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Phenotyping and Visualizing Infusion-Related Reactions for Breast Cancer Patients

机译:表型和可视化乳腺癌患者的输液相关反应

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Infusion-related reactions (IRRs) are typical adverse events for breast cancer patients. Detecting IRRs and visualizing their occurance associated with the drug treatment would potentially assist clinicians to improve patient safety and help researchers model IRRs and analyze their risk factors. We developed and evaluated a phenotyping algorithm to detect IRRs for breast cancer patients. We also designed a visualization prototype to render IRR patients' medications, lab tests and vital signs over time. By comparing with the 42 randomly selected doses that are manually labeled by a domain expert, the sensitivity, positive predictive value, specificity, and negative predictive value of the algorithms are 69%, 60%, 79%, and 85%, respectively. Using the algorithm, an incidence of 6.4% of patients and 1.8% of doses for docetaxel, 8.7% and 3.2% for doxorubicin, 10.4% and 1.2% for paclitaxel, 16.1% and 1.1% for trastuzumab were identified retrospectively. The incidences estimated are consistent with related studies.
机译:输液相关的反应(IRRS)是乳腺癌患者的典型不良事件。检测isss和可视化与药物治疗相关的发生可能有助于临床医生,以改善患者的安全性,帮助研究人员模型,分析其风险因素。我们开发并评估了一种表型鉴定算法,用于检测乳腺癌患者的IRS。我们还设计了一种可视化原型,以使IRR患者的药物,实验室测试和生命症状随着时间的推移。通过与由域专家手动标记的可随机选择的剂量进行比较,算法的敏感度,阳性预测值,特异性和负预测值分别为69%,60%,79%和85%。使用该算法,6.4%的患者的发病率和多西紫杉醇剂量为1.8%,对紫杉醇的8.7%和3.2%,对紫杉醇的10.4%和1.2%进行了回顾性,16.1%和1.1%的曲妥珠单抗。估计的发病率与相关研究一致。

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