Building prediction models for coronary heart disease by synthesizing multiple longitudinal research findings
- ASU Author/Contributor (non-ASU co-authors, if there are any, appear on document)
- Martin Root Ph.D, Associate Professor (Creator)
- Institution
- Appalachian State University (ASU )
- Web Site: https://library.appstate.edu/
Abstract: No methodology is currently available to allow the combining of individual risk factor information derived from different longitudinal studies for a chronic disease in a multivariate fashion. This paper introduces such a methodology, named Synthesis Analysis, which is essentially a multivariate meta-analytic technique.Design The construction and validation of statistical models using available data sets.Methods and results Two analyses are presented. (1) With the same data, Synthesis Analysis produced a similarprediction model to the conventional regression approach when using the same risk variables. Synthesis Analysis produced better prediction models when additional risk variables were added. (2) A four-variable empirical logistic model for death from coronary heart disease was developed with data from the FraminghamHeart Study. A synthesized prediction model with five new variables added to this empirical model was developed using Synthesis Analysis and literature information. This model was then compared with the four variable empirical model using the first National Health and Nutrition Examination Survey (NHANES I) Epidemiologic Follow-up Study data set. The synthesized model had significantly improved predictive power (v2 = 43.8, P < 0.00001). Conclusions: Synthesis Analysis provides a new means of developing complex disease predictive models fromthe medical literature.
Building prediction models for coronary heart disease by synthesizing multiple longitudinal research findings
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Created on 2/29/2016
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Additional Information
- Publication
- Guizhou Hu and Martin M. Root(2005) Building prediction models for coronary heart disease by synthesizing multiple longitudinal research findings. European Journal of Cardiovascular Prevention and Rehabilitation (vol.12 pg.459–464)
- Language: English
- Date: 2005
- Keywords
- , coronary, heart, disease, longitudinal, findings,