Effective Management of Severe Asthma with Biologic Medications in Adult Patients: A Literature Review and International Expert Opinion
Bibliographic record
Abstract
Severe asthma often remains uncontrolled despite effective treatments and evidence-based guidelines. A group of global experts in asthma and biologic medications from 9 countries considered the most relevant clinical variables to manage severe asthma in adult patients and guide treatment choice. The resulting recommendations address the investigation of biomarker levels (blood eosinophil count along with fractional concentration of exhaled nitric oxide [FeNO]), clinical features (oral corticosteroid [OCS] dependence, specific comorbid disease entities associated with severe type 2 asthma), and safety considerations. Current evidence suggests that biomarkers, including both blood or sputum eosinophil counts as well as FeNO, add prognostic and predictive value and should be measured in all patients with severe asthma. OCS use is an important factor in biologic selection, especially given the documented ability of some biologics to reduce OCS dependence. Comorbid diseases and relevant safety considerations to each biologic should also be considered. More data are needed to determine whether biomarker profiles identify patients suited to one biologic versus another as limited data support differential predictors of response. Further prospective head-to-head trials and post hoc analyses of clinical trial data are warranted. The authors believe that these recommendations have value as they offer expert opinion to assist health care providers in making difficult decisions regarding the quality of care in severe, type 2 asthma with biologic medications. They remain conditional and are based on limited data owing to a lack of head-to-head comparisons.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".