The Prognostic and Predictive Value of Melanoma-related MicroRNAs Using Tissue and Serum: A MicroRNA Expression Analysis

The overall 5-year survival for melanoma is 91%. However, if distant metastasis occurs (stage IV), cure rates are = 82%) when = 4 miRNAs were expressed. Moreover, the 'MELmiR-7' panel characterised overall survival of melanoma patients better than both serum LDH and S100B (delta log likelihood=11, p < 0.001). This panel was found to be superior to currently used serological markers for melanoma progression, recurrence, and survival; and would be ideally suited to monitor tumour progression in patients diagnosed with early metastatic disease (stages IIIa-c/IV M1a-b) to detect relapse following surgical or adjuvant treatment. (C) 2015 The Authors. Published by Elsevier B. V

Balanced prior data

The dataset used for this study contained the estimated pharmacokinetic (PK) data after intravenous tobramycin administration to children and adults with and without cystic fibrosis, which was previously analysed using a mixed effects modelling approach [1]. Hence, the following two compartment PK parameters: individual clearance (CL), central volume of distribution (V1), distributional clearance (Q) and peripheral volume of distribution (V2) estimates for each patient were available. For the purpose of this study, these individual PK parameter estimates were considered as data.From the whole dataset [1], only patients aged 1-25 years were included which resulted in data from 570 subjects (6.4 to 120 kg, 204 male patients) treated with tobramycin. Included in the Balanced prior data set are: ID (subejct identifier), AGE (age in years), WT (total body weight in kg), CL (clearance of tobramycin from the central compartment), V1 (volume of distribution of the central compartment), Q (intercompartmental clearance), and V2 (volume of distribution of the peripheral compartment)

Population pharmacokinetic modelling of S-warfarin to evaluate the design of drug–drug interaction studies for CYP2C9

This study is to assess pharmacokinetic (PK) sampling time schedules and trial size requirements of drug-drug interaction (DDI) studies for CYP2C9, based on S-warfarin population PK models. S-warfarin plasma concentrations from eight DDI studies were utilized to develop S-warfarin population PK models. Optimal PK sampling times were obtained that minimized mean squared error of geometric mean of the area under the concentration-time curve (AUC(0-∞)). The powers and type I error rates of testing the equivalences of the geometric means of AUC(0-∞) only and AUC(0-∞) and maximum concentration (C (max)), jointly, were assessed via simulation for two-by-two cross-over designs. The results were compared to those from three bioequivalence sample size calculation methods. Two-compartment population PK models with first order absorption were established for non-Asian and Asian subjects. The optimal PK sampling times of size 17 per individual per period were found to be 0.0, 0.5, 1.0, 2.0, 4.0, 6.0, 10.0, 12.0, 16.0, 24.0, 36.0, 48.0, 60.0, 72.0, 96.0, 120.0, 144.0 h post a single oral dose of 25 mg warfarin. For non-Asian subjects, the minimum numbers of subjects required per trial with the optimal PK sampling schedule to achieve 80% power and 5% type I error rate, ranged from 6 to 19 for the equivalence of AUC(0-∞) and C (max) jointly. It has been demonstrated that appropriately selected PK sampling time points can greatly increase the corresponding power of the study without increasing the number of subjects, especially when the true ratio is near the default bioequivalence boundary (0.8-1.25)

Blood pressure trajectories before death in patients with type 2 diabetes

The aim of this study is to examine the trajectory of blood pressure (BP) over two yrs before death or censoring and its association with mortality in patients (pts) with T2DM. A cohort of 19966 pts with minimum 3 yrs of diabetes duration (DD) was selected from the UK General Practice Research Database (1990-2008), who had four consecutive 6-monthly BP measures over 2 yrs immediately before death or censoring. In the cohort, 46% were female, mean (SD) age of 68 (11) years and 14% had at least one cardiovascular event (CVE) before diagnosis of diabetes. During 6.5 years of median duration of follow-up, 7% pts died, of whom 83% were aged ≥ 68 yrs, 53% and 20% pts had CVE respectively in dead and alive groups. During 2 yrs of follow-up, pts’ systolic and diastolic BP trajectories were significantly higher by 5 and 2 mmHg respectively in those who died, compared to those who were alive (Fig 1). These estimates were adjusted for the effects of age, DD, sex, CVE, glucose-lowering and anti-hypertensive medication usages, baseline weight and HbA1c. Compared to pts with systolic BP level 125 - 130 mmHg, pts with BP 140 mmHg had significantly higher mortality risk by 240% (adjusted odds ratio : 2.4, 95% CI: 1.9, 3.1) and 210% (adjusted odds ratio: 2.1, 95% CI: 1.8, 2.5) respectively. Mortality risk was not higher in patients with BP within 130 - 140 mmHg (Fig 1). The population level analyses of BP trajectories leading up to death are revealing, and provide clear message in terms of the requirement for intensive BP control and related management policies at primary care level. Our findings also establish the J-shaped relationship between systolic BP and mortality

A Bayesian modelling approach with balancing informative prior for analysing imbalanced data

When a dataset is imbalanced, the prediction of the scarcely-sampled subpopulation can be over-influenced by the population contributing to the majority of the data. The aim of this study was to develop a Bayesian modelling approach with balancing informative prior so that the influence of imbalance to the overall prediction could be minimised. The new approach was developed in order to weigh the data in favour of the smaller subset(s). The method was assessed in terms of bias and precision in predicting model parameter estimates of simulated datasets. Moreover, the method was evaluated in predicting optimal dose levels of tobramycin for various age groups in a motivating example. The bias estimates using the balancing informative prior approach were smaller than those generated using the conventional approach which was without the consideration for the imbalance in the datasets. The precision estimates were also superior. The method was further evaluated in a motivating example of optimal dosage prediction of tobramycin. The resulting predictions also agreed well with what had been reported in the literature. The proposed Bayesian balancing informative prior approach has shown a real potential to adequately weigh the data in favour of smaller subset(s) of data to generate robust prediction model

Weight gain in insulin-treated patients by body mass index category at treatment initiation: new evidence from real-world data in patients with type 2 diabetes

AimsTo evaluate, in patients with type 2 diabetes (T2DM) treated with insulin, the extent of weight gain over 2 years of insulin treatment, and the dynamics of weight gain in relation to glycaemic achievements over time according to adiposity levels at insulin initiation.Materials and methodsPatients with T2DM (n = 155 917), who commenced insulin therapy and continued it for at least 6 months, were selected from a large database of electronic medical records in the USA. Longitudinal changes in body weight and glycated haemoglobin (HbA1c) according to body mass index (BMI) category were estimated.ResultsPatients had a mean age of 59 years, a mean HbA1c level of 9.5%, and a mean BMI of 35 kg/m2 at insulin initiation. The HbA1c levels at insulin initiation were significantly lower (9.2-9.4%) in the obese patients than in patients with normal body weight (10.0%); however, the proportions of patients with HbA1c >7.5% or >8.0% were similar across the BMI categories. The adjusted weight gain fell progressively with increasing baseline BMI category over 6, 12 and 24 months (p 2 to a 0.32 kg loss in those with a BMI > 40 kg/m2.ConclusionsDuring 24 months of insulin treatment, obese patients gained significantly less body weight than normal-weight and overweight patients, while achieving clinically similar glycaemic benefits. These data provide reassurance with regard to the use of insulin in obese patients

Pre-, pro-, and synbiotics: do they have a role in reducing uremic toxins? A systematic review and meta-analysis

Objective. This paper assessed the effectiveness of pre-, pro-, and synbiotics on reducing two protein-bound uremic toxins, p-cresyl sulphate (PCS) and indoxyl sulphate (IS). Methods. English language studies reporting serum, urinary, or fecal PCS and/or IS (or their precursors) following pre-, pro-, or synbiotic interventions (>1 day) in human adults were included. Population estimates of differences in the outcomes between the pre- and the postintervention were estimated for subgroups of studies using four meta-analyses. Quality was determined using the GRADE approach. Results. 19 studies met the inclusion criteria, 14 in healthy adults and five in haemodialysis patients. Eight studies investigated prebiotics, six probiotics, one synbiotics, one both pre- and probiotics, and three studies trialled all three interventions. The quality of the studies ranged from moderate to very low. 12 studies were included in the meta-analyses with all four meta-analyses reporting statistically significant reductions in IS and PCS with pre- and probiotic therapy. Conclusion. There is a limited but supportive evidence for the effectiveness of pre- and probiotics on reducing PCS and IS in the chronic kidney disease population. Further studies are needed to provide more definitive findings before routine clinical use can be recommended