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Record W2897161734 · doi:10.1002/cncr.31595

Checkpoint inhibitors in patients with metastatic renal cell carcinoma: Results from the International Metastatic Renal Cell Carcinoma Database Consortium

2018· article· en· W2897161734 on OpenAlexaff
Steven Yip, J. Connor Wells, Raphael Brandão Moreira, Alex H.C. Wong, Sandy Srinivas, Benoit Beuselinck, Camillo Porta, Hao‐Wen Sim, D. Scott Ernst, Brian I. Rini, Takeshi Yuasa, Naveen S. Basappa, Ravindran Kanesvaran, Lori Wood, Christina Canil, Anil Kapoor, Simon Fu, Toni K. Choueiri, Daniel Y.C. Heng

Bibliographic record

VenueCancer · 2018
Typearticle
Languageen
FieldMedicine
TopicRenal cell carcinoma treatment
Canadian institutionsJuravinski Cancer CentreUniversity of OttawaHealth Sciences CentreUniversity of AlbertaQueen Elizabeth II Health Sciences CentreMcMaster UniversityLondon Health Sciences CentrePrincess Margaret Cancer Centre
FundersFoundation MedicineNovartis PharmaGenentechIpsenCelldex TherapeuticsAstellas PharmaEisaiNational Comprehensive Cancer NetworkSanofiExelixisGlaxoSmithKlineBristol-Myers SquibbAstraZenecaPfizer
KeywordsMedicineNivolumabRenal cell carcinomaIpilimumabInternal medicineOncologyClear cell renal cell carcinomaRetrospective cohort studyCarcinomaCancerGastroenterologyImmunotherapy

Abstract

fetched live from OpenAlex

BACKGROUND: To the authors' knowledge, outcomes and prognostic tools have yet to be clearly defined in patients with metastatic renal cell carcinoma (mRCC) who are treated with immuno-oncology (IO) checkpoint inhibitors (programmed death-ligand 1 [PD-L1] inhibitors). In the current study, the authors aimed to establish IO efficacy benchmarks in patients with mRCC and update patient outcomes in each International Metastatic Renal Cell Carcinoma Database Consortium (IMDC) prognostic class. METHODS: A retrospective analysis was performed using the IMDC database with data from 38 centers. It included patients with mRCC who were treated with ≥1 line of IO. Overall response rates (ORRs), duration of treatment (DOT), and overall survival (OS) were calculated. Patients were stratified using IMDC prognostic factors. RESULTS: A total of 687 patients (90% with clear cell and 10% with non-clear cell) were included. The ORR was 27% in evaluable patients (461 patients). In patients treated with first-line nivolumab and ipilimumab (49 patients), the combination of PD-L1 inhibitor and vascular endothelial growth factor inhibitor (72 patients), and PD-L1 inhibitor (51 patients), the ORR was 31%, 39%, and 40%, respectively, and the median DOT was 8.3 months, 14.7 months, and 8.3 months, respectively. The ORR for second-line, third-line, and fourth-line nivolumab was 22%, 24%, and 26%, respectively. The median DOT was 5.7 months, 6.2 months, and 8.3 months, respectively, in the second-line, third-line, and fourth-line settings. When segregated into IMDC favorable-risk, intermediate-risk, and poor-risk groups, the median OS rates for the first-line, second-line, third-line, and fourth-line treatment settings were not reached (NR), NR, and NR, respectively (P = .163); NR, 26.7 months, and 7.4 months, respectively (P < 0. 0001); 36.1 months, 28.2 months, and 11.1 months, respectively (P = .016); and NR, NR, and 6.7 months, respectively (P = .047). CONCLUSIONS: The ORR was not found to deteriorate from the first-line to the fourth-line of IO therapy. In the second line through fourth line, the IMDC criteria appropriately stratified patients into favorable-risk, intermediate-risk, and poor-risk groups for OS.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.242
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.027
GPT teacher head0.260
Teacher spread0.233 · 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 teacher head, not a consensus.

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".

Quick stats

Citations66
Published2018
Admission routes1
Has abstractyes

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