Faculty Bibliography

OBJECTIVES: We aimed to determine adherence, virological, and immunological outcomes one year after starting a first combination antiretroviral therapy (ART) regimen. DESIGN: Observational; synthesis of administrative, laboratory, and pharmacy data. Antiretroviral regimens were divided into efavirenz, nevirapine, boosted protease inhibitor (PI), and single PI categories. Propensity scores were used to control for confounding by treatment assignment. Adherence was estimated from pharmacy refill records. SETTING: Veterans Affairs Healthcare System, all sites. PARTICIPANTS: HIV-infected individuals starting combination ART with a low likelihood of previous antiretroviral exposure. INTERVENTIONS: None. OUTCOMES: The proportion of antiretroviral prescriptions filled as prescribed, a change in log HIV-RNA, the proportion with log HIV-RNA viral suppression, a change in CD4 cell count. RESULTS: A total of 6394 individuals unlikely to have previous antiretroviral exposure started combination ART between 1996 and 2004, and were eligible for analysis. Adherence overall was low (63% of prescriptions filled as prescribed), and adherence with efavirenz (67%) and nevirapine (65%) regimens was significantly greater than adherence with boosted PI (59%) or single PI (61%) regimens (P < 0.001). Efavirenz regimens were more likely to suppress HIV-RNA at one year (74%) compared with nevirapine (62%), boosted PI (63%), or single PI (53%) regimens (all P < 0.001), and this superiority was maintained when analyses were adjusted for baseline clinical characteristics and propensity for treatment assignment. Efavirenz also yielded more favorable immunological outcomes. CONCLUSION: HIV-infected individuals initiating their first combination ART using an efavirenz-based regimen had improved virological and immunological outcomes and greater adherence levels

BACKGROUND: Cigarette smoking is an important risk factor for morbidity and mortality in HIV-positive patients on combination antiretroviral therapy. OBJECTIVE: To determine whether awareness of smoking differs between HIV and non-HIV providers, and to identify factors associated with failure to recognize current smoking. DESIGN: Observational study. PARTICIPANTS: 801 HIV-positive and 602 HIV-negative patients, 72 HIV and 71 non-HIV providers enrolled in the Veterans Aging Cohort 5 Site Study. MEASUREMENTS: Data sources included patient and provider questionnaires; electronic medical records; and the national administrative VA database. We calculated sensitivity, specificity, and measures of agreement between patient- and provider-reported smoking, and examined factors associated with failure to recognize current smoking using logistic regression. RESULTS: Whereas most providers were correct when they identified a patient as a current smoker (specificity > or = 90%), HIV providers missed current smoking more often (sensitivity 65% for HIV vs. 82% for non-HIV). Kappa scores for current smoking were significantly lower for HIV compared to non-HIV providers (0.55 vs. 0.75, p < .001). In models adjusted for age, gender, race, and other differences, patient HIV status and provider specialty in infectious diseases were independent predictors of a provider's failure to recognize current smoking. Comorbid illnesses, cough/dyspnea, degree of immune competence and HIV viral suppression did not impact recognition of current smoking. Only 39% of HIV providers reported confidence in their ability to influence smoking cessation compared to 62% of non-HIV providers (p = .049). CONCLUSIONS: Interventions to increase HIV provider awareness of current smoking and skills to influence smoking cessation are needed. Efforts should also target patient populations with smoking-related comorbid diseases who would especially benefit from smoking cessation

OBJECTIVE: HIV mutation accumulation has great implications for pharmacoeconomics and clinical care, yet scarcity of data has hindered its representation in decision analytic models. Our objective is to determine the accuracy with which mutation accumulation and other unmeasured parameters could be estimated during model calibration. METHODS: We used a second-order Monte Carlo simulation of HIV natural history that had been calibrated by varying two unmeasured parameters (mutation accrual rate and probability of adherence) to minimize differences between estimated and observed clinical outcomes (time to treatment failure and survival). We compared these estimated values first with only those results that had been already published at the time of model calibration, and second including results that were published after model calibration. RESULTS: The value for mutation accrual rate assigned during calibration was 0.014 mutations per month for antiretroviral-naive patients, at the lower bound of the results for nine heterogeneous studies published at the time of calibration (pooled 95% confidence interval [CI] 0.014-0.039 mutations per month). In contrast, this estimate accurately anticipated results from 11 larger and more homogeneous studies published after calibration (pooled 95% CI for antiretroviral-naive patients, 0.012-0.015 mutations per month). The value for probability of adherence assigned during calibration (75%) was also within the range of published results (pooled 95% CI 62-76%). CONCLUSION: Estimates for unobserved parameters derived during model calibration were not only within the range of clinical observations, but anticipated with accuracy clinical results that were not yet available. It may be feasible to use models to estimate unobserved parameters

As the financial burden of cost sharing continues to rise, patients increasingly avoid necessary care, thereby contributing to the high morbidity and mortality of the U.S. population compared with that of other developed countries. The rationale for cost sharing is often based on the moral hazard argument, which states that individuals may overuse care if they do not share in its costs. We evaluate this argument in detail, using it to distinguish between appropriate and inappropriate settings for cost sharing. Cost sharing may be appropriate when health services are of low value (low ratio of benefits to costs), whereas it is inappropriate when health services are of high value (high ratio of benefits to costs). In practice, cost sharing is rarely linked to value, and therefore much of the cost sharing that currently occurs is inappropriate and harmful. Cost-effectiveness analysis is an objective method to estimate the value of health services and may be a way to systematically evaluate whether cost-sharing policies are appropriate. Systematic efforts to discourage inappropriate cost sharing may improve public health

Alcohol consumption is associated with decreased antiretroviral adherence, and decreased adherence results in poorer outcomes. However the magnitude of alcohol's impact on survival is unknown. Our objective was to use a calibrated and validated simulation of HIV disease to estimate the impact of alcohol on survival. We incorporated clinical data describing the temporal and dose-response relationships between alcohol consumption and adherence in a large observational cohort (N=2,702). Individuals were categorized as nondrinkers (no alcohol consumption), hazardous drinkers (consume > or =5 standard drinks on drinking days), and nonhazardous drinkers (consume <5 standard drinks on drinking days). Our results showed that nonhazardous alcohol consumption decreased survival by more than 1 year if the frequency of consumption was once per week or greater, and by 3.3 years (from 21.7 years to 18.4 years) with daily consumption. Hazardous alcohol consumption decreased overall survival by more than 3 years if frequency of consumption was once per week or greater, and by 6.4 years (From 16.1 years to 9.7 years) with daily consumption. Our results suggest that alcohol is an underappreciated yet modifiable risk factor for poor survival among individuals with HIV

The present study prospectively investigated the association between family life stress and insomnia symptoms among 115 undergraduates, ages 17-22 years. Participants completed the following questionnaires at 2 study time points, spaced 3 weeks apart: the Insomnia Severity Index, the Negative Life Events Questionnaire (NLEQ), and the Beck Depression Inventory. First, family life stress at baseline was hypothesized to predict elevated insomnia symptoms 3 weeks later, above and beyond depressive symptoms. Second, compared with academic stressors, negative family and social life events were expected to best predict increased insomnia. Regression analyses were conducted to test study predictions. Hypotheses were partially supported. Family life stress was significantly associated with increased insomnia symptomatology, even after controlling for depression. Results also revealed that negative family life events, together with academic stress, predicted the highest levels of insomnia

Our objective was to illustrate the effects of using stricter standards for the quality of evidence used in decision analytic modeling. We created a simple 10-parameter probabilistic Markov model to estimate the cost-effectiveness of directly observed therapy (DOT) for individuals with newly diagnosed HIV infection. We evaluated quality of evidence on the basis of U.S. Preventive Services Task Force methods, which specified 3 separate domains: study design, internal validity, and external validity. We varied the evidence criteria for each of these domains individually and collectively. We used published research as a source of data only if the quality of the research met specified criteria; otherwise, we specified the parameter by randomly choosing a number from a range within which every number has the same probability of being selected (a uniform distribution). When we did not eliminate poor-quality evidence, DOT improved health 99% of the time and cost less than 100,000 dollars per additional quality-adjusted life-year (QALY) 85% of the time. The confidence ellipse was extremely narrow, suggesting high precision. When we used the most rigorous standards of evidence, we could use fewer than one fifth of the data sources, and DOT improved health only 49% of the time and cost less than 100,000 dollars per additional QALY only 4% of the time. The confidence ellipse became much larger, showing that the results were less precise. We conclude that the results of decision modeling may vary dramatically depending on the stringency of the criteria for selecting evidence to use in the model

OBJECTIVES: Determining the relationship between antiretroviral adherence and resistance accumulation is important for the design and evaluation of adherence interventions. Our objective was to explain heterogeneity observed in this relationship. METHODS: We first conducted a systematic review to locate published reports describing the relationship between adherence and resistance. We then used a validated computer simulation to simulate the patient populations in these reports, exploring the impact of changes in individual patient characteristics (age, CD4, viral load, prior antiretroviral experience) on the shape of the adherence-resistance (A-R) curve. RESULTS: The search identified 493 titles, of which 3 contained relevant primary data and 2 had sufficient follow-up for inclusion (HOMER and REACH cohorts). When simulating HOMER, the A-R curve had a high peak with a greatly increased hazard ratio (HR) of accumulating mutations at partial compared to complete adherence (simulation, HR 2.9; HOMER, HR 2.7). When simulating REACH, the A-R curve had a shallow peak with a slightly increased hazard of accumulating mutations at partial adherence (simulation, HR 1.2; REACH, HR 1.4). This heterogeneity was primarily attributable to differences in antiretroviral experience between the cohorts. CONCLUSIONS: Our computer simulation was able to explain much of the heterogeneity in observed A-R curves

BACKGROUND: Studies have established that physiologic instability and services mismatching precede adverse events in hospitalized patients. In response to these considerations, the concept of a Rapid Response System (RRS) has emerged. The responding team is commonly known as a medical emergency team (MET), rapid response team (RRT), or critical care outreach (CCO). Studies show that an RRS may improve outcome, but questions remain regarding the benefit, design elements, and advisability of implementing a MET system. METHODS: In June 2005 an International Conference on Medical Emergency Teams (ICMET) included experts in patient safety, hospital medicine, critical care medicine, and METs. Seven of 25 had no experience with an RRS, and the remainder had experience with one of the three major forms of RRS. After preconference telephone and e-mail conversations by the panelists in which questions to be discussed were characterized, literature reviewed, and preliminary answers created, the panelists convened for 2 days to create a consensus document. Four major content areas were addressed: What is a MET response? Is there a MET syndrome? What are barriers to METS? How should outcome be measured? Panelists considered whether all hospitals should implement an RRS. RESULTS: Patients needing an RRS intervention are suddenly critically ill and have a mismatch of resources to needs. Hospitals should implement an RRS, which consists of four elements: an afferent, 'crisis detection' and 'response triggering' mechanism; an efferent, predetermined rapid response team; a governance/administrative structure to supply and organize resources; and a mechanism to evaluate crisis antecedents and promote hospital process improvement to prevent future events