Interferon‐gamma serum level and immunohistochemical expression of CD8 cells in tissue biopsies in patients with alopecia areata in correlation with trichoscopic findings

Alopecia areata (AA) is an autoimmune form of nonscarring hair loss. The aim of the study was to assess the serum concentration of interferon gamma (IFN‐γ) and CD8 cell expression in lesional skin biopsies in correlation with the disease severity, activity, duration, and trichoscopic findings in patients with AA. The study included 30 patients with AA and 15 age‐ and sex‐matched healthy controls. Trichoscopy was performed and photographs were captured for the alopecic areas, and the enzyme‐linked immunosorbent assay technique was used for serum level of IFN‐γ assessment and immunohistochemistry for CD8 cells. The results obtained indicate that IFN‐γ serum level in patients was significantly higher than that of control subjects, and significantly correlated with the activity status and the duration of the disease. CD8+ T cells infiltrate intensity significantly correlated with severity. Yellow dots (YDs), vellus hair, black dot, and exclamation marks were the most common trichoscopic findings. The presence of black dots significantly correlated to the disease activity, duration, serum IFN‐γ, and CD8+ infiltrate intensity. The presence of YDs significantly correlated with the mean serum IFN‐γ level. Exclamation marks significantly correlated with the disease activity and the degree of CD8+ infiltrate. In conclusion, trichoscopy could be a reliable indicator of the IFN‐γ serum level and CD8+ T cell infiltrate intensity in AA patient.     

The effect of gender on mental health service use: an examination of mediation through material,social and health-related pathways

Purpose

We aimed to understand how much of the gender difference in mental health service use could be due to the joint mediation of employment, behavioural and material factors, social support and mental health need.

Methods

We used data from employed individuals aged 18–65 years who participated in the 2015–2017 waves of the Household, Income and Labour Dynamics in Australia survey. The exposure (male, female) and confounders were measured in 2015, mediators in 2016 and the outcome—whether a person had seen a mental health professional in the previous year—was measured in 2017. We estimated natural mediation effects using weighted counterfactual predictions from a logistic regression model.

Results

Men were less likely to see a mental health care provider than women. The total causal effect on the risk difference scale was  − 0.045 (95% CI  − 0.056,  − 0,034). The counterfactual of men taking the mediator values of women explained 28% (95% CI 1.7%, 54%) of the total effect, with the natural direct effect estimated to represent an absolute risk difference of  − 0.033 (95% CI  − 0.048,  − 0.018) and the natural indirect effect  − 0.012 (95% CI  − 0.022,  − 0.0027).

Conclusion

Gendered differences in the use of mental health services could be reduced by addressing inequalities in health, employment, material and behavioural factors, and social support.

     

Introduction to causal diagrams for confounder selection

In respiratory health research, interest often lies in estimating the effect of an exposure on a health outcome. If randomization of the exposure of interest is not possible, estimating its effect is typically complicated by confounding bias. This can often be dealt with by controlling for the variables causing the confounding, if measured, in the statistical analysis. Common statistical methods used to achieve this include multivariable regression models adjusting for selected confounding variables or stratification on those variables. Therefore, a key question is which measured variables need to be controlled for in order to remove confounding. An approach to confounder‐selection based on the use of causal diagrams (often called directed acyclic graphs) is discussed. A causal diagram is a visual representation of the causal relationships believed to exist between the variables of interest, including the exposure, outcome and potential confounding variables. After creating a causal diagram for the research question, an intuitive and easy‐to‐use set of rules can be applied, based on a foundation of rigorous mathematics, to decide which measured variables must be controlled for in the statistical analysis in order to remove confounding, to the extent that is possible using the available data. This approach is illustrated by constructing a causal diagram for the research question: ‘Does personal smoking affect the risk of subsequent asthma?’. Using data taken from the Tasmanian Longitudinal Health Study, the statistical analysis suggested by the causal diagram approach was performed.     

Older people with cancer: perceptions and feelings about information, decision-making and treatment--a pilot study.

Several studies have identified inadequacies in the care and treatment received by older patients with cancer, as opposed to their younger counterparts. These include over or under diagnosis, ineffective symptom management and lower survival rates in older people with cancer. Despite these inadequacies, there is lack of evidence of older peoples' perspectives regarding their cancer diagnosis and treatment. This on going 2-site hospital based study focuses on older people's perceptions of information and decision-making in relation to treatment for cancer by using a semi-structured interview schedule. Results of the pilot study with 6 patients are presented and discussed in the light of research and clinical implications.