Detailed Information

Cited 2 time in webofscience Cited 2 time in scopus
Metadata Downloads

Prediction of Overall Disease Burden in (y)pN1 Breast Cancer Using Knowledge-Based Machine Learning Modelopen access

Authors
Chun, Seok-JooJang, Bum-SupChoi, Hyeon SeokChang, Ji HyunShin, Kyung Hwan
Issue Date
Apr-2024
Publisher
Multidisciplinary Digital Publishing Institute (MDPI)
Keywords
Bayesian network; disease burden; disability weights; breast cancer; radiotherapy; de-escalation; in silico
Citation
Cancers, v.16, no.8, pp 1 - 10
Pages
10
Indexed
SCIE
SCOPUS
Journal Title
Cancers
Volume
16
Number
8
Start Page
1
End Page
10
URI
https://scholarworks.dongguk.edu/handle/sw.dongguk/21895
DOI
10.3390/cancers16081494
ISSN
2072-6694
2072-6694
Abstract
Simple Summary We aimed to develop a Bayesian Network model to predict treatment outcomes and quality of life. Conditional probabilities and disability weights for radiotherapy-related benefit and risk were collected from nationwide expert survey. Overall disease burden (ODB) was defined as sum of conditional probabilities multiplied by disability weights. A Bayesian network model to predict ODB for (y)pN1 breast cancer was constructed. This model evaluated ongoing prospective trials for (y)pN1 breast cancer such as the Alliance A011202, PORT-N1, RAPCHEM, and RT-CHARM trials, validating reported results and assumptions.Abstract Background: We aimed to construct an expert knowledge-based Bayesian network (BN) model for assessing the overall disease burden (ODB) in (y)pN1 breast cancer patients and compare ODB across arms of ongoing trials. Methods: Utilizing institutional data and expert surveys, we developed a BN model for (y)pN1 breast cancer. Expert-derived probabilities and disability weights for radiotherapy-related benefit (e.g., 7-year disease-free survival [DFS]) and toxicities were integrated into the model. ODB was defined as the sum of disability weights multiplied by probabilities. In silico predictions were conducted for Alliance A011202, PORT-N1, RAPCHEM, and RT-CHARM trials, comparing ODB, 7-year DFS, and side effects. Results: In the Alliance A011202 trial, 7-year DFS was 80.1% in both arms. Axillary lymph node dissection led to higher clinical lymphedema and ODB compared to sentinel lymph node biopsy with full regional nodal irradiation (RNI). In the PORT-N1 trial, the control arm (whole-breast irradiation [WBI] with RNI or post-mastectomy radiotherapy [PMRT]) had an ODB of 0.254, while the experimental arm (WBI alone or no PMRT) had an ODB of 0.255. In the RAPCHEM trial, the radiotherapy field did not impact the 7-year DFS in ypN1 patients. However, there was a mild ODB increase with a larger irradiation field. In the RT-CHARM trial, we identified factors associated with the major complication rate, which ranged from 18.3% to 22.1%. Conclusions: The expert knowledge-based BN model predicted ongoing trial outcomes, validating reported results and assumptions. In addition, the model demonstrated the ODB in different arms, with an emphasis on quality of life.
Files in This Item
There are no files associated with this item.
Appears in
Collections
Graduate School > Department of Medicine > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher Chun, Seok Joo photo

Chun, Seok Joo
Graduate School (Department of Medicine)
Read more

Altmetrics

Total Views & Downloads

BROWSE