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; P <0.001) and multivariable (adjusted hazard ratio, 2.2 95% CI, 1.0–4.7; P =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; P <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; P <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.