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Prognostic relevance of baseline pro- and anti-inflammatory markers in STEMI: an APEX AMI substudy
Sean van Diepen1, L Kristin Newby, Renato D Lopes
1Duke Clinical Research Institute, Duke University Medical Center, Durham, NC, USA; Division of Cardiology, University of Alberta, Edmonton, Alberta, Canada.
Insights
Adding inflammatory biomarkers like interleukin-6 (IL-6) and N-terminal pro-B-type natriuretic peptide (NT-proBNP) to STEMI prediction models offers limited improvement. While IL-6 and NT-proBNP showed individual predictive value, they added little to models already including NT-proBNP.
Area of Science:
- Cardiology
- Biomarkers
- Clinical Prediction Models
Background:
- Acute coronary syndromes involve complex inflammatory responses.
- The utility of baseline inflammatory biomarkers in ST-elevation myocardial infarction (STEMI) prediction models is not well-established.
Purpose of the Study:
- To determine if baseline inflammatory biomarkers improve STEMI clinical prediction models.
- To assess the incremental prognostic value of biomarkers like hsCRP, NT-proBNP, and IL-6.
Main Methods:
- A substudy of the APEX-AMI trial included 772 patients.
- Baseline serum biomarkers, including hsCRP, NT-proBNP, and IL-6, were measured.
- Biomarkers were added to a clinical prediction model for 90-day death, shock, or heart failure.
Main Results:
- hsCRP, NT-proBNP, and IL-6 were independent predictors of clinical outcomes.
- NT-proBNP and IL-6 significantly improved risk prediction models (NRI 8.6% and 8.8%, respectively).
- Adding NT-proBNP provided the most significant improvement, with other biomarkers adding little further value.
Conclusions:
- Multiple inflammatory biomarkers independently predict adverse outcomes in STEMI patients.
- Baseline NT-proBNP is a valuable addition to STEMI prediction models.
- Future research should evaluate inflammatory biomarkers within models that already include NT-proBNP.
Background:
Plaque rupture, acute ischemia, and necrosis in acute coronary syndromes are accompanied by concurrent pro- and anti-inflammatory cascades. Whether STEMI clinical prediction models can be improved with the addition of baseline inflammatory biomarkers remains unknown.
Methods:
In an APEX-AMI trial substudy, 772 patients had a panel of 9 inflammatory serum biomarkers, high sensitivity C reactive protein (hsCRP), and N-terminal pro-B-type natriuretic peptide (NT-proBNP) measured at baseline after randomization. Baseline biomarkers were incorporated into a clinical prediction model for a composite of 90-day death, shock, or heart failure. Incremental prognostic value was assessed using Net Reclassification Improvement (NRI) and Integrated Discrimination Improvement (IDI).
Results:
Individually, several biomarkers were independent predictors of clinical outcome: hsCRP (hazard ratio [HR] 1.12; 95% confidence interval [CI], 1.03-1.21; p=0.007, per doubling), NT-proBNP (HR 1.14; 95% CI, 1.06-1.23; p<0.001, per doubling), interleukin (IL)-6 (HR 1.26; 95% CI, 1.12-1.41;p<0.001, per doubling), and inducible protein-10 (IP-10) (HR 0.86; 95% CI, 0.76-0.98; p<0.025, per doubling). The addition of baseline NT-proBNP (NRI 8.6%, p=0.028; IDI 0.030, p<0.001) and IL-6 (NRI 8.8%, p=0.012; IDI 0.036, p<0.001) improved the clinical risk prediction model and the addition of hsCRP (NRI 6.5%, p=0.069; IDI 0.018, p=0.004) yielded minimal improvement. After incorporating NT-proBNP into the model, the remaining biomarkers added little additional predictive value.
Conclusions:
Multiple inflammatory biomarkers independently predicted 90-day death, shock or heart failure; however, they added little value to a clinical prediction model that included NT-proBNP. Future studies of inflammatory biomarkers in STEMI should report incremental value in a prediction model that includes NT-proBNP.
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