| Title: | Assessing Risk Factors and Developing an Early Prediction Model for Cancer Therapy-Related Cardiotoxicity |
| Lead Institution: | The First Affiliated Hospital of Chongqing Medical University |
| Principal investigator: |
Application 387995
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About
With advancements in cancer detection and treatment, the number of cancer survivors has significantly increased. However, cancer therapies often come with severe side effects, particularly cardiovascular toxicity. Cancer therapy-related cardiovascular dysfunction occurs in approximately 10% of patients and has a mortality rate exceeding 50%. Many cancer patients are more likely to die from cardiovascular issues than from cancer itself. Therefore, it is crucial to focus on early prediction and risk assessment of cardiotoxicity to improve prevention and management, ultimately enhancing long-term health outcomes for cancer patients. Our project aims to identify risk factors and develop an early prediction model for cancer therapy-related cardiotoxicity. We also seek to uncover any genetic risk factors associated with this condition, helping clinicians stratify patients by risk level, enabling earlier interventions, and closer monitoring for those at high risk. This three-year project will utilize data from the UK Biobank. Initially, we will integrate comprehensive data on cancer patients, including environmental and behavioral factors, laboratory results, imaging data, omics, and genetic information. By analyzing these diverse data sources, we aim to discover the risk factors that contribute to the onset and progression of cardiovascular disease following cancer therapy. Once identified, we will select the most relevant markers to develop assessment models tailored for various clinical scenarios. These models will be created using both traditional statistical methods (such as Cox regression and logistic regression) and machine learning techniques. Additionally, our research will delve into the mechanisms behind cancer therapy-related cardiotoxicity, potentially identifying new therapeutic targets. This research underscores the need for heightened attention to cardiovascular risks in cancer patients. By providing a method for early prediction and risk assessment, our work will significantly impact the prevention and management of cancer therapy-related cardiotoxicity. Early identification of high-risk individuals will allow for timely interventions, potentially reducing morbidity and mortality rates among cancer patients. Our findings will also contribute to a better understanding of the underlying mechanisms of cardiotoxicity, paving the way for improved treatments and patient care strategies. In summary, this project will offer valuable insights into the risk factors of cancer therapy-related cardiotoxicity and provide practical tools for early prediction, ultimately enhancing the quality of life and survival rates for cancer patients.1 Publication
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 17503 | Ripk1-dependent PANoptosis promotes EndMT and aggravates hypoglycemia-related cardiac fibrosis in diabetes | Shuting Chang (+12) | 2026 | Journal of Translational Medicine |
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