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Record W2783322352 · doi:10.1017/s0266462317003981

VP161 Identification Of Needs Of Pigmented Villonodular Synovitis Patients Using Online Bulletin Board

2017· article· en· W2783322352 on OpenAlexaboutno aff
Nigel S. Cook, Kyle Landskroner, Susann Walda, Olivia Weiss, Vikrant Pallapotu

Bibliographic record

VenueInternational Journal of Technology Assessment in Health Care · 2017
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal synovial abnormalities and treatments
Canadian institutionsnot available
Fundersnot available
KeywordsPigmented villonodular synovitisMedicineFamily medicineReferralHealth careQualitative researchSynovitisInternal medicine

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.441

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.015
GPT teacher head0.373
Teacher spread0.358 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2017
Admission routes1
Has abstractyes

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