Adherence to Antiretroviral Treatment and Correlation with Risk of Hospitalization among Commercially Insured HIV Patients in the United States

Purpose: A lower daily pill burden may improve adherence to antiretroviral treatment (ART) and clinical outcomes in patients with human immunodeficiency virus (HIV). This study assessed differences in adherence using the number of pills taken per day, and evaluated how adherence correlated with hospitalization. Methodology: Commercially insured patients in the LifeLink database with an HIV diagnosis (International Classification of Diseases, 9th Revision, Clinical Modification code 042.xx) between 6/1/2006 and 12/31/2008 and receipt of a complete ART regimen were selected for inclusion. Patients were grouped according to their daily pill count and remained on ART for at least 60 days. Outcomes included adherence and rates of hospitalization. Adherence was measured as the proportion of days between the start and end of the regimen in which the patient maintained supply of all initiated ART components. Logistic regressions assessed the relationship between pills per day, adherence, and hospitalization, controlling for demographics, comorbidities, and ART-naïve (vs. experienced) status. Results: 7,073 patients met the study inclusion criteria, and 33.4%, 5.8%, and 60.8 % received an ART regimen comprising one, two, or three or more pills per day, respectively. Regression analysis showed patients receiving a single pill per day were significantly more likely to reach a 95 % adherence threshold versus patients receiving three or more pills per day (odds ratio [OR] = 1.59; P,0.001). Regardless of the number of pills received per day, patients were over 40 % less likely to have

Polymorphism in Gag Gene Cleavage Sites of HIV-1 Non-B Subtype and Virological Outcome of a First-Line Lopinavir/Ritonavir Single Drug Regimen

Virological failure on a boosted-protease inhibitor (PI/r) first-line triple combination is usually not associated with the detection of resistance mutations in the protease gene. Thus, other resistance pathways are being investigated. First-line PI/r monotherapy is the best model to investigate in vivo if the presence of mutations in the cleavage sites (CS) of gag gene prior to any antiretroviral treatment might influence PI/r efficacy. 83 patients were assigned to initiate antiretroviral treatment with first-line lopinavir/r monotherapy in the randomised Monark trial. We compared baseline sequence of gag CS between patients harbouring B or non-B HIV-1 subtype, and between those who achieved viral suppression and those who experienced virological failure while on LPV/r monotherapy up to Week 96. Baseline sequence of gag CS was available for 82/83 isolates; 81/82 carried at least one substitution in gag CS compared to HXB2 sequence. At baseline, non-B subtype isolates were significantly more likely to harbour mutations in gag CS than B subtype isolates (p<0.0001). Twenty-three patients experienced virological failure while on lopinavir/r monotherapy. The presence of more than two substitutions in p2/NC site at baseline significantly predicted virological failure (p = 0.0479), non-B subtype isolates being more likely to harbour more than two substitutions in this specific site. In conclusion, gag cleavage site was highly polymorphic in antiretroviral-naive patients harbouring a non-B HIV-1 strain. We show that pre-therapy mutations in gag cleavage site sequence were significantly associated with the virological outcome of a first-line LPV/r single drug regimen in the Monark trial

HIV-1 co-receptor usage:influence on mother-to-child transmission and pediatric infection

Viral CCR5 usage is not a predictive marker of mother to child transmission (MTCT) of HIV-1. CXCR4-using viral variants are little represented in pregnant women, have an increased although not significant risk of transmission and can be eventually also detected in the neonates. Genetic polymorphisms are more frequently of relevance in the child than in the mother. However, specific tissues as the placenta or the intestine, which are involved in the prevalent routes of infection in MTCT, may play an important role of selective barriers

Self-reported race/ethnicity in the age of genomic research: its potential impact on understanding health disparities

This review explores the limitations of self-reported race, ethnicity, and genetic ancestry in biomedical research. Various terminologies are used to classify human differences in genomic research including race, ethnicity, and ancestry. Although race and ethnicity are related, race refers to a person’s physical appearance, such as skin color and eye color. Ethnicity, on the other hand, refers to communality in cultural heritage, language, social practice, traditions, and geopolitical factors. Genetic ancestry inferred using ancestry informative markers (AIMs) is based on genetic/genomic data. Phenotype-based race/ethnicity information and data computed using AIMs often disagree. For example, self-reporting African Americans can have drastically different levels of African or European ancestry. Genetic analysis of individual ancestry shows that some self-identified African Americans have up to 99% of European ancestry, whereas some self-identified European Americans have substantial admixture from African ancestry. Similarly, African ancestry in the Latino population varies between 3% in Mexican Americans to 16% in Puerto Ricans. The implication of this is that, in African American or Latino populations, self-reported ancestry may not be as accurate as direct assessment of individual genomic information in predicting treatment outcomes. To better understand human genetic variation in the context of health disparities, we suggest using “ancestry” (or biogeographical ancestry) to describe actual genetic variation, “race” to describe health disparity in societies characterized by racial categories, and “ethnicity” to describe traditions, lifestyle, diet, and values. We also suggest using ancestry informative markers for precise characterization of individuals’ biological ancestry. Understanding the sources of human genetic variation and the causes of health disparities could lead to interventions that would improve the health of all individuals