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Cited by Other Article(s)

Emuren L, Welles S, Macalino G, Evans AA, Polansky M, Ganesan A, Colombo RE, Agan BK. Predictors of health-related quality of life among military HIV-infected individuals. Qual Life Res 2020;29:1855-1869. [PMID: 32076926 DOI: 10.1007/s11136-020-02441-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/01/2020] [Indexed: 12/01/2022]

Affiliation(s)

Leonard Emuren Department of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, Philadelphia, PA, USA.,Department of Pediatrics, Eastern Virginia Medical School, Norfolk, VA, USA.,Children's Hospital of the King's Daughters, 601 Children's Lane, Norfolk, VA, USA
Seth Welles Department of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, Philadelphia, PA, USA
Grace Macalino Infectious Disease Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA.,The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, MD, USA
Alison A Evans Department of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, Philadelphia, PA, USA
Marcia Polansky Department of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, Philadelphia, PA, USA
Anuradha Ganesan Infectious Disease Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA.,The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, MD, USA.,Division of Infectious Diseases, Walter Reed National Military Medical Center, Bethesda, MD, USA
Rhonda E Colombo Infectious Disease Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA.,The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, MD, USA.,Division of Infectious Diseases, Madigan Army Medical Center, Joint Base Lewis-McChord, WA, USA
Brian K Agan Infectious Disease Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA. .,The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, MD, USA.

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Dubrocq G, Rakhmanina N. Antiretroviral therapy interruptions: impact on HIV treatment and transmission. HIV AIDS-RESEARCH AND PALLIATIVE CARE 2018;10:91-101. [PMID: 29942160 PMCID: PMC6005325 DOI: 10.2147/hiv.s141965] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]

Abstract

Introduction

Successful management of pediatric and adult human immunodeficiency virus (HIV) disease includes lifelong administration of antiretroviral therapy (ART). The need for the continuous use of antiretroviral drugs throughout the life course poses a challenge to children, adolescents, and adults living with HIV and their caregivers. Historically, treatment interruptions have been viewed as a negative therapeutic strategy. Recently, however, treatment interruptions or treatment reduction strategies have become a focus of investigations as innovative approaches to the long-term management of HIV disease. Current challenges with treatment interruptions include identifying an appropriate timeframe for length of interruptions and identifying HIV patient populations in whom the treatment interruption can be successful.

Objective

In this review, we aimed at summarizing recent studies of planned and unplanned treatment interruptions in children and adults living with HIV.

Materials and methods

We searched two databases (PubMed and Cochrane Controlled Trials Register) using keywords (HIV OR AIDS OR acquired immunodeficiency syndrome OR HIV-1 OR antiretroviral) AND (treatment interruption OR planned interruption OR therapeutic interruption OR unplanned interruption), for published randomized and nonrandomized clinical trials and observational cohort studies in children and adults (from birth to 99 years of age) in global settings covering a period from 2012 to 2018. In this review, only the studies that contained pediatric and adolescent populations with baseline immunological, virological, and clinical characteristics and outcomes after treatment interruption were included.

Results

A total of 174 eligible citations from the two databases were identified. We identified 10 prospective treatment interruption studies on children (five studies) and adults (five studies) during 2012–2018 with a total of 863 pediatric and 273 adult subjects. Collectively, recent studies on children and adults with HIV infection suggest that treatment interruptions with proper monitoring can be successful by instituting well-defined immunological and virological parameters or thresholds such as CD4 count, CD4%, and HIV RNA viral load that identify low-risk populations with treatment failure. In addition to standard virological and immunological outcome measurements, selected biomarkers that help detect early immune activation may also be useful in the monitoring of treatment interruption.

Conclusion

Treatment interruptions in adult and especially pediatric patients with well-controlled HIV disease may provide an alternative opportunity to optimize long-term HIV management by minimizing drug-associated toxicity and improving long-term adherence and quality of life.

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Joyce VR, Sun H, Barnett PG, Bansback N, Griffin SC, Bayoumi AM, Anis AH, Sculpher M, Cameron W, Brown ST, Holodniy M, Owens DK. Mapping MOS-HIV to HUI3 and EQ-5D-3L in Patients With HIV. MDM Policy Pract 2017;2:2381468317716440. [PMID: 30288427 PMCID: PMC6125043 DOI: 10.1177/2381468317716440] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2016] [Accepted: 05/10/2017] [Indexed: 12/25/2022] Open

Abstract

Objectives: The Medical Outcomes Study HIV Health Survey (MOS-HIV) is frequently used in HIV clinical trials; however, scores generated from the MOS-HIV are not suited for cost-effectiveness analyses as they do not assign utility values to health states. Our objective was to estimate and externally validate several mapping algorithms to predict Health Utilities Index Mark 3 (HUI3) and EQ-5D-3L utility values from the MOS-HIV. Methods: We developed and validated mapping algorithms using data from two HIV clinical trials. Data from the first trial (n = 367) formed the estimation data set for the HUI3 (4,610 observations) and EQ-5D-3L (4,662 observations) mapping algorithms; data from the second trial (n = 168) formed the HUI3 (1,135 observations) and EQ-5D-3L (1,152 observations) external validation data set. We compared ordinary least squares (OLS) models of increasing complexity with the more flexible two-part, beta regression, and finite mixture models. We assessed model performance using mean absolute error (MAE) and mean squared error (MSE). Results: The OLS model that used MOS-HIV dimension scores along with squared terms gave the best HUI3 predictions (mean observed 0.84; mean predicted 0.80; MAE 0.0961); the finite mixture model gave the best EQ-5D-3L predictions (mean observed 0.90; mean predicted 0.88; MAE 0.0567). All models produced higher prediction errors at the lower end of the HUI3 and EQ-5D-3L score ranges (<0.40). Conclusions: The proposed mapping algorithms can be used to predict HUI3 and EQ-5D-3L utility values from the MOS-HIV, although greater error may pose a problem in samples where a substantial proportion of patients are in poor health. These algorithms may be useful for estimating utility values from the MOS-HIV for cost-effectiveness studies when HUI3 or EQ-5D-3L data are not available.

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Affiliation(s)

Vilija R Joyce VA Palo Alto Health Care System, VA Cooperative Studies Program Coordinating Center, VA HSR&D Health Economics Resource Center, Menlo Park, California (VRJ, PGB).,Centre for Health Evaluation and Outcome Sciences, St. Paul's Hospital, Vancouver, British Columbia, Canada (HS, NB, AHA).,Canadian HIV Trials Network, Vancouver, British Columbia, Canada (HS).,School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada (NB, AHA).,Centre for Health Economics, University of York, York, UK (SCG, MS).,Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute and Division of General Internal Medicine, St. Michael's Hospital, Toronto, Ontario, Canada (AMB).,Departments of Medicine and Health Policy, Management and Evaluation, University of Toronto, Ontario, Canada (AMB).,Division of Infectious Diseases, University of Ottawa at The Ottawa Hospital, Ottawa, Ontario, Canada (WC).,James J. Peters VA Medical Center, Bronx, New York (STB).,VA Palo Alto Health Care System, Palo Alto, California (MH, DKO).,Center for Primary Care and Outcomes Research, Stanford University, Stanford, California (DKO)
Huiying Sun VA Palo Alto Health Care System, VA Cooperative Studies Program Coordinating Center, VA HSR&D Health Economics Resource Center, Menlo Park, California (VRJ, PGB).,Centre for Health Evaluation and Outcome Sciences, St. Paul's Hospital, Vancouver, British Columbia, Canada (HS, NB, AHA).,Canadian HIV Trials Network, Vancouver, British Columbia, Canada (HS).,School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada (NB, AHA).,Centre for Health Economics, University of York, York, UK (SCG, MS).,Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute and Division of General Internal Medicine, St. Michael's Hospital, Toronto, Ontario, Canada (AMB).,Departments of Medicine and Health Policy, Management and Evaluation, University of Toronto, Ontario, Canada (AMB).,Division of Infectious Diseases, University of Ottawa at The Ottawa Hospital, Ottawa, Ontario, Canada (WC).,James J. Peters VA Medical Center, Bronx, New York (STB).,VA Palo Alto Health Care System, Palo Alto, California (MH, DKO).,Center for Primary Care and Outcomes Research, Stanford University, Stanford, California (DKO)
Paul G Barnett VA Palo Alto Health Care System, VA Cooperative Studies Program Coordinating Center, VA HSR&D Health Economics Resource Center, Menlo Park, California (VRJ, PGB).,Centre for Health Evaluation and Outcome Sciences, St. Paul's Hospital, Vancouver, British Columbia, Canada (HS, NB, AHA).,Canadian HIV Trials Network, Vancouver, British Columbia, Canada (HS).,School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada (NB, AHA).,Centre for Health Economics, University of York, York, UK (SCG, MS).,Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute and Division of General Internal Medicine, St. Michael's Hospital, Toronto, Ontario, Canada (AMB).,Departments of Medicine and Health Policy, Management and Evaluation, University of Toronto, Ontario, Canada (AMB).,Division of Infectious Diseases, University of Ottawa at The Ottawa Hospital, Ottawa, Ontario, Canada (WC).,James J. Peters VA Medical Center, Bronx, New York (STB).,VA Palo Alto Health Care System, Palo Alto, California (MH, DKO).,Center for Primary Care and Outcomes Research, Stanford University, Stanford, California (DKO)
Nick Bansback VA Palo Alto Health Care System, VA Cooperative Studies Program Coordinating Center, VA HSR&D Health Economics Resource Center, Menlo Park, California (VRJ, PGB).,Centre for Health Evaluation and Outcome Sciences, St. Paul's Hospital, Vancouver, British Columbia, Canada (HS, NB, AHA).,Canadian HIV Trials Network, Vancouver, British Columbia, Canada (HS).,School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada (NB, AHA).,Centre for Health Economics, University of York, York, UK (SCG, MS).,Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute and Division of General Internal Medicine, St. Michael's Hospital, Toronto, Ontario, Canada (AMB).,Departments of Medicine and Health Policy, Management and Evaluation, University of Toronto, Ontario, Canada (AMB).,Division of Infectious Diseases, University of Ottawa at The Ottawa Hospital, Ottawa, Ontario, Canada (WC).,James J. Peters VA Medical Center, Bronx, New York (STB).,VA Palo Alto Health Care System, Palo Alto, California (MH, DKO).,Center for Primary Care and Outcomes Research, Stanford University, Stanford, California (DKO)
Susan C Griffin VA Palo Alto Health Care System, VA Cooperative Studies Program Coordinating Center, VA HSR&D Health Economics Resource Center, Menlo Park, California (VRJ, PGB).,Centre for Health Evaluation and Outcome Sciences, St. Paul's Hospital, Vancouver, British Columbia, Canada (HS, NB, AHA).,Canadian HIV Trials Network, Vancouver, British Columbia, Canada (HS).,School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada (NB, AHA).,Centre for Health Economics, University of York, York, UK (SCG, MS).,Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute and Division of General Internal Medicine, St. Michael's Hospital, Toronto, Ontario, Canada (AMB).,Departments of Medicine and Health Policy, Management and Evaluation, University of Toronto, Ontario, Canada (AMB).,Division of Infectious Diseases, University of Ottawa at The Ottawa Hospital, Ottawa, Ontario, Canada (WC).,James J. Peters VA Medical Center, Bronx, New York (STB).,VA Palo Alto Health Care System, Palo Alto, California (MH, DKO).,Center for Primary Care and Outcomes Research, Stanford University, Stanford, California (DKO)
Ahmed M Bayoumi VA Palo Alto Health Care System, VA Cooperative Studies Program Coordinating Center, VA HSR&D Health Economics Resource Center, Menlo Park, California (VRJ, PGB).,Centre for Health Evaluation and Outcome Sciences, St. Paul's Hospital, Vancouver, British Columbia, Canada (HS, NB, AHA).,Canadian HIV Trials Network, Vancouver, British Columbia, Canada (HS).,School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada (NB, AHA).,Centre for Health Economics, University of York, York, UK (SCG, MS).,Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute and Division of General Internal Medicine, St. Michael's Hospital, Toronto, Ontario, Canada (AMB).,Departments of Medicine and Health Policy, Management and Evaluation, University of Toronto, Ontario, Canada (AMB).,Division of Infectious Diseases, University of Ottawa at The Ottawa Hospital, Ottawa, Ontario, Canada (WC).,James J. Peters VA Medical Center, Bronx, New York (STB).,VA Palo Alto Health Care System, Palo Alto, California (MH, DKO).,Center for Primary Care and Outcomes Research, Stanford University, Stanford, California (DKO)
Aslam H Anis VA Palo Alto Health Care System, VA Cooperative Studies Program Coordinating Center, VA HSR&D Health Economics Resource Center, Menlo Park, California (VRJ, PGB).,Centre for Health Evaluation and Outcome Sciences, St. Paul's Hospital, Vancouver, British Columbia, Canada (HS, NB, AHA).,Canadian HIV Trials Network, Vancouver, British Columbia, Canada (HS).,School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada (NB, AHA).,Centre for Health Economics, University of York, York, UK (SCG, MS).,Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute and Division of General Internal Medicine, St. Michael's Hospital, Toronto, Ontario, Canada (AMB).,Departments of Medicine and Health Policy, Management and Evaluation, University of Toronto, Ontario, Canada (AMB).,Division of Infectious Diseases, University of Ottawa at The Ottawa Hospital, Ottawa, Ontario, Canada (WC).,James J. Peters VA Medical Center, Bronx, New York (STB).,VA Palo Alto Health Care System, Palo Alto, California (MH, DKO).,Center for Primary Care and Outcomes Research, Stanford University, Stanford, California (DKO)
Mark Sculpher VA Palo Alto Health Care System, VA Cooperative Studies Program Coordinating Center, VA HSR&D Health Economics Resource Center, Menlo Park, California (VRJ, PGB).,Centre for Health Evaluation and Outcome Sciences, St. Paul's Hospital, Vancouver, British Columbia, Canada (HS, NB, AHA).,Canadian HIV Trials Network, Vancouver, British Columbia, Canada (HS).,School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada (NB, AHA).,Centre for Health Economics, University of York, York, UK (SCG, MS).,Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute and Division of General Internal Medicine, St. Michael's Hospital, Toronto, Ontario, Canada (AMB).,Departments of Medicine and Health Policy, Management and Evaluation, University of Toronto, Ontario, Canada (AMB).,Division of Infectious Diseases, University of Ottawa at The Ottawa Hospital, Ottawa, Ontario, Canada (WC).,James J. Peters VA Medical Center, Bronx, New York (STB).,VA Palo Alto Health Care System, Palo Alto, California (MH, DKO).,Center for Primary Care and Outcomes Research, Stanford University, Stanford, California (DKO)
William Cameron VA Palo Alto Health Care System, VA Cooperative Studies Program Coordinating Center, VA HSR&D Health Economics Resource Center, Menlo Park, California (VRJ, PGB).,Centre for Health Evaluation and Outcome Sciences, St. Paul's Hospital, Vancouver, British Columbia, Canada (HS, NB, AHA).,Canadian HIV Trials Network, Vancouver, British Columbia, Canada (HS).,School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada (NB, AHA).,Centre for Health Economics, University of York, York, UK (SCG, MS).,Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute and Division of General Internal Medicine, St. Michael's Hospital, Toronto, Ontario, Canada (AMB).,Departments of Medicine and Health Policy, Management and Evaluation, University of Toronto, Ontario, Canada (AMB).,Division of Infectious Diseases, University of Ottawa at The Ottawa Hospital, Ottawa, Ontario, Canada (WC).,James J. Peters VA Medical Center, Bronx, New York (STB).,VA Palo Alto Health Care System, Palo Alto, California (MH, DKO).,Center for Primary Care and Outcomes Research, Stanford University, Stanford, California (DKO)
Sheldon T Brown VA Palo Alto Health Care System, VA Cooperative Studies Program Coordinating Center, VA HSR&D Health Economics Resource Center, Menlo Park, California (VRJ, PGB).,Centre for Health Evaluation and Outcome Sciences, St. Paul's Hospital, Vancouver, British Columbia, Canada (HS, NB, AHA).,Canadian HIV Trials Network, Vancouver, British Columbia, Canada (HS).,School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada (NB, AHA).,Centre for Health Economics, University of York, York, UK (SCG, MS).,Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute and Division of General Internal Medicine, St. Michael's Hospital, Toronto, Ontario, Canada (AMB).,Departments of Medicine and Health Policy, Management and Evaluation, University of Toronto, Ontario, Canada (AMB).,Division of Infectious Diseases, University of Ottawa at The Ottawa Hospital, Ottawa, Ontario, Canada (WC).,James J. Peters VA Medical Center, Bronx, New York (STB).,VA Palo Alto Health Care System, Palo Alto, California (MH, DKO).,Center for Primary Care and Outcomes Research, Stanford University, Stanford, California (DKO)
Mark Holodniy VA Palo Alto Health Care System, VA Cooperative Studies Program Coordinating Center, VA HSR&D Health Economics Resource Center, Menlo Park, California (VRJ, PGB).,Centre for Health Evaluation and Outcome Sciences, St. Paul's Hospital, Vancouver, British Columbia, Canada (HS, NB, AHA).,Canadian HIV Trials Network, Vancouver, British Columbia, Canada (HS).,School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada (NB, AHA).,Centre for Health Economics, University of York, York, UK (SCG, MS).,Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute and Division of General Internal Medicine, St. Michael's Hospital, Toronto, Ontario, Canada (AMB).,Departments of Medicine and Health Policy, Management and Evaluation, University of Toronto, Ontario, Canada (AMB).,Division of Infectious Diseases, University of Ottawa at The Ottawa Hospital, Ottawa, Ontario, Canada (WC).,James J. Peters VA Medical Center, Bronx, New York (STB).,VA Palo Alto Health Care System, Palo Alto, California (MH, DKO).,Center for Primary Care and Outcomes Research, Stanford University, Stanford, California (DKO)
Douglas K Owens VA Palo Alto Health Care System, VA Cooperative Studies Program Coordinating Center, VA HSR&D Health Economics Resource Center, Menlo Park, California (VRJ, PGB).,Centre for Health Evaluation and Outcome Sciences, St. Paul's Hospital, Vancouver, British Columbia, Canada (HS, NB, AHA).,Canadian HIV Trials Network, Vancouver, British Columbia, Canada (HS).,School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada (NB, AHA).,Centre for Health Economics, University of York, York, UK (SCG, MS).,Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute and Division of General Internal Medicine, St. Michael's Hospital, Toronto, Ontario, Canada (AMB).,Departments of Medicine and Health Policy, Management and Evaluation, University of Toronto, Ontario, Canada (AMB).,Division of Infectious Diseases, University of Ottawa at The Ottawa Hospital, Ottawa, Ontario, Canada (WC).,James J. Peters VA Medical Center, Bronx, New York (STB).,VA Palo Alto Health Care System, Palo Alto, California (MH, DKO).,Center for Primary Care and Outcomes Research, Stanford University, Stanford, California (DKO)

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Enns EA, Zaric GS, Strike CJ, Jairam JA, Kolla G, Bayoumi AM. Potential cost-effectiveness of supervised injection facilities in Toronto and Ottawa, Canada. Addiction 2016;111:475-89. [PMID: 26616368 DOI: 10.1111/add.13195] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/06/2015] [Revised: 06/15/2015] [Accepted: 09/30/2015] [Indexed: 02/06/2023]

Abstract

BACKGROUND AND AIMS

Supervised injection facilities (legally sanctioned spaces for supervised consumption of illicitly obtained drugs) are controversial public health interventions. We determined the optimal number of facilities in two Canadian cities using health economic methods.

DESIGN

Dynamic compartmental model of HIV and hepatitis C transmission through sexual contact and sharing of drug use equipment.

SETTING

Toronto and Ottawa, Canada.

PARTICIPANTS

Simulated population of each city.

INTERVENTIONS

Zero to five supervised injection facilities.

MEASUREMENTS

Direct health-care costs and quality-adjusted life-years (QALYs) over 20 years, discounted at 5% per year; incremental cost-effectiveness ratios.

FINDINGS

In Toronto, one facility cost $4.1 million and resulted in a gain of 385 QALYs over 20 years, for an incremental cost-effectiveness ratio (ICER) of $10,763 per QALY [95% credible interval (95CrI): cost-saving to $278,311]. Establishing one facility in Ottawa had an ICER of $6127 per QALY (95CrI: cost-saving to $179,272). At a $50,000 per QALY threshold, three facilities would be cost-effective in Toronto and two in Ottawa. The probability that establishing three, four, or five facilities in Toronto was cost-effective was 17, 21, and 41%, respectively. Establishing one, two, or three facilities in Ottawa was cost-effective with 13, 35, and 41% probability, respectively. Establishing no facility was unlikely to be the most cost-effective option (14% in Toronto and 10% in Ottawa). In both cities, results were robust if the reduction in needle-sharing among clients of the facilities was at least 50% and fixed operating costs were less than $2.0 million.

CONCLUSIONS

Using a $50,000 per quality-adjusted life-years threshold for cost-effectiveness, it is likely to be cost-effective to establish at least three legally sanctioned spaces for supervised injection of illicitly obtained drugs in Toronto, Canada and two in Ottawa, Canada.

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Tran BX, Nguyen LH, Ohinmaa A, Maher RM, Nong VM, Latkin CA. Longitudinal and cross sectional assessments of health utility in adults with HIV/AIDS: a systematic review and meta-analysis. BMC Health Serv Res 2015;15:7. [PMID: 25609449 PMCID: PMC4307193 DOI: 10.1186/s12913-014-0640-z] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2014] [Accepted: 12/08/2014] [Indexed: 11/17/2022] Open

Abstract

Background

Utility estimates are important health outcomes for economic evaluation of care and treatment interventions for patients with HIV/AIDS. We conducted a systematic review and meta-analysis of utility measurements to examine the performance of preference-based instruments, estimate health utility of patients with HIV/AIDS by disease stages, and investigate changes in their health utility over the course of antiretroviral treatment.

Methods

We searched PubMed/Medline, Cochrane Database of Systematic Review, NHS Economic Evaluation Database and Web of Science for English-language peer-reviewed papers published during 2000–2013. We selected 49 studies that used 3 direct and 6 indirect preference based instruments to make a total of 218 utility measurements. Random effect models with robust estimation of standard errors and multivariate fractional polynomial regression were used to obtain the pooled estimates of utility and model their trends.

Results

Reliability of direct-preference measures tended to be lower than other types of measures. Utility elicited by two of the indirect preference measures - SF-6D (0.171) and EQ-5D (0.114), and that of Time-Trade off (TTO) (0.151) was significantly different than utility elicited by Standard Gamble (SG). Compared to asymptomatic HIV patients, symptomatic and AIDS patients reported a decrement of 0.025 (p&#×2009;=&#×2009;0.40) and 0.176 (p&#×2009;=&#×2009;0.001) in utility scores, adjusting for method of assessment. In longitudinal studies, the pooled health utility of HIV/AIDS patients significantly decreased in the first 3 months of treatment, and rapidly increased afterwards. Magnitude of change varied depending on the method of assessment and length of antiretroviral treatment.

Conclusion

The study provides an accumulation of evidence on measurement properties of health utility estimates that can help inform the selection of instruments for future studies. The pooled estimates of health utilities and their trends are useful in economic evaluation and policy modelling of HIV/AIDS treatment strategies.

Electronic supplementary material

The online version of this article (doi:10.1186/s12913-014-0640-z) contains supplementary material, which is available to authorized users.

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Remenschneider AK, Scangas G, Meier JC, Gray ST, Holbrook EH, Gliklich RE, Metson R. EQ-5D-derived health utility values in patients undergoing surgery for chronic rhinosinusitis. Laryngoscope 2014;125:1056-61. [PMID: 25431320 DOI: 10.1002/lary.25054] [Citation(s) in RCA: 51] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2014] [Revised: 10/29/2014] [Accepted: 10/31/2014] [Indexed: 11/09/2022]

Cost-effectiveness of newer antiretroviral drugs in treatment-experienced patients with multidrug-resistant HIV disease. J Acquir Immune Defic Syndr 2013;64:382-91. [PMID: 24129369 DOI: 10.1097/qai.0000000000000002] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]

Abstract

OBJECTIVE

Newer antiretroviral drugs provide substantial benefits but are expensive. The cost-effectiveness of using antiretroviral drugs in combination for patients with multidrug-resistant HIV disease was determined.

DESIGN

A cohort state-transition model was built representing treatment-experienced patients with low CD4 counts, high viral load levels, and multidrug-resistant virus. The effectiveness of newer drugs (those approved in 2005 or later) was estimated from published randomized trials. Other parameters were estimated from a randomized trial and from the literature. The model had a lifetime time horizon and used the perspective of an ideal insurer in the United States. The interventions were combination antiretroviral therapy, consisting of 2 newer drugs and 1 conventional drug, compared with 3 conventional drugs. Outcome measures were life-years, quality-adjusted life-years (QALYs), costs, and incremental cost-effectiveness.

RESULTS

Substituting newer antiretroviral drugs increased expected survival by 3.9 years in advanced HIV disease. The incremental cost-effectiveness ratio of newer, compared with conventional, antiretroviral drugs was $75,556/QALY gained. Sensitivity analyses showed that substituting only one newer antiretroviral drug cost $54,559 to $68,732/QALY, depending on assumptions about efficacy. Substituting 3 newer drugs cost $105,956 to $117,477/QALY. Cost-effectiveness ratios were higher if conventional drugs were not discontinued.

CONCLUSIONS

In treatment-experienced patients with advanced HIV disease, use of newer antiretroviral agents can be cost-effective, given a cost-effectiveness threshold in the range of $50,000 to $75,000 per QALY gained. Newer antiretroviral agents should be used in carefully selected patients for whom less expensive options are clearly inferior.

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Joyce VR, Smith MW, Johansen KL, Unruh ML, Siroka AM, O'Connor TZ, Palevsky PM. Health-related quality of life as a predictor of mortality among survivors of AKI. Clin J Am Soc Nephrol 2012;7:1063-70. [PMID: 22595826 DOI: 10.2215/cjn.00450112] [Citation(s) in RCA: 22] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]

Schwartz A. Measuring Health-Related Quality of Life. Med Decis Making 2012;32:9-10. [DOI: 10.1177/0272989x11434207] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]