Comparison of the Sensitivity to Change of the 36‐Item Short Form Health Survey and the Lupus Quality of Life Measure Using Various Definitions of Minimum Clinically Important Differences in Patients With Active Systemic Lupus Erythematosus
Bibliographic record
Abstract
OBJECTIVE: The Medical Outcomes Study Short Form 36 (SF-36) and Lupus Quality of Life (LupusQoL) are health-related quality of life questionnaires used in systemic lupus erythematosus (SLE). We first determined the hypothesis-testing construct validity of the SF-36 and LupusQoL against disease activity in patients with active SLE and then compared the sensitivity to change of SF-36 and LupusQoL domains according to different definitions of minimum clinically important differences (MCIDs) for improvement and worsening in the current cohort. METHODS: Seventy-eight clinically active SLE patients concurrently completed both questionnaires at their baseline and followup visits. Questionnaire domain scores were correlated with the SLE Disease Activity Index 2000 (SLEDAI-2K) and evaluated for floor/ceiling effects. The sensitivity to change of domains in each questionnaire was analyzed first, according to the various MCID definitions and, second, by clinically meaningful changes in disease activity. The magnitudes of change in each domain score between the baseline and followup visit were evaluated using standardized response means. RESULTS: In the 78 patients, the mean ± SD SLEDAI-2K scores were 9.7 ± 4.8 at baseline and 8.8 ± 5.1 at followup. SF-36/LupusQoL domain scores did not correlate with disease activity. The SF-36 showed floor effects, and ceiling effects were evident in both questionnaires. All domains of both questionnaires showed sensitivity to change over time. Specific domains that reflected worsening or improvement differed according to differing MCID definitions. CONCLUSION: In SLE patients with active disease, both the SF-36 and LupusQoL are sensitive to change, reflecting both improvement and worsening. More importantly, the LupusQoL SLE-specific domains (planning, burden to others, body image, and intimate relationships) were largely responsive to change.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.059 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 source (direct Gemma or distilled Codex), 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".