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Record W2997000594 · doi:10.3390/cancers12010084

Real-World Data on Cabozantinib in Previously Treated Patients with Metastatic Renal Cell Carcinoma: Focus on Sequences and Prognostic Factors

2019· article· en· W2997000594 on OpenAlexaff
Matteo Santoni, Daniel Y.C. Heng, Sergio Bracarda, Giuseppe Procopio, Michèle Milella, Camillo Porta, Marc Matrana, Giacomo Cartenì, Simon J. Crabb, Ugo De Giorgi, Umberto Basso, Cristina Masini, Fabio Calabrò, Maria Giuseppa Vitale, Daniele Santini, Francesco Massari, Luca Galli, Giuseppe Fornarini, Riccardo Ricotta, Sebastiano Buti, Paolo Andrea Zucali, Orazio Caffo, Franco Morelli, Francesco Carrozza, Angelo Martignetti, Alain Gelibter, Roberto Iacovelli, Alessandra Mosca, Francesco Atzori, Nuno Vau, Lorena Incorvaia, Cinzia Ortega, Marina Scarpelli, Antonio López-Beltrán, Liang Cheng, Vittorio Paolucci, Jeffrey Graham, Erin Pierce, Sarah Scagliarini, Pierangela Sepe, Elena Verzoni, Sara Merler, Mimma Rizzo, Giulia Sorgentoni, Alessandro Conti, Francesco Piva, Alessia Cimadamore, Rodolfo Montironi, Nicola Battelli

Bibliographic record

VenueCancers · 2019
Typearticle
Languageen
FieldMedicine
TopicRenal cell carcinoma treatment
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsCabozantinibRenal cell carcinomaMedicineFocus (optics)OncologyInternal medicineCancer researchPathology

Abstract

fetched live from OpenAlex

Cabozantinib is approved for the treatment of renal cell carcinoma (RCC). However, prognostic factors are still lacking in this context. The aim of this study was to evaluate prognostic factors in RCC patients treated with second- or third-line cabozantinib. A multicenter retrospective real-world study was conducted, involving 32 worldwide centers. A total of 237 patients with histologically confirmed clear-cell and non-clear-cell RCC who received cabozantinib as second- or third-line therapy for metastatic disease were included. We analyzed overall survival (OS), progression-free survival (PFS) and time-to-strategy failure (TTSF) using Kaplan–Meier curves. Cox proportional models were used at univariate and multivariate analyses.The median PFS and OS of cabozantinib were 7.76 months (95% CI 6.51–10.88) and 11.57 months (95% CI 10.90–not reached (NR)) as second-line and 11.38 months (95% CI 5.79–NR) and NR (95% CI 11.51–NR) as third-line therapy. The median TTSF and OS were 11.57 and 15.52 months with the sequence of cabozantinib–nivolumab and 25.64 months and NR with nivolumab–cabozantinib, respectively. The difference between these two sequences was statistically significant only in good-risk patients. In the second-line setting, hemoglobin (Hb) levels (HR= 2.39; 95% CI 1.24–4.60, p = 0.009) and IMDC (International Metastatic Renal Cell Carcinoma Database Consortium) group (HR = 1.72, 95% CI 1.04–2.87, p = 0.037) were associated with PFS while ECOG-PS (HR = 2.33; 95%CI, 1.16–4.69, p = 0.018) and Hb levels (HR = 3.12; 95%CI 1.18–8.26, p = 0.023) correlated with OS at multivariate analysis, while in the third-line setting, only Hb levels (HR = 2.72; 95%CI 1.04–7.09, p = 0.042) were associated with OS. Results are limited by the retrospective nature of the study.This real-world study provides evidence on the presence of prognostic factors in RCC patients receiving cabozantinib.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0000.000

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 head0.040
GPT teacher head0.278
Teacher spread0.239 · 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.

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".

Quick stats

Citations31
Published2019
Admission routes1
Has abstractyes

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