Lung Cancer
- Cancer PHGKB -
What's New
Last Posted: Dec 24, 2020
- A Genomic-Pathologic Annotated Risk Model to Predict Recurrence in Early-Stage Lung Adenocarcinoma
GD Jones et al JAMA SUregery, December 23, 2020 - Clinical Application of the FoundationOne CDx Assay to Therapeutic Decision-Making for Patients with Advanced Solid Tumors.
Takeda Masayuki et al. The oncologist 2020 Dec - Development and Validation of a Machine Learning Model to Explore Tyrosine Kinase Inhibitor Response in Patients With Stage IV EGFR Variant-Positive Non-Small Cell Lung Cancer.
Song Jiangdian et al. JAMA network open 2020 Dec 3(12) e2030442 - Artificial intelligence-based imaging analytics and lung cancer diagnostics: Considerations for health system leaders.
Zarzeczny Amy et al. Healthcare management forum 2020 Dec 840470420975062 - Deep convolutional neural networks for multi-planar lung nodule detection: improvement in small nodule identification.
Zheng Sunyi et al. Medical physics 2020 Dec - Eliminating biasing signals in lung cancer images for prognosis predictions with deep learning.
van Amsterdam W A C et al. NPJ digital medicine 2019 Dec 2(1) 122 - Genomic characteristics of driver genes in Chinese patients with non-small cell lung cancer.
Si Xiaoyan et al. Thoracic cancer 2020 Dec - Prognostic Value of EZH2 in Non-Small-Cell Lung Cancers: A Meta-Analysis and Bioinformatics Analysis.
Fan Kui et al. BioMed research international 2020 20202380124 - Application of Machine Learning for Tumor Growth Inhibition - Overall Survival Modeling Platform.
Chan Phyllis et al. CPT: pharmacometrics & systems pharmacology 2020 Dec - Putting artificial intelligence (AI) on the spot: machine learning evaluation of pulmonary nodules.
Tandon Yasmeen K et al. Journal of thoracic disease 2020 Nov 12(11) 6954-6965 - A Highly Sensitive Next-Generation Sequencing-Based Genotyping Platform for EGFR Mutations in Plasma from Non-Small Cell Lung Cancer Patients.
Shin Jung-Young et al. Cancers 2020 Nov 12(12) - PTEN, ATM, IDH1 mutations and MAPK pathway activation as modulators of PFS and OS in patients treated by first line EGFR TKI, an ancillary study of the French Cooperative Thoracic Intergroup (IFCT) Biomarkers France project.
Blons H et al. Lung cancer (Amsterdam, Netherlands) 2020 Nov - Detection of KRAS G12/G13 Mutations in Cell Free-DNA by Droplet Digital PCR, Offers Prognostic Information for Patients with Advanced Non-Small Cell Lung Cancer.
Michaelidou Kleita et al. Cells 2020 Nov 9(11) - A genomic signature for accurate classification and prediction of clinical outcomes in cancer patients treated with immune checkpoint blockade immunotherapy.
Lu Mei et al. Scientific reports 2020 Nov 10(1) 20575 - Clinical and Pathologic Implications of Tumor Genomics of Predominant Histologic Subtypes in Lung Adenocarcinoma.
Xu Xuejun et al. Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer 2020 Dec 15(12) e187-e188
About Cancer PHGKB
Cancer PHGKB is an online, continuously updated, searchable database of published scientific literature, CDC and NIH resources, and other materials that address the translation of genomic discoveries into improved health care and prevention related to cancer...more
Content Summary
- CDC Information (4)
- NIH Information (19)
- COVID-19 (43)
- CDC Genomics Publications (5)
- Human Genome Epidemiologic Studies (5409)
- GWAS Studies (66)
- Human Genomics Translation/Implementation Studies (533)
- Genomic Tests Evidence Synthesis (51)
- Genomic Tests Guidelines (43)
- Tier-Classified Guidelines (20)
- Non-Genomics Precision Health (87)
- State Public Health Genomics Programs (3)
- Reviews/Commentaries (271)
- Tools/Methods (3)
- Ethical/Legal and Social Issues (ELSI) (3)
Common Type
Disclaimer: Articles listed in the Public Health Knowledge Base are selected by the CDC Office of Public Health Genomics to provide current awareness of the literature and news. Inclusion in the update does not necessarily represent the views of the Centers for Disease Control and Prevention nor does it imply endorsement of the article's methods or findings. CDC and DHHS assume no responsibility for the factual accuracy of the items presented. The selection, omission, or content of items does not imply any endorsement or other position taken by CDC or DHHS. Opinion, findings and conclusions expressed by the original authors of items included in the update, or persons quoted therein, are strictly their own and are in no way meant to represent the opinion or views of CDC or DHHS. References to publications, news sources, and non-CDC Websites are provided solely for informational purposes and do not imply endorsement by CDC or DHHS.
- Page last reviewed:Oct 1, 2020
- Page last updated:Dec 28, 2020
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