title: Practical prediction model for the risk of 2-year mortality of individuals in the general population.
abstract: This study proposed to validate a prediction model and risk-stratification tool of 2-year mortality rates of individuals in the general population suitable for office practice use. A risk indicator (R) derived from data in the literature was based on only 6 variables: to calculate R for an individual, starting with 0, for each year of age above 60, add 0.14; for a male, add 0.9; for diabetes mellitus, add 0.7; for albuminuria > 30 mg/g of creatinine, add 0.7; for stage ≥ 3 chronic kidney disease (CKD), add 0.9; for cardiovascular disease (CVD), add 1.4; or for both CKD and CVD, add 1.7. We developed a univariate logistic regression model predicting 2-year individual mortality rates. The National Health and Nutrition Examination Survey (NHANES) data set (1999-2004 with deaths through 2006) was used as the target for validation. These 12,515 subjects had a mean age of 48.9 ± 18.1 years, 48% males, 9.5% diabetes, 11.7% albuminuria, 6.8% CVD, 5.4% CKD, and 2.8% both CKD and CVD. Using the risk indicator R alone to predict mortality demonstrated good performance with area under the receiver operating characteristic (ROC) curve of 0.84. Dividing subjects into low-risk (R=0-1.0), low intermediate risk (R > 1.0-3.0), high intermediate risk (R > 3.0-5.0) or high-risk (R > 5.0) categories predicted 2-year mortality rates of 0.52%, 1.44%, 5.19% and 15.24%, respectively, by the prediction model compared with actual mortality rates of 0.29%, 2.48%, 5.13% and 13.40%, respectively. We have validated a model of risk stratification using easily identified clinical characteristics to predict 2-year mortality rates of individuals in the general population. The model demonstrated performance adequate for its potential use for clinical practice and research decisions.
authors.affiliation: Division of Nephrology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA.
authors.forename: Alexander
authors.initials: A
authors.lastname: Goldfarb-Rumyantzev
authors.affiliation: Department of Internal Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA.
authors.forename: Shiva
authors.initials: S
authors.lastname: Gautam
authors.affiliation: Division of Nephrology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA.
authors.forename: Robert S
authors.initials: RS
authors.lastname: Brown
mesh_terms: D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D008962:Models, Theoretical; D009026:Mortality; D012372:ROC Curve; D012044:Regression Analysis; D012307:Risk Factors; D012680:Sensitivity and Specificity
keywords: Death; Decision Making; Medicine; Risk