Authors
Latest:
Optimization of Genetic Testing for mCRPCJason M. Hafron, MD, CMO, and Oliver Sartor, MD, share their approach for the optimal management of mCRPC through genetic testing.
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Squamous Cell Carcinoma of the Kidney: A Large Case SeriesSyed Arslan Shehzad Shah, MD, and colleagues present findings from a broad investigation into this rare neoplasm of the kidney, including data on patient demographics and mean survival.
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Molecular Pathogenesis of Cholangiocarcinoma: Implications for Disease Classification and TherapyKhaled W. Kabbara, MD, and colleagues, research treatment options for cholangiocarcinoma.
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Unmet Needs and Future Perspectives on the Treatment of EGFR-Mutated NSCLCThe expert panel concludes with thoughts on unmet needs and future perspectives on the treatment of patients with EGFR-mutated non–small cell lung cancer.
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AI and Changing the Future of Pancreatic Cancer ScreeningIn an era where medical records are digitalized, artificial intelligence has the potential to identify patterns that can locate at-risk patients with pancreatic cancer.
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An Embarrassment of Riches Treatment Sequencing in Gastrointestinal CancersLaura W. Goff, MD, MSCI, MMHC, discusses the onslaught of treatment sequencing available in gastrointestinal cancer.
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Leveraging Artificial Intelligence to Bolster Equitable Cancer CareAuthors of a manuscript published in ONCOLOGY® discuss how artificial intelligence may help with cancer detection and improving various patient outcomes.
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CDK4/6 Inhibitor Use May Expand in HR+ HER2– Breast CancerDaniel G. Stover, MD, describes how findings from the phase 3 NATALEE trial may support expanding the portion of patients who receive CDK 4/6 inhibitors as a treatment for hormone receptor–positive, HER2-negative breast cancer.
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Cross Q&A: The Memorial Sloan-Kettering MavericksThe Moffitt Marrowvingians take their turn questioning the Memorial Sloan Kettering Mavericks on their presented clinical trial data.
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ABBV-400 Shows Early Promise in Pretreated, Metastatic Colorectal Cancer“It does appear like MET expression could be one of the mechanisms wherein you could differentiate between responders and non-responders,” Kanwal P.S. Raghav, MBBS, MD, stated.
