Omalizumab Treatment Patterns Among Patients with Asthma in the US Medicare Population
Bibliographic record
Abstract
BACKGROUND: Asthma in older adults is associated with high rates of morbidity and mortality; similarly, asthma can be severe enough among younger adults to warrant disability benefits. Reasons for poor outcomes in both groups of patients may include discontinuation and lack of adherence to controller therapies. OBJECTIVE: To examine characteristics and treatment patterns of US Medicare patients initiating omalizumab for asthma, and factors associated with its discontinuation and adherence. METHODS: A retrospective claims database analysis of Medicare beneficiaries with asthma initiating omalizumab treatment was carried out. The primary outcomes were omalizumab discontinuation (gap in use ≥90 days) and adherence (proportion of days covered ≥0.8) over a 12-month follow-up. Multivariable regressions were used to examine factors associated with omalizumab discontinuation and adherence. RESULTS: Of the 3058 Medicare patients initiating omalizumab for asthma (mean age, 62.7 years), 36.9% discontinued omalizumab and 60.6% were adherent. Discontinuation rates were 32.7% and 42.8%, and adherence rates were 65.4% and 53.9%, for disabled and older Medicare patients, respectively. Patients aged 65 to 69 years and 70 to 74 years had significantly lower odds of discontinuation (odds ratios [95% CI], 0.66 [0.46-0.93] and 0.62 [0.43-0.89], respectively) and higher odds of adherence than did patients aged 80 years or older. Compared with patients receiving low-income subsidy, patients not receiving low-income subsidy had lower odds of discontinuation (0.66 [0.52-0.83]) and higher odds of adherence (1.52 [1.20-1.93]). Greater numbers of preindex evaluation and management physician visits and comorbid rhinitis were associated with lower odds of discontinuation and higher odds of adherence. CONCLUSIONS: More than 60% of Medicare patients with asthma continued and were adherent to omalizumab over a 12-month follow-up. Patient age, low-income subsidy status, and the numbers of evaluation and management physician visits were among factors associated with treatment adherence and discontinuation.
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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 | 0.000 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".