2022 Multidisciplinary Head and Neck Cancers Symposium Press Kit
The 2022 Multidisciplinary Head and Neck Cancers Symposium took place February 24-26 in Phoenix, Arizona. This two-and-a-half-day meeting for the head and neck cancer community provided the most up-to-date information on multidisciplinary therapies, clinical research, treatment strategies, supportive care and scientific breakthroughs.
The meeting was co-sponsored by the American Society for Radiation Oncology (ASTRO), the American Society of Clinical Oncology (ASCO), the American Head & Neck Society (AHNS) and the Society for Immunotherapy of Cancer (SITC).
News Releases
Symposium leadership selected three studies as highlights for media:
This phase II trial found that PET scans obtained before and midway through treatment for p16-positive oropharynx cancer (OPC) can help determine whether a patient can receive a lower dose of radiation therapy in the second half of their treatment course without compromising cancer control. Patients in the trial who received de-escalated therapy experienced fewer short-term side effects than those who received standard therapy.
- Abstract 1: Early Toxicity and Patient Reported Outcomes from a Phase 2 Trial of FDG-PET Response-Based De-Escalated Definitive Radiotherapy for p16+ Oropharynx Cancer; presented by Steven Allen, MD, PhD, University of Michigan
This large, multi-institutional study demonstrated that a blood test to detect circulating tumor DNA can accurately predict recurrence of HPV-driven oropharyngeal cancer following treatment. Results also indicate that the biomarker test may detect recurrent disease earlier than imaging or other standard methods of post-treatment surveillance, allowing physicians to personalize treatment more quickly for patients whose cancer returns.
- Abstract 3: Detection of Occult Recurrence Using Circulating HPV Tumor DNA Among Patients Treated for HPV-driven Oropharyngeal Squamous Cell Carcinoma; presented by Glenn J. Hanna, MD, Dana-Farber Cancer Institute
This found that an artificial intelligence (AI) model incorporating multiple methods of machine learning accurately detects thyroid cancer and predicts pathological and genomic outcomes through analysis of routine ultrasound images. The AI model could present a low-cost, non-invasive option for screening, staging and personalized treatment planning for the disease.
- Abstract 10: An Artificial Intelligence Ultrasound Platform for Screening and Staging of Thyroid Cancer; presented by Annie Chan, MD, Mass General Cancer Center
For More Information
For media-related questions and interview requests, email ASTRO’s media relations team.
For details about the meeting, visit the symposium website. Abstracts and author disclosures are available in the conference planner.
For the latest updates, follow the meeting hashtag, #HNCS22, and follow ASTRO on social media.
For general information about radiation therapy, visit RTAnswers.org.