Incidence and drug treatment of emotional distress after cancer diagnosis : a matched primary care case-control study

Notes This work is published under the standard license to publish agreement. After 12 months the work will become freely available and the license terms will switch to a Creative Commons Attribution-NonCommercial-Share Alike 3.0 Unported License.Peer reviewedPublisher PD

Statistical biopsy: An emerging screening approach for early detection of cancers

Despite large investment cancer continues to be a major source of mortality and morbidity throughout the world. Traditional methods of detection and diagnosis such as biopsy and imaging, tend to be expensive and have risks of complications. As data becomes more abundant and machine learning continues advancing, it is natural to ask how they can help solve some of these problems. In this paper we show that using a person's personal health data it is possible to predict their risk for a wide variety of cancers. We dub this process a “statistical biopsy.” Specifically, we train two neural networks, one predicting risk for 16 different cancer types in females and the other predicting risk for 15 different cancer types in males. The networks were trained as binary classifiers identifying individuals that were diagnosed with the different cancer types within 5 years of joining the PLOC trial. However, rather than use the binary output of the classifiers we show that the continuous output can instead be used as a cancer risk allowing a holistic look at an individual's cancer risks. We tested our multi-cancer model on the UK Biobank dataset showing that for most cancers the predictions generalized well and that looking at multiple cancer risks at once from personal health data is a possibility. While the statistical biopsy will not be able to replace traditional biopsies for diagnosing cancers, we hope there can be a shift of paradigm in how statistical models are used in cancer detection moving to something more powerful and more personalized than general population screening guidelines

An approach to measure compliance to clinical guidelines in psychiatric care

<p>Abstract</p> <p>Background</p> <p>The aim of this study was to measure six months compliance to Swedish clinical guidelines in psychiatric care after an active supported implementation process, using structured measures derived from the guidelines.</p> <p>Methods</p> <p>In this observational study four psychiatric clinics each participated in active implementation of the clinical guidelines for the assessment and treatment of depression and guidelines for assessment and treatment of patients with suicidal behaviours developed by The Stockholm Medical Advisory Board for Psychiatry. The implementation programme included seminars, local implementation teams, regular feedback and academic visits. Additionally two clinics only received the guidelines and served as controls. Compliance to guidelines was measured using indicators, which operationalised requirements of preferred clinical practice. 725 patient records were included, 365 before the implementation and 360 six months after.</p> <p>Results</p> <p>Analyses of indicators registered showed that the actively implementing clinics significantly improved their compliance to the guidelines. The total score differed significantly between implementation clinics and control clinics for management of depression (mean scores 9.5 (1.3) versus 5.0 (1.5), p < 0.001) as well as for the management of suicide (mean scores 8.1 (2.3) versus 4.5 (1.9), p < 0.001). No changes were found in the control clinics and only one of the OR was significant.</p> <p>Conclusion</p> <p>Compliance to clinical guidelines measured by process indicators of required clinical practice was enhanced by an active implementation.</p

Telephone Consultation for Improving Health of People Living with or at Risk of HIV: A Systematic Review

BACKGROUND: Low cost, effective interventions are needed to deal with the major global burden of HIV/AIDS. Telephone consultation offers the potential to improve health of people living with HIV/AIDS cost-effectively and to reduce the burden on affected people and health systems. The aim of this systematic review was to assess the effectiveness of telephone consultation for HIV/AIDS care. METHODS: We undertook a comprehensive search of peer-reviewed and grey literature. Two authors independently screened citations, extracted data and assessed the quality of randomized controlled trials which compared telephone interventions with control groups for HIV/AIDS care. Telephone interventions were voice calls with landlines or mobile phones. We present a narrative overview of the results as the obtained trials were highly heterogeneous in design and therefore the data could not be pooled for statistical analysis. RESULTS: The search yielded 3321 citations. Of these, nine studies involving 1162 participants met the inclusion criteria. The telephone was used for giving HIV test results (one trial) and for delivering behavioural interventions aimed at improving mental health (four trials), reducing sexual transmission risk (one trial), improving medication adherence (two trials) and smoking cessation (one trial). Limited effectiveness of the intervention was found in the trial giving HIV test results, in one trial supporting medication adherence and in one trial for smoking cessation by telephone. CONCLUSIONS: We found some evidence of the benefits of interventions delivered by telephone for the health of people living with HIV or at risk of HIV. However, only limited conclusions can be drawn as we only found nine studies for five different interventions and they mainly took place in the United States. Nevertheless, given the high penetration of low-cost mobile phones in countries with high HIV endemicity, more evidence is needed on how telephone consultation can aid in the delivery of HIV prevention, treatment and care

Association between Catechol-O-Methyltrasferase Val108/158Met Genotype and Prefrontal Hemodynamic Response in Schizophrenia

BACKGROUND:"Imaging genetics" studies have shown that brain function by neuroimaging is a sensitive intermediate phenotype that bridges the gap between genes and psychiatric conditions. Although the evidence of association between functional val108/158met polymorphism of the catechol-O-methyltransferase gene (COMT) and increasing risk for developing schizophrenia from genetic association studies remains to be elucidated, one of the most topical findings from imaging genetics studies is the association between COMT genotype and prefrontal function in schizophrenia. The next important step in the translational approach is to establish a useful neuroimaging tool in clinical settings that is sensitive to COMT variation, so that the clinician could use the index to predict clinical response such as improvement in cognitive dysfunction by medication. Here, we investigated spatiotemporal characteristics of the association between prefrontal hemodynamic activation and the COMT genotype using a noninvasive neuroimaging technique, near-infrared spectroscopy (NIRS). METHODOLOGY/PRINCIPAL FINDINGS:Study participants included 45 patients with schizophrenia and 60 healthy controls matched for age and gender. Signals that are assumed to reflect regional cerebral blood volume were monitored over prefrontal regions from 52-channel NIRS and compared between two COMT genotype subgroups (Met carriers and Val/Val individuals) matched for age, gender, premorbid IQ, and task performance. The [oxy-Hb] increase in the Met carriers during the verbal fluency task was significantly greater than that in the Val/Val individuals in the frontopolar prefrontal cortex of patients with schizophrenia, although neither medication nor clinical symptoms differed significantly between the two subgroups. These differences were not found to be significant in healthy controls. CONCLUSIONS/SIGNIFICANCE:These data suggest that the prefrontal NIRS signals can noninvasively detect the impact of COMT variation in patients with schizophrenia. NIRS may be a promising candidate translational approach in psychiatric neuroimaging

Subcortical volumes across the lifespan: Data from 18,605 healthy individuals aged 3–90 years

Age has a major effect on brain volume. However, the normative studies available are constrained by small sample sizes, restricted age coverage and significant methodological variability. These limitations introduce inconsistencies and may obscure or distort the lifespan trajectories of brain morphometry. In response, we capitalized on the resources of the Enhancing Neuroimaging Genetics through Meta‐Analysis (ENIGMA) Consortium to examine age‐related trajectories inferred from cross‐sectional measures of the ventricles, the basal ganglia (caudate, putamen, pallidum, and nucleus accumbens), the thalamus, hippocampus and amygdala using magnetic resonance imaging data obtained from 18,605 individuals aged 3–90 years. All subcortical structure volumes were at their maximum value early in life. The volume of the basal ganglia showed a monotonic negative association with age thereafter; there was no significant association between age and the volumes of the thalamus, amygdala and the hippocampus (with some degree of decline in thalamus) until the sixth decade of life after which they also showed a steep negative association with age. The lateral ventricles showed continuous enlargement throughout the lifespan. Age was positively associated with inter‐individual variability in the hippocampus and amygdala and the lateral ventricles. These results were robust to potential confounders and could be used to examine the functional significance of deviations from typical age‐related morphometric patterns

Cortical thickness across the lifespan: Data from 17,075 healthy individuals aged 3–90 years

Delineating the association of age and cortical thickness in healthy individuals is critical given the association of cortical thickness with cognition and behavior. Previous research has shown that robust estimates of the association between age and brain morphometry require large-scale studies. In response, we used cross-sectional data from 17,075 individuals aged 3–90 years from the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to infer age-related changes in cortical thickness. We used fractional polynomial (FP) regression to quantify the association between age and cortical thickness, and we computed normalized growth centiles using the parametric Lambda, Mu, and Sigma method. Interindividual variability was estimated using meta-analysis and one-way analysis of variance. For most regions, their highest cortical thickness value was observed in childhood. Age and cortical thickness showed a negative association; the slope was steeper up to the third decade of life and more gradual thereafter; notable exceptions to this general pattern were entorhinal, temporopolar, and anterior cingulate cortices. Interindividual variability was largest in temporal and frontal regions across the lifespan. Age and its FP combinations explained up to 59% variance in cortical thickness. These results may form the basis of further investigation on normative deviation in cortical thickness and its significance for behavioral and cognitive outcomes