Biomedical subjects

Andrew Zolopa

Publications and source records attributed to Andrew Zolopa.

6 recordsLinked to original sources

PubMed2006

A randomized, partially blinded phase 2 trial of antiretroviral therapy, HIV-specific immunizations, and interleukin-2 cycles to promote efficient control of viral replication (ACTG A5024).

Strategies to limit life-long dependence on antiretroviral therapy (ART) are needed. We randomized 81 human immunodeficiency virus (HIV)-infected subjects to 4 interventional arms involving continued ART plus ALVAC vCP1452 (or placebo) with or without interleukin (IL)-2 infusions. Viral load rebound 12 weeks after ART interruption was then analyzed to assess immune control. Fifty-two subjects reached the study end point. ALVAC recipients had 0.5 log(10) lower virologic rebounds (P=.033). IL-2 plus vaccine boosted CD4(+) T cell counts (P<.001) but did not diminish viral rebound. Significant changes were not detected for HIV-specific lymphoproliferative responses in any arm. This exploratory protocol provides useful clinical data for future therapeutic immunization trial design.

AIDS Vaccines↗

PubMed2006

The effect of diagnosis with HIV infection on health-related quality of Life.

We sought to understand how diagnosis with HIV affects health-related quality of life. We assessed health-related quality of life using utility-based measures in a Department of Veterans Affairs (VA) clinic and a University-based clinic. Respondents assessed health-related quality of life regarding their current health, and retrospectively assessed their health 1 month prior to and 2 months after diagnosis with HIV infection. Sixty-six patients completed the study. The overall mean utilities for health 1 month before and 2 months after diagnosis were 0.87 (standard error 0.037), and 0.80 (0.043) (p<0.005 by rank sign test), but the effect of diagnosis differed between the two clinics, with a substantial decrease in the university clinic and a small non-significant decrease in the VA clinic. The overall mean utility for current health was 0.85 (0.034), assessed on average 7.5 years after diagnosis. When asked directly whether diagnosis of HIV decreased health-related quality of life, 47% agreed, but 35% stated that HIV diagnosis positively affected health-related quality of life. Diagnosis with HIV decreased health-related quality of life at 2 months on average, but this effect diminished over time, and differed among patient populations. Years after diagnosis, although half of the patients believed that diagnosis reduced health-related quality of life, one-third reported improved health-related quality of life.

Acquired Immunodeficiency Syndrome↗

PubMed2004

Clinically validated genotype analysis: guiding principles and statistical concerns.

Whereas previously the output of HIV resistance tests has been based on therapeutically arbitrary criteria, there is now an ongoing move towards correlating test interpretation with virological outcomes on treatment. This approach is undeniably superior, in principle, for tests intended to guide drug choices. However the predictive accuracy of a given stratagem that links genotype or phenotype to drug response is strongly influenced by the study design, data capture and analytical methodology used to derive it. For genotyping, the most widely used resistance tool in clinical practice, these considerations are further complicated by the range of mutational patterns present in the treated population. There is no definitively superior methodology for generating a genotype-response association for use in interpreting a resistance test, and the various approaches used to date all have their strengths and weaknesses. This review discusses the processes involved in constructing such tools, with particular emphasis on establishing validated mutation score rules, and examines the key issues and confounding factors that influence predictive accuracy outside the originating dataset. Since the size of the sample is a key influence on the statistical power to determine an effect, it is hoped that a greater understanding of the influence of study design and methodology will assist the development of standardized outcome measures and reporting formats that allow data pooling at the international level.

Anti-HIV Agents↗

PubMed2003

High levels of adherence do not prevent accumulation of HIV drug resistance mutations.

OBJECTIVES: To assess the relationship between development of antiretroviral drug resistance and adherence by measured treatment duration, virologic suppression, and the rate of accumulating new drug resistance mutations at different levels of adherence. METHODS: Adherence was measured with unannounced pill counts performed at the participant's usual place of residence in a prospective cohort of HIV-positive urban poor individuals. Two genotypic resistance tests separated by 6 months (G1 and G2) were obtained in individuals on a stable regimen and with detectable viremia (> 50 copies/ml). The primary resistance outcome was the number of new HIV antiretroviral drug resistance mutations occurring over the 6 months between G1 and G2. RESULTS: High levels of adherence were closely associated with greater time on treatment (P < 0.0001) and viral suppression (P < 0.0001) in 148 individuals. In a subset of 57 patients with a plasma viral load > 50 copies/ml on stable therapy, the accumulation of new drug resistance mutations was positively associated with the duration of prior treatment (P = 0.03) and pill count adherence (P = 0.002). Assuming fully suppressed individuals (< 50 copies/ml) do not develop resistance, it was estimated that 23% of all drug resistance occurs in the top quintile of adherence (92-100%), and over 50% of all drug resistance mutations occur in the top two quintiles of adherence (79-100%). CONCLUSION: Increasing rates of viral suppression at high levels of adherence is balanced by increasing rates of drug resistance among viremic patients. Exceptionally high levels of adherence will not prevent population levels of drug resistance.

Adult↗

PubMed2003

Current management challenges in HIV: antiretroviral resistance.

Emergence of drug-resistant viral variants is a major reason why HIV-infected patients experience viral rebound during antiretroviral therapy. Although combination antiretroviral therapy substantially inhibits viral replication, replication-competent mutant virus remains. In addition, it is now clear that virologic failure is not necessarily caused by failure of all drugs in a regimen. The use of resistance-testing data can assist in understanding the reasons for failure of antiretroviral therapy. However, there is a need for additional trials to better define the role resistance testing may play in developing management approaches to mitigate or minimize emergence of resistant HIV.

Anti-HIV Agents↗

PubMed2002

Virtual inhibitory quotient predicts response to ritonavir boosting of indinavir-based therapy in human immunodeficiency virus-infected patients with ongoing viremia.

Depending on the degree of underlying resistance present, optimization of the pharmacokinetics of protease inhibitors may result in improved virologic suppression. Thirty-seven human immunodeficiency virus (HIV)-infected subjects who had chronic detectable viremia and who were receiving 800 mg of indinavir three times a day (TID) were switched to 400 mg of indinavir BID with 400 mg of ritonavir two times a day (BID) for 48 weeks. Full pharmacokinetic evaluations were obtained for 12 subjects before the switch and 3 weeks after the switch. Combination therapy increased the indinavir predose concentrations in plasma by 6.47-fold, increased the minimum concentration in serum by 3.41-fold, and reduced the maximum concentration in serum by 57% without significantly changing the area under the plasma concentration-time curve at 24 h. At week 3, 58% (21 of 36) of the subjects for whom postbaseline measurements were available achieved a viral load in plasma of <50 copies/ml or a reduction from the baseline load of > or =0.5 log(10) copies/ml. Of these subjects, 82% (14 of 17) whose viruses had three or fewer protease inhibitor mutations and 88% (14 of 16) whose viruses had an indinavir virtual phenotypic susceptibility test of more than sixfold less than that for the baseline isolate were considered virologic responders. The indinavir virtual inhibitory quotient, which is a function of baseline indinavir phenotypic resistance (estimated by virtual phenotype) and the indinavir predose concentration in plasma achieved with indinavir-ritonavir combination therapy, was the best predictor of a viral load reduction. Sixteen subjects discontinued the study by week 48 due to adverse events, predominantly related to hyperlipidemia. Pharmacokinetic intensification of indinavir-based therapy with ritonavir reduced the viral loads in subjects but added toxicity. The virtual inhibitory quotient, which incorporates both baseline viral resistance and the level of drug exposure in plasma, was superior to either baseline resistance or drug exposure alone in predicting the virologic response.

Adult↗