Clinical impact of direct HDLc and LDLc method bias in hypertriglyceridemia. A simulation study of the EAS-EFLM Collaborative Project Group
Introduction
The EAS/ESC guidelines recommend that asymptomatic individuals at high cardiovascular disease (CVD) mortality risk should be identified for statin therapy [1]. For this purpose, risk assessment is performed using the SCORE (Systematic COronary Risk Evaluation) prediction model estimating 10-y risk of CVD mortality, based on gender, age, total cholesterol, systolic blood pressure and smoking status. Recently, the 2011 ESC–EAS guidelines on the management of dyslipidemias have considered the additional impact of high-density lipoprotein cholesterol (HDLc) on CVD risk by displaying 4 separate SCORE charts to 4 different levels of HDLc (mmol/l): 0.8, 1.0, 1.4 and 1.8 [1]. The effects of differing HDLc levels may also be calculated from the classical SCORE using HDL- and sex-specific multipliers according to Descamps et al. [2].
In patients with dyslipidemia, prevention strategies with either lifestyle changes or lipid-lowering agents are primarily targeted by low-density lipoprotein cholesterol (LDLc). The higher the predicted risk, the lower is the recommended LDLc goal and hence the need to initiate statin therapy. The recommended LDLc therapeutic goal is <2.50 mmol/l in high risk individuals (SCORE 5–9%) and <1.80 mmol/l or a 50% reduction in LDLc in very high risk individuals (SCORE ≥10%) [1].
There is a direct relationship between serum LDLc and incidence of CVD. Similarly, there is a strong inverse association between HDLc and CVD, although recent Mendelian randomization studies found no causal relationship between genetically decreased or increased HDLc and the risk of myocardial infarction [3], [4]. However, our concern about including HDLc and LDLc in risk estimation models relates to the potential for analytical error due to imprecision and bias of the lipid measurements. Despite the widespread belief that the calculation or measurement of LDLc or HDLc is standardized and reproducible, results can vary significantly with methods from different manufacturers. In the previous century, the earliest measurements involved ultracentrifugation and precipitation for isolation of LDL and HDL [5]. In the late 1990s, “homogeneous” or “direct” LDLc and HDLc methods have been introduced in the clinical laboratories and largely replaced the older assays [6], [7], [8]. Direct LDLc and HDLc methods are commercially available as ready-to-use reagents, enabling full automation of the measurements, however their bias (deviation from “true” value) is a major point of concern. Discrepant results have been reported among the various direct methods, particularly in hypertriglyceridemic and dyslipidemic samples [9], [10], [11], [12], [13]. This is also evident from large-scale accuracy-based quality surveys organized across different laboratories [14]. Problems with direct HDLc assays also raise concerns about the reliability of calculated LDLc and non-HDLc treatment goals [12]. Poor reliability of these methods relate to the heterogeneity of both LDL and HDL particles [11], [12].
In this study, we aimed to illustrate the potential impact of analytical errors in current LDLc and HDLc measurements on making clinical decisions. A simulation is used here to explore potential CVD risk misclassifications as defined by the SCORE model. Misclassification may occur if a true lipid concentration is within a desirable range, but the reported lipid value is in a high-risk range, or if a true lipid concentration is in a high-risk range but the reported lipid value is in a desirable range [15]. These misclassifications represent a clinically relevant issue because they reflect the practically difficult situation with treatment options: to avoid unnecessary treatment of a patient whose lipid concentration is in a desirable risk category, or failure to treat a patient whose lipid concentration is in a high-risk category, and to distinguish between ‘moderate’ and ‘high-risk’ categories when lipid values are near a cutpoint [15]. Misclassification as defined here is of greatest concern because of its potential impact on the patient and healthcare economics. Using data of the Dutch National EQA-2012 external quality assessment of clinical laboratories, representing all LDLc and HDLc reagent systems used in The Netherlands, we simulated the effects of analytical error and hypertriglyceridemia on HDL-adjusted SCORES and concordance of treatment goals.
Section snippets
Samples
The Dutch external quality assessment (EQA) organizer, the Stichting Kwaliteitsbewaking Medische Laboratoriumdiagnostiek (SKML), runs an accuracy-based EQA scheme for clinical chemistry analytes including lipids and apolipoproteins. Quality of the Dutch EQA program has been described previously [16], [17]. Briefly, serum pools are prepared in an ISO 13485:2003 certified production facility according to CLSI C37-A protocol [18] and value-assigned for total cholesterol, LDLc and HDLc with CDC
HDL-adjusted SCORES
Median HDLc concentrations measured by the various methods did not show any major differences in the NTG serum (Table 2A). However, inter-laboratory imprecision caused a variability of HDLc concentrations reported among the participating laboratories. The application of HDL-multipliers to a fictitious woman (SCORE 3%) or man (SCORE 4%) yielded high-risk categories (SCORE >5%) in a minority of all HDLc measurements (3% and 1%, respectively). According to the HDLc target value measured in the
Discussion
In this study on a Dutch EQA database, representing all LDLc and HDLc methods used in the clinical laboratories in The Netherlands and most other countries, we observed marked deviations from the analytical target value (bias) with measurements in HTG sera. These biases exceeded far beyond the U.S. National Cholesterol Education Program (NCEP) recommendations for LDLc (≤4%) and HDLc (≤5%) [21], [22]. We simulated that application of HDL-multipliers of SCORE may yield different risk
Conclusion
As pointed out in this simulation study and previously by Warnick, Nauck, and Rifai [6], “Laboratories supporting lipid clinics with a high proportion of specimens with atypical lipoproteins could observe discrepant results on certain specimens that might confound treatment decisions.” It is vitally important for clinical laboratories to consider assay reliability and specificity when choosing methods, particularly in dyslipidemic samples. Additionally, more efforts are needed to address
Acknowledgments
We thank Alberico Catapano (EAS President), John Chapman (EAS Past-president), and Sverre Sandberg (EFLM Chair of Scientific Division) for establishing the EAS-EFLM Collaborative Project, intended to produce laboratory testing recommendations and guidelines for management of dyslipidemia and prevention of CVD.
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