A Cancer Paradox: Machine-Learning Backed Propensity-Score Analysis of Coronary Angiography Findings in Cardio-Oncology.

Journal: The Journal of invasive cardiology

PMID: 30611123

Abstract

OBJECTIVES: Cancer has been proposed as a cardiovascular risk factor. We aimed to assess the cardiovascular risk profile and coronary angiography (CA) findings of cancer patients and compare them to those of patients without cancer.

Authors

Dinu Valentin Balanescu
Dominique J Monlezun

Department of Cardiology, The University of Texas M.D. Anderson Cancer Center, Houston, TX, United States.
Teodora Donisan
David Boone
Frances Cervoni-Curet
Nicolas Palaskas
Juan Lopez-Mattei

Department of Cardiology, The University of Texas M.D. Anderson Cancer Center, Houston, TX, United States.
Peter Kim

Department of Cardiology, The University of Texas M.D. Anderson Cancer Center, Houston, TX, United States.
Cezar Iliescu

Department of Cardiology, The University of Texas M.D. Anderson Cancer Center, Houston, TX, United States.
Serban Mihai Balanescu

Keywords

Academic Medical Centers Age Factors Aged Aged, 80 and over Cancer Care Facilities Case-Control Studies Coronary Angiography Coronary Artery Disease Female Humans Logistic Models Machine Learning Male Multivariate Analysis Neoplasms Prevalence Propensity Score Reference Values Retrospective Studies Risk Assessment Sex Factors Texas

External Resources

View on PubMed Access via DOI PubMed (30611123)

A Cancer Paradox: Machine-Learning Backed Propensity-Score Analysis of Coronary Angiography Findings in Cardio-Oncology.

Abstract

Authors

Keywords

External Resources

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