Assessment of the minimal clinically important difference for the Health Assessment Questionnaire Disability Index in patients with arthralgia at risk for progression to rheumatoid arthritis
Bibliographic record
Abstract
INTRODUCTION: Patients with arthralgia at-risk for rheumatoid arthritis (RA) experience considerable functional disability, though generally less than at RA diagnosis. Secondary prevention trials have shown that treatment can improve disability in patients with arthralgia. However, interpreting the clinical relevancy of the improvements in Health Assessment Questionnaire Disability Index (HAQ-DI) is hampered by the lack of a defined minimal clinically important difference (MCID) in this disease stage. Results from other disciplines than rheumatology suggested that the MCID depends on absolute severity values. Therefore, we hypothesised that the MCID for HAQ-DI in RA depends on absolute values. We aimed to investigate this and, if so, to determine the MCID for disability in the risk setting. METHODS: We studied the literature and determined the correlation of baseline HAQ-DI and MCID estimates in RA. To determine the MCID in arthralgia, we studied 97 patients treated with methotrexate in the TREAT EARLIER trial with HAQ-DI data at baseline and 12 months. At 12 months, a short-form 36 questionnaire anchor question compared patients' general health to that of 1 year before. The MCID was determined using the mean change in HAQ-DI score of patients reporting 'somewhat better' and 'somewhat worse'. RESULTS: In RA, the MCID estimates ranged from -0.06 to -0.38, and higher absolute HAQ values correlated with a higher MCID. In the at-risk patients studied, the MCID for improvement was -0.07±0.28. Likewise, for deterioration, the MCID was +0.05±0.6. CONCLUSION: In arthralgia at-risk for RA, the MCID for improvement in HAQ-DI is -0.07. This is lower than generally reported in RA. This implies that in arthralgia, compared with RA, smaller improvements in HAQ-DI are clinically relevant.
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) | 0.001 | 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) | 0.000 | 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".