Do lupus disease activity measures detect clinically important change?
Bibliographic record
Abstract
OBJECTIVE: New scales for the clinical assessment of patients with systemic lupus erythematosus (SLE) are valid and reliable, and quantitate disease activity. We assessed the responsiveness to change of 2 widely used standardized multi-item lupus activity measures, the revised Systemic Lupus Activity Measure (SLAM-R) and the Systemic Lupus Erythematosus Disease Activity Index (SLEDAI), and their ability to detect clinically relevant changes. METHODS: Ninety-six (96) patients with definite SLE participated in this study. The group mean age was 45.0 (13.7) years, 91% were female, and the mean disease duration was 14.9 (7.5) years. Sociodemographic information, lupus activity (SLAM-R, SLEDAI), and damage were recorded at baseline. At each of the 5 monthly followup visits, the activity measures were repeated and a transition scale asked the physician if their patient's lupus activity had changed. Five different methods were used to compare the responsiveness of the activity measures studied: 1. the effect size; 2. the standardized response mean; 3. the control standardized response mean; 4. the area under the curve of a receiver operating characteristic (ROC) curve; and 5. a new multiple response modeling approach. RESULTS: Both SLAM-R and SLEDAI are responsive. SLAM-R is consistently, although moderately, more responsive than SLEDAI. All 5 methods of evaluating responsiveness yielded a consistent ranking of disease activity measures. CONCLUSION: SLAM-R and SLEDAI are responsive measures of lupus activity. SLAM-R appears to be more responsive than SLEDAI.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".