Dose analysis of ASSURE (E2805): Adjuvant sorafenib or sunitinib for unfavorable renal carcinoma, an ECOG-ACRIN-led, NCTN phase 3 trial.
Bibliographic record
Abstract
4508 Background: E2805 is a phase III trial of sunitinib (SU), sorafenib (SOR) or placebo (PB) in patients (pts) with completely resected locally advanced renal cell carcinoma (RCC). There was no difference in DFS between the arms. Midway through the trial, starting doses were reduced. We analyzed the effect of this approach on drug dosing, toxicity and outcome. Methods: 1,943 pts stratified by risk, histology, ECOG PS, and nephrectomy type, were randomized to SU daily (4 of 6 wk cycle), SOR daily, or PB, for ≤ 1 yr. The primary endpoint was disease-free survival (DFS). After 1322 pts, starting doses of SU and SOR were reduced from 50 to 37.5 mg (25%) and from 800 to 400mg (50%), respectively, to mitigate the impact of pt discontinuation (DISC). Escalation to full dose after the first 2 cycles was mandatory when tolerated. Total dose of each agent over the entire yr, relative dose (actual/intended x 100), and number (no.) of cycles were related to DFS. Results: The redesign reduced the 3-month DISC rate from adverse events or refusal from 25%/30% in pts starting at full dose to 17%/11% in pts starting at reduced dose on SU/SOR (Gray’s p = 0.01/0.0001). Total dose did not differ between groups on either SOR (p = 0.41) or SUN (p = 0.83). Most common grade ≥ 3 adverse events were hypertension, hand-foot reaction, rash and fatigue. There was no relationship between no. of cycles received or dose intensity and DFS. Conclusions: Dose titration reduced the DISC rate but not the total dose, with no impact on overall DFS by arm. Decreased DFS with reduced-dose SOR raises concern about the differential effects of multi-kinase inhibitors across a range of doses. Clinical trial information: NCT00326898. SU SOR PB Randomized 647 649 647 Treated 629 630 632 DFS Events 265 272 270 Median DFS (yrs) 5.8 5.8 6.0 Hazard Ratio 1.01 0.98 (ref) 97.5% CI 0.83 – 1.23 0.81 – 1.20 Starting Dose Grp Pts Full 438 Red 191 Full 441 Red 189 Full 443 Red 189 SOR/PB, rel dose, % (sd) 85 (22) 91 (18) 84 (42) 91 (22) 92 (14) 93 (14) SU/PB, rel dose, % (sd) 90 (18) 93 (16) 87 (42) 93 (18) 95 (13) 95 (13) Cycles, median[range] 8 [1 –9] 9 [1 –9] 7 [1 –9] 9 [1 –9] 9 [1 –9] 9 [1 –9] 5-yr DFS (%) 55.1 56.0 56.6 29.2 55.0 55.8 97.5% CI 49.7 – 61.2 46.7 – 67.1 51.2 – 62.6 15.0 – 56.7 49.7 – 61.0 45.5 – 68.3 Hazard Ratio 0.92 1.13 0.86 1.44 ref ref
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".