Pilar Fernandez-Calle

Biological variation database: structure and criteria used for generation and update

Abstract Background: Numerical data on the components of biological variation (BV) have many uses in laboratory medicine, including in the setting of analytical quality specifications, generation of reference change values and assessment of the utility of conventional reference values. Methods: Generation of a series of up-to-date comprehensive database of components of BV was initiated in 1997, integrating the more relevant information found in publications concerning BV. A scoring system was designed to evaluate the robustness of the data included. The database has been updated every 2 years, made available on the Internet and derived analytical quality specifications for imprecision, bias and total allowable error included in the tabulation of data. Results and conclusions: Our aim here is to document, in detail, the methodology we used to evaluate the reliability of the included data compiled from the published literature. To date, our approach has not been explicitly documented, although the principles have been presented at many symposia, courses and conferences.

A checklist for critical appraisal of studies of biological variation

Abstract Data on biological variation are used for many purposes in laboratory medicine but concern exists over the validity of the data reported in some studies. A critical appraisal checklist has been produced by a working group established by the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) to enable standardised assessment of existing and future publications of biological variation data. The checklist identifies key elements to be reported in studies to enable safe accurate and effective transport of biological variation data sets across healthcare systems. The checklist is mapped to the domains of a minimum data set required to enable this process.

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

Abstract 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 cut-off/decision limits are established for either diagnosing, screening or monitoring. Total cholesterol, glucose, HbA1c, 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 state-of-the-art of the measurement, should be used for all the measurands that cannot be included in models 1 or 2.

Rationale for using data on biological variation

Abstract The aims of this study are: 1) to use the data included in the biological variation (BV) database to address the usability of BV estimates; and 2) to use different examples from the authors’ laboratories to illustrate the use and the usefulness of BV data in laboratory medicine. The BV database is an essential tool for laboratory management. Examples of application of data derived from BV are given in this paper, such as analytical performance specifications that have been included in various quality control software designed to optimize operative rules; also they have been incorporated as acceptability limits in external quality assurance reports. BV data from pathological status are of utmost interest for monitoring patients and differences between the intra-individual coefficients of variation (CVI) estimated from healthy and patients are shown. However, for a number of analytes there are limited data available and for many there are no data, consequently new studies should be encouraged at an international level. In addition, developing international criteria to evaluate publications dealing with the estimation of BV components would be of the utmost interest. We are ready and willing to collaborate with such worthy initiatives. The first EFLM strategic conference on analytical performance specifications is an excellent opportunity for debating these ideas.

A category 1 EQA scheme for comparison of laboratory performance and method performance: An international pilot study in the framework of the Calibration 2000 project

INTRODUCTION In the modern healthcare service, patients receive care in multiple hospitals and healthcare settings. Therefore, harmonization of results from different methods and instruments, both between and within laboratories, is of the utmost importance. The present pilot study aims to test the use of a Category 1 EQA scheme across four European countries by assessing the current level of equivalence of test results. METHOD This work was led by the Dutch External Quality Assurance Scheme SKML and involved 28 laboratories from three regions in the UK, Spain and Portugal, and 120 laboratories from The Netherlands. A set of six commutable samples, targeted with reference methods, were circulated and 18 biochemistry analytes were tested. RESULTS AND CONCLUSIONS The Total Error (TE) score, defined as the probability (%) that results are within the Total Error Acceptable (TEA) limits, for the eighteen analytes was calculated. Our data show that there is a need for further harmonization of laboratory data, in particular for electrolytes (calcium, chloride, magnesium, sodium), enzymes (ALT, amylase, AST, LDH), lipids (HDL-cholesterol), and for substrates (creatinine, total protein). Lack of performance consistency between instruments was seen for most analytes. The lack of harmonization is still present despite manufacturer claims of established traceability.

Sample collections from healthy volunteers for biological variation estimates' update: a new project undertaken by the Working Group on Biological Variation established by the European Federation of Clinical Chemistry and Laboratory Medicine.

Abstract Background: Biological variation (BV) data have many fundamental applications in laboratory medicine. At the 1st Strategic Conference of the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) the reliability and limitations of current BV data were discussed. The EFLM Working Group on Biological Variation is working to increase the quality of BV data by developing a European project to establish a biobank of samples from healthy subjects to be used to produce high quality BV data. Methods: The project involved six European laboratories (Milan, Italy; Bergen, Norway; Madrid, Spain; Padua, Italy; Istanbul, Turkey; Assen, The Netherlands). Blood samples were collected from 97 volunteers (44 men, aged 20–60 years; 43 women, aged 20–50 years; 10 women, aged 55–69 years). Initial subject inclusion required that participants completed an enrolment questionnaire to verify their health status. The volunteers provided blood specimens once per week for 10 weeks. A short questionnaire was completed and some laboratory tests were performed at each sampling consisting of blood collected under controlled conditions to provide serum, K2EDTA-plasma and citrated-plasma samples. Results: Samples from six out of the 97 enroled subjects were discarded as a consequence of abnormal laboratory measurements. A biobank of 18,000 aliquots was established consisting of 120 aliquots of serum, 40 of EDTA-plasma, and 40 of citrated-plasma from each subject. The samples were stored at –80 °C. Conclusions: A biobank of well-characterised samples collected under controlled conditions has been established delivering a European resource to enable production of contemporary BV data.

Biological Variation Estimates Obtained from 91 Healthy Study Participants for 9 Enzymes in Serum

BACKGROUND We sought to develop estimates of biological variation (BV) for 9 enzymes in blood serum as part of the European Biological Variation Study. METHODS Ninety-one healthy study participants (38 male and 53 female, 21-69 years old) were phlebotomized in each of 10 consecutive weeks at 6 European laboratories. The same preanalytical sample-handling protocol was followed at each center before transport to San Raffaele Hospital, Milan, Italy, for analysis. Sera were stored at -80 °C before analysis in duplicate within a single run on an ADVIA 2400 Clinical Chemistry System (Siemens Healthcare) following a protocol designed to minimize analytical imprecision. Assay traceability was established using frozen sera with target values assigned by reference methods. The results were subjected to outlier analysis before CV-ANOVA to deliver valid BV estimates. Results for 9 enzymes were subsequently partitioned for graphical display allowing visual assessment of the effects of country of origin, sex, and age on BV estimates. RESULTS We found no effect of country upon the observed variation, but overall sex-related differences were evident for alanine amino transferase (ALT), γ-glutamyl transferase (GGT), and creatine kinase (CK). The following estimates for within-subject BV (CVI) and between-subject BV (CVG), respectively, were obtained: ALT: 9.3%, 28.2%; aspartate aminotransferase: 9.5%, 20.3%; GGT: 8.9%, 41.7%; alkaline phosphatase : 5.3%, 24.9%; lactate dehydrogenase: 5.2%, 12.6%; CK: 14.5%, 31.5%; amylase: 6.8%, 30.4%; pancreatic α-amylase: 6.3%, 24.9%; and lipase (LIP): 7.7%, 23.8%. CONCLUSIONS All CVI and some CVG estimates were lower than those reported in the online BV 2014 updated database. Analytical performance specifications derived from BV can be applied internationally.

The EuBIVAS Project: Within–and Between-Subject Biological Variation Data for Serum Creatinine Using Enzymatic and Alkaline Picrate Methods and Implications for Monitoring

BACKGROUND The European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) European Biological Variation Study (EuBIVAS) has been established to deliver rigorously determined biological variation (BV) indices. EuBIVAS determined BV for serum creatinine using the enzymatic and alkaline picrate measurement methods. METHOD In total, 91 healthy individuals (38 males, 53 females; age range, 21-69 years) were bled for 10 consecutive weeks at 6 European laboratories. An equivalent protocol was followed at each center. Sera were stored at -80 °C before analysis. Analyses for each patient were performed in duplicate within a single run on an ADVIA 2400 system (San Raffaele Hospital, Milan). The data were subjected to outlier and homogeneity analysis before performing CV-ANOVA to determine BV and analytical variation (CVA) estimates with confidence intervals (CI). RESULTS The within-subject BV estimates [CVI (95% CI)] were similar for enzymatic [4.4% (4.2-4.7)] and alkaline picrate [4.7% (4.4-4.9)] methods and lower than the estimate presently available online (CVI = 5.9%). No significant male/female BV differences were found. Significant differences were observed in mean creatinine values between men and women and between Turkish individuals and those of other nationalities. Between-subject BV (CVG) estimates, stratified accordingly, produced CVG values similar to historical BV data. CVA was 1.1% for the enzymatic and 4.4% for alkaline picrate methods, indicating that alkaline picrate methods fail to fulfill analytical performance specifications for imprecision (CVAPS). CONCLUSIONS The serum creatinine CVI obtained by EuBIVAS specifies a more stringent CVAPS than previously identified. The alkaline picrate method failed to meet this CVAPS, raising questions regarding its future use.

External quality assurance programs as a tool for verifying standardization of measurement procedures: Pilot collaboration in Europe

INTRODUCTION Current external quality assurance schemes have been classified into six categories, according to their ability to verify the degree of standardization of the participating measurement procedures. SKML (Netherlands) is a Category 1 EQA scheme (commutable EQA materials with values assigned by reference methods), whereas SEQC (Spain) is a Category 5 scheme (replicate analyses of non-commutable materials with no values assigned by reference methods). AIM The results obtained by a group of Spanish laboratories participating in a pilot study organized by SKML are examined, with the aim of pointing out the improvements over our current scheme that a Category 1 program could provide. METHOD Imprecision and bias are calculated for each analyte and laboratory, and compared with quality specifications derived from biological variation. RESULTS Of the 26 analytes studied, 9 had results comparable with those from reference methods, and 10 analytes did not have comparable results. The remaining 7 analytes measured did not have available reference method values, and in these cases, comparison with the peer group showed comparable results. The reasons for disagreement in the second group can be summarized as: use of non-standard methods (IFCC without exogenous pyridoxal phosphate for AST and ALT, Jaffé kinetic at low-normal creatinine concentrations and with eGFR); non-commutability of the reference material used to assign values to the routine calibrator (calcium, magnesium and sodium); use of reference materials without established commutability instead of reference methods for AST and GGT, and lack of a systematic effort by manufacturers to harmonize results. CONCLUSIONS Results obtained in this work demonstrate the important role of external quality assurance programs using commutable materials with values assigned by reference methods to correctly monitor the standardization of laboratory tests with consequent minimization of risk to patients.

The Biological Variation Data Critical Appraisal Checklist: A Standard for Evaluating Studies on Biological Variation

BACKGROUND Concern has been raised about the quality of available biological variation (BV) estimates and the effect of their application in clinical practice. A European Federation of Clinical Chemistry and Laboratory Medicine Task and Finish Group has addressed this issue. The aim of this report is to (a) describe the Biological Variation Data Critical Appraisal Checklist (BIVAC), which verifies whether publications have included all essential elements that may impact the veracity of associated BV estimates, (b) use the BIVAC to critically appraise existing BV publications on enzymes, lipids, kidney, and diabetes-related measurands, and (c) apply metaanalysis to deliver a global within-subject BV (CVI) estimate for alanine aminotransferase (ALT). METHODS In the BIVAC, publications were rated as A, B, C, or D, indicating descending compliance for 14 BIVAC quality items, focusing on study design, methodology, and statistical handling. A D grade indicated that associated BV estimates should not be applied in clinical practice. Systematic searches were applied to identify BV studies for 28 different measurands. RESULTS In total, 128 publications were identified, providing 935 different BV estimates. Nine percent achieved D scores. Outlier analysis and variance homogeneity testing were scored as C in >60% of 847 cases. Metaanalysis delivered a CVI estimate for ALT of 15.4%. CONCLUSIONS Application of BIVAC to BV publications identified deficiencies in required study detail and delivery, especially for statistical analysis. Those deficiencies impact the veracity of BV estimates. BV data from BIVAC-compliant studies can be combined to deliver robust global estimates for safe clinical application.