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Record W3173471637 · doi:10.1186/s13223-021-00550-5

Letting the patients speak: an in-depth, qualitative research-based investigation of factors relevant to health-related quality of life in real-world patients with hereditary angioedema using subcutaneous C1 inhibitor replacement therapy

2021· article· en· W3173471637 on OpenAlexvenueno aff
John Anderson, Donald S. Levy, William R. Lumry, Patricia Koochaki, Sally Lanar, H. Henry Li

Bibliographic record

VenueAllergy Asthma and Clinical Immunology · 2021
Typearticle
Languageen
FieldMedicine
TopicCoagulation, Bradykinin, Polyphosphates, and Angioedema
Canadian institutionsnot available
FundersCSL Behring
KeywordsFeelingThematic analysisQuality of life (healthcare)Qualitative researchMedicineHereditary angioedemaAnxietyWorryPhysical therapyPsychologyClinical psychologyPsychiatryNursing

Abstract

fetched live from OpenAlex

BACKGROUND: While many studies of effective hereditary angioedema (HAE) therapy have demonstrated improved health-related quality of life (HRQoL) using validated instruments, specific reasons behind the improved scores have never been investigated using qualitative methods. A non-interventional, qualitative research study was designed to investigate the reasons for improvements in HRQoL while using effective prophylaxis, in this case subcutaneous C1INH (C1INH[SC]) replacement therapy. METHODS: Adult patients with HAE-C1INH type 1 or 2 who had been using C1INH(SC) for ≥ 3 consecutive months were recruited through four HAE specialty practices in the US to participate in a 60-min phone interview performed by a trained qualitative research specialist (ICON plc) using a semi-structured interview guide with open-ended questions developed with the Angioedema Quality of Life (AE-QoL) items in mind. Interview transcripts were analyzed using thematic analysis methods to identify concepts (specific symptoms/impacts) and themes (higher-level categories grouping related concepts). A cross-mapping exercise was performed between interview-identified concepts and items included in the AE-QoL. RESULTS: Fourteen patients were interviewed and included in the analysis (age range, 28-82 years [mean 47.5 years]; 64% female; 93% white). In 10 interviews, patients mentioned having no or nearly no HAE attacks, no longer feeling limited by HAE, less HAE-related anxiety/worry and depression, an improved ability to travel, fewer emergency room/hospital visits, and ease of administration of C1INH(SC), including not requiring assistance from others. Other commonly expressed concepts included: increased feelings of confidence, independence, optimism, and normalcy; less absence from work/school; better productivity; improved sleep and energy; healthier family relationships; and improved cognition. While all AE-QoL items emerged from patient interviews, a number of identified concepts were not addressed by the AE-QoL, including sensitivity to various potential attack-triggers (e.g., stress/anxiety, sports), attack frequency, not having to cancel social plans, improvements in ability to perform day-to-day tasks, and a lower burden from medical visits. CONCLUSIONS: From these interviews, a large number of common themes and concepts emerged: a greater sense of freedom and normalcy, increased productivity, and improved interpersonal relationships while using convenient and effective prophylaxis. These findings provide insights into real-world experiences and the many facets of HRQoL that are important to patients with HAE-C1INH.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.032
metaresearch head score (Gemma)0.035
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score0.169

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0320.035
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0080.010
Scholarly communication0.0050.005
Open science0.0030.006
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0030.000

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 head0.134
GPT teacher head0.427
Teacher spread0.293 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations31
Published2021
Admission routes1
Has abstractyes

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