Impact of biologic initiation on oral corticosteroids in the International Severe Asthma Registry and the Optimum Patient Care Research Database: a pooled analysis
Bibliographic record
Abstract
This study estimated the impact of biologic initiation on using oral corticosteroids (OCS) in severe asthma (SA) patients from real-life specialist and primary care settings. Adult patients with SA were identified from the International Severe Asthma Registry (ISAR, specialist care) and the Optimum Patient Care Research Database (OPCRD, primary care, UK). Biologic initiators were identified and propensity-score matched with non-initiators. Impact of biologic initiation on total OCS (TOCS, including bursts for exacerbations) daily dose in the 1st- and 2nd-year follow-up period was assessed using multivariable generalized linear models. Among 8060 patients (ISAR 34%, OPCRD 76%), the risk ratios (RR) of biologic initiators achieving zero TOCS in year 1 and 2 of follow up were 1.53 (95% CI: 1.28-1.82) and 1.72 (1.43-2.07), while the RRs of achieving low daily dose (0-5 mg) were 1.07 (1.00-1.16) and 1.11 (1.03-1.19), respectively. Biologic initiators also had a greater likelihood of achieving any reduction in TOCS and optimal (≥75%) reduction in both year 1 and 2 of follow-up (Table 1). Compared to non-initiators, biologic initiators had greater reduction in TOCS daily dose in both 1st (mg/day, -3.2 vs -2.0) and 2nd (−4.2 vs -3.5) year (p<.001). Biologic initiation results in reduced OCS burden in patients with SA over two years versus usual care. erj;64/suppl_68/PA2175/F1 F1 F1
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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 | 0.033 | 0.042 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.027 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".