Suppr超能文献

检测异质性治疗效果以指导个性化血压治疗:一项随机临床试验的建模研究

Detecting Heterogeneous Treatment Effects to Guide Personalized Blood Pressure Treatment: A Modeling Study of Randomized Clinical Trials.

作者信息

Basu Sanjay, Sussman Jeremy B, Hayward Rod A

机构信息

From Stanford University, Stanford, California; Harvard Medical School, Boston, Massachusetts; and University of Michigan, Ann Arbor, Michigan.

出版信息

Ann Intern Med. 2017 Mar 7;166(5):354-360. doi: 10.7326/M16-1756. Epub 2017 Jan 3.

Abstract

BACKGROUND

Two recent randomized trials produced discordant results when testing the benefits and harms of treatment to reduce blood pressure (BP) in patients with cardiovascular disease (CVD).

OBJECTIVE

To perform a theoretical modeling study to identify whether large, clinically important differences in benefit and harm among patients (heterogeneous treatment effects [HTEs]) can be hidden in, and explain discordant results between, treat-to-target BP trials.

DESIGN

Microsimulation.

DATA SOURCES

Results of 2 trials comparing standard (systolic BP target <140 mm Hg) with intensive (systolic BP target <120 mm Hg) BP treatment and data from the National Health and Nutrition Examination Survey (2013 to 2014).

TARGET POPULATION

U.S. adults.

TIME HORIZON

5 years.

PERSPECTIVE

Societal.

INTERVENTION

BP treatment.

OUTCOME MEASURES

CVD events and mortality.

RESULTS OF BASE-CASE ANALYSIS: Clinically important HTEs could explain differences in outcomes between 2 trials of intensive BP treatment, particularly diminishing benefit with each additional BP agent (for example, adding a second agent reduces CVD risk [hazard ratio, 0.61], but adding a fourth agent to a third has no benefit) and increasing harm at low diastolic BP.

RESULTS OF SENSITIVITY ANALYSIS

Conventional treat-to-target trial designs had poor (<5%) statistical power to detect the HTEs, despite large samples (n > 20 000), and produced biased effect estimates. In contrast, a trial with sequential randomization to more intensive therapy achieved greater than 80% power and unbiased HTE estimates, despite small samples (n = 3500).

LIMITATIONS

The HTEs as a function of the number of BP agents only were explored. Simulated aggregate data from the trials were used as model inputs because individual-participant data were not available.

CONCLUSION

Clinically important heterogeneity in intensive BP treatment effects remains undetectable in conventional trial designs but can be detected in sequential randomization trial designs.

PRIMARY FUNDING SOURCE

National Institutes of Health and U.S. Department of Veterans Affairs.

摘要

背景

最近两项随机试验在测试降低心血管疾病(CVD)患者血压(BP)治疗的益处和危害时得出了不一致的结果。

目的

进行一项理论建模研究,以确定患者之间在益处和危害方面是否存在巨大的、具有临床重要意义的差异(异质性治疗效果[HTEs]),这些差异是否可能隐藏在血压达标治疗试验中,并解释试验结果之间的不一致。

设计

微观模拟。

数据来源

两项比较标准(收缩压目标<140 mmHg)与强化(收缩压目标<120 mmHg)血压治疗的试验结果,以及来自美国国家健康与营养检查调查(2013年至2014年)的数据。

目标人群

美国成年人。

时间范围

5年。

视角

社会层面。

干预措施

血压治疗。

结局指标

心血管疾病事件和死亡率。

基础病例分析结果

具有临床重要意义的HTEs可以解释强化血压治疗两项试验之间结局的差异,特别是每增加一种降压药物益处就会减少(例如,添加第二种药物可降低心血管疾病风险[风险比,0.61],但在第三种药物基础上添加第四种药物则无益处),并且在舒张压较低时危害增加。

敏感性分析结果

尽管样本量很大(n > 20000),但传统的达标治疗试验设计检测HTEs的统计效能较低(<5%),并产生有偏差的效应估计值。相比之下,一项采用序贯随机分组至更强化治疗的试验,尽管样本量较小(n = 3500),但检测效能大于80%,且HTE估计值无偏差。

局限性

仅探讨了作为降压药物数量函数的HTEs。由于无法获得个体参与者数据,试验的模拟汇总数据被用作模型输入。

结论

强化血压治疗效果中具有临床重要意义的异质性在传统试验设计中仍无法检测到,但在序贯随机试验设计中可以检测到。

主要资金来源

美国国立卫生研究院和美国退伍军人事务部。

相似文献

引用本文的文献

本文引用的文献

1
A Randomized Trial of Intensive versus Standard Blood-Pressure Control.强化与标准血压控制的随机试验
N Engl J Med. 2015 Nov 26;373(22):2103-16. doi: 10.1056/NEJMoa1511939. Epub 2015 Nov 9.
5
Dynamic Treatment Regimes.动态治疗方案
Annu Rev Stat Appl. 2014;1:447-464. doi: 10.1146/annurev-statistics-022513-115553.
7
Blood pressure j-curve: current concepts.血压 J 型曲线:当前概念。
Curr Hypertens Rep. 2012 Dec;14(6):556-66. doi: 10.1007/s11906-012-0314-3.
8
A "SMART" design for building individualized treatment sequences.一种构建个体化治疗序列的“SMART”设计。
Annu Rev Clin Psychol. 2012;8:21-48. doi: 10.1146/annurev-clinpsy-032511-143152. Epub 2011 Dec 12.
9
Measuring blood pressure for decision making and quality reporting.测量血压以用于决策制定和质量报告。
Ann Intern Med. 2011 Oct 18;155(8):565; author reply 565-6. doi: 10.7326/0003-4819-155-8-201110180-00026.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验