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Record W4308026783 · doi:10.1136/jitc-2022-005780

FRACTION-RCC: nivolumab plus ipilimumab for advanced renal cell carcinoma after progression on immuno-oncology therapy

2022· article· en· W4308026783 on OpenAlexaff
Toni K. Choueiri, Harriet M. Kluger, Saby George, Scott S. Tykodi, Timothy M. Kuzel, Ruth Perets, Suresh Nair, Giuseppe Procopio, Michael A. Carducci, Vincent Castonguay, Edmund Folefac, Chung‐Han Lee, Sebastién J. Hotte, Shruti Shally Saggi, Chung‐Wei Lee, Heshani Desilva, Prabhu Bhagavatheeswaran, Robert J. Motzer, Bernard Escudier

Bibliographic record

VenueJournal for ImmunoTherapy of Cancer · 2022
Typearticle
Languageen
FieldMedicine
TopicRenal cell carcinoma treatment
Canadian institutionsMcGill UniversityJewish General HospitalUniversité LavalJuravinski Cancer CentreUniversité du Québec à Montréal
FundersNational Center for Advancing Translational SciencesFoundation MedicineEMD SeronoGenentechEuropean Society for Medical OncologyShionogiNateraSeagenPfizerIncyteJounce TherapeuticsAstellas PharmaEisaiOno PharmaceuticalEli Lilly and CompanyNational Comprehensive Cancer NetworkNational Cancer InstituteGilead SciencesCalithera BiosciencesCelldex TherapeuticsIpsenArray BioPharmaKaryopharm TherapeuticsExelixisSanofiMemorial Sloan-Kettering Cancer CenterDana-Farber/Harvard Cancer CenterBristol-Myers SquibbAstraZenecaAmerican Society of Clinical OncologyGlaxoSmithKlineAmgenDana-Farber Cancer Institute
KeywordsNivolumabIpilimumabMedicineInternal medicineOncologyTolerabilityRenal cell carcinomaDiscontinuationCombination therapyHazard ratioClinical endpointProgression-free survivalAdverse effectClinical trialCancerImmunotherapyChemotherapyConfidence interval

Abstract

fetched live from OpenAlex

BACKGROUND: The role and sequencing of combination immuno-oncology (IO) therapy following progression on or after first-line IO therapy has not been well-established. The Fast Real-time Assessment of Combination Therapies in Immuno-ONcology (FRACTION) program is an open-label, phase 2 platform trial designed to evaluate multiple IO combinations in patients with advanced renal cell carcinoma (aRCC) who progressed during or after prior IO therapy. Here, we describe the results for patients treated with nivolumab plus ipilimumab. For enrollment in track 2 (reported here), patients with histologically confirmed clear cell aRCC, Karnofsky performance status ≥70%, and life expectancy ≥3 months who had previously progressed after IO (anti-programmed death 1 (PD-1), anti-programmed death-ligand 1 (PD-L1), or anti-cytotoxic T-lymphocyte antigen 4 (CTLA-4)) therapy were eligible. Previous treatment with anti-CTLA-4 therapy plus anti-PD-1/PD-L1 therapy precluded eligibility for enrollment in the nivolumab plus ipilimumab arm. Patients were treated with nivolumab 3 mg/kg plus ipilimumab 1 mg/kg every 3 weeks for four doses, followed by nivolumab 480 mg every 4 weeks for up to 2 years or until progression, toxicity, or protocol-specified discontinuation. The primary outcome measures were objective response rate (ORR), duration of response (DOR), and progression-free survival (PFS) rate at 24 weeks. Secondary outcomes were safety and tolerability up to 2 years. Overall survival (OS) was a tertiary/exploratory endpoint. Overall, 46 patients were included with a median follow-up of 33.8 months. The ORR was 17.4% (95% CI, 7.8 to 31.4) with eight (17.4%) patients achieving partial response. Stable disease was achieved in 19 (41.3%) patients, while 14 (30.4%) had progressive disease. Median DOR (range) was 16.4 (2.1+ to 27.0+) months. The PFS rate at 24 weeks was 43.2%, and median OS was 23.8 (95% CI, 13.2 to not reached) months. Grade 3-4 immune-mediated adverse events were reported in seven (15.2%) patients. No treatment-related deaths were reported. Patients with aRCC treated with nivolumab plus ipilimumab may derive durable clinical benefit after progression on previous IO therapies, including heavily pretreated patients, with a manageable safety profile that was consistent with previously published safety outcomes. These outcomes contribute to the knowledge of optimal sequencing of IO therapies for patients with aRCC with high unmet needs. TRIAL REGISTRATION NUMBER: NCT02996110.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.024
GPT teacher head0.352
Teacher spread0.328 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized 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

Citations38
Published2022
Admission routes1
Has abstractyes

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