Differential response to biologics in a patient with severe asthma and ABPA: a role for dupilumab?
Bibliographic record
Abstract
BACKGROUND: Allergic bronchopulmonary aspergillosis (ABPA) is a severe hypersensitivity reaction to aspergillus species colonizing the airways of patients with asthma or cystic fibrosis. Biologics including anti-IgE and anti-IL5 antibodies have strongly changed the treatment of severe asthmatics and have partly been reported to be effective in the treatment of ABPA. Recently, dupilumab, an anti-IL4-Rα antibody which inhibits signaling by the Th2-cytokines IL4 and IL13, has been approved for the treatment of severe asthma. CASE PRESENTATION: Here, we report the case of a 49-year-old woman with severe asthma and ABPA, who was uncontrolled despite maximum inhalative therapy, anti-IL5-Rα antibody and continuous oral steroid therapy. Moreover, trials of itraconazole as well as omalizumab showed insufficient efficacy. Lung function revealed peripheral obstruction. FeNO and IgE were increased, eosinophils were suppressed under treatment while marked increases had been documented previously. Switching to dupilumab led to a complete resolution of pulmonary symptoms, resolution of exacerbations and complete withdrawal of oral steroids. A drastic improvement in lung function was noted, with an increase in FEV1 of almost 1 l. FeNO was normalized and IgE strongly reduced. CONCLUSION: Our case highlights that a patient may exhibit differential treatment responses to the currently available asthma biologics and suggests switching treatment if outcome is insufficient. A potential role for dupilumab in the treatment of ABPA warrants future studies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".