Phase I Trial of 17-Allylamino-17-Demethoxygeldanamycin in Patients with Advanced Cancer
Bibliographic record
Abstract
PURPOSE: To define the maximum tolerated dose (MTD), toxicities, and pharmacokinetics of 17-allylamino-17-demethoxygeldanamycin (17-AAG) when administered using continuous and intermittent dosing schedules. EXPERIMENTAL DESIGN: Patients with progressive solid tumor malignancies were treated with 17-AAG using an accelerated titration dose escalation schema. The starting dose and schedule were 5 mg/m(2) daily for 5 days with cycles repeated every 21 days. Dosing modifications based on safety, pharmacodynamic modeling, and clinical outcomes led to the evaluation of the following schedules: daily x 3 repeated every 14 days; twice weekly (days 1, 4, 8, and 11) for 2 weeks every 3 weeks; and twice weekly (days 1 and 4) without interruption. During cycle 1, blood was collected for pharmacokinetic and pharmacodynamic studies. RESULTS: Fifty-four eligible patients were treated. The MTD was schedule dependent: 56 mg/m(2) on the daily x 5 schedule; 112 mg/m(2) on the daily x 3 schedule; and 220 mg/m(2) on the days 1, 4, 8, and 11 every-21-day schedule. Continuous twice-weekly dosing was deemed too toxic because of delayed hepatotoxicity. Hepatic toxicity was also dose limiting with the daily x 5 schedule. Other common toxicities encountered were fatigue, myalgias, and nausea. This latter adverse effect may have been attributable, in part, to the DMSO-based formulation. Concentrations of 17-AAG above those required for activity in preclinical models could be safely achieved in plasma. Induction of a heat shock response and down-regulation of Akt and Raf-1 were observed in biomarker studies. CONCLUSION: The MTD and toxicity profile of 17-AAG were schedule dependent. Intermittent dosing schedules were less toxic and are recommended for future phase II studies.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".