Imatinib Plasma Levels Are Correlated With Clinical Benefit in Patients With Unresectable/Metastatic Gastrointestinal Stromal Tumors
Bibliographic record
Abstract
PURPOSE To study the pharmacokinetics (PK) of imatinib (IM) in patients with advanced GI stromal tumors (GISTs) treated in a randomized phase II study and to explore the potential relationship between IM plasma levels and long-term clinical outcomes. PATIENTS AND METHODS Patients were randomly assigned to receive IM at 400 mg versus 600 mg daily. IM plasma levels were analyzed in a subset of patients (n = 73) for whom PK data on day 1 and at steady-state (SS, day 29) were available. IM PK was evaluated using a population PK approach. The relationship between IM plasma exposure and clinical outcome was explored by grouping patients into quartiles according to IM trough concentration (C(min)). The clinical outcome parameters evaluated include overall objective benefit rate (OOBR; complete response plus partial response plus stable disease) time to progression (TTP), and KIT genotyping. Results IM PK exposure showed a high inter-patient variability, and clinical outcomes were correlated with IM trough levels at SS. The median TTP was 11.3 months for patients in the lowest C(min) quartile (Q1, < 1,110 ng/mL) compared with more than 30 months for Q2 to Q4 (P = .0029). OOBR was also inferior in Q1 patients. In patients with GIST with KIT exon 11 mutations (n = 39), the OOBR was 67% for Q1 patients versus 100% for all others (P = .001). CONCLUSION In patients with advanced GIST, IM trough levels at SS were associated with clinical benefit. Patients with IM C(min) below 1,100 ng/mL showed a shorter TTP and lower rate of clinical benefit (OOBR). Further studies are justified to test whether monitoring IM plasma levels might optimize clinical outcomes for patients with GIST.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.000 |
| 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".