title: Discriminant ratio and biometrical equivalence of measured vs. calculated apolipoprotein B100 in patients with T2DM.
abstract: BACKGROUND
  Apolipoprotein B100 (ApoB100) determination is superior to low-density lipoprotein cholesterol (LDL-C) to establish cardiovascular (CV) risk, and does not require prior fasting. ApoB100 is rarely measured alongside standard lipids, which precludes comprehensive assessment of dyslipidemia.
  
  
  OBJECTIVE
  To evaluate two simple algorithms for apoB100 as regards their performance, equivalence and discrimination with reference apoB100 laboratory measurement.
  
  
  METHODS
  Two apoB100-predicting equations were compared in 87 type 2 diabetes mellitus (T2DM) patients using the Discriminant ratio (DR). Equation 1: apoB100 = 0.65*non-high-density lipoprotein cholesterol + 6.3; and Equation 2: apoB100 = -33.12 + 0.675*LDL-C + 11.95*ln[triglycerides]. The underlying between-subject standard deviation (SDU) was defined as SDU = √ (SD2B - SD2W/2); the within-subject variance (Vw) was calculated for m (2) repeat tests as (Vw) = Σ(xj -xi)2/(m-1)), the within-subject SD (SDw) being its square root; the DR being the ratio SDU/SDW.
  
  
  RESULTS
  All SDu, SDw and DR's values were nearly similar, and the observed differences in discriminatory power between all three determinations, i.e. measured and calculated apoB100 levels, did not reach statistical significance. Measured Pearson's product-moment correlation coefficients between all apoB100 determinations were very high, respectively at 0.94 (measured vs. equation 1); 0.92 (measured vs. equation 2); and 0.97 (equation 1 vs. equation 2), each measurement reaching unity after adjustment for attenuation.
  
  
  CONCLUSIONS
  Both apoB100 algorithms showed biometrical equivalence, and were as effective in estimating apoB100 from routine lipids. Their use should contribute to better characterize residual cardiometabolic risk linked to the number of atherogenic particles, when direct apoB100 determination is not available.
authors: Endocrinology & Nutrition, Cliniques universitaires St-Luc and Institut de Recherche Expérimentale et Clinique (IREC), Université catholique de Louvain, Brussels, Belgium. michel.hermans@diab.ucl.ac.be
authors: Michel P
authors: MP
authors: Hermans
authors: Sylvie A
authors: SA
authors: Ahn
authors: Michel F
authors: MF
authors: Rousseau
mesh_terms: D000368:Aged; D000465:Algorithms; D053299:Apolipoprotein B-100 / Q000097:blood*; D002318:Cardiovascular Diseases / Q000097:blood / Q000175:diagnosis; D008076:Cholesterol, HDL / Q000097:blood; D003924:Diabetes Mellitus, Type 2 / Q000097:blood* / Q000175:diagnosis*; D005260:Female; D006801:Humans; D008077:Lipoproteins, LDL / Q000097:blood; D008297:Male; D008875:Middle Aged; D012307:Risk Factors; D014280:Triglycerides / Q000097:blood
chemical_list: D053299:Apolipoprotein B-100; D008076:Cholesterol, HDL; D008077:Lipoproteins, LDL; D014280:Triglycerides