VP161 Identification Of Needs Of Pigmented Villonodular Synovitis Patients Using Online Bulletin Board
Bibliographic record
Abstract
INTRODUCTION: Pigmented villonodular synovitis (PVNS) is a very rare, benign proliferative tumor affecting the inner lining of synovial joints and tendon sheets. Information on treatment needs of PVNS patients to inform drug development is currently scarce, hence we conducted qualitative research with patients using an online bulletin board (OBB) methodology to generate insights on objective and emotional aspects related to the medical journey and living with this disease. METHODS: OBB is an asynchronous, online qualitative market research tool that allows participants to comprehensively answer pre-defined questions in a comprehensive manner. Patients were recruited via physician referral and underwent screening questions to ensure eligibility for the study and willingness to participate. The discussion was moderated, structured, and allowed open answers and in response to other participants posts. Analysis was conducted using a combination of different qualitative analytical tools. RESULTS: The patient OBB ran for 4 days with eleven participants (n = 3 Canada, n = 4 United Kingdom, n = 4 United States of America) aged 28–57 years, suffering from PVNS for 2–27 years. The key patient insights were: (i) pain is the primary factor, constituting a significant emotional and psychological burden; (ii) surgery (arthroscopy) does not get rid of PVNS, relapse rate was high in these patients; and (iii) PVNS has a big financial impact on patients, their families, and the healthcare system, due in particular to time off work/lost wages (patient & caretaker), for healthcare system it is repeat costs for surgeries/hospital stays plus other medical expenses. We also identified orthopedic specialists/surgeons are the physicians who predominantly manage PVNS at this point, as surgery is the only option. CONCLUSIONS: This study shows the suitability of the OBB for uncovering qualitative patient insights to inform decision making and strategy in early pharmaceutical drug development. OBB lends itself very well to uncovering patient insights which might not be revealed in focus group or telephone interviews, particularly in a rare disease like this. PVNS patients are in need of a medical drug treatment which can reduce pain, relapses and provide an alternative to surgery, the current standard of care.
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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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".