Clinical impact of direct HDLc and LDLc method bias in hypertriglyceridemia. A simulation study of the EAS-EFLM Collaborative Project Group

Langlois, Michel; Descamps, Olivier; Laarse, Arnoud van der; Weykamp, Cas; Baum, Hannsjörg; Pulkki, Kari; Eckardstein, Arnold von; Bacquer, Dirk De; Borén, Jan; Wiklund, Olov; Laitinen, Päivi; Oosterhuis, Wytze P.; Cobbaert, Christa

doi:10.1016/j.atherosclerosis.2013.12.016

Cited by 56 publications

(47 citation statements)

References 47 publications

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“…Langlois et al [41] have performed a simulation study showing the clinical impact of some analytical bias caused by hypertriglyceridemia on commercial assays for direct measurements of HDL and LDL cholesterol. For instance, considering HDL cholesterol and its use as risk multiplier in the systematic coronary risk evaluation (SCORE) prediction model estimating 10-years risk of cardiovascular mortality [42], when the two assays showing a negative bias of ~20% at serum triglyceride concentration ~6.8 mmol/L were used, SCORE of 4% in male individuals were falsely brought to a value >5% in approximately 2/3 of subjects (Table 2) [41].…”

Section: Stimulating Studies Using Milan Models To Obtain Psmentioning

confidence: 99%

“…For instance, considering HDL cholesterol and its use as risk multiplier in the systematic coronary risk evaluation (SCORE) prediction model estimating 10-years risk of cardiovascular mortality [42], when the two assays showing a negative bias of ~20% at serum triglyceride concentration ~6.8 mmol/L were used, SCORE of 4% in male individuals were falsely brought to a value >5% in approximately 2/3 of subjects (Table 2) [41]. In these cases, clinicians may wrongly modify treatment from lifestyle changes alone to drug therapy.…”

Section: Stimulating Studies Using Milan Models To Obtain Psmentioning

confidence: 99%

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Strategies to define performance specifications in laboratory medicine: 3 years on from the Milan Strategic Conference

Panteghini

Ceriotti

Jones

et al. 2017

Clinical Chemistry and Laboratory Medicine (CCLM)

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Abstract:Measurements in clinical laboratories produce results needed in the diagnosis and monitoring of patients. These results are always characterized by some uncertainty. What quality is needed and what measurement errors can be tolerated without jeopardizing patient safety should therefore be defined and specified for each analyte having clinical use. When these specifications are defined, the total examination process will be "fit for purpose" and the laboratory professionals should then set up rules to control the measuring systems to ensure they perform within specifications. The laboratory community has used different models to set performance specifications (PS). Recently, it was felt that there was a need to revisit different models and, at the same time, to emphasize the presuppositions for using the different models. Therefore, in 2014 the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) organized a Strategic Conference in Milan. It was felt that there was a need for more detailed discussions on, for instance, PS for EQAS, which measurands should use which models to set PS and how to set PS for the extra-analytical phases. There was also a need to critically evaluate the quality of data on biological variation studies and further discussing the use of the total error (TE) concept. Consequently, EFLM established five Task Finish Groups (TFGs) to address each of these topics. The TFGs are finishing their activity on 2017 and the content of this paper includes deliverables from these groups.

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Section: Stimulating Studies Using Milan Models To Obtain Psmentioning

confidence: 99%

Section: Stimulating Studies Using Milan Models To Obtain Psmentioning

confidence: 99%

Strategies to define performance specifications in laboratory medicine: 3 years on from the Milan Strategic Conference

Panteghini

Ceriotti

Jones

et al. 2017

Clinical Chemistry and Laboratory Medicine (CCLM)

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“…Standardization of enzyme methods towards IFCC Figure 2 shows improvements reached in analytical performance in the Netherlands for enzymes, creatinine and other analytes after running the type 1 EQA-program for 5 years [44,58]. Additional challenges were demonstrated when lipemic sera were used for testing lipid methodology [59] or high glucose sera in creatinine analysis [60]. …”

Section: General Chemistrymentioning

confidence: 99%

“…Notwithstanding adequate standardization of direct highdensity lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C) tests, it was demonstrated at the national level that direct HDL-C and LDL-C tests suffer from non-selectivity in hypertriglyceridemic sera, leading to significant misclassification rates [59]. As the residual cardiovascular risk after reaching the treatment goals for LDL-C, blood pressure and diabetes remains high (around 70%), alternative (apolipo)protein tests should help to unravel cardiovascular disease pathophysiology and to select better treatment targets.…”

Section: Lipid and Apolipoprotein Standardizationmentioning

confidence: 99%

The quest for equivalence of test results: the pilgrimage of the Dutch Calibration 2.000 program for metrological traceability

Jansen

Cobbaert

Weykamp

et al. 2018

Clinical Chemistry and Laboratory Medicine (CCLM)

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Calibration 2.000 was initiated 20 years ago for standardization and harmonization of medical tests. The program also intended to evaluate adequate implementation of the In Vitro Diagnostics (IVD) 98/79/EC directive, in order to ensure that medical tests are fit-for-clinical purpose. The Calibration 2.000 initiative led to ongoing verification of test standardization and harmonization in the Netherlands using commutable external quality assessment (EQA)-tools and a type 1 EQA-design, where feasible. National support was guaranteed by involving all laboratory professionals as well as laboratory technicians responsible for EQA and quality officers. A category 1 EQA-system for general chemistry analytes, harmonizers for specific analytes like hGH and IGF-1, and commutable materials for other EQA-sections have been developed and structurally introduced in the EQA-schemes. The type 1 EQA-design facilitates the dialogue between individual specialists in laboratory medicine and the IVD-industry to reduce lot-to-lot variation and to improve standardization. In such a way, Calibration 2.000 sheds light on the metrological traceability challenges that we are facing and helps the laboratory community to get the issues on the table and resolved. The need for commutable trueness verifiers and/or harmonizers for other medical tests is now seen as paramount. Much knowledge is present in the Netherlands and for general chemistry, humoral immunology and protein chemistry, a few endocrinology tests, and various therapeutic drug monitoring (TDM) tests, commutable materials are available. Also the multi sample evaluation scoring system (MUSE) and the category 1 EQA-design offer many possibilities for permanent education of laboratory professionals to further improve the between and within laboratory variation and the test equivalence.

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“…Even if more recent guidelines [4] are discouraging the use of multiple decision thresholds for making clinical decisions, the analytical quality of the measurement of plasma lipids and lipoproteins is crucial for avoiding misclassification of subjects with reference to their cardiovascular risk [5].…”

Section: Reasons For Choosing Model 1 (Outcome Model)mentioning

confidence: 99%

Criteria for assigning laboratory measurands to models for analytical performance specifications defined in the 1st EFLM Strategic Conference

Ceriotti

Fernández–Calle

Klee

et al. 2016

Clinical Chemistry and Laboratory Medicine (CCLM)

138

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This paper, prepared by the EFLM Task and Finish Group on Allocation of laboratory tests to different models for performance specifications (TFG-DM), is dealing with criteria for allocating measurands to the different models for analytical performance specifications (APS) recognized in the 1st EFLM Strategic Conference Consensus Statement. Model 1, based on the effect of APS on clinical outcome, is the model of choice for measurands that have a central role in the decision-making of a specific disease or clinical situation and where cutoff/decision limits are established for either diagnosing, screening or monitoring. Total cholesterol, glucose, HbA 1c , serum albumin and cardiac troponins represent practical examples. Model 2 is based on components of biological variation and should be applied to measurands that do not have a central role in a specific disease or clinical situation, but where the concentration of the measurand is in a steady state. This is best achieved for measurands under strict homeostatic control in order to preserve their concentrations in the body fluid of interest, but it can also be applied to other measurands that are in a steady state in biological fluids. In this case, it is expected that the "noise" produced by the measurement procedure will not significantly alter the signal provided by the concentration of the measurand. This model especially applies to electrolytes and minerals in blood plasma (sodium, potassium, chloride, bicarbonate, calcium, magnesium, inorganic phosphate) and to creatinine, cystatin C, uric acid and total protein in plasma. Model 3, based on stateof-the-art of the measurement, should be used for all the measurands that cannot be included in models 1 or 2.

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Clinical impact of direct HDLc and LDLc method bias in hypertriglyceridemia. A simulation study of the EAS-EFLM Collaborative Project Group

Cited by 56 publications

References 47 publications

Strategies to define performance specifications in laboratory medicine: 3 years on from the Milan Strategic Conference

Strategies to define performance specifications in laboratory medicine: 3 years on from the Milan Strategic Conference

The quest for equivalence of test results: the pilgrimage of the Dutch Calibration 2.000 program for metrological traceability

Criteria for assigning laboratory measurands to models for analytical performance specifications defined in the 1st EFLM Strategic Conference

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