|Although new cancer treatment therapy has been increasingly developed, fluoropyrimidines, such as 5-fluorouracil (5-FU) and capecitabine, are widely used alone or in combination regimens as chemotherapy for the treatment of cancer, especially as first-line treatments for colorectal malignancies. However, fluoropyrimidine-based regimens have a variety of associated toxicity, in which cardiotoxicity is one of the most severe, life-threatening adverse reactions leading to emergency department visits, hospitalizations, and even sudden death. Understanding the risk and risk factors will help physicians early predict fluoropyrimidine-induced cardiotoxicity (FIC) and detect cardiotoxicity before cardiac tissues become pathologically damaged. Several attempts to identify potential risk factors for FIC have been made; however, the evidence is not compelling due to data heterogeneity, low statistical power, and methodological limitations. In this doctoral dissertation project, a mixed-methods approach was used to assess the risk of FIC with the overall objective that patients at high risks could be identified before the adverse event of FIC to ensure safe application of fluoropyrimidine medications. In detail, this study 1) systematically evaluated existing literature in risk factors for fluoropyrimidine-induced cardiotoxicity (FIC) among cancer patients, 2) estimated and compared the risk of cardiotoxicity by types of colorectal cancer (CRC) treatments in older CRC patients, 3) developed cardiotoxicity risk screening tools based on relevant treatment-related and patient-related risk factors using machine learning algorithm-based prediction modeling to predict cardiotoxicity risks for CRC patients who were undergoing fluoropyrimidine-based treatments.
In order to present the dissertation clearly, this synopsis provides a summary of the chapters and contents.
Chapter 1 presents a brief introduction on the background, objective, and meaningfulness of my work.
Chapter 2 illustrates a detailed literature review on the burden of CRC in the U.S., CRC treatments, fluoropyrimidine-induced cardiotoxicity and risk factors, machine learning methods, and knowledge gaps.
Chapter 3 describes the methodology of this dissertation study by each aim.
Chapter 4 provides the results of each aim.
Chapter 5 summarizes key findings and implications of this research work and outlines possible future directions that would follow this work.