Skip to content
Licensed Unlicensed Requires Authentication Published by De Gruyter October 14, 2017

Indirect method for validating transference of reference intervals

  • Simon Lykkeboe , Claus Gyrup Nielsen and Peter Astrup Christensen EMAIL logo

Abstract

Background:

Transference of reference intervals (RIs) from multicentre studies are often verified by use of a small number of samples from reference individuals or by the use of one serum sample (Serum X for NORIP RI). Despite recommended and appropriate methods, both have inconveniencies and drawbacks. Several attempts have been made to develop an indirect method, which uses historical data from the laboratory. These methods are retrospective relying on older test results. A near prospective method would be preferable for the laboratories introducing new methods or changing analytical platforms.

Methods:

We performed a data mining experiment using results from our laboratory information system covering patients from a large geographic area. Request patterns for patients with assumed healthy characteristics were identified and used to extract laboratory results for calculation of new RI by an indirect method. Calculated RI and confidence intervals (CIs) were compared to transferred NORIP RI verified by NFKK Reference Serum X.

Results:

We found that our indirect method and NFKK Reference Serum X in general produced similar results when verifying transference of RI. The method produces results for all stratifications. Only single stratifications and one analyte showed unexplained incongruences to the NORIP RI.

Conclusions:

Our results suggest using request patterns as a surrogate measure for good health status. This allows for a data mining method for validation of RI or validating their transference, which is likely to be applicable in countries with similar healthcare and laboratory information system.

Acknowledgments

The authors thank the staff at the Department of Clinical Biochemistry, Aalborg University Hospital, for valuable discussions and Professor Aase Handberg for critical reading of the manuscript.

  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 organisation(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. Ceriotti F, Hinzmann R, Panteghini M. Reference intervals: the way forward. Ann Clin Biochem 2009;46:8–17.10.1258/acb.2008.008170Search in Google Scholar

2. Horn PS, Pesce AJ. Reference intervals: an update. Clin Chim Acta 2003;334:5–23.10.1016/S0009-8981(03)00133-5Search in Google Scholar

3. CLSI. Defining, establishing, and verifying reference intervals in the clinical laboratory; approved guideline – third edition. CLSI document EP28 – A3c ed: Wayne, PA, USA: CLSI (Clinical Laboratory Standards Institute), 2010.Search in Google Scholar

4. Rustad P, Felding P, Franzson L, Kairisto V, Lahti A, Martensson A, et al. The Nordic Reference Interval Project 2000: recommended reference intervals for 25 common biochemical properties. Scand J Clin Lab Invest 2004;64: 271–84.10.1080/00365510410006324Search in Google Scholar PubMed

5. Bakan E, Polat H, Ozarda Y, Ozturk N, Baygutalp NK, Umudum FZ, et al. A reference interval study for common biochemical analytes in Eastern Turkey: a comparison of a reference population with laboratory data mining. Biochem Med (Zagreb) 2016;26:210–23.10.11613/BM.2016.023Search in Google Scholar PubMed PubMed Central

6. Bock BJ, Dolan CT, Miller GC, Fitter WF, Hartsell BD, Crowson AN, et al. The data warehouse as a foundation for population-based reference intervals. Am J Clin Pathol 2003;120:662–70.10.1309/W8J85AG4WDG6JGJ9Search in Google Scholar

7. Grossi E, Colombo R, Cavuto S, Franzini C. The REALAB project: a new method for the formulation of reference intervals based on current data. Clin Chem 2005;51:1232–40.10.1373/clinchem.2005.047787Search in Google Scholar PubMed

8. Tozzoli R, Giavarina D, Villalta D, Soffiati G, Bizzaro N. Definition of reference limits for autoantibodies to thyroid peroxidase and thyroglobulin in a large population of outpatients using an indirect method based on current data. Arch Pathol Lab Med 2008;132:1924–8.10.5858/132.12.1924Search in Google Scholar PubMed

9. Katayev A, Balciza C, Seccombe DW. Establishing reference intervals for clinical laboratory test results: is there a better way? Am J Clin Pathol 2010;133:180–6.10.1309/AJCPN5BMTSF1CDYPSearch in Google Scholar PubMed

10. Pedersen MM, Ornemark U, Rustad P, Steensland H, Loikkanen M, Olafsdottir E, et al. The Nordic Trueness Project 2002: use of reference measurement procedure values in a general clinical chemistry survey. Scand J Clin Lab Invest 2004;64:309–20.10.1080/00365510410002805Search in Google Scholar PubMed

11. Rustad P. Evaluation spreadsheet for X. Available at: http://nyenga.net/norip/X/x.htm. Accessed: 24 May 2017.Search in Google Scholar

12. Friedewald WT, Levy RI, Fredrickson DS. Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clin Chem 1972;18:499–502.10.1093/clinchem/18.6.499Search in Google Scholar

13. Horn PS, Feng L, Li Y, Pesce AJ. Effect of outliers and nonhealthy individuals on reference interval estimation. Clin Chem 2001;47:2137–45.10.1093/clinchem/47.12.2137Search in Google Scholar

14. Bjerner J, Theodorsson E, Hovig E, Kallner A. Non-parametric estimation of reference intervals in small non-Gaussian sample sets. Accredit Qual Assur 2009;14:185–92.10.1007/s00769-009-0490-2Search in Google Scholar

15. Solberg HE. The IFCC recommendation on estimation of reference intervals. The RefVal program. Clin Chem Lab Med 2004;42:710–4.10.1515/CCLM.2004.121Search in Google Scholar PubMed

16. Fraser CG, Hyltoft Petersen P, Libeer JC, Ricos C. Proposals for setting generally applicable quality goals solely based on biology. Ann Clin Biochem 1997;34:8–12.10.1177/000456329703400103Search in Google Scholar PubMed

17. Christensen PA. Reference intervals for the P-Albumin bromocresol purple method. Scand J Clin Lab Invest 2017;77:472–6.10.1080/00365513.2017.1337217Search in Google Scholar PubMed

18. Henriksen LO, Faber NR, Moller MF, Nexo E, Hansen AB. Stability of 35 biochemical and immunological routine tests after 10 hours storage and transport of human whole blood at 21 degrees C. Scand J Clin Lab Invest 2014;74:603–10.10.3109/00365513.2014.928940Search in Google Scholar PubMed PubMed Central

19. Ricos C. Desirable biological variation database specifications. Available at: http://www.westgard.com/biodatabase1.htm. Accessed: 24 May 2017.Search in Google Scholar

20. Warnick GR, Nauck M, Rifai N. Evolution of methods for measurement of HDL-cholesterol: from ultracentrifugation to homogeneous assays. Clin Chem 2001;47:1579–96.10.1093/clinchem/47.9.1579Search in Google Scholar

21. 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;55:341–7.10.1515/cclm-2016-1112Search in Google Scholar PubMed

22. Henny J, Vassault A, Boursier G, Vukasovic I, Mesko Brguljan P, Lohmander M, et al. Recommendation for the review of biological reference intervals in medical laboratories. Clin Chem Lab Med 2016;54:1893–900.10.1515/cclm-2016-0793Search in Google Scholar PubMed

Received: 2017-6-30
Accepted: 2017-8-23
Published Online: 2017-10-14
Published in Print: 2018-2-23

©2018 Walter de Gruyter GmbH, Berlin/Boston

Downloaded on 30.5.2024 from https://www.degruyter.com/document/doi/10.1515/cclm-2017-0574/html
Scroll to top button