published_or_final_version / Nursing Studies / Master / Master of Nursing

Thesis (M.Nurs.)--University of Hong Kong, 2008. / Includes bibliographical references (p. 49-57)

Thesis (M Med Pharmacy)--University of Limpopo, 2011 / Most pharmaceutical agents can result in side effects and toxicities that in some instances may be life threatening, especially if there is delay in their recognition. For various reasons it is therefore imperative to study adverse events associated with antiretroviral agents (ARVs). The aim of this study was to study the adverse events in adult HIV-infected patients receiving antiretroviral therapy at a public health treatment site, and to quantify the frequency of adverse events in different population subgroups. A retrospective cohort study was conducted in a sample of 99 patients (i.e. 70% females and 30% males) from a public health clinic providing antiretroviral drugs to more than 1500 patients. The reported adverse events were neurological disorders (33%), rash (17%), gastrointestinal toxicity (16%), lactic acidosis (14%), hepatitis (7%), lipodystrophy (7%), pancreatitis (5%), IRIS (3%), anaemia (1%), and gynaecomastia (1%). Based on the analysis of the presented data in this report, age, weight, gender, and pCD4 count are not the predictors for the development of lactic acidosis, pancreatitis, and peripheral neuropathy. The duration of treatment was found to be the predictor for the development of lactic acidosis, pancreatitis, and peripheral neuropathy in this study sample. More frequent and closer monitoring of the reported adverse events will be necessary for patients treated longer on ART. Information bias is possible as case data for all reported adverse effects were collected retrospectively from hand-written patient records which were not consistent and standardised.

This thesis assesses factors associated with a number of short and long-term outcomes in HIV-infected patients receiving antiretroviral treatment in Asia. Analyses in this thesis were based on two cohorts of HIV-infected patients; The Treat Asia HIV Observational Database (TAHOD), a multi-centre prospective observational cohort from countries in Asia-Pacific region, and the HIV Netherlands Australia Thailand (HIV-NAT) collaboration cohort, a cohort of patients treated with antiretroviral treatments at HIV-NAT in Bangkok, Thailand. We examined factors associated with time to immunological failure endpoints, such as CD4≤ 200 cells/??L, CD4≤ 100 cells/ ??L, and CD4 return to baseline, and with the virological failure endpoint, detectable viral load defined as a value greater than 500 copies/mL. Multivariate Cox proportional hazard models were used. Results showed that CD4 count at baseline and changes in CD4 strongly predicted immunological failure. For virological failure, detectable viral load at baseline was the strongest predictor. As a step to developing simplified monitoring strategies, in which patients with a low risk of failure could have their monitoring CD4 count and viral load tests deferred, we developed predictive models for each immunological and virological failure endpoint. Models were developed on the HIV-NAT cohort, and validated on the independent TAHOD cohort. For predictive models, the complementary log-log transformation for each endpoint was fitted appropriate to the interval censored nature of the data. To assess goodness-of-fit, cut-offs were defined for the predicted risks that separated patients from low risk to high risk. Overall, the observed versus expected failures from HIV-NAT data agreed quite well across all endpoints, probably reflecting that the HIV-NAT database was the data we built the models upon. Not only did these models fit the HIV-NAT database well, they also discriminated patients from low to high risk groups. When we validated models with TAHOD data, the observed and expected failures agreed well only in the model for CD4 count return to baseline. For most of the endpoints, the predictive models overestimated the number of failures, with predicted values larger than observed. However, the proportions of failures were lowest in the low risk group and highest in the high risk group, indicating that our models did discriminate between patients at high and low risk, and that the predictive models might still be of use for the purpose of simplified monitoring strategies. With CD4 count and viral load monitoring tests now comprising a large component of the cost of HIV treatment in resource limited settings, we developed and assessed a simplified monitoring strategy that aimed to reduce the numbers of monitoring tests performed. The predictive models developed earlier were used to calculate the probabilities of failure in TAHOD patients. We assumed that patients would have their CD4 and viral load assessments annually, at baseline and at one year, predicted risk of failure at ensuing clinical visits, week 12, 24 and 36. For patients at low predicted risk of failure at ensuing clinical visits, we assessed the effect of deferring monitoring tests, both in terms of blood tests avoided, and in terms of delaying detection of failure in some patients. A number of levels for the predicted risk of failure that lead to deferral of testing were evaluated. The results suggested that predicted probabilities of failure of 10% - 20% gave the best results across all failure endpoints. These cut-offs could save a median of 598 (51.6%) (range 37 (2.6%)_-1,218 (81.9%) ) blood tests over the first year of treatment, but would fail to detect 29 (18%) (range 10 (7.4%) - 128 (39.3%) ) failures. The median time from failure to detection in those patients who did fail and had deferred monitoring tests was 28 weeks. Rates of antiretroviral treatment change in TAHOD were examined. We identified patterns and factors associated with the rate of treatment change. Median time to the first treatment change was 3.2 years. Factors predicting rate of treatment change in TAHOD were treatment combination, being on second or third combination, number of drugs available in each site and being an injecting drug user. The overall rate of treatment change in TAHOD was 29 per 1OO-person-year. Around 30% of patients stopped their treatment due to adverse events. These rates of treatment change are lower than have been seen in patients in western countries. This may be due to patients in developing countries having access to fewer antiretroviral drugs than patients in developed countries.

This thesis assesses factors associated with a number of short and long-term outcomes in HIV-infected patients receiving antiretroviral treatment in Asia. Analyses in this thesis were based on two cohorts of HIV-infected patients; The Treat Asia HIV Observational Database (TAHOD), a multi-centre prospective observational cohort from countries in Asia-Pacific region, and the HIV Netherlands Australia Thailand (HIV-NAT) collaboration cohort, a cohort of patients treated with antiretroviral treatments at HIV-NAT in Bangkok, Thailand. We examined factors associated with time to immunological failure endpoints, such as CD4≤ 200 cells/??L, CD4≤ 100 cells/ ??L, and CD4 return to baseline, and with the virological failure endpoint, detectable viral load defined as a value greater than 500 copies/mL. Multivariate Cox proportional hazard models were used. Results showed that CD4 count at baseline and changes in CD4 strongly predicted immunological failure. For virological failure, detectable viral load at baseline was the strongest predictor. As a step to developing simplified monitoring strategies, in which patients with a low risk of failure could have their monitoring CD4 count and viral load tests deferred, we developed predictive models for each immunological and virological failure endpoint. Models were developed on the HIV-NAT cohort, and validated on the independent TAHOD cohort. For predictive models, the complementary log-log transformation for each endpoint was fitted appropriate to the interval censored nature of the data. To assess goodness-of-fit, cut-offs were defined for the predicted risks that separated patients from low risk to high risk. Overall, the observed versus expected failures from HIV-NAT data agreed quite well across all endpoints, probably reflecting that the HIV-NAT database was the data we built the models upon. Not only did these models fit the HIV-NAT database well, they also discriminated patients from low to high risk groups. When we validated models with TAHOD data, the observed and expected failures agreed well only in the model for CD4 count return to baseline. For most of the endpoints, the predictive models overestimated the number of failures, with predicted values larger than observed. However, the proportions of failures were lowest in the low risk group and highest in the high risk group, indicating that our models did discriminate between patients at high and low risk, and that the predictive models might still be of use for the purpose of simplified monitoring strategies. With CD4 count and viral load monitoring tests now comprising a large component of the cost of HIV treatment in resource limited settings, we developed and assessed a simplified monitoring strategy that aimed to reduce the numbers of monitoring tests performed. The predictive models developed earlier were used to calculate the probabilities of failure in TAHOD patients. We assumed that patients would have their CD4 and viral load assessments annually, at baseline and at one year, predicted risk of failure at ensuing clinical visits, week 12, 24 and 36. For patients at low predicted risk of failure at ensuing clinical visits, we assessed the effect of deferring monitoring tests, both in terms of blood tests avoided, and in terms of delaying detection of failure in some patients. A number of levels for the predicted risk of failure that lead to deferral of testing were evaluated. The results suggested that predicted probabilities of failure of 10% - 20% gave the best results across all failure endpoints. These cut-offs could save a median of 598 (51.6%) (range 37 (2.6%)_-1,218 (81.9%) ) blood tests over the first year of treatment, but would fail to detect 29 (18%) (range 10 (7.4%) - 128 (39.3%) ) failures. The median time from failure to detection in those patients who did fail and had deferred monitoring tests was 28 weeks. Rates of antiretroviral treatment change in TAHOD were examined. We identified patterns and factors associated with the rate of treatment change. Median time to the first treatment change was 3.2 years. Factors predicting rate of treatment change in TAHOD were treatment combination, being on second or third combination, number of drugs available in each site and being an injecting drug user. The overall rate of treatment change in TAHOD was 29 per 1OO-person-year. Around 30% of patients stopped their treatment due to adverse events. These rates of treatment change are lower than have been seen in patients in western countries. This may be due to patients in developing countries having access to fewer antiretroviral drugs than patients in developed countries.

This thesis assesses factors associated with a number of short and long-term outcomes in HIV-infected patients receiving antiretroviral treatment in Asia. Analyses in this thesis were based on two cohorts of HIV-infected patients; The Treat Asia HIV Observational Database (TAHOD), a multi-centre prospective observational cohort from countries in Asia-Pacific region, and the HIV Netherlands Australia Thailand (HIV-NAT) collaboration cohort, a cohort of patients treated with antiretroviral treatments at HIV-NAT in Bangkok, Thailand. We examined factors associated with time to immunological failure endpoints, such as CD4≤ 200 cells/??L, CD4≤ 100 cells/ ??L, and CD4 return to baseline, and with the virological failure endpoint, detectable viral load defined as a value greater than 500 copies/mL. Multivariate Cox proportional hazard models were used. Results showed that CD4 count at baseline and changes in CD4 strongly predicted immunological failure. For virological failure, detectable viral load at baseline was the strongest predictor. As a step to developing simplified monitoring strategies, in which patients with a low risk of failure could have their monitoring CD4 count and viral load tests deferred, we developed predictive models for each immunological and virological failure endpoint. Models were developed on the HIV-NAT cohort, and validated on the independent TAHOD cohort. For predictive models, the complementary log-log transformation for each endpoint was fitted appropriate to the interval censored nature of the data. To assess goodness-of-fit, cut-offs were defined for the predicted risks that separated patients from low risk to high risk. Overall, the observed versus expected failures from HIV-NAT data agreed quite well across all endpoints, probably reflecting that the HIV-NAT database was the data we built the models upon. Not only did these models fit the HIV-NAT database well, they also discriminated patients from low to high risk groups. When we validated models with TAHOD data, the observed and expected failures agreed well only in the model for CD4 count return to baseline. For most of the endpoints, the predictive models overestimated the number of failures, with predicted values larger than observed. However, the proportions of failures were lowest in the low risk group and highest in the high risk group, indicating that our models did discriminate between patients at high and low risk, and that the predictive models might still be of use for the purpose of simplified monitoring strategies. With CD4 count and viral load monitoring tests now comprising a large component of the cost of HIV treatment in resource limited settings, we developed and assessed a simplified monitoring strategy that aimed to reduce the numbers of monitoring tests performed. The predictive models developed earlier were used to calculate the probabilities of failure in TAHOD patients. We assumed that patients would have their CD4 and viral load assessments annually, at baseline and at one year, predicted risk of failure at ensuing clinical visits, week 12, 24 and 36. For patients at low predicted risk of failure at ensuing clinical visits, we assessed the effect of deferring monitoring tests, both in terms of blood tests avoided, and in terms of delaying detection of failure in some patients. A number of levels for the predicted risk of failure that lead to deferral of testing were evaluated. The results suggested that predicted probabilities of failure of 10% - 20% gave the best results across all failure endpoints. These cut-offs could save a median of 598 (51.6%) (range 37 (2.6%)_-1,218 (81.9%) ) blood tests over the first year of treatment, but would fail to detect 29 (18%) (range 10 (7.4%) - 128 (39.3%) ) failures. The median time from failure to detection in those patients who did fail and had deferred monitoring tests was 28 weeks. Rates of antiretroviral treatment change in TAHOD were examined. We identified patterns and factors associated with the rate of treatment change. Median time to the first treatment change was 3.2 years. Factors predicting rate of treatment change in TAHOD were treatment combination, being on second or third combination, number of drugs available in each site and being an injecting drug user. The overall rate of treatment change in TAHOD was 29 per 1OO-person-year. Around 30% of patients stopped their treatment due to adverse events. These rates of treatment change are lower than have been seen in patients in western countries. This may be due to patients in developing countries having access to fewer antiretroviral drugs than patients in developed countries.

Thesis (M.S.) -- Worcester Polytechnic Institute. / Keywords: gene function and regulation; splicing; apobec3; genetics. Includes bibliographical references (p. 55-58).

Thesis (Ph. D.)--University of Texas at Austin, 2006. / Vita. Includes bibliographical references.

Thesis (MNutr)--University of Stellenbosch, 2008. / Bibliography. Also available via the Internet.

Ph.D. / Despite nearly three decades of intensive research, the HIV/AIDS pandemic remains a major challenge to modern medicine. The discovery and development of antiretroviral agents acting against various essential viral processes and enzymatic targets have greatly enhanced the quality of life for infected individuals, but no cure or preventative vaccine is available as yet and HIV infection is currently considered irreversible. Furthermore, the emergence of viral resistance to every class and type of antiretroviral treatment agent necessitates the continued discovery of antiretroviral agents with novel mechanisms of action. The first antiretroviral agent targeting the retroviral integrase enzyme (InsentressTM, Raltegravir) received regulatory approval from the United States Food and Drug Administration during 2007, validating HIV-1 integrase as a therapeutic target and providing a much-needed second- or third-line treatment option for treatment experienced patients. This enzyme was selected as a target for the current work. As limited data were available on the primary and secondary structure of the biologically relevant HIV-1 integrase enzyme, a first step in the present work was the construction of monomeric, dimeric and tetrameric models of the enzyme with biologically relevant catalytic centres incorporating both viral and host co-factors and DNA. The models were constructed to identify potential inhibitors of the strandtransfer reaction of HIV-1 integrase and were based on observations and interactions reported in the literature and on crystal structure data of HIV-1 integrase sub-domains and related structures available in the Protein Data Bank. The monomeric model was used as the macromolecular target in docking studies with “drug-like” compound databases, identifying the pyrrolidinone compound class as an in silico hit candidate for further development. Initial activity screening of a number of commercially available pyrrolidinone analogues against recombinant HIV-1 subtype B integrase in direct enzyme assays confirmed the predicted potential for strand transfer inhibition of the compound class, and provided initial support in the further development of this compound class as inhibitors of HIV-1 integrase that target the strand-transfer step. Retrosynthetic analysis of the pyrrolidinone hit candidates provided a facile one-pot, three-component synthetic pathway from readily available starting materials, which generally gave the proposed products cleanly and in acceptable yields. A range of closely related analogues were designed and synthesised. The analogues making up this series generally differed by only one functional group, in order to enable initial structureactivity relationship investigations during later stages of the project. Foreword Page XVI The synthesised pyrrolidinone analogues were screened through a range of direct and cell-based in vitro assays to determine the toxicity and strand-transfer activity of each. In general, the pyrrolidinone compounds proved well-tolerated in PM1 cell culture, with clear potential to further develop the strandtransfer inhibition of the compound family in second- and further-generation optimisation stages. Furthermore, the aqueous solubility and membrane permeability of each compound were determined in vitro, providing initial biological profiles of each test compound. As no in vivo testing was performed with any of the compounds during this first round of drug discovery and optimisation, several computational models were employed to extrapolate the in vitro and structural data to possible in vivo scenarios. Two pyrrolidinone analogues (11.6 and 15.2) were identified as low micro-molar strand-transfer inhibitors of wildtype-equivalent HIV-1 integrase, with low toxicity in cell culture and favourable solubility and permeability profiles. Resistance screening of these two compounds against four mutant HIV-1 integrases (Q148H; Q148H/G140S; N155H and N155H/E92Q) has shown some promise, with compound 15.2 retaining a measure of activity against the Raltegravir-resistant N155-mutants. These hit candidates will form the basis of structure-activity relationship optimisations in second- and further generation design stages.