Establishing and using reference intervals

2020 ◽  
Vol 45 (1) ◽  
pp. 1-10
Author(s):  
Yesim Ozarda
Keyword(s):  
Clinical Chemistry ◽  
Laboratory Data ◽  
Age Groups ◽  
Clinical Decision ◽  
Reference Population ◽  
External Source ◽  
Reference Intervals ◽  
Multicenter Studies ◽  
Indirect Methods ◽  
Laboratory Test Results

AbstractReference intervals (RIs) and clinical decision limits (CDLs) are fundamental tools used by healthcare and laboratory professionals to interpret patient laboratory test results. The traditional method for establishing RIs, 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. For challenging groups such as pediatric and geriatric age groups, indirect methods are appointed for the derivation of RIs in the EP28-A3c guideline. However, there has been an increasing demand to use the indirect methods of deriving RIs by the use of routine laboratory data stored in the laboratory information system. International Federation of Clinical Chemistry (IFCC), Committee on Reference Intervals and Decision Limits (C-RIDL) is currently working on the study for the comparison of the conventional (direct) and alternative (indirect) approaches for the determination of reference intervals. As a matter of fact that, the process of developing RIs is often beyond the capabilities of an individual laboratory due to the complex, expensive and time-consuming process to develop them. Therefore, a laboratory can alternatively transfer and verify RIs established by an external source (i.e. manufacturers’ package inserts, publications). IFCC, C-RIDL has focused primarily on RIs and has performed multicenter studies to obtain common RIs in recent years. However, as the broader responsibility of the Committee, from its name, includes “decision limits”, the C-RIDL also emphasizes the importance of the correct use of both RIs and CDLs and to encourage laboratories to specify the appropriate information to clinicians as needed.

scholarly journals Verification of reference intervals in routine clinical laboratories: practical challenges and recommendations

2018 ◽  
Vol 0 (0) ◽  
Author(s):  
Yesim Ozarda ◽  
Victoria Higgins ◽  
Khosrow Adeli
Keyword(s):  
Clinical Laboratory ◽  
Local Population ◽  
Age Groups ◽  
External Source ◽  
Reference Intervals ◽  
Laboratory Method ◽  
Test Results ◽  
Multicenter Studies ◽  
Clinical Laboratories ◽  
Laboratory Test Results

Abstract Reference intervals (RIs) are fundamental tools used by healthcare and laboratory professionals to interpret patient laboratory test results, ideally enabling differentiation of healthy and unhealthy individuals. Under optimal conditions, a laboratory should perform its own RI study to establish RIs specific for its method and local population. However, the process of developing RIs is often beyond the capabilities of an individual laboratory due to the complex, expensive and time-consuming process to develop them. Therefore, a laboratory can alternatively verify RIs established by an external source. Common RIs can be established by large, multicenter studies and can subsequently be received by local laboratories using various verification procedures. The standard approach to verify RIs recommended by the Clinical Laboratory Standards Institute (CLSI) EP28-A3c guideline for routine clinical laboratories is to collect and analyze a minimum of 20 samples from healthy subjects from the local population. Alternatively, “data mining” techniques using large amounts of patient test results can be used to verify RIs, considering both the laboratory method and local population. Although procedures for verifying RIs in the literature and guidelines are clear in theory, gaps remain for the implementation of these procedures in routine clinical laboratories. Pediatric and geriatric age-groups also continue to pose additional challenges in respect of acquiring and verifying RIs. In this article, we review the current guidelines/approaches and challenges to RI verification and provide a practical guide for routine implementation in clinical laboratories.

scholarly journals Indirect methods for reference interval determination – review and recommendations

2018 ◽  
Vol 0 (0) ◽  
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.

Establishment of Reference Intervals for Alkaline Phosphatase in Pakistani Children Using a Data Mining Approach

2019 ◽  
Vol 51 (5) ◽  
pp. 484-490 ◽  
Author(s):  
Sibtain Ahmed ◽  
Jakob Zierk ◽  
Aysha Habib Khan
Keyword(s):  
Data Mining ◽  
Alkaline Phosphatase ◽  
Clinical Decision Making ◽  
Clinical Chemistry ◽  
Age Groups ◽  
Clinical Decision ◽  
German Society ◽  
Reference Intervals ◽  
Photometric Method ◽  
Data Mining Approach

Abstract Objective To establish reference intervals (RIs) for alkaline phosphatase (ALP) levels in Pakistani children using an indirect data mining approach. Methods ALP levels analyzed on a Siemens Advia 1800 analyzer using the International Federation of Clinical Chemistry’s photometric method for both inpatients and outpatients aged 1 to 17 years between January 2013 and December 2017, including patients from intensive care units and specialty units, were retrieved. RIs were calculated using a previously validated indirect algorithm developed by the German Society of Clinical Chemistry and Laboratory Medicine’s Working Group on Guide Limits. Results From a total of 108,845 results, after the exclusion of patients with multiple specimens, RIs were calculated for 24,628 males and 18,083 females with stratification into fine-grained age groups. These RIs demonstrate the complex age- and sex-related ALP dynamics occurring during physiological development. Conclusion The population-specific RIs serve to allow an accurate understanding of the fluctuations in analyte activity with increasing age and to support clinical decision making.

High-resolution pediatric reference intervals for 15 biochemical analytes described using fractional polynomials

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Jakob Zierk ◽  
Hannsjörg Baum ◽  
Alexander Bertram ◽  
Martin Boeker ◽  
Armin Buchwald ◽  
...  
Keyword(s):  
Information Systems ◽  
Laboratory Test ◽  
Clinical Decision Making ◽  
Age Groups ◽  
Clinical Decision ◽  
Reference Intervals ◽  
Test Results ◽  
Laboratory Test Results ◽  
Glutamyl Transferase ◽  
Laboratory Information Systems

Abstract Objectives Assessment of children’s laboratory test results requires consideration of the extensive changes that occur during physiological development and result in pronounced sex- and age-specific dynamics in many biochemical analytes. Pediatric reference intervals have to account for these dynamics, but ethical and practical challenges limit the availability of appropriate pediatric reference intervals that cover children from birth to adulthood. We have therefore initiated the multi-center data-driven PEDREF project (Next-Generation Pediatric Reference Intervals) to create pediatric reference intervals using data from laboratory information systems. Methods We analyzed laboratory test results from 638,683 patients (217,883–982,548 samples per analyte, a median of 603,745 test results per analyte, and 10,298,067 test results in total) performed during patient care in 13 German centers. Test results from children with repeat measurements were discarded, and we estimated the distribution of physiological test results using a validated statistical approach (kosmic). Results We report continuous pediatric reference intervals and percentile charts for alanine transaminase, aspartate transaminase, lactate dehydrogenase, alkaline phosphatase, γ-glutamyl-transferase, total protein, albumin, creatinine, urea, sodium, potassium, calcium, chloride, anorganic phosphate, and magnesium. Reference intervals are provided as tables and fractional polynomial functions (i.e., mathematical equations) that can be integrated into laboratory information systems. Additionally, Z-scores and percentiles enable the normalization of test results by age and sex to facilitate their interpretation across age groups. Conclusions The provided reference intervals and percentile charts enable precise assessment of laboratory test results in children from birth to adulthood. Our findings highlight the pronounced dynamics in many biochemical analytes in neonates, which require particular consideration in reference intervals to support clinical decision making most effectively.

Age-specific thyroid hormone and thyrotropin reference intervals for a pediatric and adolescent population

2012 ◽  
Vol 50 (5) ◽  
Author(s):  
Eduardo A. Chaler ◽  
Romina Fiorenzano ◽  
Carla Chilelli ◽  
Vanessa Llinares ◽  
Giselle Areny ◽  
...  
Keyword(s):  
Thyroid Hormones ◽  
Clinical Chemistry ◽  
Laboratory Data ◽  
Age Groups ◽  
Reference Value ◽  
Reference Intervals ◽  
Reference Distribution ◽  
Free T4 ◽  
Reference Change Value ◽  
Serum Tsh

AbstractEstablishment of reliable reference intervals remains valuable for confirming validity and advancing standardization across methods and populations. Moreover, knowledge of the measurement uncertainty (U) and of the reference change value (RCV) has important applications in clinical chemistry.Starting from the information available in the laboratory data base (29,901 subjects) an initial selection was carried out by eliminating all subjects with a clinical or laboratory pathological report; data from 7581 0- to 20-year-old subjects (53.87% girls) remained in the study. These subjects, divided into nine age groups, were used to define reference distribution percentiles (2.5th, 50th and 97.5th) of serum thyrotropin (TSH), triiodothyronine (T3), thyroxine (T4), and free T4 (fT4), as well as U and RCV of these assays.In early infancy, T4 and fT4 values were higher than in the older age groups. Serum T4 95th percentile reference value, useful for the diagnosis of hyperthyroidism, was 142.9 in 20-year-old boys and 230.4 nmol/L in early infants and serum T3 95th percentile was 2.6 and 3.5 nmol/L, respectively, while fT4 2.5th percentile reference value, useful for the diagnosis of hypothyroidism, was 9.6 and 13.0 pmol/L, respectively. Serum TSH 97.5th percentile showed less age variation, 4.38–4.88 mIU/L. Performance of the four assays resulted in approximately 20% Us, reflecting simple and complex imprecision, trueness, analytical and functional sensitivity. RCV of serum TSH (58.6%) was larger than for thyroid hormones (28.3%–34.7%), probably due to the high biological variation of this hormone.We have established reference interval for TSH and thyroid hormones, as well as Us for assessing reliability of measurements, and RCVs to alert users on the presence of clinical significant changes.

scholarly journals Personalized Reference Intervals in Laboratory Medicine: A New Model Based on Within-Subject Biological Variation

2020 ◽  
Author(s):  
Abdurrahman Coşkun ◽  
Sverre Sandberg ◽  
Ibrahim Unsal ◽  
Coskun Cavusoglu ◽  
Mustafa Serteser ◽  
...  
Keyword(s):  
Steady State ◽  
Personalized Medicine ◽  
Clinical Chemistry ◽  
Reference Interval ◽  
Reference Intervals ◽  
Biological Variation ◽  
Test Results ◽  
Steady State Condition ◽  
Laboratory Test Results ◽  
Measurement Results

Abstract Background The concept of personalized medicine has received widespread attention in the last decade. However, personalized medicine depends on correct diagnosis and monitoring of patients, for which personalized reference intervals for laboratory tests may be beneficial. In this study, we propose a simple model to generate personalized reference intervals based on historical, previously analyzed results, and data on analytical and within-subject biological variation. Methods A model using estimates of analytical and within-subject biological variation and previous test results was developed. We modeled the effect of adding an increasing number of measurement results on the estimation of the personal reference interval. We then used laboratory test results from 784 adult patients (>18 years) considered to be in a steady-state condition to calculate personalized reference intervals for 27 commonly requested clinical chemistry and hematology measurands. Results Increasing the number of measurements had little impact on the total variation around the true homeostatic set point and using ≥3 previous measurement results delivered robust personalized reference intervals. The personalized reference intervals of the study participants were different from one another and, as expected, located within the common reference interval. However, in general they made up only a small proportion of the population-based reference interval. Conclusions Our study shows that, if using results from patients in steady state, only a few previous test results and reliable estimates of within-subject biological variation are required to calculate personalized reference intervals. This may be highly valuable for diagnosing patients as well as for follow-up and treatment.

scholarly journals Plasma midregional proadrenomedullin (MR-proADM) concentrations and their biological determinants in a reference population

2018 ◽  
Vol 56 (7) ◽  
pp. 1161-1168 ◽  
Author(s):  
Magdalena Krintus ◽  
Marek Kozinski ◽  
Federica Braga ◽  
Jacek Kubica ◽  
Grazyna Sypniewska ◽  
...  
Keyword(s):  
Reference Group ◽  
Adult Population ◽  
Reference Population ◽  
Cross Sectional Study ◽  
Reference Intervals ◽  
Cross Sectional ◽  
Multiple Organs ◽  
Laboratory Test Results ◽  
Biological Determinants ◽  
Apparently Healthy

Abstract Background: Midregional proadrenomedullin (MR-proADM) is emerging as a prognostic biomarker for detecting the failure of multiple organs. Establishment of scientifically robust reference intervals facilitates interpretation of laboratory test results. The objectives of this study were (i) to establish reliable reference intervals for plasma MR-proADM using a commercially available automated fluoroimmunoassay in apparently healthy individuals, and (ii) to identify biological determinants of MR-proADM concentrations. Methods: A total of 506 questionnaire-identified apparently healthy adults were enrolled in a single-center, cross-sectional study. A final reference group (n=172) was selected after exclusion of obese individuals, those with increased values of laboratory biomarkers indicating asymptomatic myocardial injury or dysfunction, ongoing inflammation, diabetes, dyslipidemia and renal dysfunction and outliers. Results: The 2.5th and 97.5th percentile intervals for MR-proADM values in the reference group (90% confidence interval) were 0.21 (0.19–0.23) and 0.57 (0.55–0.59) nmol/L, respectively. Although older age, higher values of HbA1c, C-reactive protein, B-type natriuretic peptide and body mass index, together with a history of smoking and a decreased estimated glomerular filtration rate were significantly associated with increasing concentrations of MR-proADM in both univariate and multivariate analyses, magnitudes of these relationships were modest and did not substantially influence MR-proADM reference intervals. Sex-dependent difference in MR-proADM reference intervals was not detected [0.19 (0.16–0.22)–0.56 (0.54–0.60) nmol/L in females vs. 0.22 (0.20–0.25)–0.58 (0.57–0.63) nmol/L in males]. Conclusions: Our study successfully established robust reference intervals for MR-proADM concentrations in plasma. Considering the negligible influence of potential biological determinants on plasma MR-proADM, we recommend the adoption of single reference intervals for adult population as a whole.

Age- and Sex-Specific Dynamics in 22 Hematologic and Biochemical Analytes from Birth to Adolescence

2015 ◽  
Vol 61 (7) ◽  
pp. 964-973 ◽  
Author(s):  
Jakob Zierk ◽  
Farhad Arzideh ◽  
Tobias Rechenauer ◽  
Rainer Haeckel ◽  
Wolfgang Rascher ◽  
...  
Keyword(s):  
Cell Count ◽  
Clinical Decision Making ◽  
Clinical Care ◽  
Age Groups ◽  
Reference Intervals ◽  
Interindividual Variation ◽  
Red Cell ◽  
Distribution Width ◽  
Laboratory Test Results ◽  
Age And Sex

Abstract BACKGROUND Pediatric laboratory test results must be interpreted in the context of interindividual variation and age- and sex-dependent dynamics. Reference intervals as presently defined for separate age groups can only approximate the age-related dynamics encountered in pediatrics. Continuous reference intervals from birth to adulthood are not available for most laboratory analytes because of the ethical and practical constraints of defining reference intervals using a population of healthy community children. We applied an indirect method to generate continuous reference intervals for 22 hematologic and biochemical analytes by analyzing clinical laboratory data from blood samples taken during clinical care of patients. METHODS We included samples from 32 000 different inpatients and outpatients (167 000 samples per analyte) from a German pediatric tertiary care center. Measurements were performed on a Sysmex-XE 2100 and a Cobas Integra 800 during clinical care over a 6-year period. The distribution of samples considered normal was estimated with an established indirect statistical approach and used for the calculation of reference intervals. RESULTS We provide continuous reference intervals from birth to adulthood for 9 hematology analytes (hemoglobin, hematocrit, red cell indices, red cell count, red cell distribution width, white cell count, and platelet count) and 13 biochemical analytes (sodium, chloride, potassium, calcium, magnesium, phosphate, creatinine, aspartate transaminase, alanine transaminase, γ-glutamyltransferase, alkaline phosphatase, lactate dehydrogenase, and total protein). CONCLUSIONS Continuous reference intervals capture the population changes in laboratory analytes during pediatric development more accurately than age groups. After local validation, the reference intervals provided should allow a more precise consideration of these dynamics in clinical decision making.

Biochemical reference intervals for sex hormones with a new AutoDelfia method in aged men

2007 ◽  
Vol 45 (2) ◽  
Author(s):  
Seija Eskelinen ◽  
Tero Vahlberg ◽  
Raimo Isoaho ◽  
Sirkka-Liisa Kivelä ◽  
Kerttu Irjala
Keyword(s):  
Sex Hormones ◽  
Follicle Stimulating Hormone ◽  
Age Groups ◽  
Free Testosterone ◽  
Reference Population ◽  
Reference Intervals ◽  
Sex Hormone ◽  
Sex Hormone Binding Globulin ◽  
Reference Ranges ◽  
Hormone Binding

AbstractOur aim was to establish sex hormone reference intervals measured with a new AutoDelfia immunoassay method for aged men free of medication and/or conditions known to influence sex hormone levels.The reference population consisted of 466 individuals between 64 and 97 years (mean 72 years) and a mean body mass index (BMI) of 26.9 kg/mBecause age correlated significantly with most sex hormones studied, we calculated reference intervals for three age groups (64–69, 70–74 and ≥75 years). In clinical practice, single ranges can be used for men aged 64 years or over for testosterone, estradiol and follicle-stimulating hormone (FSH) with the AutoDelfia method. For free testosterone and luteinizing hormone (LH), separate reference intervals should be used for men aged 64–74 years and those aged 75 years or over. For sex hormone-binding globulin, two separate reference intervals by age (64–69 and ≥70 years) are also needed for aged men. LH and FSH reference ranges should be judged with caution, because they may be too high due to cases of subclinical hypogonadism included in the reference population.Clin Chem Lab Med 2007;45:249–53.

Recommendation for the review of biological reference intervals in medical laboratories

2016 ◽  
Vol 54 (12) ◽  
Author(s):  
Joseph Henny ◽  
Anne Vassault ◽  
Guilaine Boursier ◽  
Ines Vukasovic ◽  
Pika Mesko Brguljan ◽  
...  
Keyword(s):  
Expert Panel ◽  
Clinical Chemistry ◽  
Simple Procedure ◽  
Reference Population ◽  
Reference Intervals ◽  
Medical Laboratories ◽  
Reference Limits ◽  
Original Procedure ◽  
Selection Of

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.

Sign in / Sign up

Export Citation Format

Share Document