Biomarker profile and disease burden associated with intermittent and long-term oral corticosteroid use in patients with severe asthma prior to biologic initiation in real-life (STAR)
Bibliographic record
Abstract
Background: Asthma characterization using blood eosinophil count (BEC) (among other biomarkers and clinical indices) is recommended in severe asthma (SA), but the masking effect of oral corticosteroids (OCS), makes this challenging. Aim: Our aim was to explore the effect of OCS use (both intermittent [iOCS] and long-term [LTOCS]) prior to biologic initiation on SA phenotype and biomarker profile in real-life and to characterize the burden of SA among patients prescribed LTOCS by biomarker profile. Methods: This was a registry-based cohort study, including data from 23 countries collected between 2003 and 2023 and shared with the Internatonal Severe Asthma Registry (ISAR). Patients with SA were categorized into 3 cohorts, those with: (i) no prescription for OCS, (ii) prescription(s) for iOCS (ie, ≤90 days in previous 12-months, usually short courses for exacerbations), and (iii) prescriptions for LTOCS (ie, >90 days in previous 12-months). Biomarker distribution (ie, BEC, fractional exhaled nitric oxide [FeNO], and total Immunoglobulin E [IgE]) were quantified in the year prior to biologic initiation in patients with SA according to OCS prescription pattern. Phenotypes were characterized for those prescribed LTOCS according to BEC cut-off (<150 and ≥ 150 cells/μL). Results: Of 4305 patients included, 5.0% (n = 215), 54.1% (n = 2330) and 40.9% (n = 1760) were prescribed no OCS, iOCS, and LTOCS, respectively. The BEC distribution varied by prescription pattern and LTOCS dose (<5 mg to ≥20 mg/day); BEC was <150 cells/μL in 28.6% (n = 369/1288) of LTOCS patients, compared to 19.5% (n = 284/1460) of iOCS patients and 14.0% (n = 21/150) of those in the no OCS group. Median BEC was also significantly lower in the LTOCS versus the iOCS group (310 vs 400 cells/μL; p < 0.001). A similar pattern was noted for IgE, but not FeNO. Among LTOCS patients with BEC <150 cells/μL, 39.9% experienced ≥4 exacerbations, 75.1% had uncontrolled asthma symptoms and 55.9% had evidence of persistent airflow obstruction (compared with 40.9%, 76.2% and 59.5% of those with BEC ≥150 cells/μL, respectively). Conclusions: OCS, whether prescribed intermittently or long term, affect BEC distribution potentially leading to heightened risk of phenotype misclassification and influencing subsequent treatment decisions. FeNO appears to be less susceptible to OCS-induced suppression. Disease burden was high for those in the LTOCS group and was high independent of dose and BEC. Our findings highlight the importance of considering OCS use, even intermittent use, when characterizing SA, and suggests the need for earlier phenotyping and alternative treatment strategies for LTOCS patients with low BEC.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".