Brown University and Rhode Island Hospital, Providence, RI.
Provista Diagnostics, New York, NY.
Clin Breast Cancer. 2017 Nov;17(7):516-525.e6. doi: 10.1016/j.clbc.2017.05.004. Epub 2017 May 23.
Despite significant advances in breast imaging, the ability to detect breast cancer (BC) remains a challenge. To address the unmet needs of the current BC detection paradigm, 2 prospective clinical trials were conducted to develop a blood-based combinatorial proteomic biomarker assay (Videssa Breast) to accurately detect BC and reduce false positives (FPs) from suspicious imaging findings.
Provista-001 and Provista-002 (cohort one) enrolled Breast Imaging Reporting and Data System 3 or 4 women aged under 50 years. Serum was evaluated for 11 serum protein biomarkers and 33 tumor-associated autoantibodies. Individual biomarker expression, demographics, and clinical characteristics data from Provista-001 were combined to develop a logistic regression model to detect BC. The performance was tested using Provista-002 cohort one (validation set).
The training model had a sensitivity and specificity of 92.3% and 85.3% (BC prevalence, 7.7%), respectively. In the validation set (BC prevalence, 2.9%), the sensitivity and specificity were 66.7% and 81.5%, respectively. The negative predictive value was high in both sets (99.3% and 98.8%, respectively). Videssa Breast performance in the combined training and validation set was 99.1% negative predictive value, 87.5% sensitivity, 83.8% specificity, and 25.2% positive predictive value (BC prevalence, 5.87%). Overall, imaging resulted in 341 participants receiving follow-up procedures to detect 30 cancers (90.6% FP rate). Videssa Breast would have recommended 111 participants for follow-up, a 67% reduction in FPs (P < .00001).
Videssa Breast can effectively detect BC when used in conjunction with imaging and can substantially reduce unnecessary medical procedures, as well as provide assurance to women that they likely do not have BC.
尽管乳腺成像技术取得了重大进展，但乳腺癌（BC）的检测仍然具有挑战性。为了满足当前 BC 检测模式的未满足需求，进行了两项前瞻性临床试验，以开发一种基于血液的组合蛋白质组生物标志物检测（Videssa Breast），以准确检测 BC 并减少可疑影像学结果的假阳性（FP）。
Provista-001 和 Provista-002（队列一）纳入了乳腺影像报告和数据系统 3 或 4 级、年龄在 50 岁以下的女性。评估了 11 种血清蛋白生物标志物和 33 种肿瘤相关自身抗体的血清。将 Provista-001 中的个体生物标志物表达、人口统计学和临床特征数据结合起来，开发了一种逻辑回归模型来检测 BC。使用 Provista-002 队列一（验证集）对性能进行了测试。
训练模型的敏感性和特异性分别为 92.3%和 85.3%（BC 患病率为 7.7%）。在验证集中（BC 患病率为 2.9%），敏感性和特异性分别为 66.7%和 81.5%。两个队列的阴性预测值均较高（分别为 99.3%和 98.8%）。Videssa Breast 在训练和验证集的综合表现为 99.1%的阴性预测值、87.5%的敏感性、83.8%的特异性和 25.2%的阳性预测值（BC 患病率为 5.87%）。总的来说，影像学导致 341 名参与者接受了后续程序以检测 30 例癌症（90.6%的 FP 率）。Videssa Breast 将建议 111 名参与者进行随访，FP 减少 67%（P<.00001）。
当与影像学结合使用时，Videssa Breast 可以有效地检测 BC，并可大大减少不必要的医疗程序，同时向女性保证她们很可能没有 BC。
