Cardiac risk stratification in cancer patients: A longitudinal patient –patient network analysis

by Yuan Hou, Yadi Zhou, Muzna Hussain, G. Thomas Budd, Wai Hong Wilson Tang, James Abraham, Bo Xu, Chirag Shah, Rohit Moudgil, Zoran Popovic, Chris Watson, Leslie Cho, Mina Chung, Mohamed Kanj, Samir Kapadia, Brian Griffin, Lars Svensson, Patrick Collier, Feixiong Cheng BackgroundCardiovascular disease is a leading cause of death in general population and the second leading cause of mortality and morbidity in cancer survivors after recurrent malignancy in the United States. The growing awareness of cancer therapy –related cardiac dysfunction (CTRCD) has led to an emerging field of cardio-oncology; yet, there is limited knowledge on how to predict which patients will experience adverse cardiac outcomes. We aimed to perform unbiased cardiac risk stratification for cancer patients using our large-scale, insti tutional electronic medical records. Methods and findingsWe built a large longitudinal (up to 22 years ’ follow-up from March 1997 to January 2019) cardio-oncology cohort having 4,632 cancer patients in Cleveland Clinic with 5 diagnosed cardiac outcomes: atrial fibrillation, coronary artery disease, heart failure, myocardial infarction, and stroke. The entire population includes 84% white Americans and 11% black Americans, and 59% females versus 41% males, with median age of 63 (interquartile range [IQR]: 54 to 71) years old.We utilized a topology-based K-means clustering approach for unbiased patient–patient network analyses of data from general demographics, echocar...
Source: PLoS Medicine - Category: Internal Medicine Authors: Source Type: research