Joann G. Elmore, MD, MPH, on Cancer Diagnosis: When Pathologists Disagree, Artificial Intelligence May Help
AACR Annual Meeting 2021
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).
The ASCO Post Staff
Matthew J. Matasar, MD, of Memorial Sloan Kettering Cancer Center, discusses phase III results of the CHRONOS-3 trial, which showed that copanlisib plus rituximab led to a 48% reduction in the risk of disease progression or death compared with placebo plus rituximab in patients with relapsed indolent non-Hodgkin lymphoma (Abstract CT001).
The ASCO Post Staff
Brian I. Rini, MD, of Vanderbilt University, discusses the IMmotion151 trial results on overall survival and the association of gene expression and clinical outcomes with atezolizumab plus bevacizumab vs sunitinib in patients with locally advanced or metastatic renal cell carcinoma (Abstract CT188).
The ASCO Post Staff
Jessica C. Hassel, MD, of University Hospital Heidelberg, discusses phase III results of a study that compared tebentafusp, a bispecific fusion protein, with investigator’s choice in patients with metastatic uveal melanoma. Tebentafusp nearly halved the risk of death among patients in the trial with this rare eye cancer (Abstract CT002).
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
Jeanne Tie, MD, MBChB, of the Peter MacCallum Cancer Centre, discusses how to improve the current, somewhat imprecise, approach based on pathologic staging alone, used to select patients for adjuvant treatment. Circulating tumor DNA analysis after curative-intent treatment may detect minimal residual disease and might be used to predict recurrence and adjuvant treatment efficacy across multiple tumor types.
