Indirect Reference Intervals: Harnessing the Power of Stored Laboratory Data

Reference intervals are relied upon by clinicians when interpreting their patients’ test results. Therefore, laboratorians directly contribute to patient care when they report accurate reference intervals. The traditional approach to establishing reference intervals is to perform a study on healthy volunteers. However, the practical aspects of the staff time and cost required to perform these studies make this approach difficult for clinical laboratories to routinely use. Indirect methods for deriving reference intervals, which utilise patient results stored in the laboratory’s database, provide an alternative approach that is quick and inexpensive to perform. Additionally, because large amounts of patient data can be used, the approach can provide more detailed reference interval information when multiple partitions are required, such as with different age-groups. However, if the indirect approach is to be used to derive accurate reference intervals, several considerations need to be addressed. The laboratorian must assess whether the assay and patient population were stable over the study period, whether data ‘clean-up’ steps should be used prior to data analysis and, often, how the distribution of values from healthy individuals should be modelled. The assumptions and potential pitfalls of the particular indirect technique chosen for data analysis also need to be considered. A comprehensive understanding of all aspects of the indirect approach to establishing reference intervals allows the laboratorian to harness the power of the data stored in their laboratory database and ensure the reference intervals they report are accurate.

Reference values of plasma homocysteine in Cuban children and adults

LaboratoriumsMedizin ◽

10.1515/labmed-2019-0195 ◽

2020 ◽

Vol 0 (0) ◽

Author(s):

Alina Concepción Alvarez ◽

Ivette Camayd Viera ◽

Lisy Vento Buigues ◽

Yanet Fernández Martínez ◽

Eraida Hernández ◽

...

Keyword(s):

Reference Values ◽

High Performance ◽

Age Groups ◽

Coffee Consumption ◽

Reference Interval ◽

Reference Intervals ◽

Multifactorial Diseases ◽

Weak Association ◽

Different Populations ◽

Cuban Population

AbstractObjectivesHomocysteine (Hcy) is a nonessential amino acid, produced by the demethylation of methionine. High Hcy levels, or hyperhomocysteinemia, have been associated with genetic and multifactorial diseases. Hcy reference values may vary between different populations, as Hcy levels are affected by factors such as sex, age, diet, smoking, and coffee consumption. The estimation reference interval (RI) allows to establish the normal values of this marker in population. At present, these levels are unknown in Cuba. The aim of this work is to estimate the Hcy reference intervals in Cuban children and adults.MethodsTotal Hcy concentration was quantified by high performance liquid chromatography (HPLC) in plasma. Hcy levels were evaluated in samples from 507 healthy individuals (260 children, 247 adults).ResultsRIs were estimated by nonparametric methods. We found significant differences between both age groups, but we did not find significant differences between sexes, within these groups. The established ranges were 2.56–14.55 µM and 3.63–17.19 µM for children and adults, respectively. Also, we observed a weak association between Hcy levels and age in both sex groups.ConclusionsThis is the first study that assesses Hcy reference values in Cuban population. Our results will allow the introduction of Hcy as a biochemical marker in laboratory testing.

Reference intervals for hematology test parameters from apparently healthy individuals in southwest Ethiopia

SAGE Open Medicine ◽

10.1177/2050312118807626 ◽

2018 ◽

Vol 6 ◽

pp. 205031211880762 ◽

Cited By ~ 6

Author(s):

Lealem Gedefaw Bimerew ◽

Tesfaye Demie ◽

Kaleab Eskinder ◽

Aklilu Getachew ◽

Shiferaw Bekele ◽

...

Keyword(s):

Platelet Count ◽

Blood Cell ◽

White Blood Cell ◽

Red Blood Cell ◽

Hematological Parameters ◽

Age Groups ◽

Reference Interval ◽

Reference Intervals ◽

Southwest Ethiopia ◽

Apparently Healthy

Background: Clinical laboratory reference intervals are an important tool to identify abnormal laboratory test results. The generating of hematological parameters reference intervals for local population is very crucial to improve quality of health care, which otherwise may lead to unnecessary expenditure or denying care for the needy. There are no well-established reference intervals for hematological parameters in southwest Ethiopia. Objective: To generate hematological parameters reference intervals for apparently healthy individuals in southwest Ethiopia. Methods: A community-based cross-sectional study was conducted involving 883 individuals from March to May 2017. Four milliliter of blood sample was collected and transported to Jimma University Medical Center Laboratory for hematological analysis and screening tests. A hematological parameters were measured by Sysmex XS-500i hematology analyzer (Sysmex Corporation Kobe, Japan). The data were analyzed by SPSS version 20 statistical software. The non-parametric independent Kruskal–Wallis test and Wilcoxon rank-sum test (Mann–Whitney U test) were used to compare the parameters between age groups and genders. The 97.5 percentile and 2.5 percentile were the upper and lower reference limit for the population. Results: The reference interval of red blood cell, white blood cell, and platelet count in children were 4.99 × 1012/L (4.26–5.99 × 1012/L), 7.04 × 109/L (4.00–11.67 × 109/L), and 324.00 × 109/L (188.00–463.50 × 109/L), respectively. The reference interval of red blood cell, white blood cell, and platelet count in adults was 5.19 × 1012/L (4.08–6.33 × 1012/L), 6.35 × 109/L (3.28–11.22 × 109/L), and 282.00 × 109/L (172.50–415.25 × 109/L), respectively. The reference interval of red blood cell, white blood cell, and platelet count in geriatrics were 5.02 × 1012/L (4.21–5.87 × 1012/L), 6.21 × 109/L (3.33–10.03 × 109/L), and 265.50 × 109/L (165.53–418.80 × 109/L), respectively. Most of the hematological parameters showed significant differences across all age groups. Conclusion: Most of the hematological parameters in this study showed differences from similar studies done in the country. This study provided population-specific hematological reference interval for southwest Ethiopians. Reference intervals should also be established in the other regions of the country.

Establishment of the reference interval for serum pro-gastrin-releasing peptide in healthy adults of Chinese Han ethnicity

The International Journal of Biological Markers ◽

10.1177/1724600818783416 ◽

2018 ◽

Vol 33 (4) ◽

pp. 487-491 ◽

Cited By ~ 3

Author(s):

Bing Zhao ◽

Miaomiao Zhang ◽

Feng Lin ◽

Jing Xie ◽

Yan Liang ◽

...

Keyword(s):

Age Groups ◽

Reference Interval ◽

Reference Intervals ◽

Chinese Han ◽

Gastrin Releasing Peptide ◽

Han Ethnicity ◽

Significant Difference ◽

Healthy Chinese ◽

Han Adults ◽

Non Parametric

Objective: The aim of this study is to establish the reference interval for serum pro-gastrin-releasing peptide (proGRP) determined by electrochemiluminescence immunoassay (ECLIA) in healthy Chinese Han ethnic adults. Methods: After screening, 9932 healthy Chinese Han adults (age range 18–95 years) were enrolled in this study, including 6220 men and 3712 women. Serum proGRP levels were measured by ECLIA. The reference interval was defined by non-parametric 95th percentile interval. Results: Serum proGRP levels conformed to a non-Gussian distribution. The reference interval for healthy Chinese Han adults calculated by the non-parametric method was 0–73.90 ng/mL in this study. Since serum proGRP levels were significantly correlated with age (r=0.226, P<0.001), the participants were divided into six age groups: 18–39, 40–49, 50–59, 60–69, 70–79, and ⩾80 years. No significant difference for serum proGRP levels was found between the sexes at each of six age groups. The reference intervals were gradually increased with age (65.35 ng/mL, 68.65 ng/mL, 74.10 ng/mL, 77.65 ng/mL, 84.57 ng/mL, and 98.03 ng/mL in 18–39, 40–49, 50–59, 60–69, 70–79, and ⩾80 years, respectively). Conclusions: We established the reference interval for serum proGRP, which was determined by ECLIA in the healthy Chinese Han population. Furthermore, our study suggests that it is necessary to establish the age-specific reference intervals for serum proGRP.

A multi-stage Gaussian transformation algorithm for clinical laboratory data.

Clinical Chemistry ◽

10.1093/clinchem/28.8.1735 ◽

1982 ◽

Vol 28 (8) ◽

pp. 1735-1741 ◽

Cited By ~ 26

Author(s):

J C Boyd ◽

D A Lacher

Keyword(s):

Mean Squared Error ◽

Clinical Laboratory ◽

Statistical Tests ◽

Random Noise ◽

Laboratory Data ◽

Reference Interval ◽

Reference Intervals ◽

Distributed Data ◽

Multi Stage ◽

Positive Coefficients

Abstract We have developed a multi-stage computer algorithm to transform non-normally distributed data to a normal distribution. This transformation is of value for calculation of laboratory reference intervals and for normalization of clinical laboratory variates before applying statistical procedures in which underlying data normality is assumed. The algorithm is able to normalize most laboratory data distributions with either negative or positive coefficients of skewness or kurtosis. Stepwise, a logarithmic transform removes asymmetry (skewness), then a Z-score transform and power function transform remove residual peakedness or flatness (kurtosis). Powerful statistical tests of data normality in the procedure help the user evaluate both the necessity for and the success of the data transformation. Erroneous assessments of data normality caused by rounded laboratory test values have been minimized by introducing computer-generated random noise into the data values. Reference interval endpoints that were estimated parametrically (mean +/- 2 SD) by using successfully transformed data were found to have a smaller root-mean-squared error than those estimated by the non-parametric percentile technique.

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.

Reference intervals for hemoglobin and mean corpuscular volume in an ethnically diverse community sample of Canadian children 2 to 36 months

BMC Pediatrics ◽

10.1186/s12887-021-02709-w ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Jemila S. Hamid ◽

Eshetu G. Atenafu ◽

Cornelia M. Borkhoff ◽

Catherine S. Birken ◽

Jonathon L. Maguire ◽

...

Keyword(s):

Confidence Intervals ◽

Mean Corpuscular Volume ◽

Community Sample ◽

Age Groups ◽

Ethnically Diverse ◽

Reference Interval ◽

Reference Intervals ◽

Corpuscular Volume ◽

Link Type ◽

Diverse Community

Abstract Objective To establish reference intervals for hemoglobin and mean corpuscular volume (MCV) in an ethnically diverse community sample of Canadian children 36 months and younger. Methods We collected blood samples from young children at scheduled primary care health supervision visits at 2 weeks, 2, 4, 6, 9, 12, 15, 18, 24, and 36 months of age. Samples were analyzed on the Sysmex XN-9000 Hematology Analyzer. We followed the Clinical and Laboratory Standards Institute guidelines in our analysis. Data were partitioned by sex and also combined. We considered large age partitions (3 and 6 months) as well as monthly partitions. Reference intervals (lower and upper limits) and 90% confidence intervals were calculated. Results Data from 2106 children were included. The age range was 2 weeks to 36 months, 46% were female, 48% were European and 23% were of mixed ethnicity. For hemoglobin, from 2 to 36 months of age, we found a wide reference interval and the 90% confidence intervals indicated little difference across age groups or according to sex. For MCV, from 2 to 7 months of age there was considerable decrease in the reference interval, which was lowest during the second year of life, followed by a slight increase in the last months of the third year of life. Conclusion These findings suggest adoption of a single hemoglobin reference interval for children 2–36 months of age. Further studies in children under 4 months of age are needed. Trial registration TARGet Kids! cohort is registered at ClinicalTrials.gov. www.clinicaltrials.gov. Identifier: NCT01869530.

A Comparison of Complete Blood Count Reference Intervals in Healthy Elderly Versus Younger Korean Adults: A Large Population Study

Blood ◽

10.1182/blood-2018-99-113203 ◽

2018 ◽

Vol 132 (Supplement 1) ◽

pp. 4708-4708

Author(s):

Young Kyung Lee ◽

Eun Jin Lee ◽

Miyoung Kim ◽

Eunyup Lee ◽

Kibum Jeon ◽

...

Keyword(s):

Blood Count ◽

Complete Blood Count ◽

Conflicts Of Interest ◽

Large Population ◽

Age Groups ◽

Reference Interval ◽

Reference Intervals ◽

Healthy Elderly ◽

Elderly Koreans ◽

Lower Limits

Abstract Background: The use of laboratory reference intervals based on younger populations is of questionable validity in older populations. We established reference intervals for 16 complete blood count (CBC) parameters in healthy elderly Koreans aged ≥60 years and compared them to those of individuals aged 20-59 years. Methods: Among 64,532 individuals (39,609 men and 24,923 women) aged ≥20 years who underwent medical check-ups, 8,151 healthy subjects (12.6%, 5,270 men and 2,881 women, including 675 and 511, respectively, who were ≥60 years of age) were enrolled based on stringent criteria including laboratory, imaging, and endoscopy results; previous medical history; and medication history. CBC parameters were measured using an Advia2120i instrument. The difference between 2 age groups in subjects of each sex was compared using the Mann-Whitney U-test. P-values <0.05 were considered statistically significant. The reference intervals for measured CBC parameters were established according to a nonparametric method based on the CLSI EP28A-3C in each subgroup. The 90% confidence intervals for the upper and lower limits of each reference interval were calculated; the Reed method was used to remove extreme outliers. The Harris and Boyd method was used to determine the necessity of separating the reference intervals for different age groups within each sex group. To identify reference intervals in different age groups in individuals aged 60 years and over, such individuals of each sex were subdivided into 5 age subgroups with 5-year age interval: since the sizes of 4 of these subgroups were not sufficiently large, we used the Robust method. Results: A statistical difference in the medians of the following parameters were observed between the <60- and ≥60-year age groups: RBC, Hb, hematocrit (Hct), basophils, and platelets in men aged <60 years were higher than those in men aged ≥60 years; furthermore, MCV, MCH, and RDW in men aged ≥60 years were higher than those in men aged <60 years. Neutrophils in women aged <60 years were higher than in those aged ≥60 years. Hb, Hct, MCV, MCH, MCHC, lymphocytes, and basophils in women aged ≥60 years were higher than in those aged <60 years. Separate reference intervals were required only for RDW and MCH in women ≥60 from those < 60 years of age. Men aged ≥60 years versus those <60 years did not require separate reference intervals for any of the 16 measured parameters. In subjects aged ≥60 years, RBC, Hb, Hct, MCV, MCH, MCHC, RDW, WBC, neutrophils, monocytes, eosinophils, MPV, and PDW were higher in men than in women, while the opposite was true for lymphocytes and platelets. Partitioning of reference intervals by sex was required for RBC, Hb, Hct, MCH, monocytes, and eosinophils. In men, median values and the lower limits of the reference intervals for RBC, Hb, and Hct tended to decrease with advancing age. The upper and lower limits of reference intervals for WBC, neutrophils, lymphocytes, and MPV also showed increasing and decreasing tendencies, respectively, widening the reference intervals as the subjects aged (except in the 70-74-year-old group for men). Among women, the lower limits of the reference intervals for RBC, Hb, and Hct showed a tendency to decrease with increasing age for those >70 years of age; however, the median values did not show such a tendency. The reference interval for PDW narrowed as women aged. Separate reference intervals were required among men for MCH and eosinophils in the 70-74-year group, and for basophils in the 65-69-year group. Among women, separate reference intervals were required for MCV in the 65-69-year group; for MCH in the 60-64, 65-69, and ≥75-years groups; and for RDW in all the 4 elderly age subgroups. Conclusion: Healthy elderly Koreans can use the same reference intervals as younger populations. Thus, abnormal CBC results may not necessarily be attributable to physiologic changes but possible underlying diseases that should be investigated. Disclosures No relevant conflicts of interest to declare.

Separating disease and health for indirect reference intervals

Journal of Laboratory Medicine ◽

10.1515/labmed-2020-0157 ◽

2021 ◽

Vol 45 (2) ◽

pp. 55-68 ◽

Cited By ~ 1

Author(s):

Kenneth A. Sikaris

Keyword(s):

A Priori ◽

Laboratory Data ◽

Reference Interval ◽

Statistical Technique ◽

Reference Intervals ◽

Large Databases ◽

Statistical Issues ◽

Physiological Variations ◽

Indirect Reference ◽

Apparently Healthy

Abstract The indirect approach to defining reference intervals operates ‘a posteriori’, on stored laboratory data. It relies on being able to separate healthy and diseased populations using one or both of clinical techniques or statistical techniques. These techniques are also fundamental in a priori, direct reference interval approaches. The clinical techniques rely on using clinical data that is stored either in the electronic health record or within the laboratory database, to exclude patients with possible disease. It depends on the investigators understanding of the data and the pathological impacts on tests. The statistical technique relies on identifying a dominant, apparently healthy, typically Gaussian distribution, which is unaffected by the overlapping populations with higher (or lower) results. It depends on having large databases to give confidence in the extrapolation of the narrow portion of overall distribution representing unaffected individuals. The statistical issues involved can be complex, and can result in unintended bias, particularly when the impacts of disease and the physiological variations in the data are under appreciated.

Blood sampling frequency as a proxy for comorbidity indices when identifying patient samples for review of reference intervals

Clinical Chemistry and Laboratory Medicine (CCLM) ◽

10.1515/cclm-2021-0987 ◽

2021 ◽

Vol 0 (0) ◽

Author(s):

Simon Lykkeboe ◽

Stine Linding Andersen ◽

Claus Gyrup Nielsen ◽

Peter Vestergaard ◽

Peter Astrup Christensen

Keyword(s):

Laboratory Data ◽

Low Frequency ◽

Reference Interval ◽

Reference Intervals ◽

Sampling Frequency ◽

Blood Sampling ◽

Test Results ◽

Healthy Individuals ◽

Simple Method ◽

Blood Samples

Abstract Objectives Indirect data mining methods have been proposed for review of published reference intervals (RIs), but methods for identifying patients with a low likelihood of disease are needed. Many indirect methods extract test results on patients with a low frequency blood sampling history to identify putative healthy individuals. Although it is implied there has been no attempt to validate if patients with a low frequency blood sampling history are healthy and if test results from these patients are suitable for RI review. Methods Danish nationwide health registers were linked with a blood sample database, recording a population of 316,337 adults over a ten-year period. Comorbidity indexes were defined from registrations of hospital diagnoses and redeemed prescriptions of drugs. Test results from patients identified as having a low disease burden were used for review of RIs from the Nordic Reference Interval Project (NORIP). Results Blood sampling frequency correlated with comorbidity Indexes and the proportion of patients without disease conditions were enriched among patients with a low number of blood samples. RIs based on test results from patients with only 1–3 blood samples per decade were for many analytes identical compared to NORIP RIs. Some analytes showed expected incongruences and gave conclusive insights into how well RIs from a more than 10 years old multi-center study (NORIP) performed on current pre-analytical and analytical methods. Conclusions Blood sampling frequency enhance the selection of healthy individuals for reviewing reference intervals, providing a simple method solely based on laboratory data without the addition of clinical information.