Economic costs of minor depression: a population-based study

Objective: Although the clinical relevance of minor depression has been demonstrated in many studies, the economic costs are not well explored. In this study, we examine the economic costs of minor depression. Method: In a large-scale, population-based study in the Netherlands (n ¼ 5504) the costs of minor depression were compared with the costs of major depression and dysthymia. Excess costs, i.e. the costs of a disorder over and above the costs attributable to other illnesses, were estimated with help of regression analysis. The direct medical costs, the direct non-medical costs and the indirect non-medical costs were calculated. The year 2003 was used as the reference year. Results: The annual per capita excess costs of minor depression were US$2141 (95$ 1023, while the costs of major depression were US$ 3313 (95% CI ¼ 1234–5390) higher than the base rate. The costs of minor depression per 1 million inhabitants were 160 million dollars per year, which is somewhat less than the costs of major depression (192 million dollars per year). Conclusion: The economic costs associated with minor depression are considerable and approach those of major depression

Predicting the onset of major depression in subjects with subthreshold depression in primary care: A prospective study.

Objective: That subjects with subthreshold depression have an increased probability of developing major depression has been confirmed by many studies. However, the factors which may predict the onset of major depression have yet to be fully examined. Method: We examined the control group of a randomized trial in primary care patients with subthreshold depression (N ¼ 109), of whom 20 had developed major depression 1 year later. Using the vulnerability-stress theory, we examined which factors predicted the onset of major depression. Results: In both univariate and multivariate analyses, family history and chronic illnesses predicted the onset of major depression. Conclusion: It is possible to predict to a certain degree whether a subject with subthreshold depression will develop major depression within a year

Breast cancer outcome prediction with tumour tissue images and machine learning

PurposeRecent advances in machine learning have enabled better understanding of large and complex visual data. Here, we aim to investigate patient outcome prediction with a machine learning method using only an image of tumour sample as an input.MethodsUtilising tissue microarray (TMA) samples obtained from the primary tumour of patients (N=1299) within a nationwide breast cancer series with long-term-follow-up, we train and validate a machine learning method for patient outcome prediction. The prediction is performed by classifying samples into low or high digital risk score (DRS) groups. The outcome classifier is trained using sample images of 868 patients and evaluated and compared with human expert classification in a test set of 431 patients.ResultsIn univariate survival analysis, the DRS classification resulted in a hazard ratio of 2.10 (95% CI 1.33-3.32, p=0.001) for breast cancer-specific survival. The DRS classification remained as an independent predictor of breast cancer-specific survival in a multivariate Cox model with a hazard ratio of 2.04 (95% CI 1.20-3.44, p=0.007). The accuracy (C-index) of the DRS grouping was 0.60 (95% CI 0.55-0.65), as compared to 0.58 (95% CI 0.53-0.63) for human expert predictions based on the same TMA samples.ConclusionsOur findings demonstrate the feasibility of learning prognostic signals in tumour tissue images without domain knowledge. Although further validation is needed, our study suggests that machine learning algorithms can extract prognostically relevant information from tumour histology complementing the currently used prognostic factors in breast cancer.Peer reviewe

Preventing mood and anxiety disorders in youth: a multi-centre RCT in the high risk offspring of depressed and anxious patients

<p>Abstract</p> <p>Background</p> <p>Anxiety and mood disorders are highly prevalent and pose a huge burden on patients. Their offspring is at increased risk of developing these disorders as well, indicating a clear need for prevention of psychopathology in this group. Given high comorbidity and non-specificity of intergenerational transmission of disorders, prevention programs should target both anxiety and depression. Further, while the indication for preventive interventions is often elevated symptoms, offspring with other high risk profiles may also benefit from resilience-based prevention programs.</p> <p>Method/design</p> <p>The current STERK-study (Screening and Training: Enhancing Resilience in Kids) is a randomized controlled clinical trial combining selected and indicated prevention: it is targeted at both high risk individuals without symptoms and at those with subsyndromal symptoms. Individuals without symptoms meet two of three criteria of the High Risk Index (HRI; female gender, both parents affected, history of a parental suicide (attempt). This index was developed in an earlier study and corresponds with elevated risk in offspring of depressed patients. Children aged 8–17 years (n = 204) with subthreshold symptoms or meeting the criteria on the HRI are randomised to one of two treatment conditions, namely (a) 10 weekly individual child CBT sessions and 2 parent sessions or (b) minimal information. Assessments are held at pre-test, post-test and at 12 and 24 months follow-up. Primary outcome is the time to onset of a mood or anxiety disorder in the offspring. Secondary outcome measures include number of days with depression or anxiety, child and parent symptom levels, quality of life, and cost-effectiveness. Based on models of aetiology of mood and anxiety disorders as well as mechanisms of change during interventions, we selected potential mediators and moderators of treatment outcome, namely coping, parent–child interaction, self-associations, optimism/pessimism, temperament, and emotion processing.</p> <p>Discussion</p> <p>The current intervention trial aims to significantly reduce the risk of intergenerational transmission of mood and anxiety disorders with a short and well targeted intervention that is directed at strengthening the resilience in potentially vulnerable children. We plan to evaluate the effectiveness and cost-effectiveness of such an intervention and to identify mechanisms of change.</p> <p>Trial registration</p> <p>NTR2888</p