Analytical Error of Cardiac Troponin and Impact on the Performance of Accelerated Diagnostic Protocols in Patients
Nasir Saeed1, Ingar Z Restan2, Ole-Thomas Steiro3
1Department of Clinical Science, University of Bergen, Bergen, Norway.
Insights
Analytical bias in high-sensitivity cardiac troponin (hs-cTn) assays significantly impacts the clinical rule-out rate of accelerated diagnostic protocols (ADPs). This bias may influence patient admission rates and explain variations in ADP rule-out rates.
Area of Science:
- Clinical Chemistry
- Cardiology
- Biomarker Assay Performance
Background:
- Accelerated diagnostic protocols (ADPs) using high-sensitivity cardiac troponin (hs-cTn) assays are crucial for rapid chest pain evaluation.
- Assay-specific analytical bias can potentially affect the diagnostic accuracy and clinical utility of these ADPs.
- Understanding the impact of bias is essential for standardizing ADP performance across different hs-cTn assays.
Purpose of the Study:
- To simulate and quantify the influence of assay-specific bias on the diagnostic performance of 0/1-hour ADPs for three different hs-cTn assays.
- To compare the effects of worst-case scenario bias on sensitivity, specificity, predictive values, and rule-out proportions.
Main Methods:
- 1493 patients with chest pain were included.
- hs-cTnT (Roche), hs-cTnI (Abbott), and hs-cTnI (Siemens) were measured.
- Simulated maximum bias by adding EQA study errors to admission concentrations; evaluated impact on diagnostic metrics and rule-out rates for 0-h and 0-/1-h algorithms.
Main Results:
- Initial sensitivities for 0-h rule-out were >99.0% (hs-cTnI-S, hs-cTnT) and 97.7% (hs-cTnI-A).
- Simulated bias reduced sensitivity for hs-cTnT (to 95.5%) and hs-cTnI-A (to 96.2%) at 0-h, but not hs-cTnI-S.
- For the 0-/1-h algorithm, bias reduced hs-cTnT sensitivity to 95.5% but did not affect hs-cTnI assays (100.0%); rule-out proportions varied significantly with bias.
Conclusions:
- Analytical bias in hs-cTn assays impacts the clinical rule-out rate of 0/1-h ADPs more than diagnostic sensitivity.
- Bias may disproportionately affect the number of patients requiring hospital admission.
- Assay bias is a potential contributor to the heterogeneity observed in reported ADP rule-out rates.
Background:
This study simulates how assay-specific bias influences the diagnostic performance of 0/1-h accelerated diagnostic protocols (ADPs) for 3 different high-sensitivity cardiac troponin (hs-cTn) assays.
Methods:
We included 1493 patients presenting with chest pain. hs-cTnT (Roche Diagnostics), hs-cTnI from Abbott Diagnostics (hs-cTnI-A), and Siemens Healthineers (hs-cTnI-S) were measured at admission. The absolute total error observed in a state-of-the-art EQA study were added to the admission concentrations, producing 6 new variables being adjusted for maximum possible bias (if analytical variation is 0) (+biasmean, +biasmax95%CI, +biasmin95%CI, -biasmean, -biasmax95%CI, -biasmin95%CI). The influence of this "worst-case scenario" bias was compared after calculating sensitivity, specificity, negative and positive predictive values, and rule-out proportion for 30-day myocardial infarction or death for the observed and bias-adjusted hs-cTn concentrations.
Results:
For 0-h rule-out, hs-cTnI-S and hs-cTnT had a sensitivity of >99.0%, compared to 97.7% for hs-cTnI-A. After adding the bias, sensitivity was unchanged for hs-cTnI-S (99.5%), but lower for hs-cTnT (95.5%), and hs-cTnI-A (96.2%). For the 0-/1-h algorithm, adding bias reduced sensitivity to 95.5% for hs-cTnT, while both hs-cTnI algorithms were unchanged (100.0%). Rule-out proportions for 0 h ranged from 0% to 60.0% for hs-cTnT, 28.2%-62.7% for hs-cTnI-A, and 3.5%-35.5% for hs-cTnI-S. For the 0-/1-h algorithm, ranges were 57.7%-75.8% (hs-cTnT), 52.8%-67.5% (hs-cTnI-A), and 45.7%-61.2% (hs-cTnI-S).
Conclusion:
Analytical bias of hs-cTn assays affects the clinical rule-out rate of the 0/1-h ADPs more than the diagnostic sensitivity. Bias may have a greater influence on the proportion of patients requiring hospital admission and may contribute to the heterogeneity of the reported rule-out rates of current ADPs. ClinicalTrials.gov Registration Number: NCT02620202.
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