Extracellular Matrix Proteins Improve Risk Prediction in Patients Undergoing Transcatheter Aortic Valve Replacement.

Background: Cardiac fibrosis is common in patients with severe aortic stenosis and an independent predictor of death. Therefore, we examined the additional value of circulating fibrosis markers as a putative biomarker platform to identify patients with aortic stenosis undergoing transcatheter aortic valve replacement (TAVR) who are at a higher risk of death.

Methods: In this study, 2-year survival analyses were conducted in 378 consecutive patients undergoing TAVR to evaluate the association between fibrosis marker and risk of adverse long-term outcome. Implementation of fibrosis marker into TAVR risk stratification was tested by a machine-learning algorithm.

Results: Among 20 circulating fibrosis markers involved in pathological extracellular matrix remodeling, high tissue inhibitor of metalloproteinase-1 (TIMP-1) levels independently predicted risk of death in univariable (hazard ratio, 5.0 [95% CI, 2.6-9.7]; <0.001) and multivariable (adjusted hazard ratio, 2.2 [95% CI, 1.0-4.7]; =0.046) Cox regression analyses. Consequently, higher TIMP-1 levels offered a significantly higher overall prediction of reduced survival compared with the conventional Society of Thoracic Surgeons Predicted Risk of Mortality score (area under the curve, 0.753 [95% CI, 0.682-0.824] versus area under the curve, 0.656 [95% CI, 0.578-0.734]; <0.05). Applying an independent machine-learning algorithm allowed identification of a simple combination of 2 biomarkers (TIMP-1 and high-sensitivity cardiac troponin T) with superior prognostic value compared with Society of Thoracic Surgeons Predicted Risk of Mortality alone (area under the curve, 0.757 [95% CI, 0.686-0.828] versus 0.656 [95% CI, 0.578-0.34]; <0.05).

Conclusions: Circulating TIMP-1 is an independent predictor of reduced 2-year overall survival in patients undergoing TAVR. Combined with high-sensitivity cardiac troponin T, circulating TIMP-1 should be incorporated into risk stratification to identify patients undergoing TAVR who are at a higher risk of death.