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217 Results of a patient survey on feasibility and face validity of outcome measures for intended use in future studies enrolling participants with polymyalgia rheumatica

2019· article· en· W2938028941 on OpenAlexaffabout
Max Yates, Claire Owen, Sara Müller, Karly Graham, Lorna Neill, Helen Twohig, Maarten Boers, Mar Pujades‐Rodríguez, Susan M. Goodman, Jonathan T. L. Cheah, Christian Dejaco, Chetan Mukhtyar, Berit Dalsgaard Nielsen, Jo Robson, Lee S. Simon, Bev Shae, Sarah Mackie, Catherine Hill

Bibliographic record

VenueLara D. Veeken · 2019
Typearticle
Languageen
FieldMedicine
TopicOtitis Media and Relapsing Polychondritis
Canadian institutionsOttawa Public HealthUniversity of Ottawa
Fundersnot available
KeywordsMedicinePolymyalgia rheumaticaFace validityPatient-reported outcomeOutcome (game theory)Physical therapyExternal validityFamily medicineClinical psychologyPsychometricsQuality of life (healthcare)Social psychologyNursingPathologyGiant cell arteritis

Abstract

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Background: Too few studies to date have used robust, validated outcome measures that are relevant to patients resulting in difficulty in comparing results from trials. The Outcome Measures in Rheumatology (OMERACT) polymyalgia rheumatica (PMR) working group have previously developed a core domain set for PMR and identified candidate outcome measures following the OMERACT Filter 2.1 Instrument Selection Algorithm. The aim of this study was to conduct a survey amongst patients with PMR to evaluate the face validity, acceptability and domain match of the proposed candidate outcome measures. Methods: The previously identified core domains and measurement instruments comprised: 1. Pain severity: visual analogue scale (VAS), numerical rating score (NRS); 2. Stiffness: severity: VAS, NRS; duration of morning stiffness: minutes; 3. Physical Function: modified Health Assessment Questionnaire (mHAQ), Health Assessment Questionnaire Disability Index (HAQ-DI); 4. Inflammation: C-reactive protein (CRP), erythrocyte sedimentation rate (ESR). A structured online, anonymous questionnaire following the OMERACT instrument selection algorithm was disseminated to patient support groups via their own networks and online forums. Free text answers were analysed using descriptive thematic analysis to explore respondent views of the candidate instruments in relation to participants’ lived experience of PMR. Results: 78 people with PMR from six countries (UK, France, USA, Canada, Australia and New Zealand) participated in the survey. Disease duration ranged from 0 (newly diagnosed) to 17 years with current doses of prednisolone ranging from 0 mg to 50 mg (nine were off glucocorticoids). Most respondents agreed candidate instruments “good to go”. Approval: for pain measurement by VAS was given by 66.7% of participants and by 59.3% for NRS. Stiffness measured by VAS or NRS achieved 51.9% and 48.2% approval, respectively; and duration of stiffness 50%. Physical health as captured by HAQ-DI achieved 68.5% approval and mHAQ 53.3%. Furthermore, 56.3% of respondents agreed that CRP or ESR reflected disease activity in terms of levels of inflammation.ve themes were identified which patients felt were not covered adequately by the proposed instruments. These themes related to: (i) the variation, context and location of pain, (ii) the variability of stiffness, (iii) fatigue, (iv) disability, and (v) the variable correlation of inflammatory markers to their severity of symptoms. Conclusion: The identified core domains and associated proposed candidate instruments were broadly acceptable to people with PMR. However, participants felt that there were gaps. The greatest concerns were for the proposed measures to capture the experience of stiffness, and that fatigue is missing altogether (although this is included as “important” rather than “core” for PMR). We plan to explore these issues in more depth with patients via cognitive interviewing. If outcome measures fail to capture adequately the impact of PMR on patients’ lives, then clinical trials of new treatments may be compromised. Disclosures: M. Yates: None. C.E. Owen: None. S. Muller: None. K. Graham: None. L. Neill: None. H. Twohig: None. M. Boers: None. M.D.M. Pujades-Rodriguez: None. S. Goodman: None. J.T.L. Cheah: None. C. Dejaco: None. C. Mukhtyar: None. B. Dalsgaard Nielsen: None. J. Robson: None. L.S. Simon: None. B. Shae: None. S.L. Mackie: None. C. Hill: None.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.007
Threshold uncertainty score0.472

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.141
GPT teacher head0.351
Teacher spread0.210 · 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".

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Citations0
Published2019
Admission routes2
Has abstractyes

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