A retrospective look: Industry partnership and transparency in phase III randomized clinical trials of breast cancer targeted therapies across two decades.
Bibliographic record
Abstract
580 Background: To unveil industry involvement with respect to sponsorship, authorship, and demographic shifts in the trends of randomized clinical trials for breast cancer targeted therapies over the past two decades. Methods: All randomized phase III clinical trials focusing on targeted therapies for breast cancer were systematically identified from clinicaltrials.gov and reviewed using peer-reviewed publications. Trials that focused solely on chemotherapy and hormonal therapy were excluded. SAS Enterprise Guide v7.1 was used to analyze trial characteristics, authorship, and demographic details with Chi-square and Fisher’s exact tests. Results: From 2005-2023, 998 breast cancer treatment clinical trials were identified; 110 trials were included in the final analysis. Overall, 8.2% were limited to the U.S. and Canada while 67.3% were carried out internationally. 34.5% were led by cooperative (Co-op) groups vs 65.5% by pharmaceutical industries. 19.1% of trials were published in the New England Journal of Medicine (NEJM); all NEJM published trials reported positive results and 76.2% of were industry led. In contrast, of the 4.5% of trials featured in The Lancet, only 60% showed positive findings and 60% had major industry sponsorship. The most common industry partnerships were with Roche (27.3%), Novartis (12.7%), and Pfizer (7.3%) while the most common leading Co-op group was the National Cancer Institute (7.3%). To evaluate trends, trials were split into 3 time periods based on publication dates: 2005-2011, 2012-2017, and 2018-2023. The number of trial publications increased from 13 to 43 to 54. Of the 70% of trials that reported race/ethnicity data, the proportion of White patients decreased (84.5%, 78.8%, 79.3%; p<0.001) and the proportion of Asian patients increased (8.9%, 18.4%, 16.7%; p<0.001). However, enrollment of Black (6.6%, 2.8%, 4.0%; p<0.001) and Hispanic (7.0%, 2.8%, 5.0%; p<0.001) patients remained low. There were no statistically significant changes in international participation (46.2%, 69.8%, 70.4%; p=0.22), the proportion of exclusively industry-led (46.2%, 74.4%, 63.0%; p=0.15) or Co-op group-designed trials (61.5%, 35.7%, 26.4%; p=0.10). Industry-involved data collection increased from 23.1% to 64.2% to 73.6% (p=0.01) while industry sponsored data analysis (38.5%, 61.9%, 66.0%; p=0.49) and manuscript drafting (38.5%, 66.7%, 71.7%; p=0.09) did not significantly change. Conclusions: Over time, there was a notable rise in the number of phase III clinical trials for breast cancer targeted therapies. More than 70% of these trials now engage in international collaboration. Despite this progress, there remains an underrepresentation of Black and Hispanic participants in trial enrollment. Today, nearly 70% of trials have major industry sponsorship in study design, data analysis, and manuscript preparation.
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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 | 0.045 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.008 | 0.013 |
| Insufficient payload (model declined to judge) | 0.000 | 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; 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".