Bayesian joint modelling of longitudinal and time to event data: a methodological review.

Background: In clinical research, there is an increasing interest in joint modelling of longitudinal and time-to-event data, since it reduces bias in parameter estimation and increases the efficiency of statistical inference. Inference and prediction from frequentist approaches of joint models have been extensively reviewed, and due to the recent popularity of data-driven Bayesian approaches, a review on current Bayesian estimation of joint model is useful to draw recommendations for future researches.

Methods: We have undertaken a comprehensive review on Bayesian univariate and multivariate joint models.

Rapid immunoprofiling of cytokines, chemokines and growth factors in patients with active rheumatoid arthritis using Luminex Multiple Analyte Profiling technology for precision medicine.

Objectives: Rheumatoid arthritis (RA) is a chronic autoimmune inflammatory disease of unknown etiology, characterised by symmetric erosive synovitis, leading inevitably to the destruction of cartilage and bone as well as bursa and tendon sheaths of joints. Our aim of this study was to decipher the differential expression of cytokines, chemokines and growth factors in the plasma of RA patients with active disease, using magnetic bead-based Luminex Multiple Analyte Profiling (xMAP) technology, for precision medicine.

Methods: We obtained plasma samples from RA patients (n=25) from the Rheumatology Clinic at the King Abdulaziz University Hospital (KAUH), Jeddah, Kingdom of Saudi Arabia (KSA) after written informed consent for their inclusion in this study.