Impact of cancer-related symptom synergisms on health-related quality of life and performance status

To identify the impact of multiple symptoms and their co-occurrence on health-related quality of life (HRQOL) dimensions and performance status (PS), 115 outpatients with cancer, who were not receiving active cancer treatment and were recruited from, a university hospital in Sao Paulo, Brazil completed the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire-C30, the Beck Depression Inventory, and the Brief Pain Inventory. Karnofsky Performance Status scores also were completed. Application of TwoStep Cluster analysis resulted in two distinct patient subgroups based on 113 patient experiences with pain, depression, fatigue, insomnia, constipation, lack of appetite, dyspnea, nausea, vomiting, and diarrhea. One group had multiple and severe symptom subgroup and another had Less symptoms and with lower severity. Multiple and severe symptoms had worse PS, role functioning, and physical, emotional, cognitive, social, and overall HRQOL. Multiple and severe symptom subgroup was also six times as likely as lower severity to have poor role functioning;five times more likely to have poor emotional;four times more likely to have poor PS, physical, and overall HRQOL, and three times as likely to have poor cognitive and social HRQOL, independent of gender, age, level of education, and economic condition. Classification and Regression Tree analyses were undertaken to identify which co-occurring symptoms would best determine reduction in HRQOL and PS. Pain and fatigue were identified as indicators of reduction on physical HRQOL and PS. Fatigue and insomnia were associated with reduction in cognitive; depression and pain in social; and fatigue and constipation in role functioning. Only depression was associated with reduction in overall HRQOL. These data demonstrate that there is a synergic effect among distinct cancer symptoms that result in reduction in HRQOL dimensions and PS.

Evidence for low-grade systemic proinflammatory activity in patients with posttraumatic stress disorder

Posttraumatic stress disorder (PTSD) may increase cardiovascular risk but the psychophysiological mechanisms involved are elusive. We hypothesized that proinflammatory activity is elevated in patients with PTSD as diagnosed by the Clinician Administered PTSD Scale (CAPS) interview. Plasma levels of proinflammatory C-reactive protein (CRP), interleukin (IL)-1beta, IL-6, and tumor necrosis factor (TNF)-alpha, and of anti-inflammatory IL-4 and IL-10 were measured in 14 otherwise healthy PTSD patients and in 14 age- and gender-matched healthy non-PTSD controls. Levels of TNF-alpha (p=0.038; effect size Cohen's d=0.58) and of IL-1beta (p=0.075, d=0.68) were higher in patients than in controls. CRP (d=0.10), IL-6 (d=0.18), IL-4 (d=0.42), and IL-10 (d=0.37) were not significantly different between groups. Controlling for traditional cardiovascular risk factors, mood, and time since trauma revealed lower IL-4 in patients than in controls (p=0.029) and rendered group differences in TNF-alpha and IL-1beta insignificant. In all subjects, TNF-alpha correlated with total (frequency and intensity) PTSD symptom cluster of re-experiencing (r=0.49, p=0.008), avoidance (r=0.37, p=0.050), and hyperarousal (r=0.42, p=0.026), and with PTSD total symptom score (r=0.37, p=0.054). Controlling for time since trauma attenuated these associations. The correlation between IL-1beta and total avoidance symptoms (r=0.42, p=0.028) became insignificant when controlling for anxiety and depression. IL-4 correlated with total hyperarousal symptoms (r=-0.38, p=0.047), and after controlling for systolic blood pressure and smoking status, with PTSD total symptom score (r=-0.41, p=0.035). PTSD patients showed a low-grade systemic proinflammatory state, which, moreover, was related to PTSD symptom levels suggesting one mechanism by which PTSD could contribute to atherosclerotic disease.

Fatigue and Co-occurring Symptoms in Women with Irritable Bowel Syndrome

Thesis (Ph.D.)--University of Washington, 2016-06

The differential impact of oxytocin receptor (OXTR) genotypes on the risk of autism spectrum disorder (ASD) and resulting social communication deficits

Background: Autism spectrum disorder (ASD) is multifactorial and is likely the result of complex interactions between multiple environmental and genetic factors. Recently, it has been suggested that each symptom cluster of the disorder, such as poor social communication, may be mediated by different genetic influences. Genes in the oxytocin pathway, which mediates social behaviours in humans, have been studied with single nucleotide polymorphisms (SNPs) in the oxytocin receptor gene (OXTR) being implicated in ASD. This thesis examines the presence of different oxytocin receptor genotypes, and their associations with ASD and resulting social communication deficits. Methods: The relationship between four OXTR variants and ASD was evaluated in 607 ASD simplex (SPX) families. Cases were compared to their unaffected siblings using a conditional logistic approach. Odds ratios and associated 95 percent confidence intervals were obtained. A second sample of 235 individuals with a diagnosis of ASD was examined to evaluate whether these four OXTR variants were associated with social communication scores on the Autism Diagnostic Interview – Revised (ADI-R). Parameter estimates and associated 95 percent confidence intervals were generated using a linear regression approach. Multiple testing issues were addressed using false discovery adjustments. Results: The rs53576 AG genotype was significantly associated with a lower risk of ASD (OR = 0.707, 95% CI: 0.512-0.975). A single genotype (AG) provided by the rs2254298 marker was found to be significantly associated with higher social communication scores (Parameter estimate = 1.833, SE = 0.762, p = 0.0171). This association was also seen in a Caucasian only and mothers as the respondent samples. No association was significant following false discovery rate adjustments. Conclusion: The findings from these studies provide limited support for the role of OXTR SNPs in ASD, especially in social communication skills. The clinical significance of these associations remains unknown, however, it is likely that these associations do not play a role in the severity of symptoms associated with ASD. Rather, they may be important in the appearance of social deficits due to the rs2254298 markers association with enlarged amygdalas.

Symptom experience during acute coronary syndrome and the development of posttraumatic stress symptoms

There is growing evidence for the development of posttraumatic stress symptoms as a consequence of acute cardiac events. Acute coronary syndrome (ACS) patients experience a range of acute cardiac symptoms, and these may cluster together in specific patterns. The objectives of this study were to establish distinct symptom clusters in ACS patients, and to investigate whether the experience of different types of symptom clusters are associated with posttraumatic symptom intensity at six months. ACS patients were interviewed in hospital within 48 h of admission, 294 patients provided information on symptoms before hospitalisation, and cluster analysis was used to identify patterns. Posttraumatic stress symptoms were assessed in 156 patients at six months. Three symptom clusters were identified; pain symptoms, diffuse symptoms and symptoms of dyspnea. In multiple regression analyses, adjusting for sociodemographic, clinical and psychological factors, the pain symptoms cluster (β = .153, P = .044) emerged as a significant predictor of posttraumatic symptom severity at six months. A marginally significant association was observed between symptoms of dyspnea and reduced intrusive symptoms at six months (β = -.156, P = .061). Findings suggest acute ACS symptoms occur in distinct clusters, which may have distinctive effects on intensity of subsequent posttraumatic symptoms. Since posttraumatic stress is associated with adverse outcomes, identifying patients at risk based on their symptom experience during ACS may be useful in targeting interventions.

Efficacy and effectiveness of an rVSV-vectored vaccine expressing Ebola surface glycoprotein: interim results from the Guinea ring vaccination cluster-randomised trial.

BACKGROUND A recombinant, replication-competent vesicular stomatitis virus-based vaccine expressing a surface glycoprotein of Zaire Ebolavirus (rVSV-ZEBOV) is a promising Ebola vaccine candidate. We report the results of an interim analysis of a trial of rVSV-ZEBOV in Guinea, west Africa. METHODS For this open-label, cluster-randomised ring vaccination trial, suspected cases of Ebola virus disease in Basse-Guinée (Guinea, west Africa) were independently ascertained by Ebola response teams as part of a national surveillance system. After laboratory confirmation of a new case, clusters of all contacts and contacts of contacts were defined and randomly allocated 1:1 to immediate vaccination or delayed (21 days later) vaccination with rVSV-ZEBOV (one dose of 2 × 10(7) plaque-forming units, administered intramuscularly in the deltoid muscle). Adults (age ≥18 years) who were not pregnant or breastfeeding were eligible for vaccination. Block randomisation was used, with randomly varying blocks, stratified by location (urban vs rural) and size of rings (≤20 vs >20 individuals). The study is open label and masking of participants and field teams to the time of vaccination is not possible, but Ebola response teams and laboratory workers were unaware of allocation to immediate or delayed vaccination. Taking into account the incubation period of the virus of about 10 days, the prespecified primary outcome was laboratory-confirmed Ebola virus disease with onset of symptoms at least 10 days after randomisation. The primary analysis was per protocol and compared the incidence of Ebola virus disease in eligible and vaccinated individuals in immediate vaccination clusters with the incidence in eligible individuals in delayed vaccination clusters. This trial is registered with the Pan African Clinical Trials Registry, number PACTR201503001057193. FINDINGS Between April 1, 2015, and July 20, 2015, 90 clusters, with a total population of 7651 people were included in the planned interim analysis. 48 of these clusters (4123 people) were randomly assigned to immediate vaccination with rVSV-ZEBOV, and 42 clusters (3528 people) were randomly assigned to delayed vaccination with rVSV-ZEBOV. In the immediate vaccination group, there were no cases of Ebola virus disease with symptom onset at least 10 days after randomisation, whereas in the delayed vaccination group there were 16 cases of Ebola virus disease from seven clusters, showing a vaccine efficacy of 100% (95% CI 74·7-100·0; p=0·0036). No new cases of Ebola virus disease were diagnosed in vaccinees from the immediate or delayed groups from 6 days post-vaccination. At the cluster level, with the inclusion of all eligible adults, vaccine effectiveness was 75·1% (95% CI -7·1 to 94·2; p=0·1791), and 76·3% (95% CI -15·5 to 95·1; p=0·3351) with the inclusion of everyone (eligible or not eligible for vaccination). 43 serious adverse events were reported; one serious adverse event was judged to be causally related to vaccination (a febrile episode in a vaccinated participant, which resolved without sequelae). Assessment of serious adverse events is ongoing. INTERPRETATION The results of this interim analysis indicate that rVSV-ZEBOV might be highly efficacious and safe in preventing Ebola virus disease, and is most likely effective at the population level when delivered during an Ebola virus disease outbreak via a ring vaccination strategy. FUNDING WHO, with support from the Wellcome Trust (UK); Médecins Sans Frontières; the Norwegian Ministry of Foreign Affairs through the Research Council of Norway; and the Canadian Government through the Public Health Agency of Canada, Canadian Institutes of Health Research, International Development Research Centre, and Department of Foreign Affairs, Trade and Development.

Development and validation of the Neuro Symptom Inventory in the primary brain tumor patient population

Symptoms has been shown to predict quality of life, treatment course and survival in solid tumor patients. Currently, no instrument exists that measures both cancer-related symptoms and the neurologic symptoms that are unique to persons with primary brain tumors (PBT). The aim of this study was to develop and validate an instrument to measure symptoms in patients who have PBT. A conceptual analysis of symptoms and symptom theories led to defining the symptoms experience as the perception of the frequency, intensity, distress, and meaning that occurs as symptoms are produced, perceived, and expressed. The M.D. Anderson Symptom Inventory (MDASI) measures both symptoms and how they interfere with daily functioning in patients with cancer, which is similar to the situational meaning defined in the analysis. A list of symptoms pertinent to the PBT population was added to the core MDASI and reviewed by a group of experts for validity. As a result, 18 items were added to the core MDASI (the MDASI-BT) for the next phase of instrument development, establishing validity and reliability through a descriptive, cross-sectional approach with PBT patients. Data were collected with a patient completed demographic data sheet, an investigator completed clinician checklist, and the MDASI-BT. Analysis evaluated the reliability and validity of the MDASI-BT in PBT patients. Data were obtained from 201 patients. The number of items was reduced to 22 by evaluation of symptom severity as well as cluster analysis. Regression analysis showed more than half (56%) of the variability in symptom severity was explained by the brain tumor module items. Factor analysis confirmed that the 22 item MDASI-BT measured six underlying constructs: (a) affective; (b) cognitive; (c) focal neurologic deficits; (d) constitutional symptoms; (e) treatment-related symptoms; and (f) gastrointestinal symptoms. The MDASI-BT was sensitive to disease severity and if the patient was hospitalized. The MDASI-BT is the first instrument to measure symptoms in PBT patients that has demonstrated reliability and validity. It is the first step in a program of research to evaluate the occurrence of symptoms and plan and evaluate interventions for PBT patients. ^

Symptom Clusters and Survival in Portuguese Patients with Advanced Cancer

This study aimed to identify clusters of symptoms, to determine the patient characteristics associated with identified, and determine their strength of association with survival in patients with advanced cancer (ACPs). Consecutively eligible ACPs not receiving cancer-specific treatment, and referred to a Tertiary Palliative Care Clinic, were enrolled in a prospective cohort study. At first consultation, patients rated 9 symptoms through the Edmonton Symptom Assessment System (0-10 scale) and 10 others using a Likert scale (1-5). Principal component analysis was used in an exploratory factor analysis to identify. Of 318 ACPs, 301 met eligibility criteria with a median (range) age of 69 (37-94) years. Three SCs were identified: neuro-psycho-metabolic (NPM) (tiredness, lack of appetite, lack of well-being, dyspnea, depression, and anxiety); gastrointestinal (nausea, vomiting, constipation, hiccups, and dry mouth) and sleep impairment (insomnia and sleep disturbance). Exploratory factor analysis accounted for 40% of variance of observed variables in all SCs. Shorter survival was observed for patients with the NPM cluster (58 vs. 23, P < 0.001), as well as for patients with two or more SCs (45 vs. 21, P = 0.005). In a multivariable model for survival at 30-days, age (HR: 0.98; 95% CI: 0.97-0.99; P = 0.008), hospitalization at inclusion (HR: 2.27; 95% CI: 1.47-3.51; P < 0.001), poorer performance status (HR: 1.90, 95% CI: 1.24-2.89; P = 0.003), and NPM (HR: 1.64; 95% CI: 1.17-2.31; P = 0.005), were associated with worse survival. Three clinically meaningful SC in patients with advanced cancer were identifiable. The NPM cluster and the presence of two or more SCs, had prognostic value in relation to survival.

Cluster Analysis To Identify Elderly People's Profiles: A Healthcare Strategy Based On Frailty Characteristics.

The new social panorama resulting from aging of the Brazilian population is leading to significant transformations within healthcare. Through the cluster analysis strategy, it was sought to describe the specific care demands of the elderly population, using frailty components. Cross-sectional study based on reviewing medical records, conducted in the geriatric outpatient clinic, Hospital de Clínicas, Universidade Estadual de Campinas (Unicamp). Ninety-eight elderly users of this clinic were evaluated using cluster analysis and instruments for assessing their overall geriatric status and frailty characteristics. The variables that most strongly influenced the formation of clusters were age, functional capacities, cognitive capacity, presence of comorbidities and number of medications used. Three main groups of elderly people could be identified: one with good cognitive and functional performance but with high prevalence of comorbidities (mean age 77.9 years, cognitive impairment in 28.6% and mean of 7.4 comorbidities); a second with more advanced age, greater cognitive impairment and greater dependence (mean age 88.5 years old, cognitive impairment in 84.6% and mean of 7.1 comorbidities); and a third younger group with poor cognitive performance and greater number of comorbidities but functionally independent (mean age 78.5 years old, cognitive impairment in 89.6% and mean of 7.4 comorbidities). These data characterize the profile of this population and can be used as the basis for developing efficient strategies aimed at diminishing functional dependence, poor self-rated health and impaired quality of life.

Electrocatalytic oxidation of methanol by the [Ru3O(OAc)6(py)2(CH3OH)]3+cluster: improving the metal-ligand electron transfer by accessing the higher oxidation states of a multicentered system

The [Ru3O(Ac)6(py)2(CH3OH)]+ cluster provides an effective electrocatalytic species for the oxidation of methanol under mild conditions. This complex exhibits characteristic electrochemical waves at -1.02, 0.15 and 1.18 V, associated with the Ru3III,II,II/Ru3III,III,II/Ru 3III,III,III /Ru3IV,III,III successive redox couples, respectively. Above 1.7 V, formation of two RuIV centers enhances the 2-electron oxidation of the methanol ligand yielding formaldehyde, in agreement with the theoretical evolution of the HOMO levels as a function of the oxidation states. This work illustrates an important strategy to improve the efficiency of the oxidation catalysis, by using a multicentered redox catalyst and accessing its multiple higher oxidation states.

First Description of a Cluster of Acute/Subacute Paracoccidioidomycosis Cases and Its Association with a Climatic Anomaly

Background: Identifying clusters of acute paracoccidioidomycosis cases could potentially help in identifying the environmental factors that influence the incidence of this mycosis. However, unlike other endemic mycoses, there are no published reports of clusters of paracoccidioidomycosis. Methodology/Principal Findings: A retrospective cluster detection test was applied to verify if an excess of acute form (AF) paracoccidioidomycosis cases in time and/or space occurred in Botucatu, an endemic area in Sao Paulo State. The scan-test SaTScan v7.0.3 was set to find clusters for the maximum temporal period of 1 year. The temporal test indicated a significant cluster in 1985 (P<0.005). This cluster comprised 10 cases, although 2.19 were expected for this year in this area. Age and clinical presentation of these cases were typical of AF paracccidioidomycosis. The space-time test confirmed the temporal cluster in 1985 and showed the localities where the risk was higher in that year. The cluster suggests that some particularities took place in the antecedent years in those localities. Analysis of climate variables showed that soil water storage was atypically high in 1982/83 (similar to 2.11/2.5 SD above mean), and the absolute air humidity in 1984, the year preceding the cluster, was much higher than normal (similar to 1.6 SD above mean), conditions that may have favored, respectively, antecedent fungal growth in the soil and conidia liberation in 1984, the probable year of exposure. These climatic anomalies in this area was due to the 1982/83 El Nino event, the strongest in the last 50 years. Conclusions/Significance: We describe the first cluster of AF paracoccidioidomycosis, which was potentially linked to a climatic anomaly caused by the 1982/83 El Nino Southern Oscillation. This finding is important because it may help to clarify the conditions that favor Paracoccidioides brasiliensis survival and growth in the environment and that enhance human exposure, thus allowing the development of preventive measures.

Abundance variations in the globular cluster M71 (NGC 6838)

Context. Abundance variations in moderately metal-rich globular clusters can give clues about the formation and chemical enrichment of globular clusters. Aims. CN, CH, Na, Mg and Al indices in spectra of 89 stars of the template metal-rich globular cluster M71 are measured and implications on internal mixing are discussed. Methods. Stars from the turn-off up to the Red Giant Branch (0.87 < log g < 4.65) observed with the GMOS multi-object spectrograph at the Gemini-North telescope are analyzed. Radial velocities, colours, effective temperatures, gravities and spectral indices are determined for the sample. Results. Previous findings related to the CN bimodality and CN-CH anticorrelation in stars of M71 are confirmed. We also find a CN-Na correlation, and Al-Na, as well as an Mg(2)-Al anticorrelation. Conclusions. A combination of convective mixing and a primordial pollution by AGB or massive stars in the early stages of globular cluster formation is required to explain the observations.

Discovery of VVV CL001 A low-mass globular cluster next to UKS 1 in the direction of the Galactic bulge

Context. It is not known how many globular clusters may remain undetected towards the Galactic bulge. Aims. One of the aims of the VISTA Variables in the Via Lactea (VVV) Survey is to accurately measure the physical parameters of the known globular clusters in the inner regions of the Milky Way and search for new ones, hidden in regions of large extinction. Methods. From deep near-infrared images, we derive deep JHK(S)-band photometry of a region surrounding the known globular cluster UKS 1 and reveal a new low-mass globular cluster candidate that we name VVV CL001. Results. We use the horizontal-branch red clump to measure E(B-V) similar to 2.2 mag, (m - M)(0) = 16.01 mag, and D = 15.9 kpc for the globular cluster UKS 1. On the basis of near-infrared colour-magnitude diagrams, we also find that VVV CL001 has E(B-V) similar to 2.0, and that it is at least as metal-poor as UKS 1, although its distance remains uncertain. Conclusions. Our finding confirms the previous projection that the central region of the Milky Way harbours more globular clusters. VVV CL001 and UKS 1 are good candidates for a physical cluster binary, but follow-up observations are needed to decide if they are located at the same distance and have similar radial velocities.

SPITZER OBSERVATIONS OF A1763. II. CONSTRAINING THE NATURE OF ACTIVITY IN THE CLUSTER-FEEDING FILAMENT WITH VLA AND XMM-NEWTON DATA

The A1763 superstructure at z = 0.23 contains the first galaxy filament to be directly detected using mid-infrared observations. Our previous work has shown that the frequency of starbursting galaxies, as characterized by 24 mu m emission is much higher within the filament than at either the center of the rich galaxy cluster, or the field surrounding the system. New Very Large Array and XMM-Newton data are presented here. We use the radio and X-ray data to examine the fraction and location of active galaxies, both active galactic nuclei (AGNs) and starbursts (SBs). The radio far-infrared correlation, X-ray point source location, IRAC colors, and quasar positions are all used to gain an understanding of the presence of dominant AGNs. We find very few MIPS-selected galaxies that are clearly dominated by AGN activity. Most radio-selected members within the filament are SBs. Within the supercluster, three of eight spectroscopic members detected both in the radio and in the mid-infrared are radio-bright AGNs. They are found at or near the core of A1763. The five SBs are located further along the filament. We calculate the physical properties of the known wide angle tail (WAT) source which is the brightest cluster galaxy of A1763. A second double lobe source is found along the filament well outside of the virial radius of either cluster. The velocity offset of the WAT from the X-ray centroid and the bend of the WAT in the intracluster medium are both consistent with ram pressure stripping, indicative of streaming motions along the direction of the filament. We consider this as further evidence of the cluster-feeding nature of the galaxy filament.

Confronting dark energy models using galaxy cluster number counts

The mass function of cluster-size halos and their redshift distribution are computed for 12 distinct accelerating cosmological scenarios and confronted to the predictions of the conventional flat Lambda CDM model. The comparison with Lambda CDM is performed by a two-step process. First, we determine the free parameters of all models through a joint analysis involving the latest cosmological data, using supernovae type Ia, the cosmic microwave background shift parameter, and baryon acoustic oscillations. Apart from a braneworld inspired cosmology, it is found that the derived Hubble relation of the remaining models reproduces the Lambda CDM results approximately with the same degree of statistical confidence. Second, in order to attempt to distinguish the different dark energy models from the expectations of Lambda CDM, we analyze the predicted cluster-size halo redshift distribution on the basis of two future cluster surveys: (i) an X-ray survey based on the eROSITA satellite, and (ii) a Sunayev-Zeldovich survey based on the South Pole Telescope. As a result, we find that the predictions of 8 out of 12 dark energy models can be clearly distinguished from the Lambda CDM cosmology, while the predictions of 4 models are statistically equivalent to those of the Lambda CDM model, as far as the expected cluster mass function and redshift distribution are concerned. The present analysis suggests that such a technique appears to be very competitive to independent tests probing the late time evolution of the Universe and the associated dark energy effects.