Tezepelumab compared with other biologics for the treatment of severe asthma: a systematic review and indirect treatment comparison
Bibliographic record
Abstract
To compare the efficacy of tezepelumab with other approved biologics via indirect treatment comparisons (ITCs) in patients aged ≥ 12 years with severe uncontrolled asthma. Data from randomized controlled trials (RCTs) identified from a systematic literature review were synthesized using two different ITC approaches: network meta-analysis (NMA) and simulated treatment comparison (STC). Outcomes of interest were annualized asthma exacerbation rate (AAER) and AAER for exacerbations leading to hospitalization. To address potential heterogeneity between study populations, various subgroup analyses were performed for the NMA (based on blood eosinophil count, fractional exhaled nitric oxide level, and presence of allergic asthma), and for the STC, models were adjusted for potential treatment effect modifiers. Sensitivity analyses were performed to assess the impact of study design (exclusion of non-placebo-controlled studies and non-phase 3 or 4 studies). Results were reported as rate ratios (RRs) with 95% credible/confidence intervals and ranking statistics were computed for the NMAs. Sixteen RCTs were included in at least one of the ITCs. All biologics (tezepelumab, dupilumab, benralizumab, mepolizumab, reslizumab, and omalizumab) had similar efficacy, with no statistically significant RRs for either exacerbation outcome; however, tezepelumab was favorably associated with numerically lower AAERs and was ranked first in the network for both types of exacerbation outcome. This trend was consistent in the subgroup and sensitivity analyses. As with the primary NMA, the STC results did not demonstrate any significant differences between biologics, but point estimates were favorable towards tezepelumab. Heterogeneity between trials was observed among eligibility criteria and clinically important patient characteristics; however, the impact on findings is expected to be low, based on consistency across analyses. Findings from both ITCs (NMA and STC) support the use of tezepelumab in a broad patient population of severe uncontrolled asthma of any phenotype.
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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 | 0.018 | 0.040 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.027 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".