The Individualized Genetic Barrier Predicts Treatment Response in a Large Cohort of HIV-1 Infected Patients

The success of combination antiretroviral therapy is limited by the evolutionary escape dynamics of HIV-1. We used Isotonic Conjunctive Bayesian Networks (I-CBNs), a class of probabilistic graphical models, to describe this process. We employed partial order constraints among viral resistance mutations, which give rise to a limited set of mutational pathways, and we modeled phenotypic drug resistance as monotonically increasing along any escape pathway. Using this model, the individualized genetic barrier (IGB) to each drug is derived as the probability of the virus not acquiring additional mutations that confer resistance. Drug-specific IGBs were combined to obtain the IGB to an entire regimen, which quantifies the virus' genetic potential for developing drug resistance under combination therapy. The IGB was tested as a predictor of therapeutic outcome using between 2,185 and 2,631 treatment change episodes of subtype B infected patients from the Swiss HIV Cohort Study Database, a large observational cohort. Using logistic regression, significant univariate predictors included most of the 18 drugs and single-drug IGBs, the IGB to the entire regimen, the expert rules-based genotypic susceptibility score (GSS), several individual mutations, and the peak viral load before treatment change. In the multivariate analysis, the only genotype-derived variables that remained significantly associated with virological success were GSS and, with 10-fold stronger association, IGB to regimen. When predicting suppression of viral load below 400 cps/ml, IGB outperformed GSS and also improved GSS-containing predictors significantly, but the difference was not significant for suppression below 50 cps/ml. Thus, the IGB to regimen is a novel data-derived predictor of treatment outcome that has potential to improve the interpretation of genotypic drug resistance tests.

[Meningitis (I)--differential diagnosis; aseptic and chronic meningitis].

Meningitis is the most common serious manifestation of infection of the central nervous system. Inflammatory involvement of the subarachnoid space with meningeal irritation leads to the classical triad of headache, fever, and meningism, and to a pleocytosis of the cerebrospinal fluid (CSF). Meningitis is clinically categorized into an acute and chronic disease based on the acuity of symptoms. Acute meningitis develops over hours to days, while in chronic meningitis symptoms evolve over days or even weeks. Aseptic meningitis, in which no bacterial pathogen can be isolated by routine cultures, can mimic bacterial meningitis, but the disease has a much more favorable prognosis. Many cases of aseptic meningitis are caused by viruses, primarily enteroviruses, but bacteria and noninfectious etiologies also cause meningitis with negative cultures. Symptoms of meningeal inflammation with CSF pleocytosis that persist for more than 4 weeks define the chronic meningitis syndrome. The diagnosis is based on the patient history, clinical evidence of meningitis, CSF examination, and often imaging studies. The differential diagnosis is broad, and the predominant CSF cell type can provide clues as to the underlying disease. Empiric therapy is primarily based on the age of the patient, with modifications if there are positive findings on CSF gram stain or if the patient presents with special risk factors. In patients with chronic meningitis, a definite diagnosis is often not available or delayed for days, in which case empiric therapy may have to be initiated. It is important to cover the treatable causes of meningitis, for which the outcome is poor if treatment is delayed.