Phenotyping and Visualizing Infusion-Related Reactions for Breast Cancer Patients

摘要：

　　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.

关键词： Phenotype Patient Safety Algorithms

作者: Deyu Sun Gopal Sarda Steven J.Skube Anne H.Blaes Saif Khairat Genevieve B.Melton Rui Zhang

作者单位: School of Statistics Department of Computer Science and Engineering Department of Surgery Department of Medicine Carolina Health Informatics Program,University of North Carolina,NC,USA Department of Surgery;Institute for Health Informatics,University of Minnesota,MN,USA

会议类型: 国际会议

会议名称: 第十六届世界医药健康信息学大会((MEDINFO2017)、第二届世界医药健康信息学华语论坛(WCHIS 2017)、第15届全国医药信息学大会(CMIA 2017)

会议地点: 苏州

会议语种:英文

页码: 599-603

在线出版日期: 2017-08-21（万方平台首次上网日期，不代表论文的发表时间）