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Record W4410715702 · doi:10.3899/jrheum.2025-0390.o034

FRAMEWORK FOR IMPLEMENTING TREAT-TO-TARGET IN SYSTEMIC LUPUS ERYTHEMATOSUS ROUTINE CLINICAL CARE: CONSENSUS STATEMENTS FROM AN INTERNATIONAL TASK FORCE.

2025· article· en· W4410715702 on OpenAlexaffvenue
Matteo Piga, Ioannis Parodis, Zahi Touma, Alexandra Legge, Manuel F. Ugarte‐Gil, Ihsane Hmamouchi, José A. Gómez‐Puerta, Hervé Devilliers, Margherita Zen, Jiacai Cho, Nelly Ziadé, Johanna Mücke, Carlos Enrique Toro Gutiérrez, Shinji Izuka, Peter Korsten, Baïdy Sy Kane, Vera Golder, Benjamin F. Chong, Guillermo Pons‐Estel, François Chasset

Bibliographic record

VenueThe Journal of Rheumatology · 2025
Typearticle
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsDalhousie UniversityToronto Western Hospital
Fundersnot available
KeywordsMedicineTask forceTask (project management)Consensus conferenceIntensive care medicineSystemic lupus erythematosusMEDLINEPhysical therapyPathologyInternal medicineDisease

Abstract

fetched live from OpenAlex

O034 / #681 Topic:AS09 - Emerging Approaches in SLE Management ABSTRACT CONCURRENT SESSION 05: EMERGING INSIGHTS ON THE MANAGEMENT OF LUPUS MANIFESTATIONS AND COMORBIDITIES 23-05-2025 1:40 PM - 2:40 PM Background/Purpose The adoption of Treat-to-Target (T2T) in routine clinical care for systemic lupus erythematosus (SLE) is limited, with evidence showing ongoing overuse of glucocorticoids (GCs) and inadequate disease control in many patients. An international task force convened to address the challenges and identify effective strategies for implementing T2T in adult SLE patients in real-life settings. Methods The T2T task force comprised a multidisciplinary panel of 22 physicians with extensive experience in SLE management and 3 lupus patient research partners. The panel’s geographical distribution included 9 (40.9%) experts from Europe, 4 (16.5%) from Asia-Pacific, 3 (13.6%) from North America, 3 (13.6%) from Latin America, and 3 (13.6%) from Africa. Through a scoping review and online discussions, the panel mapped, identified, and discussed the current limitations and best available options for implementing T2T in SLE. Drawing from these findings, the panel formulated a series of potential framework statements, which were rigorously debated and refined before reaching an agreement through a Delphi consensus process. Results The resulting framework outlines 5 overarching principles and 11 specific statements (Table). The T2T strategy should be implemented as early as possible during the disease course, favored by a shared decision-making approach and by including nonpharmacological measures and telehealth in the process. The importance of achieving remission within a prespecified timeframe is highlighted. At the same time, LLDAS is highlighted as a valuable alternative target when remission cannot be achieved or maintained. The task force suggests time intervals between visits, guided by disease activity status. If remission is not attained within the recommended timeframe, adherence to therapy should be evaluated, and treatment strategies should be optimized accordingly. At each clinical visit, prioritizing the tapering of glucocorticoids is essential, with complete discontinuation considered for patients in sustained remission, ideally by following a slow tapering protocol. Prolonged remission, defined as remission lasting 5 years or longer, opens the possibility of discontinuing immunosuppressants and/or biologics in patients who have successfully discontinued glucocorticoids. Goals, priorities, and areas of investigation for future research endeavors were identified (Figure). Table. Figure. Conclusions Although formal evidence proving the superiority of T2T to conventional SLE management is lacking, the approach has been recommended for over a decade due to its potential to standardize care and improve patient outcomes. This framework represents a practical, consensus-driven tool for implementing T2T in real-world SLE management. It is designed to guide a broad spectrum of healthcare providers, including those beyond the specialized circle of lupus experts, in delivering structured, goal-oriented care to their patients.

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)0.418
metaresearch head score (Gemma)0.282
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.418
Threshold uncertainty score0.718

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.4180.282
Meta-epidemiology (narrow)0.0040.003
Meta-epidemiology (broad)0.0040.010
Bibliometrics0.0110.008
Science and technology studies0.0110.008
Scholarly communication0.0150.010
Open science0.0130.022
Research integrity0.0160.022
Insufficient payload (model declined to judge)0.0050.003

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 head0.044
GPT teacher head0.427
Teacher spread0.383 · 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.

Study designNot applicable
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

Citations0
Published2025
Admission routes2
Has abstractyes

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