Cost-effectiveness of tiotropium versus omalizumab for uncontrolled allergic asthma in US
Bibliographic record
Abstract
BACKGROUND: A significant minority of asthma patients remain uncontrolled despite the use of inhaled corticosteroids (ICS) and long-acting beta-agonists (LABA). A number of add-on therapies, including monoclonal antibodies (namely omalizumab) and more recently tiotropium bromide have been recommended for this subgroup of patients. The purpose of this study was to assess the cost-effectiveness of tiotropium versus omalizumab as add-on therapies to ICS + LABA for patients with uncontrolled allergic asthma. METHODS: A probabilistic Markov model of asthma was created. Total costs (in 2013 US $) and health outcomes of three interventions including standard therapy (ICS + LABA), add-on therapy with tiotropium, and add-on therapy with omalizumab, were calculated over a 10-year time horizon. Future costs and quality-adjusted life years (QALYs) were discounted at the rate of 3%. Multiple sensitivity analyses were conducted. Cost-effectiveness was evaluated at willingness-to-pay value of $50,000. RESULTS: The 10-year discounted costs and QALYs for standard therapy were $38,432 and 6.79, respectively. The corresponding values for add-on therapy with tiotropium and with omalizumab were $41,535 and 6.88, and $217,847 and 7.17, respectively. The incremental cost-effectiveness ratios (ICER) of add-on therapy with tiotropium versus standard therapy, and omalizumab versus tiotropium were $34,478/QALY, and $593,643/QALY, respectively. The model outcomes were most sensitive to the costs of omalizumab but were robust against other assumptions. CONCLUSIONS: Although omalizumab had the best health outcomes, add-on therapy with tiotropium was a cost-effective alternative to omalizumab and standard therapy for uncontrolled allergic asthma at willingness-to-pay of $50,000/QALY.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".