Phenotyping and Visualizing Infusion-Related Reactions for Breast Cancer Patients

Abstract

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.

Keywords: Algorithms; Patient Safety; Phenotype.

Figure 1

Flowchart of the method

Figure 2

IRRs phenotyping algorithm

Figure 3

Visualization of two IRRs events (a) An IRR detected by greatly increased blood pressure after the infusion of 141 mg of paclitaxel. (b) An IRR of chills and nausea after the infusion of 140 mg of docetaxel.