Biological variation estimates of thyroid related measurands - meta-analysis of BIVAC compliant studies.

OBJECTIVES: Testing for thyroid disease constitutes a high proportion of the workloads of clinical laboratories worldwide. The setting of analytical performance specifications (APS) for testing methods and aiding clinical interpretation of test results requires biological variation (BV) data. A critical review of published BV studies of thyroid disease related measurands has therefore been undertaken and meta-analysis applied to deliver robust BV estimates. METHODS: A systematic literature search was conducted for BV studies of thyroid related analytes. BV data from studies compliant with the Biological Variation Data Critical Appraisal Checklist (BIVAC) were subjected to meta-analysis. Global estimates of within subject variation (CVI) enabled determination of APS (imprecision and bias), indices of individuality, and indicative estimates of reference change values. RESULTS: The systematic review identified 17 relevant BV studies. Only one study (EuBIVAS) achieved a BIVAC grade of A. Methodological and statistical issues were the reason for B and C scores. The meta-analysis derived CVI generally delivered lower APS for imprecision than the mean CVA of the studies included in this systematic review. CONCLUSIONS: Systematic review and meta-analysis of studies of BV of thyroid disease biomarkers have enabled delivery of well characterized estimates of BV for some, but not all measurands. The newly derived APS for imprecision for both free thyroxine and triiodothyronine may be considered challenging. The high degree of individuality identified for thyroid related measurands reinforces the importance of RCVs. Generation of BV data applicable to multiple scenarios may require definition using "big data" instead of the demanding experimental approach.

Critical appraisal and meta-analysis of biological variation estimates for kidney related analytes.

OBJECTIVES: Kidney markers are some of the most frequently used laboratory tests in patient care, and correct clinical decision making depends upon knowledge and correct application of biological variation (BV) data. The aim of this study was to review available BV data and to provide updated BV estimates for the following kidney markers in serum and plasma; albumin, creatinine, cystatin C, chloride, potassium, sodium and urea. CONTENT: Relevant studies were identified from a historical BV database as well as by systematic literature searches. Retrieved publications were appraised by the Biological Variation Data Critical Appraisal Checklist (BIVAC). Meta-analyses of BIVAC compliant studies with similar design were performed to deliver global estimates of within-subject (CVI) and between-subject (CVG) BV estimates. Out of the 61 identified papers, three received a BIVAC grade A, four grade B, 48 grade C, five grade D grade and one was not appraised as it did not report numerical BV estimates. Most studies were identified for creatinine (n=48). BV estimates derived from the meta-analysis were in general lower than previously reported estimates for all analytes except urea. For some measurands, BV estimates may be influenced by age or states of health, but further data are required. SUMMARY: This review provides updated global BV estimates for kidney related measurands. For all measurands except for urea, these estimates were lower than previously reported. OUTLOOK: For the measurands analyzed in this review, there are sufficient well-designed studies available to publish a trustworthy estimate of BV. However, for a number of newly appearing kidney markers no suitable data is available and additional studies are required.

Within-subject biological variation estimates using an indirect data mining strategy. Spanish multicenter pilot study (BiVaBiDa).

OBJECTIVES: The estimates of biological variation (BV) have traditionally been determined using direct methods, which present limitations. In response to this issue, two papers have been published addressing these limitations by employing indirect methods. Here, we present a new procedure, based on indirect methods that analyses data collected within a multicenter pilot study. Using this method, we obtain CVI estimates and calculate confidence intervals (CI), using the EFLM-BVD CVI estimates as gold standard for comparison. METHODS: Data were collected over a 18-month period for 7 measurands, from 3 Spanish hospitals; inclusion criteria: patients 18-75 years with more than two determinations. For each measurand, four different strategies were carried out based on the coefficient of variation ratio (rCoeV) and based on the use of the bootstrap method (OS1, RS2 and RS3). RS2 and RS3 use symmetry reference change value (RCV) to clean database. RESULTS: RS2 and RS3 had the best correlation for the CVI estimates with respect to EFLM-BVD. RS2 used the symmetric RCV value without eliminating outliers, while RS3 combined RCV and outliers. When using the rCoeV and OS1 strategies, an overestimation of the CVI value was obtained. CONCLUSIONS: Our study presents a new strategy for obtaining robust CVI estimates using an indirect method together with the value of symmetric RCV to select the target population. The CVI estimates obtained show a good correlation with those published in the EFLM-BVD database. Furthermore, our strategy can resolve some of the limitations encountered when using direct methods such as calculating confidence intervals.

Critical review and meta-analysis of biological variation estimates for tumor markers.

OBJECTIVES: Biological variation data (BV) can be used for different applications, but this depends on the availability of robust and relevant BV data. In this study, we aimed to summarize and appraise BV studies for tumor markers, to examine the influence of study population characteristics and concentrations on BV estimates and to discuss the applicability of BV data for tumor markers in clinical practice. METHODS: Studies reporting BV data for tumor markers related to gastrointestinal, prostate, breast, ovarian, haematological, lung, and dermatological cancers were identified by a systematic literature search. Relevant studies were evaluated by the Biological Variation Data Critical Appraisal Checklist (BIVAC) and meta-analyses were performed for BIVAC compliant studies to deliver global estimates of within-subject (CVI) and between-subject (CVG) BV with 95% CI. RESULTS: The systematic review identified 49 studies delivering results for 22 tumor markers; four papers received BIVAC grade A, 3 B, 27 C and 15 D. Out of these, 29 CVI and 29 CVG estimates met the criteria to be included in the meta-analysis. Robust data are lacking to conclude on the relationship between BV and different disease states and tumor marker concentrations. CONCLUSIONS: This review identifies a lack of high-quality BV studies for many tumor markers and a need for delivery of BIVAC compliant studies, including in different disease states and tumor marker concentrations. As of yet, the state-of-the-art may still be the most appropriate model to establish analytical performance specifications for the majority of tumor markers.

Biological Variation of Cardiac Troponins in Health and Disease: A Systematic Review and Meta-analysis.

BACKGROUND: Many studies have assessed the biological variation (BV) of cardiac-specific troponins (cTn), reporting widely varying within-subject BV (CVI) estimates. The aim of this study was to provide meta-analysis-derived BV estimates for troponin I (cTnI) and troponin T (cTnT) for different sampling intervals and states of health. METHODS: Relevant studies were identified by a systematic literature search. Studies were classified according to their methodological quality by the Biological Variation Data Critical Appraisal Checklist (BIVAC). Meta-analyses of BIVAC-compliant studies were performed after stratification by cTn isoform, exclusion of results below the limit of detection, states of health, and sampling interval to deliver reference change values (RCV), index of individuality (II) and analytical performance specifications (APS) for these settings. RESULTS: Sixteen and 15 studies were identified for cTnI and cTnT, respectively, out of which 6 received a BIVAC grade A. Five studies had applied contemporary cTnI assays, but none contemporary cTnT. High-sensitivity (hs-) cTnI and cTnT delivered similar estimates in all settings. Long-term CVI estimates (15.1; 11.3%) derived from healthy individuals were higher than short-term (4.3%; 5.3%) for hs-cTnI and hs-cTnT, respectively, although confidence intervals overlapped. Estimates derived from diseased subjects were similar to estimates in healthy individuals for all settings. CONCLUSIONS: This study provides robust estimates for hs-cTnI and hs-cTnT applicable for different clinical settings and states of health, allowing for the use of RCV both to aid in the diagnosis of myocardial injury and for prognosis. BV-based APS appear too strict for some currently available technologies.

Systematic review and meta-analysis of within-subject and between-subject biological variation estimates of 20 haematological parameters.

Background Interpretation of the complete blood count (CBC) parameters requires reliable biological variation (BV) data. The aims of this study were to appraise the quality of publications reporting BV data for CBC parameters by applying the BV Data Critical Appraisal Checklist (BIVAC) and to deliver global BV estimates based on BIVAC compliant studies. Methods Relevant publications were identified by a systematic literature search and evaluated for their compliance with the 14 BIVAC criteria, scored as A, B, C or D, indicating decreasing compliance. Global CVI and CVG estimates with 95% CI were delivered by a meta-analysis approach using data from BIVAC compliant papers (grades A-C). Results In total, 32 studies were identified; four received a BIVAC grade A, 2 B, 20 C and 6 D. Meta-analysis derived CVI and CVG estimates were generally lower or in line with those published in a historical BV database available online. Except for reticulocytes, CVI estimates of erythrocyte related parameters were below 3%, whereas platelet (except MPV and PDW) and leukocyte related parameters ranged from 5% to 15%. Conclusions A systematic review of CBC parameters has provided updated, global estimates of CVI and CVG that will be included in the newly published European Federation of Clinical Chemistry and Laboratory Medicine BV Database.

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.

Rationale for using data on biological variation.

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.

European Biological Variation Study (EuBIVAS): within- and between-subject biological variation estimates for serum biointact parathyroid hormone based on weekly samplings from 91 healthy participants.

BACKGROUND: The European Biological Variation Study (EuBIVAS) was created by the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) Working Group on Biological Variation to establish high-quality biological variation (BV) estimates for clinically important measurands. In this study, the aim was to deliver reliable BV estimates for the biointact parathyroid hormone (PTH 1-84). METHODS: Serum samples were obtained from a population of 91 healthy individuals (38 men, 43 pre-menopausal women, and 10 post-menopausal women; 21-69 years) from 5 European countries, with all samples stored at -80 °C prior to analysis. PTH 1-84 analysis was performed at the San Raffaele Hospital (Milan, Italy) on the Roche Cobas e801. All samples from each individual were analysed in duplicate within a single run. CV-ANOVA was applied, after analysis of variance homogeneity and outliers, to obtain BV estimates for PTH 1-84 with 95% CIs. RESULTS: The within-subject BV [CVI (95% CI)] estimates were significantly different between men and women [13.0% (12.1-14.2%) and 15.2% (14.3-16.3%), respectively], while the between-subject estimates [CVG (95% CI)] were similar (men: 26.8% (21.4-35.1%), pre-menopausal women: 27.8% (22.7-36.1%)], allowing for delivery of updated analytical performance specifications and reference change values. CONCLUSIONS: Updated BV estimates for serum PTH 1-84 based on the large-scale EuBIVAS may be beneficial for the diagnosis and management of parathyroid glands and bone turnover pathologies.

Critical appraisal and meta-analysis of biological variation studies on glycosylated albumin, glucose and HbA1c.

Objectives: Numerous biological variation (BV) studies have been performed over the years, but the quality of these studies vary. The objectives of this study were to perform a systematic review and critical appraisal of BV studies on glycosylated albumin and to deliver updated BV estimates for glucose and HbA1c, including recently published high-quality studies such as the European Biological Variation study (EuBIVAS). Methods: Systematic literature searches were performed to identify BV studies. Nine publications not included in a previous review were identified; four for glycosylated albumin, three for glucose, and three for HbA1c. Relevant studies were appraised by the Biological Variation Data Critical Appraisal Checklist (BIVAC). Global BV estimates were derived by meta-analysis of BIVAC-compliant studies in healthy subjects with similar study design. Results: One study received BIVAC grade A, 2B, and 6C. In most cases, the C-grade was associated with deficiencies in statistical analysis. BV estimates for glycosylated albumin were: CVI=1.4% (1.2-2.1) and CVG=5.7% (4.7-10.6), whereas estimates for HbA1c, CVI=1.2% (0.3-2.5), CVG=5.4% (3.3-7.3), and glucose, CVI=5.0% (4.1-12.0), CVG=8.1% (2.7-10.8) did not differ from previously published global estimates. Conclusions: The critical appraisal and rating of BV studies according to their methodological quality, followed by a meta-analysis, generate robust, and reliable BV estimates. This study delivers updated and evidence-based BV estimates for glycosylated albumin, glucose and HbA1c.