Ripretinib versus sunitinib in gastrointestinal stromal tumor: ctDNA biomarker analysis of the phase 3 INTRIGUE trial
Bibliographic record
Abstract
INTRIGUE was an open-label, phase 3 study in adult patients with advanced gastrointestinal stromal tumor who had disease progression on or intolerance to imatinib and who were randomized to once-daily ripretinib 150 mg or sunitinib 50 mg. In the primary analysis, progression-free survival (PFS) with ripretinib was not superior to sunitinib. In clinical and nonclinical studies, ripretinib and sunitinib have demonstrated differential activity based on the exon location of KIT mutations. Therefore, we hypothesized that mutational analysis using circulating tumor DNA (ctDNA) might provide further insight. In this exploratory analysis (N = 362), baseline peripheral whole blood was analyzed by a 74-gene ctDNA next-generation sequencing-based assay. ctDNA was detected in 280/362 (77%) samples with KIT mutations in 213/362 patients (59%). Imatinib-resistant mutations were found in the KIT ATP-binding pocket (exons 13/14) and activation loop (exons 17/18). Mutational subgroup assessment showed 2 mutually exclusive populations with differential treatment effects. Patients with only KIT exon 11 + 13/14 mutations (ripretinib, n = 21; sunitinib, n = 20) had better PFS with sunitinib versus ripretinib (median, 15.0 versus 4.0 months). Patients with only KIT exon 11 + 17/18 mutations (ripretinib, n = 27; sunitinib, n = 25) had better PFS with ripretinib versus sunitinib (median, 14.2 versus 1.5 months). The results of this exploratory analysis suggest ctDNA sequencing may improve the prediction of the efficacy of single-drug therapies and support further evaluation of ripretinib in patients with KIT exon 11 + 17/18 mutations. ClinicalTrials.gov identifier: NCT03673501.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".