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Record W4225464106 · doi:10.1002/cncr.34180

Conditional survival and long‐term efficacy with nivolumab plus ipilimumab versus sunitinib in patients with advanced renal cell carcinoma

2022· article· en· W4225464106 on OpenAlexaff
Robert J. Motzer, David F. McDermott, Bernard Escudier, Mauricio Burotto, Toni K. Choueiri, Hans J. Hammers, Philippe Barthélémy, Elizabeth R. Plimack, Camillo Porta, Saby George, Thomas Powles, Frede Donskov, Howard Gurney, Christian Kollmannsberger, Marc‐Oliver Grimm, Carlos H. Barrios, Yoshihiko Tomita, Daniel Castellano, Viktor Grünwald, Brian I. Rini, M. Brent McHenry, Chung‐Wei Lee, Jennifer L. McCarthy, Flavia Ejzykowicz, Nizar M. Tannir

Bibliographic record

VenueCancer · 2022
Typearticle
Languageen
FieldMedicine
TopicRenal cell carcinoma treatment
Canadian institutionsBC Cancer Agency
FundersCilagUniversity of Texas MD Anderson Cancer CenterGenentechIpsenPharmaMarEuropean Society for Medical OncologyShionogiAstellas PharmaEisaiHalozymeMirati TherapeuticsNational Institutes of HealthMylanArrowhead PharmaceuticalsLes Laboratories Pierre FabreIncytePfizerDaiichi Sankyo EuropeNational Cancer InstituteLEO PharmaIntuitive SurgicalMerck KGaATaiho PharmaceuticalMemorial Sloan-Kettering Cancer CenterCelgenePTC TherapeuticsExelixisSanofiAmgenEUSA PharmaAstraZenecaOno PharmaceuticalEli Lilly and CompanyBristol-Myers Squibb
KeywordsMedicineIpilimumabSunitinibHazard ratioNivolumabRenal cell carcinomaInternal medicineClinical endpointOncologyProgression-free survivalKidney cancerProportional hazards modelSurvival analysisRandomized controlled trialCancerOverall survivalConfidence intervalImmunotherapy

Abstract

fetched live from OpenAlex

BACKGROUND: Conditional survival estimates provide critical prognostic information for patients with advanced renal cell carcinoma (aRCC). Efficacy, safety, and conditional survival outcomes were assessed in CheckMate 214 (ClinicalTrials.gov identifier NCT02231749) with a minimum follow-up of 5 years. METHODS: Patients with untreated aRCC were randomized to receive nivolumab (NIVO) (3 mg/kg) plus ipilimumab (IPI) (1 mg/kg) every 3 weeks for 4 cycles, then either NIVO monotherapy or sunitinib (SUN) (50 mg) daily (four 6-week cycles). Efficacy was assessed in intent-to-treat, International Metastatic Renal Cell Carcinoma Database Consortium intermediate-risk/poor-risk, and favorable-risk populations. Conditional survival outcomes (the probability of remaining alive, progression free, or in response 2 years beyond a specified landmark) were analyzed. RESULTS: The median follow-up was 67.7 months; overall survival (median, 55.7 vs 38.4 months; hazard ratio, 0.72), progression-free survival (median, 12.3 vs 12.3 months; hazard ratio, 0.86), and objective response (39.3% vs 32.4%) benefits were maintained with NIVO+IPI versus SUN, respectively, in intent-to-treat patients (N = 550 vs 546). Point estimates for 2-year conditional overall survival beyond the 3-year landmark were higher with NIVO+IPI versus SUN (intent-to-treat patients, 81% vs 72%; intermediate-risk/poor-risk patients, 79% vs 72%; favorable-risk patients, 85% vs 72%). Conditional progression-free survival and response point estimates were also higher beyond 3 years with NIVO+IPI. Point estimates for conditional overall survival were higher or remained steady at each subsequent year of survival with NIVO+IPI in patients stratified by tumor programmed death ligand 1 expression, grade ≥3 immune-mediated adverse event experience, body mass index, and age. CONCLUSIONS: Durable clinical benefits were observed with NIVO+IPI versus SUN at 5 years, the longest phase 3 follow-up for a first-line checkpoint inhibitor-based combination in patients with aRCC. Conditional estimates indicate that most patients who remained alive or in response with NIVO+IPI at 3 years remained so at 5 years.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
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 science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.254
Teacher spread0.235 · 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 designObservational
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

Citations263
Published2022
Admission routes1
Has abstractyes

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