The BRCA2 372 HH genotype is associated with risk of breast cancer in Australian women under age 60 years

The BRCA2 N372H nonconservative amino acid substitution polymorphism appears to affect fetal survival in a sex-dependent manner, and the HH genotype was found to be associated with a 1.3-fold risk of breast cancer from pooling five case-control studies of Northern European women. We investigated whether the BR 2 N372H polymorphism was associated with breast cancer in Australian women using a population-based case-control design. The BRCA2 372 genotype was determined in 1397 cases under the age of 60 years at diagnosis of a first primary breast cancer and in 775 population-sampled controls frequency matched for age. Case-control analyses and comparisons of genotype distributions were conducted using logistic regression. All of the statistical tests were two-tailed. The HH genotype was independent of age and family history of breast cancer within cases and controls, and was more common in cases (9.2% versus 6.5%). It was associated with an increased risk of breast cancer, 1.47-fold unadjusted (95% confidence interval, 1.05-2.07; P = 0.02), and 1.42-fold (95% confidence interval, 1.00-2.02; P = 0.05) after adjusting for measured risk factors. This effect was still evident after excluding women with any non-Caucasian ancestry or the 33 cases known to have inherited a mutation in BRCA1 or BRCA2, and would explain similar to3% of breast cancer. The BRCA2 N372H polymorphism appears to be associated with a modest recessively inherited risk of breast cancer in Australian women. This result is consistent with the findings for Northern European women.

Bayesian population pharmacokinetic analysis of sirolimus

Objective: It is usual that data collected from routine clinical care is sparse and unable to support the more complex pharmacokinetic (PK) models that may have been reported in previous rich data studies. Informative priors may be a pre-requisite for model development. The aim of this study was to estimate the population PK parameters of sirolimus using a fully Bayesian approach with informative priors. Methods: Informative priors including prior mean and precision of the prior mean were elicited from previous published studies using a meta-analytic technique. Precision of between-subject variability was determined by simulations from a Wishart distribution using MATLAB (version 6.5). Concentration-time data of sirolimus retrospectively collected from kidney transplant patients were analysed using WinBUGS (version 1.3). The candidate models were either one- or two-compartment with first order absorption and first order elimination. Model discrimination was based on computation of the posterior odds supporting the model. Results: A total of 315 concentration-time points were obtained from 25 patients. Most data were clustered at trough concentrations with range of 1.6 to 77 hours post-dose. Using informative priors, either a one- or two-compartment model could be used to describe the data. When a one-compartment model was applied, information was gained from the data for the value of apparent clearance (CL/F = 18.5 L/h), and apparent volume of distribution (V/F = 1406 L) but no information was gained about the absorption rate constant (ka). When a two-compartment model was fitted to the data, the data were informative about CL/F, apparent inter-compartmental clearance, and apparent volume of distribution of the peripheral compartment (13.2 L/h, 20.8 L/h, and 579 L, respectively). The posterior distribution of the volume distribution of central compartment and ka were the same as priors. The posterior odds for the two-compartment model was 8.1, indicating the data supported the two-compartment model. Conclusion: The use of informative priors supported the choice of a more complex and informative model that would otherwise have not been supported by the sparse data.