Abstract 43P
Background
Breast cancer remains a significant concern worldwide. Risk-based screening, which tailors screening recommendations to individual risk levels, has been shown to enhance patient stratification. However, most research on model development focuses on Western populations, leaving the predictive accuracy of these models for Southeast Asian populations largely uncharacterized.
Methods
We conducted an observational case-control study comprising 305 Indonesian women to assess the applicability of published risk models to the local population. We employed a combined risk model to classify patients as either elevated or average risk. Our combined model evaluates two separate risk factors: genetic risk, assessed using ancestry-adjusted PRS scores based on the Mavaddat model, and clinical risk, evaluated using the Gail model. The performance of each individual model and their combined effectiveness were analyzed using the Area Under the Curve (AUC) and Odds Ratio (OR).
Results
Individual risk models retained their predictive efficacy in the Indonesian context. Specifically, the AUC achieved for genetic risk is AUC of 0.674 (p = 1.28 x 10-3; Risk group: OR = 3.16; p = 2.5 x 10-1). For clinical risk, the AUC stands at 0.674 (p = 5.16 x 10-4; Risk group: OR = 7.636; p = 6.1 x 10-3). Remarkably, when combined, the AUC increased to 0.701 (Risk group: OR= 3.897; p = 4.28 x 10-2), signifying the benefits of a multi-factor model. Based on a subset of the samples taken from this study, the Nala Breast Cancer Risk genetic risk algorithm generated higher AUC when compared to a leading third-party software that uses the same PRS model for breast cancer (0.63 vs 0.55). This improvement is primarily due to our method of translating PRS scores into categorical outcomes, which integrates localized disease incidence and mortality rates.
Conclusions
Our findings demonstrate for the first time the applicability of the Polygenic Risk Score using Mavaddat model and clinical score using Gail model to Indonesian populations. In addition, our study shows that, within this demographic, combined risk models provide a superior predictive framework compared to single-factor approaches.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
The authors.
Funding
NalaGenetics.
Disclosure
The author has declared no conflicts of interest.
Resources from the same session
362P - Efficacy and safety of MCLA-129, an anti-EGFR/c-MET bispecific antibody, in head and neck squamous cell cancer (HNSCC)
Presenter: Irene Braña
Session: Poster Display
Resources:
Abstract
363P - Effect of financial distress and mental well-being of patients with early vs advanced oral cancer on informal caregiver's quality of life: A prospective real-world data from public health sector hospital
Presenter: Abhinav Thaduri
Session: Poster Display
Resources:
Abstract
364P - Artificial intelligence provides more accurately neck lymph nodes auto-segmentation in radiotherapy
Presenter: chiencheh Chen
Session: Poster Display
Resources:
Abstract
365P - Radiotherapy treatment outcomes and treatment compliance of nasopharyngeal cancer patients in Sabah: A retrospective analysis
Presenter: Anbarasan Anbazagan
Session: Poster Display
Resources:
Abstract
366P - Pre-treatment oral fungal microbiome and nasopharyngeal carcinoma prognosis: A population-based cohort study in southern China
Presenter: Yufeng Chen
Session: Poster Display
Resources:
Abstract
367P - Prevalence and association of sarcopenia with mortality in patients with head and neck cancer: A meta-analysis
Presenter: Claire Lim
Session: Poster Display
Resources:
Abstract
368P - Distinct gene expression profiling explored using nanostring tumor signalling 360 panel with validations in different clinical stages of oral submucous fibrosis patients: A first Indian study
Presenter: Yasasve Madhavan
Session: Poster Display
Resources:
Abstract
370P - Low-dose nivolumab with induction chemotherapy for inoperable HNSCC in 111 patients: Response rates, survival, and implications for LMICs
Presenter: Josh Thomas Georgy
Session: Poster Display
Resources:
Abstract
371P - The role of FDG-PET/CT in the assessment of response to radiation therapy in head and neck cancers: A systematic review and meta-analysis
Presenter: Felix Wijovi
Session: Poster Display
Resources:
Abstract
372P - Effectiveness of HAN-MI-RADS (head and neck molecular imaging-reporting and data system) criterion in head and neck squamous cell carcinoma post concurrent chemoradiotherapy
Presenter: Manoj Gupta
Session: Poster Display
Resources:
Abstract