Recently, we developed multivariate prediction models that combine information from these AT markers (the Established Models in this paper). for other covariates and cross-validated by bootstrapping. After adding Rabbit Polyclonal to ZP4 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 DY131 power to identify patients destined to develop CAV (using 1stbiopsy: 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 1stbiopsy: 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. == Conclusions == Early 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 enhances its predictive power. == Introduction == Cardiac allograft vasculopathy (CAV), an aggressive form of atherosclerosis, is the leading cause of graft failure in heart-transplant patients DY131 surviving beyond the first year[1]and is responsible for up to 30% of all deaths[2]. CAV is similar in many respects to native coronary artery disease (CAD). Unlike native CAD, however, which takes a lifetime to develop, CAV occurs very rapidly, within months to a few years after transplantation and evolves uniformly throughout the entire vasculature. Because of its quick occurrence, early detection is critical to the successful management of transplant patients. Thus, research has focused on identifying biomarkers that can reliably predict future CAV and graft failure. We have shown previously that atherothrombotic (AT) markers detectable very early in biopsied heart tissue are reliably associated with CAV development and graft failure. These markers include the expression of intercellular adhesion molecule-1 (ICAM-1)[3][5], the presence of fibrin[6],[7], and the loss of microvascular antithrombin[8]and tissue plasminogen activator (tPA)[9]. Recently, we tested all of these AT markers in risk prediction models and exhibited that Graft Failure Due to CAV (GFDCAV) very rarely evolves in patients who show early absence of fibrin within 9 days post-transplantation (unfavorable predictive accuracy using a single biopsy: 99% at 5 years and 96% at 10 years)[10], and persistence of normal tPA levels over the next 3 months (unfavorable predictive accuracies: 99% at 5 years and 95% at 10 years)[10],[11]. This obtaining is usually clinically significant, implying that it is possible to identify a subgroup of patients within weeks of transplantation that may be able to safely forgo rigorous monitoring with serial biopsies, a common practice in most transplant centers that is expensive and carries risks for patients. Since CAV is also 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. == Methods == == Patients == The study population consisted of 241 consecutive adult patients with hearts transplanted from August 1989 to August 2004. Patients were included in DY131 the analysis if they survived at least three months after transplantation, experienced serial endomyocardial biopsies performed in the first three months, and experienced their coronary arteries examined angiographically and/or histopathologically for CAV at annual follow-ups. Of the original 241 candidates, 69 patients were excluded from analysis for the following reasons: 29 patients were missing three-month biopsy data, either because they died prior to three months (n = 14) or because transplantation occurred at another institution (n = 15); 38 survived three months but were excluded because of incomplete biopsy data; two survived but were excluded because of missing follow-up coronary evaluations. This left a sample of 172 patients who were followed prospectively until DY131 September 2010 (mean follow-up: 8.95.0 years). The Indiana University or college local Institutional Review Table approved the study protocol and all subjects signed a consent form. Clinical management and end result criteria have been previously explained by Labarrere et al[10]. Endomyocardial biopsies were performed on all 172 donor hearts at the time of transplantation before reperfusion (baseline) and serially during the first three months, with the first post-transplant biopsy obtained within a median 9 days of transplantation. CAV was evaluated in annual angiograms (mean number per patient: 5.251.0). CAV was diagnosed if there were evidence of narrowing or luminal irregularities either in the left main or any main or branch.
Recently, we developed multivariate prediction models that combine information from these AT markers (the Established Models in this paper)