Clinical Challenges and AI Opportunities in Decision-Making for Cancer Treatment-Induced Cardiotoxicity

TL;DR

This paper explores the clinical challenges in diagnosing and monitoring cancer treatment-induced cardiotoxicity and discusses how digital health tools can support clinicians in improving decision-making processes.

Contribution

It provides a detailed analysis of clinicians' decision-making workflows and identifies key needs for digital health solutions to enhance cardiotoxicity management.

Findings

Clinicians face difficulties due to lack of unified protocols.

Monitoring relies on subjective patient reports, which are often inaccurate.

There is a strong need for early detection tools with remote monitoring capabilities.

Abstract

Cardiotoxicity induced by cancer treatment has become a major clinical concern, affecting the long-term survival and quality of life of cancer patients. Effective clinical decision-making, including the detection of cancer treatment-induced cardiotoxicity and the monitoring of associated symptoms, remains a challenging task for clinicians. This study investigates the current practices and needs of clinicians in the clinical decision making of cancer treatment-induced cardiotoxicity and explores the potential of digital health technologies to support this process. Through semi-structured interviews with seven clinical experts, we identify a three-step decision-making paradigm: 1) symptom identification, 2) diagnostic testing and specialist collaboration, and 3) clinical decision-making and intervention. Our findings highlight the difficulties of diagnosing cardiotoxicity (absence of unified protocols and high variability in symptoms) and monitoring patient symptoms (lacking accurate and timely patient self-reported symptoms). The clinicians also expressed their need for effective early detection tools that can integrate remote patient monitoring capabilities. Based on these insights, we discuss the importance of understanding the dynamic nature of clinical workflows, and the design considerations for future digital tools to support cancer-treatment-induced cardiotoxicity decision-making.