Pivotal studies of pharmacotherapies approved by the United States Food and Drug Administration for the treatment of cancer: A systematic review.
Bibliographic record
Abstract
e23125 Background: The development of pharmacotherapies for cancer treatment has increased significantly. However, an assessment of approvals by the US Food and Drug Administration (FDA) and sample sizes for pivotal studies leading to approval has not yet been conducted. Our aim was to determine the number of pharmacotherapies approved by the FDA for people with cancer and assess the characteristics of studies, including sample size. Methods: We developed a web scraper to collect approved pharmacotherapies for cancer treatments from the FDA website until December 31, 2024. Pharmacotherapies with different routes of administration (i.e., intravenous or a previously approved oral formulation of the same pharmacotherapy) and combinations of previously approved pharmacotherapies were excluded. For each pharmacotherapy, we noted: the pivotal study as per the product monograph; the proposed sample size from the study protocol; and the final sample size of the completed study. We recorded the type of pharmacotherapy (chemotherapy, hormonal therapy, immunotherapy, or targeted therapy) and study design (phase 1, 2, or 3). Regression analyses and data discretisation were conducted to identify trends in sample size. Type I error was set at 0.05. Quality assessment was conducted. OSF Registration DOI: 10.17605/OSF.IO/KVA23. Results: We identified 255 pharmacotherapies: 49.0% were targeted therapies, 23.9% chemotherapies, and 18.4% immunotherapies. A larger proportion of recent novel pharmacotherapies were targeted therapies, compared to previous decades (59.7% in 2020 to 2024 vs 12.0% in 1990 to 1999). The mean and median sample size were 386 (SD 361) and 290 (IQR 427). Three-quarters (75.3%) of studies were at low risk of bias. Table 1 shows that sample sizes were larger in studies since 1990, but no difference from 1990 onwards. Stratified analysis by study design reports phase 2 studies between 1970 and 1979 had smaller median sample sizes than those since 1990; there was no difference among phase 3 studies. For 165 studies reporting proposed sample sizes, these were lower from 2020 to 2024 than from 2010 to 2019. Conclusions: There was a substantial increase in sample size in the 1990s, likely driven by new policies and legislation. There has since been no significant increase, likely due to increasing proportion of novel pharmacotherapies being targeted therapies, employing biomarker-defined subpopulations and modern trial designs such as basket and umbrella studies that require smaller proposed samples. Year Median IQR Q1, Q3 Mean SD 1950-1959 (n = 6) 61 86 21, 107 66.3 52.6 1960-1969 (n = 9) 40 37 33, 70 54.4 36.8 1970-1979 (n = 9) 48 29 46, 75 104.9 157.6 1980-1989 (n = 8) 169 421 74, 495 290.6 318.2 1990-1999 (n = 25) 407 561 222, 764 510.5 398.9 2000-2009 (n = 39) 329 344 153, 497 398.4 343.3 2010-2019 (n = 92) 350 460 190, 650 461.5 403.1 2020-2024 (n = 67) 290 386 126, 512 350.9 292.6
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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 | 0.029 | 0.092 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.009 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".