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Belzutifan plus lenvatinib for patients (pts) with advanced clear cell renal cell carcinoma (ccRCC) after progression on a PD-1/L1 and VEGF inhibitor: Preliminary results of arm B5 of the phase 1/2 KEYMAKER-U03B study.

2023· article· en· W4379333933 on OpenAlexaff
Laurence Albigès, Katy Beckermann, Wilson H. Miller, Jeffrey C. Goh, Pablo Gajate, Carole A. Harris, Cristina Suárez, Avivit Peer, Se Hoon Park, Walter M. Stadler, Andrew Weickhardt, Guy Faust, Peter C.C. Fong, Tom Waddell, Balaji Venugopal, Lina Yin, Ding Wang, Rodolfo F. Perini, Thomas Powles

Bibliographic record

VenueJournal of Clinical Oncology · 2023
Typearticle
Languageen
FieldMedicine
TopicRenal cell carcinoma treatment
Canadian institutionsJewish General Hospital
Fundersnot available
KeywordsMedicineLenvatinibTolerabilityInternal medicineClinical endpointRenal cell carcinomaOncologyPhases of clinical researchAdverse effectClear cell renal cell carcinomaUrologyCancerSurgeryClinical trial

Abstract

fetched live from OpenAlex

4553 Background: The oral HIF-2α inhibitor belzutifan demonstrated antitumor activity with manageable safety as monotherapy in pts with heavily pretreated ccRCC and in combination with a VEGF-TKI in pts who previously received a PD-1/L1 inhibitor. KEYMAKER-U03B (NCT04626518) is phase 1/2, multicenter, multi-arm, open-label, adaptive umbrella study. We present preliminary results from arm B5 for belzutifan + lenvatinib. Methods: In all arms, adults with histologically confirmed ccRCC, KPS ≥70%, and disease progression on or after PD-1/L1 inhibitor and VEGF-TKI treatment (in sequence or in combination) were enrolled. In arm B5, pts received belzutifan 120 mg PO QD + lenvatinib 20 mg PO QD. The study comprised a safety lead-in phase to establish the recommended phase 2 dose (RP2D), followed by an efficacy phase. Primary end point for the safety lead-in phase was safety and tolerability to establish RP2D; co-primary end points of the efficacy phase were safety and ORR per RECIST v1.1 by blinded independent central review (BICR). Secondary end points include clinical benefit rate (CBR; CR + PR + SD ≥6 mo), DOR and PFS per RECIST v1.1 by BICR. Response will be presented in pts who had an opportunity to receive ≥2 postbaseline scans due to ongoing enrollment. PFS was evaluated in all enrolled pts and safety in all treated pts. End points will be evaluated in each arm separately; no comparisons will be made across arms. Results: As of September 29, 2022, 32 pts were enrolled and 30 received treatment. Median age was 60.5 y, 78% were male and 78% had intermediate/poor IMDC risk. 23 pts were on treatment at data cutoff date. Median follow up was 6.9 mo (range: 0.1-18.2). Safety of belzutifan 120 mg + lenvatinib 20 mg was manageable. Of 10 evaluable pts in the safety lead-in phase, only 1 experienced a dose-limiting toxicity (grade 1 dyspnea). Among pts who had opportunity for ≥2 postbaseline scans (n = 24), ORR was 50% (95% CI, 29-71; all PRs); CBR was 54% (95% CI, 33-74). Median DOR was not reached (NR; range: 1.4+ to 14.0+ mo); 74% of responders remained in response for ≥12 mo by KM estimation. For all enrolled pts, median PFS was 11.2 mo (95% CI, 4-NR); 6-mo rate was 55%. In the safety analysis, 28 pts (93%) experienced a treatment-related AE (TRAE), most commonly (≥40%) anemia (43%), fatigue (43%), and hypertension (43%). Grade 3-4 TRAEs occurred in 15 pts (50%); most commonly hypertension (27%) and anemia (17%). 1 pt experienced grade 2 hypoxia. No pt died due to a TRAE. Conclusions: Preliminary data from the belzutifan + lenvatinib combination exhibited promising antitumor activity in pts with ccRCC that progressed on PD-1/L1 inhibitors and VEGF-TKIs. Safety findings were consistent with individual profiles of each agent. The combination is being further evaluated in the phase 3 LITESPARK-011 study. Clinical trial information: NCT04626518 .

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 score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.068
GPT teacher head0.414
Teacher spread0.346 · 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

Citations10
Published2023
Admission routes1
Has abstractyes

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