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 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.

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 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.

Impact of implementing a category 1 external quality assurance scheme for monitoring harmonization of clinical laboratories in Spain.

Background: The objective of the present study was to examine the evolution of the analytical performance specifications (APS) used in External Quality Assurance (EQA) schemes, as well as the efficacy of a category 1 EQA scheme in monitoring the harmonization of clinical laboratory results in Spain. Methods: A review of the literature on the types of quality specifications used in schemes in other countries and their evolution was performed. In addition, a comparative analysis of the potential impact that different APS from eight countries had on clinical decision-making was made based on three measurands: sodium, thyroid-stimulating hormone (TSH), and activated partial thromboplastin time (aPTT). Results: Harmonization of analytical methods was demonstrated by assessing whether average results deviated from the certified reference value of control materials within the APS derived from biological variation (BV). The APS used in EQA have evolved from state-of-the-art models to BV. Poor clinical decision-making would occur if the results accepted by some APS were applied. Conclusions: In Spain, only 2 of the 18 measurands studied are considered to be well harmonized. Closer collaboration between laboratories and analytical system providers would be required to resolve discrepancies.

Quality indicators for extra-analytical processes in clinical laboratory: ten years’ experience / Indicadores de calidad para los procesos extra-analíticos en el laboratorio clínico: 10 años de experiencia

Introduction. The selection and definition of quality indicators is essential for proper control of processes. This is not always easy, particularly with extra-analytical indicators, due to the complexity and degree of comparison of processes between laboratories, and the fact that data collection is not always automated. For this reason, the indicators and specifications need to be dynamic and re-designed in accordance with changes in the system. The aim of this paper is to describe the methodology used in the selection and definition of quality indicators, and their specifications for extra-analytical processes in public laboratories in Catalonia. Material and methods. During the study period (2004-2013), the members of the working group reported the mean annual value for each indicator, and the overall yearly mean of all participants was calculated. These results were compared and analyzed during periodic meetings, with regards to the pre-established specifications of the different laboratories. Results. Quality indicators and their specifications are presented. The evaluation of the validity of each quality indicator was made taking into account aspects including usefulness of the indicator in process monitoring, a clear definition, and a precise and reliable quantification. This methodology has made it possible to contrast the validity of the indicators or to reconsider the specification. Conclusions. The last 10 years’ experience of the Catalonian Health Institute Working Group on Quality Indicators in designing indicators and establishing quality specifications has proved very useful for improving the monitoring of processes in clinical laboratories included in the group (AU)

Introducción. La selección y definición de los indicadores de la calidad es imprescindible para controlar adecuadamente un proceso. Ello no siempre es fácil, sobre todo en el caso de los indicadores extraanalíticos, dada la complejidad y grado de comparabilidad de los procesos entre laboratorios y la necesaria recogida de datos que en muchas ocasiones no está automatizada. Asimismo, los indicadores y especificaciones deben ser dinámicos y rediseñarse en función de los cambios del sistema. El objetivo de este trabajo es describir la metodología utilizada en la selección y definición de indicadores de calidad y especificaciones para los procesos extraanalíticos en los laboratorios públicos de Cataluña. Material y métodos. Durante el período de estudio (2004-2013), los miembros del grupo han informado del valor medio anual para cada indicador, y se ha calculado la media anual de todos los participantes para cada uno de ellos. Estos resultados se han comparado y analizado a través de reuniones periódicas, con respecto a las especificaciones preestablecidas de los diferentes laboratorios. Resultados. Se presentan los indicadores de calidad y sus especificaciones. La evaluación de la validez de cada indicador de calidad se llevó a cabo teniendo en cuenta los aspectos incluyendo la utilidad del indicador en la supervisión de procesos, una definición clara y una cuantificación precisa y fiable. Esta metodología ha permitido contrastar la validez de los indicadores o reconsiderar la especificación. Conclusiones. Los últimos 10 años de experiencia del Grupo de Trabajo del Instituto Catalán de la Salud de Indicadores de Calidad en el diseño de indicadores y en establecer especificaciones de calidad ha demostrado ser muy útil para mejorar el seguimiento de los procesos en los laboratorios clínicos integrados en el grupo (AU)