Understanding the Multilevel Drivers of Liver Cancer Disparities

了解肝癌差异的多层次驱动因素

基本信息

批准号：
10524105
负责人：
Salma Shariff-Marco
金额：
$ 13.29万
依托单位：
UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
依托单位国家：
美国
项目类别：
财政年份：
2019
资助国家：
美国
起止时间：
2019-08-16 至 2024-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10524105
关键词：
Address Adherence Alcohols Asian Americans Behavioral Sciences Biological Biological Factors Biology Biometry Birth Black Populations Black race California Caring Characteristics Cirrhosis Clinical Data Data Set Diabetes Mellitus Diagnosis Education Electronic Health Record Environmental Risk Factor Epidemiologic Monitoring Ethnic Origin Ethnic group Federally Qualified Health Center Female Fibrinogen Future Geographic Factor Geography HIV Infections Hawaii Health Insurance Health Maintenance Organizations Health Services Research Healthcare Healthcare Systems Hepatitis B Infection Hepatitis B Virus Hepatitis C Hepatitis C virus Heterogeneity Hispanic Hispanic Populations Incidence Individual Infection Institution Insurance Coverage Interdisciplinary Study Intervention Investigation Knowledge Language Linear Regressions Link Liver neoplasms Malignant Neoplasms Malignant neoplasm of liver Metabolic Diseases Methods Modeling Native Hawaiian Neighborhoods Not Hispanic or Latino Pacific Islander Patients Pharmaceutical Preparations Prevention strategy Preventive measure Primary Prevention Primary carcinoma of the liver cells Race Research Resources Risk Risk Factors Sampling Sampling Studies Secondary Prevention Services Shapes Smoking Social Sciences System Tobacco smoking behavior Translating Translations United States built environment cancer epidemiology cancer health disparity chronic alcohol ingestion cohort community setting comorbidity data registry disparity reduction electronic data ethnic minority evidence base experience follow-up health care settings high risk innovation machine learning method male mortality neoplasm registry non-alcoholic fatty liver disease nonalcoholic steatohepatitis novel population based prospective racial and ethnic racial and ethnic disparities racial minority sex social social determinants social disparities social factors socioeconomics tertiary prevention

项目摘要

Project Summary/Abstract From 2000-2014, hepatocellular carcinoma, or HCC, incidence rates increased nearly 4% per year, while most cancers in the United States were on the decline. HCC disproportionately impacts minority racial/ethnic groups who are diagnosed at rates approximately twice that of non-Hispanic Whites. To inform primary prevention strategies that will reduce disparities in HCC risk, we need to determine the relative contribution of well- established and emerging (e.g., hepatitis B virus, hepatitis C virus, alcohol, smoking, cirrhosis, NAFLD, metabolic disorders, diabetes, HIV infection), and novel (e.g., medications, comorbidities, neighborhood attributes) risk factors to these disparities. To inform secondary and tertiary prevention strategies to reduce disparities in HCC burden, we need to understand the multilevel factors that contribute to HCC surveillance disparities. Answering these gaps in knowledge requires a robust high-quality study with a sample enriched for racial/ethnic minorities. Thus, we propose to leverage existing multi-disciplinary collaborations to develop an integrated dataset that includes electronic health records (EHR) data linked to population-based state cancer registry data and geospatial contextual data. This multilevel resource will include data on nearly 2.3 million individuals from three healthcare systems (mixed payer, integrated healthcare, federally qualified health centers) in California and Hawaii, thus providing diversity in healthcare settings and enrichment for racial/ethnic minorities: 59,400 are Black, 189,500 are Hispanic, and 441,700 are Asian American/Native Hawaiian/Pacific Islander (AANHPI). With this resource, we specifically aim to: (1) assess the relative importance of established and emerging examine the extent to which these factors independently and jointly contribute to racial/ethnic disparities in HCC risk; (2) discover novel risk factors and assess their relative importance to HCC risk; and (3) assess racial/ethnic disparities in adherence with surveillance for HCC as well as examine the extent to which these disparities are attributable to modifiable individual-, clinician-, system-, and neighborhood factors (Aim 3). For Aim 1, using prospective data, we will assess the relative importance of risk factors and their contribution to racial/ethnic disparities in HCC risk with causal inference methods. For Aim 2, we will apply innovative machine learning methods to identify novel factors and validate their associations with HCC risk using modeling strategy from Aim 1. For Aim 3, we will use multilevel generalized linear regression to investigate the patient, clinician, institutional and geographic factors that contribute to disparities in HCC surveillance. Given the importance of sex and age/birth cohort for HCC risk, these social determinants will be considered together with race/ethnicity using an intersectional approach. By applying a multilevel framework to understand how biological, clinical, and social factors at multiple levels contribute to HCC disparities in incidence and surveillance, the proposed study will identify modifiable factors that can be translated to the clinical and community settings to collaboratively identify strategies to ameliorate racial/ethnic disparities in HCC.

项目概要/摘要从 2000 年到 2014 年，肝细胞癌（HCC）的发病率每年增加近 4%，而大多数美国的癌症发病率正在下降。 HCC 对少数种族/族裔群体的影响尤为严重他们的诊断率大约是非西班牙裔白人的两倍。告知一级预防减少 HCC 风险差异的策略，我们需要确定健康状况的相对贡献已形成和新出现的疾病（例如乙型肝炎病毒、丙型肝炎病毒、酒精、吸烟、肝硬化、NAFLD、代谢紊乱、糖尿病、艾滋病毒感染）和新颖的（例如药物、合并症、邻里关系）属性）造成这些差异的风险因素。告知二级和三级预防策略，以减少由于 HCC 负担存在差异，我们需要了解有助于 HCC 监测的多层次因素差异。回答这些知识差距需要进行强有力的高质量研究，并提供丰富的样本少数种族/族裔。因此，我们建议利用现有的多学科合作来开发综合数据集，包括与基于人口的州癌症相关的电子健康记录 (EHR) 数据注册数据和地理空间上下文数据。这一多级资源将包含近 230 万个数据来自三个医疗保健系统（混合付款人、综合医疗保健、联邦合格健康）的个人中心）在加利福尼亚州和夏威夷，从而提供医疗保健环境的多样性和种族/民族的丰富少数族裔：59,400 人为黑人，189,500 人为西班牙裔，441,700 人为亚裔美国人/夏威夷原住民/太平洋人岛民 (AANHPI)。有了这个资源，我们的具体目标是：（1）评估已建立的以及新兴的研究这些因素独立和共同影响种族/民族的程度 HCC 风险的差异； (2) 发现新的危险因素并评估其对 HCC 风险的相对重要性；和（3）评估 HCC 监测中的种族/民族差异，并检查其程度这些差异可归因于可改变的个人、临床医生、系统和社区因素（目标 3）。对于目标 1，我们将使用前瞻性数据评估风险因素的相对重要性及其贡献通过因果推理方法了解 HCC 风险的种族/民族差异。对于目标 2，我们将应用创新机器学习方法可识别新因素并验证其与 HCC 风险的关联目标 1 的建模策略。对于目标 3，我们将使用多级广义线性回归来研究导致 HCC 监测差异的患者、临床医生、机构和地理因素。给定性别和年龄/出生队列对 HCC 风险的重要性，这些社会决定因素将被一起考虑使用交叉方法处理种族/族裔。通过应用多层次框架来了解如何多个层面的生物、临床和社会因素导致 HCC 发病率和死亡率的差异监测，拟议的研究将确定可修改的因素，这些因素可以转化为临床和社区环境共同确定改善 HCC 种族/民族差异的策略。