IMPLICATIONS OF GLOBAL PRICING POLICIES ON ACCESS TO INNOVATIVE DRUGS: THE CASE OF TRASTUZUMAB IN SEVEN LATIN AMERICAN COUNTRIES
Bibliographic record
Abstract
OBJECTIVES: Differential pricing, based on countries' purchasing power, is recommended by the World Health Organization to secure affordable medicines. However, in developing countries innovative drugs often have similar or even higher prices than in high-income countries. We evaluated the potential implications of trastuzumab global pricing policies in terms of cost-effectiveness (CE), coverage, and accessibility for patients with breast cancer in Latin America (LA). METHODS: A Markov model was designed to estimate life-years (LYs), quality-adjusted life-years (QALYs), and costs from a healthcare perspective. To better fit local cancer prognosis, a base case scenario using transition probabilities from clinical trials was complemented with two alternative scenarios with transition probabilities adjusted to reflect breast cancer epidemiology in each country. RESULTS: Incremental discounted benefits ranged from 0.87 to 1.00 LY and 0.51 to 0.60 QALY and incremental CE ratios from USD 42,104 to USD 110,283 per QALY (2012 U.S. dollars), equivalent to 3.6 gross domestic product per capita (GDPPC) per QALY in Uruguay and to 35.5 GDPPC in Bolivia. Probabilistic sensitivity analysis showed 0 percent probability that trastuzumab is CE if the willingness-to-pay threshold is one GDPPC per QALY, and remained so at three GDPPC threshold except for Chile and Uruguay (4.3 percent and 26.6 percent, respectively). Trastuzumab price would need to decrease between 69.6 percent to 94.9 percent to became CE in LA. CONCLUSIONS: Although CE in other settings, trastuzumab was not CE in LA. The use of health technology assessment to prioritize resource allocation and support price negotiations is critical to making innovative drugs available and affordable in developing countries.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".