The cost-effectiveness of azithromycin in reducing exacerbations in uncontrolled asthma
Bibliographic record
Abstract
Add-on azithromycin (AZM) results in a significant reduction in exacerbations among adults with persistent uncontrolled asthma. The aim of this study was to assess the cost-effectiveness of add-on AZM in terms of healthcare and societal costs.The AMAZES trial randomly assigned 420 participants to AZM or placebo. Healthcare use and asthma exacerbations were measured during the treatment period. Healthcare use included all prescribed medicine and healthcare contacts. Costs of antimicrobial resistance (AMR) were estimated based on overall consumption and published estimates of costs. The value of an avoided exacerbation was based on published references. Differences in cost between the two groups were related to differences in exacerbations in a series of net monetary benefit estimates. Societal costs included lost productivity, over the counter medicines, steroid induced morbidity and AMR costs.Add-on AZM resulted in a reduction in healthcare costs (mean (95% CI)) including nights in hospital (AUD 433.70 (AUD 48.59-818.81) or EUR 260.22 (EUR 29.15-491.29)), unplanned healthcare visits (AUD 20.25 (AUD 5.23-35.27) or EUR 12.15 (EUR 3.14-21.16)), antibiotic costs (AUD 14.88 (AUD 7.55-22.21) or EUR 8.93 (EUR 4.53-13.33)) and oral corticosteroid costs (AUD 4.73 (AUD 0.82-8.64) or EUR 2.84 (EUR 0.49-5.18)); all p<0.05. Overall healthcare and societal costs were lower (AUD 77.30 (EUR 46.38) and AUD 256.22 (EUR 153.73) respectively) albeit not statistically significant. The net monetary benefit of add-on AZM was estimated to be AUD 2072.30 (95% CI AUD 1348.55-2805.23) or (EUR 1243.38 (EUR 809.13-1683.14) assuming a willingness to pay per exacerbation avoided of AUD 2651 (EUR 1590.60). Irrespective of the sensitivity analysis applied, the net monetary benefit for total, moderate and severe exacerbations remained positive and significant.Add-on AZM therapy in poorly controlled asthma was a cost-effective therapy. Costs associated with AMR did not influence estimated cost-effectiveness.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".