Functional impairment measurement in psoriatic arthritis: Importance and challenges
Bibliographic record
Abstract
OBJECTIVES: Patients with psoriatic arthritis (PsA) experience substantial physical impairment. This is commonly assessed using the patient-reported Health Assessment Questionnaire-Disability Index (HAQ-DI), which was originally developed in rheumatoid arthritis. The purpose of this review is to examine the value and challenges of using the HAQ-DI in patients with PsA, and to discuss alternative measures of functional impairment in this condition. METHODS: A literature search was performed in the MEDLINE, BIOSIS Previews, Embase, Derwent Drug File, and SciSearch databases using relevant terms and key words. Additional references from personal libraries were identified by the authors. RESULTS: Although validated in PsA, the HAQ-DI has limitations, including marked floor effects, lack of responsiveness to treatment effects in later disease stages, and underestimation of physical impairment in patients whose symptoms are predominantly skin related. Nonetheless, it has been widely used in clinical trials of PsA treatment and is generally responsive to change with effective therapy, discriminating between active and placebo treatments. Other generic or arthritis-specific patient-reported questionnaires with a focus on physical impairment include the Medical Outcomes Study Short Form-36 Health Survey, the EuroQol-5D, the Arthritis Impact Measurement Scales, and the Routine Assessment of Patient Index Data 3. There are currently no PsA-specific instruments to assess physical function, but health-related quality-of-life questionnaires with elements related to functional impairment include the PsA Quality of Life questionnaire, the PsA Impact of Disease questionnaire, and VITACORA-19. As the available measures of physical impairment may not reflect the impact of all aspects of PsA on a patient, additional health-related quality-of-life instruments, such as the Dermatology Life Quality Index, may be used in parallel to obtain a more complete picture of the disease burden. CONCLUSIONS: The HAQ-DI is a valuable assessment tool that clinicians should continue to use in clinical trials and practice. Because instruments to specifically assess physical function in patients with PsA are currently lacking, clinicians should consider using a combination of instruments to conduct the most thorough evaluation possible.
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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 | 0.017 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".