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Supporting community translation of lung cancer screening: A web-based decision aid to support informed decision making.
Transl Behav Med
January 2025
Department of Health Outcomes and Behavior, H. Lee Moffitt Cancer Center, Tampa, FL, 33162, USA.
Background: Results of the National Lung Screening Trial create the potential to reduce lung cancer mortality, but community translation of lung cancer screening (LCS) has been challenging. Subsequent policies have endorsed informed and shared decision-making and using decision support tools to support person-centered choices about screening to facilitate implementation. This study evaluated the feasibility and acceptability of LuCaS CHOICES, a web-based decision aid to support delivery of accurate information, facilitate communication skill development, and clarify personal preferences regarding LCS-a key component of high-quality LCS implementation.
View Article and Find Full Text PDFMultiplexed Molecular Endophenotypes Help Identify Hub Genes in Non-Small Cell Lung Cancer: Unlocking Next-Generation Cancer Phenomics.
OMICS
January 2025
Department of Biotechnology, Brainware University, Barasat, West Bengal, India.
Next-generation cancer phenomics by deployment of multiple molecular endophenotypes coupled with high-throughput analyses of gene expression offer veritable opportunities for triangulation of discovery findings in non-small cell lung cancer (NSCLC) research. This study reports differentially expressed genes in NSCLC using publicly available datasets (GSE18842 and GSE229253), uncovering 130 common genes that may potentially represent crucial molecular signatures of NSCLC. Additionally, network analyses by GeneMANIA and STRING revealed significant coexpression and interaction patterns among these genes, with four notable hub genes-, , and -identified as pivotal in NSCLC progression.
View Article and Find Full Text PDFCancer statistics, 2025.
CA Cancer J Clin
January 2025
Surveillance and Health Equity Science, American Cancer Society, Atlanta, Georgia, USA.
Each year, the American Cancer Society estimates the numbers of new cancer cases and deaths in the United States and compiles the most recent data on population-based cancer occurrence and outcomes using incidence data collected by central cancer registries (through 2021) and mortality data collected by the National Center for Health Statistics (through 2022). In 2025, 2,041,910 new cancer cases and 618,120 cancer deaths are projected to occur in the United States. The cancer mortality rate continued to decline through 2022, averting nearly 4.
View Article and Find Full Text PDFAutomatic machine learning accurately predicts the efficacy of immunotherapy for patients with inoperable advanced non-small cell lung cancer using a computed tomography-based radiomics model.
Diagn Interv Radiol
January 2025
Huadong Hospital, Fudan University, Department of Thoracic Surgery, Shanghai, China.
Purpose: Patients with advanced non-small cell lung cancer (NSCLC) have varying responses to immunotherapy, but there are no reliable, accepted biomarkers to accurately predict its therapeutic efficacy. The present study aimed to construct individualized models through automatic machine learning (autoML) to predict the efficacy of immunotherapy in patients with inoperable advanced NSCLC.
Methods: A total of 63 eligible participants were included and randomized into training and validation groups.
Weight and Blood-Based Markers of Cachexia Predict Disability, Hospitalization and Worse Survival in Cancer Immunotherapy Patients.
J Cachexia Sarcopenia Muscle
February 2025
Center for Health Information Partnerships, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA.
Background: Cancer-associated cachexia can inhibit immune checkpoint inhibitor (ICI) therapy efficacy. Cachexia's effect on ICI therapy has not been studied in large cohorts of cancer patients aside from lung cancer. We studied associations between real-world routinely collected clinical cachexia markers and disability-free, hospitalization-free and overall survival of cancer patients.
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