Uptake of aromatase inhibitors (AI) and trastuzumab (T) during the first 5 years after market introduction. A North American and European comparison
Bibliographic record
Abstract
6536 Background: During the 1990s both 3rd generation AIs (anastrozole; A, exemestane; E and letrozole; L) as well as T got their first global approval in metastatic breast cancer/MBC (A in 1995; E in 1999; L in 1996; T in 1998). Both AIs and T have later been approved for early breast cancer (EBC). The report focuses on similarities and differences in the usage during the first five years of use of the drugs in Europe and North America. Methods: Based on data from IMS Health, sales/uptake of AIs and T were studied in Denmark; DK, Germany; GE, Norway; NO, Sweden; SE, Switzerland; CH and the UK; UK, as well as in Canada; CA and USA; US. The uptake, measured as accumulated sales per capita during the first five years after first sale (market introduction) in each country, was related to number of deaths in breast cancer in 2001 in each country. Results: GE and CH had the fastest uptake of AI in Europe. DK had low uptake, while the other countries had relatively similar uptake. The US, SE and CH had the fastest uptake of T, while UK and NO were far below other countries. Conclusions: This study reveals very different patterns of uptake of new innovative breast cancer drugs, both between AIs and T and within the group of AIs. While US were relatively slow with the introduction of AIs, they were at the top with CH and SE with the introduction of T. Most remarkable is the slow introduction of T in UK and Norway. The US, GE, SE and CH were on top with respect to “investment” in new targeted drugs for breast cancer during 1996–2005. Sales in euros per patient dying of breast cancer of AIs and trastuzumab during the first 5 y anastrozole exemestane letrozole AI(A+E+L) trastuzumab AI/T AI+T US 3 923 2 050 1 987 7 960 21 108 0.38 29 067 CA 4 132 1 657 1 804 7 593 11 548 0.66 19 142 DK 535 1 428 2 940 4 903 12 119 0.40 17 022 GE 3 526 3 639 2 891 9 683 11 106 0.87 20 789 NO 4 387 2 990 802 8 179 8 671 0.94 18 337 SE 4 555 1 403 984 6 943 15 184 0.46 22 127 CH 2 810 3 073 4 663 10 546 21 770 0.48 32 316 UK 5 027 1 235 209 6 470 5 786 1.12 12 257 Author Disclosure Employment or Leadership Consultant or Advisory Role Stock Ownership Honoraria Research Expert Testimony Other Remuneration Pfizer, Roche AstraZeneca, Novartis, Roche
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".