyes

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