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.
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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 | 0.006 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".