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Real-world efficacy and toxicity of ipilimumab and nivolumab as first line treatment of metastatic renal cell carcinoma (mRCC) in a subpopulation of elderly and poor performance status patients.

2024· article· en· W4391303281 on OpenAlexaffabout
Ana-Alicia Beltran-Bless, Noa Shani Shrem, Sunita Ghosh, Camilla Tajzler, Lori Wood, Christian Kollmannsberger, Naveen S. Basappa, Jeffrey Graham, Nazanin Fallah‐Rad, Daniel Yick Chin Heng, Denis Soulières, Aly‐Khan A. Lalani, Rodney H. Breau, Antonio Finelli, Simon Tanguay, Bimal Bhindi, Georg A. Bjarnason, Frédéric Pouliot, Christina M. Canil

Bibliographic record

VenueJournal of Clinical Oncology · 2024
Typearticle
Languageen
FieldMedicine
TopicRenal cell carcinoma treatment
Canadian institutionsSunnybrook Health Science CentreMcGill University Health CentreMcMaster UniversityUniversité LavalCentre Hospitalier de l’Université de MontréalUniversity of CalgaryPrincess Margaret Cancer CentreUniversity of ManitobaOttawa HospitalBC Cancer AgencyUniversity of AlbertaQueen Elizabeth II Health Sciences CentreUniversity of TorontoDalhousie University
Fundersnot available
KeywordsMedicineNivolumabIpilimumabRenal cell carcinomaToxicityOncologyInternal medicineMetastatic melanomaPerformance statusImmunotherapyOverall survivalCancer

Abstract

fetched live from OpenAlex

367 Background: Ipilimumab and nivolumab (ipi/nivo) improved overall survival (OS) and response rates compared to sunitinib in the pivotal Checkmate 214 trial of intermediate/poor risk mRCC. A subgroup analysis showed no significant difference in OS for ipi/nivo in pts 65 to 75 years old (yo), as well as pts >75 yo. In another subgroup analysis, Karnofsky performance status (KPS) <70 was associated with worse median OS compared with pts with KPS ≥ 70. We evaluated efficacy and toxicity of ipi/nivo in an older and frailer population in a real-world cohort. Methods: Analysis was conducted on a real-world cohort with mRCC (N=378) treated with ipi/nivo as first line treatment from the Canadian Kidney Cancer Information System (CKCis) database from January 2011 to March 2022. Median follow-up was 14.3 m (range 0 to 87.6). A comparison was made between outcomes and toxicity in pts ≥ versus (vs) <70 yo, ≥ vs <75 yo, KPS < vs ≥70, and ≥70 yo with KPS <70 vs <70 yo with KPS >70. Toxicity was graded as per CTCAE v4.03 or any toxicity that resulted in a dose/schedule change. OS, progression free survival (PFS) and time to treatment failure (TTF) were calculated by Kaplan-Meier analysis. Log rank tests were used for comparison between groups. Multivariate analysis was done including IMDC for all outcomes. Results: Median OS was worse in older patients at 30.0 m in pts ≥ 70 yo vs 45.4 m in pts < 70 yo (p=0.060), and 19.0 m in the pts ≥ 75 yo vs 45.5 m in pts < 75 yo (p=0.003) despite similar disease control rates and toxicity. Median PFS was similar in younger and older pts: < vs ≥ 70 yo (p=0.560) and < vs ≥ 75 yo (p=0.296). Median TTF was comparable in < 70 yo and ≥ 70 yo (p=0.106) and < 75 and ≥ 75 yo groups (p-value=0.733). Median OS, PFS and TTF were comparable in pts KPS < 70 vs pts KPS ≥ 70 and in pts ≥70 yo with KPS < 70 vs pts < 70 yo with KPS >70. Adjusted and unadjusted analysis showed no difference in OS and PFS between groups. Conclusions: Use of ipi/nivo in mRCC in older patients was associated with inferior OS, while decreased performance status had equivalent OS. Both groups had equivalent TTF and PD without higher toxicity. We believe that ipi/nivo is a reasonable treatment option for older and low performance status patients. [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)0.003
metaresearch head score (Gemma)0.006
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
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 head0.080
GPT teacher head0.398
Teacher spread0.318 · 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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Citations2
Published2024
Admission routes2
Has abstractyes

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