Adjunctive corticosteroids for Pneumocystis jiroveci pneumonia in patients with HIV-infection

BACKGROUND: Pneumocystis jiroveci pneumonia (PCP) remains the most common opportunistic infection in patients infected with the human immunodeficiency virus (HIV). Among patients with HIV infection and PCP the mortality rate is 10 to 20% during the initial infection and increases substantially with the need for mechanical ventilation. It was suggested that in these patients corticosteroids adjunctive to standard treatment for PCP could prevent the need for mechanical ventilation and decrease mortality. OBJECTIVES: To assess the effects of adjunctive corticosteroids on overall mortality and the need for mechanical ventilation in HIV-infected patients with PCP and substantial hypoxemia (arterial oxygen partial pressure <70 mmHg or alveolar-arterial gradient >35 mmHg on room air). SEARCH STRATEGY: We searched Medline (January 1980-December 2004), EMBASE (January 1985-December 2004) and The Cochrane Library (Issue 4, 2004) without language restrictions to identify randomised controlled trials that compared adjunctive corticosteroids to control in HIV-infected patients with PCP. We further reviewed the reference lists from previously published overviews, we searched UptoDate version 2005 and Clinical Evidence Concise (Issue 12, 2004), contacted experts of the field, and searched reference lists of identified publications for citations of additional relevant articles. SELECTION CRITERIA: Trials were considered eligible for this review if they compared corticosteroids to placebo or usual care in HIV-infected patients with PCP in addition to baseline treatment with trimethoprim-sulfamethoxazole, pentamidine or dapsone-trimethoprim, used random allocation, and reported mortality data. We excluded trials in patients with no or mild hypoxemia (arterial oxygen partial pressure >70 mmHg or an alveolar-arterial gradient <35 mmHg on room air) and trials with a follow-up of less than 30 days. DATA COLLECTION AND ANALYSIS: Two teams of reviewers independently evaluated the methodology and extracted data from each primary study. We pooled treatment effects across studies and calculated a weighted average risk ratio of overall mortality in the treatment and control groups by using a random effects model. MAIN RESULTS: Six studies were included in the review and meta-analysis. Risk ratios for overall mortality for adjunctive corticosteroids were 0.56 (95% confidence interval [CI], 0.32-0.98) at 1 month and 0.68 (95% CI, 0.50-0.94) at 3-4 months of follow-up. To prevent 1 death, numbers needed to treat are 9 patients in a setting without highly active antiretroviral therapy (HAART) available, and 23 patients with HAART available. Only the 3 largest trials provided data on the need for mechanical ventilation with a risk ratio of 0.38 (95% CI, 0.20-0.73) in favour of adjunctive corticosteroids. AUTHORS' CONCLUSIONS: The number and size of trials investigating adjunctive corticosteroids for HIV-infected patients with PCP is small, but evidence from this review suggests a beneficial effect for patients with substantial hypoxemia.

Estimating the Number of Essential Genes in a Genome by Random Transposon Mutagenesis

We describe a Bayesian method for estimating the number of essential genes in a genome, on the basis of data on viable mutants for which a single transposon was inserted after a random TA site in a genome,potentially disrupting a gene. The prior distribution for the number of essential genes was taken to be uniform. A Gibbs sampler was used to estimate the posterior distribution. The method is illustrated with simulated data. Further simulations were used to study the performance of the procedure.

Posterior Simulation in the Generalized Linear Model with Semiparmetric Random Effects

Generalized linear mixed models with semiparametric random effects are useful in a wide variety of Bayesian applications. When the random effects arise from a mixture of Dirichlet process (MDP) model, normal base measures and Gibbs sampling procedures based on the Pólya urn scheme are often used to simulate posterior draws. These algorithms are applicable in the conjugate case when (for a normal base measure) the likelihood is normal. In the non-conjugate case, the algorithms proposed by MacEachern and Müller (1998) and Neal (2000) are often applied to generate posterior samples. Some common problems associated with simulation algorithms for non-conjugate MDP models include convergence and mixing difficulties. This paper proposes an algorithm based on the Pólya urn scheme that extends the Gibbs sampling algorithms to non-conjugate models with normal base measures and exponential family likelihoods. The algorithm proceeds by making Laplace approximations to the likelihood function, thereby reducing the procedure to that of conjugate normal MDP models. To ensure the validity of the stationary distribution in the non-conjugate case, the proposals are accepted or rejected by a Metropolis-Hastings step. In the special case where the data are normally distributed, the algorithm is identical to the Gibbs sampler.

The Optimal Confidence Region for a Random Parameter

Under a two-level hierarchical model, suppose that the distribution of the random parameter is known or can be estimated well. Data are generated via a fixed, but unobservable realization of this parameter. In this paper, we derive the smallest confidence region of the random parameter under a joint Bayesian/frequentist paradigm. On average this optimal region can be much smaller than the corresponding Bayesian highest posterior density region. The new estimation procedure is appealing when one deals with data generated under a highly parallel structure, for example, data from a trial with a large number of clinical centers involved or genome-wide gene-expession data for estimating individual gene- or center-specific parameters simultaneously. The new proposal is illustrated with a typical microarray data set and its performance is examined via a small simulation study.