Assessment and Implication of Prognostic Imbalance in Randomized Controlled Trials with a Binary Outcome – A Simulation Study

Chance imbalance in baseline prognosis of a randomized controlled trial can lead to over or underestimation of treatment effects, particularly in trials with small sample sizes. Our study aimed to (1) evaluate the probability of imbalance in a binary prognostic factor (PF) between two treatment arms, (2) investigate the impact of prognostic imbalance on the estimation of a treatment effect, and (3) examine the effect of sample size (n) in relation to the first two objectives.We simulated data from parallel-group trials evaluating a binary outcome by varying the risk of the outcome, effect of the treatment, power and prevalence of the PF, and n. Logistic regression models with and without adjustment for the PF were compared in terms of bias, standard error, coverage of confidence interval and statistical power.For a PF with a prevalence of 0.5, the probability of a difference in the frequency of the PF≥5% reaches 0.42 with 125/arm. Ignoring a strong PF (relative risk = 5) leads to underestimating the strength of a moderate treatment effect, and the underestimate is independent of n when n is >50/arm. Adjusting for such PF increases statistical power. If the PF is weak (RR = 2), adjustment makes little difference in statistical inference. Conditional on a 5% imbalance of a powerful PF, adjustment reduces the likelihood of large bias. If an absolute measure of imbalance ≥5% is deemed important, including 1000 patients/arm provides sufficient protection against such an imbalance. Two thousand patients/arm may provide an adequate control against large random deviations in treatment effect estimation in the presence of a powerful PF.The probability of prognostic imbalance in small trials can be substantial. Covariate adjustment improves estimation accuracy and statistical power, and hence should be performed when strong PFs are observed

The flavonoid galangin is an inhibitor of CYP1A1 activity and an agonist/antagonist of the aryl hydrocarbon receptor

The effect of the dietary flavonoid galangin on the metabolism of 7,12-dimethylbenz[a]anthracene (DMBA), the activity of cytochrome P 450 1A1 (CYP1A1), and the expression of CYP1A1 in MCF-7 human breast carcinoma cells was investigated. Galangin inhibited the catabolic breakdown of DMBA, as measured by thin-layer chromatography, in a dose-dependent manner. Galangin also inhibited the formation of DMBA-DNA adducts, and prevented DMBA-induced inhibition of cell growth. Galangin caused a potent, dose-dependent inhibition of CYP1A1 activity, as measured by ethoxyresorufin-O-deethylase activity, in intact cells and in microsomes isolated from DMBA-treated cells. Analysis of the inhibition kinetics by double-reciprocal plot demonstrated that galangin inhibited CYP1A1 activity in a non-competitive manner. Galangin caused an increase in the level of CYP1A1 mRNA, indicating that it may be an agonist of the aryl hydrocarbon receptor, but it inhibited the induction of CYP1A1 mRNA by DMBA or by 2,3,5,7-tetrachlorodibenzo-p-dioxin (TCDD). Galangin also inhibited the DMBA- or TCDD-induced transcription of a reporter vector containing the CYP1A1 promoter. Thus, galangin is a potent inhibitor of DMBA metabolism and an agonist/antagonist of the AhR, and may prove to be an effective chemopreventive agent. © 1999 Cancer Research Campaig

Gene expression profiles in human HepG2 cells treated with extracts of the Tamarindus indica fruit pulp

Tamarindus indicaL. (T. indica) or locally known as asam jawa belongs to the family of Leguminosae. The fruit pulp had been reported to have antioxidant activities and possess hypolipidaemic effects. In this study, we attempted to investigate the gene expression patterns in human hepatoma HepG2 cell line in response to treatment with low concentration of the fruit pulp extracts. Microarray analysis using Affymetrix Human Genome 1.0 S.T arrays was used in the study. Microarray data were validated using semi-quantitative RT–PCR and real-time RT–PCR. Amongst the significantly up-regulated genes were those that code for the metallothioneins (MT1M, MT1F, MT1X) and glutathione S-transferases (GSTA1, GSTA2, GST02) that are involved in stress response. APOA4, APOA5, ABCG5 and MTTP genes were also significantly regulated that could be linked to hypolipidaemic activities of the T. indica fruit pulp