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Record W4281481270 · doi:10.2196/27273

Self-Reported Data and Physician-Reported Data in Patients With Eosinophilic Granulomatosis With Polyangiitis: Comparative Analysis

2022· article· en· W4281481270 on OpenAlexaffvenueabout
Irena Doubelt, Jason Springer, Tanaz A. Kermani, Antoine G. Sreih, Cristina Burroughs, David Cuthbertson, Simon Carette, Nader Khalidi, Curry L. Koening, Carol A. Langford, Carol A. McAlear, Larry W. Moreland, Paul A. Monach, Dianne G. Shaw, Philip Seo, Ulrich Specks, Kenneth J. Warrington, Kalen Young, Peter A. Merkel, Christian Pagnoux

Bibliographic record

VenueInteractive Journal of Medical Research · 2022
Typearticle
Languageen
FieldMedicine
TopicVasculitis and related conditions
Canadian institutionsSt. Joseph’s Healthcare HamiltonMcMaster UniversityUniversity of TorontoMount Sinai Hospital
FundersNational Center for Advancing Translational SciencesNational Institute of Arthritis and Musculoskeletal and Skin DiseasesRare Diseases Clinical Research NetworkPatient-Centered Outcomes Research InstituteNational Center for Research ResourcesGlaxoSmithKline
KeywordsGranulomatosis with polyangiitisMedicineCohortEosinophilicInternal medicineAsthmaVasculitisRheumatologyCohort studyMicroscopic polyangiitisPediatricsPathologyDisease

Abstract

fetched live from OpenAlex

BACKGROUND: Patient-based registries can help advance research on rare diseases such as eosinophilic granulomatosis with polyangiitis (EGPA), a complex multiorgan form of antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis. OBJECTIVE: The aim of this study is to compare patient-reported and physician-reported data on manifestations, treatments, and outcomes for patients with EGPA. METHODS: We completed a comparative analysis of patients ≥18 years with EGPA in Canada and the United States from the following 2 cohorts: (1) The Vasculitis Patient-Powered Research Network (VPPRN), a self-enrolled secure portal with patient-entered data updated quarterly (2014-2019) and (2) the Vasculitis Clinical Research Consortium (VCRC) observational studies, a physician-entered database (2003-2019) of patients who fulfilled the 1990 American College of Rheumatology classification criteria for EGPA. The studied parameters included demographic characteristics, clinical manifestations, ANCA status, treatments, and relapses. RESULTS: Data from 195 patients with a validated diagnosis of EGPA in the VPPRN and 354 patients enrolled in the VCRC were analyzed. Compared to the VCRC cohort, the patients in the VPPRN cohort were more likely to be female (135/195, 69.2% compared to 209/354, 59%; P=.02) and younger at diagnosis (47.3 compared to 50.0 years; P=.03); both cohorts reported similar frequencies of asthma (177/184, 96.2% in the VPPRN cohort compared to 329/354, 92.9% in the VCRC cohort; P=.13) and cardiac manifestations (44/153, 28.8% compared to 75/354, 21.2%; P=.06), but the VPPRN cohort reported less frequent lung manifestations other than asthma and more frequent disease manifestations in all other organ systems. The ANCA positivity was 48.9% (64/131) in the VPPRN patients compared to 38.9% (123/316; P=.05) in the VCRC cohort. Relapsing disease after study enrollment was reported in 32.3% (63/195) of patients in the VPPRN compared to 35.7% (99/277) of patients in the VCRC. Most therapies (GC, cyclophosphamide, mepolizumab) were used at similar frequencies in both groups, except for rituximab with VPPRN patients reporting more use than the VCRC cohort (47/195, 24.1% compared to 29/277, 10.5%; P<.001). CONCLUSIONS: Overall, patients and physicians report manifestations of EGPA at similar frequencies. However, observed differences between patient and physician reports imply the potential occurrence of selection biases. These results support the use of patient-reported data in EGPA but also the need for careful consideration of disease-specific definitions for the study of EGPA and how patient- and physician-reported data are collected. TRIAL REGISTRATION: ClinicalTrials.gov NCT00315380, https://clinicaltrials.gov/ct2/show/NCT00315380; ClinicalTrials.gov NCT01241305, https://clinicaltrials.gov/ct2/show/NCT01241305.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.077
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0010.000

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 head0.074
GPT teacher head0.420
Teacher spread0.346 · 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.

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

Citations5
Published2022
Admission routes3
Has abstractyes

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