Editor's Note: The 47th San Antonio Breast Cancer Symposium (SABCS), held from December 10–13, 2024, in San Antonio, USA, showcased the latest breakthroughs in breast cancer research, clinical practices, and technological innovations. This edition of "SABCS Broadcast" is hosted by Prof. Yongmei Yin from Jiangsu Provincial People’s Hospital, with live reporting by Prof. Junjie Li from Fudan University Shanghai Cancer Center. The discussion highlights the joint analysis of NRG Oncology/RTOG 9804 and ECOG-ACRIN E5194 on tamoxifen (TAM) use in low-risk ductal carcinoma in situ (DCIS), findings from the INSEMA trial on avoiding sentinel lymph node biopsy (SLND) in breast-conserving surgery patients, and the application of artificial intelligence (AI) in breast cancer risk screening.

01. DCIS: Can TAM Be Skipped Along With Radiation?

Prof. Junjie Li: Study GS2-02 combines data from two pivotal trials, NRG Oncology/RTOG 9804 and ECOG-ACRIN E5194, which investigate whether low-risk DCIS patients undergoing breast-conserving surgery benefit from adjuvant radiation therapy (RT) and endocrine therapy.

This joint analysis focuses on patients who did not receive RT and found that TAM reduces the risk of ipsilateral breast recurrence, particularly invasive breast cancer, but offers no significant benefit in preventing DCIS recurrence.

This is an intriguing development. For low-risk DCIS patients who forgo RT, the risk of breast recurrence remains low. This raises the question: can endocrine therapy, such as TAM, also be omitted, further simplifying treatment?

In current clinical practice, decisions for DCIS patients after breast-conserving surgery often rely on the Van Nuys Prognostic Index (VNPI), which considers factors like age, tumor size, and margin status. However, this study suggests that even without RT and TAM, low-risk DCIS patients may still achieve favorable outcomes.

Nevertheless, caution is critical when de-escalating treatment. While progression from DCIS to life-threatening disease is rare, local recurrence is still a concern. For low-risk patients in this study, the 15-year ipsilateral breast recurrence rate was 11.4% with TAM but rose to 19.0% without any adjuvant therapy, meaning one in five patients could experience local recurrence during follow-up. These findings must be carefully weighed in clinical decision-making.

02. Breast-Conserving Surgery: No Need for SLND in Certain Patients

Prof. Junjie Li: The second study (GS2-07) focuses on the INSEMA trial, a topic of great interest to surgeons. The study offers a comparison between the SOUND and INSEMA trials in its final presentation slides. INSEMA had a larger sample size, covering more than 5,500 patients, and included a broader patient population. While the SOUND trial only enrolled patients with clinical T1N0 tumors ≤2 cm, INSEMA included a subset of T2 tumors ≤5 cm, with 90% being ≤2 cm.

The INSEMA trial demonstrated that clinically node-negative patients could safely omit sentinel lymph node biopsy (SLND) without affecting treatment outcomes. Long-term follow-up showed that the five-year invasive disease-free survival (iDFS) rates for the SLND and no-SLND groups were 91.9% and 91.7%, respectively, meeting the non-inferiority criterion (HR 0.91).

This finding is particularly appealing to surgeons. By omitting SLND, patients can avoid potential upper limb complications, and the procedure time can be significantly reduced. From a pharmacoeconomic perspective, eliminating surgery and extensive pathological evaluations leads to substantial cost savings. Among every 100 patients, only one experienced local axillary recurrence. With more accurate clinical assessments, this recurrence rate is expected to decrease even further.

03. AI Risk Prediction: What’s My 10-Year Breast Cancer Risk?

Prof. Junjie Li: The third study (GS2-10) explores the use of artificial intelligence (AI) in predicting breast cancer risk. This research relied on long-term population observations and utilized AI models to track normal women over time, identifying those who eventually developed breast cancer.

What makes this study unique is the integration of AI-driven image analysis at the outset. By collecting imaging data and identifying specific characteristics, the study predicts which individuals are more likely to develop breast cancer in the future.

However, implementing this approach on a large scale is challenging, as it is impractical to test every woman and provide predictions about their future breast cancer risk. Nonetheless, the study is groundbreaking, showcasing AI’s potential in the diagnosis and treatment of breast cancer and other tumors.

Previously, AI was primarily used to analyze CT images, such as identifying pulmonary nodules. Now, AI plays a significant role in assisting mammographic screenings. Moreover, by capturing and analyzing large datasets, AI can build predictive models for breast cancer risk. Importantly, these models become increasingly accurate as more data is input.

This study underscores the importance of adopting a broader perspective as clinicians, exploring innovative methods to improve patient outcomes.

Closing Remarks

Prof. Yongmei Yin: Thank you, Prof. Junjie Li, for your insightful reporting on these studies. Your analysis provides a more comprehensive understanding of early breast cancer treatment and prevention.

• Combined trial data suggests that low-risk DCIS patients may safely skip both RT and endocrine therapy post-breast-conserving surgery.
• The INSEMA trial confirms that early breast cancer patients can omit SLND after breast-conserving surgery without compromising outcomes.
• AI-powered imaging models offer innovative tools for breast cancer screening and prevention.

These studies pave the way for new clinical directions and have the potential to benefit more patients. Stay tuned for tomorrow’s “SABCS Broadcast,” where we will connect with Prof. Qiang Liu from Sun Yat-sen Memorial Hospital for more exciting updates from SABCS. Don’t miss it!

Prof. Yongmei Yin

• Vice President, Jiangsu Provincial People’s Hospital
• Professor, Chief Physician, PhD Supervisor
• Vice President, Chinese Society of Clinical Oncology (CSCO)
• Secretary-General, CSCO Breast Cancer Expert Committee

Chair, CSCO Patient Education Expert Committee

• Deputy Chair, CSCO Smart Healthcare Committee
• Executive Member, Breast Cancer Committee, Chinese Anti-Cancer Association (CBCS)

Prof. Junjie Li

• Deputy Chief Physician, Associate Professor, Fudan University Shanghai Cancer Center
• Administrative Deputy Director, Breast Surgery; Director, Pudong Ward
• Youth Expert, Breast Cancer Committee, Chinese Anti-Cancer Association
• Youth Expert, Breast Cancer Group, Chinese Medical Association
• Secretary-General, Breast Cancer Committee, Shanghai Anti-Cancer Association
• Executive Member, Breast Cancer Rehabilitation Committee, Chinese Anti-Cancer Association
• Co-Editor, Chinese Journal of Breast Disease
• Specialized training in breast cancer at Massachusetts General Hospital Cancer Center
• Published nearly 20 SCI papers in leading journals like JCO
• Principal Investigator, National Natural Science Foundation Project