Reverse Transcriptase Inhibitors

Data for this analysis were taken from the LifeLink database (formerly the PharMetrics Integrated Outcomes database), a national insurance claims database encompassing 95 United States managed care organizations covering over 61 million lives between 1997 and 2008. This database contains patient-level demographics, periods of health plan enrollment, primary and secondary diagnoses, and detailed information about hospitalizations and therapeutic procedures, inpatient and outpatient physician services, and prescription drug use. In compliance with the Health Insurance and Portability and Accountability Act of 1996, all data were de-identified to protect the privacy of individual patients, physicians, and hospitals. Because the data were retrospective, preexisting, and de-identified, RTI International's institutional review board determined that this study met all criteria for exemption.
Patients were selected for inclusion if they received at least one HIV or AIDS diagnosis (International Classification of Diseases, 9th Revision, Clinical Modification [ICD-9-CM] code 042.xx) between June 1, 2006, and December 31, 2008. Patients also were required to have evidence of receipt of a complete ART regimen, defined as two nucleoside/nucleotide reverse transcriptase inhibitors plus a third agent (i.e., another nucleoside/nucleotide reverse transcriptase inhibitor, a nonnucleoside/nucleotide reverse transcriptase inhibitor, a protease inhibitor [PI], a chemokine receipt 5 antagonist, or an integrase inhibitor). ART agents were identified in the claims database by using National Drug Codes associated with relevant generic and brand names. Further, patients were required to remain on the complete regimen for at least 60 days following first observed uptake and to have evidence of continuous enrollment in their health plan during this period.
Patients were grouped into three mutually exclusive cohorts according to the daily pill count of their complete ART regimen. Patients were assigned to the single-pill-per-day cohort if they received an ART regimen consisting of a single pill at any point during the selection window, regardless of prior or subsequent use of other regimens. At the time of this study, only coformulated tenofovir/emtricitabine/efavirenz was available as a single pill per day. Patients were assigned to the two-pills-per-day cohort if they received a regimen consisting of two pills per day at any point during the selection window and if they did not receive a regimen consisting of a single pill per day at any point during the selection window. Finally, patients were assigned to the three-or-more-pills-per-day cohort if they received a regimen consisting of three or more pills per day at any point during the selection window and if they did not receive a regimen consisting of either a single pill per day or two pills per day at any point during the selection window.
Patients were followed from the start of their complete ART regimen (which defined the study index date) until the earliest date of regimen discontinuation, disenrollment from the health plan, or the end of the database (i.e., March 31, 2009). Discontinuation was defined as 90 consecutive days in which no refills were observed for any component of the regimen.
Patient characteristics measured at the index date included age, sex, geographic region, health insurance coverage, and ART classes received (i.e., nucleoside/nucleotide reverse transcriptase inhibitors, nonnucleoside/nucleotide reverse transcriptase inhibitors, PIs, ritonavir boosting, and other therapies). The presence of comorbid medical conditions other than HIV or AIDS was assessed during the 6-month pre-index period using an established algorithm, the Charlson Comorbidity Index (CCI) score [12] (link). This score is made up of 17 comorbidities (defined by ICD-9-CM diagnosis and procedure codes), such as myocardial infarction and chronic pulmonary disease, which are weighted to correspond to the severity of the comorbid condition of interest. A higher comorbidity score represents a higher overall comorbidity burden during the pre-index period. Additionally, the incidence of other concomitant mental disorders (ICD-9-CM codes 306.xx to 319.xx) and drug and alcohol abuse (ICD-9-CM codes 292.xx and 303.xx to 305.xx) during the 6-month pre-index period also were assessed.
Medication adherence was assessed using the medication possession ratio (MPR), which has been shown to be the most widely adopted measure in published claims-based analyses (57% of all studies) of medication adherence [13] (link) and has been used in studies of ART adherence among individuals with HIV [14] (link). For each patient, the MPR was calculated over the period in which the patient remained exposed to his or her ART regimen. The MPR, which is a proxy for refill compliance, generally measures the proportion of the ART exposure period in which supply was maintained for all ART components comprising the regimen. Specifically, MPR was calculated as the number of filled prescription days for all ART regimen components (using the days supplied in the pharmacy claims) divided by the number of days from the first observed prescription in the regimen through the earliest of either the exhaustion of the days supplied of the last observed prescription or the end of follow-up. For patients in either of the two- or three-or-more-pill-per-day cohorts, late refills and resulting days of missing supply for only one ART component were factored against their adherence measurement. Patients in the three-or-more pills-per-day cohort with a supply for only two of their ART components on a given day, for example, were considered to have zero adherence for that day. In addition to reporting the mean (standard deviation) MPR achieved, we also reported the numbers and percentages of patients achieving various adherence thresholds (i.e., MPRs of 0.95, 0.90, 0.85, and 0.80, corresponding to 95%, 90%, 85%, and 80% adherence, respectively).
Hospitalizations were identified from the claims database using relevant place of service codes. Hospitalizations were observed from the index date until the earliest date of regimen discontinuation, end of enrollment in the health plan, or end of the database. The number and percentage of patients with at least one hospitalization were reported, along with the mean (standard deviation) number of hospitalizations.
All analyses were carried out using SAS (Version 9; Cary, North Carolina) statistical software. Descriptive analyses were conducted for all outcome measures and included means and standard deviations for continuous variables of interest (e.g., MPR) and frequency distributions of categorical variables of interest (e.g., geographic region). All descriptive analyses were stratified by each pill-count cohort.
Multivariate logistic regression analyses were conducted to assess the relationship between the number of pills per day, adherence, and hospitalization. The dependent variables included binary indicators for achieving an MPR threshold of 0.95 (i.e., 95% adherence) and whether the patient was hospitalized during exposure to the ART regimen. Independent variables included in each logistic model were as follows: treatment regimen received (i.e., single pill per day and two pills per day vs. the reference category of three or more pills per day), age, sex, geographic region, health plan type, payer type, CCI score, treatment-naïve status, pre-index presence of mental health disorders, and pre-index presence of alcohol or drug abuse disorders. Since the number of pills received per day and achieving a 95% adherence threshold were likely proxies for each other, two separate models assessing hospitalization risk were estimated. Odds ratios (ORs) were reported for all covariates.

Continuous variables are reported as mean ± standard deviation or median [25th–75th interquartile range], as appropriate. Categorical variables are reported in frequency and percentages. Student t test or Mann–Whitney U test was used to compare normally and nonnormally distributed variables between participants with HIV and controls and chi-squared test was used to compare categorical variables.
The association of EF density with cardiovascular risk factors, as well as with HIV related parameters, was assessed using univariable and multivariable linear regression models, with and without inclusion of EF volume into the models. Multivariable model included all HIV-related parameters and cardiovascular risk factors risk factors significantly associated with EF density.
The association of EF density with coronary plaque (CAC, total, calcified, noncalcified and mixed plaque volume) was evaluated using zero-inflated Poisson regression, as previously described.^{[10 (link)]} The use of zero-inflated model is made necessary by the excess of 0 in the distribution of total coronary plaque volumes. Coronary plaque volume variables were natural-log transformed prior to statistical analysis. Multivariable models were adjusted for CVD risk factors.
In addition and as an exploratory analysis, the association of EF with inflammatory biomarkers was evaluated using univariable and multivariable linear regression models. Multivariable models included inflammatory biomarkers and CVD risk factors if they showed a univariable association with EF. As this analysis was hypothesis-generating, we did multiple tests and did not correct for multiple comparisons.
Effect modification by HIV of each association was assessed by inclusion of an interaction term to the fully adjusted models, and significance of the interaction term was assessed by a likelihood ratio test.
For patients with incomplete data, the mean or median value was used to impute the missing data. Values for the following number of participants were missing and imputed: Body mass index (BMI),^{[5 (link)]} smoking exposure,^{[14 (link)]} high density lipoprotein-cholesterol,^{[4 (link)]} low density lipoprotein-cholesterol,^{[9 (link)]} antiretroviral therapy (ART) exposure duration,^{[7 (link)]} non-nucleoside reverse transcriptase inhibitors exposure duration.^{[7 (link)]} A P value <.05 was considered statistically significant. Statistical analyses were performed using R (version 3.3.2; R Foundation for Statistical Computing, Vienna, Austria).

This study utilized a case-series design comparing the hepatic expression of cholesterol regulating genes in HIV-positive (case) and HIV-negative (control) patients presenting with symptomatic gallstones. Ethical approval was obtained from the University of KwaZulu Natal (UKZN) Biomedical Research Ethics Committee (BREC) (BE276/16). Patients undergoing cholecystectomy for gallstone disease (biliary cholic, cholecystitis, jaundice, and gallstone pancreatitis) at King Edward VIII Hospital, Durban, KwaZulu Natal, South Africa, from January–December 2017 were recruited. In total, 96 Black South African women provided informed consent (standard consent form in two official main languages, i.e., English and isiZulu) for the retrieval of a liver biopsy and the recording of patient clinical parameters, including age, race, BMI, family history of gallstones, and comorbidities (HIV, hypertension, diabetes, hypercholesterolemia). The study was carried out in accordance with the institutional guidelines.
Following the analysis of clinical parameters in all subjects, five HIV-negative (control) and five HIV-positive (cases) were selected for mRNA analysis to identify if hepatic nuclear factors were differentially regulated. All patients selected were of Black African ethnicity and female gender, with no co-morbidities (diabetes and hypertensive statin therapy, hepatitis infection, or tuberculosis treatment). All HIV-positive patients were on fixed dose combination (FDC) therapy, with CD4 counts above 500 cells/mm³ and undetectable viral loads. The FDC regimen consisted of 3 drugs, namely two nucleoside reverse transcriptase inhibitors (NRTIs) drugs [tenofovir disoproxil fumarate (TDF) and emtricitabine (FTC)] and one non-nucleoside reverse transcriptase inhibitor (NNRTI) [efavirenz (EFV)]. Common second-line agents used were protease inhibitors (PI) [lopinivar/ritonavir (Aluvia) or atazanavir/ritonavir]. None of the patients were on integrase strand transfer inhibitor (InSTI) [dolutegravir (DTG)] based therapies.