Partially linear Bayesian modeling of longitudinal rank and time-to-event data using accelerated failure time model with application to brain tumor data.

Joint modeling of longitudinal rank and time-to-event data with random effects model using a Bayesian approach is presented. Accelerated failure time (AFT) models can be used for the analysis of time-to-event data to estimate the effects of covariates on acceleration/deceleration of the survival time. The parametric AFT models require determining the event time distribution. So, we suppose that the time variable is modeled with Weibull AFT distribution. In many real-life applications, it is difficult to determine the appropriate distribution. To avoid this restriction, several semiparametric AFT models were proposed, containing spline-based model. So, we propose a flexible extension of the accelerated failure time model. Furthermore, the usual joint linear model, a joint partially linear model, is also considered containing the nonlinear effect of time on the longitudinal rank responses and nonlinear and time-dependent effects of covariates on the hazard. Also, a Bayesian approach that yields Bayesian estimates of the model's parameters is used. Some simulation studies are conducted to estimate parameters of the considered models. The model is applied to a real brain tumor patient's data set that underwent surgery. The results of analyzing data are presented to represent the method.

Evaluating the effect of adding Fish oil to Fingolimod on TNF-α, IL1ß, IL6, and IFN-γ in patients with relapsing-remitting multiple sclerosis: A double-blind randomized placebo-controlled trial.

OBJECTIVES: Fish oil is claimed to improve outcome in multiple sclerosis (MS) through anti-inflammatory and antioxidant effects by reducing cytokines including TNF-α, IFN-γ, IL6, and IL-1ß. We aimed to evaluate the efficacy of adding fish oil to Fingolimod on these serum cytokines. PATIENTS AND METHODS: This double-blind randomized trial was conducted during April 2015 to September 2016 in Isfahan, Iran. Patients with diagnosis of relapsing remitting MS, aged 18-45years old and expanded disability status scale (EDSS) ≤5 were enrolled in the study. The experimental group received 1g/day of fish oil. Serum levels of TNF-α, IFN-γ, IL6, and IL-1ß were measured before intervention, 6 months, and 12 months after intervention as the primary outcome. Also, EDSS was evaluated before and at the end of study. RESULTS: 50 patients were recruited initially and nine of them left the study. We found no difference between serum levels of TNF-α, IFN-γ, IL6, and IL-1ß at three time-points between two groups (P-value >0.05). Also, there was no statistically significant difference in the mean EDSS between the experimental group and the control group after 12 months of intervention (P-value=0.08). CONCLUSIONS: Administration of fish oil did not lower the serum levels of TNF-α, IL1ß, IL6, and IFN-γ compared to placebo. Similarly, it did not improve the disability in patients.