Personalized dynamic risk-stratification model for childhood cancer survivors

儿童癌症幸存者的个性化动态风险分层模型

• 批准号: 10166232
• 负责人: MELISSA M HUDSON
• 金额: $ 13.79万
• 依托单位: ST. JUDE CHILDREN'S RESEARCH HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-08-10 至 2021-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10166232
• 关键词: Address; Administrative Supplement; Affect; Algorithmic Analysis; Algorithms; Cancer Survivor; Cancer Survivorship; Cardiac; Cardiovascular system; Caring; Cause of Death; Cessation of life; Characteristics; Classification; Clinical; Code; Cohort Studies; Computer software; Congestive Heart Failure; Data; Development; Disease; Disease Outcome; Dose; Evaluation; Event; Future; General Population; Genetic Markers; Genomics; Goals; Health behavior; Heart Diseases; Heterogeneity; Intervention; Investigation; Length; Life Style; Literature; Malignant Childhood Neoplasm; Measurement; Measures; Methodology; Methods; Modeling; Nature; Neighborhoods; Obesity; Outcome; Patients; Pattern; Performance; Positioning Attribute; Preventive Intervention; Principal Component Analysis; Research; Resources; Risk; Risk Factors; Risk stratification; Saint Jude Children' s Research Hospital; Scheme; Socioeconomic Factors; Statistical Models; Stratification; Structure; Survivors; System; Time; Treatment Protocols; Update; Validation; Work; base; cancer risk; cardiovascular risk factor; childhood cancer survivor; cohort; comorbidity; design; follow-up; genetic profiling; high dimensionality; improved; insight; interest; novel; open source; patient oriented; personalized risk prediction; predictive modeling; premature; response; risk prediction model; simulation; socioeconomics; survivorship; tool; trend

PROJECT SUMMARY/ABSTRACT This application is being submitted in response to the Notice of Special Interest (NOSI) identified as NOT-CA-20-038. Cardiovascular complications have emerged as the leading cause of death among long-term childhood cancer survivors. It has been well-studied that these survivors have 15- and 7-fold of increased risk of developing congestive heart failure and premature death due to cardiac events compared to the general population. Since a long latency period often occurs before the clinically evident disease, the ability to predict is critical to expand the impact of survivor-based research to inform the future design and treatment regimes. To provide proper follow-up care for survivors, it is imperative to conduct patient-centered risk predictions that incorporate patient heterogeneity in a personalized and dynamic manner. While there is a growing body of literature on risk-stratification methods, most models only utilize baseline factors associated with the disease outcome. Cardiovascular burden is well-documented among childhood cancer survivor with cardiac risk factors increasing over time. In addition, a range of neighborhood and socioeconomic factors can affect risk for specific outcomes such as obesity. Leveraging the resources of the St. Jude Lifetime Cohort study (SJLIFE), we aim to develop a novel statistical model for personalized dynamic cancer risk prediction to improve the current cancer risk classification paradigm. Given that longitudinal information is routinely measured and documented for SJLIFE survivors, it is optimal to make full use of available longitudinal data to improve risk classification and guide timely risk-based prevention interventions to reduce the burden of cardiac diseases. The proposed method is appealing for its conceptual simplicity and efficiency for conducting dynamic prediction incorporating comprehensive longitudinal information, where risk prediction/ stratification can be updated as new observations are gathered to reflect the patient's latest health and behavior status. The proposed solutions will be accessible through open-source R software that we will make publicly available, and will be applied to data from childhood cancer survivors participating in SJLIFE.

项目总结/文摘