Startseite Next-generation reference intervals for pediatric hematology
Artikel
Lizenziert
Nicht lizenziert Erfordert eine Authentifizierung

Next-generation reference intervals for pediatric hematology

  • Jakob Zierk EMAIL logo , Johannes Hirschmann , Dennis Toddenroth , Farhad Arzideh , Rainer Haeckel , Alexander Bertram , Holger Cario , Michael C. Frühwald , Hans-Jürgen Groß , Arndt Groening , Stefanie Grützner , Thomas Gscheidmeier , Torsten Hoff , Reinhard Hoffmann , Rainer Klauke , Alexander Krebs , Ralf Lichtinghagen , Sabine Mühlenbrock-Lenter , Michael Neumann , Peter Nöllke , Charlotte M. Niemeyer , Oliver Razum , Hans-Georg Ruf , Udo Steigerwald , Thomas Streichert , Antje Torge , Wolfgang Rascher , Hans-Ulrich Prokosch , Manfred Rauh und Markus Metzler
Veröffentlicht/Copyright: 22. April 2019
Veröffentlichen auch Sie bei De Gruyter Brill

Abstract

Background

Interpreting hematology analytes in children is challenging due to the extensive changes in hematopoiesis that accompany physiological development and lead to pronounced sex- and age-specific dynamics. Continuous percentile charts from birth to adulthood allow accurate consideration of these dynamics. However, the ethical and practical challenges unique to pediatric reference intervals have restricted the creation of such percentile charts, and limitations in current approaches to laboratory test result displays restrict their use when guiding clinical decisions.

Methods

We employed an improved data-driven approach to create percentile charts from laboratory data collected during patient care in 10 German centers (9,576,910 samples from 358,292 patients, 412,905–1,278,987 samples per analyte). We demonstrate visualization of hematology test results using percentile charts and z-scores (www.pedref.org/hematology) and assess the potential of percentiles and z-scores to support diagnosis of different hematological diseases.

Results

We created percentile charts for hemoglobin, hematocrit, red cell indices, red cell count, red cell distribution width, white cell count and platelet count in girls and boys from birth to 18 years of age. Comparison of pediatricians evaluating complex clinical scenarios using percentile charts versus conventional/tabular representations shows that percentile charts can enhance physician assessment in selected example cases. Age-specific percentiles and z-scores, compared with absolute test results, improve the identification of children with blood count abnormalities and the discrimination between different hematological diseases.

Conclusions

The provided reference intervals enable precise assessment of pediatric hematology test results. Representation of test results using percentiles and z-scores facilitates their interpretation and demonstrates the potential of digital approaches to improve clinical decision-making.

Acknowledgments

We thank the members of the German Society for Clinical Chemistry and Laboratory Medicine’s working group on guide limits (“AG Richtwerte der DGKL”) for their valuable input.

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

  2. Research funding: Supported by the Interdisciplinary Center for Clinical Research (IZKF) at the University Hospital of the University of Erlangen-Nuremberg.

  3. Employment or leadership: None declared.

  4. Honorarium: None declared.

  5. Competing interests: The funding organization(s) played no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the report for publication.

References

1. Adeli K, Raizman JE, Chen Y, Higgins V, Nieuwesteeg M, Abdelhaleem M, et al. Complex biological profile of hematologic markers across pediatric, adult, and geriatric ages: establishment of robust pediatric and adult reference intervals on the basis of the Canadian health measures survey. Clin Chem 2015;61:1075–86.10.1373/clinchem.2015.240531Suche in Google Scholar PubMed

2. Ceriotti F. Establishing pediatric reference intervals: a challenging task. Clin Chem 2012;58:808–10.10.1373/clinchem.2012.183483Suche in Google Scholar PubMed

3. Metz MP, Loh TP. Describing children’s changes using clinical chemistry analytes. Clin Chem Lab Med 2016;55:1–2.10.1515/cclm-2016-0911Suche in Google Scholar PubMed

4. Higgins V, Adeli K. Advances in pediatric reference intervals: from discrete to continuous. J Lab Precis Med 2018;3. Available from: http://jlpm.amegroups.com/article/view/3976.10.21037/jlpm.2018.01.02Suche in Google Scholar

5. Mørkrid L, Rowe AD, Elgstoen KB, Olesen JH, Ruijter G, Hall PL, et al. Continuous age- and sex-adjusted reference intervals of urinary markers for cerebral creatine deficiency syndromes: a novel approach to the definition of reference intervals. Clin Chem 2015;61:760–8.10.1373/clinchem.2014.235564Suche in Google Scholar PubMed

6. Loh TP, Metz MP. Trends and physiology of common serum biochemistries in children aged 0–18 years. Pathology (Phila). 2015;47:452–61.10.1097/PAT.0000000000000274Suche in Google Scholar PubMed

7. Bussler S, Vogel M, Pietzner D, Harms K, Buzek T, Penke M, et al. New pediatric percentiles of liver enzyme serum levels (ALT, AST, GGT): effects of age, sex, BMI and pubertal stage. Hepatol Baltim Md 2017.Suche in Google Scholar

8. Dortschy R, Schaffrath RA, Scheidt-Nave C, Thierfelder W, Thamm M, Gutsche J, u. a. Bevölkerungsbezogene Verteilungswerte ausgewählter Laborparameter aus der Studie zur Gesundheit von Kindern und Jugendlichen in Deutschland (KiGGS). Berlin: Robert Koch-Institut; 2009. (Beiträge zur Gesundheitsberichterstattung des Bundes)Suche in Google Scholar

9. Zierk J, Arzideh F, Rechenauer T, Haeckel R, Rascher W, Metzler M, et al. Age- and sex-specific dynamics in 22 hematologic and biochemical analytes from birth to adolescence. Clin Chem 2015;61:964–73.10.1373/clinchem.2015.239731Suche in Google Scholar PubMed

10. Zongbo C, Guoxuan L, Biyun Z, Ziping L. The investigation of venous blood cell reference interval for 3–14 years old healthy children in Nanhai district of Foshan city. Int J Lab Med 2014;8:1005–6.Suche in Google Scholar

11. Orkin SH, Nathan DG, Ginsburg D, Look AT, Fisher DE, Lux S IV. Nathan and Oski’s hematology and oncology of infancy and childhood, 8th ed. Philadelphia, PA, USA: Saunders, 2014:2752.Suche in Google Scholar

12. Cembrowski G, Chan J, Cheng C, Bamforth F. NHANES 1999–2000 Data used to create comprehensive health-associated race-, sex-, and age-stratified reference intervals for the Coulter MAXM. Lab Hematol 2004;10:245–6.Suche in Google Scholar

13. Aldrimer M, Ridefelt P, Rödöö P, Niklasson F, Gustafsson J, Hellberg D. Population-based pediatric reference intervals for hematology, iron and transferrin. Scand J Clin Lab Invest 2013;73:253–61.10.3109/00365513.2013.769625Suche in Google Scholar PubMed

14. Zierk J, Arzideh F, Haeckel R, Rascher W, Rauh M, Metzler M. Indirect determination of pediatric blood count reference intervals. Clin Chem Lab Med 2013;51:863–72.10.1515/cclm-2012-0684Suche in Google Scholar PubMed

15. Adetifa IM, Hill PC, Jeffries DJ, Jackson-Sillah D, Ibanga HB, Bah G, et al. Haematological values from a Gambian cohort – possible reference range for a West African population. Int J Lab Hematol 2009;31:615–22.10.1111/j.1751-553X.2008.01087.xSuche in Google Scholar PubMed

16. Revision of the “Guideline of the German Medical Association on Quality Assurance in Medical Laboratory Examinations – Rili-BAEK” (unauthorized translation). LaboratoriumsMedizin 2015;39:26.10.1515/labmed-2014-0046Suche in Google Scholar

17. Neufassung der „Richtlinie der Bundesärztekammer zur Qualitätssicherung laboratoriumsmedizinischer Untersuchungen – Rili-BÄK“ – Richtlinie der Bundesärztekammer zur Qualitätssicherung laboratoriumsmedizinischer Untersuchungen. Dtsch Arztebl Int 2014;111:A-1583.Suche in Google Scholar

18. Arzideh F, Wosniok W, Haeckel R. Reference limits of plasma and serum creatinine concentrations from intra-laboratory data bases of several German and Italian medical centres: comparison between direct and indirect procedures. Clin Chim Acta 2010;411:215–21.10.1016/j.cca.2009.11.006Suche in Google Scholar PubMed

19. Arzideh F, Wosniok W, Haeckel R. Indirect reference intervals of plasma and serum thyrotropin (TSH) concentrations from intra-laboratory data bases from several German and Italian medical centres. Clin Chem Lab Med 2011;49:659–64.10.1515/CCLM.2011.114Suche in Google Scholar PubMed

20. Zierk J, Arzideh F, Haeckel R, Rauh M, Metzler M, Ganslandt T, et al. Indirect determination of hematology reference intervals in adult patients on Beckman Coulter UniCell DxH 800 and Abbott CELL-DYN Sapphire devices. Clin Chem Lab Med 2018; doi: 10.1515/cclm-2018-0771. [Epub ahead of print].10.1515/cclm-2018-0771Suche in Google Scholar PubMed

21. Zierk J, Arzideh F, Haeckel R, Cario H, Frühwald MC, Groß H-J, et al. Pediatric reference intervals for alkaline phosphatase. Clin Chem Lab Med 2017;55:102–10.10.1515/cclm-2016-0318Suche in Google Scholar PubMed

22. R Core Team. R: A Language and Environment for Statistical Computing [Internet]. Vienna, Austria: R Foundation for Statistical Computing; 2016. Available from: https://www.R-project.org/.Suche in Google Scholar

23. Razum O, Wenner J. Social and health epidemiology of immigrants in Germany: past, present and future. Public Health Rev 2016;37:4.10.1186/s40985-016-0019-2Suche in Google Scholar PubMed PubMed Central

24. Quantity quotient reporting versus z-value for standardizing quantitative laboratory results: LaboratoriumsMedizin – J Lab Med [Internet] 2017 [cited 2017 Aug 26]. Available from: https://www.degruyter.com/view/j/labm.2017.41.issue-2/labmed-2017-0007/labmed-2017-0007.xml.10.1515/labmed-2017-0007Suche in Google Scholar

25. Bailey D, Colantonio D, Kyriakopoulou L, Cohen AH, Chan MK, Armbruster D, et al. Marked biological variance in endocrine and biochemical markers in childhood: establishment of pediatric reference intervals using healthy community children from the CALIPER cohort. Clin Chem 2013;59:1393–405.10.1373/clinchem.2013.204222Suche in Google Scholar PubMed

26. Hasle H, Aricò M, Basso G, Biondi A, Cantù Rajnoldi A, Creutzig U, et al. Myelodysplastic syndrome, juvenile myelomonocytic leukemia, and acute myeloid leukemia associated with complete or partial monosomy 7. European Working Group on MDS in Childhood (EWOG-MDS). Leukemia 1999;13:376–85.10.1038/sj.leu.2401342Suche in Google Scholar PubMed

27. Niemeyer CM, Arico M, Basso G, Biondi A, Cantu Rajnoldi A, Creutzig U, et al. Chronic myelomonocytic leukemia in childhood: a retrospective analysis of 110 cases. European Working Group on Myelodysplastic Syndromes in Childhood (EWOG-MDS). Blood 1997;89:3534–43.Suche in Google Scholar

28. Baumann I, Führer M, Behrendt S, Campr V, Csomor J, Furlan I, et al. Morphological differentiation of severe aplastic anaemia from hypocellular refractory cytopenia of childhood: reproducibility of histopathological diagnostic criteria. Histopathology 2012;61:10–7.10.1111/j.1365-2559.2011.04156.xSuche in Google Scholar PubMed

29. Pedregosa F, Varoquaux G, Gramfort A, Michel V, Thirion B, Grisel O, et al. Scikit-learn: machine learning in Python. J Mach Learn Res 2011;12:2825−30.Suche in Google Scholar

30. Razum O, Zeeb H, Akgün S. How useful is a name-based algorithm in health research among Turkish migrants in Germany? Trop Med Int Health 2001;6:654–61.10.1046/j.1365-3156.2001.00760.xSuche in Google Scholar

31. Razum O, Zeeb H, Beck K, Becher H, Ziegler H, StegmaierC. Combining a name algorithm with a capture–recapture method to retrieve cases of Turkish descent from a German population-based cancer registry. Eur J Cancer 2000;36:2380–4.10.1016/S0959-8049(00)00333-6Suche in Google Scholar

32. Van den Bossche J, Devreese K, Malfait R, Van de Vyvere M, Wauters A, Neels H, et al. Reference intervals for a complete blood count determined on different automated haematology analysers: Abx Pentra 120 Retic, Coulter Gen-S, Sysmex SE 9500, Abbott Cell Dyn 4000 and Bayer Advia 120. Clin Chem Lab Med 2005;40:69–73.10.1515/CCLM.2002.014Suche in Google Scholar

33. Gollomp K, Arulselvan A, Tanzer M, Shibutani S, Lambert MP. Honing in on the range: using the electronic medical record to establish normal reference ranges for pediatric coagulation testing. Blood 2015;126:4450.10.1182/blood.V126.23.4450.4450Suche in Google Scholar

34. Haeckel R, Wosniok W, Arzideh F, Zierk J, Gurr E, Streichert T. Critical comments to a recent EFLM recommendation for the review of reference intervals. Clin Chem Lab Med 2017 [cited 2017 Feb 3];0(0). Available from: https://www.degruyter.com/view/j/cclm.ahead-of-print/cclm-2016-1112/cclm-2016-1112.xml?format=INT.10.1515/cclm-2016-1112Suche in Google Scholar PubMed

35. Minter Baerg MM, Stoway SD, Hart J, Mott L, Peck DS, Nett SL, et al. Precision newborn screening for lysosomal disorders. Genet Med Off J Am Coll Med Genet 2018;20:847–54.10.1038/gim.2017.194Suche in Google Scholar PubMed

36. Marquardt G, Currier R, McHugh DM, Gavrilov D, MageraMJ, Matern D, et al. Enhanced interpretation of newborn screening results without analyte cutoff values. Genet Med 2012;14:648–55.10.1038/gim.2012.2Suche in Google Scholar PubMed

37. Wilkes EH, Rumsby G, Woodward GM. Using machine learning to aid the interpretation of urine steroid profiles. Clin Chem 2018;64:1586–95.10.1373/clinchem.2018.292201Suche in Google Scholar PubMed

38. Sheffer-Mimouni G, Mimouni FB, Lubetzky R, Kupferminc M, Deutsch V, Dollberg S. Labor does not affect the neonatal absolute nucleated red blood cell count. Am J Perinatol 2003;20:367–71.10.1055/s-2003-45285Suche in Google Scholar PubMed

39. Melioli G, Risso FM, Sannia A, Serra G, Bologna R, Mussap M, et al. Reference values of blood cell counts in the first days of life. Front Biosci Elite Ed 2011;3:871–8.10.2741/e295Suche in Google Scholar PubMed

40. Andropoulos DB. Appendix B: Pediatric normal laboratory values. In: Gregory GA, Andropoulos DB, editors. Gregory’s Pediatric Anesthesia [Internet]. Hoboken, NJ, USA: Wiley- Blackwell, 2012:1300–14 [cited 2016 Nov 19]. http:// onlinelibrary.wiley.com/doi/10.1002/9781444345186.app2/summary.10.1002/9781444345186Suche in Google Scholar

41. Wiedmeier SE, Henry E, Sola-Visner MC, Christensen RD. Platelet reference ranges for neonates, defined using data from over 47,000 patients in a multihospital healthcare system. J Perinatol 2009;29:130–6.10.1038/jp.2008.141Suche in Google Scholar PubMed

42. Lawrie D, Payne H, Nieuwoudt M, Glencross DK. Observed full blood count and lymphocyte subset values in a cohort of clinically healthy South African children from a semi-informal settlement in Cape Town. S Afr Med J 2015;105:589–95.10.7196/SAMJnew.7914Suche in Google Scholar PubMed


Supplementary Material

The online version of this article offers supplementary material (https://doi.org/10.1515/cclm-2018-1236).



Article note:

Prior presentations: 22th Congress of the European Hematology Association (EHA), Madrid, Spain, June 2017 (abstract/e-poster); 14th Annual Congress of the German Society of Clinical Chemistry and Laboratory Medicine (DGKL), Oldenburg, Germany, October 2017 (talk and poster); XIVth International Congress of Paediatric Laboratory Medicine, Durban, South Africa October 2017 (talk and poster), IFCC WorldLab 2017, Durban, South Africa, October 2017 (poster); preliminary percentile charts have been published by the German Society for Paediatric Oncology and Haematology (GPOH) at www.kinderblutkrankheiten.de


Received: 2018-11-18
Accepted: 2019-03-02
Published Online: 2019-04-22
Published in Print: 2019-09-25

©2019 Walter de Gruyter GmbH, Berlin/Boston

Artikel in diesem Heft

  1. Frontmatter
  2. Editorial
  3. Blood biomarkers in neurology: “a call to arms” for laboratory professionals
  4. Reviews
  5. Diagnostic accuracy of glycated hemoglobin for gestational diabetes mellitus: a systematic review and meta-analysis
  6. Laboratory medicine: health evaluation in elite athletes
  7. Prostate cancer screening: guidelines review and laboratory issues
  8. Opinion Papers
  9. Extra-analytical sources of uncertainty: which ones really matter?
  10. Benefits and harms of wellness initiatives
  11. Genetics and Molecular Diagnostics
  12. Analytical and clinical validation of a novel amplicon-based NGS assay for the evaluation of circulating tumor DNA in metastatic colorectal cancer patients
  13. General Clinical Chemistry and Laboratory Medicine
  14. Pre-analytical practices for routine coagulation tests in European laboratories. A collaborative study from the European Organisation for External Quality Assurance Providers in Laboratory Medicine (EQALM)
  15. Preanalytical robustness of blood collection tubes with RNA stabilizers
  16. Continual improvement of the pre-analytical process in a public health laboratory with quality indicators-based risk management
  17. Comparison of six commercial serum exosome isolation methods suitable for clinical laboratories. Effect in cytokine analysis
  18. A multicenter study to evaluate harmonization of assays for N-terminal propeptide of type I procollagen (PINP): a report from the IFCC-IOF Joint Committee for Bone Metabolism
  19. Correlations between serum and CSF pNfH levels in ALS, FTD and controls: a comparison of three analytical approaches
  20. Dynamics of extracellular matrix proteins in cerebrospinal fluid and serum and their relation to clinical outcome in human traumatic brain injury
  21. Free light chains in the cerebrospinal fluid. Comparison of different methods to determine intrathecal synthesis
  22. Reference Values and Biological Variations
  23. Reference interval by the indirect approach of serum thyrotropin (TSH) in a Mediterranean adult population and the association with age and gender
  24. Next-generation reference intervals for pediatric hematology
  25. Hematology and Coagulation
  26. Preliminary evaluation of a new flow cytometry method for the routine hematology workflow
  27. Diabetes
  28. Trueness assessment of HbA1c routine assays: are processed EQA materials up to the job?
  29. Infectious Diseases
  30. Utility of procalcitonin for differentiating cryptogenic organising pneumonia from community-acquired pneumonia
  31. A high C-reactive protein/procalcitonin ratio predicts Mycoplasma pneumoniae infection
  32. Letters to the Editor
  33. Evaluation of reference change values for a hs-cTnI immunoassay using both plasma samples of healthy subjects and patients and quality control samples
  34. Outlier removal methods for skewed data: impact on age-specific high-sensitive cardiac troponin T 99th percentiles
  35. Comparison of precision and operational performances across six immunochemistry analyzers
  36. Evaluation of the possible interference of abiraterone therapy on testosterone immunoassay
  37. Erroneous thyroid and steroid hormones profile due to anti-streptavidin antibodies
  38. Reference values for 24,25-dihydroxyvitamin D and the 25-hydroxyvitamin D/24,25-dihydroxyvitamin D ratio
  39. Pre-analytical error in a hematology laboratory: an avoidable cause of compromised quality in reporting
  40. Stability of tubular damage markers epidermal growth factor and heparin-binding EGF-like growth factor in urine
  41. Blood from heparin tubes is an acceptable alternative to assess hematocrit determination
Heruntergeladen am 3.11.2025 von https://www.degruyterbrill.com/document/doi/10.1515/cclm-2018-1236/html?lang=de
Button zum nach oben scrollen