Review of Phase II Trial Designs Used in Studies of Molecular Targeted Agents: Outcomes and Predictors of Success in Phase III
Bibliographic record
Abstract
PURPOSE: Because the appropriate design and end points for phase II evaluation of targeted anticancer agents are unclear, we undertook a review of recent reports of phase II trials of targeted agents to determine the types of designs used, the planned end points, the outcomes, and the relationship between trial outcomes and regulatory approval. METHODS: We retrieved reports of single-agent phase II trials in six solid tumors for 19 targeted drugs. For each, we abstracted data regarding planned design and actual results. Response rates were examined for any relationship to eventual success of the agents, as determined by US Food and Drug Administration approval for at least one indication. RESULTS: Eighty-nine trials were identified. Objective response was the primary or coprimary end point in the majority of trials (61 of 89 trials). Fourteen reports were of randomized studies generally evaluating different doses of agents, not as controlled experiments. Enrichment for target expression was uncommon. Objective responses were seen in 38 trials; in 19 trials, response rates were more than 10%, and in eight, they were more than 20%. Agents with high response rates tended to have high nonprogression rates; renal cell carcinoma was the exception to this. Higher overall response rates were predictive of regulatory approval in the tumor types reviewed (P = .005). CONCLUSION: In practice, phase II design for targeted agents is similar to that for cytotoxics. Objective response seems to be a useful end point for screening new targeted agents because, in our review, its observation predicted for eventual success. Improvements in design are recommended, as is more frequent inclusion of biological questions as part of phase II trials.
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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 | 0.127 | 0.420 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.010 | 0.013 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".