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Relationship between baseline triglyceride concentration and triglyceride reduction with 4 g/d long‐chain omega‐3 acid ethyl esters (1035.6)
Author(s) -
Nieman Kristin,
Dicklin Mary,
Bell Margie,
Rains Tia,
Maki Kevin
Publication year - 2014
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.28.1_supplement.1035.6
Subject(s) - triglyceride , hypertriglyceridemia , eicosapentaenoic acid , medicine , linear regression , docosahexaenoic acid , chemistry , endocrinology , fatty acid , mathematics , cholesterol , biochemistry , statistics , polyunsaturated fatty acid
Long‐chain omega‐3 acid ethyl esters (OM3‐EE) reduce plasma triglycerides; this effect appears to be larger in individuals with hypertriglyceridemia vs. those with lower fasting triglycerides (TG). Limited information exists on the relationship between baseline TG and the TG response to OM3‐EE. This investigation assessed the relationship between baseline fasting TG concentration and % reduction in TG with use of 4 g/d of OM3‐EE (eicosapentaenoic or eicosapentaenoic + docosahexaenoic acid EE). Data from 16 published studies were assessed. Baseline mean/median TG concentrations ranged from 113 to 1203 mg/dL. Linear and non‐linear regression models were fit to the mean/median values with baseline and % TG change as the independent and dependent variables, respectively. Both weighted and non‐weighted models were fit and provided similar results, thus unweighted results are reported. The model fit improved slightly with log e transformation of the response data (r 2 = 0.636 vs. 0.620). The best fit regression line was % TG change = 24.986 – 8.912 (ln baseline TG), p<0.001. Using this equation, predicted TG changes are ‐19.7, ‐25.8, and ‐32.0% with mean/median baseline TG concentrations of 150, 300, and 500 mg/dL, respectively. These findings confirm the relationship between baseline TG concentration and TG response, and provide a means for predicting response for clinical trial planning.