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FRACTION-RCC: Innovative, high-throughput assessment of nivolumab + ipilimumab for treatment-refractory advanced renal cell carcinoma (aRCC).

2020· article· en· W3031933721 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, Wilson H. Miller, Shruti Shally Saggi, David Gold, Robert J. Motzer, Bernard Escudier

Bibliographic record

VenueJournal of Clinical Oncology · 2020
Typearticle
Languageen
FieldMedicine
TopicRenal cell carcinoma treatment
Canadian institutionsMcGill UniversityJewish General HospitalMcMaster UniversityJuravinski Cancer CentreHôtel-Dieu de Québec
Fundersnot available
KeywordsMedicineIpilimumabNivolumabInternal medicineDiscontinuationRefractory (planetary science)OncologyRenal cell carcinomaCancerImmunotherapy

Abstract

fetched live from OpenAlex

5007 Background: The immuno-oncology (I-O) combination nivolumab + ipilimumab (NIVO+IPI) is approved for first-line (1L) and NIVO is approved for second-line treatment post TKI therapy in aRCC. The open-label, randomized, phase 2 Fast Real-Time Assessment of Combination Therapies in Immuno-Oncology (FRACTION-RCC; NCT02996110) platform study has an adaptive design allowing rapid evaluation of I-O therapies, including NIVO+IPI or other investigational combinations. This FRACTION analysis reports preliminary outcomes with NIVO+IPI in aRCC pts after progression on checkpoint inhibitor therapy. Methods: All pts, except 1, had previously received and progressed on checkpoint inhibitor treatment. Pts received NIVO+IPI (NIVO 3 mg/kg + IPI 1 mg/kg Q3W ×4, then after 6 weeks, NIVO 480 mg Q4W), up to 2 years or until progression, toxicity, or protocol-specified discontinuation. Primary endpoints were confirmed objective response rate (ORR; per investigator using RECIST v1.1), duration of response (DOR), and progression-free survival probability at week 24. Safety outcomes were reported. Results: 46 pts were randomized to NIVO+IPI. Pts had 0 (n = 1), 1 (n = 10), 2 (n = 12), 3 (n = 10), or ≥4 (n = 13) prior lines of therapy. All pretreated pts had prior anti-PD-(L)1-, none had prior anti-CTLA-4- therapy, and 37 had prior TKI-based therapy; 45 pts progressed on anti-PD-(L)1 as the most recent therapy. Most pts had clear cell aRCC (n = 44). After a median study follow-up of 8.9 months, ORR was 15.2%; no pts achieved complete response and 7 achieved partial response. DOR ranged from 2–19+ months (n = 7); 5 pts had ongoing response. Six of 7 responders had received ≥2 prior lines of therapy. Any-grade treatment-related adverse events (AEs) were reported in 36 pts (78.3%; fatigue, rash [both 19.6%], and diarrhea [17.4%] were most common). Grade 3–4 treatment-related AEs were reported in 13 pts (28.3%; diarrhea [8.7%], ↑amylase and ↑lipase [both 6.5%] were most common). Treatment-related immune-mediated AEs of any grade were reported in 22 pts (47.8%; rash [19.6%], diarrhea [17.4%], and ↑alanine aminotransferase [8.7%]). No treatment-related deaths were reported. Updated and expanded results with an additional 3 months of follow-up will be presented. Conclusions: These results suggest that NIVO+IPI may provide durable partial response in some pts with prior progression on checkpoint inhibitors, including some heavily pretreated pts. The safety profile of NIVO+IPI in FRACTION pts was similar to historic data in aRCC with this combination. Clinical trial information: 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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.138
GPT teacher head0.458
Teacher spread0.320 · 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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Citations32
Published2020
Admission routes1
Has abstractyes

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