Non-Invasive Measurement of PD-L1 Status and Prediction of Immunotherapy Response Using Deep Learning of PET/CT Images

Last Updated: Monday, August 16, 2021

A deeply learned score accurately predicted PD-L1 expression among a cohort of patients with non–small cell lung cancer who underwent PET/CT scans. The authors propose that this score could be used as a surrogate for IHC-determined PD-L1 measurement to guide individual pretherapy decisions pending larger prospective trials.

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Non-Invasive Measurement of PD-L1 Status and Prediction of Immunotherapy Response Using Deep Learning of PET/CT Images

Journal of Thoracic Oncology

Biomarker Discovery and Validation: Statistical Considerations

Lung Cancer

Biomarker Testing in Non-Small Cell Lung Cancer in Routine Care: Analysis of the First 3,717 Patients in the German Prospective, Observational, Nation-Wide CRISP Registry (AIO-TRK-0315)

Journal of Clinical Oncology

Therapy for Stage IV Non–Small-Cell Lung Cancer With Driver Alterations: ASCO and OH (CCO) Joint Guideline Update

European Journal of Cancer

COVID-19 in Lung Cancer Patients Receiving ALK/ROS1 Inhibitors

Translational Lung Cancer Research

Emerging Biomarkers for Neoadjuvant Immune Checkpoint Inhibitors in Operable Non–Small Cell Lung Cancer

Translational Lung Cancer Research

Neoadjuvant Treatment of Stage IIIA-N2 in EGFR-Mutant/ALK-Rearranged Non–Small Cell Lung Cancer

New England Journal of Medicine

Trastuzumab Deruxtecan in HER2-Mutant Non–Small-Cell Lung Cancer

The ASCO Post

FDA Grants Accelerated Approval to Mobocertinib for Patients With Metastatic NSCLC and EGFR Exon 20 Insertion Mutations

International Association for the Study of Lung Cancer

Perceptions of Biomarker Testing for Underserved Patients With Lung Cancer: A Mixed-Methods Survey of US-Based Oncology Clinicians

Frontiers in Oncology

A Retrospective Study of Brain Metastases From Solid Malignancies: The Effect of Immune Checkpoint Inhibitors

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