Skip to content
Licensed Unlicensed Requires Authentication Published by De Gruyter December 20, 2022

Verification of sex- and age-specific reference intervals for 13 serum steroids determined by mass spectrometry: evaluation of an indirect statistical approach

  • Sophie C. Anker EMAIL logo , Jakob Morgenstern , Jakob Adler , Maik Brune , Sebastian Brings , Thomas Fleming , Elisabeth Kliemank , Markus Zorn , Andreas Fischer , Julia Szendroedi , Lars Kihm and Johanna Zemva

Abstract

Objectives

Conventionally, reference intervals are established by direct methods, which require a well-characterized, obviously healthy study population. This elaborate approach is time consuming, costly and has rarely been applied to steroid hormones measured by mass spectrometry. In this feasibility study, we investigate whether indirect methods based on routine laboratory results can be used to verify reference intervals from external sources.

Methods

A total of 11,259 serum samples were used to quantify 13 steroid hormones by mass spectrometry. For indirect estimation of reference intervals, we applied a “modified Hoffmann approach”, and verified the results with a more sophisticated statistical method (refineR). We compared our results with those of four recent studies using direct approaches.

Results

We evaluated a total of 81 sex- and age-specific reference intervals, for which at least 120 measurements were available. The overall agreement between indirectly and directly determined reference intervals was surprisingly good as nearly every fourth reference limit could be confirmed by narrow tolerance limits. Furthermore, lower reference limits could be provided for some low concentrated hormones by the indirect method. In cases of substantial deviations, our results matched the underlying data better than reference intervals from external studies.

Conclusions

Our study shows for the first time that indirect methods are a valuable tool to verify existing reference intervals for steroid hormones. A simple “modified Hoffmann approach” based on the general assumption of a normal or lognormal distribution model is sufficient for screening purposes, while the refineR algorithm may be used for a more detailed analysis.


Corresponding author: Sophie C. Anker, Department of Internal Medicine I and Clinical Chemistry, University Hospital Heidelberg, Heidelberg, Germany, E-mail:
Sophie C. Anker and Jakob Morgenstern have contributed equally to this work.
  1. Research funding: Non-declared.

  2. Author contribution: 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: Research involving human subjects complied with all relevant national regulations, institutional policies and is in accordance with the tenets of the Helsinki Declaration (as revised in 2013), and has been approved by the responsible Ethics Board of the Medical Faculty of the University of Heidelberg (S-566/2021).

References

1. Miller, WL, Auchus, RJ. The molecular biology, biochemistry, and physiology of human steroidogenesis and its disorders. Endocr Rev 2011;32:81–151. https://doi.org/10.1210/er.2010-0013.Search in Google Scholar PubMed PubMed Central

2. Gaudl, A, Bae, YJ, Kratzsch, J. Steroid analysis in clinical routine diagnostics – discussing crucial questions. LaboratoriumsMedizin 2017;41:73–9. https://doi.org/10.1515/labmed-2017-0011.Search in Google Scholar

3. Shackleton, C. Clinical steroid mass spectrometry: a 45-year history culminating in HPLC–MS/MS becoming an essential tool for patient diagnosis. J Steroid Biochem Mol Biol 2010;121:481–90. https://doi.org/10.1016/j.jsbmb.2010.02.017.Search in Google Scholar PubMed

4. Hawley, JM, Owen, LJ, Lockhart, SJ, Monaghan, PJ, Armston, A, Chadwick, CA, et al.. Serum cortisol: an up-to-date assessment of routine assay performance. Clin Chem 2016;62:1220–9. https://doi.org/10.1373/clinchem.2016.255034.Search in Google Scholar PubMed

5. Bae, YJ, Gaudl, A, Jaeger, S, Stadelmann, S, Hiemisch, A, Kiess, W, et al.. Immunoassay or LC-MS/MS for the measurement of salivary cortisol in children? Clin Chem Lab Med 2016;54:811–22. https://doi.org/10.1515/cclm-2015-0412.Search in Google Scholar PubMed

6. de Hora, MR, Heather, NL, Patel, T, Bresnahan, LG, Webster, D, Hofman, PL. Measurement of 17-hydroxyprogesterone by LCMSMS improves newborn screening for CAH due to 21-hydroxylase deficiency in New Zealand. Int J Neonatal Screen 2020;6:6. https://doi.org/10.3390/ijns6010006.Search in Google Scholar PubMed PubMed Central

7. Bae, YJ, Zeidler, R, Baber, R, Vogel, M, Wirkner, K, Loeffler, M, et al.. Reference intervals of nine steroid hormones over the life-span analyzed by LC-MS/MS: effect of age, gender, puberty, and oral contraceptives. J Steroid Biochem Mol Biol 2019;193:105409. https://doi.org/10.1016/j.jsbmb.2019.105409.Search in Google Scholar PubMed

8. Eisenhofer, G, Peitzsch, M, Kaden, D, Langton, K, Pamporaki, C, Masjkur, J, et al.. Reference intervals for plasma concentrations of adrenal steroids measured by LC-MS/MS: impact of gender, age, oral contraceptives, body mass index and blood pressure status. Clin Chim Acta 2017;470:115–24. https://doi.org/10.1016/j.cca.2017.05.002.Search in Google Scholar PubMed PubMed Central

9. Kushnir, MM, Rockwood, AL, Roberts, WL, Pattison, EG, Owen, WE, Bunker, AM, et al.. Development and performance evaluation of a tandem mass spectrometry assay for 4 adrenal steroids. Clin Chem 2006;52:1559–67. https://doi.org/10.1373/clinchem.2006.068445.Search in Google Scholar PubMed

10. Shiraishi, S, Lee, PW, Leung, A, Goh, VH, Swerdloff, RS, Wang, C. Simultaneous measurement of serum testosterone and dihydrotestosterone by liquid chromatography-tandem mass spectrometry. Clin Chem 2008;54:1855–63. https://doi.org/10.1373/clinchem.2008.103846.Search in Google Scholar PubMed

11. Hsing, AW, Stanczyk, FZ, Bélanger, A, Schroeder, P, Chang, L, Falk, RT, et al.. Reproducibility of serum sex steroid assays in men by RIA and mass spectrometry. Cancer Epidemiol Biomarkers Prev 2007;16:1004–8. https://doi.org/10.1158/1055-9965.epi-06-0792.Search in Google Scholar

12. Keefe, CC, Goldman, MM, Zhang, K, Clarke, N, Reitz, RE, Welt, CK. Simultaneous measurement of thirteen steroid hormones in women with polycystic ovary syndrome and control women using liquid chromatography-tandem mass spectrometry. PLoS One 2014;9:e93805. https://doi.org/10.1371/journal.pone.0093805.Search in Google Scholar PubMed PubMed Central

13. Jones, GRD, Haeckel, R, Loh, TP, Sikaris, K, Streichert, T, Katayev, A, et al.. Indirect methods for reference interval determination - review and recommendations. Clin Chem Lab Med 2018;57:20–9. https://doi.org/10.1515/cclm-2018-0073.Search in Google Scholar PubMed

14. Ozarda, Y, Ichihara, K, Jones, G, Streichert, T, Ahmadian, R. Comparison of reference intervals derived by direct and indirect methods based on compatible datasets obtained in Turkey. Clin Chim Acta 2021;520:186–95. https://doi.org/10.1016/j.cca.2021.05.030.Search in Google Scholar PubMed

15. CLSI. Defining, establishing, and verifying reference intervals in the clinical laboratory; Approved Guideline - Third Edition. CLSI document EP28-A3c. Wayne, PA: Clinical and Laboratory Standards Institute; 2008.Search in Google Scholar

16. Klawonn, F, Hoffmann, G, Orth, M. Quantitative laboratory results: normal or lognormal distribution? J Lab Med 2020;44:143–50. https://doi.org/10.1515/labmed-2020-0005.Search in Google Scholar

17. Ammer, T, Schützenmeister, A, Prokosch, HU, Rauh, M, Rank, CM, Zierk, J. refineR: a novel algorithm for reference interval estimation from real-world data. Sci Rep 2021;11:16023. https://doi.org/10.1038/s41598-021-95301-2.Search in Google Scholar PubMed PubMed Central

18. Hoffmann, G, Lichtinghagen, R, Wosniok, W. Simple estimation of reference intervals from routine laboratory data. LaboratoriumsMedizin 2016;39:000010151520150104. https://doi.org/10.1515/labmed-2015-0104.Search in Google Scholar

19. Arzideh, F, Özcürümez, M, Albers, E, Haeckel, R, Streichert, T. Indirect estimation of reference intervals using first or last results and results from patients without repeated measurements. J Lab Med 2021;45:103–9. https://doi.org/10.1515/labmed-2020-0149.Search in Google Scholar

20. Gaudl, A, Kratzsch, J, Bae, YJ, Kiess, W, Thiery, J, Ceglarek, U. Liquid chromatography quadrupole linear ion trap mass spectrometry for quantitative steroid hormone analysis in plasma, urine, saliva and hair. J Chromatogr A 2016;1464:64–71. https://doi.org/10.1016/j.chroma.2016.07.087.Search in Google Scholar PubMed

21. Keski-Rahkonen, P, Huhtinen, K, Poutanen, M, Auriola, S. Fast and sensitive liquid chromatography-mass spectrometry assay for seven androgenic and progestogenic steroids in human serum. J Steroid Biochem Mol Biol 2011;127:396–404. https://doi.org/10.1016/j.jsbmb.2011.06.006.Search in Google Scholar PubMed

22. Bundesärztekammer. Neufassung der “Richtlinie der Bundesärztekammer zur Qualitätssicherung laboratoriumsmedizinischer Untersuchungen – Rili-BÄK”. Dtsch Ärztebl; 2019.Search in Google Scholar

23. Dakks. Beschlüsse des Sektorkomitees Medizinische Laboratorien zu Anforderungen der DIN EN ISO 15189:2014 an die Qualität und Kompetenz von Medizinischen Laboratorien; 2017.Search in Google Scholar

24. Özcürümez, MK, Haeckel, R, Gurr, E, Streichert, T, Sack, U. Determination and verification of reference interval limits in clinical chemistry. Recommendations for laboratories on behalf of the working group guide limits of the DGKL with respect to ISO standard 15189 and the guideline of the German medical association on quality assurance in medical laboratory examinations (Rili-BAEK). J Lab Med 2019;43:127–33. https://doi.org/10.1515/labmed-2018-0500.Search in Google Scholar

25. Mezzullo, M, Pelusi, C, Fazzini, A, Repaci, A, Di Dalmazi, G, Gambineri, A, et al.. Female and male serum reference intervals for challenging sex and precursor steroids by liquid chromatography - tandem mass spectrometry. J Steroid Biochem Mol Biol 2020;197:105538. https://doi.org/10.1016/j.jsbmb.2019.105538.Search in Google Scholar PubMed

26. Haeckel, R, Wosniok, W, Arzideh, F. Equivalence limits of reference intervals for partitioning of population data. Relevant differences of reference limits. LaboratoriumsMedizin 2016;40:199–205. https://doi.org/10.1515/labmed-2016-0002.Search in Google Scholar

27. Haeckel, R, Wosniok, W. A new concept to derive permissible limits for analytical imprecision and bias considering diagnostic requirements and technical state-of-the-art. Clin Chem Lab Med 2011;49:623–35. https://doi.org/10.1515/cclm.2011.116.Search in Google Scholar

28. Reed, BG, Carr, BR. The normal menstrual cycle and the control of ovulation. In: Feingold, KR, Anawalt, B, Boyce, A, Chrousos, G, de Herder, WW, Dhatariya, K, et al.. editors. Endotext. South Dartmouth (MA): MDText.com, Inc.; 2000.Search in Google Scholar

29. Bender, S. Alternative Erarbeitung von laborinternen Referenzintervallen für die Beurteilung der Hormonkonzentrationen von 20- bis 45-jährigen Frauen unter Einbeziehung neuer indirekter Verfahren; 2019.Search in Google Scholar

30. Hoffmann, RG. Statistics in the practice of medicine. JAMA 1963;185:864–73. https://doi.org/10.1001/jama.1963.03060110068020.Search in Google Scholar PubMed

31. Shaw, JLV, Cohen, A, Konforte, D, Binesh-Marvasti, T, Colantonio, DA, Adeli, K. Validity of establishing pediatric reference intervals based on hospital patient data: a comparison of the modified Hoffmann approach to CALIPER reference intervals obtained in healthy children. Clin Biochem 2014;47:166–72. https://doi.org/10.1016/j.clinbiochem.2013.11.008.Search in Google Scholar PubMed

32. Holmes, DT. Correct implementation of the Hoffmann method. Clin Biochem 2019;70:49–50. https://doi.org/10.1016/j.clinbiochem.2019.02.007.Search in Google Scholar PubMed

33. Tan, RZ, Markus, C, Vasikaran, S, Loh, TP. Comparison of 8 methods for univariate statistical exclusion of pathological subpopulations for indirect reference intervals and biological variation studies. Clin Biochem 2022;103:16–24. https://doi.org/10.1016/j.clinbiochem.2022.02.006.Search in Google Scholar PubMed

34. Haeckel, R, Wosniok, W. Observed, unknown distributions of clinical chemical quantities should be considered to be log-normal: a proposal. Clin Chem Lab Med 2010;48:1393–6. https://doi.org/10.1515/cclm.2010.273.Search in Google Scholar


Supplementary Material

The online version of this article offers supplementary material (https://doi.org/10.1515/cclm-2022-0603).


Received: 2022-06-22
Accepted: 2022-11-16
Published Online: 2022-12-20
Published in Print: 2023-02-23

© 2022 Walter de Gruyter GmbH, Berlin/Boston

Downloaded on 27.4.2024 from https://www.degruyter.com/document/doi/10.1515/cclm-2022-0603/html
Scroll to top button