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Purpose: To compare the efficacy of intravitreal bevacizumab (IVB) injection alone or with intravitreal triamcinolone acetonide (IVB/IVT) versus macular photocoagulation (MPC) in bilateral diabetic macular edema (DME). Methods: In this study we revisited data from a subset of subjects previously enrolled in a randomized clinical trial. The original study included 150 eyes randomized to three treatment arms: 1.25 mg IVB alone, combined injection of 1.25 mg IVB and 2 mg IVT, and focal or modified grid MPC. To eliminate the possible effects of systemic confounders, we selected fellow eyes of bilaterally treated subjects who had undergone different treatments; eventually 30 eyes of 15 patients were re-evaluated at baseline, 6, 12, 18, and 24 months. Using mixed model analysis, we compared the treatment protocols regarding visual acuity (VA) and central macular thickness (CMT). Results: Improvement in VA in the IVB group was significantly greater compared to MPC at months 6 and 12 (P = 0.037 and P = 0.035, respectively) but this difference did not persist thereafter up to 24 months. Other levels of VA were comparable at different follow-up intervals (all P > 0.05). The only significant difference in CMT was observed in favor of the IVB group as compared to IVB/IVT group at 24 months (P = 0.048). Conclusion: Overall VA was superior in IVB group as compared to MPC up to 12 months. Although the IVB group showed superiority regarding CMT reduction over 24 months as compared to IVB/IVT group, it was comparable to the MPC group through the same period of follow up.

More than one series of longitudinal data frequently encountered in biomedical, psychological and clinical research are routinely analyzed under a multivariate linear mixed model framework with underlying multivariate normality assumptions for the random effects and within-subject errors. However, such normality assumption might not offer robust inference if the data, even after being transformed, particularly exhibit skewness. In this paper, we propose a multivariate skew-normal linear mixed model constructed by assuming a multivariate skew-normal distribution for the random effects and a multivariate normal distribution for the random errors. A damped exponential correlation structure is adopted to address the within-subject autocorrelation possibly existing among irregularly observed measures. We present an efficient alternating expectation-conditional maximization (AECM) algorithm for maximum likelihood estimation of parameters. The techniques for estimation of random effects and prediction of future outcomes are discussed. Our proposed model is motivated by, and used for, the analysis of AIDS clinical trials in which we investigate the ‘association-of-the-evolutions’ and the ‘evolution-of-the-association’ of HIV-1 RNA copies and CD4+T cell counts during antiviral therapies. [ABSTRACT FROM AUTHOR]