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Understanding and managing interferences in clinical laboratory assays: the role of laboratory professionals

  • Martina Zaninotto und Mario Plebani ORCID logo EMAIL logo
Veröffentlicht/Copyright: 17. Oktober 2019

Abstract

The recently raised concerns regarding biotin interference in immunoassays have increased the awareness of laboratory professionals and clinicians of the evidence that the analytical phase is still vulnerable to errors, particularly as analytical interferences may lead to erroneous results and risks for patient safety. The issue of interference in laboratory testing, which is not new, continues to be a challenge deserving the concern and interest of laboratory professionals and clinicians. Analytical interferences should be subdivided into two types on the basis of the possibility of their detection before the analytical process. The first (type 1) is represented by lipemia, hemolysis and icterus, and the second (type 2), by unusual constituents that are not undetectable before analysis, and may affect the matrix of serum/plasma of individual subjects. Type 2 cannot be identified with current techniques when performing the pre-analytical phase. Therefore, in addition to a more careful evaluation and validation of the method to be used in clinical practice, the awareness of laboratory professionals should be raised as to the importance of evaluating the quality of biological samples before analysis and to adopt algorithms and approaches in the attempt to reduce problems related to erroneous results due to specific or non-specific interferences.


Corresponding author: Prof. Mario Plebani, Department of Laboratory Medicine, University-Hospital of Padova, Padova, Italy, Phone: 0498212792

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

  2. Research funding: None declared.

  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. Luong JH, Male KB, Glennon JD. Biotin interference in immunoassays based on biotin-strept (avidin) chemistry: an emerging threat. Biotechnol Adv 2019;37:634–41.10.1016/j.biotechadv.2019.03.007Suche in Google Scholar PubMed

2. Colon PJ, Greene DN. Biotin interference in clinical immunoassays. J Appl Lab Med 2018;3:941–5.10.1373/jalm.2017.024257Suche in Google Scholar PubMed

3. Li J, Wagar EA, Meng QH. Comprehensive assessment of biotin interference in immunoassays. Clin Chim Acta 2018;487:293–8.10.1016/j.cca.2018.10.013Suche in Google Scholar PubMed

4. Plebani M. Errors in clinical laboratories or errors in laboratory medicine? Clin Chem Lab Med 2006;44:750–9.10.1515/CCLM.2006.123Suche in Google Scholar PubMed

5. Carraro P, Plebani M. Errors in a stat laboratory: types and frequencies 10 years later. Clin Chem 2007;53:1338–42.10.1373/clinchem.2007.088344Suche in Google Scholar PubMed

6. Plebani M. Towards a new paradigm in laboratory medicine: the five rights. Clin Chem Lab Med 2016;54:1881–91.10.1515/cclm-2016-0848Suche in Google Scholar PubMed

7. Plebani M. Analytical quality: an unfinished journey. Clin Chem Lab Med 2018;56:357–9.10.1515/cclm-2017-0717Suche in Google Scholar PubMed

8. Robert L. Schmidt, Pearson LN. Estimating the cost of quality of errors in the analytical phase. Clin Chim Acta 2019;495:60–6.10.1016/j.cca.2019.03.1635Suche in Google Scholar PubMed

9. Zaninotto M, Tognon C, Venturini R, Betterle C, Plebani M. Interference in thyroid hormones with Roche immunoassays: an unfinished story. Clin Chem Lab Med 2014;52:e269–70.10.1515/cclm-2014-0454Suche in Google Scholar PubMed

10. Dundas CM, Demonte D, Park S. Streptavidin-biotin technology: improvements and innovations in chemical and biological applications. Appl Microbiol Biotechnol 2013;97:9343–53.10.1007/s00253-013-5232-zSuche in Google Scholar PubMed

11. Sedel F, Papeix C, Bellanger A, Touitou V, Lebrun-Frenay C, Galanaud D, et al. High doses of biotin in chronic progressive multiple sclerosis: a pilot study. Mult Scler Relat Disord 2015;4:159–69.10.1016/j.msard.2015.01.005Suche in Google Scholar PubMed

12. Plebani M, Laposata M, Lundberg GD. The brain-to-brain loop concept for laboratory testing 40 years after its introduction. Am J Clin Pathol 2011;136:829–33.10.1309/AJCPR28HWHSSDNONSuche in Google Scholar PubMed

13. Badrick T, Gay S, Mackay M, Sikaris K. The key incident monitoring and management system – history and role in quality improvement. Clin Chem Lab Med 2018;56:264–72.10.1515/cclm-2017-0219Suche in Google Scholar PubMed

14. Sciacovelli L, O’Kane M, Skaik YA, Caciagli P, Pellegrini C, Da Rin G, et al. IFCC WG-LEPS. Quality indicators in laboratory medicine: from theory to practice. Preliminary data from the IFCC Working Group Project “Laboratory errors and patient safety”. Clin Chem Lab Med 2011;49:835–44.10.1515/CCLM.2011.128Suche in Google Scholar

15. Plebani M, Sciacovelli L, Aita A, Pelloso M, Chiozza ML. Performance criteria and quality indicators for the pre-analytical phase. Clin Chem Lab Med 2015;53:943–8.10.1515/cclm-2014-1124Suche in Google Scholar PubMed

16. Lippi G, Salvagno GL, Blanckaert N, Giavarina D, Green S, Kitchen S, et al. Multicenter valuation of the hemolysis index in automated clinical chemistry systems. Clin Chem Lab Med 2009;47:934–9.10.1515/CCLM.2009.218Suche in Google Scholar PubMed

17. Farrell JC, Carter AC. Serum indices: managing assay interference. Ann Clin Biochem 2016;53:527–38.10.1177/0004563216643557Suche in Google Scholar PubMed

18. Smith MB, Chan YW, Dolci A, Kellogg MD, McCudden CR, McLean M, et al. Hemolysis, icterus, and lipemia/turbidity indices as indicators of interference in clinical laboratory analysis, approved guideline. Wayne, PA, USA: Clinical and Laboratory Standards Institute, 2012. Document C56-A.Suche in Google Scholar

19. Lippi G, Cadamuro C, von Meyer A, Simundic AM, on behalf of the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) Working Group for Preanalytical Phase (WG-PRE). Practical recommendations for managing hemolyzed samples in clinical chemistry testing. Clin Chem Lab Med 2018;56:718–27.10.1515/cclm-2017-1104Suche in Google Scholar PubMed

20. Dolci A, Panteghini M. Harmonization of automated hemolysis index assessment and use: Is it possible? Clin Chim Acta 2014;432:38–43.10.1016/j.cca.2013.10.012Suche in Google Scholar PubMed

21. Lippi G, Cervellin G, Plebani M. Reporting altered test results in hemolyzed samples: is the cure worse than the disease? Clin Chem Lab Med 2017;55:1112–4.10.1515/cclm-2017-0011Suche in Google Scholar PubMed

22. Cadamuro J, Mrazek C, Haschke-Becher E, Sandberg S. To report or not to report: proposal on how to deal with altered test results in hemolytic samples. Clin Chem Lab Med 2017;55:1109–11.10.1515/cclm-2016-1064Suche in Google Scholar PubMed

23. Quinones-Torrelo C, Villanueva-Gil MP, Rodrıguez-Munoz A, Abellan-Tejada L, Aparici-Ibanez M, Carratala-Calvo A. When an analytical interference is a useful diagnostic tool: finding monoclonal gammopathies in routine analysis. J Clin Lab Anal 2016;30:140–4.10.1002/jcla.21827Suche in Google Scholar

24. Monk C, Wallage M, Wassell J, Whiteway A, James J, Beetham R. A monoclonal protein identified by an anomalous lipaemia index. Ann Clin Biochem 2009;46:250–2.10.1258/acb.2008.008192Suche in Google Scholar

25. Jara-Aguirre JC, Baumann NA, Block DR, Algeciras-Schimnich A. Human chorionic gonadotropin suspected heterophile interference investigations inimmunoassays: a recommended approach. Clin Chem Lab Med 2019;57:1192–6.10.1515/cclm-2018-1142Suche in Google Scholar

26. Kavsak PA, Roy C, Malinowski P, Mark CT, Scott T, Clark L, et al. Macrocomplexes and discordant high-sensitivity cardiac troponin concentrations. Ann Clin Biochem 2018;55:500–4.10.1177/0004563217734883Suche in Google Scholar

27. Rhea JM, Molinaro R. Pathology consultation on HbA1c methods and interferences. Am J Clin Pathol 2014;141:5–16.10.1309/AJCPQ23GTTMLAEVLSuche in Google Scholar

28. Warda G, Simpson A, Boscatoc L, Hickman PE. The investigation of interferences in immunoassay. Clin Biochem 2017;50:1306–11.10.1016/j.clinbiochem.2017.08.015Suche in Google Scholar

29. Censi S, Cavedon E, Fernando SW, Barollo S, Bertazza L, Zambonin L, et al. Calcitonin measurement and immunoassay interference: a case report and literature review. Clin Chem Lab Med 2016;54:1861–70.10.1515/cclm-2015-1161Suche in Google Scholar

30. Briani C, Zaninotto M, Forni M, Burra P. Macroenzymes: too often overlooked. J Hepatol 2003;38:119.10.1016/S0168-8278(02)00333-1Suche in Google Scholar

31. Rubin AS, Sass DA, Stickle DF. Distribution of serum concentrations reported for macroenzyme aspartate aminotransferase (macro-AST). Pract Lab Med 2017;8:65–9.10.1016/j.plabm.2017.05.003Suche in Google Scholar PubMed PubMed Central

32. Ismail AA. Identifying and reducing potentially wrong immunoassay results even when plausible and “not-unreasonable”. Adv Clin Chem 2014;66:241–94.10.1016/B978-0-12-801401-1.00007-4Suche in Google Scholar

33. Sturgeon CM, Viljoen A. Analytical error and interference in immunoassay: minimizing risk. Ann Clin Biochem 2011;48: 418–32.10.1258/acb.2011.011073Suche in Google Scholar PubMed

34. Vogeser M, Seger C. Irregular analytical errors in diagnostic testing – a novel concept. Clin Chem Lab Med 2018;56:386–96.10.1515/cclm-2017-0454Suche in Google Scholar PubMed

35. Clerico A, Belloni L, Carrozza C, Correale M, Dittadi R, Dotti C, et al. A Black Swan in clinical laboratory practice: the analytical error due to interferences in immunoassay methods. Clin Chem Lab Med 2018;56:397–402.10.1515/cclm-2017-0881Suche in Google Scholar PubMed

36. Trambas C, Lu Z, Yen T, Sikaris K. Depletion of biotin using streptavidin-coated microparticles: a validated solution to the problem of biotin interference in streptavidin–biotin immunoassays. Ann Clin Biochem 2018;55:216–26.10.1177/0004563217707783Suche in Google Scholar PubMed

37. Ismail AA. When laboratory tests can mislead even when they appear plausible. Clin Med 2017;4:329–32.10.7861/clinmedicine.17-4-329Suche in Google Scholar PubMed PubMed Central

38. Favresse J, Burlacu MC, Maiter D, Gruson D. Interferences with thyroid function immunoassays: clinical implications and detection algorithm. Endocr Rev 2018;39:830–50.10.1210/er.2018-00119Suche in Google Scholar PubMed

39. Barth JH, Lippiatt CM, Gibbons SG, Desborough RA. Observational studies on macroprolactin in a routine clinical laboratory. Clin Chem Lab Med 2018;56:1259–62.10.1515/cclm-2018-0074Suche in Google Scholar PubMed

40. Lippi G, Bonetti G, Modenese A, Padoan A, Giavarina D. Biotin interference inimmunoassays: recommendations of the SIBioC Working Group on Extra Analytical Variability (WG-VEA). Biochim Clin 2019;43:343–7.Suche in Google Scholar

41. Clerico A, Plebani M. Biotin interference on immunoassay methods: sporadic cases or hidden epidemic? Clin Chem Lab Med 2017;55:777–9.10.1515/cclm-2017-0070Suche in Google Scholar PubMed

42. Piketty ML, Polak M, Flechtner I, Gonzales-Briceno L,Souberbielle JC. False biochemical diagnosis of hyperthyroidism in streptavidin-biotin-based immunoassays: the problem of biotin intake and related interferences. Clin Chem Lab Med 2017;55:780–8.10.1515/cclm-2016-0606Suche in Google Scholar PubMed

Received: 2019-08-23
Accepted: 2019-09-15
Published Online: 2019-10-17
Published in Print: 2020-02-25

©2020 Walter de Gruyter GmbH, Berlin/Boston

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