Associations of vitamin D pathway genes with circulating 25-hydroxyvitamin-D, 1,25-dihydroxyvitamin-D, and prostate cancer:a nested case-control study

Vitamin D pathway single nucleotide polymorphisms (SNPs) are potentially useful proxies for investigating whether circulating vitamin D metabolites [total 25-hydroxyvitamin-D, 25(OH)D; 1,25-dihydroxyvitamin, 1,25(OH)2D] are causally related to prostate cancer. We investigated associations of sixteen SNPs across seven genes with prostate-specific antigen-detected prostate cancer

“Clinical features of women with gout arthritis.” A systematic review

Clinically, gout is generally considered as a preferential male disease. However, it definitely does not occur exclusively in males. Our aim was to assess differences in the clinical features of gout arthritis between female and male patients. Five electronic databases were searched to identify relevant original studies published between 1977 and 2007. The included studies had to focus on adult patients with primary gout arthritis and on sex differences in clinical features. Two reviewers independently assessed eligibility and quality of the studies. Out of 355 articles, 14 were selected. Nine fulfilled the quality and score criteria. We identified the following sex differences in the clinical features of gout in women compared to men: the onset of gout occurs at a higher age, more comorbidity with hypertension or renal insufficiency, more often use of diuretics, less likely to drink alcohol, less often podagra but more often involvement of other joints, less frequent recurrent attacks. We found interesting sex differences regarding the clinical features of patients with gout arthritis. To diagnose gout in women, knowledge of these differences is essential, and more research is needed to understand and explain the differences , especially in the general population

External validation and calibration of IVFpredict:A national prospective cohort study of 130,960 in vitro fertilisation Cycles

© 2015 Smith et al. Background Accurately predicting the probability of a live birth after in vitro fertilisation (IVF) is important for patients, healthcare providers and policy makers. Two prediction models (Templeton and IVFpredict) have been previously developed from UK data and are widely used internationally. The more recent of these, IVFpredict, was shown to have greater predictive power in the development dataset. The aim of this study was external validation of the two models and comparison of their predictive ability. Methods and Findings 130,960 IVF cycles undertaken in the UK in 2008-2010 were used to validate and compare the Templeton and IVFpredict models. Discriminatory power was calculated using the area under the receiver-operator curve and calibration assessed using a calibration plot and Hosmer-Lemeshow statistic. The scaled modified Brier score, with measures of reliability and resolution, were calculated to assess overall accuracy. Both models were compared after updating for current live birth rates to ensure that the average observed and predicted live birth rates were equal. The discriminative power of both methods was comparable: the area under the receiver-operator curve was 0.628 (95% confidence interval (CI): 0.625-0.631) for IVFpredict and 0.616 (95% CI: 0.613-0.620) for the Templeton model. IVFpredict had markedly better calibration and higher diagnostic accuracy, with calibration plot intercept of 0.040 (95% CI: 0.017-0.063) and slope of 0.932 (95% CI: 0.839 - 1.025) compared with 0.080 (95% CI: 0.044-0.117) and 1.419 (95% CI: 1.149-1.690) for the Templeton model. Both models underestimated the live birth rate, but this was particularly marked in the Templeton model. Updating the models to reflect improvements in live birth rates since the models were developed enhanced their performance, but IVFpredict remained superior. Conclusion External validation in a large population cohort confirms IVFpredict has superior discrimination and calibration for informing patients, clinicians and healthcare policy makers of the probability of live birth following IVF

A genetic programming approach to development of clinical prediction models: A case study in symptomatic cardiovascular disease

BACKGROUND:Genetic programming (GP) is an evolutionary computing methodology capable of identifying complex, non-linear patterns in large data sets. Despite the potential advantages of GP over more typical, frequentist statistical approach methods, its applications to survival analyses are rare, at best. The aim of this study was to determine the utility of GP for the automatic development of clinical prediction models. METHODS:We compared GP against the commonly used Cox regression technique in terms of the development and performance of a cardiovascular risk score using data from the SMART study, a prospective cohort study of patients with symptomatic cardiovascular disease. The composite endpoint was cardiovascular death, non-fatal stroke, and myocardial infarction. A total of 3,873 patients aged 19-82 years were enrolled in the study 1996-2006. The cohort was split 70:30 into derivation and validation sets. The derivation set was used for development of both GP and Cox regression models. These models were then used to predict the discrete hazards at t = 1, 3, and 5 years. The predictive ability of both models was evaluated in terms of their risk discrimination and calibration using the validation set. RESULTS:The discrimination of both models was comparable. At time points t = 1, 3, and 5 years the C-index was 0.59, 0.69, 0.64 and 0.66, 0.70, 0.70 for the GP and Cox regression models respectively. At the same time points, the calibration of both models, which was assessed using calibration plots and the generalization of the Hosmer-Lemeshow test statistic, was also comparable, but with the Cox model being better calibrated to the validation data. CONCLUSION:Using empirical data, we demonstrated that a prediction model developed automatically by GP has predictive ability comparable to that of manually tuned Cox regression. The GP model was more complex, but it was developed in a fully automated way and comprised fewer covariates. Furthermore, it did not require the expertise normally needed for its derivation, thereby alleviating the knowledge elicitation bottleneck. Overall, GP demonstrated considerable potential as a method for the automated development of clinical prediction models for diagnostic and prognostic purposes

Prevalence and risk factors of depressive symptoms in a Canadian palliative home care population: a cross-sectional study

Background: Depression in palliative care patients is important because of its intrinsic burden and association with elevated physical symptoms, reduced immunity and increased mortality risk. Identifying risk factors associated with depression can enable clinicians to more readily diagnose it, which is important since depression is treatable. The purpose of this cross-sectional study was to determine the prevalence of depressive symptoms and risk factors associated with them in a large sample of palliative home care patients. Methods: The data come from interRAI Palliative Care assessments completed between 2006 and 2012. The sample (n = 5144) consists of adults residing in Ontario (Canada), receiving home care services, classified as palliative, and not experiencing significant cognitive impairment. Logistic regression identified the risk factors associated with depressive symptoms. The dependent variable was the Depression Rating Scale (DRS) and the independent variables were functional indicators from the interRAI assessment and other variables identified in the literature. We examined the results of the complete case and multiple imputation analyses, and found them to be similar. Results:The prevalence of depressive symptoms was 9.8%. The risk factors associated with depressive symptoms were (pooled estimates, multiple imputation): low life satisfaction (OR = 3.01 [CI = 2.37-3.82]), severe and moderate sleep disorders (2.56 [2.05-3.19] and 1.56 [1.18-2.06]), health instability (2.12 [1.42-3.18]), caregiver distress 2.01 [1.62-2.51]), daily pain (1.73 [1.35-2.22]), cognitive impairment (1.45 [1.13-1.87]), being female (1.37 [1.11-1.68]), and gastrointestinal symptoms (1.27 [1.03-1.55]). Life satisfaction mediated the effect of prognostic awareness on depressive symptoms. Conclusions: The prevalence of depressive symptoms in our study was close to the median of 10-20% reported in the palliative care literature, suggesting they are present but by no means inevitable in palliative patients. Most of the factors associated with depressive symptoms in our study are amenable to clinical intervention and often targeted in palliative care programs. Designing interventions to address them can be challenging, however, requiring careful attention to patient preferences, the spectrum of comorbid conditions they face, and their social supports. Life satisfaction was one of the strongest factors associated with depressive symptoms in our study, and is likely to be among the most challenging to address

Associations of circulating retinol, vitamin E, and 1,25-dihydroxyvitamin D with prostate cancer diagnosis, stage, and grade

Some epidemiological studies suggest that vitamin A (retinol), vitamin E, and vitamin D (total 25-hydroxyvitamin D, 25(OH)D; 1,25-dihydroxyvitamin, 1,25(OH)(2)D) are protective against prostate cancer. However, the evidence is not conclusive, with positive and null associations reported for all three vitamins. Limitations of previous studies include small sample size, lack of population controls, and reliance on self-reported dietary intake. Few studies have explored the interactions of circulating 25(OH)D with 1,25(OH)(2)D or retinol, which are biologically plausible interactions