Efficacy, safety, tolerability and price of newly approved drugs in solid tumors.
Bibliographic record
Abstract
e18336 Background: New anti-cancer drugs utilize diverse mechanisms of action. Here we evaluate their differential efficacy, safety, tolerability and price. Methods: Drugs approved for the treatment of solid tumors between 2000 and 2015 were identified and analyzed in subgroups: agents targeting oncogenes or dysregulated pathways (group 1), anti-angiogenic drugs (group 2), immunotherapy (group 3), and chemotherapy (group 4). Hazard ratios (HRs) were extracted from the reports of randomized trials supporting registration and pooled in a meta-analysis. Odds ratios (ORs) for rates of toxic death, treatment discontinuation and grade 3-4 toxicity were compared relative to control groups. The Micromedex Red Book was used to calculate the monthly price of each agent. Results: Analysis included 74 studies comprising 48,527 patients. Progression-free survival (PFS) was improved to a lesser degree with groups 3 and 4 than with groups 1 and 2, (pooled HR:0.54, 0.56, 0.63, and 0.76 for groups 1–4 respectively, p for difference < 0.001). Compared to PFS, there was a lower magnitude of improvement overall survival in all groups and the degree of benefit was less for group 4 than for other groups (pooled HR:0.77, 0.78, 0.68, and 0.83 for groups 1–4 respectively, p for difference = 0.007). Compared to control groups in individual trials, immunotherapy was associated with better safety and tolerability than other groups. Drug prices have increased over time with no statistically significant difference between groups. There was limited to no correlation between drug pricing and efficacy. Conclusions: Compared to control groups, chemotherapy improves efficacy to a lesser degree than the other groups. Immunotherapy appears to have better safety and tolerability profile compared to other cancer therapies. Market price of drugs is not related to efficacy.
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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 | 0.011 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.006 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".