A prospective study of mortality from cryptococcal meningitis following treatment induction with 1200 mg oral fluconazole in Blantyre, Malawi.

OBJECTIVE: We have previously reported high ten-week mortality from cryptococcal meningitis in Malawian adults following treatment-induction with 800 mg oral fluconazole (57% [33/58]). National guidelines in Malawi and other African countries now advocate an increased induction dose of 1200 mg. We assessed whether this has improved outcomes. DESIGN: This was a prospective observational study of HIV-infected adults with cryptococcal meningitis confirmed by diagnostic lumbar puncture. Treatment was with fluconazole 1200 mg/day for two weeks then 400mg/day for 8 weeks. Mortality within the first 10 weeks was the study end-point, and current results were compared with data from our prior patient cohort who started on fluconazole 800 mg/day. RESULTS: 47 participants received fluconazole monotherapy. Despite a treatment-induction dose of 1200 mg, ten-week mortality remained 55% (26/47). This was no better than our previous study (Hazard Ratio [HR] of death on 1200 mg vs. 800 mg fluconazole: 1.29 (95% CI: 0.77-2.16, p = 0.332)). There was some evidence for improved survival in patients who had repeat lumbar punctures during early therapy to lower intracranial pressure (HR: 0.27 [95% CI: 0.07-1.03, p = 0.055]). CONCLUSION: There remains an urgent need to identify more effective, affordable and deliverable regimens for cryptococcal meningitis

Evidence of improving antiretroviral therapy treatment delays: an analysis of eight years of programmatic outcomes in Blantyre, Malawi

Background: Impressive achievements have been made towards achieving universal coverage of antiretroviral therapy (ART) in sub-Saharan Africa. However, the effects of rapid ART scale-up on delays between HIV diagnosis and treatment initiation have not been well described. Methods: A retrospective cohort study covering eight years of ART initiators (2004–2011) was conducted at Queen Elizabeth Central Hospital (QECH) in Blantyre, Malawi. The time between most recent positive HIV test and ART initiation was calculated and temporal trends in delay to initiation were described. Factors associated with time to initiation were investigated using multivariate regression analysis. Results: From 2004–2011, there were 15,949 ART initiations at QECH (56% female; 8% children [0–10 years] and 5%adolescents [10–20 years]). Male initiators were likely to have more advanced HIV infection at initiation than female initiators (70% vs. 64% in WHO stage 3 or 4). Over the eight years studied, there were declines in treatment delay, with 2011 having the shortest delay at 36.5 days. On multivariate analysis CD4 count <50 cells/μl (adjusted geometric mean ratio [aGMR]: aGMR: 0.53, bias-corrected accelerated [BCA] 95% CI: 0.42-0.68) was associated with shorter ART treatment delay. Women (aGMR: 1.12, BCA 95% CI: 1.03-1.22) and patients diagnosed with HIV at another facility outside QECH (aGMR: 1.61, BCA 95% CI: 1.47-1.77) had significantly longer treatment delay. Conclusions: Continued improvements in treatment delays provide evidence that universal access to ART can be achieved using the public health approach adopted by Malawi However, the longer delays for women and patients diagnosed at outlying sites emphasises the need for targeted interventions to support equitable access for these groups

Longitudinal Pharmacokinetic-Pharmacodynamic Biomarkers Correlate With Treatment Outcome in Drug-Sensitive Pulmonary Tuberculosis: A Population Pharmacokinetic-Pharmacodynamic Analysis

BACKGROUND: This study aims to explore relationships between baseline demographic covariates, plasma antibiotic exposure, sputum bacillary load, and clinical outcome data to help improve future tuberculosis (TB) treatment response predictions. METHODS: Data were available from a longitudinal cohort study in Malawian drug-sensitive TB patients on standard therapy, including steady-state plasma antibiotic exposure (154 patients), sputum bacillary load (102 patients), final outcome (95 patients), and clinical details. Population pharmacokinetic and pharmacokinetic-pharmacodynamic models were developed in the software package NONMEM. Outcome data were analyzed using univariate logistic regression and Cox proportional hazard models in R, a free software for statistical computing. RESULTS: Higher isoniazid exposure correlated with increased bacillary killing in sputum (P < .01). Bacillary killing in sputum remained fast, with later progression to biphasic decline, in patients with higher rifampicin area under the curve (AUC)_{0-24} (P < .01). Serial sputum colony counting negativity at month 2 (P < .05), isoniazid C_{MAX} (P < .05), isoniazid C_{MAX}/minimum inhibitory concentration ([MIC] P < .01), and isoniazid AUC_{0-24}/MIC (P < .01) correlated with treatment success but not with remaining free of TB. Slower bacillary killing (P < .05) and earlier progression to biphasic bacillary decline (P < .01) both correlate with treatment failure. Posttreatment recurrence only correlated with slower bacillary killing (P < .05). CONCLUSIONS: Patterns of early bacillary clearance matter. Static measurements such as month 2 sputum conversion and pharmacokinetic parameters such as C_{MAX}/MIC and AUC_{0-24}/MIC were predictive of treatment failure, but modeling of quantitative longitudinal data was required to assess the risk of recurrence. Pooled individual patient data analyses from larger datasets are needed to confirm these findings

All nonadherence is equal but is some more equal than others? Tuberculosis in the digital era

Adherence to treatment for tuberculosis (TB) has been a concern for many decades, resulting in the World Health Organization's recommendation of the direct observation of treatment in the 1990s. Recent advances in digital adherence technologies (DATs) have renewed discussion on how to best address nonadherence, as well as offering important information on dose-by-dose adherence patterns and their variability between countries and settings. Previous studies have largely focussed on percentage thresholds to delineate sufficient adherence, but this is misleading and limited, given the complex and dynamic nature of adherence over the treatment course. Instead, we apply a standardised taxonomy – as adopted by the international adherence community – to dose-by-dose medication-taking data, which divides missed doses into 1) late/noninitiation (starting treatment later than expected/not starting), 2) discontinuation (ending treatment early), and 3) suboptimal implementation (intermittent missed doses). Using this taxonomy, we can consider the implications of different forms of nonadherence for intervention and regimen design. For example, can treatment regimens be adapted to increase the “forgiveness” of common patterns of suboptimal implementation to protect against treatment failure and the development of drug resistance? Is it reasonable to treat all missed doses of treatment as equally problematic and equally common when deploying DATs? Can DAT data be used to indicate the patients that need enhanced levels of support during their treatment course? Critically, we pinpoint key areas where knowledge regarding treatment adherence is sparse and impeding scientific progress

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)

A Bayesian method for evaluating and discovering disease loci associations

Background: A genome-wide association study (GWAS) typically involves examining representative SNPs in individuals from some population. A GWAS data set can concern a million SNPs and may soon concern billions. Researchers investigate the association of each SNP individually with a disease, and it is becoming increasingly commonplace to also analyze multi-SNP associations. Techniques for handling so many hypotheses include the Bonferroni correction and recently developed Bayesian methods. These methods can encounter problems. Most importantly, they are not applicable to a complex multi-locus hypothesis which has several competing hypotheses rather than only a null hypothesis. A method that computes the posterior probability of complex hypotheses is a pressing need. Methodology/Findings: We introduce the Bayesian network posterior probability (BNPP) method which addresses the difficulties. The method represents the relationship between a disease and SNPs using a directed acyclic graph (DAG) model, and computes the likelihood of such models using a Bayesian network scoring criterion. The posterior probability of a hypothesis is computed based on the likelihoods of all competing hypotheses. The BNPP can not only be used to evaluate a hypothesis that has previously been discovered or suspected, but also to discover new disease loci associations. The results of experiments using simulated and real data sets are presented. Our results concerning simulated data sets indicate that the BNPP exhibits both better evaluation and discovery performance than does a p-value based method. For the real data sets, previous findings in the literature are confirmed and additional findings are found. Conclusions/Significance: We conclude that the BNPP resolves a pressing problem by providing a way to compute the posterior probability of complex multi-locus hypotheses. A researcher can use the BNPP to determine the expected utility of investigating a hypothesis further. Furthermore, we conclude that the BNPP is a promising method for discovering disease loci associations. © 2011 Jiang et al

Long term time variability of cosmic rays and possible relevance to the development of life on Earth

An analysis is made of the manner in which the cosmic ray intensity at Earth has varied over its existence and its possible relevance to both the origin and the evolution of life. Much of the analysis relates to the 'high energy' cosmic rays ($E>10^{14}eV;=0.1PeV$) and their variability due to the changing proximity of the solar system to supernova remnants which are generally believed to be responsible for most cosmic rays up to PeV energies. It is pointed out that, on a statistical basis, there will have been considerable variations in the likely 100 My between the Earth's biosphere reaching reasonable stability and the onset of very elementary life. Interestingly, there is the increasingly strong possibility that PeV cosmic rays are responsible for the initiation of terrestrial lightning strokes and the possibility arises of considerable increases in the frequency of lightnings and thereby the formation of some of the complex molecules which are the 'building blocks of life'. Attention is also given to the well known generation of the oxides of nitrogen by lightning strokes which are poisonous to animal life but helpful to plant growth; here, too, the violent swings of cosmic ray intensities may have had relevance to evolutionary changes. A particular variant of the cosmic ray acceleration model, put forward by us, predicts an increase in lightning rate in the past and this has been sought in Korean historical records. Finally, the time dependence of the overall cosmic ray intensity, which manifests itself mainly at sub-10 GeV energies, has been examined. The relevance of cosmic rays to the 'global electrical circuit' points to the importance of this concept.Comment: 18 pages, 5 figures, accepted by 'Surveys in Geophysics

Hierarchy Theory of Evolution and the Extended Evolutionary Synthesis: Some Epistemic Bridges, Some Conceptual Rifts

Contemporary evolutionary biology comprises a plural landscape of multiple co-existent conceptual frameworks and strenuous voices that disagree on the nature and scope of evolutionary theory. Since the mid-eighties, some of these conceptual frameworks have denounced the ontologies of the Modern Synthesis and of the updated Standard Theory of Evolution as unfinished or even flawed. In this paper, we analyze and compare two of those conceptual frameworks, namely Niles Eldredge’s Hierarchy Theory of Evolution (with its extended ontology of evolutionary entities) and the Extended Evolutionary Synthesis (with its proposal of an extended ontology of evolutionary processes), in an attempt to map some epistemic bridges (e.g. compatible views of causation; niche construction) and some conceptual rifts (e.g. extra-genetic inheritance; different perspectives on macroevolution; contrasting standpoints held in the “externalism–internalism” debate) that exist between them. This paper seeks to encourage theoretical, philosophical and historiographical discussions about pluralism or the possible unification of contemporary evolutionary biology

An approach for the identification of targets specific to bone metastasis using cancer genes interactome and gene ontology analysis

Metastasis is one of the most enigmatic aspects of cancer pathogenesis and is a major cause of cancer-associated mortality. Secondary bone cancer (SBC) is a complex disease caused by metastasis of tumor cells from their primary site and is characterized by intricate interplay of molecular interactions. Identification of targets for multifactorial diseases such as SBC, the most frequent complication of breast and prostate cancers, is a challenge. Towards achieving our aim of identification of targets specific to SBC, we constructed a 'Cancer Genes Network', a representative protein interactome of cancer genes. Using graph theoretical methods, we obtained a set of key genes that are relevant for generic mechanisms of cancers and have a role in biological essentiality. We also compiled a curated dataset of 391 SBC genes from published literature which serves as a basis of ontological correlates of secondary bone cancer. Building on these results, we implement a strategy based on generic cancer genes, SBC genes and gene ontology enrichment method, to obtain a set of targets that are specific to bone metastasis. Through this study, we present an approach for probing one of the major complications in cancers, namely, metastasis. The results on genes that play generic roles in cancer phenotype, obtained by network analysis of 'Cancer Genes Network', have broader implications in understanding the role of molecular regulators in mechanisms of cancers. Specifically, our study provides a set of potential targets that are of ontological and regulatory relevance to secondary bone cancer.Comment: 54 pages (19 pages main text; 11 Figures; 26 pages of supplementary information). Revised after critical reviews. Accepted for Publication in PLoS ON

A multi-center population-based case–control study of ovarian cancer in African-American women: the African American Cancer Epidemiology Study (AACES)

Abstract: Background: Ovarian cancer (OVCA) is the leading cause of death from gynecological cancer, with poorer survival for African American (AA) women compared to whites. However, little is known about risk factors for OVCA in AA. To study the epidemiology of OVCA in this population, we started a collaborative effort in 10 sites in the US. Here we describe the study and highlight the challenges of conducting a study of a lethal disease in a minority population. Methods: The African American Cancer Epidemiology Study (AACES) is an ongoing, population-based case–control study of OVCA in AA in 10 geographic locations, aiming to recruit 850 women with invasive epithelial OVCA and 850 controls age- and geographically-matched to cases. Rapid case ascertainment and random-digit-dialing systems are in place to ascertain cases and controls, respectively. A telephone survey focuses on risk factors as well as factors of particular relevance for AAs. Food-frequency questionnaires, follow-up surveys, biospecimens and medical records are also obtained. Results: Current accrual of 403 AA OVCA cases and 639 controls exceeds that of any existing study to date. We observed a high proportion (15%) of deceased non-responders among the cases that in part is explained by advanced stage at diagnosis. A logistic regression model did not support that socio-economic status was a factor in advanced stage at diagnosis. Most risk factor associations were in the expected direction and magnitude. High BMI was associated with ovarian cancer risk, with multivariable adjusted ORs and 95% CIs of 1.50 (0.99-2.27) for obese and 1.27 (0.85- 1.91) for morbidly obese women compared to normal/underweight women. Conclusions: AACES targets a rare tumor in AAs and addresses issues most relevant to this population. The importance of the study is accentuated by the high proportion of OVCA cases ascertained as deceased. Our analyses indicated that obesity, highly prevalent in this population (>60% of the cases), was associated with increased OVCA risk. While these findings need to be replicated, they suggest the potential for an effective intervention on the risk in AAs. Upon completion of enrollment, AACES will be the largest epidemiologic study of OVCA in AA women