Temporal trends in oncology drug revenue among the world’s major pharmaceutical companies: A 2010-2019 cohort study.
Bibliographic record
Abstract
6505 Background: In the past decade there has been a 70% increase in the number of clinical trials for cancer drugs. During this time, there has also been a substantial increase in the price of cancer drugs. It is unclear how these trends have changed the revenue landscape of major pharmaceutical companies. In this study we characterize temporal trends in cancer drug revenue relative to non-cancer drugs. Methods: This retrospective cohort study used publicly available global sales data from the 10 pharmaceutical companies with the highest annual revenue in 2019; Abbvie (AB), AstraZeneca (AZ), Bristol Myers Squibb (BMS), GlaxoSmithKline (GSK), Johnson & Johnson (JJ), Merck (M), Novartis (N), Pfizer (P), Roche (R) and Sanofi (S). We quantified the contribution of cancer drugs to net revenue for each company from 2010 – 2019 using consolidated annual financial reports (i.e. 10-K or 20-F forms). Cancer drugs were defined as those with an FDA-approved indication for anti-cancer effect or supportive care. All sales data were converted to USD and adjusted for global inflation. Trends in the percentage of company revenues accounted for by cancer drugs were assessed with the Kendall-Mann test. P-values were adjusted for multiple hypothesis testing using the Benjamini-Hochberg method. Results: During 2010-2019, cumulative annual revenue generated from cancer drugs in our cohort of companies (n = 10) increased by 96%, from $52.8 billion to $103.5 billion. The cumulative revenue from non-oncology drugs decreased by 19%, from $342.5 billion to $276.9 billion. The proportion of total revenue generated from cancer drugs grew over time; from 13% in 2010 to 27% in 2019 (p < 0.001). During 2015-2019, annual revenue for the study cohort grew by 12%: from $339.7 billion to $380.4 billion. During this period non-oncology revenues remained stagnant (mean $278.9 billion, range 276.9 – 281.9), while oncology revenues grew by 66%; from $61.4 billion to $103.5 billion. Six companies (AB, AZ, BMS, JJ, N, and P) saw substantial increases in the proportion of revenue attributable to cancer drugs. R had both the highest net revenue ($23.9 billion), and highest proportion of revenue (57%) from cancer drugs in 2010 among the cohort, similar to 2019 ($27.7 billion, 57%; p = 0.37). While not reaching significance over the total study period, M saw increases in oncology revenue from $1.5 billion in 2015 to $12.3 billion in 2019 (4% to 30% of total revenue); driven almost exclusively by sales of Pembrolizumab. Conclusions: Amongst the world’s largest pharmaceutical companies, sales revenue from cancer drugs have increased by 96% over the past decade, while revenues from non-cancer drugs have decreased by 19%. Revenues from cancer drugs accounted for 27% of company revenues in 2019. Further work is needed to understand if this massive increase in sales revenues has translated into proportional improvements in patient and population outcomes.
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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 | 0.004 |
| 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) | 0.002 | 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; 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".