Surveillance of cardiovascular diseases using a multivariate dynamic screening system

Stat Med. 2015 Jun 30;34(14):2204-21. doi: 10.1002/sim.6477. Epub 2015 Mar 11.

Abstract

In the SHARe Framingham Heart Study of the National Heart, Lung and Blood Institute, one major task is to monitor several health variables (e.g., blood pressure and cholesterol level) so that their irregular longitudinal pattern can be detected as soon as possible and some medical treatments applied in a timely manner to avoid some deadly cardiovascular diseases (e.g., stroke). To handle this kind of applications effectively, we propose a new statistical methodology called multivariate dynamic screening system (MDySS) in this paper. The MDySS method combines the major strengths of the multivariate longitudinal data analysis and the multivariate statistical process control, and it makes decisions about the longitudinal pattern of a subject by comparing it with other subjects cross sectionally and by sequentially monitoring it as well. Numerical studies show that MDySS works well in practice.

Keywords: LASSO; dynamic screening; multivariate longitudinal data; process monitoring; process screening; standardization; unequal sampling intervals.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Blood Glucose / analysis
  • Blood Pressure / physiology
  • Cardiovascular Diseases / epidemiology*
  • Cardiovascular Diseases / etiology
  • Cardiovascular Diseases / prevention & control
  • Cholesterol / blood
  • Computer Simulation
  • Cross-Sectional Studies
  • Humans
  • Longitudinal Studies
  • Models, Statistical
  • Monitoring, Physiologic / methods*
  • Monitoring, Physiologic / statistics & numerical data
  • Multivariate Analysis
  • Population Surveillance / methods*
  • Risk Factors
  • Stroke / epidemiology
  • Stroke / etiology
  • Stroke / prevention & control

Substances

  • Blood Glucose
  • Cholesterol