Depression is a risk factor for incident coronary heart disease in women: an 18-year longitudinal study

BACKGROUND: According to a recent position paper by the American Heart Association, it remains unclear whether depression is a risk factor for incident Coronary Heart Disease (CHD). We assessed whether a depressive disorder independently predicts 18-year incident CHD in women. METHOD: A prospective longitudinal study of 860 women enrolled in the Geelong Osteoporosis Study (1993-2011) was conducted. Participants were derived from an age-stratified, representative sample of women (20-94 years) randomly selected from electoral rolls in South-Eastern Australia. The exposure was a diagnosis of a depressive disorder using the Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders. Outcomes data were collected from hospital medical records: (1) Primary outcome: a composite measure of cardiac death, non-fatal Myocardial Infarction or coronary intervention. (2) Secondary outcome: any cardiac event (un/stable angina, cardiac event not otherwise defined) occurring over the study period. RESULTS: Seven participants were excluded based on CHD history. Eighty-three participants (9.6%) recorded ≥1 cardiac event over the study period; 47 had a diagnosis that met criteria for inclusion in the primary analysis. Baseline depression predicted 18-year incidence, adjusting for (1) anxiety (adj. OR:2.39; 95% CIs:1.19-4.82), plus (2) typical risk factors (adj. OR:3.22; 95% CIs:1.45-6.93), plus (3) atypical risk factors (adj. OR:3.28; 95% CIs:1.36-7.90). This relationship held when including all cardiac events. No relationship was observed between depression and recurrent cardiac events. CONCLUSION: The results of this study support the contention that depression is an independent risk factor for CHD incidence in women. Moreover, the strength of association between depression and CHD incidence was of a greater magnitude than any typical and atypical risk factor.

Fusing data mining, machine learning and traditional statistics to detect biomarkers associated with depression

BACKGROUND: Atheoretical large-scale data mining techniques using machine learning algorithms have promise in the analysis of large epidemiological datasets. This study illustrates the use of a hybrid methodology for variable selection that took account of missing data and complex survey design to identify key biomarkers associated with depression from a large epidemiological study.

METHODS: The study used a three-step methodology amalgamating multiple imputation, a machine learning boosted regression algorithm and logistic regression, to identify key biomarkers associated with depression in the National Health and Nutrition Examination Study (2009-2010). Depression was measured using the Patient Health Questionnaire-9 and 67 biomarkers were analysed. Covariates in this study included gender, age, race, smoking, food security, Poverty Income Ratio, Body Mass Index, physical activity, alcohol use, medical conditions and medications. The final imputed weighted multiple logistic regression model included possible confounders and moderators.

RESULTS: After the creation of 20 imputation data sets from multiple chained regression sequences, machine learning boosted regression initially identified 21 biomarkers associated with depression. Using traditional logistic regression methods, including controlling for possible confounders and moderators, a final set of three biomarkers were selected. The final three biomarkers from the novel hybrid variable selection methodology were red cell distribution width (OR 1.15; 95% CI 1.01, 1.30), serum glucose (OR 1.01; 95% CI 1.00, 1.01) and total bilirubin (OR 0.12; 95% CI 0.05, 0.28). Significant interactions were found between total bilirubin with Mexican American/Hispanic group (p = 0.016), and current smokers (p<0.001).

CONCLUSION: The systematic use of a hybrid methodology for variable selection, fusing data mining techniques using a machine learning algorithm with traditional statistical modelling, accounted for missing data and complex survey sampling methodology and was demonstrated to be a useful tool for detecting three biomarkers associated with depression for future hypothesis generation: red cell distribution width, serum glucose and total bilirubin.

Using Patient Health Questionnaire-9 item parameters of a common metric resulted in similar depression scores compared to independent item response theory model reestimation

Objectives: To investigate the validity of a common depression metric in independent samples. Study Design and Setting: We applied a common metrics approach based on item-response theory for measuring depression to four German-speaking samples that completed the Patient Health Questionnaire (PHQ-9). We compared the PHQ item parameters reported for this common metric to reestimated item parameters that derived from fitting a generalized partial credit model solely to the PHQ-9 items. We calibrated the new model on the same scale as the common metric using two approaches (estimation with shifted prior and StockingeLord linking). By fitting a mixed-effects model and using BlandeAltman plots, we investigated the agreement between latent depression scores resulting from the different estimation models. Results: We found different item parameters across samples and estimation methods. Although differences in latent depression scores between different estimation methods were statistically significant, these were clinically irrelevant. Conclusion: Our findings provide evidence that it is possible to estimate latent depression scores by using the item parameters from a common metric instead of reestimating and linking a model. The use of common metric parameters is simple, for example, using a Web application (http://www.common-metrics.org) and offers a long-term perspective to improve the comparability of patient-reported outcome measures.

Statins for the treatment of depression: a meta-analysis of randomized, double-blind, placebo-controlled trials

BACKGROUND: In epidemiological studies, statins appear to benefit mood, and there are now some randomized controlled trials examining the efficacy of statins. However, the role of statins in depression remains uncertain. Thus the aim of this paper was to assess the effect of statins on depressive symptoms by performing a meta-analysis of all double-blind, randomized, placebo controlled clinical trials (RCT) conducted in subjects with depression. METHODS: A systematic search was executed using PubMed and ClinicalTrials.gov in November 30th, 2015 for all double-blind, RCT of statins versus placebo in persons with depressive symptoms. Sixty-seven potential articles were identified through search of electronic databases, of those three met inclusion criteria and were included in the meta-analysis. The outcome measure was change in Hamilton Depression Rating Scale (HDRS) scores associated with statin use. A meta-analysis was conducted and standardized mean differences (SMDs) with 95% confidence intervals (CIs) were calculated. GRADE was used to assess study quality. RESULTS: The three articles included provided data on 165 participants with moderate to severe depression. Of these, 82 were randomized to statins as an adjuvant therapy to antidepressant treatment (i.e., citalopram or fluoxetine) and 83 to the placebo arm. All studies were double-blind RCTs, with a follow-up of 6-12 weeks. The statin agents evaluated were lovastatin, atorvastatin, and simvastatin. When compared to placebo, statins, as add-on to treatment as usual, largely improved depressive symptoms as assessed by the HDRS (SMD=-0.73, 95% IC -1.04 to -0.42, p<0.001, 3 between-group comparisons, n=165). No serious adverse effects were reported. CONCLUSIONS: Our results suggest that adjunctive treatment with statins could be useful for the treatment of depressive symptoms. Additional double-blind, randomised, placebo-controlled trials are necessary to settle the matter.

Illness cognitions and coping self-efficacy in depression among persons with low vision

PURPOSE: To investigate the mediating role of coping self-efficacy (CSE) between two types of illness cognitions (i.e., acceptance and helplessness) and depressive symptoms in persons with low vision.

METHODS: This was a single-group, cross-sectional study. Patients with visual acuity < 6/12 in the better eye and at least minimal depressive symptoms (≥5 on the Patient Health Questionnaire-9 [PHQ-9]) were recruited from vision rehabilitation services and participated in telephone-administered structured interviews at one time point. Measures were the PHQ-9, CSE Scale, and Illness Cognition Questionnaire. Structural equation modeling (SEM) devised the causal flow of illness cognitions and their observed indirect effects on depressive symptoms via the CSE mediators: problem focused, emotion focused, and social support.

RESULTS: The study comprised 163 patients (mean age 62 years; 61% female), most with age-related macular degeneration (26%) and moderate vision impairment (44%, <6/18-6/60). Structural equation modeling indices indicated a perfect fit (χ2 < 0.001, P = 1.00), accounting for 55% of the variance in depressive symptoms. Lower levels of acceptance and higher levels of helplessness illness cognitions were associated with lower self-efficacy in problem-focused coping (β = 0.38, P < 0.001, β = -0.28, P < 0.01, respectively), which in turn was associated with greater depressive symptom severity (β = -0.54, P < 0.001).

CONCLUSIONS: Lack of acceptance and greater helplessness relating to low vision led to a lack of perceived capability to engage in problem-focused coping, which in turn promoted depressive symptoms. Third-wave cognitive-behavioral treatments that focus on acceptance may be efficacious in this population.

Controversies revisited: a systematic review of the comorbidity of depression and anxiety with inflammatory bowel diseases

BACKGROUND: Although mental health concerns are known to occur commonly for those with inflammatory bowel diseases (IBD), the nature of this comorbid relationship has not been systematically reviewed to date. A review in 2007 identified 5 controversies regarding anxiety/depression rates and various comparators between and within IBD. We aimed to systematically analyze and critique the current evidence regarding this comorbidity, providing an update to the 5 controversies.

METHODS: Ebscohost Medline, CINAHL, Embase, and PsychINFO were searched between 2005 and 2014 using systematic review methodology. Controlled quantitative studies examining either symptoms or diagnoses of anxiety and depression in IBD were included in the review, with study quality assessed using a scale developed a priori to evaluate observational research.

RESULTS: (1) IBD versus healthy controls (pooled mean proportions) (n = 13 studies): anxiety 19.1% versus 9.6%, depression 21.2% versus 13.4%; (2) IBD inactive versus IBD active disease (n = 26): anxiety 28.2% versus 66.4%, depression 19.9% versus 34.7%; (3) ulcerative colitis versus Crohn's disease (n = 28): anxiety 31% versus 37%, depression 22% versus 24.4%; (4) IBD versus other chronic medical conditions (n = 17): anxiety 41.9% versus 48.2%, depression 14.5% versus 28.4%; (5) onset of anxiety/depression before or after IBD onset (n = 2): adults more likely to develop anxiety/depression before IBD onset, but a substantial proportion develops depression after onset; an increased risk for children of developing anxiety/depression after IBD onset.

CONCLUSIONS: The high rates of anxiety and depression for those with IBD, particularly when disease is active, warrant a systemic approach to screening and treatment.