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Efficacy of second line (2L) treatment with tivozanib (Tivo) as monotherapy or with nivolumab (Nivo) in patients (pts) with metastatic renal cell carcinoma (mRCC) previously treated with an immune checkpoint inhibitor (ICI) combination of ipilimumab (Ipi)/Nivo or vascular endothelial growth factor receptor-tyrosine kinase inhibitor (VEGFR-TKI)/ICI in the phase 3 TiNivo-2 study.

2025· article· en· W4410823043 on OpenAlexaff
Alex Chehrazi‐Raffle, Robert J. Motzer, Katy Beckermann, Philippe Barthélémy, Roberto Iacovelli, Sheik Emambux, Javier Molina Cerrillomd, Benjamin Garmezy, Pedro C. Barata, Rana R. McKay, Hans J. Hammers, Daniel Yick Chin Heng, Bo Jin, Claudia Lebedinsky, Edgar Braendle, Bradley A. McGregor, Laurence Albigès, Toni K. Choueiri

Bibliographic record

VenueJournal of Clinical Oncology · 2025
Typearticle
Languageen
FieldMedicine
TopicRenal cell carcinoma treatment
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsNivolumabMedicineRenal cell carcinomaMetastatic melanomaOncologyImmune checkpointInternal medicineIpilimumabCancer researchImmunotherapyCancer

Abstract

fetched live from OpenAlex

4540 Background: In TiNivo-2, the addition of Nivo to Tivo did not prolong progression-free survival (PFS) relative to Tivo alone (Choueiri, Lancet 2024). To assess study outcomes in the context of contemporary treatment sequencing, a subset of pts treated in the 2L who failed 1L Ipi/Nivo or VEGFR-TKI/ICI therapy was evaluated. Methods: Pts were randomized 1:1 to receive Tivo once daily for 21/28 days at either 1.34mg alone or at 0.89 mg with Nivo at 480 mg by IV on day 1 of each 28-day cycle. We characterized PFS, objective response rate (ORR), and best percentage change from baseline in tumor size in two cohorts consisting of pts who did not previously receive adjuvant therapy and who progressed in 1L on Ipi/Nivo, or VEGFR-TKI/ICI therapy. Results: Among the 153 eligible 2L pts, 70 (46%) previously received Ipi/Nivo and 83 (54%) previously received a VEGFR-TKI/ICI regimen (TKI/ICI): axitinib/pembrolizumab (54.2%), cabozantinib/nivolumab (25.3%), axitinib/avelumab (12.0%), and lenvatinib/pembrolizumab (8.4%). Overall, the median follow-up was 11.6 months. More pts with lung metastasis and age <65 years were in the Tivo arm than in the Tivo+Nivo arm in both cohorts. In the Ipi/Nivo cohort, median PFS was 9.2 months (95% CI, 4.5-NR) with Tivo and 9.3 months (95% CI, 7.3-15.3) with Tivo+Nivo. ORR was 32.4% (95% CI, 18.0%-49.8%) with Tivo and 24.2% (95% CI, 11.1%-42.6%) with Tivo+Nivo. In the TKI/ICI cohort, median PFS was 7.4 months (95% CI, 3.7-9.3) with Tivo and 3.9 months (95% CI, 2.1-5.7) with Tivo+Nivo. ORR was 22.0% (95% CI, 10.6%-37.6%) with Tivo and 9.5% (95% CI, 2.7%-22.6%) with Tivo+Nivo. Target tumor size reduction from baseline was observed in both arms (Table). More pts had target tumor reductions (≥30% or ≥50%) in the Tivo arm than in the Tivo+Nivo arm in both cohorts. Of 7 pts with target tumor reduction of ≥50% from Tivo, 6 (85.7%) and 1 (14.3%) were previously treated with axitinib and cabozantinib, respectively. Conclusions: In this TiNivo-2 subgroup analysis, Tivo monotherapy at 1.34 mg daily showed activity in pts who previously received a contemporary 1L mRCC regimen. At this dose of Tivo, substantial tumor size reduction was observed, both after Ipi/Nivo and VEGFR-TKI/ICI regimens. There appeared to be no benefit with the addition of Nivo to Tivo in this context, akin to the results of the parent trial. Clinical trial information: NCT04987203 . Best percentage change in target tumor size. Best % Change from Baseline Prior Treatment ≥30% Reduction ≥50% Reduction Tivo TKI/ICI 30.5% 19.4% Ipi/Nivo 44.4% 27.8% Tivo+ Nivo TKI/ICI 17.5% 2.5% Ipi/Nivo 33.3% 12.1%

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: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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 integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.052
GPT teacher head0.363
Teacher spread0.311 · 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 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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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