RMTD-07 LOST CHANCES: THE SYSTEMATIC EXCLUSION OF PATIENTS WITH BRAIN METASTASIS IN EARLY-PHASE ONCOLOGY TRIALS
Bibliographic record
Abstract
Abstract RATIONALE Historically, cancer trials have often excluded patients with brain metastases (BrM). This limits our understanding of CNS-specific drug efficacy. We aimed to determine the proportion of phase I clinical trials for patients with solid tumors that exclude patients with BrM. METHODS In March 2023, a systematic search of the clinicaltrials.gov website was performed. Results are described as frequencies and compared using the Pearson’s chi-square or Cochran-Armitage tests. RESULTS 1,714 phase I trials were identified and 990 met inclusion criteria. Most trials spanned several tumor types (n=659, 66.6%) and were registered between 2000- 2023 (n=884, 89.3%). Trials were mainly conducted in Asia (n=95, 9.6%), Europe (n=112, 11.3%), and North America (n=619, 62.5%). Categories of investigational agents were: targeted therapy (n=496, 50.1%), cytotoxic chemotherapy (n=118, 11.9%), immunotherapy (n=73, 7.37%); the most common combinations included chemotherapy plus targeted therapy (n=265, 26.8%) and chemotherapy plus immunotherapy (n=14, 1.4%). Patients with BrM were included in 25.1% (n=248) trials, included under certain conditions in 53.6% (n= 521), and excluded in the remaining 22.3% (n=221) of trials. Recent trials (2015-2019) were less likely to exclude patients with BrM compared to trials conducted between 2000-2004 (18% vs 38%, p=0.003). Exclusion of patients with BrM was less common in trials focusing on melanoma (16%), breast (15%) and lung (14%) cancer. Trials involving the use of cytotoxic chemotherapy were significantly more likely to exclude patients with BrM (n=58, 49%) than those employing targeted therapy (n= 110, 22%) or immunotherapy (n=15, 21%) (p=0.016). Trial location and stage of disease were not associated with exclusion of patients with BrM. CONCLUSION Recent phase I trials, particularly those evaluating the use of targeted therapy and/or immunotherapy, have a low rate of exclusion of patients with BrM compared to previous cytotoxic trials. However, many opportunities to test drugs with potential CNS efficacy are still lost.
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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 | 0.298 | 0.487 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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; the direct Gemma label and the distilled Codex classifier 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".