Metabolic Obesity Phenotypes and Obesity-related Cancer Survival

项目摘要。肥胖相关癌症（ORC）的发病率继续迅速增加，尽管 总体癌症发病率下降;目前ORC占所有癌症的40%以上，使其成为一种 重大公共卫生问题。强有力的证据表明，肥胖和代谢功能障碍（通常 定义为存在高血糖症、高血压、血脂异常或肥胖症）增加ORC的风险。 然而，关于代谢功能障碍与ORC后生存率之间关系的研究有限。的 癌症和癌症治疗对癌症诊断后代谢健康的影响在很大程度上也是未知的。 此外，虽然代谢功能障碍通常与肥胖高度相关，但正在出现 有证据表明，多达三分之一的正常体重的人有一定程度的代谢功能障碍。代谢 肥胖表型，根据代谢综合征标准和肥胖状态定义 （通过BMI测量）是一种新兴的评估代谢功能障碍的方法，不仅仅是肥胖。的目标 这个F30项目是为了更好地了解癌症对代谢健康的影响，以及 ORC诊断后的代谢功能障碍和生存率。首先，我将评估 ORC诊断时的代谢功能障碍，通过代谢性肥胖表型和ORC特异性和 总生存期（目标1）。为了实现这一目标，我将利用欧洲前瞻性调查， 癌症和营养（EPIC）-InterAct病例队列，包括代谢生物标志物的详细数据， 几例ORC患者的癌症诊断（N~ 1，777）。在有ORC的参与者中，我将确定 考克斯比例风险回归分析代谢性肥胖表型与生存率的关系 模型，调整相关协变量。其次，我的目标是确定与 代谢健康和代谢性肥胖表型均恶化（目的2）。使用数据提取自 在Huntsman Cancer接受治疗的ORC患者队列（N= 3，021）的电子病历 研究所在犹他州大学，我将研究的变化，代谢健康和代谢性肥胖表型 随着时间的推移，使用混合效应模型和多变量逻辑回归模型，并确定预测因子 代谢紊乱的症状结果可能有助于为干预措施提供信息，并改变临床实践指南， ORC诊断后代谢功能障碍的管理，并可能改善生活质量和 癌症患者的生存经验。本建议中概述的目标将为我提供 在癌症和代谢研究方面的丰富经验，同时有助于弥补 代谢功能障碍在癌症进展中的作用。此外，结合严谨的研究， 先进的流行病学和生物统计学方法，经验学习，临床背景和专家培训 导师将确保我过渡到一个成功的医生，科学家从事积极的研究。

PROJECT SUMMARY. The incidence of obesity-related cancer (ORC) continues to increase rapidly despite a decrease in overall cancer incidence; currently ORCs constitute over 40% of all cancers making them a significant public health concern. Strong evidence suggests that both obesity and metabolic dysfunction (often defined as the presence of hyperglycemia, hypertension, dyslipidemia, or adiposity) increase the risk of ORCs. However, there is limited research on the association of metabolic dysfunction with survival after ORC. The impact of cancer and cancer treatment on metabolic health after cancer diagnosis is also largely unknown. Additionally, although metabolic dysfunction is usually highly correlated with obesity, there is emerging evidence that up to a third of normal weight individuals have some degree of metabolic dysfunction. Metabolic obesity phenotypes, defined according to both presence of metabolic syndrome criteria and obesity status (measured by BMI), is an emerging way to assess metabolic dysfunction beyond obesity alone. The goal of this F30 project is to better understand the impact of cancer on metabolic health, and the relationship of metabolic dysfunction with survival after ORC diagnosis. Firstly, I will evaluate the association between metabolic dysfunction at ORC diagnosis, measured by metabolic obesity phenotypes, and ORC-specific and overall survival (Aim 1). To accomplish this aim, I will leverage the European Prospective Investigation into Cancer and Nutrition (EPIC)-InterAct case-cohort, which comprises detailed data on metabolic biomarkers and cancer diagnoses in several ORC patients (N~1,777). Among participants with ORC, I will ascertain associations between metabolic obesity phenotypes and survival using Cox proportional hazards regression models, adjusting for relevant covariates. Secondly, I aim to identify clinicodemographic factors associated with both metabolic health and metabolic obesity phenotype worsening (Aim 2). Using data extracted from electronic medical records on a cohort of ORC patients (N=3,021) receiving treatment at the Huntsman Cancer Institute at the University of Utah, I will examine changes to metabolic health and metabolic obesity phenotype over time, using both mixed effects models and multivariable logistic regression models, and identify predictors of metabolic dysfunction. Results may help inform interventions and transform clinical practice guidelines for the management of metabolic dysfunction following ORC diagnosis, and may improve the quality of life and the survivorship experience of cancer patients. The objectives outlined in this proposal will provide me with extensive experience in cancer and metabolism research, while contributing to the large knowledge gap of the role of metabolic dysfunction on cancer progression. Furthermore, the combination of rigorous research training in advanced epidemiologic and biostatistical methods, experiential learning, clinical context, and expert mentorship will ensure my transition to a successful physician-scientist engaged in active research.