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
204P - A radiomics strategy based on CT intra-tumoral and peritumoral regions for preoperative prediction of neoadjuvant chemoradiotherapy for esophageal cancer
Presenter: zhiyang li
Session: Poster Display
Resources:
Abstract
205TiP - IMPACT: Randomized, multicenter, phase III study evaluating the efficacy of immunotherapy (atezolizumab) plus anti-VEGF therapy (bevacizumab) in combination with transcatheter arterial chemoembolization for unresectable hepatocellular carcinoma (HCC)
Presenter: Tatsuya Yamashita
Session: Poster Display
Resources:
Abstract
206TiP - SIERRA: A phase IIIb, single-arm, multicentre study of tremelimumab plus durvalumab for first-line treatment of advanced unresectable hepatocellular carcinoma
Presenter: Stephen Chan
Session: Poster Display
Resources:
Abstract
207TiP - A two-arm randomized open-label prospective design superiority phase III clinical trial to compare the efficacy of docetaxel-oxaliplatin-capecitabine/ 5 -fluorouracil (DOC/F) followed by docetaxel versus CAPOX/mFOLFOX-7 in advanced gastric cancers
Presenter: Prabhat Bhargava
Session: Poster Display
Resources:
Abstract
212P - Mutational landscape and characteristics of ERBB2 in urothelial carcinoma
Presenter: Mingwei Li
Session: Poster Display
Resources:
Abstract
213P - Prognostic significance of absolute lymphocyte count in patients with metastatic renal cell carcinoma treated with first-line combination immunotherapies: Results from the International metastatic renal cell carcinoma database consortium (IMDC)
Presenter: Kosuke Takemura
Session: Poster Display
Resources:
Abstract
214P - Development and prospective validation of a multiplex RNA urine test for noninvasive detection and surveillance of urothelial carcinoma
Presenter: Hua Xu
Session: Poster Display
Resources:
Abstract
215P - Real-world outcomes of first-line tislelizumab plus axitinib in patients with metastatic non-clear cell renal cell carcinoma (mnccRCC)
Presenter: Pei Dong
Session: Poster Display
Resources:
Abstract
216P - Preliminary efficacy and safety results from ‘ReBirth’: A phase II study of risk-based bladder-sparing therapy for MIBC
Presenter: Yijun Shen
Session: Poster Display
Resources:
Abstract
217P - Conditional reprogramming of urine-derived bladder cancer cells: A model for precision medicine
Presenter: Yu Dong
Session: Poster Display
Resources:
Abstract