Gray matter volume in women with the BRCA mutation with and without ovarian removal: evidence for increased risk of late-life Alzheimer's disease or dementia.

OBJECTIVE: Ovarian removal prior to spontaneous/natural menopause (SM) is associated with increased risk of late life dementias including Alzheimer's disease. This increased risk may be related to the sudden and early loss of endogenous estradiol. Women with breast cancer gene mutations (BRCAm) are counseled to undergo oophorectomy prior to SM to significantly reduce their risk of developing breast, ovarian, and cervical cancers. There is limited evidence of the neurological effects of ovarian removal prior to the age of SM showing women without the BRCAm had cortical thinning in medial temporal lobe structures. A second study in women with BRCAm and bilateral salpingo-oophorectomy (BSO) noted changes in cognition. METHODS: The present, cross-sectional study examined whole-brain differences in gray matter (GM) volume using high-resolution, quantitative magnetic resonance imaging in women with BRCAm and intact ovaries (BRCA-preBSO [study cohort with BRCA mutation prior to oophorectomy]; n = 9) and after surgery with (BSO + estradiol-based therapy [ERT]; n = 10) and without (BSO; n = 10) postsurgical estradiol hormone therapy compared with age-matched women (age-matched controls; n = 10) with their ovaries. RESULTS: The BRCA-preBSO and BSO groups showed significantly lower GM volume in the left medial temporal and frontal lobe structures. BSO + ERT exhibited few areas of lower GM volume compared with age-matched controls. Novel to this study, we also observed that all three BRCAm groups exhibited significantly higher GM volume compared with age-matched controls, suggesting continued plasticity. CONCLUSIONS: The present study provides evidence, through lower GM volume, to support both the possibility that the BRCAm, alone, and early life BSO may play a role in increasing the risk for late-life dementia. At least for BRCAm with BSO, postsurgical ERT seems to ameliorate GM losses.

Can't bibliometric analysts do better? How quality assessment without field expertise does not work: A comment on G. Madison and T. Söderlund: Comparisons of scientific quality indicators across peer-reviewed journal articles with more or less gender perspective: Gender studies can do better.

The article is an invited comment on Guy Madison and Therese Söderlund (M&S): Comparisons of content and scientific quality indicators across peer-reviewed journal articles with more or less gender perspective: Gender studies can do better. Scientometrics 115(3):1161-1183. The article pinpoints a series of serious problems in M&S's quantitative quality assessment and analysis of the field of gender studies, pertaining to their overall conceptual framework, their general approach and their specific analysis. It is argued that the over-arching problem in M&S's study is their lack of expert knowledge of the field of gender studies, their lack of respect for differences between qualitative and quantitative research, and their research design, which is biased towards quantitative social and natural science research. Firstly, it is demonstrated that a key concept, 'gender perspective', is used in an incoherent and confusing way in M&S's analysis. Secondly, it is argued that the confusion is not an isolated definitional problem, but related to a series of slippages between M&S's source of inspiration (Ganetz in Genusvetenskapliga projektansökningar inom humaniora-samhällsvetenskap - en uppföljning av Vetenskapsrådets beredning och utfall år 2004. Vetenskapsrådets rapportserie, Stockholm 15/2005, 2005) and their own adoption of the category. Thirdly, differences between qualitative and quantitative research, and between hermeneutic and explanatory knowledge production, are discussed more broadly to sustain the argument that the mentioned slippages occur, because M&S transfer analytical tools from Ganetz' qualitative study, based on a peer review methodology, to a quantitative quality assessment, carried out without field specific expert knowledge. It is argued that, to be adequate and relevant, a quality assessment would need to respect these differences, and develop tools and research designs accordingly. Fourthly, the validity of M&S's content analysis-the core of their study-is questioned in detail because of its use of inadequate analytical categories, and because of its exclusion of central elements from the analysis. Finally, it is argued that the bias in M&S's research design is reproduced in their results.

Inequity in waiting for cataract surgery--an analysis of data from the Swedish National Cataract Register.

BACKGROUND: Swedish Health and Medical Services act states that good care should be given to the entire population on equal terms. Still studies show that access to care in Sweden differ related to for example gender and socioeconomic variables. One of the areas in Swedish health care that has attracted attention for potential inequity in access is Cataract Extraction (CE). Previous studies of access to CE in Sweden show that female patients have in general poorer vision before they are operated and longer waiting times for CE than male patients. The aim of the study was to describe the waiting times in different patient groups with regards to visual acuity, gender, age, native country, educational level, annual income and whether the patient was retired or still working. METHODS: The study was designed as a register study of 102 532 patients who have had CE performed in Sweden 2010-2011. Linear regression was used to analyse the association between patient characteristics and waiting times. Mean waiting times for women and men were calculated for all groups. RESULTS: At significance level p < 0.05 longer waiting times corresponded to patients having good visual acuity, being of female gender, high age, retired, born outside the Nordic countries and having low income and education. Calculations of mean waiting times for all groups showed that women had longer waiting times than men. CONCLUSIONS: The differences between groups defined, for example, by gender, age, native country, income, education and retirement are statistically significant. We do not consider them as clinically significant, but we consider the consistent pattern that we have found noteworthy in relation to the principle of equity in health care.