BRCA testing in Asian ovarian cancer patients: Standard clinical practice or Mutation prediction model?

BACKGROUND: Germline BRCA1/2 testing is recommended for all ovarian cancer patients, as identifying pathogenic variants (PVs) informs treatment and enables family cascade testing. However, in resource-limited settings, high testing costs often limit feasibility. An alternative approach is to use predictive models to prioritize patients at risk, optimizing resource allocation. Existing models are largely Western-derived; in Asian populations, models exist for breast cancer-not ovarian cancer. METHODS: Using data from a multi-center study of 1,126 Asian patients with ovarian cancer (including 147 BRCA PV carriers), we developed models incorporating cancer history, clinicopathological features, and reproductive factors to estimate likelihood of carrying PVs. We assessed discrimination, calibration, and accuracy, and compared genetic testing costs to a universal testing strategy. RESULTS: Our final model demonstrated good calibration and strong discriminatory power, with an area under the curve of 0.80 (95% confidence interval:0.74-0.87). Factors included in the model were age at diagnosis, ethnicity, personal and family cancer history, and clinicopathological features. The model had 77% accuracy at the optimal threshold for testing, compared to 13% accuracy with universal testing, reducing genetic testing costs from ~USD4,371 to ~USD1,974 per identified carrier. Notably, while maintaining 100% sensitivity, the model reduced testing by 15%, yielding potential savings of ~USD68,182 per 800 patients each year. CONCLUSIONS: Targeted testing using a prediction model potentially offers a more efficient and scalable alternative when universal testing is not feasible, optimizing impact in resource-limited settings. IMPACT: This work supports more affordable and equitable BRCA testing pathways for Asian ovarian cancer patients.

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Publication Details

Journal
Cancer Epidemiology Biomarkers & Prevention
Published
2026-04-21
DOI
https://doi.org/10.1158/1055-9965.epi-25-2008
Primary Topic
BRCA gene mutations in cancer
Type
article
Field-Weighted Citation Impact
0.00
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article

BRCA testing in Asian ovarian cancer patients: Standard clinical practice or Mutation prediction model?

Yin Ling Woo, M.J. Makanjang, Soo-Fan Ang, Mei-Chee Tai et al.
Cancer Epidemiology Biomarkers & Prevention
BRCA gene mutations in cancer
article

BRCA testing in Asian ovarian cancer patients: Standard clinical practice or Mutation prediction model?

Yin Ling Woo, M.J. Makanjang, Soo-Fan Ang, Mei-Chee Tai, Mohd Pazudin Ismail, Chee-Meng Yong, Rozita Abdul Malik, Soo‐Hwang Teo, Lye Mun Tho, Z. Wong, Kean-Fatt Ho, Boon Hong Ang, Mohamad Nasir Shafiee, Weang-Kee Ho, Ismail Aliyas, Ahmad Muzamir Ahmad Mustafa, Gaik-Siew Ch’ng, S.C. Lee, Chun Sen Lim, Azura Deniel, Meow‐Keong Thong, K. P. Lim, Fuad Ismail, Jamil Omar, Jo Yi Chow, Wee-Wee Sim, Xin Wen Lee, Nur Tiara Hassan, Joanna Lim, Sook-Yee Yoon, Ahmad Radzi Ahmad Badruddin, Nellie L.C. Cheah, Suguna Subramaniam, Chee‑Kin Fong, Shahila Tayib, John Seng Hooi. Low
article en

Abstract

BACKGROUND: Germline BRCA1/2 testing is recommended for all ovarian cancer patients, as identifying pathogenic variants (PVs) informs treatment and enables family cascade testing. However, in resource-limited settings, high testing costs often limit feasibility. An alternative approach is to use predictive models to prioritize patients at risk, optimizing resource allocation. Existing models are largely Western-derived; in Asian populations, models exist for breast cancer-not ovarian cancer. METHODS: Using data from a multi-center study of 1,126 Asian patients with ovarian cancer (including 147 BRCA PV carriers), we developed models incorporating cancer history, clinicopathological features, and reproductive factors to estimate likelihood of carrying PVs. We assessed discrimination, calibration, and accuracy, and compared genetic testing costs to a universal testing strategy. RESULTS: Our final model demonstrated good calibration and strong discriminatory power, with an area under the curve of 0.80 (95% confidence interval:0.74-0.87). Factors included in the model were age at diagnosis, ethnicity, personal and family cancer history, and clinicopathological features. The model had 77% accuracy at the optimal threshold for testing, compared to 13% accuracy with universal testing, reducing genetic testing costs from ~USD4,371 to ~USD1,974 per identified carrier. Notably, while maintaining 100% sensitivity, the model reduced testing by 15%, yielding potential savings of ~USD68,182 per 800 patients each year. CONCLUSIONS: Targeted testing using a prediction model potentially offers a more efficient and scalable alternative when universal testing is not feasible, optimizing impact in resource-limited settings. IMPACT: This work supports more affordable and equitable BRCA testing pathways for Asian ovarian cancer patients.

Cancer Epidemiology Biomarkers & Prevention
University of Nottingham Malaysia Campus (MY), Hospital Kuala Lumpur (MY), Hospital Tengku Ampuan Afzan (MY), Hospital Pulau Pinang (MY), Sarawak General Hospital (MY), Gleneagles Hospital (SG), University Kebangsaan Malaysia Medical Centre (MY), Assunta Hospital (MY), Penang Adventist Hospital (MY), Sultan Ismail Specialist Hospital (MY), University of Malaya (MY), Hospital Universiti Sains Malaysia (MY), Newcastle University Medicine Malaysia (MY), Cancer Research Malaysia (MY), Kanti Children's Hospital (NP), Al-Sabah Hospital (KW), National Cancer Institute (MY), Institut Penyelidikan Veterinar (MY), Subang Jaya Medical Centre (MY), Hospital Sultanah Bahiyah (MY), KPJ Ampang Puteri Specialist Hospital (MY), National Cancer Research Institute (GB), Sunway University (MY)
Reduced inequalities
Openalex Percentile: Top 12%
BRCA gene mutations in cancer
DOISourceOpenAlex
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