ESTRO 2024 - Abstract Book

S620

Clinical - Breast

ESTRO 2024

Conclusion:

In patients transitioning from cN1 to ypN0, there was no significant difference in OS, DFS, and LRRFS based on RT field and molecular subtype.

Keywords: radiotherapy field, neoadjuvant chemotherapy

2189

Digital Poster

In Silico Prediction of Prospective Trials for (y)pN1 Breast Cancer Using Bayesian Network Model

Bum-Sup Jang 1,2 , Seok-Joo Chun 1 , Hyeon Seok Choi 1 , Ji Hyun Chang 1,2 , Kyubo Kim 3 , Kyung Hwan Shin 1,2,4

1 Seoul National University Hospital, Radiation Oncology, Seoul, Korea, Republic of. 2 Seoul National University College of Medicine, Radiation Oncology, Seoul, Korea, Republic of. 3 Seoul National University Bundang Hospital, Radiation Oncology, Seoul, Korea, Republic of. 4 Seoul National University Medical Research Center, Institute of Radiation Medicine, Seoul, Korea, Republic of

Purpose/Objective:

We aimed to develop a Bayesian network (BN) model to assess the overall disease burden (ODB) in patients with (y)pN1 breast cancer. We then compared the ODB between arms of ongoing prospective trials to evaluate their outcomes.

Material/Methods:

We developed a BN model using institutional data and expert surveys to assess the ODB in patients with (y)pN1 breast cancer. Probabilities and disability weights for radiotherapy-related risks were obtained through expert surveys. The ODB was defined as the sum of disability weights multiplied by probabilities. Using the BN model, we conducted in silico prediction for four trials (Alliance A011202, PORT-N1, RAPCHEM, and RT-CHARM) to compare the ODB, 7-year disease-free survival (DFS), and side effects.