Objective Circulating cellular communication network factor 1 (CCN1) improves risk stratification in ACS patients and, as we have recently shown, predicts all-cause mortality in patients with dilated cardiomyopathy (DCM). It was the aim of this study to evaluate whether the prognostic role of CCN1 is influenced by an inflammatory phenotype. Methods Patients with a primary diagnosis of DCM, defined as LVEF 117%), were included in this single-center study. Exclusion criteria comprised primary valvular diseases (≥second degree), acute myocarditis, active infectious diseases, pulmonary diseases, cancer, chronic alcoholism, and heart failure of other origins. CCN1 levels were determined in serum at study inclusion using an enzyme-linked immunosorbent assay. The primary endpoint was all-cause mortality during follow-up. An adjusted multivariable cox regression model was used to assess the association between CCN1 and all-cause mortality. We further analysed potential effect modifications by adding either an interaction term between CCN1 and DCMi diagnosis (DCMi vs. DCM). The Meta-Analysis Global Group in Chronic Heart Failure (MAGGIC) score to predict all-cause mortality in HF patients was used as a reference model. The performance of CCN1 in combination with the MAGGIC score and NT-proBNP to predict all-cause mortality was assessed using Cox's proportional-hazards models Results A total of 283 predominantly male DCM patients (78.5% males) with a median age of 55.7 (interquartile range [IQR 48.2, 65.7]) years and predominantly recent onset of disease (3.8 [IQR 1.1, 20.5] months) with a severely reduced LVEF (31 [IQR 25, 37] %), increased LVEDD (67.0 [IQR 62.8, 72.0] mm), and normal eGFR (CKD-EPI) (90.9 [IQR73.9, 102.4] ml/min) were analyzed. During a median follow-up of 12.4 [IQR 10.5, 14.0] years, a total of 107 (37.8%) patients died. Patients in the highest CCN1 tertile had a significantly higher mortality risk than those in the lower tertile (HR 1.82; 95% CI 1.06, 3.14; P=0.030) in adjusted multivariable Cox regression models. Adding CCN1 to the MAGGIC risk score improved c-statistics for prognostic accuracy of all-cause mortality at 6 years (0.624 to 0.645, p=0.012), unlike NT-proBNP (0.624 to 0.630, p=0.123). Patients classified as DCMi (n=128) had significantly lower CCN1 levels compared with classical DCM (n=155) (154.9 (115.4–191.7) vs. 174.7 (130.0–241.0) pg/ml, P=0.022). Inflammation status (DCMi vs DCM) had no significant impact (P interaction = 0.28) on the association of CCN1 and all-cause mortality (Fig. 1). Conclusion CCN1 independently predicts all-cause mortality in DCM patients and improves risk stratification beyond the MAGGIC score. In this pilot cohort, the inflammatory phenotype had no impact on prognostic discrimination. Data are currently analyzed in a validation cohort. Funding Acknowledgement Type of funding sources: Foundation. Main funding source(s): Kerckhoff Research Foundation