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Harmonization of indirect reference intervals calculation by the Bhattacharya method

  • Luisa Martinez-Sanchez ORCID logo EMAIL logo , Pablo Gabriel-Medina , Yolanda Villena-Ortiz ORCID logo , Alba E. García-Fernández , Albert Blanco-Grau , Christa M. Cobbaert , Daniel Bravo-Nieto , Sarai Garriga-Edo , Clara Sanz-Gea , Gonzalo Gonzalez-Silva , Joan López-Hellín , Roser Ferrer-Costa , Ernesto Casis , Francisco Rodríguez-Frías und Wendy P.J. den Elzen
Veröffentlicht/Copyright: 17. November 2022
Clinical Chemistry and Laboratory Medicine (CCLM)
Aus der Zeitschrift Clinical Chemistry and Laboratory Medicine (CCLM) Band 61 Heft 2

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.

Keywords: Bhattacharya; harmonization; indirect approach; reference intervals
Corresponding author: 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; and Clinical Biochemistry Research Team, Vall d’Hebron Institute of Research (VHIR), Barcelona, Spain, Phone: +34 649445158, E-mail:
Luisa Martinez-Sanchez, Pablo Gabriel-Medina and Yolanda Villena-Ortiz contributed equally to this work as first authors. Fracisco Rodríguez–Frías and Wendy den Elzen contributed equally to this work as senior authors.

Acknowledgments

We thank Dr. Raymond Noordam for the R script to design the figures for the moving averages analysis.

  1. Research funding: None declared.

  2. Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  3. Competing interests: Authors state no conflict of interest.

  4. Informed consent: Not applicable.

  5. Ethical approval: Not applicable.

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Supplementary Material

The online version of this article offers supplementary material (https://doi.org/10.1515/cclm-2022-0439).

Received: 2022-05-05
Accepted: 2022-11-03
Published Online: 2022-11-17
Published in Print: 2023-01-27

© 2022 Walter de Gruyter GmbH, Berlin/Boston

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https://doi.org/10.1515/cclm-2022-0439
Schlagwörter für diesen Artikel
Bhattacharya; harmonization; indirect approach; reference intervals

Artikel in diesem Heft

  1. Frontmatter
  2. Editorial
  3. Standardization and harmonization in laboratory medicine: not only for clinical chemistry measurands
  4. Mini Review
  5. The effect of the immunoassay curve fitting routine on bias in troponin
  6. Opinion Papers
  7. An overview of the most important preanalytical factors influencing the clinical performance of SARS-CoV-2 antigen rapid diagnostic tests (Ag-RDTs)
  8. Time to address quality control processes applied to antibody testing for infectious diseases
  9. Perspectives
  10. Definition and application of performance specifications for measurement uncertainty of 23 common laboratory tests: linking theory to daily practice
  11. The gaps between the new EU legislation on in vitro diagnostics and the on-the-ground reality
  12. General Clinical Chemistry and Laboratory Medicine
  13. Second-generation Elecsys cerebrospinal fluid immunoassays aid diagnosis of early Alzheimer’s disease
  14. Evaluation of the interchangeability between the new fully-automated affinity chrome-mediated immunoassay (ACMIA) and the Quantitative Microsphere System (QMS) with a CE-IVD-certified LC-MS/MS assay for therapeutic drug monitoring of everolimus after solid organ transplantation
  15. Quantitative detection of anti-PLA2R antibodies targeting different epitopes and its clinical application in primary membranous nephropathy
  16. Reference Values and Biological Variations
  17. A zlog-based algorithm and tool for plausibility checks of reference intervals
  18. Harmonization of indirect reference intervals calculation by the Bhattacharya method
  19. Red blood cell parameters in early childhood: a prospective cohort study
  20. Cancer Diagnostics
  21. Association of circulating free and total oxysterols in breast cancer patients
  22. Effect of short-term storage of blood samples on gene expression in lung cancer patients
  23. Infectious Diseases
  24. Operation Moonshot: rapid translation of a SARS-CoV-2 targeted peptide immunoaffinity liquid chromatography-tandem mass spectrometry test from research into routine clinical use
  25. Seroprevalence of SARS-CoV-2 antibodies in Italy in newborn dried blood spots
  26. Positivization time of a COVID-19 rapid antigen self-test predicts SARS-CoV-2 viral load: a proof of concept
  27. New insights into SARS-CoV-2 Lumipulse G salivary antigen testing: accuracy, safety and short TAT enhance surveillance
  28. Preanalytical stability of SARS-CoV-2 anti-nucleocapsid antibodies
  29. Prognostic value of procalcitonin in cancer patients with coronavirus disease 2019
  30. 24/7 workflow for bloodstream infection diagnostics in microbiology laboratories: the first step to improve clinical management
  31. Diagnostic performance of machine learning models using cell population data for the detection of sepsis: a comparative study
  32. Diagnostic value of procalcitonin, hypersensitive C-reactive protein and neutrophil-to-lymphocyte ratio for bloodstream infections in pediatric tumor patients
  33. Letters to the Editor
  34. Pseudohyponatremia: interference of hyperglycemia on indirect potentiometry
  35. Ligand binding assay-related underestimation of 25-hydroxyvitamin D in pregnant women exaggerates the prevalence of vitamin D insufficiency
  36. Urokinase-type plasminogen activator soluble receptor (suPAR) assay in clinical routine: evaluation one year after its introduction in the high automation corelab of the A. Gemelli hospital
  37. Is this a true lambda free light chain?
  38. Effect of various blood collection tubes on serum lithium and other electrolytes: our perspective from a tertiary healthcare institute
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