A metagenomics method for the quantitative detection of bacterial pathogens causing hospital-associated and ventilator-associated pneumonia

IMPORTANCE

The management of ventilator-associated pneumonia and hospital-acquired pneumonia requires rapid and accurate quantitative detection of the infecting pathogen. To this end, we propose a metagenomic sequencing assay that includes the use of an internal sample processing control for the quantitative detection of 20 relevant bacterial species from bronchoalveolar lavage samples.

Adherence to antiretroviral therapy, virological response, and time to resistance in the Dakar cohort

In 1998, with the launch of the Senegalese Initiative for Antiretroviral Access (ISAARV), Senegal became one of the first African countries to propose an antiretroviral access program. Our objective in this paper is to study the time to any first drug resistance, as well as predictors of the time to resistance. We propose a joint model to study the effect of adherence to the HAART therapy, and virological response on the time to resistance mutations. A logistic mixed model is used to model the time-dependent adherence process; and a Markov model is used to study the virological response. Given the presence of missing data in the adherence process and in the virological response, the latent adherence and virological states are then included in the linear predictor of the time to resistance model. The proposed time to resistance model takes into account interval-censored data as well as null hazard periods, during which the viral replication is very low. A Bayesian approach is used for accommodating with missing data and for prediction. We also propose model checking tools to study model adequacy.

Application of the promotion time cure model with time-changing exposure to the study of HIV/AIDS and other infectious diseases

Infectious diseases are caused by single or successive contacts with pathogens. Nevertheless, contacts with pathogens do not implicate infection. In 1993, Yakovlev et al. proposed a model to study a population of cancer patients with a cured fraction, a well adapted model to describe an infectious disease with a unique infection occasion. Extensions of this model have been proposed in the recent years. We present a mechanistic formulation in the context of infectious diseases with multiple infection occasions. It is a mixture model that enables to study risk factors associated with infection intensity at each infection occasion and factors shortening the delay from exposure to clinical event. Simulations are performed to evaluate the model fitting and two examples are presented for illustration: an analysis of an HIV-1 mother-to-child transmission data set and an analysis of nosocomial urinary tract infections data set.

Extensive multiallelic analysis of the relationship between HLA-DRB1 and rheumatoid arthritis using a Bayesian partition model

To analyse the association between individual HLA-DRB1 locus genotypes and rheumatoid arthritis (RA) susceptibility, taking in account the multiallelic nature of the shared epitope (SE). In total, 538 patients and 536 controls were genotyped for 12 alleles of the HLA-DRB1 locus. A Bayesian partition model and multivariate logistic models were used to assess the role of the SE and of its individual components. The SE was associated with RA susceptibility (odds ratio (OR) 2 versus 0 SE copy=9.99 (95 CI 4.69-15.30) and OR 1 versus 0 SE copy=3.16 (95% CI 2.42-4.12)). The Bayesian partition model supplied a permutation of the HLA-DRBA locus alleles ordered by increasing disease risk. Alleles associated with highest risks are those that code for the SE. The individual OR estimations for the HLA-DRB1 locus genotypes went from OR=1.00 (95% CI 1.00-1.25) for the less associated genotype to OR=21.40 (95% CI 8.02-65.79) for the most associated one. In conclusion, the allele order risk and the OR estimations for individual genotypes of the HLA-DRB1 locus were consistent with the SE theory. Using an exploratory statistical method without a priori hypothesis, our study allowed a detailed analysis of the multiallelic nature of the SE.