Common Reference Intervals Research Articles

The implementation of common reference intervals

Introduction Reference intervals set by individual laboratories are commonly highly variable without good reasons based on population, pre-analytical or analytical differences. This variability is a major contributor to differences in interpretation when patients attend different laboratories. A solution is to adopt common reference intervals where this is appropriate. The key factors to achieve this are agreed intervals to adopt and the processes for local acceptance. Methods Mechanisms available for laboratories to validate external reference intervals for use include the following: analysis of a number of samples from normal subjects; performance of a local reference interval study; confirmation of sufficiently small analytical bias from the method used to set the proposed interval; data-mining from the pathology database. Proposal For laboratories to validate common reference intervals for use in their laboratories a ‘toolkit’ of suitable methods should be established. This may include a number of the available techniques listed above depending on available resources and the analyte being validated. For example data mining for a hospital laboratory may be less valid than for a laboratory with outpatient work, and validation of skewed or age-related intervals with small numbers of normal subjects may be under-powered. Conclusion The final responsibility for adoption of a common reference interval remains with the individual laboratory. Simple tools are required to ensure population, pre-analytical or analytical differences do not lead to erroneous use of common intervals and to facilitate rapid adoption when suitable.

Paediatric reference intervals

Worldwide there appear to be two main approaches to addressing the gap in paediatric biochemistry reference intervals: (1) large scale, government-funded reference interval studies based on recruiting healthy children, and (2) ‘harmonisation' to achieve common reference intervals (CRI). The first are national paediatric-focused reference interval studies, including CALIPER study (Canadian Laboratory Initiative on Pediatric Reference Intervals,), KiGGS (The German Health Interview and Examination Survey for Children and Adolescents), NORICHILD (Scandinavian Initiative for the Establishment of Pediatric Reference Intervals) and CHILDx (Children's Health Improvement through Laboratory Diagnostics) by ARUP Laboratories and the University of Utah, NIH. The second approach is a national or regional group undertaking the task of defining common reference intervals using a multicentre study design. The RIs are determined via collaboration of laboratories from different regions that use analytical methods traceable to a reference method. UK Harmony, ARQAG (Auckland Regional Quality Assurance Group) and SIQAG (South Island Quality Assurance Group) have taken this approach for adult and paediatric biochemistry RIs. This is also the approach recommended by the Australian Association of Clinical Biochemists (AACB) Paediatric Special Interest Group. Unfortunately there is no perfect solution; both approaches have obstacles that hinder the implementation by laboratories. Recent data from CALIPER suggest transference of RIs to all major instrument platforms may be possible based on their population studies

Calcium, Magnesium, Albumin, and Total Protein Measurement in Serum as Assessed with 20 Fresh-Frozen Single-Donation Sera

To the Editor: The scope of external quality assessment (EQA)1 in laboratory medicine has evolved considerably (1). With the increasing worldwide interest in the use of common reference intervals and/or medical-decision limits, modern EQA schemes need to be better at assessing the standardization status of commercial in vitro diagnostic tests. This need has led to new challenges in the design of EQA surveys. We report the outcomes of a Norwegian pilot study that investigated the use of commutable, fresh-frozen single donations to assess the current standardization status as part of an initiative toward producing common reference intervals (2). The study covered measurements of calcium, magnesium, albumin, and total protein in serum from 20 single-donation blood samples obtained from Solomon Park Research Laboratories. Serum was generated according to CLSI protocol C37-A, with 2 U human thrombin (Sigma-Aldrich) added per milliliter of plasma to facilitate clotting (3); filtration was not used. Aliquots of these samples were sent to laboratories that used the same test systems (instrument, reagent, and calibrator from the same source). Five peer groups (n ≥ 6 laboratories each; N = 47) were considered: Abbott Diagnostics ARCHITECT, Ortho Clinical Diagnostics VITROS, …

Common reference intervals of blood counts

Common reference intervals of blood counts

Intervalli di riferimento comuni? Utili? Possibili? Necessari?

The theory of the reference interval has been well-defined by authoritative professional institutions but its practical application in most clinical laboratories is far from optimal. Laboratories often use different reference intervals without any valid reason, such as variations in analytical methodology or the population served. The adoption of common reference intervals has become a matter of importance because: (1) several common decision points which are not determined or validated in individual laboratories, e.g. glucose and lipid measurements, have already been widely accepted; (2) common reference intervals have been developed in Scandinavia by an international clinical chemistry organisation (Nordic Reference Interval Project, NORIP) and are being developed in Oceania; (3) the approach has been discussed favourably at international meetings; and (4) assay standardisation has substantially advanced (e.g. in the European Union). In 1998 the NORIP programme was started with the participation of 102 Nordic clinical biochemistry laboratories which collected blood samples from at least 25 healthy reference individuals evenly distributed for gender and age, and determined 25 of the most commonly requested serum/plasma components for each reference individual. Analytical and methodological data and data describing the reference individuals were submitted to a central database for evaluation and calculation of reference intervals intended for common use in the Nordic countries. Today, common reference intervals are used by almost 100% of laboratories for some analytes (e.g. iron, bilirubin, urate, magnesium). In 2005/06 the UK Department of Health set up a national Action Learning Programme as a key part of its Modernising Pathology Programme to enable people working in NHS pathology services to tackle issues and problems they identify locally as a priority for action. The Department funded six action learning sets to work on priority areas in pathology: workforce, standardisation, networks, primary care and protocol-guided investigations. The first phase was a success and was followed by a second phase with 16 topics. Work on the learning set for harmonise of reference intervals was carried out in the West Midlands. The set took a pragmatic approach to harmonising the variations between laboratories. Different practices were identified and were examined to see whether reasons for the differences were technical, scientific or clinical (e.g. differences in equipment and reagents or in the population served). The variations at the top and bottom were then considered, and a proposal based on consensus was developed. From 2007, the Pathology Harmony Initiative started to look at the harmonisation within the clinical laboratory. Several areas were identified where it was felt that there was potential for harmonisation. Several topics (e.g. units of measurement, reference intervals, test name harmonisation) have been investigated. All these experiences demonstrate that harmonisation of the reference intervals for several analytes should at last also be considered in Italy.

Reference intervals and age and gender dependency for arterial blood gases and electrolytes in adults

Although results from blood gas analyzers are frequently used in clinical work surprisingly few and small studies have examined reference intervals for arterial blood gases and acid-base status. We have established reference values based on a large group of healthy people with a wide age distribution. A group of medical students (n=182) aged 20-32 years old and a group of health professionals aged 21-76 years were used in this study. Arterial samples were analyzed on the blood gas analyzer ABL from Radiometer(TM). Age and gender dependency was examined for all analytes and reference intervals were calculated non-parametrically. Females had significantly higher pH and lower PaCO(2) (partial pressure of carbon dioxide in an arterial sample), base excess (BE, standard, extra cellular fluid), plasma standard and actual HCO(3), when compared to males (p<0.01). However, the differences were minor and common reference intervals were therefore also determined, generally at the same level as previously published. The lactate values were similar among the genders but with a high upper limit of 2.5 mmol/L. The non-smoker group of females and males had similar PaO(2) values (partial pressure of oxygen in an arterial sample). However, an age dependent effect was found and PaO(2) decreased by 0.29 kPa per decade (confidence interval of slope -0.11 to -0.47 kPa). Electrolytes and anion gap results depicted smaller differences from previous published reference intervals for sodium (136-141 mmol/L) and anion gap (10-16 mmol/L, with potassium included or 6-12 mmol/L without potassium). Reference intervals for analytes on modern blood gas analyzers were established on a large group of healthy people. Gender and age dependency is generally without clinical importance, except for a lower PaCO(2) in women and a decreasing PaO(2) with higher age.

Common reference intervals for aspartate aminotransferase (AST), alanine aminotransferase (ALT) and γ-glutamyl transferase (GGT) in serum: results from an IFCC multicenter study

Aspartate aminotransferase (AST), alanine aminotransferase (ALT) and γ-glutamyl transferase (GGT) measurements are important for the assessment of liver damage. The aim of this study was to define the reference intervals (RIs) for these enzymes in adults, paying attention to standardization of the methods used and careful selection of the reference population. AST, ALT and GGT were measured with commercial analytical systems standardized to the IFCC-recommended reference measurement systems. Three centers (two in Italy and one in China) measured their own freshly collected samples; one of these centers also measured frozen samples from the Nordic Countries RI Project and from a Turkish center. RIs were generated using non-parametric techniques from the results of 765 individuals (411 females and 354 males, 18-85 years old) selected on the basis of the results of other laboratory tests and a specific questionnaire. AST results from the four regions (Milan, Beijing, Bursa and Nordic Countries) were statistically different, but these differences were too small to be clinically relevant. Likewise, differences between the upper reference limits for genders was only 1.7 U/L (0.03 μkat/L), allowing a single RI of 11-34 U/L (0.18-0.57 μkat/L) to be defined. Interregional differences were not statistically significant for ALT, but partitioning was required due to significant gender differences. RIs for ALT were 8-41 U/L (0.13-0.68 μkat/L) for females and 9-59 U/L (0.15-0.99 μkat/L) for males, respectively. The upper reference limits for GGT from the Nordic Country population were higher than those from the other three regions and results from this group were excluded from final calculations. The GGT RIs were 6-40 U/L (0.11-0.66 μkat/L) for females and 12-68 U/L (0.20- 1.13 μkat/L) for males, respectively. For AST and ALT, the implementation of common RIs appears to be possible, because no differences between regions were observed. However, a common RI for GGT that is applicable worldwide appears unlikely due to differences among populations.

Creatinine eGFR and all that, an update

The introduction of routine reporting of eGFR is now part of the health landscape in Australia and many countries worldwide. There are well known limitations to this process and it is appropriate to keep working to address these issues. Some areas of new activity include the development of a new formula, the CKD-EPI formula; consideration of common reference intervals for serum creatinine; estimation of GFR for drug monitoring purposes and racial effects. To date there has also been little co-ordinated progress for the paediatric population with regard to creatinine measurement, reference intervals and GFR estimation. The joint working party of the Royal College of Pathologists of Australasia, the Australasian Association of Clinical Biochemists (AACB) and Kidney Health Australia plans to address these issues during 2010.

Applicability of common reference intervals for serum creatinine concentrations to the Croatian population

In accordance with an ongoing activity for worldwide harmonization based on traceability in laboratory methods, the goal of this study was to validate the applicability of recommended "common" reference intervals for serum creatinine concentrations using a specific enzymatic method to the Croatian population. The reference group consisted of 240 healthy subjects (120 males and 120 females), between 18 and 74 years of age (median 57 years), who were selected in accordance with the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) recommendations. Creatinine in serum was measured using the creatinine enzymatic assay (Olympus OSR61204) that was standardized to the isotopic dilution mass spectrometry (IDMS) method and National Institute of Standards and Technology (NIST) Standard Reference Material (SRM) 967. In addition, creatinine was measured using a kinetic Jaffe method (Olympus OSR6178) standardized to NIST SRM 909b level 2 standard. Method comparison between enzymatic creatinine (x) and the Jaffe kinetic method (y) gave the following P/B equation for the entire group (n=240): y=1.00x+17.00; r=0.968. Reference intervals for serum creatinine (central 95th percentiles) obtained using the enzymatic creatinine method ranged from 54 to 107 micromol/L for males and from 50 to 93 micromol/L for females. The IFCC recommended common reference intervals for global applications are 64-104 micromol/L and 49-90 micromol/L for males and females, respectively. Comparability of obtained results confirmed the applicability of recently recommended "common" reference intervals to the Croatian population for all laboratories measuring serum creatinine concentrations using enzymatic methods traceable to the IDMS method and NIST SRM 967.

Common reference intervals: The IFCC position

Common reference intervals: The IFCC position

Traceability and standardization of immunoassays: A major challenge

The clinical utility of immunoassay results is dependent on precision and trueness for the application of internationally agreed clinical protocols and common reference intervals and decision limits. The application of metrological principles to achieve traceability and standardization for these assays is being pursued to this end. Comprehensive measurement systems are available for a number of the total serum hapten assays routinely measured by immunoassays while current research is investigating the appropriateness of developing defined systems for the measurement of “free” hormone levels. The standardization or harmonization of assays for heterogeneous polypeptide hormones is also another area of research for these assays.

Sources of Variation of Commonly Measured Serum Analytes in 6 Asian Cities and Consideration of Common Reference Intervals

In a previous study to determine the feasibility of common reference intervals in Asia, we found significant differences among populations from 6 cities. In this study, we attempted to define the sources of these differences. We enrolled 580 healthy volunteers (279 men, 301 women, 20-62 years old), after a selection process that was based on the Clinical and Laboratory Standards Institute guidelines, and used a lifestyle questionnaire. All sera were obtained at a basal state and frozen at -80 degrees C until the collective assay was done. We measured 21 basic chemical analytes and 10 serum proteins. We used 3-level nested ANOVA to separate the variation (SD) into between-city (SD-city), between-sex (SD-sex), between-age (SD-age), and between-individual (SD-indiv) components. SD-indiv corresponds to one-quarter of the "pure" reference interval obtained after removing variations due to city, sex, and age. The SD-sex to SD-indiv ratio was >0.8 for creatinine, urate, retinol-binding protein, and transthyretin. We observed high SD-city to SD-indiv ratios, ranging from 0.4 to 0.7, for 11 analytes including lactate dehydrogenase (LDH), electrolytes, IgG, and complement components and SD-age to SD-indiv ratios >0.4 for LDH, alkaline phosphatase, and total cholesterol. Multiple regression analysis demonstrated several other relevant sources of variation, including body mass index, alcohol consumption, and cigarette smoking, although their contributions were generally smaller than those for sex, region, or age. We observed unacceptably large regional differences in measured values of some analytes even after adjustment for age, sex, and lifestyle variables. Genetic and environmental factors may account for the residual differences.

Cautions in the Adoption of Common Reference Intervals

Transferability of test results for a given analyte has long been a goal of the laboratory community. Achievement of transferability will require development of standardized methods that have the least possible measurement uncertainty and are traceable to reference standards. Once accomplished, transferability will allow comparison of laboratory results regardless of the individual performing laboratory and will provide long-term stability of results, enabling longitudinal results to be followed for individual patients. Transferability remains an elusive goal, however. Analytical hindrances include the lack of established reference measurement systems for many quantities, lack of traceability of field methods to the reference system, and lot-to-lot variability in reagents and calibrators. When no population-specific differences exist, the use of common reference intervals for transferable tests can be envisioned. Enthusiasm for the use of common reference intervals has grown since publication of the findings …

An ELISA for apolipoprotein M reveals a strong correlation to total cholesterol in human plasma

Apolipoprotein M (apoM) is a 188 amino acid, 25 kDa protein belonging to the lipocalin protein superfamily. Although predominantly associated with high density lipoprotein, apoM is found in all major lipoprotein classes. To facilitate clinical studies of apoM, we have developed a sandwich ELISA for the measurement of apoM in human plasma. This method has been used to investigate normal apoM variation and to establish reference values for healthy individuals through the measurement of 598 samples from the Nordic Reference Interval Project Bio-bank and Database (NOBIDA) biobank. For women 18-49 years old, the reference interval for apoM was 0.58-1.18 micromol/l, whereas for women 50+ years and for men, the reference range was 0.61-1.30 micromol/l. Correlation studies of apoM with 26 common clinical chemical analytes from the NOBIDA database revealed a marked positive correlation with plasma total cholesterol (r = 0.52) and LDL and HDL cholesterol (r = 0.43 and 0.36, respectively). There was no statistically significant correlation with HDL/total cholesterol ratio or body mass index. In conclusion, a sandwich ELISA for the measurement of apoM in human plasma shows that apoM concentration is strongly correlated to total cholesterol in healthy individuals.

Reference Intervals for Hemoglobin A1c in Pregnant Women: Data from an Italian Multicenter Study

The reference intervals for hemoglobin A1c (Hb A1c) in pregnant women without diabetes are not well defined, and few examples of reference intervals established by networks of different laboratories are available. Five Italian Diabetic Care Units were involved in the study. Data were collected from 445 pregnant women without diabetes, selected on the basis of glucose challenge test results, and from 384 nonpregnant control women. The Hb A1c measurements were performed with HPLC systems aligned to the Diabetes Control and Complications Trial. Plasma glucose measurements were also performed locally. Both Hb A1c and glucose measurements were harmonized by running appropriate external quality assessment schemes. The reference intervals were calculated in terms of nonparametric 2.5th to 97.5th percentiles with 0.90 confidence intervals. The Hb A1c measurements were reproducible (CV = 2.0%) and accurate [mean (SE) difference from the target values, -0.10 (0.06)%]. Glucose measurements were also reproducible (mean CV = 3.2%) and accurate [difference from the target values, -0.01 (0.04) mmol/L]. To calculate common reference intervals, we merged the data collected in the different centers. The Hb A1c reference intervals were 4.0%-5.5% for pregnant nondiabetic women and 4.8%-6.2% for nonpregnant controls. Healthy pregnant women have lower Hb A1c concentrations than nonpregnant women. The reference intervals for Hb A1c in pregnant women should therefore be lower than those currently in use.

Prerequisites for establishing common reference intervals

Establishment of common reference intervals for homogeneous populations within regions is based on the same basic principles as the IFCC recommendations for individual laboratories, but a few additional prerequisites are needed. Thus, the need for common standardization and traceability during production of the reference values and with the application of the common reference intervals in the laboratories becomes crucial. Furthermore, the external control system must be geared to the purpose, using matrix‐correct control materials with concentration values traceable to the same reference methods, and validation of results according to analytical quality specifications designed for the use of common reference intervals. Here, the standards may have a restrictive influence on the establishing of common reference intervals, with their demands for the use of the producers' traceability, instead of a relevant high‐quality reference preparation shared by all the participants. Two main strategies for measurements are analysis immediately after the sampling, and storage of samples until analysis in one or a few analytical runs. The former strategy needs constant standardization and stability of the performance in many laboratories and in several analytical runs, resulting in between‐run variation, whereas the latter precludes this between‐run variation, but makes demands on the stability of the components under storage. When a considerable number of laboratories decide to establish common reference intervals, it is possible to obtain large sample sizes of reference values, which reduces the confidence intervals around the reference limits. It also makes it possible to collect samples from many subgroups, such as racial groups and groups related to different environmental conditions, as well as the traditional groupings according to age and gender, pregnancy and use of oestrogens. If all these subgroups are large, e.g. n>500, the confidence limits will be small and criteria for partitioning can be applied. Choosing reference individuals is not easy, as definitions of health, as well as rule‐in and rule‐out criteria vary from one investigation to the other. Therefore, the strategy and the criteria must be thoroughly described. Arguments for establishing common reference intervals are not needed. On the contrary, lack of such common reference intervals should be explained.

Effect of analytical quality on establishing common reference intervals and their use

In the Nordic Reference Interval Project (NORIP), reference intervals were established for 25 common clinical biochemical quantities. In the project, samples from more than 3000 reference individuals collected in the 102 participating laboratories from all five Nordic countries were analysed locally. In order to maintain a high level of analytical quality and to document this quality, a common calibrator/reference preparation (CAL) and a number of control samples were analysed together with the reference samples. All these materials were serum pools of unprocessed serum from many donors in order to obtain commutable materials. The CAL was used to harmonize the many different analytical procedures and calibrations by simple recalibration by the factor T/M where T is the target value based on reference methods and M is the mean of 10 replicate measurements of CAL in each laboratory. The analytical quality specifications (analytical goals) were based on specifications created directly for the purpose of sharing common reference intervals and only the bias criteria were used because bias is the dominating problem in transfer of reference intervals. These specifications were different for the evaluation of reference values to create common reference intervals and for the laboratories to use these common reference intervals (when established). An interesting outcome was that it was only for the biologically well‐regulated quantities serum‐sodium and serum‐calcium that the selection of the best laboratories gave considerably narrower reference intervals.

Are the common reference intervals truly common? Case studies on stratifying biochemical reference data by countries using two partitioning methods

The Harris‐Boyd method, recommended for partitioning biochemical reference data into subgroups by the NCCLS, and a recently proposed new method for partitioning were compared in three case studies concerning stratification by countries (Denmark, Finland, Norway, and Sweden) of reference data collected in the Nordic Reference Interval Project (NORIP) for the enzymes alkaline phosphatase (ALP), creatine kinase (CK), and γ‐glutamyl transpeptidase (GGT). The new method is based on direct estimation of the proportions of two subgroups outside the reference limits of the combined distribution, while the Harris‐Boyd method uses easy‐to‐calculate test parameters as correlates for these proportions. The decisions on partitioning suggested by the Harris‐Boyd method deviated from those obtained by using the new method for each of the three enzymes when considering pair‐wise partitioning tests. The reasons for the poor performance, as it seems to be, of the Harris‐Boyd method were discussed. Stratification of reference data into more than two subgroups was considered as both a theoretical problem and a practical one, using the four country‐specific distributions for each enzyme as illustration. Neither the Harris‐Boyd method nor the new method seems ideal to solve the partitioning problem in the case of several subgroups. The results obtained by using prevalence‐adjusted values for the proportions seemed, however, to warrant the conclusion to be made that there are no major differences in terms of the partitioning criteria between the levels of each of the three enzymes in the four countries. Because these three enzymes include those two tests (CK, GGT), which in the preliminary analyses of the project data had shown largest variation between countries, the tentative conclusion was drawn that application of common reference intervals in the Nordic countries is feasible, not only for the three enzymes examined in the present study but for all of the tests involved in the NORIP project.

Descriptive analytical data and consequences for calculation of common reference intervals in the Nordic Reference Interval Project 2000

In the Nordic Reference Interval Project (NORIP), data from 102 Nordic clinical chemical laboratories were obtained. Each laboratory reported analytical data on up to 25 of the most commonly used clinical biochemical properties, including results from each of a minimum of 25 reference individuals. A reference material consisting of a liquid frozen pool of serum with values traceable to reference methods (used as the project “calibrator” for non‐enzymes to correct reference values) was measured together with other serum pool controls in each laboratory in the same analytical series as the project samples. The data on the controls were used to evaluate the analytical quality of the routine methods. For reference interval calculations, only such reference values on enzymes were accepted that were obtained by applying the International Federation of Clinical Chemistry (IFCC) compatible methods (37°C), while “calibrator”‐corrected reference values were used in the cases of non‐enzymes. For each property, gender‐ and age‐specific reference intervals were estimated, based on simple non‐parametric calculations and using objective criteria to perform partitioning into subgroups. It is concluded that the same reference intervals are applicable in all five Nordic countries. The following descriptive data for the considered properties are presented in the tables: number of measurement values from each country and measurement system, certified/indicative target values for controls, differences between methods and measurement systems together with coefficients of variation, effects of control correction on the measurement values, differences between subgroups as determined by age, gender, country and material, and comparison of the new reference intervals with those presented in standard textbooks. The 25 components involved in this project were (listed in alphabetical order): Alanine transaminase, albumin, alkaline phosphatase, amylase, amylase pancreatic type, aspartate transaminase, bilirubin, calcium, carbamide, cholesterol, creatine kinase, creatininium, γ‐glutamyltransferase, glucose, HDL‐cholesterol, iron, iron‐binding capacity, lactate dehydrogenase, magnesium, phosphate, potassium, protein, sodium, triglyceride and urate.

Analytical quality specifications for common reference intervals.

Interpretation of laboratory test results requires comparison to some type of reference value or reference interval. These comparisons can be cross-sectional (population-based reference interval and cut-off values) or longitudinal (reference change value). Quality specifications for cross-sectional comparison have been established by determining the influence of analytical bias and imprecision on the percentage of the healthy population falling outside the reference limits, when sharing population-based reference intervals in a Gaussian distribution of results. Quality specifications for longitudinal comparisons are equally important and are often overlooked, since less work has been done in this area. Some criteria suggest that a difference between consecutive results designates a true change in a patient health status when the difference is higher than the within-subject biological variation plus the within-laboratory analytical variation. In this chapter we discuss the clinical considerations and laboratory-related factors that must be considered when quality specifications are applied to sharing reference comparisons. Real life experience shows that different analytical methods can produce comparable results when common quality goals are established, and quality can be achieved through a willingness to work together. Within the existing organization, the current specifications for analytical quality and a dedication to quality health care makes it possible to achieve transferability between laboratories within a geographic area.