# Methods to Improve Personalized Cardiovascular Disease Prevention Across the Life Course

> **NIH NIH R01** · NORTHWESTERN UNIVERSITY · 2020 · $395,000

## Abstract

Title:
Methods to Improve Personalized Cardiovascular Disease Prevention Across the Life Course
Abstract:
Cardiovascular disease (CVD) remains the leading cause of morbidity and mortality. The overall objective of
this proposal is to develop methods for improving personalized CVD prevention across the life course. CVD
risk prediction plays a central role in clinical CVD prevention strategies, by aiding decision making for lifestyle
modification and/or to match the intensity of therapy to the absolute risk of a given patient. The current risk
prediction algorithms are generally based on the risk factors measured at a single time. Recently, we and
others have shown that cumulative burden and trajectories of CV risk factors are independently associated
with incident CVD. As risk factors like blood pressure are regularly collected in clinical practice, we propose to
develop dynamic personalized prediction models for (1) short-term (e.g., 10-year) and lifetime risk of CVD and
(2) life expectancy lived free of CVD and life expectancy lived with different subtypes of CVD across the life
course using the history of time-varying CV risk factors. In addition, we will develop robust methods to improve
the prediction of personalized blood pressure-lowering and cholesterol-lowering benefit with respect to CVD
risk reduction as well as life expectancy lived free of CVD and life expectancy lived with CVD across the life
course. The investigator team of this proposal has pooled the data from 20 community-based CVD cohorts
through the Lifetime Risk Pooling Project (LRPP), which now has in excess of 25 years of follow-up data with
repeated measured CVD risk factors, detailed information about medication use (including blood pressure-
lowering and cholesterol-lowering therapy), nearly 100% follow-up for vital status, and detailed CVD event
adjudication. Therefore, the LRPP provides a unique data source for our objective. We will validate the
estimates for short-term personalized blood pressure-lowering and cholesterol-lowering treatment effects using
the data from RCTs through our collaborations with the Blood Pressure Lowering Treatment Trialists'
Collaboration and the Cholesterol Treatment Trialists' Collaboration, respectively. The consistency of the
results would suggest adequate confounding adjustment and support the long-term personalized treatment
effect estimates from LRPP which cannot otherwise be derived from RCTs data due to relatively short follow
up.

## Key facts

- **NIH application ID:** 9903441
- **Project number:** 5R01HL136942-04
- **Recipient organization:** NORTHWESTERN UNIVERSITY
- **Principal Investigator:** Lihui Zhao
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $395,000
- **Award type:** 5
- **Project period:** 2017-04-01 → 2024-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9903441

## Citation

> US National Institutes of Health, RePORTER application 9903441, Methods to Improve Personalized Cardiovascular Disease Prevention Across the Life Course (5R01HL136942-04). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9903441. Licensed CC0.

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