Georgina V. Long, MD, PhD, on Melanoma: Nivolumab Plus Ipilimumab vs Nivolumab Alone
AACR Annual Meeting 2021
Georgina V. Long, MD, PhD, of the Melanoma Institute Australia, University of Sydney, discusses results of the CheckMate 915 trial, which may reinforce nivolumab as an adjuvant standard of care in patients with stage IIIB–D/IV melanoma, with or without complete lymphadenectomy (Abstract CT004).
The ASCO Post Staff
Dennis J. Slamon, MD, PhD, of the UCLA David Geffen School of Medicine, reflects on the ways in which breast cancer research pioneered the targeted treatment approach, as understanding of the basic biology of tumors deepened and new pathways were uncovered. He sees a future ripe with possibilities for new molecular targets to further improve outcomes for patients with breast cancer and other types of tumors.
The ASCO Post Staff
Enrique Grande, MD, PhD, of The University of Texas MD Anderson Cancer Center, Madrid, discusses phase III overall survival results from the IMvigor130 study of atezolizumab plus platinum and gemcitabine vs placebo plus platinum and gemcitabine in patients with previously untreated metastatic urothelial carcinoma (Abstract CT187).
The ASCO Post Staff
Patrick M. Forde, MD, of the Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins University, discusses results from the CheckMate 816 trial, which showed that adding nivolumab to chemotherapy as a neoadjuvant treatment for patients with resectable non–small cell lung cancer improved the pathologic complete response rate to 24%, compared to 2.2% with chemotherapy alone (Abstract CT003).
The ASCO Post Staff
Katelyn T. Byrne, PhD, of the Perelman School of Medicine at the University of Pennsylvania, discusses the first in-depth analysis of the impact of selicrelumab, an anti-CD40 antibody, which was found to enrich T cells in pancreatic tumors, activate the immune system, and alter the tumor stroma (Abstract CT005).
The ASCO Post Staff
Joann G. Elmore, MD, MPH, of the UCLA Fielding School of Public Health, discusses previous studies that show wide variability in cancer diagnoses, the uncertainties introduced by computer-aided detection tools, and new research on artificial intelligence and machine learning that may lead to more consistent and accurate diagnoses and prognoses, potentially improving treatment (Abstract SY01-03).