Katrin Hruska discusses the usefulness of biomarkers in Emergency Medicine. All biomarkers are awesome predictors of badness. Elevated hS-troponins after non-cardiac surgery or an acute exacerbation of COPD are associated with increased mortality. In seemingly healthy people, elevated D-dimer levels are associated with increased mortality. Similarly, NT-proBNP levels predict mortality in patients with end-stage renal disease. A biomarker, in its broadest sense, is defined as “a characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention” (NIH Biomarkers Definitions Working group, 2001). This definition includes everything from laboratory tests to blood pressure measurements or an ultrasound scan. The clinical assessment in the Emergency Department is based on the subjective history of the patient and all available biomarkers (and their change over time). If we assume that biomarkers are objectively measured, there is an overestimation of their individual importance. As Katrin explains, over testing and over diagnosis have serious consequences. Not only for patients but also for the healthcare system. In a clinical context the ease of getting a laboratory test leads to a lower threshold for testing. This increases testing without affecting relevant clinical endpoints. Also, when a biomarker becomes part of the standardised workup for a certain symptom, primary care centres and emergency telephone services will refer patients to the Emergency Department for testing, even when the pretest probability is low. Katrin contends this bias is not an inherent problem of biomarkers themselves, but of the decision-making process of clinicians. The human brain fears uncertainty. Anything that adds to the feeling of knowing is rewarding, which is the most probable explanation of over testing in settings where medico-legal risks for the clinicians are low. There is an ever-increasing number of patients seeking to rule out serious conditions by relying on biomarker testing to provide certainty.

1. Bringing sexy back?
biomarkers - useful or useless?
Katrin Hruska

2. No disclosures

4. N Engl J Med 2015; 373:1916-1925November 12,

5. ”in the near future, high suPAR levels probably will
inform physician-patient conversations about
preventing kidney disease"

6. ”rigorous NEJM study is a significant breakthrough in preventive
medicine"

8. Groundbreaking blood test predicts kidney disease
FIVE YEARS BEFORE symptoms appear

9. ”Trisaq's product strategy has been
designed to yield early proof-of-
concept as well as commercialization
opportunities”
”Conservatively estimated, Trisaq's current pipeline
of products can benefit about 15-25% of all CKD
patients and their combined sales potential well
exceeds $1 billion.

10. Disclosure forms provided by the authors are available with the full text of this article at NEJM.org.

12. Novel Blood Biomarker May Predict CKD Risk
Outcomes studies necessary to prove clinical efficacy

13. suPAR: Strong and independent predictor of survival

16. Rather young and
healthy than old and
sick

18. The primary endpoint was to create an accurate prognostication
score of death by combining APACHE II score and serum suPAR.

19. 💀
14 ng/mL
3-70 ng/mL 1-65 ng/mL
😀
9 ng/mL
suPAR levels and survival in sepsis
range:

20. Copyright ©2012 Giamarellos-Bourboulis et al.; licensee BioMed Central Ltd. Crit Care. 2012; 16(4): R149.

21. suPAR
Copyright ©2012 Giamarellos-Bourboulis et al.; licensee BioMed Central Ltd. Crit Care. 2012; 16(4): R149.

22. APACHE II

23. Copyright ©2012 Giamarellos-Bourboulis et al.; licensee BioMed Central Ltd. Crit Care. 2012; 16(4): R149.

24. Copyright ©2012 Giamarellos-Bourboulis et al.; licensee BioMed Central Ltd. Crit Care. 2012; 16(4): R149.

25. Mortality%
0
10
20
30
40
i ii iii iv
Apache II<17 Apache II≥17
suPAR
≥12
suPAR
≥12
”validated” in a Swedish cohort

26. Mortality%
0
10
20
30
40
i ii iii iv
suPAR
≥12
suPAR
≥12
the high mortality in stratum (ii) may be due to small number of patients in
this group (n = 21) and chance variations in mortality. Apart from that
aberration, the findings validate those from the larger Greek study
”validated” in a Swedish cohort

27. ”this strong discriminative prognostic score developed in Greek
patients was validated in a cohort of Swedish patients”
”There is no doubt that suPAR has strong prognostic value in ICU
patients. However, in many cases this knowledge may not lead to
lifesaving interventions, as limited treatment options are efficient
in severely ill sepsis patients”

28. Prediction of 30 day mortality compared
to Danish Emergency Process Triage

30. Agreement in 55% of cases
”additional biomarkers other than CT are needed"
”we acknowledge the editorial and statistical contribution of
Leslie S. Prichep, PhD”

31. ”we acknowledge the editorial and
statistical contribution of Leslie S.
Prichep, PhD”

32. A biomarker is a characteristic that is objectively measured
and evaluated as an indicator of normal biological processes,
pathogenic processes or
pharmacologic responses to a therapeutic intervention

33. A clinical endpoint is a characteristic or variable that reflects how a patient
feels, functions or survives
A surrogate endpoint is a biomarker that is intended to substitute for a
clinical endpoint

34. A clinical endpoint is a characteristic or variable that reflects how a patient
feels, functions or survives
A surrogate endpoint is a biomarker that is intended to substitute for a
critical endpoint

35. Image: Bengt Nyman
SNTF

36. photo: Michele di Trani
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