Review article: Biomedical intelligence

Asking about adherence – from flipping the coin to strong evidence

DOI: https://doi.org/10.4414/smw.2014.14016
Publication Date: 21.09.2014
Swiss Med Wkly. 2014;144:w14016

Tracy Glass, Matthias Cavassini

Please find the affiliations for this article in the PDF.

Summary

In the era of antiretroviral therapy (ART) as prevention for transmission of HIV as well as treatment for HIV-positive individuals irrespective of CD4 cell counts, the importance of adherence has grown. Although adherence is not the only determinant of treatment success, it is one of the only modifiable risk factors. Treatment failure reduces future treatment options and therefore long-term clinical success as well as increases the possibility of developing drug resistant mutations. Drug-resistant strains of HIV can then be transmitted to uninfected or drug-naïve individuals limiting their future treatment options, making adherence an important public-health topic, especially in resource-limited settings.

Adherence should be monitored as a part of routine clinical care; however, no gold standard for assessment of adherence exists. For use in daily clinical practice, self-report is the most likely candidate for widespread use due to its many advantages over other measurement methods, such as low cost and ease of administration. Asking individuals about their adherence behaviour has been shown to yield valid and predictive data – well beyond the mere flip of a coin.

However, there is still work to be done. This article reviews the literature and evidence on self-reported adherence, identifies gaps in adherence research, and makes recommendations for clinicians on how to best utilise self-reported adherence data to support patients in daily clinical practice.

Keywords: prevention, surveillance, adherence, antiretroviral therapy, self-report

Adherence – definitions and terminology

The World Health Organization (WHO) defines adherence as “the extent to which a person’s behaviour – taking medications, following diet and/or executing lifestyle changes – corresponds with agreed recommendations from a health care provider”. It is estimated that adherence to long-term therapy for chronic illness in developed countries averages 50% and is even lower in developing countries [1]. Poor adherence leads to poor patient outcomes, increased health care costs, decreases patient safety, and diminishes the effectiveness of improvements in and access to medications.

In the context of HIV, adherence to antiretroviral therapy (ART) can be defined as the “ability of the person living with HIV/AIDS to be involved in choosing, starting, managing, and maintaining a given therapeutic medication regimen to control HIV replication and to improve immune function” [2]. This definition of adherence – with an emphasis on the patient’s role in choosing both when to start ART and which ART to take – highlights the movement toward a ‘new’ paradigm of provider-patient interaction for HIV care as suggested by Noring and colleagues [3]. A key element of the recommendations from this working group was the idea that the term ‘adherence’ should be replaced with ‘treatment maintenance’ as it better reflects the collaborative relationship between a patient as proactive participant and a provider as professional guide. In support of this are the European AIDS Clinical Society (EACS) guidelines which emphasise patient readiness to start ART as a key to adherence and successful treatment [4].

Why measure adherence?

Regardless of how one defines and names this concept, the importance of adherence to ART has increased as HIV has become a chronic illness and treatment of HIV requires life-long therapy once initiated. Although adherence is not the only determinant of treatment success, non-adherence is the most critical and one of the only modifiable risk factors leading to a chain of negative clinical outcomes, resulting in both personal and public-health implications.

Treatment failure

The initial goal of ART is to not only attain but maintain an undetectable viral load. Early reports in individuals on non-boosted protease inhibitors (PIs) estimated that they must take 95% of their medication to remain virally suppressed [12]. Several studies were done to explore whether the 95% rule applied to other drug classes and found non-nucleoside reverse transcriptase inhibitors (NNRTI) and boosted PI regimens to be more ‘forgiving’ – able to achieve and maintain viral suppression despite imperfect medication adherence [13–16]. Recent evidence looking at an integrase inhibitor (raltegravir) found that the risk of virologic failure was 50% after treatment interruptions of 7 days compared to a 15–day interruption on an NNRTI [17]. The majority of patients on potent regimens are able to maintain viral suppression at adherence rates lower than 95% [18–21].

Resistance

Virologic failure not only reduces future treatment options and therefore long-term clinical success but also increases the possibility of developing drug resistant mutations [6, 7, 23]. Studies of the relationship between adherence and resistance in HIV indicate that the relationship is more complicated than originally thought, with each drug class having a unique adherence-resistance relationship [26–29]. Boosted PI regimens – PIs taken with ritonavir (or cobicistat) – allow for more potent viral suppression than unboosted PI regimens [30] and have a longer half-life so PI concentrations remain at subinhibitory concentrations for only a brief time during periods of non-adherence [31]. In addition, this allows for a once daily formulation which for some patients may have a positive impact on adherence [32]. Resistance to PIs usually requires multiple mutations; therefore high level resistance requires both ongoing viral replication and sufficient drug exposure to create a selective advantage for drug-resistant virus [31].

For NNRTI regimens, resistance is associated with interruptions in therapy [33] and develops at a lower level of adherence than PI resistance [34]. Unlike most PI drugs, resistance to the NNRTIs nevirapine and efavirenz requires only a single mutation [35]. However, most NNRTIs have longer half-lives requiring more than one missed dose for the virus to replicate at subinhibitory plasma drug concentrations [36]. The clinical implications of NNRTI resistance are considerable since NNRTI resistance almost universally confers to cross-resistance to first generation NNRTIs [37]. In case of virological failure, the accumulation of NRTI mutation is higher for patients failing a NNRTI regimen compared to patients failing a boosted PI regimen [38]. The mechanism behind the protective effect of PIs on NRTIs remains unclear but has been confirmed in clinical trials and cohorts.

AIDS-defining illness and mortality

Several studies have shown non-adherence to be associated with mortality [39–42] and progression to AIDS [43]. A meta-analysis of the association between adherence and mortality found a pooled odds ratio of death in the subset of HIV studies of 0.53 (95% CI: 0.41 –0.69) in adherent patients compared to non-adherent patients [44].

Public health implications of non-adherence to antiretroviral drugs

The importance of adherence in the life of an HIV-infected person on ART is undisputed. However, the adherence patterns of individuals can also have public health implications. In those already infected with HIV, it is now known that ART reduces the viral load and therefore infectiousness, limiting the risk of onward transmission [45–48]. The test and treat policy – universal HIV testing to enhance the identification of all HIV-positive individuals followed by immediate treatment irrespective of their CD4 cell counts – has been postulated as a potential tool capable of reducing HIV incidence at a population level [49, 50].

Pre-exposure prophylaxis (PrEP), the use of antiretroviral agents by HIV-uninfected persons before potential sexual exposure to HIV-infected partners, is a new approach to HIV prevention and has been approved by the FDA in 2013 [51]. Several double-blind randomised clinical trials have studied the efficacy and tolerance of PrEP to prevent HIV acquisition in high risk groups with varying results with regards to efficacy [52–55]. This large range of efficacy (0–75%) has been mostly linked to adherence to PrEP. Not surprisingly the adherence (and efficacy) was highest in the study that randomised individuals who had sex with an HIV infected stable partner compared to studies where individuals had sexual partners of unknown HIV status. The potential to develop resistance from PrEP can jeopardise the therapeutic use of these drugs in the subsequent treatment of the individual and for the community at large if resistance to the agents spreads more broadly [56, 57]. The low adherence levels reported in some of these studies [54] lend credence to these concerns especially in settings where adherence, viral load, and resistance are not being monitored.

How should adherence be measured?

The importance of adherence as a predictor or determinant of the success of treatment has been clearly documented above, and as such, it would seem clear that the adherence of a patient should be closely monitored. In addition, adherence is a dynamic process and has been shown to vary over time [58–63] and therefore should be measured regularly as part of routine clinical care. However, there is no gold standard for the assessment of adherence nor is there a single optimal tool that enhances adherence to HIV treatment regimens [64].

There are five main methods for adherence measurement: self-report, medication event monitoring system (MEMS), pill count, pharmacy refill, and therapeutic drug monitoring (TDM). Each method has its own strengths and weaknesses and therefore the choice of measurement method often depends on the purpose and intended use of the measurement. Using a combination of methods to measure adherence is likely to provide the most accurate results. Several articles have provided a good overview of measurement methods [65, 66].

Asking about adherence

For the purpose of this article, we will focus on self-reported adherence. Self-report is by far the simplest and most convenient method of measuring adherence. The main advantages are its low cost, low staff and respondent burden, and extreme flexibility [65]. Self-report can measure all four dimensions of adherence behaviour – taking adherence (the extent to which a patient is taking the prescribed medication), timing adherence (the extent to which a patient is adhering to the prescribed schedule for drug intake), drug holidays (missing several doses of medication in a row), and food restrictions (the extent a patient is adhering to drug intake in relation to food restrictions) [1]. For use in daily clinical practice and management of a patient, self-report comes out as the most likely candidate for widespread use due to its many advantages over other measurement methods especially when considering resource-limited settings.

However, self-report is subject to overreporting [67]. While patients’ reporting of non-adherence has been found to be credible [68, 69], their estimate of adherence is often inaccurate [70, 71] overestimating adherence by 10–20% compared to MEMS [72, 73] and 5–10% compared to TDM [69]. A recent study in PrEP in high-risk African women found self-reported adherence to be unreliable with 95% of women reporting taking the drugs on a regular basis whereas only 22% showed evidence of taking the drug on study visits according to TDM [54].

Belli and colleagues suggested the cognitive processes responsible for this overreporting are intentional deception and misremembering [74]. Intentional deception happens as a result of social-desirability bias; the tendency of patient’s to answer questions in a manner that will be viewed favourably by others. Respondents may alter their responses if they believe answers will trigger either pleasant or unpleasant reactions. Most of the overreporting of adherence, however, is thought to be due to misremembering [75] which presents a tougher challenge to overcome. When asking about mundane behaviour carried out on a routine basis, it is believed that patients are unable to separate action from intention. So when they report having taken their medication, they may be misremembering their intention to take the medication as the actual act of taking the medication.

There exist many different validated self-report instruments for measuring adherence complicating the comparability and interpretability of study findings. Adherence questions range from global estimates of how much medication was taken using estimation recall to specific inquiries into the exact number of missed doses utilising count-based recall. The methods for administering questionnaires also differ, such as structured interviews and paper or computer self-assessments. Nevertheless, two systematic reviews including a large number of observational studies (mostly count-based) found a robust association between self-reported adherence and viral load over varying measures and recall periods [76] and indicated that self-reported adherence measures can distinguish between clinically meaningful patterns of medication-taking behaviour [77]. Simoni and colleagues found that self-reported adherence was significantly correlated with viral load in 84% of comparisons [76]. Nieuwkerk and Oort compiled 65 studies of self-reported adherence to estimate a pooled odds ratio of having a detectable viral load of 2.31 (95% confidence interval (CI): 1.99–2.68) in non-adherent patients compared to adherent patients [77]. In addition, they found that studies using a threshold for non-adherence below 95% had stronger association with treatment failure suggesting a lower threshold to be more appropriate. Predictive validity for estimation recall has also been established for virologic and immunologic outcomes [78–80].

Strategies to improve accuracy of self-report

Regardless of the evidence of the validity of self-report, it is clear there should be a focus on improving the accuracy of self-report. Review of the literature has identified several issues that need to be considered in the quest for the best self-report tool: what questions should be asked, what recall period should be used, and how the questionnaire should be administered.

Which instrument should be used?

Examples of instruments using estimation recall include the Swiss HIV Cohort Study (SHCS) adherence questionnaire [81, 82], visual analogue scales [83, 84], and the Case Index Questionnaire [80]. A common used example of an instrument with count-based recall is the AIDS Clinical Trial Group (ATCG) questionnaire [85]. Lu and colleagues found that estimation of one’s ability to adhere, outperformed count-based measures of adherence in relation to MEMS data [86]. Similarly, Schneider and colleagues found that patient’s found it easier to answer questions using Likert scales (in which respondents specify their level of agreement or disagreement on a symmetric agree-disagree scale for a series of statements), which use estimation recall, rather than asking for the specific number of missed doses or percentage adherence [87]. A typical example of a 5–point Likert scale are: strongly disagree, disagree, neither agree nor disagree, agree, strongly agree. Recent guidelines from the EACS recommend using the SHCS adherence questionnaire for routine clinical assessment [4].

What is the optimal recall period?

Several studies suggest ways to minimise misremembering by keeping the recall period relatively short. The optimal recall period for count-based measures is over the last three days [86]. Estimation recall measures have the added benefit of allowing assessment over longer time frames [78] and recent evidence suggests that a recall period of 30 days may be optimal with less overreporting than 3–7 day recall [75, 76, 79, 86].

How should adherence information be collected?

The way in which adherence information is collected – interview with clinician, nurse or pharmacist, paper or computer – will also likely have an effect on the accuracy of the data. Intentional deception can occur both in interviews or with self-administered questionnaires if the respondent thinksthe answers will be provided to their clinician. One option is to use a self-administered questionnaire that patients know will not be shared with their clinician. However, interviews have the advantage that they allow for the discussion of the reason for non-adherence and potential solutions [65]. If proper training is provided, interviews can not only yield accurate adherence data, but contribute to a positive health-care provider-patient relationship, which in turn can have a positive effect on adherence [87]. Williams and colleagues provide several strategies to minimise social desirability bias during interviews such as attempting to normalise non-adherence and avoiding responses to reports implying judgment (positive or negative) [66]. Other strategies include encouraging patients to take longer to respond or using cues to jog patients’ memory [75], such as asking about their regular strategies for taking medication and recent events that might have interrupted their normal routine.

Using adherence in clinical-decision making

As much as adherence research has enlightened the medical community as to the importance of adherence as a predictor of clinical outcomes, it still needs to go that one step further and provide clinicians with a clear strategy for using adherence information in routine clinical care as a method of preventing negative clinical outcomes. Knowing who is at risk for non-adherence and therefore a good candidate for adherence support or interventions would be extremely valuable information for clinicians. Critical information is missing to allow clinicians to practice evidence-based medicine – defined as the conscientious, explicit, and judicious use of current best evidence in making decisions about the care of individual patients.

There are clinics with success stories – Krummenacher and colleagues reported high retention and persistence rates with their interdisciplinary adherence programme that supports patients at risk for non-adherence with MEMS and motivational interviewing [88, 89]. Although this programme as a whole is not transportable to all settings, especially those with limited resources, it still offers an important example of fostering a collaborative relationship between patient and clinician and interdisciplinary teamwork for improved patient care.

So what gaps do researchers need to fill in order for adherence to go from being a predictive concept to a preventative tool?

Improve current measurement tools

Take some of the most promising self-report instruments in use and make changes that may improve accuracy. For example, the SHCS adherence questionnaire consists of 2–items using estimation recall to ask about timing adherence and drug holidays in the last 30 days [82]. This validated instrument [78, 82] could be expanded to cover the timing and food restriction dimensions of adherence, as well as including a visual analogue scale. These modifications could be done working with psychologists in the field of memory and recall to develop a better understanding of how respondents interpret adherence questions and what strategies they use to recall their behaviour and formulate responses. Experts in cognitive interviewing can advise on how best to administer the questionnaire to reduce intentional deception.

Fill the evidence gap

Using selected measurement tools, researchers need to provide ART class or even regimen-based cut-offs for when non-adherence leads to negative clinical outcomes. It has been shown that the majority of patients on potent regimens are able to maintain viral suppression at adherence rates lower than 95% [18–21], however, specific levels according to class or regimen remain unknown. In addition, the simplest regimen is not always the best one for the patient [90]. Understanding specific forgiveness levels of various ART regimens can help patients and clinicians decide which regimen provides the best fit. Moreover, adherence rates initially required to reach undetectable viral loads, may not have the same adherence rate to maintain an undetectable viral load over the long run [22]. Prospective studies for specific regimens are lacking.

Develop surveillance strategies for adherence

There are many unanswered questions as how best to monitor HIV patients and specifically the potential role of adherence. In settings with only limited or no viral load testing, adherence could be used as a proxy for viral load or as an indicator of when viral load testing is warranted. There is some evidence that this strategy could work as well as if not better than CD4 monitoring [91]. There are known risk factors for poor adherence including younger age, side effects, low self-efficacy, lack of social support, and acceptability of the regimen by the patient [58, 81, 92]. Monitoring strategies could be tailored to different risk groups and populations (HIV-negative on PrEP versus HIV-positive on ART) as the challenges in taking daily medication in a healthy person can differ from that of a chronically ill patient.

Develop adherence interventions and support programmes

Once it is known what level of non-adherence should serve as a warning for future treatment failure, clinicians need to know what to do with these at-risk patients. Amico and colleagues did a review of ART adherence interventions and found the effect to be small and varied [93]. Intervention effects tended to be higher in studies which provided didactic information on ART and included interactive discussion of cognitions, motivations, and expectations regarding adherence. Development and testing of adherence interventions makes the most sense when it is clear how best to measure adherence. Once measurement methods are standardised, promising interventions that target those with different levels of non-adherence to provide individual-based support can be tested and adopted into clinical practice.

Conclusions

So, yes, asking about adherence, regardless of how one asks, is better than flipping a coin and can even provide strong evidence. However, it is clear that promising self-assessment tools can be improved upon and then adopted into routine clinical care. Then there is an urgent need to fill the gaps in adherence research. In the era of ART as prevention for acquiring HIV, the consequences of non-adherence have taken on broader public health implications. Clinicians need adherence measures that can be easily implemented in clinical care with clear guidelines as to how to interpret adherence responses so that evidence-based decisions can be made.

Funding / potential competing interests: M.C. received travel grants from BMS, Boehringer Ingelheim, Gilead. M.C.'s institution received research grants from BMS, Gilead and MSD.

References

  1 Adherence to long-term therapies: Evidence for action. World Health Organization. 2004.

  2 Jani AA. Adherence to HIV Treatment Regimens: Recommendations for Best Practices APHA – www.apha.org/ppp/hiv. 2004.

  3 Noring S, Dubler NN, Birkhead G, Agins B. A new paradigm for HIV care: ethical and clinical considerations. American journal of public health. 2001;91(5):690–4.

  4 EACS. European Guidelines for treatment of HIV-infected adults in Europe. http://www.eacsociety.org/Guidelines.aspx. 2014.

  5 El-Sadr WM, Lundgren JD, Neaton JD, Gordin F, Abrams D, Arduino RC, et al. CD4+ count-guided interruption of antiretroviral treatment. N Engl J Med. 2006;355(22):2283–96.

  6 Bangsberg DR, Charlebois ED, Grant RM, Holodniy M, Deeks SG, Perry S, et al. High levels of adherence do not prevent accumulation of HIV drug resistance mutations. AIDS. 2003;17(13):1925–32.

  7 Burman W, Grund B, Neuhaus J, Douglas J, Jr., Friedland G, Telzak E, et al. Episodic antiretroviral therapy increases HIV transmission risk compared with continuous therapy: results of a randomized controlled trial. J Acquir Immune Defic Syndr. 2008;49(2):142–50.

  8 Wainberg MA, Friedland G. Public health implications of antiretroviral therapy and HIV drug resistance. JAMA. 1998;279(24):1977–83.

  9 Castro H, Pillay D, Cane P, Asboe D, Cambiano V, Phillips A, et al. Persistence of HIV-1 transmitted drug resistance mutations. The Journal of infectious diseases. 2013;208(9):1459–63.

10 Phillips AN, Pillay D, Garnett G, Bennett D, Vitoria M, Cambiano V, et al. Effect on transmission of HIV-1 resistance of timing of implementation of viral load monitoring to determine switches from first to second-line antiretroviral regimens in resource-limited settings. AIDS. 2011;25(6):843–50.

11 Cambiano V, Bertagnolio S, Jordan MR, Lundgren JD, Phillips A. Transmission of drug resistant HIV and its potential impact on mortality and treatment outcomes in resource-limited settings. J Infect Dis. 2013;207Suppl2:S57–62.

12 Paterson DL, Swindells S, Mohr J, Brester M, Vergis EN, Squier C, et al. Adherence to protease inhibitor therapy and outcomes in patients with HIV infection. Ann Intern Med. 2000;133(1):21–30.

13 Shuter J, Sarlo JA, Kanmaz TJ, Rode RA, Zingman BS. HIV-infected patients receiving lopinavir/ritonavir-based antiretroviral therapy achieve high rates of virologic suppression despite adherence rates less than 95%. J Acquir Immune Defic Syndr. 2007;45(1):4–8.

14 Maggiolo F, Ravasio L, Ripamonti D, Gregis G, Quinzan G, Arici C, et al. Similar adherence rates favor different virologic outcomes for patients treated with nonnucleoside analogues or protease inhibitors. Clin Infect Dis. 2005;40(1):158–63.

15 Knobel H. Are nonnucleoside analogue-based regimens better than protease inhibitor-based regimens for nonadherent HIV-infected patients? Clin Infect Dis. 2005;40(1):164–6.

16 Gulick RM. Adherence to antiretroviral therapy: how much is enough? Clin Infect Dis. 2006;43(7):942–4.

17 Gras G, Schneider MP, Cavassini M, Lucht F, Loilier M, Verdon R, et al. Patterns of adherence to raltegravir-based regimens and the risk of virological failure among HIV-infected patients: the RALTECAPS cohort study. Journal of acquired immune deficiency syndromes. 2012;61(3):265–9.

18 Shuter J. Forgiveness of non-adherence to HIV-1 antiretroviral therapy. J Antimicrob Chemother. 2008;61(4):769–73.

19 Bangsberg DR. Less than 95% adherence to nonnucleoside reverse-transcriptase inhibitor therapy can lead to viral suppression. Clin Infect Dis. 2006;43(7):939–41.

20 Nachega JB, Hislop M, Dowdy DW, Chaisson RE, Regensberg L, Maartens G. Adherence to nonnucleoside reverse transcriptase inhibitor-based HIV therapy and virologic outcomes. Ann Intern Med. 2007;146(8):564–73.

21 Liu H, Miller LG, Hays RD, Golin CE, Wu T, Wenger NS, et al. Repeated measures longitudinal analyses of HIV virologic response as a function of percent adherence, dose timing, genotypic sensitivity, and other factors. J Acquir Immune Defic Syndr. 2006;41(3):315–22.

22 Rosenblum M, Deeks SG, van der LM, Bangsberg DR. The risk of virologic failure decreases with duration of HIV suppression, at greater than 50% adherence to antiretroviral therapy. PLoS One. 2009;4(9):e7196.

23 von Wyl V, Klimkait T, Yerly S, Nicca D, Furrer H, Cavassini M, et al. Adherence as a predictor of the development of class-specific resistance mutations: the Swiss HIV Cohort Study. PloS One. 2013;8(10):e77691.

24 Belkin L. TB threat: not taking the medicine. Partly cured patients are the deadliest carriers. New York Times. 1991 1991.

25 Harries AD, Nyangulu DS, Hargreaves NJ, Kaluwa O, Salaniponi FM. Preventing antiretroviral anarchy in sub-Saharan Africa. Lancet. 2001;358(9279):410–4.

26 Bangsberg DR, Moss AR, Deeks SG. Paradoxes of adherence and drug resistance to HIV antiretroviral therapy. J Antimicrob Chemother. 2004;53(5):696–9.

27 Maggiolo F, Airoldi M, Kleinloog HD, Callegaro A, Ravasio V, Arici C, et al. Effect of adherence to HAART on virologic outcome and on the selection of resistance-conferring mutations in N. HIV Clin Trials. 2007;8(5):282–92.

28 Tam LW, Chui CK, Brumme CJ, Bangsberg DR, Montaner JS, Hogg RS, et al. The relationship between resistance and adherence in drug-naive individuals initiating HAART is specific to individual drug classes. J AcquirImmune Defic Syndr. 2008;49(3):266–71.

29 von W, V, Yerly S, Boni J, Burgisser P, Klimkait T, Battegay M, et al. Emergence of HIV-1 drug resistance in previously untreated patients initiating combination antiretroviral treatment: a comparison of different regimen types. Arch Intern Med. 2007;167(16):1782–90.

30 Bangsberg DR, Acosta EP, Gupta R, Guzman D, Riley ED, Harrigan PR, et al. Adherence-resistance relationships for protease and non-nucleoside reverse transcriptase inhibitors explained by virological fitness. AIDS. 2006;20(2):223–31.

31 King MS, Brun SC, Kempf DJ. Relationship between adherence and the development of resistance in antiretroviral-naive, HIV-1–infected patients receiving lopinavir/ritonavir or nelfinavir. J Infect Dis. 2005;191(12):2046–52.

32 Parienti JJ, Bangsberg DR, Verdon R, Gardner EM. Better adherence with once-daily antiretroviral regimens: a meta-analysis. Clinical infectious diseases: an official publication of the Infectious Diseases Society of America. 2009;48(4):484–8.

33 Parienti JJ, Massari V, Descamps D, Vabret A, Bouvet E, Larouze B, et al. Predictors of virologic failure and resistance in HIV-infected patients treated with nevirapine- or efavirenz-based antiretroviral therapy. Clin Infect Dis. 2004;38(9):1311–6.

34 Sethi AK, Celentano DD, Gange SJ, Moore RD, Gallant JE. Association between adherence to antiretroviral therapy and human immunodeficiency virus drug resistance. Clin Infect Dis. 2003;37(8):1112–8.

35 Jackson JB, Becker-Pergola G, Guay LA, Musoke P, Mracna M, Fowler MG, et al. Identification of the K103N resistance mutation in Ugandan women receiving nevirapine to prevent HIV-1 vertical transmission. AIDS. 2000;14(11):F111–F5.

36 Cohen CJ, Colson AE, Sheble-Hall AG, McLaughlin KA, Morse GD. Pilot study of a novel short-cycle antiretroviral treatment interruption strategy: 48–week results of the five-days-on, two-days-off (FOTO) study. HIV clinical trials. 2007;8(1):19–23.

37 Hare CB, Mellors J, Krambrink A, Su Z, Skiest D, Margolis DM, et al. Detection of nonnucleoside reverse-transcriptase inhibitor-resistant HIV-1 after discontinuation of virologically suppressive antiretroviral therapy. Clin Infect Dis. 2008;47(3):421–4.

38 Scherrer AU, Boni J, Yerly S, Klimkait T, Aubert V, Furrer H, et al. Long-lasting protection of activity of nucleoside reverse transcriptase inhibitors and protease inhibitors (PIs) by boosted PI containing regimens. PloS One. 2012;7(11):e50307.

39 Villes V, Spire B, Lewden C, Perronne C, Besnier JM, Garre M, et al. The effect of depressive symptoms at ART initiation on HIV clinical progression and mortality: implications in clinical practice. Antivir Ther. 2007;12(7):1067–74.

40 Hogg RS, Heath K, Bangsberg D, Yip B, Press N, O'Shaughnessy MV, et al. Intermittent use of triple-combination therapy is predictive of mortality at baseline and after 1 year of follow-up. AIDS. 2002;16(7):1051–8.

41 Garcia de Olalla P, Knobel H, Carmona A, Guelar A, Lopez-Colomes JL, Cayla JA. Impact of adherence and highly active antiretroviral therapy on survival in HIV-infected patients. J Acquir Immune Defic Syndr. 2002;30(1):105–10.

42 Lima VD, Harrigan R, Bangsberg DR, Hogg RS, Gross R, Yip B, et al. The combined effect of modern highly active antiretroviral therapy regimens and adherence on mortality over time. J Acquir Immune Defic Syndr. 2009;50(5):529–36.

43 Bangsberg DR, Perry S, Charlebois ED, Clark RA, Roberston M, Zolopa AR, et al. Non-adherence to highly active antiretroviral therapy predicts progression to AIDS. AIDS. 2001;15(9):1181–3.

44 Simpson SH, Eurich DT, Majumdar SR, Padwal RS, Tsuyuki RT, Varney J, et al. A meta-analysis of the association between adherence to drug therapy and mortality. BMJ. 2006;333(7557):15.

45 Vernazza PL. HIV in semen: still more to be learned. AIDS ResTher. 2005;2:11.

46 Taylor S, Boffito M, Vernazza PL. Antiretroviral therapy to reduce the sexual transmission of HIV. JHIV Ther. 2003;8(3):55–66.

47 Cohen MS, Chen YQ, McCauley M, Gamble T, Hosseinipour MC, Kumarasamy N, et al. Prevention of HIV-1 infection with early antiretroviral therapy. N Engl J Med. 2011;365(6):493–505.

48 Donnell D, Baeten JM, Kiarie J, Thomas KK, Stevens W, Cohen CR, et al. Heterosexual HIV-1 transmission after initiation of antiretroviral therapy: a prospective cohort analysis. Lancet. 2010;375(9731):2092–8.

49 Weber J, Tatoud R, Fidler S. Postexposure prophylaxis, preexposure prophylaxis or universal test and treat: the strategic use of antiretroviral drugs to prevent HIV acquisition and transmission. AIDS. 2010;24Suppl4:S27–39.

50 Cambiano V, Rodger AJ, Phillips AN. 'Test-and-treat': the end of the HIV epidemic? Curr Opin Infect Dis. 2011;24(1):19–26.

51 Cohen MS, Baden LR. Preexposure prophylaxis for HIV--where do we go from here? N Engl J Med. 2012;367(5):459–61.

52 Thigpen MC, Kebaabetswe PM, Paxton LA, Smith DK, Rose CE, Segolodi TM, et al. Antiretroviral preexposure prophylaxis for heterosexual HIV transmission in Botswana. N Engl J Med. 2012;367(5):423–34.

53 Baeten JM, Donnell D, Ndase P, Mugo NR, Campbell JD, Wangisi J, et al. Antiretroviral prophylaxis for HIV prevention in heterosexual men and women. N Engl J Med. 2012;367(5):399–410.

54 Van Damme L, Corneli A, Ahmed K, Agot K, Lombaard J, Kapiga S, et al. Preexposure prophylaxis for HIV infection among African women. N Engl J Med. 2012;367(5):411–22.

55 MTN statement on decision to discontinue use of tenofovir gel in VOICE, major HIV prevention study in women. Pittsburg: Microbicide Trials Network; [November 25, 2011]. Available from: http://www.mtnstopshiv.org/node/3909.

56 Nichols BE, Boucher CA, van de Vijver DA. HIV testing and antiretroviral treatment strategies for prevention of HIV infection: impact on antiretroviral drug resistance. J Intern Med. 2011;270(6):532–49.

57 Hurt CB, Eron JJ, Jr., Cohen MS. Pre-exposure prophylaxis and antiretroviral resistance: HIV prevention at a cost? Clinical infectious diseases: an official publication of the Infectious Diseases Society of America. 2011;53(12):1265–70.

58 Glass TR, Battegay M, Cavassini M, De GS, Furrer H, Vernazza PL, et al. Longitudinal analysis of patterns and predictors of changes in self-reported adherence to antiretroviral therapy: Swiss HIV Cohort Study. J Acquir Immune Defic Syndr. 2010;54(2):197–203.

59 Knobel H, Urbina O, Gonzalez A, Sorli ML, Montero M, Carmona A, et al. Impact of different patterns of nonadherence on the outcome of highly active antiretroviral therapy in patients with long-term follow-up. HIV Med. 2009;10(6):364–9.

60 Lazo M, Gange SJ, Wilson TE, Anastos K, Ostrow DG, Witt MD, et al. Patterns and predictors of changes in adherence to highly active antiretroviral therapy: longitudinal study of men and women. ClinInfectDis. 2007;45(10):1377–85.

61 Levine AJ, Hinkin CH, Castellon SA, Mason KI, Lam MN, Perkins A, et al. Variations in patterns of highly active antiretroviral therapy (HAART) adherence. AIDS Behav. 2005;9(3):355–62.

62 Kleeberger CA, Buechner J, Palella F, Detels R, Riddler S, Godfrey R, et al. Changes in adherence to highly active antiretroviral therapy medications in the Multicenter AIDS Cohort Study. AIDS. 2004;18(4):683–8.

63 Mannheimer S, Friedland G, Matts J, Child C, Chesney M. The consistency of adherence to antiretroviral therapy predicts biologic outcomes for human immunodeficiency virus-infected persons in clinical trials. Clin Infect Dis. 2002;34(8):1115–21.

64 Chesney MA. The elusive gold standard. Future perspectives for HIV adherence assessment and intervention. J Acquir Immune Defic Syndr. 2006;43 Suppl 1:S149–S55.

65 Berg KM, Arnsten JH. Practical and conceptual challenges in measuring antiretroviral adherence. J Acquir Immune Defic Syndr. 2006;43 Suppl 1:S79–87.

66 Williams AB, Amico KR, Bova C, Womack JA. A proposal for quality standards for measuring medication adherence in research. AIDS and behavior. 2013;17(1):284–97.

67 Di Matteo M, Di Nicola D. Achieving Patient Compliance. New York: Pergamon Press; 1982 1982.

68 Liu H, Golin CE, Miller LG, Hays RD, Beck CK, Sanandaji S, et al. A comparison study of multiple measures of adherence to HIV protease inhibitors. Ann Intern Med. 2001;134(10):968–77.

69 Bulgiba A, Mohammed UY, Chik Z, Lee C, Peramalah D. How well does self-reported adherence fare compared to therapeutic drug monitoring in HAART? Preventive medicine. 2013;57 Suppl:S34–6.

70 Kimmerling M, Wagner G, Ghosh-Dastidar B. Factors associated with accurate self-reported adherence to HIV antiretrovirals. Int JSTD AIDS. 2003;14(4):281–4.

71 Wagner GJ, Rabkin JG. Measuring medication adherence: are missed doses reported more accurately then perfect adherence? AIDS Care. 2000;12(4):405–8.

72 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.

73 Wagner G, Miller LG. Is the influence of social desirability on patients' self-reported adherence overrated? J Acquir Immune Defic Syndr. 2004;35(2):203–4.

74 Belli RF. Inaccuracies in self-reported medication adherence: findings and psychological processes. In: Dunbar-Jacob JE J, Schlenk E, Stilley C, editor. Methodological Issues in the Study of Adherence. Pittsburgh, PA: University of Pittsburgh Press. 2005;p.35–45.

75 Wilson IB, Carter AE, Berg KM. Improving the self-report of HIV antiretroviral medication adherence: is the glass half full or half empty? Curr HIV/AIDS Rep. 2009;6(4):177–86.

76 Simoni JM, Kurth AE, Pearson CR, Pantalone DW, Merrill JO, Frick PA. Self-report measures of antiretroviral therapy adherence: A review with recommendations for HIV research and clinical management. AIDS Behav. 2006;10(3):227–45.

77 Nieuwkerk PT, Oort FJ. Self-reported adherence to antiretroviral therapy for HIV-1 infection and virologic treatment response: a meta-analysis. J Acquir Immune Defic Syndr. 2005;38(4):445–8.

78 Deschamps AE, De GS, Vandamme AM, Bobbaers H, Peetermans WE, Van WE. Diagnostic value of different adherence measures using electronic monitoring and virologic failure as reference standards. AIDS Patient Care STDS. 2008;22(9):735–43.

79 Walsh JC, Mandalia S, Gazzard BG. Responses to a 1 month self-report on adherence to antiretroviral therapy are consistent with electronic data and virological treatment outcome. AIDS. 2002;16(2):269–77.

80 Mannheimer S, Thackeray L, Huppler Hullsiek K, Chesney M, Gardner EM, Wu AW, et al. A randomized comparison of two instruments for measuring self-reported antiretroviral adherence. AIDS Care. 2008;20(2):161–9.

81 Glass TR, De Geest S, Weber R, Vernazza PL, Rickenbach M, Furrer H, et al. Correlates of self-reported nonadherence to antiretroviral therapy in HIV-infected patients: the Swiss HIV Cohort Study. J Acquir Immune Defic Syndr. 2006;41(3):385–92.

82 Glass TR, De GS, Hirschel B, Battegay M, Furrer H, Covassini M, et al. Self-reported non-adherence to antiretroviral therapy repeatedly assessed by two questions predicts treatment failure in virologically suppressed patients. Antivir Ther. 2008;13(1):77–85.

83 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 clinical trials. 2004;5(2):74–9.

84 Oyugi JH, Byakika-Tusiime J, Charlebois ED, Kityo C, Mugerwa R, Mugyenyi P, et al. Multiple validated measures of adherence indicate high levels of adherence to generic HIV antiretroviral therapy in a resource-limited setting. Journal of acquired immune deficiency syndromes. 2004;36(5):1100–2.

85 Chesney MA, Ickovics JR, Chambers DB, Gifford AL, Neidig J, Zwickl B, et al. Self-reported adherence to antiretroviral medications among participants in HIV clinical trials: the AACTG adherence instruments. Patient Care Committee & Adherence Working Group of the Outcomes Committee of the Adult AIDS Clinical Trials Group (AACTG). AIDS Care. 2000;12(3):255–66.

86 Lu M, Safren SA, Skolnik PR, Rogers WH, Coady W, Hardy H, et al. Optimal recall period and response task for self-reported HIV medication adherence. AIDS Behav. 2008;12(1):86–94.

87 Schneider J, Kaplan SH, Greenfield S, Li W, Wilson IB. Better physician-patient relationships are associated with higher reported adherence to antiretroviral therapy in patients with HIV infection. J Gen intern Med. 2004;19(11):1096–103.

88 Krummenacher I, Cavassini M, Bugnon O, Schneider MP. An interdisciplinary HIV-adherence program combining motivational interviewing and electronic antiretroviral drug monitoring. AIDS Care. 2011;23(5):550–61.

89 Krummenacher I, Cavassini M, Bugnon O, Spirig R, Schneider MP, Swiss HIVCS. Antiretroviral adherence program in HIV patients: a feasibility study in the Swiss HIV Cohort Study. Pharmacy world & science: PWS. 2010;32(6):776–86.

90 Glass TR, Furrer H, Schneider MP, De Geest S, Günthard H, Vernazza P, et al. editor. Are once daily regimens really the magic bullet? 5th International Conference on HIV Treatment and Prevention Adherence. 2010 May 30 – June 1; Miami, Florida.

91 Bisson GP, Gross R, Bellamy S, Chittams J, Hislop M, Regensberg L, et al. Pharmacy refill adherence compared with CD4 count changes for monitoring HIV-infected adults on antiretroviral therapy. PLoS medicine. 2008;5(5):e109.

92 Ammassari A, Trotta MP, Murri R, Castelli F, Narciso P, Noto P, et al. Correlates and predictors of adherence to highly active antiretroviral therapy: overview of published literature. J Acquir Immune Defic Syndr. 2002;31 Suppl 3:S123–S7.

93 Amico KR, Harman JJ, Johnson BT. Efficacy of antiretroviral therapy adherence interventions: a research synthesis of trials, 1996 to 2004. J Acquir Immune Defic Syndr. 2006;41(3):285–97.

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