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Gong M, Wang K, Sun H, Wang K, Zhou Y, Cong Y, Deng X, Mao Y. Threshold of 25(OH)D and consequently adjusted parathyroid hormone reference intervals: data mining for relationship between vitamin D and parathyroid hormone. J Endocrinol Invest 2023; 46:2067-2077. [PMID: 36920734 PMCID: PMC10514164 DOI: 10.1007/s40618-023-02057-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Accepted: 03/02/2023] [Indexed: 03/16/2023]
Abstract
PURPOSE By recruiting reference population, we aimed to (1): estimate the 25(OH)D threshold that maximally inhibits the PTH, which can be defined as the cutoff value for vitamin D sufficiency; (2) establish the PTH reference interval (RI) in population with sufficient vitamin D. METHODS Study data were retrieved from LIS (Laboratory Information Management System) under literature suggested criteria, and outliers were excluded using Tukey fence method. Locally weighted regression (LOESS) and segmented regression (SR) were conducted to estimate the threshold of 25(OH)D. Multivariate linear regression was performed to evaluate the associations between PTH concentration and variables including 25(OH)D, gender, age, estimated glomerular filtration rate (EGFR), body mass index (BMI), albumin-adjusted serum calcium (aCa), serum phosphate(P), serum magnesium(Mg), and blood collection season. Z test was adopted to evaluate whether the reference interval should be stratified by determinants such as age and gender. RESULTS A total of 64,979 apparently healthy subjects were recruited in this study, with median (Q1, Q3) 25(OH)D of 45.33 (36.15, 57.50) nmol/L and median (Q1, Q3) PTH of 42.19 (34.24, 52.20) ng/L. The segmented regression determined the 25(OH)D threshold of 55 nmol/L above which PTH would somewhat plateau and of 22 nmol/L below which PTH would rise steeply. Multivariate linear regression suggested that gender, EGFR, and BMI were independently associated with PTH concentrations. The PTH RI was calculated as 22.17-72.72 ng/L for subjects with 25(OH)D ≥ 55 nmol/L with no necessity of stratification according to gender, age, menopausal status nor season. CONCLUSION This study reported 25(OH)D thresholds of vitamin D sufficiency at 55 nmol/L and vitamin D deficiency at 22 nmol/L, and consequently established PTH RIs in subjects with sufficient vitamin D for northern China population for the first time.
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Affiliation(s)
- M Gong
- Department of Laboratory Medicine, Second Medical Center of Chinese PLA General Hospital, National Clinical Research Center for Geriatric Diseases, Beijing, China
| | - K Wang
- Department of Laboratory Medicine, Second Medical Center of Chinese PLA General Hospital, National Clinical Research Center for Geriatric Diseases, Beijing, China
| | - H Sun
- Department of Laboratory Medicine, Second Medical Center of Chinese PLA General Hospital, National Clinical Research Center for Geriatric Diseases, Beijing, China
| | - K Wang
- Department of Laboratory Medicine, Second Medical Center of Chinese PLA General Hospital, National Clinical Research Center for Geriatric Diseases, Beijing, China
| | - Y Zhou
- Department of Laboratory Medicine, Second Medical Center of Chinese PLA General Hospital, National Clinical Research Center for Geriatric Diseases, Beijing, China
| | - Y Cong
- Department of Laboratory Medicine, Second Medical Center of Chinese PLA General Hospital, National Clinical Research Center for Geriatric Diseases, Beijing, China
| | - X Deng
- Department of Laboratory Medicine, Second Medical Center of Chinese PLA General Hospital, National Clinical Research Center for Geriatric Diseases, Beijing, China.
| | - Y Mao
- Department of Laboratory Medicine, Fifth Medical Center, Chinese PLA General Hospital, Beijing, China.
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Ma S, Yu J, Qin X, Liu J. Current status and challenges in establishing reference intervals based on real-world data. Crit Rev Clin Lab Sci 2023; 60:427-441. [PMID: 37038925 DOI: 10.1080/10408363.2023.2195496] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Revised: 01/29/2023] [Accepted: 03/22/2023] [Indexed: 04/12/2023]
Abstract
Reference intervals (RIs) are the cornerstone for evaluation of test results in clinical practice and are invaluable in judging patient health and making clinical decisions. Establishing RIs based on clinical laboratory data is a branch of real-world data mining research. Compared to the traditional direct method, this indirect approach is highly practical, widely applicable, and low-cost. Improving the accuracy of RIs requires not only the collection of sufficient data and the use of correct statistical methods, but also proper stratification of heterogeneous subpopulations. This includes the establishment of age-specific RIs and taking into account other characteristics of reference individuals. Although there are many studies on establishing RIs by indirect methods, it is still very difficult for laboratories to select appropriate statistical methods due to the lack of formal guidelines. This review describes the application of real-world data and an approach for establishing indirect reference intervals (iRIs). We summarize the processes for establishing iRIs using real-world data and analyze the principle and applicable scope of the indirect method model in detail. Moreover, we compare different methods for constructing growth curves to establish age-specific RIs, in hopes of providing laboratories with a reference for establishing specific iRIs and giving new insight into clinical laboratory RI research. (201 words).
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Affiliation(s)
- Sijia Ma
- Department of Laboratory Medicine, Shengjing Hospital of China Medical University, Liaoning Clinical Research Center for Laboratory Medicine, Shenyang, P.R. China
| | - Juntong Yu
- Department of Laboratory Medicine, Shengjing Hospital of China Medical University, Liaoning Clinical Research Center for Laboratory Medicine, Shenyang, P.R. China
| | - Xiaosong Qin
- Department of Laboratory Medicine, Shengjing Hospital of China Medical University, Liaoning Clinical Research Center for Laboratory Medicine, Shenyang, P.R. China
| | - Jianhua Liu
- Department of Laboratory Medicine, Shengjing Hospital of China Medical University, Liaoning Clinical Research Center for Laboratory Medicine, Shenyang, P.R. China
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3
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Application of the Hoffmann, Bhattacharya, nonparametric test, and Q-Q plot methods for establishing reference intervals from laboratory databases. Clin Biochem 2023; 113:9-16. [PMID: 36587756 DOI: 10.1016/j.clinbiochem.2022.12.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Revised: 12/05/2022] [Accepted: 12/27/2022] [Indexed: 12/30/2022]
Abstract
BACKGROUND Reference intervals (RIs) are vital for interpreting laboratory biomarkers and enabling clinical decision-making. Among various RI-estimation methods, we explored the application value of Hoffmann, Bhattacharya, nonparametric test, and Q-Q plot methods for estimating the RI of urea, creatinine, and uric acid (UA). METHOD This cross-sectional study collected patient data recorded between January 2020 and April 2022 at the Chongqing University Central Hospital Laboratory Information System. The RIs of urea, creatinine, and UA levels were established using the Hoffmann, Bhattacharya, nonparametric, and Q-Q plot methods, and RI differences with different computational methods were verified using the reference change value (RCV%) of biological variability. RESULTS We included 16,474 and 123,570 patients in the physical examination and clinical groups, respectively. In the clinical group, differences in the RI upper limit of analytes with the four methods (excluding the Q-Q plot method) were within the permissible RCV% range; only the nonparametric test produced an RI of urea with the lower limit within the permissible RCV% range. In the physical examination group, the relative RI differences among the four methods (excluding the lower limit of RI obtained using the Q-Q plot) were all within the acceptable RCV% range; the relative deviation of the RI of UA with the four methods was within the acceptable RCV% range (excluding the lower RI limit obtained using the Q-Q plot and nonparametric test). CONCLUSION The Hoffmann and Bhattacharya methods may provide reliable RIs for indirect estimations of urea, creatinine, and UA based on laboratory datasets.
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4
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Haeckel R, Adeli K, Jones G, Sikaris K, Wosniok W. Definitions and major prerequisites of direct and indirect approaches for estimating reference limits. Clin Chem Lab Med 2023; 61:402-406. [PMID: 36457149 DOI: 10.1515/cclm-2022-1061] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2022] [Accepted: 11/23/2022] [Indexed: 12/04/2022]
Abstract
Reference intervals are established either by direct or indirect approaches. Whereas the definition of direct is well established, the definition of indirect is still a matter of debate. In this paper, a general definition that covers all indirect models presently in use is proposed. With the upcoming popularity of indirect models, it has become evident that further partitioning strategies are required to minimize the risk of patients' false classifications. With indirect methods, such partitions are much easier to execute than with direct methods. The authors believe that the future of reference interval estimation belongs to indirect models with big data pools either from one laboratory or combined from several regional centres (if necessary). Independent of the approach applied, the quality assurance of the pre-analytical and analytical phase, considering biological variables and other confounding factors, is essential.
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Affiliation(s)
- Rainer Haeckel
- Bremer Zentrum für Laboratoriumsmedizin, Klinikum Bremen Mitte, Bremen, Germany
| | - Khosrow Adeli
- Department of Pediatric Laboratory Medicine, The Hospital for Sick Children, Temerty Faculty of Medicine and University of Toronto, Toronto, ON, Canada
| | - Graham Jones
- SydPath, St Vincent's Hospital, Sydney, NSW, Australia.,Faculty of Medicine, University of NSW, Kensington, Australia
| | | | - Werner Wosniok
- Institut für Statistik, Universität Bremen, Bremen, Germany
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5
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Martinez-Sanchez L, Gabriel-Medina P, Villena-Ortiz Y, García-Fernández AE, Blanco-Grau A, Cobbaert CM, Bravo-Nieto D, Garriga-Edo S, Sanz-Gea C, Gonzalez-Silva G, López-Hellín J, Ferrer-Costa R, Casis E, Rodríguez-Frías F, den Elzen WPJ. Harmonization of indirect reference intervals calculation by the Bhattacharya method. Clin Chem Lab Med 2023; 61:266-274. [PMID: 36395007 DOI: 10.1515/cclm-2022-0439] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Accepted: 11/03/2022] [Indexed: 11/18/2022]
Abstract
OBJECTIVES The aim of this study was to harmonize the criteria for the Bhattacharya indirect method Microsoft Excel Spreadsheet for reference intervals calculation to reduce between-user variability and use these criteria to calculate and evaluate reference intervals for eight analytes in two different years. METHODS Anonymized laboratory test results from outpatients were extracted from January 1st 2018 to December 31st 2019. To assure data quality, we examined the monthly results from an external quality control program. Reference intervals were determined by the Bhattacharya method with the St Vincent's hospital Spreadsheet firstly using original criteria and then using additional harmonized criteria defined in this study. Consensus reference intervals using the additional harmonized criteria were calculated as the mean of four users' lower and upper reference interval results. To further test the operation criteria and robustness of the obtained reference intervals, an external user validated the Spreadsheet procedure. RESULTS The extracted test results for all selected laboratory tests fulfilled the quality criteria and were included in the present study. Differences between users in calculated reference intervals were frequent when using the Spreadsheet. Therefore, additional criteria for the Spreadsheet were proposed and applied by independent users, such as: to set central bin as the mean of all the data, bin size as small as possible, at least three consecutive bins and a high proportion of bins within the curve. CONCLUSIONS The proposed criteria contributed to the harmonization of reference interval calculation between users of the Bhattacharya indirect method Spreadsheet.
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Affiliation(s)
- Luisa Martinez-Sanchez
- Biochemistry Department, Clinical Laboratories, Vall d'Hebron University Hospital, Barcelona, Spain
- Departament de Bioquímica i Biologia Molecular, Universitat Autònoma de Barcelona, Bellaterra, Spain
- Department of Clinical Chemistry and Laboratory Medicine, Leiden University Medical Centre, Leiden, The Netherlands
- Clinical Biochemistry Research Team, Vall d'Hebron Institute of Research (VHIR), Barcelona, Spain
| | - Pablo Gabriel-Medina
- Biochemistry Department, Clinical Laboratories, Vall d'Hebron University Hospital, Barcelona, Spain
- Departament de Bioquímica i Biologia Molecular, Universitat Autònoma de Barcelona, Bellaterra, Spain
- Clinical Biochemistry Research Team, Vall d'Hebron Institute of Research (VHIR), Barcelona, Spain
| | - Yolanda Villena-Ortiz
- Biochemistry Department, Clinical Laboratories, Vall d'Hebron University Hospital, Barcelona, Spain
- Departament de Bioquímica i Biologia Molecular, Universitat Autònoma de Barcelona, Bellaterra, Spain
- Clinical Biochemistry Research Team, Vall d'Hebron Institute of Research (VHIR), Barcelona, Spain
| | - Alba E García-Fernández
- Biochemistry Department, Clinical Laboratories, Vall d'Hebron University Hospital, Barcelona, Spain
- Clinical Biochemistry Research Team, Vall d'Hebron Institute of Research (VHIR), Barcelona, Spain
| | - Albert Blanco-Grau
- Biochemistry Department, Clinical Laboratories, Vall d'Hebron University Hospital, Barcelona, Spain
- Departament de Bioquímica i Biologia Molecular, Universitat Autònoma de Barcelona, Bellaterra, Spain
- Clinical Biochemistry Research Team, Vall d'Hebron Institute of Research (VHIR), Barcelona, Spain
| | - Christa M Cobbaert
- Department of Clinical Chemistry and Laboratory Medicine, Leiden University Medical Centre, Leiden, The Netherlands
| | - Daniel Bravo-Nieto
- Biochemistry Department, Clinical Laboratories, Vall d'Hebron University Hospital, Barcelona, Spain
- Clinical Biochemistry Research Team, Vall d'Hebron Institute of Research (VHIR), Barcelona, Spain
| | - Sarai Garriga-Edo
- Biochemistry Department, Clinical Laboratories, Vall d'Hebron University Hospital, Barcelona, Spain
- Clinical Biochemistry Research Team, Vall d'Hebron Institute of Research (VHIR), Barcelona, Spain
| | - Clara Sanz-Gea
- Biochemistry Department, Clinical Laboratories, Vall d'Hebron University Hospital, Barcelona, Spain
- Clinical Biochemistry Research Team, Vall d'Hebron Institute of Research (VHIR), Barcelona, Spain
| | - Gonzalo Gonzalez-Silva
- Biochemistry Department, Clinical Laboratories, Vall d'Hebron University Hospital, Barcelona, Spain
- Clinical Biochemistry Research Team, Vall d'Hebron Institute of Research (VHIR), Barcelona, Spain
| | - Joan López-Hellín
- Biochemistry Department, Clinical Laboratories, Vall d'Hebron University Hospital, Barcelona, Spain
- Clinical Biochemistry Research Team, Vall d'Hebron Institute of Research (VHIR), Barcelona, Spain
| | - Roser Ferrer-Costa
- Biochemistry Department, Clinical Laboratories, Vall d'Hebron University Hospital, Barcelona, Spain
- Clinical Biochemistry Research Team, Vall d'Hebron Institute of Research (VHIR), Barcelona, Spain
| | - Ernesto Casis
- Clinical Laboratories, Vall d'Hebron University Hospital, Barcelona, Spain
| | - Francisco Rodríguez-Frías
- Biochemistry Department, Clinical Laboratories, Vall d'Hebron University Hospital, Barcelona, Spain
- Departament de Bioquímica i Biologia Molecular, Universitat Autònoma de Barcelona, Bellaterra, Spain
- Clinical Biochemistry Research Team, Vall d'Hebron Institute of Research (VHIR), Barcelona, Spain
| | - Wendy P J den Elzen
- Clinical Biochemistry Research Team, Vall d'Hebron Institute of Research (VHIR), Barcelona, Spain
- Department of Clinical Chemistry, Amsterdam UMC, University of Amsterdam, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
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Zaninotto M, Graziani MS, Plebani M. The harmonization issue in laboratory medicine: the commitment of CCLM. Clin Chem Lab Med 2022; 61:721-731. [PMID: 36383396 DOI: 10.1515/cclm-2022-1111] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Accepted: 11/03/2022] [Indexed: 11/18/2022]
Abstract
Abstract
The analytical quality of the clinical laboratory results has shown a significant improvement over the past decades, thanks to the joint efforts of different stakeholders, while the comparability among the results produced by different laboratories and methods still presents some critical issues. During these years, Clinical Chemistry and Laboratory Medicine (CCLM) published several papers on the harmonization issue over all steps in the Total Testing Process, training an important number of laboratory professionals in evaluating and monitoring all the criticisms inherent to the pre-analytical, as well as analytical and post analytical phases: from the consensus statement on the most informative testing in emergency setting, to the prevention and detection of hemolysis or to patients identification and tube labeling procedures, as far as to different approaches to harmonize hormones measurements or to describe new reference methods or to harmonize the laboratory report. During these years the commitment of the journal, devoted to the harmonization processes has allowed to improve the awareness on the topic and to provide specific instruments to monitor the rate of errors and to improve patients safety.
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7
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Coskun A, Sandberg S, Unsal I, Serteser M, Aarsand AK. Personalized reference intervals: from theory to practice. Crit Rev Clin Lab Sci 2022; 59:501-516. [PMID: 35579539 DOI: 10.1080/10408363.2022.2070905] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
Using laboratory test results for diagnosis and monitoring requires a reliable reference to which the results can be compared. Currently, most reference data is derived from the population, and patients in this context are considered members of a population group rather than individuals. However, such reference data has limitations when used as the reference for an individual. A patient's test results preferably should be compared with their own, individualized reference intervals (RI), i.e. a personalized RI (prRI).The prRI is based on the homeostatic model and can be calculated using an individual's previous test results obtained in a steady-state situation and estimates of analytical (CVA) and biological variation (BV). BV used to calculate the prRI can be obtained from the population (within-subject biological variation, CVI) or an individual's own data (within-person biological variation, CVP). Statistically, the prediction interval provides a useful tool to calculate the interval (i.e. prRI) for future observation based on previous measurements. With the development of information technology, the data of millions of patients is stored and processed in medical laboratories, allowing the implementation of personalized laboratory medicine. PrRI for each individual should be made available as part of the laboratory information system and should be continually updated as new test results become available.In this review, we summarize the limitations of population-based RI for the diagnosis and monitoring of disease, provide an outline of the prRI concept and different approaches to its determination, including statistical considerations for deriving prRI, and discuss aspects which must be further investigated prior to implementation of prRI in clinical practice.
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Affiliation(s)
- Abdurrahman Coskun
- Acibadem Labmed Clinical Laboratories, Istanbul, Turkey.,Department of Medical Biochemistry, School of Medicine, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey
| | - Sverre Sandberg
- Norwegian Organization for Quality Improvement of Laboratory Examinations (Noklus), Haraldsplass Deaconess Hospital, Bergen, Norway.,Norwegian Porphyria Centre and Department of Medical Biochemistry and Pharmacology, Haukeland University Hospital, Bergen, Norway.,Department of Global Health and Primary Care, Faculty of Medicine and Dentistry, University of Bergen, Bergen, Norway
| | - Ibrahim Unsal
- Acibadem Labmed Clinical Laboratories, Istanbul, Turkey
| | - Mustafa Serteser
- Acibadem Labmed Clinical Laboratories, Istanbul, Turkey.,Department of Medical Biochemistry, School of Medicine, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey
| | - Aasne K Aarsand
- Norwegian Organization for Quality Improvement of Laboratory Examinations (Noklus), Haraldsplass Deaconess Hospital, Bergen, Norway.,Norwegian Porphyria Centre and Department of Medical Biochemistry and Pharmacology, Haukeland University Hospital, Bergen, Norway
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8
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Kim T, Choi H, Lee SM. Parametric and non-parametric estimation of reference intervals for routine laboratory tests: an analysis of health check-up data for 260 889 young men in the South Korean military. BMJ Open 2022; 12:e062617. [PMID: 35879016 PMCID: PMC9328105 DOI: 10.1136/bmjopen-2022-062617] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Accepted: 07/04/2022] [Indexed: 11/03/2022] Open
Abstract
OBJECTIVES Determination of reference intervals (RIs) using big data faces several obstacles due to heterogeneity in analysers, period and ethnicity. The present study aimed to establish the RIs for routine common blood count (CBC) and biochemistry laboratory tests in homogeneous, healthy, male Korean soldiers in their 20s using a large health check-up data set, comparing parametric and non-parametric estimation. DESIGN A multicentre, cross-sectional study. SETTING Seven armed forces hospitals in South Korea. PARTICIPANTS A total of 609 649 men underwent health examination when promoted to corporal between January 2015 and September 2021. 260 889 eligible individuals aged 20-25 were included in the analysis. MAIN OUTCOMES AND MEASURES The RIs were established by parametric and non-parametric methods. In the parametric approach, maximum likelihood estimation was applied to measure the Box-Cox transformation parameter and the values at the 2.5th and 97.5th percentiles were recalculated. The non-parametric approach adopted the Tukey's exclusion test and the values at the 2.5th and 97.5th percentiles were obtained. Classification by body mass index was also performed. RESULTS The obtained RIs for haematology parameters were comparable between devices. If the values followed a Gaussian distribution, parametric and non-parametric methods were well matched for haematology and biochemical markers. When the values were right-skewed, the upper limits were higher with parametric than with non-parametric methods. Participants with obesity showed higher RIs for CBC, some liver function tests and some lipid profiles than participants without obesity. CONCLUSIONS Using data from healthy, male Korean soldiers in their 20s, we proposed the RIs for CBC and biochemical parameters, comparing parametric and non-parametric estimation. As such approaches based on large data sets become more prevalent, further studies are needed to discriminate eligible individuals and determine RIs in an extrapolated sample.
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Affiliation(s)
- Taeyun Kim
- Internal Medicine, The Armed Forces Goyang Hospital, Goyang, Republic of Korea
| | - Hyunji Choi
- Laboratory Medicine, Pusan National University Yangsan Hospital, Yangsan, Republic of Korea
- Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Yangsan, Gyeongnam, Republic of Korea
| | - Sun Min Lee
- Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Yangsan, Gyeongnam, Republic of Korea
- Laboratory Medicine, Pusan National University School of Medicine, Busan, Republic of Korea
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9
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Kooijmans ECM, van der Pal HJH, Pluijm SMF, van der Heiden-van der Loo M, Kremer LCM, Bresters D, van Dulmen-den Broeder E, van den Heuvel-Eibrink MM, Loonen JJ, Louwerens M, Neggers SJC, Ronckers C, Tissing WJE, de Vries ACH, Kaspers GJL, Bökenkamp A, Veening MA. Long-Term Tubular Dysfunction in Childhood Cancer Survivors; DCCSS-LATER 2 Renal Study. Cancers (Basel) 2022; 14:2754. [PMID: 35681735 PMCID: PMC9179377 DOI: 10.3390/cancers14112754] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Revised: 05/13/2022] [Accepted: 05/17/2022] [Indexed: 11/29/2022] Open
Abstract
The aim of this nationwide cross-sectional cohort study was to determine the prevalence of and risk factors for tubular dysfunction in childhood cancer survivors (CCS). In the DCCSS-LATER 2 Renal study, 1024 CCS (≥5 years after diagnosis), aged ≥ 18 years at study, treated between 1963 and 2001 with potentially nephrotoxic therapy (i.e., nephrectomy, abdominal radiotherapy, total body irradiation, cisplatin, carboplatin, ifosfamide, high-dose cyclophosphamide, or hematopoietic stem cell transplantation) participated, and 500 age- and sex-matched participants from Lifelines acted as controls. Tubular electrolyte loss was defined as low serum levels (magnesium < 0.7 mmol/L, phosphate < 0.7 mmol/L and potassium < 3.6 mmol/L) with increased renal excretion or supplementation. A α1-microglobulin:creatinine ratio > 1.7 mg/mmol was considered as low-molecular weight proteinuria (LMWP). Multivariable risk analyses were performed. After median 25.5 years follow-up, overall prevalence of electrolyte losses in CCS (magnesium 5.6%, potassium 4.5%, phosphate 5.5%) was not higher compared to controls. LMWP was more prevalent (CCS 20.1% versus controls 0.4%). LMWP and magnesium loss were associated with glomerular dysfunction. Ifosfamide was associated with potassium loss, phosphate loss (with cumulative dose > 42 g/m2) and LMWP. Cisplatin was associated with magnesium loss and a cumulative dose > 500 mg/m2 with potassium and phosphate loss. Carboplatin cumulative dose > 2800 mg/m2 was associated with potassium loss. In conclusion, long-term tubular dysfunction is infrequent. Yet, ifosfamide, cisplatin and carboplatin are risk factors.
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Affiliation(s)
- Esmee C. M. Kooijmans
- Department of Pediatric Oncology, Emma Children’s Hospital, Amsterdam UMC, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands; (E.v.D.-d.B.); (G.J.L.K.); (M.A.V.)
- Princess Máxima Center for Pediatric Oncology, 3584 CS Utrecht, The Netherlands; (H.J.H.v.d.P.); (S.M.F.P.); (M.v.d.H.-v.d.L.); (L.C.M.K.); (D.B.); (M.M.v.d.H.-E.); (C.R.); (W.J.E.T.); (A.C.H.d.V.)
| | - Helena J. H. van der Pal
- Princess Máxima Center for Pediatric Oncology, 3584 CS Utrecht, The Netherlands; (H.J.H.v.d.P.); (S.M.F.P.); (M.v.d.H.-v.d.L.); (L.C.M.K.); (D.B.); (M.M.v.d.H.-E.); (C.R.); (W.J.E.T.); (A.C.H.d.V.)
| | - Saskia M. F. Pluijm
- Princess Máxima Center for Pediatric Oncology, 3584 CS Utrecht, The Netherlands; (H.J.H.v.d.P.); (S.M.F.P.); (M.v.d.H.-v.d.L.); (L.C.M.K.); (D.B.); (M.M.v.d.H.-E.); (C.R.); (W.J.E.T.); (A.C.H.d.V.)
| | - Margriet van der Heiden-van der Loo
- Princess Máxima Center for Pediatric Oncology, 3584 CS Utrecht, The Netherlands; (H.J.H.v.d.P.); (S.M.F.P.); (M.v.d.H.-v.d.L.); (L.C.M.K.); (D.B.); (M.M.v.d.H.-E.); (C.R.); (W.J.E.T.); (A.C.H.d.V.)
- Dutch Childhood Oncology Group, 3584 CS Utrecht, The Netherlands
| | - Leontien C. M. Kremer
- Princess Máxima Center for Pediatric Oncology, 3584 CS Utrecht, The Netherlands; (H.J.H.v.d.P.); (S.M.F.P.); (M.v.d.H.-v.d.L.); (L.C.M.K.); (D.B.); (M.M.v.d.H.-E.); (C.R.); (W.J.E.T.); (A.C.H.d.V.)
- Wilhelmina Children’s Hospital, University Medical Center Utrecht, 3584 EA Utrecht, The Netherlands
- Deparmtnet of Pediatric Oncology, Emma Children’s Hospital, Amsterdam UMC, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands
| | - Dorine Bresters
- Princess Máxima Center for Pediatric Oncology, 3584 CS Utrecht, The Netherlands; (H.J.H.v.d.P.); (S.M.F.P.); (M.v.d.H.-v.d.L.); (L.C.M.K.); (D.B.); (M.M.v.d.H.-E.); (C.R.); (W.J.E.T.); (A.C.H.d.V.)
- Willem Alexander Children’s Hospital, Leiden University Medical Center, 2333 ZA Leiden, The Netherlands
| | - Eline van Dulmen-den Broeder
- Department of Pediatric Oncology, Emma Children’s Hospital, Amsterdam UMC, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands; (E.v.D.-d.B.); (G.J.L.K.); (M.A.V.)
| | - Marry M. van den Heuvel-Eibrink
- Princess Máxima Center for Pediatric Oncology, 3584 CS Utrecht, The Netherlands; (H.J.H.v.d.P.); (S.M.F.P.); (M.v.d.H.-v.d.L.); (L.C.M.K.); (D.B.); (M.M.v.d.H.-E.); (C.R.); (W.J.E.T.); (A.C.H.d.V.)
- Department of Pediatric Oncology, Sophia Children’s Hospital, Erasmus Medical Center, 3015 GD Rotterdam, The Netherlands
| | - Jacqueline J. Loonen
- Department of Hematology, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands;
| | - Marloes Louwerens
- Department of Internal Medicine, Leiden University Medical Center, 2333 ZA Leiden, The Netherlands;
| | - Sebastian J. C. Neggers
- Department of Internal Medicine, Erasmus Medical Center, 3015 GD Rotterdam, The Netherlands;
| | - Cécile Ronckers
- Princess Máxima Center for Pediatric Oncology, 3584 CS Utrecht, The Netherlands; (H.J.H.v.d.P.); (S.M.F.P.); (M.v.d.H.-v.d.L.); (L.C.M.K.); (D.B.); (M.M.v.d.H.-E.); (C.R.); (W.J.E.T.); (A.C.H.d.V.)
| | - Wim J. E. Tissing
- Princess Máxima Center for Pediatric Oncology, 3584 CS Utrecht, The Netherlands; (H.J.H.v.d.P.); (S.M.F.P.); (M.v.d.H.-v.d.L.); (L.C.M.K.); (D.B.); (M.M.v.d.H.-E.); (C.R.); (W.J.E.T.); (A.C.H.d.V.)
- Department of Pediatric Oncology, University of Groningen, University Medical Center Groningen, 8713 GZ Groningen, The Netherlands
| | - Andrica C. H. de Vries
- Princess Máxima Center for Pediatric Oncology, 3584 CS Utrecht, The Netherlands; (H.J.H.v.d.P.); (S.M.F.P.); (M.v.d.H.-v.d.L.); (L.C.M.K.); (D.B.); (M.M.v.d.H.-E.); (C.R.); (W.J.E.T.); (A.C.H.d.V.)
- Department of Pediatric Oncology, Sophia Children’s Hospital, Erasmus Medical Center, 3015 GD Rotterdam, The Netherlands
| | - Gertjan J. L. Kaspers
- Department of Pediatric Oncology, Emma Children’s Hospital, Amsterdam UMC, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands; (E.v.D.-d.B.); (G.J.L.K.); (M.A.V.)
- Princess Máxima Center for Pediatric Oncology, 3584 CS Utrecht, The Netherlands; (H.J.H.v.d.P.); (S.M.F.P.); (M.v.d.H.-v.d.L.); (L.C.M.K.); (D.B.); (M.M.v.d.H.-E.); (C.R.); (W.J.E.T.); (A.C.H.d.V.)
| | - Arend Bökenkamp
- Department of Pediatric Nephrology, Emma Children’s Hospital, Amsterdam UMC, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands;
| | - Margreet A. Veening
- Department of Pediatric Oncology, Emma Children’s Hospital, Amsterdam UMC, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands; (E.v.D.-d.B.); (G.J.L.K.); (M.A.V.)
- Princess Máxima Center for Pediatric Oncology, 3584 CS Utrecht, The Netherlands; (H.J.H.v.d.P.); (S.M.F.P.); (M.v.d.H.-v.d.L.); (L.C.M.K.); (D.B.); (M.M.v.d.H.-E.); (C.R.); (W.J.E.T.); (A.C.H.d.V.)
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10
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Martinez-Sanchez L, Cobbaert CM, Noordam R, Brouwer N, Blanco-Grau A, Villena-Ortiz Y, Thelen M, Ferrer-Costa R, Casis E, Rodríguez-Frias F, den Elzen WPJ. Indirect determination of biochemistry reference intervals using outpatient data. PLoS One 2022; 17:e0268522. [PMID: 35588100 PMCID: PMC9119462 DOI: 10.1371/journal.pone.0268522] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2021] [Accepted: 05/02/2022] [Indexed: 12/22/2022] Open
Abstract
The aim of this study was to determine reference intervals in an outpatient population from Vall d'Hebron laboratory using an indirect approach previously described in a Dutch population (NUMBER project). We used anonymized test results from individuals visiting general practitioners and analysed during 2018. Analytical quality was assured by EQA performance, daily average monitoring and by assessing longitudinal accuracy between 2018 and 2020 (using trueness verifiers from Dutch EQA). Per test, outliers by biochemically related tests were excluded, data were transformed to a normal distribution (if necessary) and means and standard deviations were calculated, stratified by age and sex. In addition, the reference limit estimator method was also used to calculate reference intervals using the same dataset. Finally, for standardized tests reference intervals obtained were compared with the published NUMBER results. Reference intervals were calculated using data from 509,408 clinical requests. For biochemical tests following a normal distribution, similar reference intervals were found between Vall d'Hebron and the Dutch study. For creatinine and urea, reference intervals increased with age in both populations. The upper limits of Gamma-glutamyl transferase were markedly higher in the Dutch study compared to Vall d'Hebron results. Creatine kinase and uric acid reference intervals were higher in both populations compared to conventional reference intervals. Medical test results following a normal distribution showed comparable and consistent reference intervals between studies. Therefore a simple indirect method is a feasible and cost-efficient approach for calculating reference intervals. Yet, for generating standardized calculated reference intervals that are traceable to higher order materials and methods, efforts should also focus on test standardization and bias assessment using commutable trueness verifiers.
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Affiliation(s)
- Luisa Martinez-Sanchez
- Clinical Laboratories, Biochemistry Department, Vall d’Hebron University Hospital, Barcelona, Spain
- Department of Clinical Chemistry and Laboratory Medicine, Leiden University Medical Centre, Leiden, The Netherlands
- Departament de Bioquímica i Biologia Molecular, Universitat Autònoma de Barcelona, Bellaterra, Spain
| | - Christa M. Cobbaert
- Department of Clinical Chemistry and Laboratory Medicine, Leiden University Medical Centre, Leiden, The Netherlands
| | - Raymond Noordam
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands
| | - Nannette Brouwer
- Diagnost-IQ, Expert Centre for Clinical Chemistry, Purmerend, The Netherlands
| | - Albert Blanco-Grau
- Clinical Laboratories, Biochemistry Department, Vall d’Hebron University Hospital, Barcelona, Spain
| | - Yolanda Villena-Ortiz
- Clinical Laboratories, Biochemistry Department, Vall d’Hebron University Hospital, Barcelona, Spain
- Departament de Bioquímica i Biologia Molecular, Universitat Autònoma de Barcelona, Bellaterra, Spain
| | - Marc Thelen
- Laboratory for Clinical Chemistry and Hematology, Amphia, Breda, The Netherlands
- Stichting Kwaliteitsbewaking Medische Laboratoriumdiagnostiek, Nijmegen, The Netherlands
- Department of Laboratory Medicine, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Roser Ferrer-Costa
- Clinical Laboratories, Biochemistry Department, Vall d’Hebron University Hospital, Barcelona, Spain
| | - Ernesto Casis
- Clinical Laboratories, Biochemistry Department, Vall d’Hebron University Hospital, Barcelona, Spain
| | - Francisco Rodríguez-Frias
- Clinical Laboratories, Biochemistry Department, Vall d’Hebron University Hospital, Barcelona, Spain
- Departament de Bioquímica i Biologia Molecular, Universitat Autònoma de Barcelona, Bellaterra, Spain
| | - Wendy P. J. den Elzen
- Clinical Laboratories, Biochemistry Department, Vall d’Hebron University Hospital, Barcelona, Spain
- Department of Clinical Chemistry and Laboratory Medicine, Leiden University Medical Centre, Leiden, The Netherlands
- Atalmedial Diagnostics Centre, Amsterdam, The Netherlands
- Department of Clinical Chemistry, Amsterdam Public Health research institute, Amsterdam UMC, Amsterdam, The Netherlands
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11
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L van Pelt J, Klatte S, Hwandih T, Barcaru A, Riphagen IJ, Linssen J, Bakker SJL. Reference intervals for Sysmex XN hematological parameters as assessed in the Dutch Lifelines cohort. Clin Chem Lab Med 2022; 60:907-920. [PMID: 35487594 DOI: 10.1515/cclm-2022-0094] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2022] [Accepted: 03/29/2022] [Indexed: 02/05/2023]
Abstract
OBJECTIVES Our aim was to derive reference intervals for all Sysmex XN hematology analyzer parameters. The rationale behind the study was the lack of reference intervals for the XN analyzer cell population data (CPD) and functional parameters. METHODS Fresh fasting blood samples from 18,484 participants in the Dutch Lifelines study were analyzed using two automated XN analyzers. Structured health questionnaire data were used to select a subgroup of 15,803 apparently healthy individuals for inclusion in the reference population. The Latent Abnormal Values Exclusion (LAVE) approach was used to reduce the influence of latent diseases in the reference population on the resulting reference intervals. We applied analysis of variance to judge the need for partitioning of the reference intervals by sex or age. RESULTS We report reference intervals for 105 XN analyzer hematological parameters with and without applying LAVE. Sex-related partitioning was required for red blood cells, (RBC, RBC-O), hemoglobin (HGB, HGB-O), hematocrit (HCT), mean corpuscular hemoglobin concentration (MCHC), reticulocyte production index (RPI), and side scattered light intensity of the red blood cell population in the RET channel (RBC-Z). Partitioning for age was not warranted. Body mass index (BMI) and smoking had moderate influence on a minority of the parameters. CONCLUSIONS We provide reference intervals for all Sysmex XN analyzer routine, CPD and functional parameters, using a direct approach in a large cohort in the Netherlands.
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Affiliation(s)
- Joost L van Pelt
- Department of Laboratory Medicine, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Stefanie Klatte
- Medical Science Department, Sysmex Europe GmbH, Norderstedt, Germany
| | - Talent Hwandih
- Medical Science Department, Sysmex Europe GmbH, Norderstedt, Germany
| | - Andrei Barcaru
- Department of Laboratory Medicine, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Ineke J Riphagen
- Department of Laboratory Medicine, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Jo Linssen
- Medical Science Department, Sysmex Europe GmbH, Norderstedt, Germany
| | - Stephan J L Bakker
- Department of Internal Medicine, Division of Nephrology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
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12
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Candel BGJ, Khoudja J, Gaakeer MI, Ter Avest E, Sir Ö, Lameijer H, Hessels RAPA, Reijnen R, van Zwet E, de Jonge E, de Groot B. Age-adjusted interpretation of biomarkers of renal function and homeostasis, inflammation, and circulation in Emergency Department patients. Sci Rep 2022; 12:1556. [PMID: 35091652 PMCID: PMC8799641 DOI: 10.1038/s41598-022-05485-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Accepted: 01/12/2022] [Indexed: 12/03/2022] Open
Abstract
Appropriate interpretation of blood tests is important for risk stratification and guidelines used in the Emergency Department (ED) (such as SIRS or CURB-65). The impact of abnormal blood test values on mortality may change with increasing age due to (patho)-physiologic changes. The aim of this study was therefore to assess the effect of age on the case-mix adjusted association between biomarkers of renal function and homeostasis, inflammation and circulation and in-hospital mortality. This observational multi-center cohort study has used the Netherlands Emergency department Evaluation Database (NEED), including all consecutive ED patients ≥ 18 years of three hospitals. A generalized additive logistic regression model was used to visualize the association between in-hospital mortality, age and five blood tests (creatinine, sodium, leukocytes, C-reactive Protein, and hemoglobin). Multivariable logistic regression analyses were used to assess the association between the number of abnormal blood test values and mortality per age category (18-50; 51-65; 66-80; > 80 years). Of the 94,974 included patients, 2550 (2.7%) patients died in-hospital. Mortality increased gradually for C-reactive Protein (CRP), and had a U-shaped association for creatinine, sodium, leukocytes, and hemoglobin. Age significantly affected the associations of all studied blood tests except in leukocytes. In addition, with increasing age categories, case-mix adjusted mortality increased with the number of abnormal blood tests. In summary, the association between blood tests and (adjusted) mortality depends on age. Mortality increases gradually or in a U-shaped manner with increasing blood test values. Age-adjusted numerical scores may improve risk stratification. Our results have implications for interpretation of blood tests and their use in risk stratification tools and acute care guidelines.Trial registration number Netherlands Trial Register (NTR) NL8422, 03/2020.
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Affiliation(s)
- Bart G J Candel
- Department of Emergency Medicine, Leiden University Medical Center, Albinusdreef 2, 2300 RC, Leiden, The Netherlands.
- Department of Emergency Medicine, Máxima Medical Center, De Run 4600, 5504 DB, Veldhoven, The Netherlands.
| | - Jamèl Khoudja
- Department of Emergency Medicine, Leiden University Medical Center, Albinusdreef 2, 2300 RC, Leiden, The Netherlands
| | - Menno I Gaakeer
- Department of Emergency Medicine, Admiraal de Ruyter Hospital, 's-Gravenpolderseweg 114, 4462 RA, Goes, The Netherlands
| | - Ewoud Ter Avest
- Department of Emergency Medicine, University Medical Center Groningen, Hanzeplein1, 9713 GZ, Groningen, The Netherlands
| | - Özcan Sir
- Department of Emergency Medicine, Radboud University Medical Center, Houtlaan 4, 6525 XZ, Nijmegen, The Netherlands
| | - Heleen Lameijer
- Department of Emergency Medicine, Medical Center Leeuwarden, Henri Dunantweg 2, 8934 AD, Leeuwarden, The Netherlands
| | - Roger A P A Hessels
- Department of Emergency Medicine, Elisabeth-TweeSteden Hospital, Doctor Deelenlaan 5, 5042 AD, Tilburg, The Netherlands
| | - Resi Reijnen
- Department of Emergency Medicine, Haaglanden Medical Center, Lijnbaan 32, 2512 VA, The Hague, The Netherlands
| | - Erik van Zwet
- Department of Biostatistics, Leiden University Medical Center, Albinusdreef 2, 2300 RC, Leiden, The Netherlands
| | - Evert de Jonge
- Department of Intensive Care Medicine, Leiden University Medical Center, Albinusdreef 2, 2300 RC, Leiden, The Netherlands
| | - Bas de Groot
- Department of Emergency Medicine, Leiden University Medical Center, Albinusdreef 2, 2300 RC, Leiden, The Netherlands
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13
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Jassam N. Population-specific adjusted calcium equations. Ann Clin Biochem 2021; 59:383-384. [PMID: 34727515 DOI: 10.1177/00045632211051181] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Affiliation(s)
- Nuthar Jassam
- Department of Clinical Biochemistry, 3746Harrogate and District NHS Foundation Trust, Harrogate, UK
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14
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Fleming JK, Katayev A, Moorer CM, Ward-Jeffries DA, Terrell CL. Development of nation-wide reference intervals using an indirect method and harmonized assays. Clin Biochem 2021; 99:20-59. [PMID: 34626611 DOI: 10.1016/j.clinbiochem.2021.10.001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Revised: 09/20/2021] [Accepted: 10/04/2021] [Indexed: 11/28/2022]
Abstract
OBJECTIVES For many years, clinical laboratories have either verified or estimated reference intervals (RI) for laboratory tests. Those calculations have largely been performed by direct sampling analysis of ostensibly healthy individuals or by post-analysis biochemical screening. Recently however, indirect calculations have come to the forefront as an IFCC endorsed method by using normal and abnormal patient data. DESIGN AND METHODS Using a large database of patient test results from Laboratory Corporation of America, age and gender based RIs, inclusive of neonatal, pediatric, and geriatric populations, were determined using a modified indirect method of Hoffmann, and represent a diverse population distributed across the United States from a nation-wide system of laboratories and is unbiased with respect to age, gender, race or geography. RESULTS The tabulation of RIs using big data by an indirect method represent 72 M patient test results. The table includes 266 individual analytes consisting of approximately 2,700 age categories, including tests across multiple medical disciplines. CONCLUSIONS To our knowledge, this is the largest collection of RIs that were calculated by an indirect method representing clinical chemistry, endocrinology, coagulation, and hematology analytes that have been derived with very powerful "Ns" for each age bracket. This process provides more robust RIs and allows for the determination of pediatric and geriatric RIs that would otherwise be difficult to obtain using traditional direct RI determinations.
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Affiliation(s)
- James K Fleming
- Laboratory Corporation of America,® Holdings (retired), USA.
| | - Alex Katayev
- Laboratory Corporation of America,® Holdings, USA
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15
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Minieri M, Leoni BD, Bellincampi L, Bajo D, Agnoli A, De Angelis AM, Pieri M, Equitani F, Rossi V, Valente F, Pignalosa S, Terrinoni A, Bernardini S. Serum iPTH range in a reference population: From an integrated approach to vitamin D prevalence impact evaluation. Clin Chim Acta 2021; 521:1-8. [PMID: 34111419 DOI: 10.1016/j.cca.2021.06.004] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Revised: 05/31/2021] [Accepted: 06/01/2021] [Indexed: 01/24/2023]
Abstract
BACKGROUND The iPTH upper reference limit (URL) reported by our laboratory provider (Abbott Laboratories) at Tor Vergata University Hospital was evaluated by internal verification procedures as not representative of our population and resulting as underestimated. In this study, a new reference interval has been investigated and established by comparing a direct and an indirect method based on a statistical reduction from results stored in the laboratory database. METHODS For reference interval calculation from the healthy population, we analyzed a cohort of 100 blood donors (84% males and 16% females) screened with no bone-related and malabsorption diseases. We analyzed a cohort of 495 patients retrieved from more than 800 iPTH results by excluding subjects with pathological measurement for calcium, phosphorus, and creatinine for the reference interval evaluation. Patients with vitamin D results were included in the analysis. Vitamin D sufficiency status during the period from January to September 2020 was also evaluated by investigating 3,050 patients. RESULTS The iPTH reference interval of a healthy blood donor population was measured as 25.2-109.1 pg/mL (2.7-11.6 pmol/L) at 2.5 and 97.5 distribution percentile. The iPTH reference interval from data stored in the laboratory database was 19.3-112.5 pg/mL (2.0-11.9 pmol/L). Furthermore, 60% of the whole population had prevalently insufficient vitamin D concentration (<30 ng/dL; <75 nmol/L). The impact of vitamin D concentration on the iPTH reference interval was measured for insufficient vitamin D (<30 ng/dL; <75 nmol/L) as 15.2-127.7 pg/mL (1.6-13.5 pmol/L), desirable vitamin D (30-40 ng/ml; 75-100 nmol/L) as 25.6-105 pg/mL (2.7-10.7 pmol/L) and optimal vitamin D (>40 ng/ml; >100 nmol/L) as 26.2-89.2 pg/mL (2.8-9.4 pmol/L), respectively. CONCLUSIONS The URL reported in manufacturer datasheets likely refers to a normal population with non-pathological vitamin D levels. On the contrary, the considered population was mostly vitamin D insufficient, resulting in a URL shift. On this basis, we suggest describing in medical reports the iPTH range for vitamin D deficiency for diagnosis of primary hyperparathyroidism even when a specific vitamin D request is lacking. On the other hand, reporting optimal vitamin D-based iPTH reference interval could be clinically relevant in supplemented patients as a marker of treatment efficacy.
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Affiliation(s)
- Marilena Minieri
- Department of Experimental Medicine, University of Rome Tor Vergata, Rome, Italy; Unit of Laboratory Medicine, Tor Vergata University Hospital, Rome, Italy.
| | | | | | - Daniela Bajo
- Unit of Laboratory Medicine, Tor Vergata University Hospital, Rome, Italy
| | - Alessia Agnoli
- Unit of Laboratory Medicine, Tor Vergata University Hospital, Rome, Italy
| | | | - Massimo Pieri
- Department of Experimental Medicine, University of Rome Tor Vergata, Rome, Italy
| | - Francesco Equitani
- Department of Transfusion Medicine, Santa Maria Goretti Hospital, AUSL Latina, Italy
| | | | | | | | - Alessandro Terrinoni
- Department of Experimental Medicine, University of Rome Tor Vergata, Rome, Italy
| | - Sergio Bernardini
- Department of Experimental Medicine, University of Rome Tor Vergata, Rome, Italy; Unit of Laboratory Medicine, Tor Vergata University Hospital, Rome, Italy
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16
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Haeckel R, Wosniok W. The importance of correct stratifications when comparing directly and indirectly estimated reference intervals. Clin Chem Lab Med 2021; 59:cclm-2021-0353. [PMID: 34049430 DOI: 10.1515/cclm-2021-0353] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2021] [Accepted: 05/17/2021] [Indexed: 11/15/2022]
Abstract
OBJECTIVES There are generally two major reasons for the comparison of reference intervals (RIs): when externally determined RIs (from the literature or provided by a manufacturer) are compared with presently used intra-laboratory RIs and when indirectly estimated RIs are compared with directly established RIs. Discrepancies within these comparisons may occur for two reasons: 1. the pre-analytical and/or analytical conditions do not agree and/or 2. biological variables influencing the establishment of RIs have not been considered adequately. If directly and indirectly estimated reference intervals (RIs) are compared with each other, they very often agree. Sometimes, however, a comparison may differ, with the reason for any discrepancy not being further studied. A major reason for differences in the comparison of RIs is that the requirement for stratification has been neglected. METHODS The present report outlines the consequences to RI comparison if stratification is neglected during RI determination with the main variables affecting RIs being sex and age. Alanine aminotransferase was chosen as an example in which the RIs depend on both these factors. RESULTS Both direct and indirect approaches lead to erroneous RIs if stratification for variables which are known to affect the estimation of RIs is not performed adequately. However, failing to include a required stratification in procedures for directly determined RIs affects the outcome in a different way to indirectly determined RIs. CONCLUSIONS The resulting difference between direct and indirect RIs is often misinterpreted as an incorrect RI estimation of the indirect method.
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Affiliation(s)
- Rainer Haeckel
- Bremer Zentrum für Laboratoriumsmedizin, Klinikum Bremen Mitte, 28305Bremen, Germany
| | - Werner Wosniok
- Institut für Statistik, Universität Bremen, Bremen, Germany
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17
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Martinez-Sanchez L, Marques-Garcia F, Ozarda Y, Blanco A, Brouwer N, Canalias F, Cobbaert C, Thelen M, den Elzen W. Big data and reference intervals: rationale, current practices, harmonization and standardization prerequisites and future perspectives of indirect determination of reference intervals using routine data. ADVANCES IN LABORATORY MEDICINE 2021; 2:9-25. [PMID: 37359198 PMCID: PMC10197285 DOI: 10.1515/almed-2020-0034] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/01/2020] [Accepted: 06/24/2020] [Indexed: 06/28/2023]
Abstract
Reference intervals are commonly used as a decision-making tool. In this review, we provide an overview on "big data" and reference intervals, describing the rationale, current practices including statistical methods, essential prerequisites concerning data quality, including harmonization and standardization, and future perspectives of the indirect determination of reference intervals using routine laboratory data.
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Affiliation(s)
- Luisa Martinez-Sanchez
- Clinical Biochemistry Department, Vall d’Hebron University Hospital, Barcelona, Spain
- Department of Clinical Chemistry and Laboratory Medicine, Leiden University Medical Centre, Leiden, The Netherlands
- Department de Bioquímica i Biologia Molecular, Universitat Autònoma de Barcelona, Bellaterra, Spain
| | | | - Yesim Ozarda
- Department of Medical Biochemistry, Uludag University School of Medicine, Bursa, Turkey
| | - Albert Blanco
- Clinical Biochemistry Department, Vall d’Hebron University Hospital, Barcelona, Spain
| | - Nannette Brouwer
- Diagnost-IQ, Expert Centre for Clinical Chemistry, Purmerend, The Netherlands
| | - Francesca Canalias
- Laboratori de Referència d’Enzimologia Clínica, Departament de Bioquímica i Biologia Molecular, Universitat Autònoma de Barcelona, Bellaterra, Spain
| | - Christa Cobbaert
- Department of Clinical Chemistry and Laboratory Medicine, Leiden University Medical Centre, Leiden, The Netherlands
| | - Marc Thelen
- Laboratory for Clinical Chemistry and Hematology, Amphia, Breda, The Netherlands
- Stichting Kwaliteitsbewaking Medische Laboratoriumdiagnostiek, Nijmegen, The Netherlands
| | - Wendy den Elzen
- Department of Clinical Chemistry and Laboratory Medicine, Leiden University Medical Centre, Leiden, The Netherlands
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18
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Ghazizadeh H, Yaghooti-Khorasani M, Khodabandeh AK, Hasanzadeh E, Sahranavard T, Banihashem-Rad SH, Zare-Feyzabadi R, Ekhteraee-Toosi MS, Akbarpour E, Timar A, Mohammadi-Bajgiran M, Assaran-Darban R, Farkhany EM, Oladi MR, Ferns GA, Esmaily H, Ghayour-Mobarhan M. Reference intervals for routine biochemical markers and body mass index: A study based on healthcare center database in northeastern Iran. IUBMB Life 2020; 73:390-397. [PMID: 33382533 DOI: 10.1002/iub.2437] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2020] [Revised: 11/24/2020] [Accepted: 12/10/2020] [Indexed: 12/11/2022]
Abstract
Age- and sex-specific reference intervals (RIs) for some biochemical tests may be useful for their interpretation, due to the variations in lifestyle and genetic, or ethnic factors. The aim of this study was to obtain RIs for some routine biochemical markers including a serum lipid profile, fasting blood glucose (FBG), aspartate and alanine aminotransferase (AST and ALT), uric acid, and body mass index (BMI) in subjects who attended primary healthcare centers. The large database of primary healthcare centers uses RIs to report results for children, adolescents, and young and old adults. RIs were obtained by using the indirect method, recommended by the CLSI Ep28-A3 guidelines. RIs for FBG, BMI, and serum lipid profile, including triglyceride, total cholesterol, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol in people aged 18 to 120 years, were obtained without age/sex segmentation. RIs for serum AST, ALT, and uric acid were obtained without age segmentation, though these RIs were higher in males than females. The RIs for AST, ALT, and uric acid were higher in men, while the RIs for the other variables were similar in both sexes. This is the first study reporting the use of indirect RIs for BMI.
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Affiliation(s)
- Hamideh Ghazizadeh
- International UNESCO Center for Health-Related Basic Sciences and Human Nutrition, Mashhad University of Medical Sciences, Mashhad, Iran.,Student Research Committee, Mashhad University of Medical Sciences, Mashhad, Iran.,Metabolic Syndrome Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
| | | | - Atieh Kamel Khodabandeh
- Social Determinants of Health Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Elahe Hasanzadeh
- Metabolic Syndrome Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Toktam Sahranavard
- Department of Biology, Faculty of Sciences, Mashhad Branch, Islamic Azad University, Mashhad, Iran
| | | | - Reza Zare-Feyzabadi
- Metabolic Syndrome Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
| | | | | | - Ameneh Timar
- Metabolic Syndrome Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Maryam Mohammadi-Bajgiran
- International UNESCO Center for Health-Related Basic Sciences and Human Nutrition, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Reza Assaran-Darban
- Department of Biology, Faculty of Sciences, Mashhad Branch, Islamic Azad University, Mashhad, Iran
| | - Ehsan Mosa Farkhany
- Metabolic Syndrome Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Mohammad Reza Oladi
- International UNESCO Center for Health-Related Basic Sciences and Human Nutrition, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Gordon A Ferns
- Brighton & Sussex Medical School, Division of Medical Education, Brighton, UK
| | - Habibollah Esmaily
- Social Determinants of Health Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Majid Ghayour-Mobarhan
- International UNESCO Center for Health-Related Basic Sciences and Human Nutrition, Mashhad University of Medical Sciences, Mashhad, Iran.,Metabolic Syndrome Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
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Jassam N, Luvai A, Narayanan D, Turnock D, Lee G, Earp K, West J, Day A, Jeffery J, Zouwail S, El-Farhan N, Dearman R, Hayden K, Willett S, Osborne J, Barth JH. Albumin and calcium reference interval using healthy individuals and a data-mining approach. Ann Clin Biochem 2020; 57:373-381. [PMID: 32646226 DOI: 10.1177/0004563220944204] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Harmonization of reference intervals for analytes that have a sound calibration and metrological traceability is a widely recommended practice. The UK Pathology Harmony has recently harmonized reference intervals for calcium and albumin. In this study, we have determined the reference intervals for calcium and albumin on the UK's most commonly used analytical platforms. METHOD A prospective reference population of healthy individuals was recruited according to the IFCC CRIDL criteria. A second indirect population was collected from 14 primary care setting and measured in laboratories using various analytical platforms and methods (Roche, Abbott, Beckman and Siemens analytical platforms). RESULTS In total, 299 subjects were recruited; the central 95th centile values for calcium for three out of four analytical platforms were in a close agreement with UK Pathology Harmony reference intervals of 2.2-2.6 mmol/L. Reference intervals of BCG methods from both cohorts and irrespective of analytical platforms were higher for both lower and upper reference limits than those for BCP. In comparison, the indirect study showed an age-related variation. The younger population reference intervals varied by up to 5.7% at the lower reference limit and up to 12% at the upper reference limit compared with Pathology Harmony reference intervals, and the older population showed a variation of up to 14% at both limits. CONCLUSION While calcium reference intervals can be a subject for harmonization, albumin reference intervals studied showed large variation which is unsupportive of embracing a common reference interval for albumin.
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Affiliation(s)
- N Jassam
- Department of Clinical Biochemistry, Harrogate Foundation Trust, Harrogate, UK
| | - A Luvai
- Department of Clinical Biochemistry, The Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK
| | - D Narayanan
- Department of Blood Sciences, Hull Royal Infirmary, Hull, UK
| | - D Turnock
- Department of Clinical Biochemistry, York Teaching Hospital NHS Foundation Trust, York, UK
| | - G Lee
- Department of Clinical Biochemistry, Mater Misericordiae University Hospital, Dublin, Ireland
| | - K Earp
- Department of Clinical Chemistry, Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, UK
| | - J West
- Department of Clinical Biochemistry and Immunology, Peterborough City Hospital, Peterborough, UK
| | - A Day
- Department of Clinical Biochemistry, University Hospitals Bristol NHS Foundation Trust, Bristol, UK
| | - J Jeffery
- Derriford Combined Laboratory, Derriford Hospital, Plymouth, UK
| | - S Zouwail
- Department of Biochemistry & Immunology, University Hospital of Wales, Cardiff, UK
| | - N El-Farhan
- Department of Biochemistry, Aneurin Bevan University Health Board, Newport, UK
| | - R Dearman
- Faculty of Biology, Medicine and Health, Manchester University, Manchester, UK
| | - K Hayden
- Department of Clinical Biochemistry, Manchester University Hospital, Manchester, UK
| | - S Willett
- Department of Clinical Biochemistry, North Cumbria University Hospitals, Carlisle, UK
| | - J Osborne
- Department of Clinical Biochemistry, Manchester University Hospital, Manchester, UK
| | - J H Barth
- Department of Clinical Biochemistry, Leeds Teaching Hospitals Trust, Leeds, UK
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Wosniok W, Haeckel R. A new indirect estimation of reference intervals: truncated minimum chi-square (TMC) approach. ACTA ACUST UNITED AC 2019; 57:1933-1947. [DOI: 10.1515/cclm-2018-1341] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2018] [Accepted: 05/19/2019] [Indexed: 01/22/2023]
Abstract
Abstract
All known direct and indirect approaches for the estimation of reference intervals (RIs) have difficulties in processing very skewed data with a high percentage of values at or below the detection limit. A new model for the indirect estimation of RIs is proposed, which can be applied even to extremely skewed data distributions with a relatively high percentage of data at or below the detection limit. Furthermore, it fits better to some simulated data files than other indirect methods. The approach starts with a quantile-quantile plot providing preliminary estimates for the parameters (λ, μ, σ) of the assumed power normal distribution. These are iteratively refined by a truncated minimum chi-square (TMC) estimation. The finally estimated parameters are used to calculate the 95% reference interval. Confidence intervals for the interval limits are calculated by the asymptotic formula for quantiles, and tolerance limits are determined via bootstrapping. If age intervals are given, the procedure is applied per age interval and a spline function describes the age dependency of the reference limits by a continuous function. The approach can be performed in the statistical package R and on the Excel platform.
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Affiliation(s)
- Werner Wosniok
- Institut für Statistik, Universität Bremen , Bremen , Germany
| | - Rainer Haeckel
- Bremer Zentrum für Laboratoriumsmedizin, Klinikum Bremen Mitte , 28305 Bremen , Germany , Phone: +49 412 273446
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