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| http://dx.doi.org/10.1200/JGO.18.00014 | DOI Listing |
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Molecular classification of endometrial cancers (EC) and association with relapse-free survival (RFS) and overall survival (OS) outcomes: Ancillary analysis of GOG-0258.
Gynecol Oncol
January 2025
Duke University, Durham, NC, United States of America. Electronic address:
Purpose: Determine if molecular classification using mismatch repair (MMR) and p53 protein expression predicts recurrence-free survival (RFS) and overall survival (OS) in endometrial cancer (EC) patients treated with chemotherapy and radiation (CRT) versus chemotherapy (CT).
Methods: GOG-0258, a phase III randomized trial (NCT00942357), compared CRT to CT. Immunohistochemistry assessed MMR and p53 status.
Durvalumab with or without bevacizumab with transarterial chemoembolisation in hepatocellular carcinoma (EMERALD-1): a multiregional, randomised, double-blind, placebo-controlled, phase 3 study.
Lancet
January 2025
Department of Diagnostic and Interventional Radiology, University of Pisa School of Medicine, Pisa, Italy.
Background: Transarterial chemoembolisation (TACE) is standard of care for patients with unresectable hepatocellular carcinoma that is amenable to embolisation; however, median progression-free survival is still approximately 7 months. We aimed to assess whether adding durvalumab, with or without bevacizumab, might improve progression-free survival.
Methods: In this multiregional, randomised, double-blind, placebo-controlled, phase 3 study (EMERALD-1), adults aged 18 years or older with unresectable hepatocellular carcinoma amenable to embolisation, an Eastern Cooperative Oncology Group performance status of 0 or 1 at enrolment, and at least one measurable intrahepatic lesion per modified Response Evaluation Criteria in Solid Tumours (RECIST) were enrolled at 157 medical sites including research centres and general and specialist hospitals in 18 countries.
Feasibility and Acceptability of Collecting Passive Smartphone Data for Potential Use in Digital Phenotyping Among Family Caregivers and Patients With Advanced Cancer.
JCO Clin Cancer Inform
January 2025
School of Nursing, University of Alabama at Birmingham, Birmingham, AL.
Purpose: Modeling passively collected smartphone sensor data (called digital phenotyping) has the potential to detect distress among family caregivers and patients with advanced cancer and could lead to novel clinical models of cancer care. The purpose of this study was to assess the feasibility and acceptability of collecting passive smartphone data from family caregivers and their care recipients with advanced cancer over 24 weeks.
Methods: This was an observational feasibility study.
A comparison of real-world data on adjuvant treatment in patients with stage III BRAF V600 mutated melanoma - Results of systematic literature research.
Eur J Cancer
January 2025
Center for Dermato-oncology, Department of Dermatology, Eberhard Karls University of Tübingen, 72076 Tübingen, Germany.
Background: Over the past decade, PD-1-based immune checkpoint inhibitors (ICI) and targeted therapies (TT) with BRAF and MEK inhibitors transformed melanoma treatment. Both are widely used in the adjuvant setting. However, for patients with a BRAF V600 mutation, the optimal adjuvant therapy remains unclear due to the lack of head-to-head comparison studies.
View Article and Find Full Text PDFReal-World and Clinical Trial Validation of a Deep Learning Radiomic Biomarker for PD-(L)1 Immune Checkpoint Inhibitor Response in Advanced Non-Small Cell Lung Cancer.
JCO Clin Cancer Inform
December 2024
Onc.AI, San Carlos, CA.
Purpose: This study developed and validated a novel deep learning radiomic biomarker to estimate response to immune checkpoint inhibitor (ICI) therapy in advanced non-small cell lung cancer (NSCLC) using real-world data (RWD) and clinical trial data.
Materials And Methods: Retrospective RWD of 1,829 patients with advanced NSCLC treated with PD-(L)1 ICIs were collected from 10 academic and community institutions in the United States and Europe. The RWD included data sets for discovery (Data Set A-Discovery, n = 1,173) and independent test (Data Set B, n = 458).
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