Reflex testing I: Algorithm for lipid and lipoprotein measurement in coronary heart disease risk assessment

Abstract

We reviewed the current literature in order to construct a reflex testing algorithm that maximizes clinical utility and cost-effectiveness of lipid and lipoprotein testing. The algorithm was based on the 2nd Report of the National Cholesterol Education Program Adult Treatment Panel guidelines for use of total cholesterol (TC), triglycerides (TG), HDL-C, and LDL-C, and published reports describing the clinical use of apolipoprotein B and lipoprotein (a). The success of this algorithm was tested in a low-risk general and a high-risk hyperlipidemic patient population. Lipid data and non-lipid risk factors were obtained from a national database and from patients seen at two lipid clinics. A total of 16 968 individuals from the National Health and Nutrition Examination Survey III database comprised the low-risk group, and 239 patients examined in the Hartford Hospital and Washington University Lipid Clinics comprised the high-risk group. We found a solid scientific base to support the NCEP guidelines and reasonable support for limited testing of apoB and Lp(a). According to the algorithm, the direct LDL-C assay was deemed unnecessary in 98% and 91% of low- and high-risk subjects, respectively, if one assumes that the Friedewald equation is adequate with TG≤4.00 g/l. With a more conservative cutoff of TG≤2.50 g/l, the algorithm canceled 92% and 81% of direct LDL tests, respectively. The algorithm also limited TG to 20 and 64%, apoB to 6 and 20%, and Lp(a) to 15 and 56%, of low- and high-risk groups, respectively. Use of a comprehensive, reflex algorithm for coronary heart disease risk assessment will substantially reduce the utilization of laboratory services without diminishing the clinical value of these tests. The algorithm will prevent the overuse of certain expensive tests (direct LDL) while promoting the limited use of underutilized tests [apoB and Lp(a)].