在干预中做出预测:来自新西兰初级保健中的PREDICT-CVD队列的案例研究
Lijing Lin1, Katrina Poppe2, Angela Wood3,4,5,6,7
1Division of Informatics, Imaging and Data Science, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom.
Frontiers in epidemiology
|April 18, 2024
概括
在干预过程中预测心血管风险对于临床决策至关重要. 这项研究比较了估计戒烟,血压和胆固醇降低的风险降低方法,在因果和非因果方法之间发现了显著的差异.
科学领域:
- 心血管疾病流行病学
- 生物统计学 生物统计学
- 医疗服务研究 医疗服务研究
背景情况:
- 现有的临床预测模型往往缺乏预测特定干预措施下结果的能力.
- 在干预过程中准确的预测对于比较不同的临床策略和支持决策至关重要.
- 心血管风险预测是基于干预的建模可以改善患者护理的关键领域.
研究的目的:
- 为了比较不同的方法方法来预测干预的个人心血管风险.
- 评估估计与戒烟,降低血压和降低胆固醇相关的风险降低策略.
- 为制定更强大的临床预测模型提供信息,这些模型包含干预效应.
主要方法:
- 利用了来自新西兰PREDICT前性队列研究的数据.
- 对比了三种策略:非因果模型与假设干预,结合预测模型与观察因果推理,并结合模型与已发表的因果效应.
- 根据戒烟,降低血压和降低胆固醇的干预措施估计的绝对心血管风险.
主要成果:
- 预计戒烟将心血管风险中位数从3.9%降低到2.5-2.8%.
- 据估计,降低血压可以将中位风险从4.9%降低到3.2-4.5%.
- 降低胆固醇预计将中位风险从3.1%降低到2.2-2.8%.
结论:
- 非因果和因果方法给出了不同的估计,对干预的绝对风险降低.
- 即使在因果估计方法中也存在实质性的变化.
- 研究人员应该清楚地说明因果假设,并在估计干预风险时使用多种方法进行敏感性分析.
相关概念视频
01:03Prediction Intervals
2.3K
The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
2.3K
01:29Bias in Epidemiological Studies
254
Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:
254
01:20Study Designs in Epidemiology
215
Epidemiological study designs are fundamental tools for investigating the distribution, determinants, and control of health conditions in populations. They help researchers understand the relationships between exposures and outcomes, and they broadly fall into two categories: "observational" and "experimental" studies.
Observational studies are those where the researcher does not intervene but rather observes natural variations. They include cross-sectional, cohort, and...
Observational studies are those where the researcher does not intervene but rather observes natural variations. They include cross-sectional, cohort, and...
215
01:23Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
126
Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
126
01:30Preventive Healthcare Services
1.0K
Preventive healthcare services keep people healthy via frequent check-ups, screening, and counseling. They primarily aid in disease prevention rather than treating an acute or chronic illness. Preventive treatment also keeps individuals productive and energetic, allowing them to work well into their retirement years. Examples of preventive care services include:
1.0K
01:12Relative Risk
162
Relative risk (RR) is a statistical measure commonly used in epidemiology to compare the likelihood of a particular event occurring between two groups. This metric is important for evaluating the relationship between exposure to a specific risk factor and the probability of a particular outcome. It plays a crucial role in medical research, public health studies, and risk assessment. Relative risk quantifies how much more (or less) likely an event is to occur in an exposed group compared to an...
162