Evaluation of soluble KIT (sKIT) as a potential surrogate marker for TTP in sunitinib malate (SU)-treated patients (pts) with advanced GIST
Bibliographic record
Abstract
10007 Background: SU is an oral, multitargeted tyrosine kinase inhibitor of KIT, PDGFRs, VEGFRs, RET and FLT3, approved multinationally for the treatment of imatinib (IM)-resistant/-intolerant GIST. Preliminary analysis in a SU phase I/II GIST study suggested that a decline in plasma sKIT levels may correlate with measures of clinical benefit. We evaluated the potential of sKIT as a surrogate marker for TTP using samples obtained in a randomized, double-blind, placebo-controlled phase III study of SU in pts with IM-resistant/-intolerant GIST, clinical results of which have been reported previously. Methods: 312 pts were randomized (2:1) to receive SU 50 mg (n=207) or placebo (n=105) daily in 6-wk cycles (4 wks on treatment, 2 wks off), respectively. The primary endpoint was TTP as per RECIST. Levels of sKIT in plasma samples were measured in cycle 1 on days 1, 14 and 28 and in cycles 2 and 3 on days 1 and 28 using a performance-validated ELISA. Prentice Criterion, Cox models and the Proportion of Treatment Effect (PTE) were used to analyze the results (PTE of 1 = ideal surrogate). Results: Numbers of pts with matched pairs of baseline and on-study plasma samples varied from 228 pts at cycle 1, day 14 to 106 pts at the end of cycle 3. After 4 wks of treatment (cycle 1, day 28), plasma sKIT levels began to exhibit a significant decrease (P<0.0001) in response to SU treatment; at the same time, changes in the level of sKIT (decreases vs. increases) also became indicators of TTP (HR=0.53; 95% CI, 0.37–0.75; P=0.0003), with decreases associated with longer TTP. This trend continued throughout the sampling period, with the effect persisting off treatment. Although the impact of SU on plasma sKIT levels continued to be seen after 2 cycles, sKIT changes became a better indicator of TTP than initial treatment group by cycle 2, day 28 (PTE = 0.62; HR=0.51; 95% CI, 0.38–0.69; P<0.0001), and at cycle 3, day 1 (PTE = 0.64; HR=0.42; 95% CI, 0.29–0.60; P<0.0001). Conclusion: These preliminary findings suggest that circulating sKIT may be a surrogate marker for TTP in GIST pts after 2 cycles of SU treatment. Further studies are warranted to confirm these findings and to establish whether sKIT can be used as a general surrogate marker of clinical outcomes in GIST pts with SU or other therapies. [Table: see text]
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".