title: Apolipoprotein B improves risk assessment of future coronary heart disease in the Framingham Heart Study beyond LDL-C and non-HDL-C.
abstract: OBJECTIVE
  Analyses using conventional statistical methodologies have yielded conflicting results as to whether low-density lipoprotein cholesterol (LDL-C) or non-high-density lipoprotein cholesterol (non-HDL-C) or apolipoprotein B (apoB) is the best marker of the apoB-associated risk of coronary heart disease. The aim of this study was to determine the additional value of apoB beyond LDL-C or non-HDL-C as a predictor of coronary heart disease.
  
  
  RESULTS
  For each patient from the Framingham Offspring Cohort aged 40-75 years (n = 2966), we calculated the extent to which the observed apoB differed from the expected apoB based on their LDL-C or non-HDL-C. We added this difference to a Cox model predicting new onset coronary heart disease over a maximum of 20 years adjusting for standard risk factors plus LDL-C or non-HDL. The difference between observed and expected apoB over LDL-C or non-HDL-C was highly prognostic of future coronary heart disease events: adjusted hazard ratios 1.26 (95% confidence interval: 1.15, 1.37) and 1.20 (1.11, 1.29), respectively, for each standard deviation increase beyond expected apoB levels. When this difference between observed and expected apoB was added to standard coronary heart disease prediction models including LDL-C or non-HDL-C, prediction improved significantly (likelihood ratio test p-values <0.0001) and discrimination c-statistics increased from 0.72 to 0.73. The corresponding relative integrated discrimination improvements were 11% and 8%, respectively.
  
  
  CONCLUSIONS
  apoB improves risk assessment of future coronary heart disease events over and beyond LDL-C or non-HDL-C, which is consistent with coronary risk being more closely related to the number of atherogenic apoB particles than to the mass of cholesterol within them.
authors: Duke University, DCRI, Biostatistics and Bioinformatics, Durham, USA Framingham Heart Study, USA michael.pencina@duke.edu.
authors: Michael J
authors: MJ
authors: Pencina
authors: Boston University, Department of Mathematics and Statistics, USA.
authors: Ralph B
authors: RB
authors: D'Agostino
authors: Medical University of Gdansk, Department of Hypertension and Diabetology, Poland.
authors: Tomasz
authors: T
authors: Zdrojewski
authors: KenAnCo Biostatistics, San Antonio, USA.
authors: Ken
authors: K
authors: Williams
authors: McGill University Health Center, Medicine, Montreal, Canada.
authors: George
authors: G
authors: Thanassoulis
authors: Wake Forest University, Public Health Sciences, Winston-Salem, USA.
authors: Curt D
authors: CD
authors: Furberg
authors: Duke University Medical Center, Duke Clinical Research Institute, Durham, USA.
authors: Eric D
authors: ED
authors: Peterson
authors: Framingham Heart Study, USA.
authors: Ramachandran S
authors: RS
authors: Vasan
authors: Royal Victoria Hospital, McGill University, Montreal, Canada.
authors: Allan D
authors: AD
authors: Sniderman
mesh_terms: D000328:Adult; D000368:Aged; D053299:Apolipoprotein B-100 / Q000097:blood*; D015415:Biomarkers / Q000097:blood; D002784:Cholesterol / Q000097:blood*; D008078:Cholesterol, LDL / Q000097:blood*; D003327:Coronary Disease / Q000175:diagnosis / Q000453:epidemiology*; D003661:Decision Support Techniques; D018572:Disease-Free Survival; D050171:Dyslipidemias / Q000097:blood* / Q000175:diagnosis / Q000453:epidemiology*; D005260:Female; D006801:Humans; D053208:Kaplan-Meier Estimate; D008297:Male; D008404:Massachusetts / Q000453:epidemiology; D008875:Middle Aged; D015999:Multivariate Analysis; D011237:Predictive Value of Tests; D016016:Proportional Hazards Models; D018570:Risk Assessment; D012307:Risk Factors; D013997:Time Factors
chemical_list: C569471:APOB protein, human; D053299:Apolipoprotein B-100; D015415:Biomarkers; D008078:Cholesterol, LDL; D002784:Cholesterol
keywords: CAD; Risk factor; apoB; discordance; guidelines; non-HDL-C; risk prediction