Clinical Biochemistry xxx (2014) xxx–xxx

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Clinical Biochemistry

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IFCC educational materials on selected analytical and clinical applicationsof high sensitivity cardiac troponin assays

Fred S. Apple a,⁎, Allan S. Jaffe b, Paul Collinson c,d, Martin Mockel e, Jordi Ordonez-Llanos f,1, Bertil Lindahl g,Judd Hollander h, Mario Plebani i, Martin Than j, M.H.M. Chan k,1,on behalf of the International Federation of Clinical Chemistry (IFCC) Task Force on Clinical Applications ofCardiac Bio-Markersa Department of Laboratory Medicine and Pathology, Hennepin County Medical Center and University of Minnesota, Minneapolis, MN, USAb Cardiovascular Division, Mayo Clinic, Rochester,MN, USAc Department of Cardiology, St George's Hospital, London, UKd Department of Clinical Blood Sciences, St George's Hospital, London, UKe Department of Cardiology, Charité-University Medicine Berlin, Campus Virchow-Klinikum, Berlin, Germanyf Biochemistry Department, IIB-Sant Pau & Universitat Autònoma, Barcelona, Spaing Department of Medical Sciences, Cardiology, and Uppsala Clinical Research Center, University of Uppsala, Swedenh Department of Emergency Medicine, Thomas Jefferson University, Philadelphia, PA, USAi Department of Laboratory Medicine, University-Hospital, Padova, Italyj Christchurch Hospital, Emergency Department, Christchurch, New Zealandk Department of Chemical Pathology, Prince of Wales Hospital, Hong Kong, China

⁎ Corresponding author. Fax: +1 612 9044229.E-mail address: apple004@umn.edu (F.S. Apple).

1 Chair.

http://dx.doi.org/10.1016/j.clinbiochem.2014.08.0210009-9120/© 2014 The Canadian Society of Clinical Chem

Please cite this article as: Apple FS, et al, IFCtroponin assays, Clin Biochem (2014), http:/

a b s t r a c t

a r t i c l e i n f o

Article history:Received 19 August 2014Received in revised form 27 August 2014Accepted 28 August 2014Available online xxxx

Keywords:High-sensitivity cardiac troponin assaysMyocardial infarctionRisk stratification99th percentileIFCC

In 2011, the IFCC Task Force on Clinical Applications of Cardiac Bio-Markers (TF-CB) was formed, with thepurpose of providing evidence based educational materials to assist all biomarker users, i.e. laboratorians, clini-cians, researchers, in-vitro diagnostics and regulatory agencies, in better understanding important analyticaland clinical aspects of established and novel cardiac biomarkers for use in clinical practice and research. Thegoal of the task force was to promulgate the same information conjointly through the in vitro diagnostic industryto the laboratory, emergency department and cardiologists. The initial undertaking of the TF-CB, which is com-prised of laboratory medicine scientists, emergency medicine physicians and cardiologists, was to address twokey issues pertaining to implementing high-sensitivity cardiac troponin (hs-cTn) assays in clinical practice: the99th percentile upper reference limit (URL) and calculating serial change values in accord with the UniversalDefinition of AMI. The highlights of both concepts from IFCC statements are described.

© 2014 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

Introduction

In 2011, the IFCC Task Force on Clinical Applications of CardiacBio-Markers (TF-CB) was formed, with the purpose of providingevidence-based educational materials to assist all biomarker users,i.e. laboratorians, clinicians, researchers, and in vitro diagnostics andregulatory agencies in better understanding important analytical andclinical aspects of established and novel cardiac biomarkers for use inclinical practice and research. The goal of the task force was to

ists. Published by Elsevier Inc. All rig

C educational materials on s/dx.doi.org/10.1016/j.clinbioc

promulgate the same information in the form of cards, posters andother educational prompts conjointly through the in vitro diagnosticindustry to the laboratory, emergency department and cardiologists.The initial undertaking of the TF-CB, which is comprised of laboratorymedicine scientists, emergency medicine physicians and cardiologists,was to address the two key issues pertaining to implementing high-sensitivity cardiac troponin (hs-cTn) assays in clinical practice. Thekey issues selected were the 99th percentile upper reference limit(URL) and calculating serial change values in accord with the universaldefinition of AMI [1]. Prior to developing the handoutmaterials, didacticdocuments containing the rationale for the advocacies that were takenwere prepared. These educational documents are now posted onthe IFCC website (http://www.ifcc.org/ifcc-news/2014-07-22-tf-cb-documents/). The highlights of both concepts from IFCC statementsare described in these articles.

hts reserved.

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99th Percentile URL

The 99th percentile value is universally endorsed as the referencecut-off to aid in the diagnosis of acute myocardial infarction (AMI) [1].As such, key components that are necessary to implement hs-cTn assaysin practice include:

a) the 99th percentile should be determined in a healthy population[1,2];

b) the 99th percentile from either peer-reviewed literature orfrom manufacturers' product information should be consideredacceptable;

c) the 99th percentile for hs-cTn assays should be measured withan analytical imprecision of ≤10% (% CV; coefficient of variation)[1,2];

d) hs assays should measure cTn above the limit of detection in ≥50%of healthy subjects [2–4];

e) 99th percentile values should be reported as whole numbers only,in ng/L units.

Factors that influence an hs-cTn assay's 99th percentile include:

a) age, because cTn values increase with increasing age, especiallyabove 60 y [5];

b) gender, as men have higher values than women [3,4,6];c) assaymethod, as the 99th percentilemust be determined individually

for each assay, as assays are not standardized;d) specimen type, because the 99th percentile may be different for

serum, plasma and/or whole blood.

99th percentile values should be established or confirmed with theappropriate statistical power for each sex (men and women) using aminimum of:

a) 300 male and 300 female subjects (by sex) [3];b) 20 subjects if confirming 99th percentiles [3], using an appropriate

1-tailed nonparametric statistical method [2].

These analytical, educational suggestions proposed and endorsed bythe IFCC TF-CB are the first of many steps to better harmonize the globaluse and reporting of hs-cTn assays in practice.

Calculating serial change values (Delta)

Determining the degree of serial changes in cardiac troponin valuesis the bestway to differentiate between patientswhohave acute cardiacinjury of any kind, including AMI from those that have more chronicelevations, many of which may be related to structural heart disease[1,7]. This approach is necessitated because there often are elevationsof cTn values, particularly with those assays that are more sensitive,i.e. the “high-sensitivity” assays. Key to this determination is theassumption that the timing of the patient's presentation allows forsuch an evaluation.

The development of criteria for such an analysis is complex. Importantfactors include the specific assay involved, the timing of the evaluation,spontaneous change in patients without acute cardiac injury, the anat-omy that led to the acute problem, the criteria being used to make the“gold standard” diagnosis and whether one is attempting to improvediagnostic sensitivity and or specificity [7–12]. It is important to recog-nize that criteria that rely on more marked changes will improvespecificity at the expense of sensitivity, whereas those that are lessmarked will improve sensitivity at the expense of specificity [8,9].Thus, considerable thought and interaction between the stakeholderswho use these assays is suggested.

The calculation of Delta change values (also called relative changevalues) for hs-cTn assays can be viewed as a simple task of generatingcriteria and then evaluating whether or not changes in either absolute

Please cite this article as: Apple FS, et al, IFCC educational materials on stroponin assays, Clin Biochem (2014), http://dx.doi.org/10.1016/j.clinbioc

or relative numbers are associated with higher diagnostic accuracy foracute events such as AMI. However, the reality is that it is a muchmore complex task. Issues that need to be kept in mind include [9]:

Problems related to the gold standard diagnosis of AMI:a. The gold standard for AMI diagnosis should always be based

on delta changes, assuming the timing allows for that. Deltachanges are essential to rule out AMI in patients with chestdiscomfort. Solitary elevations alone are inadequate becausethere can be elevated cTns due to structural heart diseaseincluding coronary artery disease or non-cardiac diseaseslike infection, metabolic disorders, etc.

b. The gold standard diagnosis may not always be accurate. In arecent manuscript by Hammarsten et al., 26% of the patientsdiagnosed with MIs had less than a 20% delta change [13].The authors reported that many of these patients had takensubstantial time prior to reporting to the hospital and warnedthat late presenters might not manifest significant changesin cTn values. In addition, some of these patients may havehad elevations due to stable coronary artery disease andmay have been included as having AMI due to diagnosticmisclassification [9].

c. If an insensitive diagnostic standard, such as an insensitiveassay or high cutoff values is utilized to define acute events,then it will include only larger events and the values, whethercalculated as percentages or absolute changes will beartifactually increased [14].

d. Most large events have very marked increases in cTn valuesand those individuals who have clearly non-cardiac eventswill not have any changes. Patients in between, such asthose with atrial fibrillation but no coronary artery disease,need to be clinically identified and taken into account, theyare likely to have some change in values [13]. Thus, theadmixture of patients used as controls will influence thecalculations regardless of the approach.

Problems related with spontaneous variation and timing.a. Small delta changes could be due to spontaneous variation or

analytic variation. Small changes with very low values lead tomarked percentage changes and small absolute changes maycause values to cross the critical 99th percentile value. Thus,even modest analytical or biological variation can lead tospontaneous changes in patients with non-acute diagnoses.These changes have been shown to overlap those seenin patients with acute diagnoses [15]. This could be due tooverlap in patients with disease but it also has at least thepotential to include some normal subjects with high biologicalvariation.

b. Timing is essential for an accurate delta calculation [9,12]. Thetiming ofmost presentations should allow for the calculation ofthe delta. However, delta changes may be absent at or nearpeak values or when the presentation is late after an acuteevent. In addition, one needs to obtain samples frequentlyenough to make sure that the intermittent release known tooccur in patients with acute coronary artery disease is not aconfounder. Ideally, two values three hours apart might beconsidered but may not be applicable to all patients.

c. Comparing the value of delta changes across approaches andfor clinical use should rely on fixed intervals.

d. cTn release is flow related. Thus, an event that occurs in apatient with an open artery, such as many patients with type2 AMI, will have greater egress to the circulation rapidly than

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will an event that occurs behind a totally occluded coronaryvessel but both need to be accommodatedwithin delta changerules. This provides some degree of difficulty because thetiming of these 2 events may well be substantially different.

Problems related to assay methods

a. Change valueswill need to bedeveloped for each assay. Assaysare different, so the use of a conjoint set of criteria would beideal but is not likely to occur in the near term [7,9].

b. All assays can have analytical and pre-analytical issues. Thesecan increase or decrease values. When this occurs, it can havean effect on the calculation of the delta.

Problems related to the delta changes calculations themselves

a. Most “optimal delta values”have beenderived byROC analysis.This analysis makes the assumption that sensitivity and speci-ficity are equally important. It may well be that in manycircumstances sensitivitymay bemore important and in othersspecificity may be more important. Thus, a metric developedfrom ROC analysis may not meet the clinical needs of specificpatient groups [13,14].It thusmight be advised that an institutional decision should bemade about this critical element by all stakeholders involved.These considerations should be conjointly determined be-tween the laboratory community and the clinical community.

b. The calculations need to be taken under advisement in regardto the number of decimal points the values are reported toand whether or not rounding is appropriate or inappropriate.

c. There is a very uncomfortable issue of naming that has been as-siduously ignored in the literature. There will be some patientsseen in whom the clinical diagnosis is unstable angina whohave elevated troponins with a pattern that does not change.The appropriate diagnosis in these patients is unclear. Theycould have unstable angina with an elevated troponin due tostructural heart disease or other comorbidities, or even due tocoronary artery disease. Alternatively, they could be patientsin whom the timing of the event under evaluation is unclear.How one designates these individuals diagnostically and dealswith them therapeutically needs to be taken under advisement.

So, howdoes one calculate delta changes? The above suggests that noprotocol for evaluation of delta change will be perfect. What is thereforenecessary is information concerning the relative sensitivity and specific-ity of each of the approaches advocated. Then, one can utilize the pretestprobability of disease to make a priori decisions about which metrics touse. Calculating the pretest probability is a clinical challenge, which willbe supported by appropriate scores under development in the future.

At present, two approaches have been advocated for calculating asignificant delta change. The first is a percentage change predicated usu-ally on conjoint biologic and analytic variation,which has been called bi-ological variation (BV) [7]. This approach can be problematic because BVis in part dependent on the type of equipment used to generate themea-surements. Some instruments are more precise than others even withthe same assay reagents. Thus, for any given instrument, BV may vary[16]. BV may also be dependent on the population studied. The studiesthus far completed suggest that a range of reference change values cal-culated from BV is between 30% and 85%. This has led some to suggestthat an appropriate mean value is in the range of 50%, and such algo-rithms have been published [17] but not prospectively validated. Themajority of comparative data looking at this metric versus the secondmetric that has been advocated for use, one that utilizes absolute num-bers, have suggested that absolute valuesmay be superior [10,11]. Thesedata are predicated onROC analysis but find that values dependinguponthe assay in absolute terms aremore valuable in terms of explaining and

Please cite this article as: Apple FS, et al, IFCC educational materials on stroponin assays, Clin Biochem (2014), http://dx.doi.org/10.1016/j.clinbioc

refining diagnostic yield despite the caveats indicated above. It appearsthatmost of the benefit may be at higher values wheremarked percent-age changesmight not be expected but where the absolute changes willbe less than BV. Finally, an additional issue relates to the calculation itselfand whether one wishes to use a one- or two-tailed test and whetherlogarithmic transformation is used to normalize what is usually not anormally distributed population of values.

For clinical use, the calculation of thedelta change value is not simpleand we have concerns over approaches using cohorts being evaluatedin less than ideally comprehensive manners that do not adhere to thecriteria delineated above. Good studies rigorously done are essential.

Acknowledgements

The Task Force acknowledges the invaluable assistance of thecorporate representatives who participated in discussions to finalizethe educational materials: (Abbott) Tricia Ravalico, Jessie Shih; (Alere)Rick San George; (Beckman) Bernard Cook; (Siemens) AlessandroOrtisi, Laurent Samson; (Randox) Mark Campbell; (Roche) SylvieMenassanch-Volker, Hans Jüergen-Loyda; (Instrumentation Laboratory)Xavier Nogue; (Radiometer) Eric Heilmann (previously); and (ThermoFisher) Joërn Vollert.

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