Adjuvant trastuzumab chemotherapy in early breast cancer: meta-analysis of randomised trials and cost-effectiveness analysis.

Background: Trastuzumab has a large financial impact on the average cost of breast cancer treatment. This study reassessed the cost-effectiveness of listing the drug on the subsidised Australian Pharmaceutical Benefits Scheme.

Methods: Using a continuous-time, discrete-event microsimulation model, we examined the effect of 1-year trastuzumab on the total number of disability-adjusted life-years (DALYs) averted among Australian women with human epidermal growth factor receptor-2 (HER2) positive early breast cancer.

Non-specific symptoms in adult patients referred to a Lyme centre.

Objectives: There is controversy whether non-specific symptoms can be related to previous Lyme borreliosis (LB). Positive serology can be considered a proxy for previous or persistent LB. We assessed non-specific symptoms and serology in patients suspected of LB referred to a Lyme centre.

Estimation of a Relative Risk Effect Size when Using Continuous Outcomes Data: An Application of Methods in the Prevention of Major Depression and Eating Disorders.

Introduction: The raw mean difference (RMD) and standardized mean difference (SMD) are continuous effect size measures that are not readily usable in decision-analytic models of health care interventions. This study compared the predictive performance of 3 methods by which continuous outcomes data collected using psychiatric rating scales can be used to calculate a relative risk (RR) effect size.

Methods: Three methods to calculate RR effect sizes from continuous outcomes data are described: the RMD, SMD, and Cochrane conversion methods.

A generalized pairwise modelling framework for network meta-analysis.

Indirect comparison methods are used to measure the effect of two treatments that were each compared against a similar control group in a meta-analysis. The network meta-analysis method extends this to multiple treatments which are assessed simultaneously. Currently, there exist Bayesian and multivariate modelling approaches to these analyses, but these are computationally intensive and rely on assumptions that may not be valid in practice.

A new improved graphical and quantitative method for detecting bias in meta-analysis.

Detection of publication and related biases remains suboptimal and threatens the validity and interpretation of meta-analytical findings. When bias is present, it usually differentially affects small and large studies manifesting as an association between precision and effect size and therefore visual asymmetry of conventional funnel plots. This asymmetry can be quantified and Egger's regression is, by far, the most widely used statistical measure for quantifying funnel plot asymmetry.