The area under the generalized receiver-operating characteristic curve.

The receiver operating-characteristic (ROC) curve is a well-known graphical tool routinely used for evaluating the discriminatory ability of continuous markers, referring to a binary characteristic. The area under the curve (AUC) has been proposed as a summarized accuracy index. Higher values of the marker are usually associated with higher probabilities of having the characteristic under study. However, there are other situations where both, higher and lower marker scores, are associated with a positive result. The generalized ROC (gROC) curve has been proposed as a proper extension of the ROC curve to fit these situations. Of course, the corresponding area under the gROC curve, gAUC, has also been introduced as a global measure of the classification capacity. In this paper, we study in deep the gAUC properties. The weak convergence of its empirical estimator is provided while deriving an explicit and useful expression for the asymptotic variance. We also obtain the expression for the asymptotic covariance of related gAUCs and propose a non-parametric procedure to compare them. The finite-samples behavior is studied through Monte Carlo simulations under different scenarios, presenting a real-world problem in order to illustrate its practical application. The R code functions implementing the procedures are provided as Supplementary Material.

Effect of Type of Dialysis on CMV-Specific CD8+ T Cells in Kidney Transplant Candidates.

Background: Dialysis is the first procedure to partially replace renal function in end-stage renal diseases, despite several adverse side effects, such as infections. The primary aim of this study was to evaluate the levels of immune CMV-specific CD8+ T cells in a representative cohort of pre-transplant patients receiving hemodialysis (HD) or peritoneal dialysis (PD). The secondary aim was to monitor the CMV-specific CD8+ T cells in kidney transplant recipients undergoing different types of dialysis during the first year following their transplant. Methods: Sixty-nine patients were enrolled and examined with respect to the type of dialysis they received. HLA class I dextramers for CMV were used to determine the quantity of CMV-specific CD8+ T cells. The CMV DNA viral load was also determined. Forty-two of the patients enrolled in the study underwent solid organ transplantation and were analyzed during their first year post-transplantation. Results: Patients receiving HD had fewer CMV-specific CD8+ T cells than those in PD (p < 0.05). We also observed that patients in PD had more CMV-specific CD8+ T cells during the follow-up period than those in HD (p < 0.05), independently of the CMV DNA. Finally, PD patients had a higher frequency of CD8+ Effector-Memory RA T cells (TEMRA) and a lower frequency of central memory T cells (TCM) than did HD patients. Conclusions: These results indicate the better status of CMV-specific T cell immunity in PD patients. The use of CMV T cell dextramers would be advantageous for monitoring the CD8+ T-specific response, enabling the use of prophylactic treatment to be optimized.

Efficient nonparametric confidence bands for receiver operating-characteristic curves.

Receiver operating-characteristic curve is a popular graphical method frequently used in order to study the diagnostic capacity of continuous (bio)markers. In spite of the existence of a huge number of papers devoted to both theoretical and practical aspects of this topic, the construction of confidence bands has had little impact in the specialized literature. As far as the authors know, in the CRAN there are only three R packages providing receiver operating-characteristic curve confidence regions: plotROC, pROC and fbroc. This work tries to fill this gap studying and proposing a new nonparametric method to build confidence bands for both the standard receiver operating-characteristic curve and its generalization for nonmonotone relationships. The behavior of the proposed procedure is studied via Monte Carlo simulations and the methodology is applied on two real-world biomedical problems. In addition, an R function to compute the proposed and some of the previously existing methodologies is provided as online supplementary material.