14 research outputs found

    Study protocol for a randomized trial of a supportive care mobile application to improve symptoms, coping, and quality of life in patients with advanced non-small cell lung cancer

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    Patients with advanced non-small cell lung cancer (NSCLC) often experience burdensome symptoms, emotional distress, and poor quality of life (QOL). While national guidelines recommend early palliative care to address these supportive care needs, most patients with advanced NSCLC lack access to such comprehensive care. Our aim in the current study is to test a novel model of palliative care delivery and use of innovative technology to evaluate the feasibility, acceptability, and preliminary efficacy of a supportive care mobile application (app) for improving symptom management and adaptive coping in patients with advanced NSCLC. We will enroll 120 patients with unresectable Stage III or IV NSCLC diagnosed within the past 12 weeks receiving care with palliative intent at a major academic comprehensive cancer center and its community affiliates. The study will take place in two phases, the first of which will be dedicated to adapting an evidence-based, early palliative care treatment guide and prior supportive care mobile app intervention to address the specific symptom management and coping needs of patients with advanced NSCLC. The second phase of the study will be a two-group, randomized controlled trial. Study patients will complete baseline self-report measures of symptoms, mood, coping skills, and QOL, after which they will be randomized to receive either the mobile app intervention combined with usual oncology care or usual oncology care alone. Intervention patients will use a tablet computer to self-administer the mobile app, which consists of six modules that teach evidence-based skills for managing burdensome symptoms and coping effectively with advanced cancer and its treatment. At 12 weeks follow up, patients in both groups will repeat the same self-report measures. We will use descriptive statistics to determine feasibility metrics of enrollment and retention rates. For secondary self-report measures, we will use linear regression controlling for baseline values. The results of the present study will contribute to a growing body of evidence regarding the supportive care needs of patients with advanced cancer and will have implications for how best to use innovative technology to widely disseminate comprehensive supportive care services to all patients who may benefit.Clinical Trial Registration: [www.ClinicalTrials.gov], identifier[NCT04629300]

    Analysis of shared heritability in common disorders of the brain

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    ience, this issue p. eaap8757 Structured Abstract INTRODUCTION Brain disorders may exhibit shared symptoms and substantial epidemiological comorbidity, inciting debate about their etiologic overlap. However, detailed study of phenotypes with different ages of onset, severity, and presentation poses a considerable challenge. Recently developed heritability methods allow us to accurately measure correlation of genome-wide common variant risk between two phenotypes from pools of different individuals and assess how connected they, or at least their genetic risks, are on the genomic level. We used genome-wide association data for 265,218 patients and 784,643 control participants, as well as 17 phenotypes from a total of 1,191,588 individuals, to quantify the degree of overlap for genetic risk factors of 25 common brain disorders. RATIONALE Over the past century, the classification of brain disorders has evolved to reflect the medical and scientific communities' assessments of the presumed root causes of clinical phenomena such as behavioral change, loss of motor function, or alterations of consciousness. Directly observable phenomena (such as the presence of emboli, protein tangles, or unusual electrical activity patterns) generally define and separate neurological disorders from psychiatric disorders. Understanding the genetic underpinnings and categorical distinctions for brain disorders and related phenotypes may inform the search for their biological mechanisms. RESULTS Common variant risk for psychiatric disorders was shown to correlate significantly, especially among attention deficit hyperactivity disorder (ADHD), bipolar disorder, major depressive disorder (MDD), and schizophrenia. By contrast, neurological disorders appear more distinct from one another and from the psychiatric disorders, except for migraine, which was significantly correlated to ADHD, MDD, and Tourette syndrome. We demonstrate that, in the general population, the personality trait neuroticism is significantly correlated with almost every psychiatric disorder and migraine. We also identify significant genetic sharing between disorders and early life cognitive measures (e.g., years of education and college attainment) in the general population, demonstrating positive correlation with several psychiatric disorders (e.g., anorexia nervosa and bipolar disorder) and negative correlation with several neurological phenotypes (e.g., Alzheimer's disease and ischemic stroke), even though the latter are considered to result from specific processes that occur later in life. Extensive simulations were also performed to inform how statistical power, diagnostic misclassification, and phenotypic heterogeneity influence genetic correlations. CONCLUSION The high degree of genetic correlation among many of the psychiatric disorders adds further evidence that their current clinical boundaries do not reflect distinct underlying pathogenic processes, at least on the genetic level. This suggests a deeply interconnected nature for psychiatric disorders, in contrast to neurological disorders, and underscores the need to refine psychiatric diagnostics. Genetically informed analyses may provide important "scaffolding" to support such restructuring of psychiatric nosology, which likely requires incorporating many levels of information. By contrast, we find limited evidence for widespread common genetic risk sharing among neurological disorders or across neurological and psychiatric disorders. We show that both psychiatric and neurological disorders have robust correlations with cognitive and personality measures. Further study is needed to evaluate whether overlapping genetic contributions to psychiatric pathology may influence treatment choices. Ultimately, such developments may pave the way toward reduced heterogeneity and improved diagnosis and treatment of psychiatric disorders

    31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two

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    Background The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd. Methods We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background. Results First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001). Conclusions In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival

    Gut microbiome is associated with multiple sclerosis activity in children.

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    ObjectiveTo identify features of the gut microbiome associated with multiple sclerosis activity over time.MethodsWe used 16S ribosomal RNA sequencing from stool of 55 recently diagnosed pediatric-onset multiple sclerosis patients. Microbiome features included the abundance of individual microbes and networks identified from weighted genetic correlation network analyses. Prentice-Williams-Peterson Cox proportional hazards models estimated the associations between features and three disease activity outcomes: clinical relapses and both new/enlarging T2 lesions and new gadolinium-enhancing lesions on brain MRI. Analyses were adjusted for age, sex, and disease-modifying therapies.ResultsParticipants were followed, on average, 2.1&nbsp;years. Five microbes were nominally associated with all three disease activity outcomes after multiple testing correction. These included butyrate producers Odoribacter (relapse hazard ratio&nbsp;=&nbsp;0.46, 95% confidence interval: 0.24, 0.88) and Butyricicoccus (relapse hazard ratio&nbsp;=&nbsp;0.49, 95% confidence interval: 0.28, 0.88). Two networks of co-occurring gut microbes were significantly associated with a higher hazard of both MRI outcomes (gadolinium-enhancing lesion hazard ratios (95% confidence intervals) for Modules 32 and 33 were 1.29 (1.08, 1.54) and 1.42 (1.18, 1.71), respectively; T2 lesion hazard ratios (95% confidence intervals) for Modules 32 and 33 were 1.34 (1.15, 1.56) and 1.41 (1.21, 1.64), respectively). Metagenomic predictions of these networks demonstrated enrichment for amino acid biosynthesis pathways.InterpretationBoth individual and networks of gut microbes were associated with longitudinal multiple sclerosis activity. Known functions and metagenomic predictions of these microbes suggest the important role of butyrate and amino acid biosynthesis pathways. This provides strong support for future development of personalized microbiome interventions to modify multiple sclerosis disease activity
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