Screening Strategies for Chronic Kidney Disease in US Populations

美国人群慢性肾病的筛查策略

• 批准号: 10305997
• 负责人: Sri Lekha Tummalapalli
• 金额: $ 7.49万
• 依托单位: WEILL MEDICAL COLL OF CORNELL UNIV
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-12-01 至 2021-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10305997
• 关键词: Address; Adult; Advisory Committees; Age; Albumins; American; Angiotensin Receptor; Angiotensin-Converting Enzyme Inhibitors; Antihypertensive Agents; Atherosclerosis; Base Ratios; Biometry; Blood; Blood Pressure; Cardiovascular Diseases; Cardiovascular system; Categories; Cessation of life; Characteristics; Chronic Kidney Failure; Clinical; Clinical Research; Clinical Trials; Computer Simulation; Cost Effectiveness Analysis; Creatinine; Data Pooling; Decision Analysis; Demographic Factors; Development; Diabetes Mellitus; Disease; Disease Progression; Early Diagnosis; End stage renal failure; Environment; Epidemiology; Ethnic Origin; Event; Family history of; Foundations; Frequencies; Funding; Future; Glomerular Filtration Rate; Goals; Guidelines; Health; Health Services Research; Hypertension; Incidence; Individual; Instruction; Intervention; K-Series Research Career Programs; Kidney; Kidney Diseases; Kidney Failure; Leadership; Longitudinal cohort; Measurement; Measures; Mentorship; Methods; Modeling; Morbidity - disease rate; Nephrology; Newly Diagnosed; Outcome; Patient Selection; Patients; Persons; Pharmaceutical Preparations; Policies; Population; Positioning Attribute; Preventive service; Probability; Professional Organizations; Proteinuria; Public Health; Quality-Adjusted Life Years; Race; Recommendation; Recording of previous events; Regimen; Research; Resources; Risk; Risk Factors; Target Populations; Techniques; Testing; Time; Training; United States; Urine; Work; base; blood pressure regulation; cardiovascular disorder epidemiology; cardiovascular disorder risk; career; demographics; design; evidence base; high risk population; improved; markov model; models and simulation; mortality; prevent; screening; screening guidelines; sex; treatment as usual; two-dimensional

PROJECT SUMMARY/ABSTRACT Screening for chronic kidney disease (CKD) can potentially decrease kidney disease-related morbidity and mortality via early diagnosis and initiation of evidence-based therapies. However, whether patients should be screened for CKD remains highly controversial, as is the optimal target population in whom screening should be implemented. Due to insufficient evidence, statements from professional organizations have either no recommendation for screening for CKD or are discordant on whether they recommend screening in high-risk populations. We will address this critical public health question and evaluate the potential benefits of screening for CKD across different populations by developing an enhanced version of the Cardiovascular Disease (CVD) Policy Model that includes kidney parameters and outcomes, called the CKD Policy Model. The CVD Policy Model is a validated state-transition Markov model of CVD events and mortality in US adults. Markov modeling is an established technique that allows us to synthesize evidence and simulate and quantify the expected benefits of interventions on downstream outcomes. We have access to pooled longitudinal cohorts, comprising over 65,000 individuals followed for up to 30 years with sequential measurements of estimated glomerular filtration rate (eGFR) and urine albumin-to-creatinine ratio (UACR). We will adapt and enhance the CVD Policy Model for nephrology applications by incorporating categories of eGFR and UACR to model CKD stage transitions in two dimensions. We will determine incident CKD probabilities based on a combination of demographics (age, sex, race/ethnicity) and risk factors, including history of diabetes, history of hypertension, and family history of kidney disease. Having developed and tailored the new CKD Policy Model, we will use a Markov decision analysis to project the impact of CKD screening. The treatment intervention triggered by CKD identification will include three treatments: 1) angiotensin converting enzyme inhibitors and angiotensin receptor blockers (ACEi/ARBs); 2) statins; and 3) blood pressure regimen intensification. The outcomes of the model will be the changing incidence of CVD events, end-stage renal disease, and mortality. The overall goal of this proposal is to establish an evidence-based framework for developing potential CKD screening strategies. Our specific aims are: 1) to determine individualized probabilities of incident CKD and CKD progression based on patient demographics and risk factors and develop the CKD Policy Model; and 2) to estimate the expected impact of different selective CKD screening strategies on CVD events, incident ESRD, and cause-specific and all-cause mortality using Markov modeling. The results of this research will identify the optimal characteristics to guide patient selection for first CKD screening and the optimal repeat screening frequency, and ultimately inform the design of a future pragmatic CKD screening trial.

项目摘要/摘要 筛查慢性肾脏疾病(CKD)可能会降低肾脏疾病相关的发病率和 通过早期诊断和启动循证治疗导致的死亡率。然而，患者是否应该 CKD的筛查仍然存在很大争议，筛查的最佳目标人群也是如此 将会得到实施。由于证据不足，专业组织的陈述要么没有 对慢性肾脏病筛查的建议，或对是否建议对高危人群进行筛查的意见不一致 人口。 我们将解决这一关键的公共卫生问题，并评估CKD筛查的潜在好处。 通过制定心血管疾病(CVD)政策的增强版来跨越不同的人群 包括肾脏参数和结果的模型，称为CKD策略模型。CVD政策模型是 美国成人心血管疾病事件和死亡率的有效状态转移马尔可夫模型。马尔可夫模型是一种 建立了一种技术，使我们能够综合证据，模拟和量化 对下游结果的干预。我们可以接触到集合的纵向队列，包括超过 对65,000人进行了长达30年的跟踪调查，并对估计的肾小球滤过率进行了连续测量 测定尿白蛋白/肌酐比值(UACR)和尿白蛋白/肌酐比值(EGFR)。我们将调整和完善CVD政策模式 通过合并EGFR和UACR的类别来模拟CKD阶段转变，以用于肾脏病应用 两个维度。我们将根据人口统计数据(年龄、 性别、种族/民族)和危险因素，包括糖尿病病史、高血压病史和 肾脏疾病。 在开发和定制了新的CKD策略模型之后，我们将使用马尔可夫决策分析来预测 慢性肾脏病筛查的影响。CKD识别引发的治疗干预将包括三个方面 治疗：1)血管紧张素转换酶抑制剂和血管紧张素受体阻滞剂(ACEI/ARBS)；2) 他汀类药物；3)强化降压方案。模型的结果将是不断变化的 心血管事件、终末期肾病和死亡率的发生率。 这项提议的总体目标是建立一个以证据为基础的框架，以发展潜在的CKD 筛选策略。我们的具体目标是：1)确定CKD事件的个性化概率和 基于患者人口统计和风险因素的CKD进展，并开发CKD策略模型；以及2) 评估不同选择性CKD筛查策略对CVD事件、事件的预期影响 ESRD，以及使用马尔可夫模型的特定原因和所有原因的死亡率。这项研究的结果将 确定最佳特征，以指导首次CKD筛查的患者选择和最佳重复筛查 筛查频率，并最终通知设计未来务实的CKD筛查试验。

项目成果

Coverage, Formulary Restrictions, and Affordability of Sodium-Glucose Cotransporter 2 Inhibitors by US Insurance Plan Types.

• DOI: 10.1001/jamahealthforum.2021.4205
• 发表时间: 2021-12
• 期刊: JAMA health forum
• 作者: Tummalapalli SL;Montealegre JL;Warnock N;Green M;Ibrahim SA;Estrella MM
• 通讯作者: Estrella MM

Predicting Risk of Kidney Disease: Is Risk-Based Kidney Care on the Horizon?

预测肾脏疾病的风险：基于风险的肾脏护理即将到来吗？

• DOI: 10.1001/jama.2019.17378
• 发表时间: 2019
• 期刊: JAMA
• 作者: Tummalapalli,SriLekha;Estrella,MichelleM
• 通讯作者: Estrella,MichelleM

A Mobile Health-Based Survey to Assess COVID-19 Vaccine Intent and Uptake Among Patients on Dialysis.

• DOI: 10.1016/j.ekir.2021.12.006
• 发表时间: 2022-03
• 期刊: Kidney international reports
• 影响因子: 6
• 作者: Tummalapalli SL;Cukor D;Bohmart A;Levine DM;Parker TS;Liu F;Perlman A;Srivatana V;Turchioe MR;Ibrahim SA;Silberzweig J
• 通讯作者: Silberzweig J

Availability and Affordability of Kidney Health Laboratory Tests around the Globe.

• DOI: 10.1159/000511848
• 发表时间: 2020
• 期刊: American journal of nephrology
• 影响因子: 4.2
• 作者: Tummalapalli SL;Shlipak MG;Damster S;Jha V;Malik C;Levin A;Johnson DW;Bello AK
• 通讯作者: Bello AK

Capitated versus fee-for-service reimbursement and quality of care for chronic disease: a US cross-sectional analysis.

• DOI: 10.1186/s12913-021-07313-3
• 发表时间: 2022-01-04
• 期刊: BMC health services research
• 影响因子: 2.8
• 作者: Tummalapalli SL;Estrella MM;Jannat-Khah DP;Keyhani S;Ibrahim S
• 通讯作者: Ibrahim S