Background and objective:In clinical settings with fixed resources allocated to predictive genetic testing for high-risk cancer predisposition genes, optimal strategies for mutation screening programmes are critically important. These depend on the mutation spectrum found in the population under consideration and the frequency of mutations detected as a function of the personal and family history of cancer, which are both affected by the presence of founder mutations and demographic characteristics of the underlying population. The results of multistep genetic testing for mutations in BRCA1 or BRCA2 in a large series of families with breast cancer in the French-Canadian population of Quebec, Canada are reported. Methods: A total of 256 high-risk families were ascertained from regional familial cancer clinics throughout the province of Quebec. Initially, families were tested for a panel of specific mutations known to occur in this population. Families in which no mutation was identified were then comprehensively tested. Three algorithms to predict the presence of mutations were evaluated, including the prevalence tables provided by Myriad Genetics Laboratories, the Manchester Scoring System and a logistic regression approach based on the data from this study. Results: 8 of the 15 distinct mutations found in 62 BRCA1/BRCA2-positive families had never been previously reported in this population, whereas 82% carried 1 of the 4 mutations currently observed in >2 families. In the subset of 191 families in which at least 1 affected individual was tested, 29% carried a mutation. Of these 27 BRCA1-positive and 29 BRCA2-positive families, 48 (86%) were found to harbour a mutation detected by the initial test. Among the remaining 143 inconclusive families, all 8 families found to have a mutation after complete sequencing had Manchester Scores >18. The logistic regression and Manchester Scores provided equal predictive power, and both were significantly better than the Myriad Genetics Laboratories prevalence tables (p,0.001). A threshold of Manchester Score >18 provided an overall sensitivity of 86% and a specificity of 82%, with a positive predictive value of 66% in this population. Conclusion: In this population, a testing strategy with an initial test using a panel of reported recurrent mutations, followed by full sequencing in families with Manchester Scores >18, represents an efficient test in terms of overall cost and sensitivity.

Purpose The aim of this longitudinal study is to quantitatively examine the impact of changes in the mix of eco-controls. More specifically, the purpose of this study is twofold. First, it investigates the nature of change occurring in eco-controls by analyzing three attributes of change, namely, direction of change, scope of change and scale of change. Second, this study investigates the impact of changes in eco-controls by examining to what extent the three attributes of change specifically explain environmental performance. Design/methodology/approach Longitudinal survey approach is used to collect data from a sample of manufacturing firms at two points in time. Findings The results suggest three main conclusions: changes leading to more (less) importance devoted to eco-controls within the organization contribute positively (negatively) to environmental performance; concerted changes on all aspects of the mix of eco-controls contribute more to environmental performance than piecemeal changes on specific aspects of the mix; and the aspect which contributes to environmental performance is not the scale of that change but the mere presence of a credible signal which reflects the seriousness of the intentions. Originality/value This paper contributes to management accounting change literature by breaking down the nature of change of management control practices in attributes (direction, scope and scale) and examining their specific impact on performance.

This paper contributes to the debate on the impact of accounting measurement rules for financial assets. We examine the association between fair value accounting for financial assets and market price volatility for nonfinancial firms in an experimental setting. One group of participants was provided with financial statements where held-for-trading securities were reported at fair market value (FVA). Another group received financial statements with investments reported at historical cost (HCA). Controlling for accounting data, we find no systematic difference between FVA and HCA for three different measures of market price volatility, despite higher earnings volatility and marginally heavier trading under FVA.

Medical genetic services are facing an unprecedented demand for counseling and testing for hereditary breast and ovarian cancer (HBOC) in a context of limited resources. To help resolve this issue, a collaborative oncogenetic model was recently developed and implemented at the CHU de Québec-Université Laval; Quebec; Canada. Here, we present the protocol of the C-MOnGene (Collaborative Model in OncoGenetics) study, funded to examine the context in which the model was implemented and document the lessons that can be learned to optimize the delivery of oncogenetic services. Within three years of implementation, the model allowed researchers to double the annual number of patients seen in genetic counseling. The average number of days between genetic counseling and disclosure of test results significantly decreased. Group counseling sessions improved participants’ understanding of breast cancer risk and increased knowledge of breast cancer and genetics and a large majority of them reported to be overwhelmingly satisfied with the process. These quality and performance indicators suggest this oncogenetic model offers a flexible, patient-centered and efficient genetic counseling and testing for HBOC. By identifying the critical facilitating factors and barriers, our study will provide an evidence base for organizations interested in transitioning to an oncogenetic model integrated into oncology care; including teams that are not specialized but are trained in genetics.