Ep 80: SABCS 2024 Recap - Precision Medicine in Breast Cancer Care with Dr. Doug Blayney-The Patient From Hell Podcasr
In this insightful episode of The Patient From Hell podcast, host Samira Daswani and Dr. Doug Blayney break down key takeaways from the 2024 San Antonio Breast Cancer Symposium (SABCS). Their discussion covers four pivotal advancements in breast cancer treatment: CDK4/6 inhibitors, antibody-drug conjugates (ADCs), de-escalation strategies for ductal carcinoma in situ (DCIS), and the transformative role of artificial intelligence in cancer diagnostics. A recurring theme throughout the conversation is the growing ability to tailor treatments to individual patients—taking into account biomarkers, treatment options, and personal priorities for both longevity and quality of life.
Key Highlights:
- Biomarker advancements are enabling more precise, personalized treatment strategies across various breast cancer subtypes.
- Patient-centered care is at the forefront, with decisions now weighing survival benefits alongside quality of life considerations.
- Innovative technologies like antibody-drug conjugates and artificial intelligence are reshaping breast cancer care, refining both diagnostic accuracy and treatment approaches.
About Our Guest:
Dr. Doug Blayney is a distinguished oncology physician specializing in breast cancer and serves as the Chief Medical Officer at Manta Cares. His research focuses on improving cancer care delivery, advancing drug development, and enhancing the patient experience.
Throughout his career, Dr. Blayney has held influential leadership roles in oncology. He was the founding Editor-in-Chief of ASCO’s flagship practice journal and, during his tenure as ASCO President, spearheaded initiatives such as the ASCO Quality Symposium and early planning for CancerLinq. Additionally, he was a founding member of the National Comprehensive Cancer Network (NCCN) Growth Factor Guideline panel and has served on both the FDA’s Oncology Drugs Advisory Committee and the NCCN Board of Directors.
Key Moments:
At 38 minutes: "There's a company now that has a gene expression panel that may predict, and it looks like it does predict, whether radiation treatment after standard treatment for DCIS is beneficial. So if this predicted biomarker of benefit for radiation pans out, and I think it probably will, that means that we can deescalate or personalize whether radiation treatment and its side effects are likely to be beneficial to that patient."
At 45 minutes: "Quality of life, can that be answered by a nine question questionnaire? Well, maybe. If you can't get out of bed, your quality of life is because something hurts or if your arm doesn't work because they're so swollen, that's one extreme... What about 15 years playing that duet? What about three? It's those kind of subtleties that we need to take into account."
At 49 minutes:"AI can interpret mammograms. The images from a mammogram 20 years ago, there were four, top, bottom, side, side, and maybe another oblique. And now there's 60 images from a mammogram. So that means that a radiologist, a human radiologist, whether it's next door or around the world, somebody needs to look at those. AI can help."
Disclaimer: All content and information provided in connection with Manta Cares is solely intended for informational and educational purposes only. This content and information is not intended to be a substitute for medical advice, diagnosis, or treatment. Always seek the advice of your physician or other qualified health provider with any questions you may have regarding a medical condition.
This episode is sponsored by Gilead Oncology. Gilead had no involvement or input in the podcast content. Gilead Oncology is working to transform how cancer is treated. We are innovating with next-generation therapies, combinations, and technologies to deliver improved outcomes for people with cancer. From antibody drug conjugates and small molecules to cell therapy-based approaches, our portfolio and pipeline assets are creating new possibilities for people with cancer.
