Patient Level Prediction of Clinical Outcomes and Cost-Effectiveness in SPRINT (Optimize-SPRINT)

SPRINT 中临床结果和成本效益的患者水平预测 (Optimize-SPRINT)

• 批准号: 10083758
• 负责人: Adam P Bress
• 金额: $ 76.27万
• 依托单位: COLUMBIA UNIVERSITY HEALTH SCIENCES
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-12-15 至 2023-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10083758
• 关键词: Acute Renal Failure with Renal Papillary Necrosis; Adult; Ancillary Study; Antihypertensive Agents; Benefits and Risks; Biometry; Blood Pressure; Cessation of life; Characteristics; Chronic Disease; Clinical; Clinical Treatment; Clinical Trials; Cost of Illness; Costs and Benefits; Data; Data Analyses; Decision Analysis; Electrolytes; Eligibility Determination; Epidemiology; Equilibrium; Event; Goals; Gold; Government; Guidelines; Health Benefit; Health Care Costs; Health Personnel; Health system; Healthcare; Healthcare Systems; Hypertension; Hypotension; Incidence; Intervention Trial; Laboratories; Maps; Measures; Methods; Modeling; National Health and Nutrition Examination Survey; Office Visits; Outcome; Participant; Patients; Pharmaceutical Preparations; Population; Privatization; Public Health; Quality of life; Quality-Adjusted Life Years; Randomized; Randomized Clinical Trials; Reasons for Geographic And Racial Differences in Stroke; Reporting; Resources; Risk; Risk Reduction; Sampling; Serious Adverse Event; Societies; Syncope; Testing; Time; Titrations; Treatment Cost; Visit; adverse event risk; arm; base; blood pressure intervention; cardiovascular disorder risk; clinical practice; clinical predictors; cost; cost effective; cost effectiveness; design; economic evaluation; health care service utilization; health economics; high risk; hypertension treatment; implementation strategy; improved; individual patient; innovation; mortality; point of care; population health; predict clinical outcome; predictive modeling; preservation; prevent; preventable death; randomized trial; standard care; statistics; tool; treatment arm; treatment choice; treatment effect

Project Summary About 80 million U.S. adults have hypertension, and hypertension treatment costs the nation about $80 billion annually. Effective and inexpensive antihypertensive medications are available, but many patients remain inadequately treated. The Systolic Blood Pressure Intervention Trial (SPRINT) showed that in high CVD risk patients intensive treatment to a lower systolic blood pressure (SBP, <120 mm Hg) reduced CVD risk and all- cause mortality compared to standard treatment (SBP <140 mm Hg). We estimated that 16.8 million adults in the US meet the SPRINT eligibility criteria. Given this large number of eligible patients and the additional resources (e.g., health care provider time, laboratory visits) required to deliver intensive treatment, we need a method for selecting “high-value” patients most likely to benefit safely from intensive SBP treatment. Optimize-SPRINT is a SPRINT ancillary study. Optimize-SPRINT will apply predictive modeling methods to SPRINT to build a clinical decision tool that will be able to select optimal patients (e.g., high absolute benefit and cost-effectiveness) for intensive SBP treatment both at the point of care (for health care providers and patients) and in the population (for private health system and government payers). Our innovative predication modeling methods will identify the highest benefit patients underlying the average summary treatment effect reported from SPRINT, while preserving the advantages of SPRINT's randomized design. We aim to: • Develop and validate a predictor of clinical benefit with intensive SBP treatment (SPRINT Clinical Benefit Tool) using baseline characteristics. • Determine cost-effectiveness of intensive versus standard SBP treatment in SPRINT overall and by level of predicted SPRINT clinical benefit, and predict cost-effectiveness of intensive SBP treatment based on baseline characteristics. • Determine the population health impact of implementing intensive SBP treatment based on predicted SPRINT Clinical Benefit and cost-effectiveness. Relevance: The results of this study may change the way health care providers, payers, and clinical guideline makers treat hypertension in the US and abroad. This study will inform treatment choice decisions by health care providers and patients, and improve implementation strategies for private and government payers.

项目摘要 大约有8000万美国成年人患有高血压，高血压治疗花费了国家大约800亿美元 每年。有效和廉价的抗高血压药物是可用的，但许多患者仍然 治疗不当。收缩压干预试验（SPRINT）显示，在高CVD风险中， 患者强化治疗以降低收缩压（SBP，<120 mm Hg）可降低CVD风险， 与标准治疗（SBP <140 mm Hg）相比，导致死亡。我们估计有1680万成年人 美国符合SPRINT的资格标准。鉴于大量合格患者和额外的 资源（例如，卫生保健提供者的时间，实验室访问），需要提供强化治疗，我们需要一个 选择最有可能从强化SBP治疗中安全获益的“高价值”患者的方法。 Optimize-SPRINT是一项SPRINT辅助研究。优化-SPRINT将应用预测建模方法， SPRINT建立一个临床决策工具，能够选择最佳患者（例如，高绝对效益 和成本效益），无论是在护理点（卫生保健提供者和 患者）和人口（私人卫生系统和政府付款人）。我们的创新预测 建模方法将确定平均总体治疗效果基础上的最高获益患者 SPRINT报告，同时保留了SPRINT随机设计的优势。我们的目标是： ·开发并验证强化SBP治疗的临床获益预测因子（SPRINT Clinical 福利工具）使用基线特征。 ·确定SPRINT整体中强化与标准SBP治疗的成本效益， 预测SPRINT临床获益水平，并预测强化SBP治疗的成本效益 基于基线特征。 ·根据预测的收缩压，确定实施强化治疗对人群健康的影响。 SPRINT临床获益和成本效益。 相关性：这项研究的结果可能会改变医疗保健提供者，付款人和临床指南的方式 制造商在美国和国外治疗高血压。这项研究将根据健康状况为治疗选择决策提供信息 保健提供者和病人，并改善私人和政府付款人的执行战略。

项目成果

An efficient approach for optimizing the cost-effective individualized treatment rule using conditional random forest.

使用条件随机森林优化具有成本效益的个体化治疗规则的有效方法。

• DOI: 10.1177/09622802221115876
• 发表时间: 2022
• 期刊: Statistical methods in medical research
• 影响因子: 2.3
• 作者: Xu,Yizhe;Greene,TomH;Bress,AdamP;Bellows,BrandonK;Zhang,Yue;Zhang,Zugui;Kolm,Paul;Weintraub,WilliamS;Moran,AndrewS;Shen,Jincheng
• 通讯作者: Shen,Jincheng

Patient Selection for Intensive Blood Pressure Management Based on Benefit and Adverse Events.

基于益处和不良事件的患者选择强化血压管理。

• DOI: 10.1016/j.jacc.2021.02.058
• 发表时间: 2021-04-27
• 期刊: Journal of the American College of Cardiology
• 影响因子: 24
• 作者: Bress AP;Greene T;Derington CG;Shen J;Xu Y;Zhang Y;Ying J;Bellows BK;Cushman WC;Whelton PK;Pajewski NM;Reboussin D;Beddu S;Hess R;Herrick JS;Zhang Z;Kolm P;Yeh RW;Basu S;Weintraub WS;Moran AE;SPRINT Research Group
• 通讯作者: SPRINT Research Group