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Ipilimumab/nivolumab (I/N) compared to axitinib/pembrolizumab (A/P) in metastatic renal cell carcinoma (mRCC): Insights from a Canadian population.

2024· article· en· W4391303054 on OpenAlexaffabout
Hyejee Ohm, Sunita Ghosh, Mehul Gupta, Lori Wood, Vincent Castonguay, Jeffrey Graham, Christian Kollmannsberger, Dominick Bossé, Denis Soulières, Daniel Yick Chin Heng, Nazanin Fallah‐Rad, Antonio Finelli, Simon Tanguay, Aly‐Khan A. Lalani, Bimal Bhindi, Georg A. Bjarnason, Rodney H. Breau, Frédéric Pouliot, Naveen S. Basappa

Bibliographic record

VenueJournal of Clinical Oncology · 2024
Typearticle
Languageen
FieldMedicine
TopicRenal cell carcinoma treatment
Canadian institutionsSunnybrook Health Science CentreMcMaster UniversityMcGill University Health CentreHealth Sciences CentreUniversity Health NetworkCancerCare ManitobaOttawa HospitalHôtel-Dieu de QuébecBC Cancer AgencyJuravinski Cancer CentreInstitute of Cancer ResearchUniversity of ManitobaDalhousie UniversityUniversity of AlbertaQueen Elizabeth II Health Sciences CentreUniversité LavalCentre Hospitalier de l’Université de MontréalPrincess Margaret Cancer CentreUniversity of Calgary
Fundersnot available
KeywordsNivolumabAxitinibMedicineIpilimumabRenal cell carcinomaPembrolizumabOncologyInternal medicinePopulationMetastatic melanomaImmunotherapyCancerSunitinib

Abstract

fetched live from OpenAlex

393 Background: First-line treatment for mRCC includes I/N and A/P. These two regimens have not been compared in a randomized clinical trial as both CM-214 and KN-426 used single-agent tyrosine kinase inhibitors (TKIs) as the comparator. Meta-analyses suggest improved efficacy outcomes with A/P, but increased likelihood of complete response with I/N. We compared these treatments in the real-world. Methods: Data of consented mRCC patients with clear cell histology from the Canadian Kidney Cancer information system (CKCis) was obtained from January 2013 to December 2021. Treatment outcomes adjusting for age including overall survival (OS), progression free survival (PFS), and response rate (RR) for all patients and intermediate-poor risk patients were completed. Chi-square tests compared the frequency of side effects. Results: Among 547 patients, 360 received I/N and 187 received A/P. Median follow-up was 30.0 (0.1-112.1) months. Median duration of treatment was 6.9 (0.0-68.4) months for I/N and 20.2 (0.1-72.4) months for A/P. Intermediate-poor risk patients were higher in the I/N compared to A/P cohort (91.9% vs. 66.2%; p<0.0001). Cox regression for OS showed no difference between I/N compared to A/P (aHR 1.1, 95% CI [0.77-1.58], p=0.61). PFS showed no statistical difference but a trend for worse with I/N at 12.1 months compared to 22.3 months for A/P (aHR=1.2, 95% CI [0.95-1.62], p=0.11). RR was 40.9% with I/N compared to 56.0% in A/P (aOR 0.52, 95%CI [0.33-0.83], p=0.005). Subgroup analyses for the intermediate-poor risk mRCC patients showed no differences in OS (aHR 0.95, 95%CI [0.65-1.38], p=0.79) and PFS (aHR 1.21, 95%CI [0.90-1.62], p=0.21) between treatment groups but improved RR (aOR 0.58, 95%CI [0.35-0.96], p=0.06) with A/P. 61.7% of I/N patients compared to 79.1% of A/P suffered adverse events that led to a dose or schedule change (p<0.001). Most common toxicities for both groups include diarrhea, fatigue, transaminitis, rash, and anorexia. Conclusions: There was no difference in OS between mRCC patients treated with I/N compared to A/P. A/P demonstrates improved RR and a trend towards longer PFS at the expense of increased frequency of side effects. Despite a median follow-up of 30 months, the data is limited by a high amount of censoring.[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)0.002
metaresearch head score (Gemma)0.004
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 score0.427
Threshold uncertainty score0.858

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.103
GPT teacher head0.406
Teacher spread0.303 · 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".

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Citations0
Published2024
Admission routes2
Has abstractyes

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