Medicare coverage and cost-sharing for abiraterone following generic entry.
Bibliographic record
Abstract
13 Background: Generic competition lowers drug prices, but may not reduce out-of-pocket costs for patients. Abiraterone, first approved by the United States Food and Drug Administration in 2011, has two commonly used dosage units (250mg and 500mg) with multiple generic market entrants over the last 5 years. This makes it ideal to evaluate the association between generic competition and changes in product coverage and cost-sharing. Methods: We studied 4 abiraterone products (tablets): generic 250mg, generic 500mg, brand-name 250mg, and brand-name 500mg. We used the FDA’s Orange Book to identify market entry of generic products until May 2022. We used Part D formulary data from 2018 to 2022 to identify changes in product coverage and expected annual out-of-pocket costs for the average Part D beneficiary (daily dose of 1000mg). We also calculated “best-case” cost-sharing in 2022, using the Part D Plan Finder. Results: During 2018-2022, 12 generic 250mg and 4 generic 500mg abiraterone formulations came to market. The first 250mg generic came to market in October 2018, and 10 of the 12 formulations came to market by 2019. The first 500mg generic formulation came to market in December 2020. The proportion of Part D plans that covered generic products increased from 0% in 2018, to 100% for 250mg and 79% for 500mg in 2022. Expected annual out-of-pocket costs for a Part D beneficiary ranged from $7,491 to $10,148 across products and years. In 2022, the average out-of-pocket costs for generic 500mg tablets was $10,148, greater than that for brand-name 500mg tablets, which was $9,298. The same was true when using the Part D plan finder (generic, $11,093, brand-name, $9,476). For the 250mg product, however, out-of-pocket costs were much higher for the brand-name versus generic product (> $150,000 versus $1,139). Conclusions: During 2018-2022, market entry of generic abiraterone products led to their preferential coverage over brand-name products on Part D formularies, but this was associated with only modest savings for beneficiaries. In fact, in 2022 for the 500mg product, average out-of-pocket costs were higher for generic, versus brand-name products. For the 250mg generic product, a patient able to price-shop could pay approximately $1,100, 1/7th of what the average beneficiary spent. These data indicate that Part D beneficiaries do not immediately benefit from price reductions associated with generic entry of specialty drugs. Part D beneficiaries’ out-of-pocket costs with generics can be higher despite lower list prices (vs. brand-name). Proposals to redesign Part D correct this fundamental flaw that makes high-cost generic drugs more expensive to patients than brands. Affordable medications should be available to all patients, not just the most resourced and able to price-shop. Limitations include that formulary files capture data from the prior 3 months, and expected out-of-pocket costs are averaged across beneficiaries and plans.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".