Use of the prognostic biomarker suPAR in the emergency department improves risk stratification but has no effect on mortality: a cluster-randomized clinical trial (TRIAGE III)

Martin Schultz, Line Jee Hartmann Rasmussen, Malene H Andersen, Jakob S Stefansson, Alexander C Falkentoft, Morten Alstrup, Andreas Sandø, Sarah L K Holle, Jeppe Meyer, Peter B S Törnkvist, Thomas Høi-Hansen, Erik Kjøller, Birgitte Nybo Jensen, Morten Lind, Lisbet Ravn, Thomas Kallemose, Theis Lange, Lars Køber, Lars Simon Rasmussen, Jesper Eugen-Olsen, Kasper Karmark Iversen, Martin Schultz, Line Jee Hartmann Rasmussen, Malene H Andersen, Jakob S Stefansson, Alexander C Falkentoft, Morten Alstrup, Andreas Sandø, Sarah L K Holle, Jeppe Meyer, Peter B S Törnkvist, Thomas Høi-Hansen, Erik Kjøller, Birgitte Nybo Jensen, Morten Lind, Lisbet Ravn, Thomas Kallemose, Theis Lange, Lars Køber, Lars Simon Rasmussen, Jesper Eugen-Olsen, Kasper Karmark Iversen

Abstract

Background: Risk stratification of patients in the emergency department can be strengthened using prognostic biomarkers, but the impact on patient prognosis is unknown. The aim of the TRIAGE III trial was to investigate whether the introduction of the prognostic and nonspecific biomarker: soluble urokinase plasminogen activator receptor (suPAR) for risk stratification in the emergency department reduces mortality in acutely admitted patients.

Methods: The TRIAGE III trial was a cluster-randomized interventional trial conducted at emergency departments in the Capitol Region of Denmark. Eligible hospitals were required to have an emergency department with an intake of acute medical and surgical patients and no previous access to suPAR measurement. Three emergency departments were randomized; one withdrew shortly after the trial began. The inclusion period was from January through June of 2016 consisting of twelve cluster-periods of 3-weeks alternating between intervention and control and a subsequent follow-up of ten months. Patients were allocated to the intervention if they arrived in interventional periods, where suPAR measurement was routinely analysed at arrival. In the control periods suPAR measurement was not performed. The main outcome was all-cause mortality 10 months after arrival of the last patient in the inclusion period. Secondary outcomes included 30-day mortality.

Results: The trial enrolled a consecutive cohort of 16,801 acutely admitted patients; all were included in the analyses. The intervention group consisted of 6 cluster periods with 8900 patients and the control group consisted of 6 cluster periods with 7901 patients. After a median follow-up of 362 days, death occurred in 1241 patients (13.9%) in the intervention group and in 1126 patients (14.3%) in the control group. The weighted Cox model found a hazard ratio of 0.97 (95% confidence interval, 0.89 to 1.07; p = 0.57). Analysis of all subgroups and of 30-day all-cause mortality showed similar results.

Conclusions: The TRIAGE III trial found no effect of introducing the nonspecific and prognostic biomarker suPAR in emergency departments on short- or long-term all-cause mortality among acutely admitted patients. Further research is required to evaluate how prognostic biomarkers can be implemented in routine clinical practice.

Trial registration: clinicaltrials.gov, NCT02643459 . Registered 31 December 2015.

Keywords: Emergency department; Prognostic biomarkers; Risk stratification.

Conflict of interest statement

Ethics approval and consent to participate

The trial was approved by the board of directors at each participating hospital and the head of each participating department provided consent. The trial was presented to the Regional Ethics Committee, which decided that no formal approval was needed for this cluster-randomized study and in accordance with Danish law it could be conducted without consent of the patients (ref. no. FSP-15003590). At the start of the trial at least one other hospital performed suPAR analysis as a routine test. All processing of personal data followed national guidelines in accordance with Danish law, and the data access and processing were approved by the Danish Data Protection Agency (ref. no. HGH-2015-042, I-Suite 04087) and by the Danish Patient Safety Authority without explicit consent from the participants (ref. no. 3–3013-1744/1).

Consent for publication

Not applicable.

Competing interests

MS, LJHR, MA, and JM have received funding for travel from ViroGates A/S, Denmark. JE-O is named as an inventor in patents for the use of suPAR as a prognostic biomarker. The patents are owned by Copenhagen University Hospital, Amager and Hvidovre, Denmark, and are licensed to ViroGates A/S. JE-O is co-founder, shareholder, and CSO of ViroGates A/S. The remaining authors have no conflicts of interest to declare.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Figures

Fig. 1
Fig. 1
CONSORT flow diagram of the TRIAGE III trial population of patients acutely admitted. EDs: emergency departments, DNPR: National Patient Registry, LABKA: Electronical laboratory database. Full CONSORT checklist is provided in Additional file 3
Fig. 2
Fig. 2
Kaplan-Meier plot displaying survival until end of follow-up. The Kaplan-Meier plot shows survival of patients acutely admitted to two emergency departments stratified by intervention period (measurement of soluble urokinase plasminogen activator receptor, suPAR) and control period (no suPAR measurement). Log-rank test: P = 0.61
Fig. 3
Fig. 3
Plot of all Cox regressions from the TRIAGE III trial. Patients acutely admitted to two emergency departments were allocated to intervention (measurement of soluble urokinase plasminogen activator receptor (suPAR)) or control (no suPAR measurement). The red squares indicate point estimates and the black horizontal lines indicate 95% confidence intervals (CIs). The figure shows hazard ratios based on unadjusted weighted Cox regression models with all-cause mortality at the end of follow-up. The primary outcome of all-cause mortality assessed at the end of follow-up and sensitivity analyses (censoring and per-protocol) are included, as are the subgroups, including cluster and age. The unadjusted model with 30-day all-cause mortality as outcome is also included
Fig. 4
Fig. 4
The area under the curve for mortality in patients acutely admitted. Comparison of prognostic ability of four biomarkers and age at 2 days, 30 days, 60 days, 90 days, and at the end of follow-up. suPAR vs. CRP, all time points: P < 0.001. suPAR vs. haemoglobin, all time points: P < 0.001. SuPAR vs albumin: 2 days: P = 0.37, suPAR vs. albumin at other time points: P < 0.001. CRP: C-reactive protein, suPAR: soluble urokinase plasminogen activator receptor

References

    1. Guttmann A, Schull MJ, Vermeulen MJ, Stukel TA. Association between waiting times and short term mortality and hospital admission after departure from emergency department: population based cohort study from Ontario, Canada. BMJ. 2011;342(jun01 1):d2983. doi: 10.1136/bmj.d2983.
    1. Sun BC, Hsia RY, Weiss RE, Zingmond D, LIang L-J, Han W, McCreath HAS. Effect of emergency department crowding on outcomes of admitted patients. Ann Emerg Med. 2013;61(6):605–611. doi: 10.1016/j.annemergmed.2012.10.026.
    1. Carter EJ, Pouch SM, Larson EL. The relationship between emergency department crowding and patient outcomes: a systematic review. J Nurs Sch. 2014;46:106–115. doi: 10.1111/jnu.12055.
    1. Seymour CW, Cooke CR, Wang Z, Kerr KF, Yealy DM, Angus DC, et al. Improving risk classification of critical illness with biomarkers: a simulation study. J Crit Care. 2013;28:541–548. doi: 10.1016/j.jcrc.2012.12.001.
    1. Schuetz P, Hausfater P, Amin D, Amin A, Haubitz S, Faessler L, et al. Biomarkers from distinct biological pathways improve early risk stratification in medical emergency patients: the multinational, prospective, observational TRIAGE study. Crit Care. 2015;19:377. doi: 10.1186/s13054-015-1098-z.
    1. Kutz A, Hausfater P, Amin D, Amin A, Canavaggio P, Sauvin G, et al. The TRIAGE-ProADM score for an early risk stratification of medical patients in the emergency department - development based on a multi-national, prospective, observational study. PLoS One. 2016;11:1–17.
    1. Kruse O, Grunnet N, Barfod C, Jansen T, Van B, Bakker J, et al. Blood lactate as a predictor for in-hospital mortality in patients admitted acutely to hospital: a systematic review. Scand J Trauma Resusc Emerg Med. 2011;19:74. doi: 10.1186/1757-7241-19-74.
    1. Iversen K, Gotze JP, Dalsgaard M, Nielsen H, Boesgaard SSS, Bay M, et al. Risk stratification in emergency patients by copeptin. BMC Med. 2014;12:80. doi: 10.1186/1741-7015-12-80.
    1. Nickel CH, Bingisser R, Morgenthaler NG. The role of copeptin as a diagnostic and prognostic biomarker for risk stratification in the emergency department. BMC Med. 2012;10:7. doi: 10.1186/1741-7015-10-7.
    1. Barfod C, LundstrØm LH, Lauritzen MMP, Danker JK, Sölétormos G, Forberg JL, et al. Peripheral venous lactate at admission is associated with in-hospital mortality, a prospective cohort study. Acta Anaesthesiol Scand. 2015;59:514–523. doi: 10.1111/aas.12503.
    1. Nickel CH, Messmer AS, Geigy N, Misch F, Mueller B, Dusemund F, et al. Stress markers predict mortality in patients with nonspecific complaints presenting to the emergency department and may be a useful risk stratification tool to support disposition planning. Acad Emerg Med. 2013;20:670–679. doi: 10.1111/acem.12172.
    1. Socorro García A, De La Fuente Hermosín I, Baztán JJ. Serum albumin and total cholesterol as prognostic factors of mortality in very old patients hospitalized by acute illness. Eur Geriatr Med. 2015;6:442–446. doi: 10.1016/j.eurger.2015.04.002.
    1. Cabrerizo S, Cuadras D, Gomez-Busto F, Artaza-Artabe I, Martin-Ciancas F, Malafarina V. Serum albumin and health in older people: review and meta analysis. Maturitas. 2015;81:17–27. doi: 10.1016/j.maturitas.2015.02.009.
    1. Gans SL, Atema JJ, Stoker J, Toorenvliet BR, Laurell H, Boermeester MA. C-reactive protein and white blood cell count as triage test between urgent and nonurgent conditions in 2961 patients with acute abdominal pain. Medicine (Baltimore) 2015;94:e569. doi: 10.1097/MD.0000000000000569.
    1. Oh J, Kim SH, Park KN, Oh SH, Kim YM, Kim HJ, et al. High-sensitivity C-reactive protein / albumin ratio as a predictor of in- hospital mortality in older adults admitted to the emergency department. Clin Exp Emerg Med. 2017;4:19–24. doi: 10.15441/ceem.16.158.
    1. Haupt TH, Petersen J, Ellekilde G, Klausen HH, Thorball CW, Eugen-Olsen J, et al. Plasma suPAR levels are associated with mortality, admission time, and Charlson comorbidity index in the acutely admitted medical patient: a prospective observational study. Crit Care. 2012;16:R130. doi: 10.1186/cc11434.
    1. Rasmussen LJH, Ladelund S, Haupt TH, Ellekilde G, Poulsen JH, Iversen K, et al. Soluble urokinase plasminogen activator receptor (suPAR) in acute care: a strong marker of disease presence and severity, readmission and mortality. A retrospective cohort study. Emerg Med J. 2016;33:769–775. doi: 10.1136/emermed-2015-205444.
    1. Nayak RK, Allingstrup M, Phanareth K, Kofoed-Enevoldsen A. suPAR as a biomarker for risk of readmission and mortality in the acute medical setting. Dan Med J. 2015;62:1–4.
    1. Eugen-Olsen J, Andersen O, Linneberg A, Ladelund S, Hansen TW, Langkilde A, et al. Circulating soluble urokinase plasminogen activator receptor predicts cancer, cardiovascular disease, diabetes and mortality in the general population. J Intern Med. 2010;268:296–308. doi: 10.1111/j.1365-2796.2010.02252.x.
    1. Desmedt S, Desmedt V, Delanghe JR, Speeckaert R, Speeckaert MM. The intriguing role of soluble urokinase receptor in inflammatory diseases. Crit Rev Clin Lab Sci. 2017;54:117–133. doi: 10.1080/10408363.2016.1269310.
    1. Østervig RM, Køber L, Forberg JL, Rasmussen LS, Eugen-Olsen J, Iversen K. suPAR – a future prognostic biomarker in emergency medicine. J Emerg Med. 2015;48:642–643. doi: 10.1016/j.jemermed.2015.04.015.
    1. Thunø M, MacHo B, Eugen-Olsen J. SuPAR: the molecular crystal ball. Dis Markers. 2009;27:157–172. doi: 10.1155/2009/504294.
    1. Sandø A, Schultz M, Eugen-Olsen J, Rasmussen LS, Køber L, Kjøller E, et al. Introduction of a prognostic biomarker to strengthen risk stratification of acutely admitted patients: rationale and design of the TRIAGE III cluster randomized interventional trial. Scand J Trauma Resusc Emerg Med. 2016;24:100. doi: 10.1186/s13049-016-0290-8.
    1. M Schultz, LJH Rasmussen, T Lange et al. TRIAGE III statistical analysis plan. Hvidovre hospital, Information on suPAR. 2016. . Accessed 6 Apr 2018.
    1. Schmidt M, Schmidt SAJ, Sandegaard JL, Ehrenstein V, Pedersen L, Sørensen HT. The Danish national patient registry: a review of content, data quality, and research potential. Clin Epidemiol. 2015;7:449–490. doi: 10.2147/CLEP.S91125.
    1. Lynge E, Sandegaard JL, Rebolj M. The Danish National Patient Register. Scand J Public Health. 2011;39(7_suppl):30–33. doi: 10.1177/1403494811401482.
    1. 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. doi: 10.1016/j.ahj.2013.12.032.
    1. Quan H, Sundararajan V, Halfon P, Fong A, Burnand B, Jean-Christophe L, et al. Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 Administrative Data. Med Care. 2005;43:1130–39.
    1. Quan H, Li B, Couris CM, Fushimi K, Graham P, Hider P, et al. Updating and validating the charlson comorbidity index and score for risk adjustment in hospital discharge abstracts using data from 6 countries. Am J Epidemiol. 2011;173:676–682. doi: 10.1093/aje/kwq433.
    1. Kumar A, Roberts D, Wood KE, Light B, Parrillo JE, Sharma S, et al. Duration of hypotension before initiation of effective antimicrobial therapy is the critical determinant of survival in human septic shock*. Crit Care Med. 2006;34:1589–1596. doi: 10.1097/01.CCM.0000217961.75225.E9.
    1. Puskarich MA, Trzeciak S, Shapiro NI, Heffner AC, Jeffrey A. Outcomes of patients undergoing early Sepsis resuscitation for cryptic shock compared with overt shock. Resuscitation. 2012;82:1289–1293. doi: 10.1016/j.resuscitation.2011.06.015.
    1. Singer M, Deutschman CS, Seymour CW, Shankar-Hari M, Annane D, Bauer M, et al. The third international consensus definitions for Sepsis and septic shock (Sepsis-3) JAMA. 2016;315:801. doi: 10.1001/jama.2016.0287.
    1. Boersma E, Maas AC, Deckers JW, Simoons ML, Davie AP. Early thrombolytic treatment in acute myocardial infarction. Lancet. 1996;348:771–775. doi: 10.1016/S0140-6736(96)02514-7.
    1. De Luca G, Suryapranata H, Zijlstra F, Van’t Hof AWJ, Hoorntje JCA, Gosselink ATM, et al. Symptom-onset-to-balloon time and mortality in patients with acute myocardial infarction treated by primary angioplasty. J Am Coll Cardiol. 2003;42:991–997. doi: 10.1016/S0735-1097(03)00919-7.
    1. Cantor W, Fitchett D, Borgundvaag B, Ducas J, Heffernan M, Cohen EA, et al. Routine early angioplasty after fibrinolysis for acute myocardial infarction. NEJM. 2009;360:2705–2718. doi: 10.1056/NEJMoa0808276.

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