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A screening method to spot biomarkers that may warn of serious events in a chronic disease – illustrated by cardiological CLARICOR trial data

  • Per Winkel EMAIL logo , Jørgen Hilden , Janus Christian Jakobsen , Jane Lindschou , Gorm Boje Jensen , Erik Kjøller , Ahmad Sajadieh , Jens Kastrup , Hans Jørn Kolmos , Anders Larsson , Johan Ärnlöv , Mette Bjerre and Christian Gluud
Published/Copyright: August 12, 2021

Abstract

Objectives

To develop a crude screening method for detecting biomarkers which frequently exhibit a rise (or fall) in level prior to a serious event (e.g. a stroke) in patients with a chronic disease, signalling that the biomarker may have an alarm-raising or prognostic potential. The subsequent assessment of the marker’s clinical utility requires costly, difficult longitudinal studies. Therefore, initial screening of candidate-biomarkers is desirable.

Methods

The method exploits a cohort of patients with biomarkers measured at entry and with recording of first serious event during follow-up. Copying those individual records onto a common timeline where a specific event occurs on the same day (Day 0) for all patients, the baseline biomarker level, when plotted against the patient’s entry time on the revised timeline, will have a positive (negative) regression slope if biomarker levels generally rise (decline) the closer one gets to the event. As an example, we study 1,958 placebo-treated patients with stable coronary artery disease followed for nine years in the CLARICOR trial (NCT00121550), examining 11 newer biomarkers.

Results

Rising average serum levels of cardiac troponin T and of N-terminal pro-B-type natriuretic peptide were seen prior to a fatal cardiovascular outcome. C-reactive protein rose prior to non-cardiovascular death. Glomerular filtration rate, seven lipoproteins, and nine newer cardiological biomarkers did not show convincing changes.

Conclusions

For early detection of biomarkers with an alarm-raising potential in chronic diseases, we proposed the described easy procedure. Using only baseline biomarker values and clinical course of participants with coronary heart disease, we identified the same cardiovascular biomarkers as those previously found containing prognostic information using longitudinal or survival analysis.


Corresponding author: Per Winkel, MD Doc Med SCI, Copenhagen Trial Unit, Centre for Clinical Intervention Research, Rigshospitalet, Copenhagen University Hospital, Blegdamsvej 9, Copenhagen, Denmark, Phone: +45 20167959, E-mail:

  1. Research funding: This study was funded by the Copenhagen Trial Unit, Centre for Clinical Intervention Research; the original funders of the CLARICOR trial [please see references 2, 3, and 7], and The Swedish Research Council, Swedish Heart-Lung Foundation; Thuréus Foundation; Marianne and Marcus Wallenberg Foundation, Dalarna University; and Uppsala University.

  2. Author contributions: PW conceived the idea of the method and JH and PW reviewed, discussed, and improved the statistical rigor of the proposed methodology. PW wrote the programs used for computation of the tables and figures. JH, PW, CG, and JCJ prepared the manuscript which was subsequently reviewed by the cardiologists of the CLARICOR trial. 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: Informed consent was obtained from all individuals included in the CLARICOR trial.

  5. Ethical approval: Ethical and regulatory approval was obtained by VEKKF01-076/99; Danish Medicines Agency 2612-975; Danish Data Protection Agency 1999-1200-174; VEK H-B-2009-015.

References

1. Winkel, P, Zhang, NF. Statistical development of quality in medicine. Statistics in practice. Chichester, West Sussex: John Wiley, and Sons Inc; 2007.10.1002/9780470515884Search in Google Scholar

2. Hansen, S, Als-Nielsen, B, Damgaard, M, Helø, OH, Petersen, L, Jespersen, CM, et al.. Intervention with clarithromycin in patients with stable coronary heart disease: the CLARICOR trial design. Heart Drug 2001;1:14–9. https://doi.org/10.1159/000022705.Search in Google Scholar

3. Jespersen, CM, Als-Nielsen, B, Damgaard, M, Hansen, JF, Hansen, S, Helø, OH, et al.. Randomised placebo controlled multicentre trial to assess short term clarithromycin for patients with stable coronary heart disease: CLARICOR trial. BMJ 2006;332:22–7. https://doi.org/10.1136/bmj.38666.653600.55.Search in Google Scholar PubMed PubMed Central

4. Winkel, P, Jakobsen, JC, Hilden, J, Lange, T, Jensen, GB, Kjøller, E, et al.. Predictors for major cardiovascular outcomes in stable ischaemic heart disease (PREMAC): statistical analysis plan for data originating from the CLARICOR (clarithromycin for patients with stable coronary heart disease) trial. Diagn Prognostic Res 2017;1:10. https://doi.org/10.1186/s41512-017-0009-y.Search in Google Scholar PubMed PubMed Central

5. Winkel, P, Jakobsen, JC, Hilden, J, Jensen, GB, Kjøller, E, Sajadieh, A, et al.. Prognostic value of 12 novel biomarkers in stable coronary artery disease. A 10-year follow-up of the placebo group of the Copenhagen CLARICOR trial. BMJ Open 2020;10:e033720. https://doi.org/10.1136/bmjopen-2019-033720.Search in Google Scholar PubMed PubMed Central

6. Winkel, P, Hilden, J, Hansen, JF, Kastrup, J, Kolmos, HJ, Kjoller, E, et al.. Clarithromycin for stable coronary heart disease increases all-cause and cardiovascular mortality and cerebrovascular morbidity over 10 years in the CLARICOR randomised, blinded clinical trial. Int J Cardiol 2015;182:459–65. https://doi.org/10.1016/j.ijcard.2015.01.020.Search in Google Scholar PubMed

7. Gluud, C, Als-Nielsen, B, Damgaard, M, Fischer Hansen, J, Hansen, S, Helø, OH, et al.. Clarithromycin for two weeks for stable coronary heart disease: six-year follow-up of the CLARICOR randomized trial and updated meta-analysis of antibiotics for coronary heart disease. Cardiology 2008;111:280–7. https://doi.org/10.1159/000128994.Search in Google Scholar PubMed PubMed Central

8. Winkel, P, Jakobsen, JC, Hilden, J, Jensen, GB, Kjøller, E, Sajadieh, A, et al.. Prognostic value of routinely available data in patients with stable coronary heart disease. A 10-year follow-up of patients sampled at random times during their disease course. Open Heart 2018;5:e000808. https://doi.org/10.1136/openhrt-2018-000808.Search in Google Scholar PubMed PubMed Central

9. Kjøller, E, Hilden, J, Winkel, P, Frandsen, NJ, Galatius, S, Jensen, G, et al.. Good interobserver agreement was attainable on outcome adjudication in patients with stable coronary heart disease. J Clin Epidemiol 2012;65:444–53. https://doi.org/10.1016/j.jclinepi.2011.09.011.Search in Google Scholar PubMed

10. Kjøller, E, Hilden, J, Winkel, P, Galatius, S, Frandsen, NJ, Jensen, GB, et al.. Agreement between public register and adjudication committee outcome in a cardiovascular randomized clinical trial. Am Heart J 2014;168:197–204. https://doi.org/10.1016/j.ahj.2013.12.032.Search in Google Scholar PubMed

11. Lynge, E, Sandegaard, JL, Rebolj, M. The Danish national patient register. Scand J Publ Health 2011;39(7 Suppl):30–3. https://doi.org/10.1177/1403494811401482.Search in Google Scholar PubMed

12. Helweg-Larsen, K. The Danish register of causes of death. Scand J Publ Health 2011;39(7 30 Suppl):26–9. https://doi.org/10.1177/1403494811399958.Search in Google Scholar PubMed

13. Mishra, RK, Judson, G, Christenson, RH, DeFilippi, C, Wu, AHB, Whooley, MA. The association of five-year changes in the levels of N-terminal fragment of the prohormone brain type natriuretic peptide (NT-proBNP) with subsequent heart failure and death in patients with coronary artery disease. The Heart and Soul Study. Cardiology 2017;137:201–6. https://doi.org/10.1159/000466682.Search in Google Scholar PubMed

14. Collet, JP, Thiele, H, Barbato, E, Barthélémy, O, Bauersachs, J, Bhatt, DL, et al.. 2020 ESC guidelines for the management of acute coronary syndromes in patients presenting without persistent ST-segment elevation: the task force for the management of acute coronary syndromes in patients presenting without persistent ST-segment elevation of the European Society of Cardiology (ESC). Eur Heart J 2021;42:1289–367. https://doi.org/10.1093/eurheartj/ehaa575.Search in Google Scholar PubMed

15. Bjerre, M, Hilden, J, Kastrup, J, Skoog, M, Hansen, JF, Kolmos, HJ, et al.. Osteoprotegerin independently predicts mortality in patients with stable coronary artery disease:the CLARICOR trial. Scand J Clin Lab Invest 2014;74:657–64. https://doi.org/10.3109/00365513.2014.930510.Search in Google Scholar PubMed

16. Bjerre, M, Hilden, J, Winkel, P, Boje Jensen, G, Kjoller, E, Sajadieh, A, et al.. Serum osteoprotegerin as a long-term predictor for patients with stable coronary artery disease and its association with diabetes and statin treatment: a CLARICOR trial 10-year follow-up sub study. Atherosclerosis 2020;301:1–14. https://doi.org/10.1016/j.atherosclerosis.2020.03.030.Search in Google Scholar PubMed

17. Hingorani, AD, van der Windt, DA, Riley, RD, Abrams, K, Moons, KGM, Steyerberg, EW, et al.. Prognosis research strategy (PROGRESS) 4: stratified medicine research. BMJ 2013;346:e5793. https://doi.org/10.1136/bmj.e5793.Search in Google Scholar PubMed PubMed Central

18. Ioannidis, JPA. Why most clinical research is not useful. PLoS Med 2016;13:e1002049. https://doi.org/10.1371/journal.pmed.1002049.Search in Google Scholar PubMed PubMed Central

19. Garattini, S, Jakobsen, JC, Wetterslev, J, Bertele’, V, Banzi, R, Rath, A, et al.. Evidence-based clinical practice: overview of threats to the validity of evidence and how to minimize them. Eur J Intern Med 2016;32:13–21. https://doi.org/10.1016/j.ejim.2016.03.020.Search in Google Scholar PubMed

20. Hemingway, H, Riley, RD, Altman, G. Ten steps towards improving prognosis research. BMJ 2009;339:b4184. https://doi.org/10.1136/bmj.b4184.Search in Google Scholar PubMed

21. Ioannidis, JPA, Tzoulaki, I. What makes a good predictor? The evidence applied to coronary artery calcium score. JAMA 2010;303:1646–47. https://doi.org/10.1001/jama.2010.503.Search in Google Scholar PubMed


Supplementary Material

The online version of this article offers supplementary Material (https://doi.org/10.1515/cclm-2021-0333).


Received: 2021-03-19
Accepted: 2021-07-21
Published Online: 2021-08-12
Published in Print: 2021-10-26

© 2021 Walter de Gruyter GmbH, Berlin/Boston

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