Assessing population diversity in phase <scp>III</scp> trials of cancer drugs supporting Food and Drug Administration approval in solid tumors
Bibliographic record
Abstract
Our study aimed to assess inequities in the clinical trial participation for the selected patient groups. We searched the Food and Drug Administration (FDA) database and extracted phase-III clinical trial data from MEDLINE for each approved drug by the FDA between January 1, 2006, and June 30, 2020. We analyzed the inclusion/exclusion criteria, participation according to gender, ethnic group, performance score, the positivity of HBV and HCV, and HIV, having comorbidities and brain metastasis. We compared the findings with that of the general population by retrieving data from the Surveillance, Epidemiology and End Results (SEER) database. We identified 142 phase III pivotal oncology trials that enrolled 105 397 patients. The proportion of female patients in trials was lower than their relative prevalence in the general population from SEER region (36% vs 49.6%, P < .001). The rates of black patients included were lower than their relative prevalence from SEER region (2.1% vs 9.8%, P < .001). 1.3% and 0.8% of patients had HBV and HCV infections, respectively. The patients' numbers with organ dysfunction were not established due to insufficient data from clinical trials. 1.6% of all patients had controlled brain metastasis. Black patients, women and patients with brain metastasis or with HBV and HCV were underrepresented. Our study underscores the importance of expanding the inclusion/exclusion criteria of pivotal oncology trials to be more representative of patients seen in clinical practice.
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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 | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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; a candidate call from one teacher head, 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".