MétaCan
Menu
Back to cohort

Nivolumab plus ipilimumab (NIVO+IPI) vs sunitinib (SUN) for first-line treatment of advanced renal cell carcinoma (aRCC): Long-term follow-up data from the phase 3 CheckMate 214 trial.

2024· article· en· W4391303220 on OpenAlexaff
Nizar M. Tannir, Bernard Escudier, David F. McDermott, Mauricio Burotto, Toni K. Choueiri, Hans J. Hammers, Elizabeth R. Plimack, Camillo Porta, Saby George, Thomas Powles, Frede Donskov, Michael B. Atkins, Christian Kollmannsberger, Marc‐Oliver Grimm, Yoshihiko Tomita, Brian I. Rini, Ruiyun Jiang, Heshani Desilva, Chung‐Wei Lee, Robert J. Motzer

Bibliographic record

VenueJournal of Clinical Oncology · 2024
Typearticle
Languageen
FieldMedicine
TopicRenal cell carcinoma treatment
Canadian institutionsBC Cancer Agency
Fundersnot available
KeywordsMedicineNivolumabSunitinibIpilimumabInternal medicineRenal cell carcinomaOncologyImmunotherapyCancer

Abstract

fetched live from OpenAlex

363 Background: First-line NIVO+IPI has provided substantial long-term survival benefits over SUN in patients (pts) with aRCC in CheckMate 214. We report survival, response per independent radiology review committee (IRRC) and safety after 6 y minimum (80 mo median) follow-up in all randomized pts, by IMDC risk and in pts with overall survival (OS) ≥ 6 y (long-term survivors; LTS). Longer follow-up data (minimum, 7.5 y) will be presented. Methods: Pts with clear cell aRCC were randomized 1:1 to NIVO 3 mg/kg + IPI 1 mg/kg Q3W×4 then NIVO 3 mg/kg Q2W vs SUN 50 mg QD for 4 wk on, 2 wk off. Endpoints: OS, progression-free survival (PFS) and objective response rate (ORR; both per IRRC using RECIST v1.1) in IMDC intermediate/poor risk (IP; primary), intent-to-treat (ITT; secondary) and favorable risk (FAV; exploratory) pts. Exploratory outcomes in LTS pts were assessed post hoc. Results: OS with NIVO+IPI vs SUN remained superior in ITT (HR 0.72) and IP (HR 0.68) pts; OS benefits were similar between arms in FAV pts (HR 0.87; Table). Median PFS was consistent with previous reports. ORR per IRRC was higher with NIVO+IPI vs SUN, with more ongoing responses in ITT (60% vs 50%) and IP (60% vs 50%) pts. In FAV pts, ORR was lower with NIVO+IPI vs SUN, yet more responses were ongoing (59% vs 52%, respectively). Median duration of response (DOR) was longer and complete response (CR) rate was higher with NIVO+IPI vs SUN regardless of IMDC risk. Incidence of any and grade 3-4 treatment-related adverse events remained largely unchanged. No new drug-related deaths occurred in either arm since the previous database lock. In the LTS subgroup (NIVO+IPI, n = 208; SUN, n = 151), ORR was higher (66% vs 53%), more pts had a CR (27% vs 9%) and fewer progressed (4% vs 11%) with NIVO+IPI vs SUN. Median DOR was longer with NIVO+IPI (n = 137) vs SUN (n = 80) among LTS with confirmed response (76 vs 40 mo). Updated survival, response and safety data with 7.5 y minimum follow-up, along with additional subgroup analyses, will be presented. Conclusions: NIVO+IPI demonstrated long-term survival and more durable response benefits vs SUN in ITT and IP pts. CR rates were higher and median DOR was longer with NIVO+IPI vs SUN regardless of IMDC risk group, and in LTS pts. No new safety signals emerged. Clinical trial information: NCT02231749 . [Table: see text]

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)0.001
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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.256
GPT teacher head0.477
Teacher spread0.221 · 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

Citations46
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Clinical OncologySame topicRenal cell carcinoma treatmentFrench-language works237,207