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Biomedical subjects

K Mengersen

Publications and source records attributed to K Mengersen.

8 recordsLinked to original sources
PubMed2007

Assessing the combined effect of asbestos exposure and smoking on lung cancer: a Bayesian approach.

We review the literature on the combined association between lung cancer and two environmental exposures, asbestos exposure and smoking, and explore a Bayesian approach to assess evidence of interaction between the exposures. The meta-analysis combines separate indices of additive and multiplicative relationships and multivariate relative risk estimates. By making inferences on posterior probabilities we can explore both the form and strength of interaction. This analysis may be more informative than providing evidence to support one relation over another on the basis of statistical significance. Overall, we find evidence for a more than additive and less than multiplicative relation.

Asbestos↗
PubMed2007

Improving the quality of patient care using reliability measures: a classification tree approach.

This paper considers the application and interpretation of new reliability measures for a classification tree-based medical risk assessment tool. Following the construction of a classification tree reliability measures may then be used to provide an estimate of the precision of the classification and the probability in each terminal node of the classification tree. Identification of unreliable nodes (those that have low precision) in this application may indicate patient groups requiring closer monitoring or scenarios in which further information about the patient is required, thereby providing medical practitioners with an avenue for more informed decision making.

Biometry↗
PubMed2006

Time-series analysis of the risk factors for haemorrhagic fever with renal syndrome: comparison of statistical models.

Three conventional regression models were compared using the time-series data of the occurrence of haemorrhagic fever with renal syndrome (HFRS) and several key climatic and occupational variables collected in low-lying land, Anhui Province, China. Model I was a linear time series with normally distributed residuals; model II was a generalized linear model with Poisson-distributed residuals and a log link; and model III was a generalized additive model with the same distributional features as model II. Model I was fitted using least squares whereas models II and III were fitted using maximum likelihood. The results show that the correlations between the HFRS incidence and the independent variables measured (i.e. difference in water level, autumn crop production and density of Apodemus agrarius) ranged from -0.40 to 0.89. The HFRS incidence was positively associated with density of A. agrarius and crop production, but was inversely associated with difference in water level. The residual analyses and the examination of the accuracy of the models indicate that model III may be the most suitable in the assessment of the relationship between the incidence of HFRS and the independent variables.

Animals↗
PubMed2006

Evaluation of oestrogen and progesterone receptor status in HER-2 positive breast carcinomas and correlation with outcome.

AIM: HER-2/neu amplification occurs in 15-25% of breast carcinomas. This oncogene, also referred to as c-erbB-2, encodes a transmembrane tyrosine kinase receptor belonging to the epidermal growth factor receptor family. HER-2 over-expression is reported to be associated with a poor prognosis in breast carcinoma patients and in some studies is associated with a poorer response to anti-oestrogen therapy. These patients are less likely to benefit from CMF (cyclophosphamide, methotrexate, fluorouracil)-based chemotherapy compared with anthracycline-based chemotherapy. The aim of this study was to evaluate breast carcinomas to determine hormone receptor status and if there is a difference in breast cancer specific survival for HER-2 positive patients. METHODS: A total of 591 breast carcinomas were evaluated using immunohistochemistry (IHC) for oestrogen receptor (ERp), progesterone receptor (PRp) and three different HER-2 antibodies (CB11, A0485 and TAB250). Percentage of tumour cells and intensity of staining for ERp were evaluated using a semiquantitative method. RESULTS: Of the 591 tumours, 91 (15.4%) showed 3+ membrane staining for HER-2 with one or more antibodies. Of these 91 tumours, 41 (45.1%) were ERp+/PRp+, seven (7.7%) were ERp+/PR-, six (6.6%) were ERp-/PRp+ and 37 (40.7%) were ERp-/PR-. Of HER-2 positive tumours, 5.5% showed >80% 3+ staining for ERp compared with 31.8% of 0-2+ HER-2 tumours; 24.2% of HER-2-positive tumours showed 60% or more cells with 2+ or 3+ staining for ERp. Treatment data were available for 209 patients and no difference was observed in breast cancer specific survival (BCSS) with HER-2 status and tamoxifen. CONCLUSION: Oestrogen receptor status cannot be used to select tumours for evaluation of HER-2 status, and oestrogen and progesterone receptor positivity does not preclude a positive HER-2 status. There is a higher proportion of ERp negative tumours associated with HER-2 positivity, however, more than 20% of HER-2 positive tumours show moderate or strong staining for ERp. HER-2 positive patients in this study did not show an adverse BCSS with tamoxifen treatment unlike some previous studies.

Biomarkers, Tumor↗
PubMed2001

Bayesian nonparametric modeling using mixtures of triangular distributions.

Nonparametric modeling is an indispensable tool in many applications and its formulation in an hierarchical Bayesian context, using the entire posterior distribution rather than particular expectations, increases its flexibility. In this article, the focus is on nonparametric estimation through a mixture of triangular distributions. The optimality of this methodology is addressed and bounds on the accuracy of this approximation are derived. Although our approach is more widely applicable, we focus for simplicity on estimation of a monotone nondecreasing regression on [0, 1] with additive error, effectively approximating the function of interest by a function having a piecewise linear derivative. Computationally accessible methods of estimation are described through an amalgamation of existing Markov chain Monte Carlo algorithms. Simulations and examples illustrate the approach.

Algorithms↗
PubMed2000

Socioeconomic status and infant mortality in Australia: a national study of small urban areas, 1985-89.

This study uses small-area data for the period 1985-89 to examine the relationship between socioeconomic status and infant mortality in each of the mainland State capital cities of Australia. An unweighted OLS regression analysis based on 195 Statistical Local Areas (SLAs) that recorded five or more deaths over the reference period shows that standardised infant mortality ratios were significantly higher in areas with greater concentrations of low income families. This relationship was independent of the effects of low birthweight, Aboriginality, ethnicity and variability between each of the capital cities. To test for the robustness of this result a sensitivity analysis was undertaken. This involved (a) performing a Principal Components Analysis on a wide range of sociodemographic variables to derive factor scales that were subsequently included in a regression analysis, (b) using weighted least-squares regression and a Poisson generalised linear model and (c) including in the analysis all SLAs irrespective of the number of infant deaths. The sensitivity analysis supported the results of this study, thus validating the observed association between the socioeconomic characteristics of urban areas and their rate of infant mortality. Despite marked reductions in overall rates of infant mortality over the last century in Australia. socioeconomic disparities were still evident during the mid-to-late 1980s. Whether and to what extent this situation persisted during the early-to-mid 1990s will be known in the near future when the next collection of area-based data are publicly released. The results of this study, therefore, represent an important baseline against which more contemporary national trends can be monitored.

Australia↗