Literature DB >> 30218599

NUMBER: standardized reference intervals in the Netherlands using a 'big data' approach.

Wendy P J den Elzen1, Nannette Brouwer2, Marc H Thelen3,4, Saskia Le Cessie5,6, Inez-Anne Haagen7, Christa M Cobbaert8.   

Abstract

Background External quality assessment (EQA) programs for general chemistry tests have evolved from between laboratory comparison programs to trueness verification surveys. In the Netherlands, the implementation of such programs has reduced inter-laboratory variation for electrolytes, substrates and enzymes. This allows for national and metrological traceable reference intervals, but these are still lacking. We have initiated a national endeavor named NUMBER (Nederlandse UniforMe Beslisgrenzen En Referentie-intervallen) to set up a sustainable system for the determination of standardized reference intervals in the Netherlands. Methods We used an evidence-based 'big-data' approach to deduce reference intervals using millions of test results from patients visiting general practitioners from clinical laboratory databases. We selected 21 medical tests which are either traceable to SI or have Joint Committee for Traceability in Laboratory Medicine (JCTLM)-listed reference materials and/or reference methods. Per laboratory, per test, outliers were excluded, data were transformed to a normal distribution (if necessary), and means and standard deviations (SDs) were calculated. Then, average means and SDs per test were calculated to generate pooled (mean±2 SD) reference intervals. Results were discussed in expert meetings. Results Sixteen carefully selected clinical laboratories across the country provided anonymous test results (n=7,574,327). During three expert meetings, participants found consensus about calculated reference intervals for 18 tests and necessary partitioning in subcategories, based on sex, age, matrix and/or method. For two tests further evaluation of the reference interval and the study population were considered necessary. For glucose, the working group advised to adopt the clinical decision limit. Conclusions Using a 'big-data' approach we were able to determine traceable reference intervals for 18 general chemistry tests. Nationwide implementation of these established reference intervals has the potential to improve unequivocal interpretation of test results, thereby reducing patient harm.

Entities:  

Keywords:  big data approach; reference intervals; standardization

Mesh:

Year:  2018        PMID: 30218599     DOI: 10.1515/cclm-2018-0462

Source DB:  PubMed          Journal:  Clin Chem Lab Med        ISSN: 1434-6621            Impact factor:   3.694


  4 in total

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Journal:  Cancers (Basel)       Date:  2022-06-01       Impact factor: 6.575

2.  Indirect determination of biochemistry reference intervals using outpatient data.

Authors:  Luisa Martinez-Sanchez; Christa M Cobbaert; Raymond Noordam; Nannette Brouwer; Albert Blanco-Grau; Yolanda Villena-Ortiz; Marc Thelen; Roser Ferrer-Costa; Ernesto Casis; Francisco Rodríguez-Frias; Wendy P J den Elzen
Journal:  PLoS One       Date:  2022-05-19       Impact factor: 3.752

3.  Age-adjusted interpretation of biomarkers of renal function and homeostasis, inflammation, and circulation in Emergency Department patients.

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Journal:  Sci Rep       Date:  2022-01-28       Impact factor: 4.379

4.  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.

Authors:  Taeyun Kim; Hyunji Choi; Sun Min Lee
Journal:  BMJ Open       Date:  2022-07-25       Impact factor: 3.006

  4 in total

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