Targeted proteomics improves cardiovascular risk prediction in secondary prevention: the impact of statin treatment?

Abstract

This commentary refers to ‘Targeted proteomics improves cardiovascular risk prediction in secondary prevention’, by N.S. Nurmohamed et al., https://doi.org/10.1093/eurheartj/ehac055 and the discussion piece ‘Different inflammatory pathways underlying cardiovascular risk in secondary prevention’, by N.S. Nurmohamed et al., https://doi.org/10.1093/eurheartj/ehac344. We read with interest the report on ‘Targeted proteomics improves cardiovascular risk prediction in secondary prevention’ from two secondary prevention cohorts which suggest that a proteome-based risk model is superior to a clinical risk model in predicting recurrent ASCVD events. In their derivation and in their validation cohort, 62.8% of patients and 77.5%, respectively, where treated by lipid-lowering drugs. The clinical risk model included systolic blood pressure and the use of antihypertensive medication, total cholesterol, HDL cholesterol but not lipid-lowering treatment. Furthermore, additional analyses were performed to explore the inflammatory pathway by dividing the SMART cohort in a high CRP (2 mg/L) and low CRP (≤2 mg/L) group. We assume that the majority of lipid-lowering treatments were statins. Statins decreased CRP,1 and this effect was specifically assessed in the Jupiter study with rosuvastatin2 in patients with high-sensitivity C-reactive protein level of 2.0 mg/L or more. In this study rosuvastatin reduced high-sensitivity C-reactive protein levels by 37%; interestingly, clinical benefit was attenuated at baseline C-reactive protein levels ≥4 mg/L.3 Thus, we questioned about the bias probably induced by statin treatment when dividing the smart cohort in high and low CRP group and the lack of adjustment with lipid-lowering drugs in the clinical risk model.4