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PROSPECTIVE IMPLEMENTATION OF T2T STRATEGIES IN ADOLESCENTS AND YOUNG ADULTS WITH CHILDHOOD-ONSET SYSTEMIC LUPUS ERYTHEMATOSUS LED TO IMPROVED DISEASE CONTROL AND MINIMIZED DAMAGE ACCRUAL

2025· article· en· W4410512919 on OpenAlexvenueno aff
Coziana Ciurtin, R. Taylor Gotch, Yumna Ahmed, Robert H. Wilson, Ellie Hawkins

Bibliographic record

VenueThe Journal of Rheumatology · 2025
Typearticle
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAccrualDiseaseSystemic diseaseProspective cohort studyPediatricsLupus erythematosusSystemic lupus erythematosusConnective tissue diseasePhysical therapyAutoimmune diseaseInternal medicineImmunologyAntibody

Abstract

fetched live from OpenAlex

PV160 / #31 Poster Topic: AS18 - Pediatric SLE Background/Purpose Treat-to-target (T2T) strategies aim to facilitate tight disease control. No previous studies evaluated prospectively the feasibility and impact of active implementation of T2T strategy at every routine clinical appointment in adolescents and young adults (AYA) with childhood-onset SLE (cSLE). Methods AYA with cSLE were recruited for T2T implementation from a large tertiary center over a period of 6 months, and followed up at least twice over a prospective period of 12 months. The study had the following design: 1. The first phase of the study was a 6-month cross-sectional evaluation of the feasibility to implement and systematically document routine outcome measures in AYA with cSLE. At the end of this phase, only AYA with cSLE and complete data collection including disease activity evaluation as well as treatment target assessment and documentation, were included. 2. The second phase of the study was a 12-month prospective evaluation of disease control against the agreed cSLE target between the baseline assessment and the final timepoint (last routine clinic appointment during the 12-month study follow-up period). In support of our project design robustness, a preliminary sample size calculation was undertaken, which showed that we needed to include at least 115 individuals to be able to detect with 90% confidence and 80% power, a 10% improvement in the proportion of AYA with cSLE achieving LLDAS after 12 months of active T2T strategy implementation. Results During Oct 2022-April 2023, 135/162 (83.3%) AYA with cSLE had disease scores evaluated at their routine appointment to enable inclusion in the study and 122/135 (91.2%) had their disease assessed, and a suitable treatment target agreed and documented at each routine clinical appointment over the following 12 months. T2T strategy led to improved disease: more AYA with cSLE achieved clinical remission off steroids (4.1% vs. 10.7%, P=0.048), or minimum childhood-lupus low disease activity (cLLDAS) (81.9% vs. 91.8%, P=0.022) (Table). Achieving minimum cLLDAS for longer than 3 months was associated with reduced damage accrual (HR=1.7; 95% CI=1.1-2.5; P<0.0001) and a trend in flare risk improvement (HR=1.6, 95% CI=0.98-1.4; P=0.06) after 12 months. We found a positive correlation between the damage (pedSDI) score and cumulative steroid dose (median dose = 615 mg) over the 12-month prospective evaluation (ro=0.37, p=0.04). Table: Assessment of disease states at the timepoint of agreeing a treatment target (baseline) and after 12 months routine follow-up Conclusions This is the first large prospective study in AYA with cSLE which showed that T2T strategy implementation was achievable in routine practice and led to an improved proportion of AYA ‘in target’. Spending at least 3/12 months in cLLDAS led to less damage accumulation over 12-month follow-up.

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)0.006
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.005
GPT teacher head0.280
Teacher spread0.275 · 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 designNon-randomized trial
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

Citations0
Published2025
Admission routes1
Has abstractyes

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