For example, higher CHADS2 and CHA2DS2-VASc scores are also associated with greater bleeding risk, but the HAS-BLED score outperforms the CHADS2 and CHA2DS2-VASc scores for predicting which was also evident in the systematic review by Zhu et al.106 Composite risk scores that include stroke and bleeding end points have also been proposed but have not been shown to perform incrementally better over the individual scores.107,108 The bleeding risk scores in AF are also predictive of bleeding in non-AF populations; for example, in patients with ACS undergoing PCI-stenting.109 Adding more clinical variables marginally improves the predictive value (at least statistically), but the c-indexes still remain approximately 0.6. The addition of biomarkers would all improve the c-indexes (to approximately 0.65) over scores based on clinical risk factors alone. Many of these risk scores have been derived from highly selected clinical trial cohorts (often anticoagulated), with the biomarkers measured at baseline (or within a few months of study entry) then end points determined many years later. Biomarkers are also expensive, and may be subject to laboratory variability, inter-assay differences, diurnal variation and may change in individual patients depending on how risk factors and drug treatments change over time. Many biomarkers (eg, troponin, natriuretic peptides, in ammatory markers, coagulation markers, etc) are also predictive of stroke, bleeding, death, HF, hospitalization,110 and even noncardiovascular conditions such as glaucoma progression (eg, as in the case of growth differentiation factor-15 used in the ABC-bleed score).111 The performance of biomarker-based scores in real-world clinical practice (outside highly selected trial cohorts) has also been disappointing,112,113 given that baseline (or near-baseline) determination of biomarkers to predict bleeding risks after many years is bedeviled by the changing clinical risk pro le of patient s risks as well as modi cation of risk factors. 