Malignancy and immune disorders in patients with hereditary angioedema
Bibliographic record
Abstract
BACKGROUND: Hereditary angioedema (HAE) is an inherited condition manifesting as recurrent angioedema episodes which is caused by deficiency or dysfunction of C1 inhibitor. Although complement dysregulation has historically been shown to be associated with various malignancy and immune disorders, it is currently not known if HAE patients are at an increased risk of developing malignancy or autoimmune conditions. CASE PRESENTATION: We reviewed the charts of 49 HAE patients and identified 6 patients who had a co-existing malignancy diagnosis (two with breast cancer, one with melanoma, one with pancreatic cancer, one with renal cancer and one with cervical dysplasia) and 6 patients who had a diagnosis of a co-existing immune disorder (two with rheumatoid arthritis, two with ulcerative colitis, one with chronic urticaria with hypothyroidism and one with Sjogren's syndrome). Nearly all malignancy cases occurred in older HAE patients (> 50 years) and malignancy was diagnosed before HAE in 3 of the patients. CONCLUSIONS: Our case series identified multiple hereditary angioedema (HAE) patients with co-existing malignancy and immune disorders. Based on these findings, we would advocate that physicians managing HAE patients should maintain a high index of suspicion for these conditions and that in patients with angioedema, C1 inhibitor deficiency and malignancy, a diagnosis of HAE should still be considered in addition to acquired angioedema (AAE).
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".