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预测高危巴基斯坦乳腺癌患者携带BRCA1或BRCA2致病变异的可能性。

Predicting the likelihood of carrying BRCA1 or BRCA2 pathogenic variants in high-risk Pakistani breast cancer patients.

作者信息

Arif Shumaila, Muhammad Noor, Ang Boon Hong, Naeemi Humaira, Sami Waqas, Ho Weang Kee, Hamann Ute, Rashid Muhammad Usman

机构信息

Basic Sciences Research, Shaukat Khanum Memorial Cancer Hospital and Research Centre, 7-A, Block R-3, Johar Town, Lahore, Pakistan.

Cancer Research Malaysia, Subang Jaya, Malaysia.

出版信息

Breast Cancer Res Treat. 2025 May 20. doi: 10.1007/s10549-025-07724-4.


DOI:10.1007/s10549-025-07724-4
PMID:40392478
Abstract

PURPOSE: Pathogenic variants (PVs) in BRCA1/2 increase the lifetime risk of breast cancer (BC). Predictive algorithms for BRCA1/2 PVs, primarily developed for Caucasian BC patients, often underestimate carrier probability in Asian populations. The recently developed Asian Risk Calculator (ARiCa) aims to predict BRCA1/2 PV likelihood in Malaysian/Singaporean BC patients. This study investigates the ARiCa's performance in Pakistani female BC patients. METHODS: A cohort of 627 high-risk Pakistani female BC patients was evaluated. Using ARiCa, the likelihood of being a BRCA1/2 carrier was estimated based on factors such as age at diagnosis, ethnicity, bilateral BC status, tumor histopathological features, and family history of BC or ovarian cancer. The tool's discriminative ability was evaluated using the area under the curve (AUC). RESULTS: Of the participants, 133 (21.2%) were BRCA1 carriers, 25 (4.0%) were BRCA2 carriers, and 469 (74.8%) were non-carriers. The mean age at BC diagnosis was 34.3 years (range 19-73). Overall, ARiCa showed well calibration for predicting BRCA1/2 (HL 12.11, P = 0.147), BRCA1 (HL 14.17, P = 0.078), and BRCA2 carriers (HL 9.01, P = 0.342). The tool showed acceptable discrimination for BRCA1/2 (AUC 0.77, 95% CI 0.72-0.81) and BRCA1 carriers (AUC 0.80, 95% CI 0.75-0.84), but lower discrimination for BRCA2 carriers (AUC 0.51, 95% CI 0.39-0.64). At a 21% threshold, ARiCa would recommend BRCA1/2 screening for 43% of patients, with sensitivity and specificity at 73% and 68%, respectively. CONCLUSION: The ARiCa tool demonstrates strong predictive performance for BRCA1/2 carriers, specifically for BRCA1 carriers in Pakistani BC patients, suggesting its potential clinical utility.

摘要

目的:BRCA1/2基因的致病性变异(PVs)会增加患乳腺癌(BC)的终生风险。BRCA1/2 PVs的预测算法主要是针对白种人BC患者开发的,在亚洲人群中往往会低估携带概率。最近开发的亚洲风险计算器(ARiCa)旨在预测马来西亚/新加坡BC患者中BRCA1/2 PVs的可能性。本研究调查了ARiCa在巴基斯坦女性BC患者中的表现。 方法:对627名高危巴基斯坦女性BC患者进行了队列评估。使用ARiCa,根据诊断年龄、种族、双侧BC状态、肿瘤组织病理学特征以及BC或卵巢癌家族史等因素,估计成为BRCA1/2携带者的可能性。使用曲线下面积(AUC)评估该工具的判别能力。 结果:在参与者中,133人(21.2%)为BRCA1携带者,25人(4.0%)为BRCA2携带者,469人(74.8%)为非携带者。BC诊断时的平均年龄为34.3岁(范围19 - 73岁)。总体而言,ARiCa在预测BRCA1/2(HL 12.11,P = 0.147)、BRCA1(HL 14.17,P = 0.078)和BRCA2携带者(HL 9.01,P = 0.342)方面表现出良好的校准。该工具对BRCA1/2(AUC 0.77,95% CI 0.72 - 0.81)和BRCA1携带者(AUC 0.80,95% CI 0.75 - 0.84)显示出可接受的判别能力,但对BRCA2携带者的判别能力较低(AUC 0.51,95% CI 0.39 - 0.64)。在21%的阈值下,ARiCa会建议对43%的患者进行BRCA1/2筛查,敏感性和特异性分别为73%和68%。 结论:ARiCa工具对BRCA1/2携带者,特别是巴基斯坦BC患者中的BRCA1携带者,显示出强大的预测性能,表明其潜在的临床实用性。

相似文献

[1]
Predicting the likelihood of carrying BRCA1 or BRCA2 pathogenic variants in high-risk Pakistani breast cancer patients.

Breast Cancer Res Treat. 2025-5-20

[2]
Anticipation effect in Pakistani breast cancer families with or without BRCA1/2 pathogenic variants.

Cancer Epidemiol. 2025-6

[3]
Second Primary Cancer Risks After Breast Cancer in and Pathogenic Variant Carriers.

J Clin Oncol. 2025-2-20

[4]
Polygenic risk scores indicate extreme ages at onset of breast cancer in female BRCA1/2 pathogenic variant carriers.

BMC Cancer. 2022-6-27

[5]
Long-term health outcomes of bilateral salpingo-oophorectomy in BRCA1 and BRCA2 pathogenic variant carriers with personal history of breast cancer: a retrospective cohort study using linked electronic health records.

Lancet Oncol. 2025-6

[6]
Predicting the likelihood of germline pathogenic variants in unselected patients with breast cancer: analysis of more than 10,000 individuals.

J Med Genet. 2025-1-27

[7]
Incorporating tumour pathology information into breast cancer risk prediction algorithms.

Breast Cancer Res. 2010-5-18

[8]
Distribution of age at natural menopause, age at menarche, menstrual cycle length, height and BMI in BRCA1 and BRCA2 pathogenic variant carriers and non-carriers: results from EMBRACE.

Breast Cancer Res. 2025-5-21

[9]
Association of a Polygenic Risk Score With Breast Cancer Among Women Carriers of High- and Moderate-Risk Breast Cancer Genes.

JAMA Netw Open. 2020-7-1

[10]
Predicting the Likelihood of Carrying a or Mutation in Asian Patients With Breast Cancer.

J Clin Oncol. 2022-5-10

本文引用的文献

[1]
Commentary: Why is genetic testing underutilized worldwide? The case for hereditary breast cancer.

BJC Rep. 2024-10-1

[2]
Independent and joint associations of cardiometabolic multimorbidity and depression on cognitive function: findings from multi-regional cohorts and generalisation from community to clinic.

Lancet Reg Health West Pac. 2024-9-12

[3]
Validation of the BOADICEA model for predicting the likelihood of carrying pathogenic variants in eight breast and ovarian cancer susceptibility genes.

Sci Rep. 2023-5-26

[4]
Predicting the Likelihood of Carrying a or Mutation in Asian Patients With Breast Cancer.

J Clin Oncol. 2022-5-10

[5]
Evaluation of Germline Genetic Testing Criteria in a Hospital-Based Series of Women With Breast Cancer.

J Clin Oncol. 2020-5-1

[6]
Evaluating BRCA mutation risk predictive models in a Chinese cohort in Taiwan.

Sci Rep. 2019-7-15

[7]
Evaluation of Cancer-Based Criteria for Use in Mainstream BRCA1 and BRCA2 Genetic Testing in Patients With Breast Cancer.

JAMA Netw Open. 2019-5-3

[8]
BRCA1/2 testing: therapeutic implications for breast cancer management.

Br J Cancer. 2018-6-5

[9]
Risks of Breast, Ovarian, and Contralateral Breast Cancer for BRCA1 and BRCA2 Mutation Carriers.

JAMA. 2017-6-20

[10]
Breast cancer risk models: a comprehensive overview of existing models, validation, and clinical applications.

Breast Cancer Res Treat. 2017-4-25

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