Aditya Bardia, MD, MPH, on Early-Stage, High-Risk Breast Cancer: New Data on Pembrolizumab Plus Chemotherapy
2023 SABCS
Aditya Bardia, MD, MPH, of Massachusetts General Hospital Cancer Center, discusses phase III findings from the KEYNOTE-756 study, which showed that adding pembrolizumab to chemotherapy increases the pathologic complete response rate and lowers the residual cancer burden in patients with early-stage, high-risk ER-positive or HER2-negative breast cancer (Abstract GS01-02).
The ASCO Post Staff
Seema Khan, MD, of Northwestern University and the Robert H. Lurie Comprehensive Cancer Center, discusses the 5-year clinical outcomes of ECOG-ACRIN 4112, a prospective trial that supports the omission of radiotherapy after surgery in patients with ductal carcinoma in situ who have a low DCIS score and its use in patients with intermediate/high DCIS scores (Abstract GS03-01).
The ASCO Post Staff
Hope S. Rugo, MD, of the University of California, San Francisco Helen Diller Family Comprehensive Cancer Center, discusses data from the phase II KEYLYNK-009 study, which compared pembrolizumab plus olaparib vs pembrolizumab plus chemotherapy after induction with pembrolizumab plus chemotherapy for patients with locally recurrent inoperable or metastatic triple-negative breast cancer (Abstract GS01-05).
The ASCO Post Staff
Daniel G. Stover, MD, of The Ohio State University Comprehensive Cancer Center, discusses a biomarker analysis from the PALLAS adjuvant trial, which compared 2 years of the CDK4/6 inhibitor palbociclib with endocrine therapy vs endocrine therapy alone, as adjuvant treatment for patients with stage II–III hormone receptor–positive, HER2-negative breast cancer. The genomic subtype PAM50 was defined in the protocol of the PALLAS trial as the primary biomarker for analysis of prediction and prognosis (Abstract GS03-07).
The ASCO Post Staff
Reshma Jagsi, MD, DPhil, of Emory University Winship Cancer Institute, discusses the IDEA trial of endocrine therapy without radiotherapy after breast-conserving surgery for postmenopausal patients between the ages of 50 and 69 with stage I breast cancer. The regimen demonstrated a low risk of relapse in this population, with a genomic assay used in combination with classic clinical and biological features for treatment selection (Abstract GS02-08).
The ASCO Post Staff
Nadia Harbeck, MD, PhD, of LMU University Hospital and Ludwig Maximilian University of Munich, and Daniel Kates-Harbeck, of the West German Study Group and an MD Candidate at Ludwig Maximilian University of Munich, discuss a learning-based neural network developed by Mr. Kates-Harbeck to predict treatment outcomes in early breast cancer as well as potentially other tumor types (Abstract PO 04 1-10).
