Rebuttal: Are drugs too expensive in Canada? YES
Bibliographic record
Abstract
When used properly, drugs can deliver value for money, but only about 10 % of the drugs brought to market offer any substantial therapeutic value over existing medications. For example, for treating uncompli-cated hypertension, older diuretics at pennies a day have proven just as good as, if not superior to, angiotensin-converting enzyme inhibitors and calcium channel block-ers that cost more than $1 a day.1 Companies do not reflect the relative value of drugs in the prices they set. For new patented drugs mar-keted in Canada, prices are typically set at the level of the most expensive product in their therapeutic group, regardless of whether they offer any incremental thera-peutic value.2 Companies charge what they think the market will bear, not what it costs to produce the drug.3 When people are ill, cost takes second place; witness the fight to get trastuzumab (Herceptin) covered despite its $35 000 price tag.4 When drugs come off patent and generic products appear, brand-name companies still refuse to engage in price competition.5 The pharmaceutical industry typically ignores costs associated with the side effects of medications. Although there are no Canadian figures, estimates from the United States suggest that more than 100 000 deaths a year are associated with adverse effects of medications.6 Many of these problems could stem from aggres-sive promotional practices. When the heavily promoted cyclooxygenase-2 (COX-2) inhibitors were introduced in Ontario, hospital admissions for gastrointestinal bleed-ing actually rose7 despite the COX-2s ’ alleged gastroin-testinal protection. The situation with COX-2 drugs and antihypertensives illustrates the problem of relying on simplistic, uncontrolled analyses of cost savings,8 such as that of Lichtenberg referred to by Mr Williams. Mr Williams mentioned pharmaceutical companies’ investment in research and development, but neglected to point out that, as a percentage of sales, investment steadily dropped from 12.9 % in 1997 to 8.5 % in 2004.9 When basic research that actually discovers new drugs is looked at separately and tax credits are factored in,
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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; both teacher heads agree on what is shown here.
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".