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INTRIGUE: A phase III, randomized, open-label study to evaluate the efficacy and safety of ripretinib versus sunitinib in patients with advanced gastrointestinal stromal tumor previously treated with imatinib

2022· article· en· W4206922330 on OpenAlexaff
Michael C. Heinrich, Robin L. Jones, Hans Gelderblom, Suzanne George, Patrick Schöffski, Margaret von Mehren, John Zalcberg, Yoon‐Koo Kang, Albiruni Ryan Abdul Razak, Jonathan C. Trent, Steven Attia, Axel Le Cesne, Ying Su, Julie Nicole Meade, Tao Wang, Matthew L. Sherman, Rodrigo Ruiz‐Soto, Jean‐Yves Blay, Sebastian Bauer

Bibliographic record

VenueJournal of Clinical Oncology · 2022
Typearticle
Languageen
FieldMedicine
TopicGastrointestinal Tumor Research and Treatment
Canadian institutionsPrincess Margaret Cancer Centre
FundersDeciphera Pharmaceuticals
KeywordsMedicineSunitinibGiSTImatinibInternal medicineClinical endpointPopulationImatinib mesylateInterim analysisOncologyRandomizationTyrosine-kinase inhibitorGastroenterologySurgeryRandomized controlled trialCancerStromal cell

Abstract

fetched live from OpenAlex

359881 Background: Sunitinib is approved for advanced gastrointestinal stromal tumor (GIST) after imatinib failure. Ripretinib, a broad-spectrum KIT and PDGFRA switch-control tyrosine kinase inhibitor (TKI), is indicated for the treatment of adult patients (pts) with GIST who received prior treatment with 3 or more TKIs, including imatinib. We compared the efficacy and safety of ripretinib vs sunitinib in pts with advanced GIST who progressed on or were intolerant to imatinib. Methods: This multicenter, global, randomized, open-label phase 3 study (NCT03673501) enrolled adult pts with GIST who progressed on or had intolerance to imatinib. Pts were randomized 1:1 to ripretinib 150 mg once daily (QD) or sunitinib 50 mg QD (4 wks on/2 wks off). Randomization was stratified by KIT mutational status and imatinib intolerance. The primary endpoint was progression-free survival (PFS) by independent radiologic review (IRR) using modified RECIST version 1.1. Key secondary endpoints were objective response rate (ORR) by IRR and overall survival (OS). Hierarchical testing was performed for primary and key secondary endpoints in a prespecified sequence; testing pts with a KIT exon 11 primary mutation (Ex11 intention-to-treat [ITT] population) preceded the all-patient (AP) ITT population. Data cutoff was 1 Sep 2021; final analyses of PFS and ORR and the first interim analysis of OS were conducted. Results: A total of 453 pts were randomized to ripretinib (n = 226; Ex11 ITT, n = 163) or sunitinib (n = 227; Ex11 ITT, n = 164). Median age was 60 yrs (range 18–88) and most pts were white (66.2%) males (62.0%). PFS was not statistically different between ripretinib and sunitinib in the Ex11 ITT (hazard ratio [HR] 0.88, 95% CI 0.66, 1.16; P = 0.36; median 8.3 vs 7.0 mos) or in the AP populations (HR 1.05, 95% CI 0.82, 1.33; P = 0.72; median 8.0 vs 8.3 mos). ORR was numerically higher for ripretinib vs sunitinib in the Ex11 ITT (23.9% vs 14.6%; difference 9.3%, 95% CI 0.7, 17.8; nominal P = 0.03) and AP ITT populations (21.7% vs 17.6%; difference 4.2%, 95% CI −3.2, 11.5; nominal P = 0.27). OS data was highly immature; median OS was not reached in either arm. Fewer pts in the ripretinib arm experienced Grade 3-4 (G3-4) treatment-emergent adverse events (TEAEs) vs sunitinib (41.3% vs 65.6%). Among G3-4 TEAEs with a difference ≥5% between arms, ripretinib had fewer events vs sunitinib (hypertension [8.5% vs 26.7%], palmar-plantar erythrodysesthesia [1.3% vs 10.0%], neutropenia [0% vs 6.3%], and neutrophil count decreased [0% vs 7.2%]). Conclusions: The PFS in both arms was longer than PFS achieved by sunitinib in its pivotal phase 3 trial. While the PFS for ripretinib did not meet the primary endpoint of superiority vs sunitinib, meaningful clinical activity and fewer G3-4 TEAEs were observed in pts with advanced GIST treated with ripretinib after imatinib failure. Clinical trial information: NCT03673501.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.279
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.098
GPT teacher head0.469
Teacher spread0.372 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designRandomized trial
Domainnot available
GenreEmpirical

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".

Quick stats

Citations18
Published2022
Admission routes1
Has abstractyes

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