Use of Expansion Cohorts in Phase I Trials and Probability of Success in Phase II for 381 Anticancer Drugs
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Bibliographic record
Abstract
Abstract Purpose: Evaluate the association between the use of phase I expansion cohorts (ECs) and drug performance in phase II as well as time to approval by the FDA. Experimental Design: We performed a systematic search of MEDLINE for single-agent dose-finding adult oncology phase I trials published in 2006 to 2011 and subsequent phase II trials. Successful phase II trials were those that met their primary endpoints. Dates of approval were obtained from the Drugs@FDA website in April 2014. A logistic regression model was used to determine the associations between variables and success in phase II. Results: We identified 533 phase I trials evaluating 381 drugs; 112 drugs had at least one phase I trial with an expansion cohort. Phase I trials with expansion cohorts of two to 20 patients were associated with a higher rate of successful phase II trials than those with no expansion cohort [48% vs. 27%; OR, 2.1; 95% confidence interval (CI), 1.1–4.0; P = 0.037]. Phase II success rates were the same for expansion cohort with two to 20 and more than 20 patients (48% vs. 52%). Other positive associations were disease-specific trials (OR, 1.7; 95% CI, 1.0–2.9; P = 0.037), industry sponsorship (OR, 2.9; 95% CI, 1.5–5.7; P = 0.0024), and response rate of 6% to 20% (OR, 2.89; 95% CI, 1.6–5.2; P = 0.0007). Drugs tested in phase I trials with expansion cohorts had a higher rate of 5-year approval (19% vs. 5%; HR, 4.4; 95% CI, 2.2–8.8; P < 0.001). Conclusions: The use of expansion cohorts in phase I trials was associated with success of subsequent phase II trials. However, confounders may play a role in this association. Clin Cancer Res; 23(15); 4020–6. ©2017 AACR.
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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 | 0.096 | 0.663 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 it