Frequency and determinants of flare and persistently active disease in systemic lupus erythematosus
Bibliographic record
Abstract
OBJECTIVE: Selection of flare as the primary outcome variable in systemic lupus erythematosus (SLE) clinical trials fails to capture patients with persistently active disease (PAD). We sought to elucidate the frequency and determinants of flare and PAD. METHODS: Prospectively collected data from the Toronto Lupus Cohort were used to determine the incidence of flare and PAD in 2004 and 2005. Flare was defined as an increase in SLE Disease Activity Index 2000 update (SLEDAI-2K) score of >/=4 from the previous visit. PAD was defined as a SLEDAI-2K score of >/=4, excluding serology alone, on >/=2 consecutive visits. Data from 1, 2, and 3 years prior were used to model flare and PAD in 2004. Model properties were tested for prediction of flare and PAD in 2005. RESULTS: One-third of the patients had >/=1 flare, whereas nearly half experienced PAD in a given year. Nearly 60% of the patients had episodes of flare or PAD per year. At least 25% of patients had PAD without achieving the definition of flare. In the best-fitting model, predictors of PAD in 2004 were SLEDAI-2K score at the start of the outcome interval and prior cutaneous or musculoskeletal disease activity. This model gave 79% correct prediction of PAD in 2005. In contrast, flare prediction models performed poorly. CONCLUSION: Persistent activity is a common disease state in SLE and should be an outcome variable in SLE clinical trials. Our PAD prediction model may aid prognostication and selection of patients for inclusion in clinical trials.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".