Incidence of WHO stage 3 and 4 conditions following initiation of Anti-Retroviral Therapy in resource limited settings

To determine the incidence of WHO clinical stage 3 and 4 conditions during early anti-retroviral therapy (ART) in resource limited settings (RLS)

Robust estimation of microbial diversity in theory and in practice

Quantifying diversity is of central importance for the study of structure, function and evolution of microbial communities. The estimation of microbial diversity has received renewed attention with the advent of large-scale metagenomic studies. Here, we consider what the diversity observed in a sample tells us about the diversity of the community being sampled. First, we argue that one cannot reliably estimate the absolute and relative number of microbial species present in a community without making unsupported assumptions about species abundance distributions. The reason for this is that sample data do not contain information about the number of rare species in the tail of species abundance distributions. We illustrate the difficulty in comparing species richness estimates by applying Chao's estimator of species richness to a set of in silico communities: they are ranked incorrectly in the presence of large numbers of rare species. Next, we extend our analysis to a general family of diversity metrics ("Hill diversities"), and construct lower and upper estimates of diversity values consistent with the sample data. The theory generalizes Chao's estimator, which we retrieve as the lower estimate of species richness. We show that Shannon and Simpson diversity can be robustly estimated for the in silico communities. We analyze nine metagenomic data sets from a wide range of environments, and show that our findings are relevant for empirically-sampled communities. Hence, we recommend the use of Shannon and Simpson diversity rather than species richness in efforts to quantify and compare microbial diversity.Comment: To be published in The ISME Journal. Main text: 16 pages, 5 figures. Supplement: 16 pages, 4 figure

A modified integrated genetic model for risk prediction in younger patients with acute myeloid leukemia

Background: Although cytogenetics-based prognostication systems are well described in acute myeloid leukemia (AML), overall survival (OS) remains highly variable within risk groups. An integrated genetic prognostic (IGP) model using cytogenetics plus mutations in nine genes was recently proposed for patients ≤60 years to improve classification. This model has not been validated in clinical practice. Methods and Findings: We retrospectively studied 197 patients with newly diagnosed de novo AML. We compared OS curves among the mutational profiles defined by the IGP model. The IGP model assigned patients with intermediate cytogenetics as having favorable, intermediate or unfavorable mutational profiles. The IGP model reassigned 50 of 137 patients with intermediate cytogenetics to favorable or unfavorable mutational profiles. Median OS was 2.8 years among 14 patients with intermediate cytogenetics and favorable mutational profiles (mutant NPM1 and mutant IDH1 or IDH2) and 1.3 years among patients with intermediate mutational profiles. Among patients with intermediate cytogenetics labeled as having unfavorable mutational profiles, median OS was 0.8 years among 24 patients with FLT3-ITD positive AML and high-risk genetic changes (trisomy 8, TET2 and/or DNMT3A) and 1.7 years among 12 patients with FLT3-ITD negative AML and high-risk mutations (TET2, ASXL1 and/or PHF6). OS for patients with intermediate cytogenetics and favorable mutational profiles was similar to OS for patients with favorable cytogenetics (p = 0.697) and different from patients with intermediate cytogenetics and intermediate mutational profiles (p = 0.028). OS among patients with FLT3-ITD positive AML and high-risk genetic changes was similar to patients with unfavorable cytogenetics (p = 0.793) and different from patients with intermediate IGP profile (p = 0.022). Patients with FLT3-ITD negative AML and high-risk mutations, defined as 'unfavorable' in the IGP model, had OS similar to patients with intermediate IGP profile (p = 0.919). Conclusions: The IGP model was not completely validated in our cohort. However, mutations in six out of the nine genes can be used to characterize survival (NPMI, IDH1, IDH2, FLT3-ITD, TET2, DNMT3A) and allow for more robust prognostication in the patients who are re-categorized by the IGP model. These mutations should be incorporated into clinical testing for younger patients outside of clinical trials, in order to guide therapy

Positive and negative well-being and objectively measured sedentary behaviour in older adults: evidence from three cohorts

Background: Sedentary behaviour is related to poorer health independently of time spent in moderate to vigorous physical activity. The aim of this study was to investigate whether wellbeing or symptoms of anxiety or depression predict sedentary behaviour in older adults. Method: Participants were drawn from the Lothian Birth Cohort 1936 (LBC1936) (n = 271), and the West of Scotland Twenty-07 1950s (n = 309) and 1930s (n = 118) cohorts. Sedentary outcomes, sedentary time, and number of sit-to-stand transitions, were measured with a three-dimensional accelerometer (activPAL activity monitor) worn for 7 days. In the Twenty-07 cohorts, symptoms of anxiety and depression were assessed in 2008 and sedentary outcomes were assessed ~ 8 years later in 2015 and 2016. In the LBC1936 cohort, wellbeing and symptoms of anxiety and depression were assessed concurrently with sedentary behaviour in 2015 and 2016. We tested for an association between wellbeing, anxiety or depression and the sedentary outcomes using multivariate regression analysis. Results: We observed no association between wellbeing or symptoms of anxiety and the sedentary outcomes. Symptoms of depression were positively associated with sedentary time in the LBC1936 and Twenty-07 1950s cohort, and negatively associated with number of sit-to-stand transitions in the LBC1936. Meta-analytic estimates of the association between depressive symptoms and sedentary time or number of sit-to-stand transitions, adjusted for age, sex, BMI, long-standing illness, and education, were β = 0.11 (95% CI = 0.03, 0.18) and β = − 0.11 (95% CI = − 0.19, −0.03) respectively. Conclusion: Our findings indicate that depressive symptoms are positively associated with sedentary behavior. Future studies should investigate the causal direction of this association

Influencia del lugar de origen en la utilización de pruebas de cribado de cáncer ginecológico en España

OBJETIVO: Analizar la asociación entre el área geográfica de procedencia en el uso de las citologías y la mamografía. MÉTODOS: Los datos analizados proceden Encuesta Nacional de Salud de España-2006 dirigida a población mayor de 16 años. La Encuesta incluye 13.422 mujeres. Las variables dependientes fueron realización de una mamografía y de una citología vaginal, ambos en los últimos 12 meses. La medida de asociación fue el odds ratio con intervalo de confianza al 95% calculado por regresión logística. RESULTADOS: Tomando como referencia la población española, la probabilidad de realizarse una mamografías entre las mujeres procedentes de África fue 0,36 (IC95% 0,21;0,62) veces menor; Europa del Este 0,40 (IC95% 0,22;0,74) veces menor; Europa Occidental, EEUU y Canadá, 0,60 (IC95% 0,43; 0,84) veces menor y América Central / Sur 0,64 (IC95% 0,52;0,81) veces menor. En relación a la prevención de cáncer de cervix, probabilidad de realizarse una citología entre las mujeres Europa del Este fue 0,38 (IC95% 0,28;0,50) veces menor que la población española, África 0,47 (IC95%:0,33;0,67) veces menor y Europa Occidental, EEUU y Canadá 0,61 (IC95% 0,46;0,81) veces menor. Dichas asociaciones fueron independientes de la edad, indicadores socioeconómicos, estado de salud y cobertura sanitaria. CONCLUSIONES: Las mujeres inmigrantes hacen menor uso de los programas de cribado que las mujeres autóctonas. Este dato podría reflejar dificultades de acceso a los programas preventivos

A Workshop on Cognitive Aging and Impairment in the 9/11-Exposed Population

The terrorist attacks on 11 September 2001 potentially exposed more than 400,000 responders, workers, and residents to psychological and physical stressors, and numerous hazardous pollutants. In 2011, the World Trade Center Health Program (WTCHP) was mandated to monitor and treat persons with 9/11-related adverse health conditions and conduct research on physical and mental health conditions related to the attacks. Emerging evidence suggests that persons exposed to 9/11 may be at increased risk of developing mild cognitive impairment. To investigate further, the WTCHP convened a scientific workshop that examined the natural history of cognitive aging and impairment, biomarkers in the pathway of neurodegenerative diseases, the neuropathological changes associated with hazardous exposures, and the evidence of cognitive decline and impairment in the 9/11-exposed population. Invited participants included scientists actively involved in health-effects research of 9/11-exposed persons and other at-risk populations. Attendees shared relevant research results from their respective programs and discussed several options for enhancements to research and surveillance activities, including the development of a multi-institutional collaborative research network. The goal of this report is to outline the meeting’s agenda and provide an overview of the presentation materials and group discussion

Extending basic principles of measurement models to the design and validation of Patient Reported Outcomes

A recently published article by the Scientific Advisory Committee of the Medical Outcomes Trust presents guidelines for selecting and evaluating health status and health-related quality of life measures used in health outcomes research. In their article, they propose a number of validation and performance criteria with which to evaluate such self-report measures. We provide an alternate, yet complementary, perspective by extending the types of measurement models which are available to the instrument designer. During psychometric development or selection of a Patient Reported Outcome measure it is necessary to determine which, of the five types of measurement models, the measure is based on; 1) a Multiple Effect Indicator model, 2) a Multiple Cause Indicator model, 3) a Single Item Effect Indicator model, 4) a Single Item Cause Indicator model, or 5) a Mixed Multiple Indicator model. Specification of the measurement model has a major influence on decisions about item and scale design, the appropriate application of statistical validation methods, and the suitability of the resulting measure for a particular use in clinical and population-based outcomes research activities