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OA39 Development of a Childhood Lupus Low Disease Activity State definition: recommendations from the International Childhood Lupus Treat-to-Target Task Force

2023· article· en· W4366832222 on OpenAlexaff
Eve Smith, Amita Aggarwal, Jenny Ainsworth, Eslam Al‐Abadi, Tadej Avčin, Lynette Bortey, Jon M. Burnham, Coziana Ciurtin, Christian M. Hedrich, Sylvia Kamphuis, Deborah M. Levy, Laura B. Lewandowski, Naomi Maxwell, Eric F. Morand, Seza Özen, Clare Pain, Angelo Ravelli, Cláudia Saad Magalhães, Clarissa Pilkington, D. Schonenberg, Christiaan Scott, Kjell Tullus, Michael W. Beresford

Bibliographic record

VenueLara D. Veeken · 2023
Typearticle
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsMedicineSystemic lupus erythematosusRheumatologySystemic lupusTask forceTask (project management)Delphi methodDiseasePhysical therapyInternal medicineArtificial intelligenceComputer scienceManagement

Abstract

fetched live from OpenAlex

Abstract Background/Aims International interest in development of treat-to-target (T2T) in both childhood-onset systemic lupus erythematosus (cSLE) and adult-onset SLE (aSLE) is increasing. T2T could facilitate more effective and structured use of treatments, aggressively controlling disease activity, preventing organ damage, and improving health-related quality of life. The first step is the selection of an appropriate target. Remission is deemed the ultimate target, but may not be attainable by all. Low disease activity (LDA), based on the principle of “tolerable” disease activity on stable treatment, with low corticosteroid dosage, may be more appropriate for some patients. The aim of this study was to derive a consensus-based cSLE appropriate definition of LDA, building upon existing aSLE definitions to improve applicability to cSLE, whilst maintaining sufficient unity to ensure that future T2T studies including adolescents and adults together are possible. Methods The International cSLE T2T Task Force, including 18 specialists from paediatric rheumatology/nephrology, and adult rheumatology undertook a series of Delphi surveys, exploring views on aSLE LDA targets. Two virtual consensus meetings were held, utilising a modified nominal group technique to debate, modify, and vote upon topics underpinning the cSLE LDA target and its criteria. Agreement of > 80% was considered consensus. Results The task force agreed that the LDA target should encompass cSLE as a whole and be based upon the aSLE Lupus Low Disease Activity State definition (LLDAS), with modifications to make it more applicable to cSLE (cLLDAS, all 100% agreement). A conceptual definition of cLLDAS was defined: ‘A state, which if sustained, is associated with a low likelihood of adverse outcome (considering disease activity, damage, and medication toxicity)’ (100% agreement). Five cLLDAS criteria were agreed, as detailed within Table 1. The final cLLDAS definition was endorsed by the Paediatric Rheumatology European Society (PReS) Executive Council and PReS cSLE Working Party Chair, on behalf of the Society. Conclusion A cSLE, age-appropriate definition of cLLDAS has been generated, preserving sufficient unity with the aSLE LLDAS definition to encourage life-course research. The development and validation of targets has been a key enabler for T2T trials, therefore this initiative represents a significant step forward for cSLE. Disclosure E.M.D. Smith: None. A. Aggarwal: None. J. Ainsworth: None. E. Al-Abadi: None. T. Avcin: None. L. Bortey: None. J. Burnham: None. C. Ciurtin: None. C.M. Hedrich: None. S. Kamphuis: None. D. Levy: None. L. Lewandowski: None. N. Maxwell: None. E. Morand: None. S. Ozen: None. C. Pain: None. A. Ravelli: None. C. Saad Magalhaes: None. C. Pilkington: None. D. Schonenberg: None. C. Scott: None. K. Tullus: None. M.W. Beresford: None.

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)0.174
metaresearch head score (Gemma)0.135
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 score0.174
Threshold uncertainty score0.920

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1740.135
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.008
Bibliometrics0.0100.008
Science and technology studies0.0040.004
Scholarly communication0.0080.005
Open science0.0100.009
Research integrity0.0080.012
Insufficient payload (model declined to judge)0.0050.004

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 head0.027
GPT teacher head0.288
Teacher spread0.261 · 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".

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Citations0
Published2023
Admission routes1
Has abstractyes

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