Dynamic Risk Stratification in ACS

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Presentation transcript:

Dynamic Risk Stratification in ACS Mark Y. Chan Associate Professor Yong-Loo Lin School of Medicine Senior Consultant National University Heart Centre, Singapore

Question 1: Does a change in biomarker levels over time confer a change in prognosis in patients with ACS?

Initial NT-proBNP and hs-CRP Re-assess NT-proBNP and hs-CRP 6 month-baseline NT-proBNP NT-proBNP NT-proBNP Mortality risk 6 month-baseline hs-CRP hs-CRP MI risk hs-CRP Hospitalization for NSTEACS Escalate or modify management? Re-measure NT-proBNP and hs-CRP? Initial treatment Baseline 6 months 30 months

TRILOGY-ACS Biomarker Substudy Presented at AHA 2014

Changes in NT-proBNP and hs-CRP (delta) from baseline to 6 months

Adjusted hazard ratio of delta NT-proBNP

Adjusted hazard ratio of delta hs-CRP for CV events

Quantitative changes in risk associated with changes in biomarker levels

Question 2: For expensive prognostic biomarkers like miRNA, what is the best timepoint to measure them

miRNAs measured at baseline and 30 days Presented at AHA 2016

Differential prediction of MI and CV death risk by miRs measured at baseline and 30 days

Conclusions An increase/decrease of NT-proBNP over time is quantitatively associated with an increase/decrease in risk of CV death An increase/decrease of hs-CRP over time is quantitatively associated with an increased/decrease in MI risk. miRs measured at 30-day are far greater prognostic value for recurrent ischemic events than miRs measured at baseline

Prognostic biomarker studies must not only study the association between measurements at individual timepoints and events, they must also investigate the delta between timepoints For multi-marker platforms, different markers may have differential prognostic value at different phases in the longitudinal evolution of the disease

Duke Molecular Physiology Lab Acknowledgements Duke Molecular Physiology Lab Svati Shah, Lydia Kwee, Libby Grass Duke Clinical Research Institute Matthew Roe, Megan Neely