Recommendation for the review of biological reference intervals in medical laboratories

AbstractThis document is based on the original recommendation of the Expert Panel on the Theory of Reference Values of the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC), updated guidelines were recently published under the auspices of the IFCC and the Clinical and Laboratory Standards Institute (CLSI). This document summarizes proposals for recommendations on: (i) The terminology, which is often confusing, noticeably concerning the terms of reference limits and decision limits. (ii) The method for the determination of reference limits according to the original procedure and the conditions, which should be used. (iii) A simple procedure allowing the medical laboratories to fulfill the requirements of the regulation and standards. The updated document proposes to verify that published reference limits are applicable to the laboratory involved. Finally, the strengths and limits of the revised recommendations (especially the selection of the reference population, the maintenance of the analytical quality, the choice of the statistical method used…) will be briefly discussed.

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IFCC recommendation: The theory of reference values. Part 4. Control of analytical variation in the production, transfer and application of reference values

Journal of Automatic Chemistry ◽

10.1155/s146392469100038x ◽

1991 ◽

Vol 13 (5) ◽

pp. 231-234 ◽

Cited By ~ 12

Author(s):

Helge Erik Solberg ◽

D. Stamm

Keyword(s):

Reference Values ◽

Reference Data ◽

Expert Panel ◽

Clinical Chemistry ◽

Statistical Treatment ◽

Reference Limits ◽

The Subject ◽

Analytical Variation ◽

Selection Of

This paper is the fourth in a series of Recommendations on the Theory of Reference Values. The others cover:Part 1. The Concept of Reference Values [1].Part 2. Selection of Individuals for the Production of Reference Values [2].Part 3. Preparation of Individuals and Collection of Specimens for the Production of Reference Values [3].Part 5. Statistical Treatment of Collected Reference Values. Determination of Reference Limits [4].Part 6. Presentation of Observed Values Related to Reference Values [5].A Guide to the Documents is currently in preparation.The Expert Panel of Theory of Reference Values (EPTRV) was created in 1970 by the Committee on Standards (at present: Scientific Division) of the International Federation of Clinical Chemistry (IFCC). Its task was to develop a nomenclature and recommend procedures for the production of reference values and their treatment, and presentation of observed values in relation to reference data.The first document in the above-mentioned series describes the subject of reference values and defines various terms. It would be best to read it for a thorough understanding of the present document.

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A simple transformation independent method for outlier definition

Clinical Chemistry and Laboratory Medicine (CCLM) ◽

10.1515/cclm-2018-0025 ◽

2018 ◽

Vol 56 (9) ◽

pp. 1524-1532 ◽

Cited By ~ 3

Author(s):

Martin Berg Johansen ◽

Peter Astrup Christensen

Keyword(s):

Detection Method ◽

Reference Intervals ◽

Independent Method ◽

Medical Laboratories ◽

Simple Transformation ◽

Reference Limits ◽

Definition Of ◽

Box Cox Transformation ◽

Better Than

AbstractBackground:Definition and elimination of outliers is a key element for medical laboratories establishing or verifying reference intervals (RIs). Especially as inclusion of just a few outlying observations may seriously affect the determination of the reference limits. Many methods have been developed for definition of outliers. Several of these methods are developed for the normal distribution and often data require transformation before outlier elimination.Methods:We have developed a non-parametric transformation independent outlier definition. The new method relies on drawing reproducible histograms. This is done by using defined bin sizes above and below the median. The method is compared to the method recommended by CLSI/IFCC, which uses Box-Cox transformation (BCT) and Tukey’s fences for outlier definition. The comparison is done on eight simulated distributions and an indirect clinical datasets.Results:The comparison on simulated distributions shows that without outliers added the recommended method in general defines fewer outliers. However, when outliers are added on one side the proposed method often produces better results. With outliers on both sides the methods are equally good. Furthermore, it is found that the presence of outliers affects the BCT, and subsequently affects the determined limits of current recommended methods. This is especially seen in skewed distributions. The proposed outlier definition reproduced current RI limits on clinical data containing outliers.Conclusions:We find our simple transformation independent outlier detection method as good as or better than the currently recommended methods.

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Determination of indirect reference intervals of vitamin B12 for outpatients admitted to primary healthcare centers

Journal of Laboratory Medicine ◽

10.1515/labmed-2018-0160 ◽

2020 ◽

Vol 44 (1) ◽

pp. 11-16

Author(s):

Esin Avci ◽

Diler Aslan

Keyword(s):

Vitamin B12 ◽

Primary Healthcare ◽

Clinical Chemistry ◽

Age Groups ◽

Vitamin B12 Deficiency ◽

Reference Intervals ◽

Microcytic Anemia ◽

Reference Limits ◽

B12 Deficiency

Abstract Background Vitamin B12 deficiency is still an important nutritional problem worldwide. There is no consensus on the reference intervals (RIs) for vitamin B12. In order to establish vitamin B12 RIs, we used the database obtained from a primary healthcare organization and estimated region-specific intervals. Methods Vitamin B12 results were collected from our laboratory information system (LIS) between January 2014 and July 2014. We excluded the results of the individuals who had megaloblastic and microcytic anemia. After outlier detection and exclusion, we estimated the RIs of the “1–12, 13–18, 19–64 and 65 +” age groups according to the International Federation of Clinical Chemistry (IFCC) method. Statistical differences were examined between groups. Results The reference limits and 90% confidence intervals (CIs) (n = 14,748, 3790 male, age: 1–96; 10,958 female, age: 1–115) were estimated with 90% CIs as 106 (104–107)–393 (391–395) pmol/L. We also estimated the reference limits of the “1–12, 13–18, 19–64 and 65 +” age groups to be 127–459, 108–398, 106–384 and 104–426 pmol/L, respectively. There was no difference between genders in all age groups. Conclusions Both the lower and upper limits of the estimated RIs were found to be lower than the reference limits recommended by the manufacturer. Our findings revealed that the RIs of vitamin B12 should be given for the “1–12, 13–18, 19–64 and 65 +” age groups separately. The big data obtained from laboratories should be used for the determination of its population health status. As our population is composed of outpatients, the estimated vitamin B12 RIs may establish the basic information for the examination of our population for vitamin B12 deficiency.

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Determination of reference limits: statistical concepts and tools for sample size calculation

Clinical Chemistry and Laboratory Medicine (CCLM) ◽

10.1515/cclm-2014-0226 ◽

2014 ◽

Vol 52 (12) ◽

Cited By ~ 12

Author(s):

Stefan Wellek ◽

Karl J. Lackner ◽

Christine Jennen-Steinmetz ◽

Iris Reinhard ◽

Isabell Hoffmann ◽

...

Keyword(s):

Sample Size ◽

Diagnostic Marker ◽

Parametric Method ◽

Sample Size Calculation ◽

Reference Intervals ◽

Healthy Population ◽

Reference Limits

AbstractReference limits are estimators for ‘extreme’ percentiles of the distribution of a quantitative diagnostic marker in the healthy population. In most cases, interest will be in the 90% or 95% reference intervals. The standard parametric method of determining reference limits consists of computing quantities of the form

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Impact of Subgroup Prevalences on Partitioning of Gaussian-distributed Reference Values

Clinical Chemistry ◽

10.1093/clinchem/48.11.1987 ◽

2002 ◽

Vol 48 (11) ◽

pp. 1987-1999 ◽

Cited By ~ 49

Author(s):

Ari Lahti ◽

Per Hyltoft Petersen ◽

James C Boyd

Keyword(s):

Reference Interval ◽

Reference Population ◽

Reference Intervals ◽

Source Population ◽

Distributed Data ◽

New Model ◽

Common Reference ◽

Reference Limits ◽

Partitioning Problem ◽

Analytical Expressions

Abstract Background: The aims of this report were to examine how unequal subgroup prevalences in the source population may affect reference interval partitioning decisions and to develop generally applicable guidelines for partitioning gaussian-distributed data. Methods: We recently proposed a new model for partitioning reference intervals when the underlying data distribution is gaussian. This model is based on controlling the proportions of the subgroup distributions that fall outside each of the common reference limits, using the distances between the reference limits of the subgroup distributions as functions to these proportions. We examine the significance of the unequal prevalence effect for the partitioning problem and quantify it for distance partitioning criteria by deriving analytical expressions to express these criteria as a function of the ratio of prevalences. An application example, illustrating various aspects of the importance of the prevalence effect, is also presented. Results: Dramatic shrinkage of the critical distances between reference limits of the subgroups needed for partitioning was observed as the ratio of prevalences, the larger one divided by the smaller one, was increased from unity. Because of this shrinkage, the same critical distances are not valid for all ratios of prevalences, but specific critical distances should be used for each particular value of this ratio. Although proportion criteria used in determining the need for reference interval partitioning are not dependent on the prevalence effect, this effect should be accounted for when these criteria are being applied by adjusting the sample sizes of the subgroups to make them correspond to the ratio of prevalences. Conclusions: The prevalences of subgroups in the reference population should be known and observed in the calculations for every reference interval study, irrespective of whether distance or proportion criteria are being used to determine the need for reference interval partitioning. We present detailed methods to account for the prevalences when applying each of these types of criteria. Analytical expressions for the distance criteria, to be used when high precision is needed, and approximate distances, to be used in practical work, are derived. General guidelines for partitioning gaussian distributed data are presented. Following these guidelines and using the new model, we suggest that partitioning can be performed more reliably than with any of the earlier models because the new model not only offers an improved correspondence between the critical distances and the critical proportions, but also accounts for the prevalence effect.

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Indirect methods for reference interval determination – review and recommendations

Clinical Chemistry and Laboratory Medicine (CCLM) ◽

10.1515/cclm-2018-0073 ◽

2018 ◽

Vol 0 (0) ◽

Cited By ~ 6

Author(s):

Graham R.D. Jones ◽

Rainer Haeckel ◽

Tze Ping Loh ◽

Ken Sikaris ◽

Thomas Streichert ◽

...

Keyword(s):

Clinical Chemistry ◽

Direct Methods ◽

Analytical Techniques ◽

Reference Interval ◽

Reference Population ◽

Reference Intervals ◽

Statistical Techniques ◽

Indirect Methods ◽

Indirect Approach ◽

Patient Health

Abstract Reference intervals are a vital part of the information supplied by clinical laboratories to support interpretation of numerical pathology results such as are produced in clinical chemistry and hematology laboratories. The traditional method for establishing reference intervals, known as the direct approach, is based on collecting samples from members of a preselected reference population, making the measurements and then determining the intervals. An alternative approach is to perform analysis of results generated as part of routine pathology testing and using appropriate statistical techniques to determine reference intervals. This is known as the indirect approach. This paper from a working group of the International Federation of Clinical Chemistry (IFCC) Committee on Reference Intervals and Decision Limits (C-RIDL) aims to summarize current thinking on indirect approaches to reference intervals. The indirect approach has some major potential advantages compared with direct methods. The processes are faster, cheaper and do not involve patient inconvenience, discomfort or the risks associated with generating new patient health information. Indirect methods also use the same preanalytical and analytical techniques used for patient management and can provide very large numbers for assessment. Limitations to the indirect methods include possible effects of diseased subpopulations on the derived interval. The IFCC C-RIDL aims to encourage the use of indirect methods to establish and verify reference intervals, to promote publication of such intervals with clear explanation of the process used and also to support the development of improved statistical techniques for these studies.

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Developing a research process procedure for academic and practical management

Scientific Papers of Silesian University of Technology Organization and Management Series ◽

10.29119/1641-3466.2020.146.5 ◽

2020 ◽

Vol 2020 (146) ◽

pp. 61-73

Author(s):

Henryk DŹWIGOŁ ◽

Keyword(s):

Research Methods ◽

Research Process ◽

Management Science ◽

Methods And Techniques ◽

Original Procedure ◽

Research Questions ◽

Conducting Research ◽

Practical Implications ◽

Selection Of

Purpose: Developing a procedure for the course of the research process for management science and practice. An original procedure for the course of the research process in management and quality sciences was presented. Design/methodology/approach: Based on the analysis of domestic and foreign literature, as well as the model of the research process, five stages have been defined, which should be included in the procedure of the research process. They included: selection of the research subject, determination of the nature of the research, determination of the transparency of the research purpose, selection of the method of conducting the research, determination of the size of the studied sample. Findings: Taking into account the model of the research process, a procedure for conducting research was developed. Research limitations/implications: The developed procedure is a premise for conducting further research in the direction of assigning research methods and techniques to individual elements of the research process stages in management and quality sciences. Selection of appropriate methods and research techniques will translate into the verification of research hypotheses, such as and answers to research questions. Practical implications: First of all, it is important to develop a procedure for the course of the research process for management science and practice, and then, for individual stages of this process, assign appropriate research methods and techniques. Social implications: The author's procedure for the course of the research process presented in this article is a response to how to operationalize phenomena in the sciences on management and quality and thus translate into research related to Industry 4.0. Originality/value: The developed procedure for the course of the research process allows for detailed familiarization and carrying out of scientific research, and in particular for a precise presentation of the characteristics of the tested entity, dispelling doubts regarding the transparency of the conducted research, appropriate description of the method of conducting the research, and determining the size of the research sample.

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Functional reference limits: a case study of serum ferritin

Journal of Laboratory Medicine ◽

10.1515/labmed-2020-0127 ◽

2021 ◽

Vol 45 (2) ◽

pp. 69-77

Author(s):

Gorkem Sezgin ◽

Tze Ping Loh ◽

Corey Markus

Keyword(s):

Serum Ferritin ◽

Reference Population ◽

Reference Intervals ◽

Reference Limit ◽

Subclinical Disease ◽

Routinely Collected Data ◽

Reference Limits ◽

Relevant Reference ◽

The Relationship

Abstract Reference intervals depend on the distribution of results within a reference population and can be influenced by subclinical disease. Functional reference limits present an opportunity to derive clinically relevant reference limits from routinely collected data sources, which consist of mixed populations of unhealthy and healthy groups. Serum ferritin is a good example of the utility of functional reference limits. Several studies have identified clinically relevant reference limits through examining the relationship between serum ferritin and erythrocyte parameters. These ferritin functional limits often represent the inflection point at which erythrocyte parameters change significantly. Comparison of ferritin functional reference limits with those based on population distributional reference limits reveals that the lower reference limit may fall below the point at which patients become clinically unwell. Functional reference limits may be considered for any biomarker that exhibits a correlated relationship with other biomarkers.

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Quantitative laboratory results: normal or lognormal distribution?

Journal of Laboratory Medicine ◽

10.1515/labmed-2020-0005 ◽

2020 ◽

Vol 44 (3) ◽

pp. 143-150

Author(s):

Frank Klawonn ◽

Georg Hoffmann ◽

Matthias Orth

Keyword(s):

Clinical Chemistry ◽

Reference Intervals ◽

Parametric Estimation ◽

Distribution Model ◽

Practical Application ◽

Lognormal Distributions ◽

Reference Limits ◽

Skewness Coefficient ◽

Complex Procedure

Abstract The identification of a suitable distribution model is a prerequisite for the parametric estimation of reference intervals and other statistical laboratory tasks. Classification of normal vs. lognormal distributions from healthy populations is easy, but from mixed populations, containing unknown proportions of abnormal results, it is challenging. We demonstrate that Bowley’s skewness coefficient differentiates between normal and lognormal distributions. This classifier is robust and easy to calculate from the quartiles Q1–Q3 according to the formula (Q1 − 2 · Q2 + Q3)/(Q3 − Q1). We validate our algorithm with a more complex procedure, which optimizes the exponent λ of a power transformation. As a practical application, we show that Bowley’s skewness coefficient is suited selecting the adequate distribution model for the estimation of reference limits according to a recent International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) recommendation, especially if the data is right-skewed.

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A self-consistent set of reference values for 23 clinical chemical analytes.

Clinical Chemistry ◽

10.1093/clinchem/35.3.448 ◽

1989 ◽

Vol 35 (3) ◽

pp. 448-452 ◽

Cited By ~ 3

Author(s):

U E Spichiger ◽

D J Vonderschmitt

Keyword(s):

Reference Values ◽

Iterative Procedure ◽

Blood Donors ◽

Reference Population ◽

Reference Intervals ◽

Men And Women ◽

A Value ◽

Self Consistent ◽

Reference Limits ◽

Clinical Chemical

Abstract Heparinized plasma of 528 blood donors was subjected to the 23 most frequently ordered chemical and enzymatic tests. The central fraction of the distribution of all results for each test was estimated. Out of the 528 donors a reference population has been selected. Because of the lack of other criteria, the result for any test of a blood donor was selected as a value belonging to the reference population if the results for the other 22 analytes of this particular donor lay within their own central fraction. On this basis an iterative procedure for the selection was programmed, considering the interaction between tests. The procedure was stopped when the reference limits for all 23 tests were converging. Fractions from 0.90 to 0.98 were applied to results for men and women donors separately. The elimination procedure and the criteria to select the best fitted fraction are discussed. The derived reference intervals are designated a "self-consistent set of reference values."

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