Feasibility and Utility of the Psoriasis Symptom Inventory (PSI) in Clinical Care Settings: A Study from the International Psoriasis Council
Bibliographic record
Abstract
BACKGROUND: The Psoriasis Symptom Inventory (PSI) is a patient-reported outcome measure designed to assess psoriasis signs and symptoms. OBJECTIVES: The aim was to assess the usefulness of the PSI in enhancing patient care in the clinical setting. METHODS: Eight dermatology clinics in six countries enrolled adults representing the full spectrum of psoriasis severity who regularly received care at the clinic. Patients were administered the eight-item PSI (score range 0-32; higher scores indicate greater severity) while waiting for the physician; the physician conducted a static physician global assessment (sPGA) and estimated psoriasis-affected body surface area (BSA) at the same visit. Physicians completed a brief questionnaire after each patient visit, and were interviewed about the PSI after all patients were seen. RESULTS: The clinics enrolled 278 patients; mean [standard deviation (SD)] psoriasis-affected BSA was 7.6% (11.4). Based on BSA, 47.8% had mild psoriasis, 29.1% had moderate psoriasis, and 23.0% had severe psoriasis. Based on sPGA, 18.7% were clear/almost clear, 67.3% were mild/moderate, and 14.0% were severe/very severe. The mean (SD) PSI total score was 12.2 (8.3). Physicians spent a mean (SD) 4.9 (4.8) min discussing PSI findings with their patients (range 0-20 min). Key benefits of PSI discussions included the following: new information regarding symptom location and severity for physicians; prompting of quality-of-life discussions; better understanding of patient treatment priorities; change in treatment regimens to target specific symptoms or areas; and improvement of patient-physician relationship. CONCLUSIONS: The PSI was useful for treated and untreated patients to enhance patient-physician communication, and influenced treatment decisions.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".