Patient and Regimen Characteristics Associated with Self-Reported Nonadherence to Antiretroviral Therapy

Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America.
PLoS ONE (Impact Factor: 3.23). 02/2007; 2(6):e552. DOI: 10.1371/journal.pone.0000552
Source: PubMed


Nonadherence to antiretroviral therapy (ARVT) is an important behavioral determinant of the success of ARVT. Nonadherence may lead to virological failure, and increases the risk of development of drug resistance. Understanding the prevalence of nonadherence and associated factors is important to inform secondary HIV prevention efforts.
We used data from a cross-sectional interview study of persons with HIV conducted in 18 U.S. states from 2000-2004. We calculated the proportion of nonadherent respondents (took <95% of prescribed doses in the past 48 hours), and the proportion of doses missed. We used multivariate logistic regression to describe factors associated with nonadherence. Nine hundred and fifty-eight (16%) of 5,887 respondents reported nonadherence. Nonadherence was significantly (p<0.05) associated with black race and Hispanic ethnicity; age <40 years; alcohol or crack use in the prior 12 months; being prescribed >or=4 medications; living in a shelter or on the street; and feeling "blue" >or=14 of the past 30 days. We found weaker associations with having both male-male sex and injection drug use risks for HIV acquisition; being prescribed ARVT for >or=21 months; and being prescribed a protease inhibitor (PI)-based regimen not boosted with ritonavir. The median proportion of doses missed was 50%. The most common reasons for missing doses were forgetting and side effects.
Self-reported recent nonadherence was high in our study. Our data support increased emphasis on adherence in clinical settings, and additional research on how providers and patients can overcome barriers to adherence.

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    • "Adherence to HIV medications. Of 47 studies addressing adherence to HIV medications (Applebaum et al., 2009; Arnsten et al., 2002; Berg et al., 2004; Beyene et al., 2009; Bonolo et al., 2005; Bouhnik et al., 2002; Campos et al., 2010; Chander et al., 2006; Chesney et al., 2000; Cohn et al., 2008; Cook et al., 2001; de Jong et al., 2005; Duran et al., 2001a, 2001b; Friedman et al., 2009; Golin et al., 2002; Halkitis et al., 2003, 2005; Heckman et al., 2004; Holmes et al., 2007; Howard et al., 2002; Ingersoll, 2004; Johnson et al., 2003; Lazo et al., 2007; Leserman et al., 2008; Liu et al., 2006; Martini et al., 2004; McDonnell Holstad et al., 2006; Mellins et al., 2009; Moatti et al., 2000; Mugavero et al., 2006; Murphy et al., 2004; Parsons et al., 2007; Peretti-Watel et al., 2006; Protopopescu et al., 2009; Rothlind et al., 2005; Roux et al., 2009; Safren et al., 2001; Samet et al., 2004; Silva et al., 2009; Spire et al., 2002; Sullivan et al., 2007; Theall et al., 2007; Waldrop-Valverde and Valverde, 2005; Waldrop-Valverde et al., 2006; Wang and Wu, 2007), 38 conducted multivariate analyses and, of these, 27 (71%) reported statistically signifi cant associations of poor adherence with alcohol consumption (range in reported effect sizes: 0.76–4.76). Among studies of specifi c patterns of alcohol use, signifi cantly poorer adherence (ORs) was reported by 9 of 12 studies of problem drinking (1.22–3.70); 2 of 3 studies of heavy episodic drinking (1.43–1.8), of which one found an effect only in women; 8 of 11 studies of moderate alcohol consumption (1.28–3.0); "
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    ABSTRACT: Nonadherence to medications can lead to adverse health outcomes. Alcohol consumption has been shown to be associated with nonadherence to antiretroviral medications, but this relationship has not been examined at different drinking levels or with other chronic disease medications. We conducted a narrative synthesis of the association of alcohol consumption with nonadherence to medications for four chronic diseases. We searched MEDLINE, PsycINFO, Cochrane Library, and Web of Science for relevant studies published through 2009. To be included in this analysis, studies had to be quantitative; have a sample size of 50 or greater; and examine the effect of alcohol consumption on medication adherence for diabetes, hypertension, depression, or HIV/AIDS. Study characteristics and results were abstracted according to pre-specified criteria, and study quality was assessed. Study heterogeneity prevented a systematic synthesis. Sixty eligible studies addressed medication adherence for HIV in 47 (78%), diabetes in 6 (10%), hypertension in 2 (3%), both diabetes and hypertension in 1 (2%), depression in 2 (3%), and all medications in 2 (3%). Mean number of subjects was 245 (range: 57-61,511). Effect sizes for the association of alcohol use with nonadherence varied (0.76-4.76). Six of the seven highest quality studies reported significant effect sizes (p < .05), ranging from 1.43 to 3.6. Most (67%) studies reporting multivariate analyses, but only half of non-HIV medicine studies, reported significant associations. Most studies reported negative effects of alcohol consumption on adherence, but evidence among non-HIV studies was less consistent. These data suggest the relevance of addressing alcohol use in improving antiretroviral adherence and a need for further rigorous study in non-HIV chronic diseases.
    Journal of studies on alcohol and drugs 11/2012; 73(6):899-910. DOI:10.15288/jsad.2012.73.899 · 2.76 Impact Factor
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    ABSTRACT: Despite the proven efficacy of prescription regimens in reducing disease symptoms and preventing or minimizing complications, poor medication adherence remains a significant public health problem. Medicare beneficiaries have high rates of chronic illness and prescription medication use, making this population particularly vulnerable to nonadherence. Failure to fill prescribed medication is a key component of nonadherence. To (1) determine the rates of self-reported failure to fill at least 1 prescription among a sample of Medicare beneficiaries in 2004, (2) identify the reasons for not filling prescribed medication, (3) examine the characteristics of Medicare beneficiaries who failed to fill their prescription(s), and (4) identify the types of medications that were not obtained. The study is a secondary analysis of the 2004 Medicare Current Beneficiary Survey (MCBS), an ongoing national panel survey conducted by the Centers for Medicare & Medicaid Services (CMS). Medicare beneficiaries living in the community (N = 14,464) were asked: "During the current year [2004], were there any medicines prescribed for you that you did not get (please include refills of earlier prescriptions as well as prescriptions that were written or phoned in by a doctor)?" Those who responded "yes" to this question (n = 664) were asked to identify the specific medication(s) not obtained. Rates of failure to fill were compared by demographic and income categories and for respondents with versus without self-reported chronic conditions, identified by asking respondents if they had ever been told by a doctor that they had the condition. Weighted population estimates for nonadherence were calculated using Professional Software for Survey Data Analysis for Multi-stage Sample Designs (SUDAAN) to account for the MCBS multistage stratified cluster sampling process. Unweighted counts of the prescriptions not filled by therapeutic class were calculated using Statistical Analysis Software (SAS). In 2004, an estimated 1.6 million Medicare beneficiaries (4.4%) failed to fill or refill 1 or more prescriptions. The most common reasons cited for failure to fill were: "thought it would cost too much" (55.5%), followed by "medicine not covered by insurance" (20.2%), "didn't think medicine was necessary for the condition" (18.0%), and "was afraid of medicine reactions/contraindications" (11.8%). Rates of failure to fill were significantly higher among Medicare beneficiaries aged 18 to 64 years eligible through Social Security Disability Insurance (10.4%) than among beneficiaries aged 65 years or older (3.3%, P < 0.001). Rates were slightly higher for women than for men (5.0 vs. 3.6%, P = 0.001), for nonwhite than for white respondents (5.5% vs. 4.2%, P = 0.010), and for dually eligible Medicaid beneficiaries than for those who did not have Medicaid coverage (6.3% vs. 4.0% P = 0.001). Failure-to-fill rates were significantly higher among beneficiaries with psychiatric conditions (8.0%, P < 0.001); arthritis (5.2%, P < 0.001); cardiovascular disease (5.2%, P = 0.003); and emphysema, asthma, or chronic obstructive pulmonary disease (6.6%, P < 0.001) than among respondents who did not report those conditions, and the rate for respondents who reported no chronic conditions was 2.5%. Rates were higher for those with more self-reported chronic conditions (3.2%, 4.0%, 4.3%, and 5.9% for those with 1, 2, 3, and 4 or more conditions, respectively, P < 0.001). Among the prescriptions not filled (993 prescriptions indentified by 664 respondents), central nervous system agents, including nonsteroidal anti-inflammatory drugs, were most frequently identified (23.6%, n = 234), followed by cardiovascular agents (18.3%, n = 182) and endocrine/metabolic agents (6.5%, n = 65). Of the reported unfilled prescriptions, 8.1% were for antihyperlipidemic agents, 5.4% were for antidepressant drugs, 4.6% were for antibiotics, and 29.9% were for unidentified therapy classes. Most Medicare beneficiaries fill their prescriptions, but some subpopulations are at significantly higher risk for nonadherence associated with unfilled prescriptions, including working-age beneficiaries, dual-eligible beneficiaries, and beneficiaries with multiple chronic conditions. Self-reported unfilled prescriptions included critical medications for treatment of acute and chronic disease, including antihyperlipidemic agents, antidepressants, and antibiotics.
    Journal of managed care pharmacy: JMCP 07/2008; 14(6):553-60. · 2.71 Impact Factor
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    ABSTRACT: Despite the effectiveness of prophylaxis, Pneumocystis jirovecii pneumonia (PCP) continues to be the most common serious opportunistic infection among HIV-infected persons. We describe factors associated with nonadherence to primary PCP prophylaxis. We used 2000-2004 data from the Supplement to HIV/AIDS Surveillance (SHAS) project, a cross-sectional interview project of HIV-infected persons >or=18 years conducted in 18 states. We limited the analysis to persons who denied having prior PCP, reported having a current prescription to prevent PCP, and answered the question "In the past 30 days, how often were you able to take the PCP medication(s) exactly the way your doctor told you to take them?" We used multivariable logistic regression to describe factors associated with nonadherence. Of 1,666 subjects prescribed PCP prophylaxis, 305 (18.3%) were nonadherent. Persons were more likely to be nonadherent if they reported using marijuana (adjusted odds ratio [aOR] = 1.6, 95% confidence interval [CI] = 1.1-2.4), non-injection drugs other than marijuana (aOR = 1.5, 95% CI = 1.0-2.1), or injection drugs (aOR = 2.3, 95% CI = 1.3-4.1) in the past year; their mental health was "not good" for >or=1 day during the past month (aOR = 1.6, 95% CI = 1.2-2.2); their most recent CD4 count was <200 cells/microL (aOR = 1.6, 95% CI = 1.1-2.2); or taking ART usually (aOR = 9.6, 95% CI = 6.7-13.7) or sometimes/rarely/never (aOR = 18.4, 95% CI = 11.1-30.4), compared with always, as prescribed. Providers should inquire about and promote strategies to improve adherence to PCP prophylaxis, particularly among persons who use illicit drugs, have mental health issues, and who are not compliant with ART to reduce the occurrence of PCP.
    PLoS ONE 02/2009; 4(3):e5002. DOI:10.1371/journal.pone.0005002 · 3.23 Impact Factor
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