BACKGROUND: Some components of the complete blood count and basic metabolic profile are commonly used risk predictors. Many of their components are not commonly used, but they might contain independent risk information. This study tested the ability of a risk score combining all components to predict all-cause mortality. METHODS:Patients with baseline complete blood count and basic metabolic profile measurements were randomly assigned (60%/40%) to independent training (N = 71,921) and test (N = 47,458) populations. A third population (N = 16,372) from the Third National Health and Nutrition Examination Survey and a fourth population of patients who underwentcoronary angiography (N = 2558) were used as additional validation groups. Risk scores were computed in the training population for 30-day, 1-year, and 5-year mortality using age- and sex-adjusted weights from multivariable modeling of all complete blood count and basic metabolic profile components. RESULTS: Area under the curve c-statistics were exceptional in the training population for death at 30 days (c = 0.90 for women, 0.87 for men), 1 year (c = 0.87, 0.83), and 5-years (c = 0.90, 0.85) and in the test population for death at 30 days (c = 0.88 for women, 0.85 for men), 1 year (c = 0.86, 0.82), and 5 years (c = 0.89, 0.83). In the test, the Third National Health and Nutrition Examination Survey, and the angiography populations, risk scores were highly associated with death (P <.001), and thresholds of risk significantly stratified all 3 populations. CONCLUSION: In large patient and general populations, risk scores combining complete blood count and basic metabolic profile components were highly predictive of death. Easily computed in a clinical laboratory at negligible incremental cost, these risk scores aggregate baseline risk information from both the popular and the underused components of ubiquitous laboratory tests.
RCT Entities:
BACKGROUND: Some components of the complete blood count and basic metabolic profile are commonly used risk predictors. Many of their components are not commonly used, but they might contain independent risk information. This study tested the ability of a risk score combining all components to predict all-cause mortality. METHODS:Patients with baseline complete blood count and basic metabolic profile measurements were randomly assigned (60%/40%) to independent training (N = 71,921) and test (N = 47,458) populations. A third population (N = 16,372) from the Third National Health and Nutrition Examination Survey and a fourth population of patients who underwent coronary angiography (N = 2558) were used as additional validation groups. Risk scores were computed in the training population for 30-day, 1-year, and 5-year mortality using age- and sex-adjusted weights from multivariable modeling of all complete blood count and basic metabolic profile components. RESULTS: Area under the curve c-statistics were exceptional in the training population for death at 30 days (c = 0.90 for women, 0.87 for men), 1 year (c = 0.87, 0.83), and 5-years (c = 0.90, 0.85) and in the test population for death at 30 days (c = 0.88 for women, 0.85 for men), 1 year (c = 0.86, 0.82), and 5 years (c = 0.89, 0.83). In the test, the Third National Health and Nutrition Examination Survey, and the angiography populations, risk scores were highly associated with death (P <.001), and thresholds of risk significantly stratified all 3 populations. CONCLUSION: In large patient and general populations, risk scores combining complete blood count and basic metabolic profile components were highly predictive of death. Easily computed in a clinical laboratory at negligible incremental cost, these risk scores aggregate baseline risk information from both the popular and the underused components of ubiquitous laboratory tests.
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