血清miRNA提高了多元指数测定的附件质量分类的准确性
Serum miRNA improves the accuracy of a multivariate index assay for triage of an adnexal mass
影响因子:4.10000
分区:医学2区 Top / 妇产科学1区 肿瘤学2区
发表日期:2024 Nov
作者:
James W Webber, Laura Wollborn, Sudhanshu Mishra, Allison F Vitonis, Daniel W Cramer, Ryan T Phan, Todd C Pappas, Konrad Stawiski, Wojciech Fendler, Dipanjan Chowdhury, Kevin M Elias
摘要
为了确定将血清microRNA与蛋白质生物标志物和元数据相结合的多模式测定是否可以改善468名培训受试者的附加质量样品的分类评估（191例癌症病例和277例良性辅助质量质量对照或健康对照组），分析了7个蛋白质生物标记物和180蛋白生物标志物和180蛋白质标记物。将循环分析物数据与年龄和更年期状态（元数据）结合到神经网络模型中，以将样本分类为病例或对照。具有十倍交叉验证的正向回归使模型的维度最小化，同时最大程度地提高了病例和对照之间的线性分离。模型验证使用内部（44例和56例对照）和外部验证集（51例和59个对照组）进行。总研究人群包括678名受试者，包括286例和392个对照。总体而言，有290名受试者（43％）是绝经前。一组10个miRNA与蛋白质和元数据结合使用时提供了最佳性能。组合模型改善了内部（AUC = 0.9; 95％CI CI 0.81-0.95）和外部验证集（AUC = 0.95; 95％CI 0.90-0.98）的接收器操作员特征区域（ROC AUC）（ROC AUC）（ROC AUC）。在外部验证中，合并的模型总体上以80％的特异性提供了92％的敏感性，早期和晚期癌症的敏感性分别为80％和100％的敏感性，包括对早期卵巢癌的78％敏感性，浆液性卵巢癌的敏感性，以及对早期阶段的82％敏感性，对早期癌症，非sos虫，多态型号的蛋白质和蛋白质的蛋白质，蛋白质的蛋白质和蛋白质的蛋白质，蛋白质的蛋白质，蛋白质的蛋白质，蛋白质味。附加质量的分类。
Abstract
To determine whether a multimodal assay combining serum microRNA with protein biomarkers and metadata improves triage assessment of an adnexal mass.Serum samples from 468 training subjects (191 cancer cases and 277 benign adnexal mass controls or healthy controls) were analyzed for seven protein biomarkers and 180 miRNA. Circulating analyte data were combined with age and menopausal status (metadata) into a neural network model to classify samples as cases or controls. Forward regression with ten-fold cross-validation minimized the dimensionality of the model while maximizing linear separation between cases and controls. Model validation proceeded using both internal (44 cases and 56 controls) and external validation sets (51 cases and 59 controls).The total study population comprised 678 subjects, including 286 cases and 392 controls. Overall, 290 (43%) of the subjects were premenopausal. A panel of 10 miRNA delivered optimal performance when combined with protein and metadata features. The combined model improved the Receiver Operator Characteristic Area Under the Curve (ROC AUC) on the internal (AUC = 0.9; 95% CI 0.81-0.95) and external validation sets (AUC = 0.95; 95% CI 0.90-0.98) compared to miRNA alone or proteins plus metadata (without miRNA). On external validation, the combined model offered 92% sensitivity at 80% specificity overall, with 80% and 100% sensitivity for early and late-stage cancers, respectively, including 78% sensitivity for early-stage, serous ovarian cancers and 82% sensitivity for early-stage, non-serous cancers.A multimodal assay combining miRNA with protein biomarkers, age, and menopausal status improves surgical triage of an adnexal mass.