Background and Methodology
Biological variation data (BVD) are reference data that have many applications in laboratory medicine. The data describe the variability of clinically important measurands around homeostatic set points within subjects (CVI) and between subjects (CVG). The availability of well characterised data enables the interpretation of laboratory results in clinical settings and can also be used to define analytical performance specifications (APS).
The literature describing studies of biological variation (BV) stretches back over 45 years, and systematic reviews of BV data have identified widely varying estimates for many measurands. Thus, the quality and usefulness of BV data have been questioned. In view of these concerns, the EFLM established a Biological Variation Working Group (WG-BV) in 2009 and following the 1st Strategic Conference of the EFLM defining Analytical Performance Specifications in November 2014, the EFLM Task and Finish Group for the Biological Variation Database (TFG-BVD).
The results of the work of the TFG-BVD and the WG-BV are the development of
- the Biological Variation Data Critical Appraisal Checklist (BIVAC)
- a Minimum Dataset for BV studies
- a meta-analysis approach for delivery of global BV estimates
The BIVAC is designed to assess the quality of BV publications by verifying whether all essential elements that may impact upon veracity and utility of the associated BV estimates are present. The main focus of the BIVAC is the effect of study design, the measurement procedure and statistical handling of data on within-subject BV estimates (CVI). The BIVAC consists of 14 quality items (QI), which can be awarded scores A, B, C or D, indicating decreasing compliance. Based on the individual scores for each of the QI, an overall grade is set for the publication. The grade A is achieved if the study shows full compliance with all BIVAC QI. If the lowest score for any QI is a B, then the overall grade is a B and similarly C or D if the lowest QI score is a C or D, respectively. In the BIVAC scoring system, the QIs related to the overall grade are shown as a subscript. BV estimates derived from studies that receive one or more D scores are considered unsuitable for use in clinical practice and are not included in the EFLM Biological Variation Database. Two different assessors independently score each publication, performing data review and data extraction for all measurands and subgroups (study populations, sampling intervals) independently. If assessors disagree, a third assessor reviews the publication, followed by discussion with the initial assessors or a larger panel to deliver a consensus grade.
Minimum Data Set
For all studies included in the EFLM Biological Variation Database, a set of data are recorded, if included in the publication; details on study population and samplings (number of subjects included, state of well-being, number of samples per subject, sampling time, sampling interval, study duration), analytical method and estimates of analytical variation (CVA), estimates of within-subject (CVI) and between-subject (CVG) with confidence intervals (CI), concentration values and measurement unit. 95% CIs for BV estimates are calculated according to Burdick RK, Graybill FA. Confidence intervals on variance components. Statistics: Textbooks and monographs, Vol. 127. New York (NY): Marcel Dekker; 1992) if information on mean number of subjects and samples and estimates of CVA are provided.
In the EFLM Biological Variation Database, BV studies for measurands of interest are identified by systematic literature searches. Relevant publications are thereafter appraised by the BIVAC. Only studies receiving an overall BIVAC grade A, B or C are considered fit to be considered for the meta-analysis. Meta-analysis is thereafter performed for studies with similar study characteristics, which include the relevant data for calculations of CI and where a minimum of 3 samples have been collected. For most measurands, and as a first step, meta-analysis is performed based on estimates from studies performed in healthy adults where sampling is bi-weekly, weekly or monthly. For the meta-analysis, the associated BIVAC grade and the width of the CI are used as weight, with the global estimate being delivered by a weighted median approach. For the meta-analysis the BIVAC grades are arbitrarily given weights A = 4, B =3 and C = 1. Percentile bootstrap with the weighted median performed on each of the resampled data sets were used for calculating the CI, which for < 10 estimates will be equal to the range. This approach enables delivery of global BV estimates with CI based on BIVAC compliant studies.
European Federation of Clinical Chemistry and Laboratory Medicine
Ms Silvia Cattaneo
Via Carlo Farini 81
20159 Milano - Italy