Hereditary angioedema: beyond international consensus - circa December 2010 - The Canadian Society of Allergy and Clinical Immunology Dr. David McCourtie Lecture
Bibliographic record
Abstract
BACKGROUND: The 2010 International Consensus Algorithm for the Diagnosis, Therapy and Management of Hereditary Angioedema was published earlier this year in this Journal (Bowen et al. Allergy, Asthma & Clinical Immunology 2010, 6:24 - http://www.aacijournal.com/content/6/1/24). Since that publication, there have been multiple phase III clinical trials published on either prophylaxis or therapy of hereditary angioedema and some of these products have changed approval status in various countries. This manuscript was prepared to review and update the management of hereditary angioedema. OBJECTIVE: To review approaches for the diagnosis and management of hereditary angioedema (HAE) circa December 2010 and present thoughts on moving from HAE management from international evidence-based consensus to facilitate more local health unit considerations balancing costs, efficacies of treatments, and risk benefits. Thoughts will reflect Canadian and international experiences. METHODS: PubMed searches including hereditary angioedema and diagnosis, therapy, management and consensus were reviewed as well as press releases from various pharmaceutical companies to early December 2010. RESULTS: The 2010 International Consensus Algorithms for the Diagnosis, Therapy and Management of Hereditary Angioedema is reviewed in light of the newly published phase III Clinical trials for prevention and therapy of HAE. Management approaches and models are discussed. CONCLUSIONS: Consensus approach and double-blind placebo controlled trials are only interim guides to a complex disorder such as HAE and should be replaced as soon as possible with large phase IV clinical trials, meta analyses, data base registry validation of approaches including quality of life and cost benefit analyses, safety, and head-to-head clinical trials investigating superiority or non-inferiority comparisons of available approaches. Since not all therapeutic products are available in all jurisdictions and since health care delivery approaches and philosophy vary between countries, each health care delivery sector will likely devise their own algorithms based on local practicalities for implementing evidence-based guidelines and standards for HAE disease management. Quality-of-life and cost affordability benefit conclusions will likely vary between countries and health care units. Data base registries for rare disorders like HAE should be used to detect early adverse events for new therapies and to facilitate phase IV clinical trials and encourage superiority and non-inferiority comparisons of HAE management approaches.
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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 | 0.036 | 0.063 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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".