Cancers
Historical Baseline Electrocardiogram Ascertainment Prior to Cancer Diagnosis and Cardiovascular Diagnosis Patterns in Cancer Survivors: A Retrospective Observational Cohort Study
By Cameron Otto, Rushabh Shah, Sneha Nagavally and 3 others.
Abstract
Background
Cardiovascular disease (CVD) remains a leading cause of morbidity and mortality among cancer survivors. Contemporary cardio-oncology frameworks emphasize baseline cardiovascular risk assessment before potentially cardiotoxic cancer therapies. Historical real world implementation of baseline electrocardiography (ECG), however, remains incompletely characterized. The objective of this study was to characterize historical baseline ECG ascertainment before cancer diagnosis and examine its association with documented cardiovascular diagnosis patterns in cancer survivors.
Methods
We conducted a retrospective observational cohort study of 4592 adult cancer survivors within the Froedtert & Medical College of Wisconsin health system from 2000 to 2020. The analytic cohort was derived from a previously established longitudinal cancer survivor resource integrating demographic and cardiovascular clinical data, cancer treatment exposures, multimodality cardiac function ascertainment, and linked clinical, radiation oncology, and cancer registry information. Cardiac function ascertainment from an available cardiovascular imaging modality within three years before cancer diagnosis was one component of the analytic cohort definition. Patients were stratified by ascertainment of a 12-lead ECG within the same pre-diagnostic interval. Cardiovascular diagnoses documented before and after cancer diagnosis were characterized separately. For the newly documented diagnosis analyses, each cardiovascular outcome was evaluated among participants without a prior diagnosis of that same condition before cancer diagnosis. A multivariable logistic regression model evaluated the association between baseline ECG ascertainment and newly documented overall CVD diagnosis (including HF, AFIB, CAD, and stroke) while adjusting for age, sex, race, comorbidity count, and treatment count.