Abstract
BackgroundIdentification of risk is essential to prevent cardiac allograft vasculopathy (CAV) and graft failure due to CAV (GFDCAV) in heart transplant patients, which account for 30% of all deaths. Early CAV detection involves invasive, risky, and expensive monitoring approaches. We determined whether prediction of CAV and GFDCAV improves by adding inflammatory markers to a previously validated atherothrombotic (AT) model.Methods and FindingsAT and inflammatory markers interleukin-6 (IL-6) and C-reactive protein (CRP) were measured in heart biopsies and sera of 172 patients followed prospectively for 8.9±5.0 years. Models were estimated for 5- and 10-year risk using (1) the first post-transplant biopsy only, or (2) all biopsies obtained within 3 months. Multivariate models were adjusted for other covariates and cross-validated by bootstrapping. After adding IL-6 and CRP to the AT models, we evaluated the significance of odds ratios (ORs) associated with the additional inflammatory variables and the degree of improvement in the area under the receiver operating characteristic curve (AUROC). When inflammatory markers were tested alone in prediction models, CRP (not IL-6) was a significant predictor of CAV and GFDCAV at 5 (CAV: p<0.0001; GFDCAV: p = 0.005) and 10 years (CAV: p<0.0001; GFDCAV: p = 0.003). Adding CRP (not IL-6) to the best AT models improved discriminatory power to identify patients destined to develop CAV (using 1st biopsy: p<0.001 and p = 0.001; using all 3-month biopsies: p<0.04 and p = 0.008 at 5- and 10-years, respectively) and GFDCAV (using 1st biopsy: 0.92 vs. 0.95 and 0.86 vs. 0.89; using all 3-month biopsies: 0.94 vs. 0.96 and 0.88 vs. 0.89 at 5- and 10-years, respectively), as indicated by an increase in AUROC.ConclusionsEarly inflammatory status, measured by a patient's CRP level (a non-invasive, safe and inexpensive test), independently predicts CAV and GFDCAV. Adding CRP to a previously established AT model improves its predictive power.
Highlights
Cardiac allograft vasculopathy (CAV), an aggressive form of atherosclerosis, is the leading cause of graft failure in heart-transplant patients surviving beyond the first year [1] and is responsible for up to 30% of all deaths [2]
After adding IL-6 and C-reactive protein (CRP) to the AT models, we evaluated the significance of odds ratios (ORs) associated with the additional inflammatory variables and the degree of improvement in the area under the receiver operating characteristic curve (AUROC)
Since CAV is associated with systemic inflammation, as measured by elevated serum C-reactive protein (CRP) levels [3, 12], we sought to determine in the present study whether a patient’s inflammatory status is independently predictive of CAV and Graft Failure Due to CAV (GFDCAV) and whether adding inflammatory status to our previously established AT models would significantly improve the model’s predictive value
Summary
Cardiac allograft vasculopathy (CAV), an aggressive form of atherosclerosis, is the leading cause of graft failure in heart-transplant patients surviving beyond the first year [1] and is responsible for up to 30% of all deaths [2]. We tested all of these AT markers in risk prediction models and demonstrated that Graft Failure Due to CAV (GFDCAV) very rarely develops in patients who show early absence of fibrin within 9 days post-transplantation (negative predictive accuracy using a single biopsy: 99% at 5 years and 96% at 10 years) [10], and persistence of normal tPA levels over the 3 months (negative predictive accuracies: 99% at 5 years and 95% at 10 years) [10, 11]. Since CAV is associated with systemic inflammation, as measured by elevated serum C-reactive protein (CRP) levels [3, 12], we sought to determine in the present study whether a patient’s inflammatory status is independently predictive of CAV and GFDCAV and whether adding inflammatory status to our previously established AT models would significantly improve the model’s predictive value
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