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
Rita Nanda, MD, of the University of Chicago, discusses the latest data on novel treatment strategies for triple-negative breast cancer, including immune checkpoint, PARP, and ATK inhibitors; antibody-drug conjugates; and targeting the androgen receptor.
The ASCO Post Staff
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
Lipika Goyal, MD, of Massachusetts General Hospital, discusses phase II results of the FOENIX-CCA2 trial, which explored the clinical benefit of futibatinib, an FGFR1–4 inhibitor, tested in patients with intrahepatic cholangiocarcinoma that harbored FGFR2 gene fusions or other rearrangements (Abstract CT010).
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.
