Skip to main content
Top
Published in: AIDS and Behavior 1/2013

01-01-2013 | Original Paper

MACH14: A Multi-Site Collaboration on ART Adherence Among 14 Institutions

Published in: AIDS and Behavior | Issue 1/2013

Login to get access

Abstract

The integration of original data from multiple antiretroviral (ARV) adherence studies offers a promising, but little used method to generate evidence to advance the field. This paper provides an overview of the design and implementation of MACH14, a collaborative, multi-site study in which a large data system has been created for integrated analyses by pooling original data from 16 longitudinal ARV adherence studies. Studies selected met specific criteria including similar research design and data domains such as adherence measured with medication event monitoring system, psychosocial factors related to adherence behavior, and virologic and clinical outcomes. The data system created contains individual data (collected between 1997 and 2009) from 2,860 HIV patients. Collaboration helped resolve the challenges inherent in pooling data across multiple studies, yet produced a data system with strong statistical power and potentially greater capacity to address key scientific questions than possible with single-sample studies or even meta-analytic designs.
Literature
1.
go back to reference Feeney ER, Mallon PWG. HIV and HAART-associated dyslipidemia. Open Cardiovasc Med J. 2011;5:49–63.PubMedCrossRef Feeney ER, Mallon PWG. HIV and HAART-associated dyslipidemia. Open Cardiovasc Med J. 2011;5:49–63.PubMedCrossRef
2.
go back to reference Enanoria WTA, Ng C, Saha SR, Colford JM Jr. Treatment outcomes after highly active antiretroviral therapy: a meta-analysis of randomised controlled trials. Lancet Infect Dis. 2004;4(7):414–25.PubMedCrossRef Enanoria WTA, Ng C, Saha SR, Colford JM Jr. Treatment outcomes after highly active antiretroviral therapy: a meta-analysis of randomised controlled trials. Lancet Infect Dis. 2004;4(7):414–25.PubMedCrossRef
3.
go back to reference Bhaskaran K, Hamouda O, Sannes M, et al. Changes in the risk of death after HIV seroconversion compared with mortality in the general population. JAMA. 2008;300(1):51–9.PubMedCrossRef Bhaskaran K, Hamouda O, Sannes M, et al. Changes in the risk of death after HIV seroconversion compared with mortality in the general population. JAMA. 2008;300(1):51–9.PubMedCrossRef
4.
go back to reference Bangsberg DR, Hecht FM, Charlebois ED, et al. Adherence to protease inhibitors, HIV-1 viral load, and development of drug resistance in an indigent population. AIDS. 2000;14(4):357–66.PubMedCrossRef Bangsberg DR, Hecht FM, Charlebois ED, et al. Adherence to protease inhibitors, HIV-1 viral load, and development of drug resistance in an indigent population. AIDS. 2000;14(4):357–66.PubMedCrossRef
5.
go back to reference Lucas GM. Antiretroviral adherence, drug resistance, viral fitness and HIV disease progression: a tangled web is woven. J Antimicrob Chemother. 2005;55(4):413–6.PubMedCrossRef Lucas GM. Antiretroviral adherence, drug resistance, viral fitness and HIV disease progression: a tangled web is woven. J Antimicrob Chemother. 2005;55(4):413–6.PubMedCrossRef
6.
go back to reference Chen LF, Hoy J, Lewin SR. Ten years of highly active antiretroviral therapy for HIV infection. Med J Aust. 2007;186(3):146–51.PubMed Chen LF, Hoy J, Lewin SR. Ten years of highly active antiretroviral therapy for HIV infection. Med J Aust. 2007;186(3):146–51.PubMed
7.
go back to reference Liu H, Golin CE, Miller LG, et al. A comparison study of multiple measures of adherence to HIV protease inhibitors. Ann Intern Med. 2001;134(10):968–77.PubMed Liu H, Golin CE, Miller LG, et al. A comparison study of multiple measures of adherence to HIV protease inhibitors. Ann Intern Med. 2001;134(10):968–77.PubMed
8.
go back to reference Reynolds NR. Adherence to antiretroviral therapies: state of the science. Curr HIV Res. 2004;2(3):207–14.PubMedCrossRef Reynolds NR. Adherence to antiretroviral therapies: state of the science. Curr HIV Res. 2004;2(3):207–14.PubMedCrossRef
9.
go back to reference Pearson CR, Simoni JM, Hoff P, Kurth AE, Martin DP. Assessing antiretroviral adherence via electronic drug monitoring and self-report: an examination of key methodological issues. AIDS Behav. 2007;11(2):161–73.PubMedCrossRef Pearson CR, Simoni JM, Hoff P, Kurth AE, Martin DP. Assessing antiretroviral adherence via electronic drug monitoring and self-report: an examination of key methodological issues. AIDS Behav. 2007;11(2):161–73.PubMedCrossRef
10.
go back to reference Wagner GJ. Predictors of antiretroviral adherence as measured by self-report, electronic monitoring, and medication diaries. AIDS Patient Care STD. 2002;16(12):599–608.CrossRef Wagner GJ. Predictors of antiretroviral adherence as measured by self-report, electronic monitoring, and medication diaries. AIDS Patient Care STD. 2002;16(12):599–608.CrossRef
11.
go back to reference Wagner G. Placebo practice trials: the best predictor of adherence readiness for HAART among drug users? HIV Clinical Trials. 2003;4(4):269–81.PubMedCrossRef Wagner G. Placebo practice trials: the best predictor of adherence readiness for HAART among drug users? HIV Clinical Trials. 2003;4(4):269–81.PubMedCrossRef
12.
go back to reference Berg KM, Arnsten JH. Practical and conceptual challenges in measuring antiretroviral adherence. J Acquir Immune Defic Syndr. 2006;43(Suppl 1):S79–87.PubMedCrossRef Berg KM, Arnsten JH. Practical and conceptual challenges in measuring antiretroviral adherence. J Acquir Immune Defic Syndr. 2006;43(Suppl 1):S79–87.PubMedCrossRef
13.
go back to reference Levine AJ, Hinkin CH, Marion S, et al. Adherence to antiretroviral medications in HIV: differences in data collected via self-report and electronic monitoring. Health Psychol. 2006;25(3):329–35.PubMedCrossRef Levine AJ, Hinkin CH, Marion S, et al. Adherence to antiretroviral medications in HIV: differences in data collected via self-report and electronic monitoring. Health Psychol. 2006;25(3):329–35.PubMedCrossRef
14.
go back to reference Nachega JB, Hislop M, Dowdy DW, et al. Efavirenz versus nevirapine-based initial treatment of HIV infection: clinical and virological outcomes in Southern African adults. AIDS. 2008;22(16):2117–25.PubMedCrossRef Nachega JB, Hislop M, Dowdy DW, et al. Efavirenz versus nevirapine-based initial treatment of HIV infection: clinical and virological outcomes in Southern African adults. AIDS. 2008;22(16):2117–25.PubMedCrossRef
15.
go back to reference Rivet Amico K, Harman JJ, Johnson BT. Efficacy of antiretroviral therapy adherence interventions: a research synthesis of trials, 1996 to 2004. JAIDS J Acq Immune Defic Syndr. 2006;41(3):285–297. Rivet Amico K, Harman JJ, Johnson BT. Efficacy of antiretroviral therapy adherence interventions: a research synthesis of trials, 1996 to 2004. JAIDS J Acq Immune Defic Syndr. 2006;41(3):285–297.
16.
go back to reference Konkle-Parker DJ, Erlen JA, Dubbert PM. Lessons learned from an HIV adherence pilot study in the Deep South. Patient Educ Couns. 2010;78(1):91–6.PubMedCrossRef Konkle-Parker DJ, Erlen JA, Dubbert PM. Lessons learned from an HIV adherence pilot study in the Deep South. Patient Educ Couns. 2010;78(1):91–6.PubMedCrossRef
17.
go back to reference Giordano TP, Guzman D, Clark R, Charlebois ED, Bangsberg DR. Measuring adherence to antiretroviral therapy in a diverse population using a visual analogue scale. HIV Clin Trials. 2004;5(2):74–9.PubMedCrossRef Giordano TP, Guzman D, Clark R, Charlebois ED, Bangsberg DR. Measuring adherence to antiretroviral therapy in a diverse population using a visual analogue scale. HIV Clin Trials. 2004;5(2):74–9.PubMedCrossRef
18.
go back to reference Pinheiro JC, Bates DM. Mixed-effects models in S and S-PLUS. New York: Springer; 2009. Pinheiro JC, Bates DM. Mixed-effects models in S and S-PLUS. New York: Springer; 2009.
19.
go back to reference Teramukai S, Matsuyama Y, Mizuno S, Sakamoto J. Individual patient-level and study-level meta-analysis for investigating modifiers of treatment effect. Jpn J Clin Oncol. 2004;34(12):717–21.PubMedCrossRef Teramukai S, Matsuyama Y, Mizuno S, Sakamoto J. Individual patient-level and study-level meta-analysis for investigating modifiers of treatment effect. Jpn J Clin Oncol. 2004;34(12):717–21.PubMedCrossRef
20.
go back to reference Jones AP, Riley RD, Williamson PR, Whitehead A. Meta-analysis of individual patient data versus aggregate data from longitudinal clinical trials. Clin Trials. 2009;6(1):16.PubMedCrossRef Jones AP, Riley RD, Williamson PR, Whitehead A. Meta-analysis of individual patient data versus aggregate data from longitudinal clinical trials. Clin Trials. 2009;6(1):16.PubMedCrossRef
21.
go back to reference Lambert PC, Sutton AJ, Abrams KR, Jones DR. A comparison of summary patient-level covariates in meta-regression with individual patient data meta-analysis. J Clin Epidemiol. 2002;55(1):86–94.PubMedCrossRef Lambert PC, Sutton AJ, Abrams KR, Jones DR. A comparison of summary patient-level covariates in meta-regression with individual patient data meta-analysis. J Clin Epidemiol. 2002;55(1):86–94.PubMedCrossRef
22.
go back to reference Cooper H, Patall EA. The relative benefits of meta-analysis conducted with individual participant data versus aggregated data. Psychol Methods. 2009;14(2):165–76.PubMedCrossRef Cooper H, Patall EA. The relative benefits of meta-analysis conducted with individual participant data versus aggregated data. Psychol Methods. 2009;14(2):165–76.PubMedCrossRef
23.
go back to reference Liu H, Miller LG, Hays RD, et al. A practical method to calibrate self-reported adherence to antiretroviral therapy. JAIDS J Acq Immune Defic Syndr. 2006;43:S104–12.CrossRef Liu H, Miller LG, Hays RD, et al. A practical method to calibrate self-reported adherence to antiretroviral therapy. JAIDS J Acq Immune Defic Syndr. 2006;43:S104–12.CrossRef
24.
go back to reference Liu H, Miller LG, Hays RD, et al. Repeated measures longitudinal analyses of HIV virologic response as a function of percent adherence, dose timing, genotypic sensitivity, and other factors. JAIDS J Acq Immune Defic Syndr. 2006;41(3):315–22.CrossRef Liu H, Miller LG, Hays RD, et al. Repeated measures longitudinal analyses of HIV virologic response as a function of percent adherence, dose timing, genotypic sensitivity, and other factors. JAIDS J Acq Immune Defic Syndr. 2006;41(3):315–22.CrossRef
25.
go back to reference Little RJA, Rubin DB. Statistical analysis with missing data. 2nd ed. New York: Wiley-Interscience; 2002. Little RJA, Rubin DB. Statistical analysis with missing data. 2nd ed. New York: Wiley-Interscience; 2002.
26.
go back to reference Schafer JL, Graham JW. Missing data: our view of the state of the art. Psychol Methods. 2002;7(2):147–77.PubMedCrossRef Schafer JL, Graham JW. Missing data: our view of the state of the art. Psychol Methods. 2002;7(2):147–77.PubMedCrossRef
27.
go back to reference Collins LM, Schafer JL, Kam CM. A comparison of inclusive and restrictive strategies in modern missing data procedures. Psychol Methods. 2001;6(4):330–51.PubMedCrossRef Collins LM, Schafer JL, Kam CM. A comparison of inclusive and restrictive strategies in modern missing data procedures. Psychol Methods. 2001;6(4):330–51.PubMedCrossRef
28.
go back to reference Newgard CD, Haukoos JS. Advanced statistics: missing data in clinical research—part 2: multiple imputation. Acad Emerg Med. 2007;14(7):669–78.PubMed Newgard CD, Haukoos JS. Advanced statistics: missing data in clinical research—part 2: multiple imputation. Acad Emerg Med. 2007;14(7):669–78.PubMed
Metadata
Title
MACH14: A Multi-Site Collaboration on ART Adherence Among 14 Institutions
Publication date
01-01-2013
Published in
AIDS and Behavior / Issue 1/2013
Print ISSN: 1090-7165
Electronic ISSN: 1573-3254
DOI
https://doi.org/10.1007/s10461-012-0272-4

Other articles of this Issue 1/2013

AIDS and Behavior 1/2013 Go to the issue