Recent advances in antiretroviral therapy have dramatically reduced hospitalization rates, opportunistic infections, and deaths associated with HIV infection . The objective of the treatment is the lasting suppression of viral replication . Numerous factors may negatively influence the desired therapeutic objectives, such as the stage of the disease, viral strain, a history of previous treatment, baseline viraemia and pharmacokinetic interactions. Among such factors the importance of inadequate adherence to treatment must be highlighted . Adherence to treatment is a potent predictor of effectiveness, both in clinical trials and cohort studies [4–6]. The potential consequences of non-adherence to highly active antiretroviral therapy (HAART) are treatment failure, resistance and cross-resistance, and the transmission of resistant viruses to other patients, thus limiting future therapeutic options, both for the individual and the community [7,8].
Adherence to pharmacological therapy in general has been shown to be low, ranging from 10 to 90% . For patients on HAART, adherence rates to prescribed therapies were found to vary from 40 to 80%, both in clinical trials and clinical practice settings [4–6,10–13]. The measurement of adherence is thus an essential component in anti-HIV therapy. However, there is no ‘gold standard’ when talking about the measurement of adherence. The approaches employed include patient self-report, patient attendance at programmed visits, pill counts, pharmacy records, the measurement of drug levels, biological surrogate markers and the use of the medication-event monitoring system (MEMS cap). However, none are completely accurate, and most are not practical to apply in clinical practice  with the only exception being self-reported measurement.
The measurements may be compared with respect to three attributes: (i) multidimensional adherence measurements versus missed-dose measurements; (ii) the classification of adherence as a continuum (0–100%) versus a dichotomy (adherent/non-adherent) variable; and (iii) the time interval evaluated (weeks versus days). The self-report (self administered or interviewer administered) obtains a patient's subjective evaluation of his or her own level of treatment compliance behaviour.
The advantages of this over other methods of measurement include its simplicity, speed, and viability of use. The disadvantages include both the reliance on recall and social desirability bias, with a tendency to overestimate adherence [14,15]. However, several studies highlighted the usefulness of the self-report as an adherence measurement tool, and showed it to correlate well with the virological outcome [16–18]. A problem with comparative self-report studies is that there is no standardized questionnaire, no standard cut-off value for each different level of adherence, and the time intervals evaluated are inconsistent, making it hard to compare the different adherence ratios .
Therefore, a simplified medication adherence questionnaire (SMAQ) was developed to evaluate a low cost, reliable and easily applicable instrument for measuring adherence. The aim of the present study was to assess the performance of the SMAQ in identifying non-adherent patients, and the association thereof with virological outcomes in a large cohort of HIV-infected patients.
Development of the simplified medication adherence questionnaire
A group of researchers, including physicians, nurses, pharmacists, psychologists and patients, all with experience in antiretroviral treatment and adherence, developed the SMAQ. The questionnaire was based on the Morisky scale , which had previously proved easy to integrate into a standard medical visit. The original scale contained four items: (1) ‘Do you ever forget to take your medicine?'; (2) ‘Are you careless at times about taking your medicine?'; (3) ‘When you feel better, do you sometimes stop taking your medicine?'; (4) ‘If sometimes you feel worse when taking the medicine, do you stop taking it?'.
By consensus, the research group then made the following changes: item 3 was eliminated as many HIV-infected patients are asymptomatic. Item 4 was re-formulated as follows: ‘If at times you feel worse, do you stop taking your medicine?'. Three additional questions were incorporated, with the aim of obtaining more adherence-specific measurements. A modified version of a question used by Samet et al.  to determine the number of missed doses over the previous 24 h was employed.. Although such a limited time frame may enhance the accuracy of patient recall, it may well not reflect the overall trend of patient medication adherence. Therefore, the additional questions were: (a) Thinking about the last week. How often have you not taken your medicine?; (b) Did you not take any of your medicine over the last weekend?; (c) Over the past 3 months, how many days have you not taken any medicine at all?.
The SMAQ was considered ‘positive’ when a non-adherent patient was detected, that is, when there was a positive response to any of the qualitative questions, more than two doses missed over the past week, or over 2 days of total non-medication during the past 3 months.
Evaluation of the performance of the simplified medication adherence questionnaire
The performance of the SMAQ was evaluated in three stages: (i) criterion validity, comparing it with an objective instrument of adherence assessment; (iii) construct validity, analysing the association of adherence, as defined by the SMAQ, and virological outcomes; and (iii) reliability, assessing both the internal consistency and reproducibility of the SMAQ when administered by two independent investigators.
To assess criterion validity we compared the SMAQ with another instrument used to assess adherence. The MEMS (Aardex, Zurich) was used as a standard adherence measurement. The MEMS cap system employs normal medication bottles fitted with a pressure-activated microprocessor in the cap. The microprocessor records each opening and lists the date, time, and duration of opening. The information is then stored in a database. Although the MEMS cap system cannot prove drug intake by the patient, prolonged deception by patients has been shown to be unlikely . The criterion validity assessment was carried out in a subset of 40 patients at the first evaluation (at month 3). The subset consisted of the first 40 patients enrolled at the coordinating centre. The patients were provided with a MEMS cap bottle for each pack of nelfinavir prescribed, and were specifically instructed in their use. Adherence ratios were defined as the number of doses recorded by the MEMS cap divided by the total number of doses prescribed during the monitoring period. Non- adherence, according to MEMS, was defined as when less than 90% of the prescribed doses were recorded.
The association of adherence, as defined by the SMAQ, and the effectiveness of treatment was determined to assess construct validity. Effectiveness was defined as a 1.5 log10/ml reduction in viral load, from a baseline or viral load of less than 500 copies/ml in the month 3 evaluation, or a viral load of less than 500 copies/ml in the month 6 or 12 evaluations. The construct validity assessment was carried out on 2528 (84.15%) of the 3004 patients included in the study.
The reliability of the SMAQ was assessed in two ways: (i) By measuring the internal consistency of the test in 2528 patients. Internal consistency is a measure of how similar the responses to the items in a questionnaire are. The number of items (the more the items, the greater the reliability) bears an influence. So, in the case of a short instrument for use in clinical practice, internal consistency may be compromised thereby; (ii) By measuring the reproducibility of the SMAQ when administered first by a physician and then by a nurse or pharmacist (treatment adherence counsellor; TAC). The SMAQ was administered by both to the patients on the same day (1376 patients). Inter-observer reliability defines the degree of similarity of measurements made by different observers with the same instrument. To minimize the possibility of real clinical change, it is recommended that there be only a short lapse of time between the two measurements.
Patients and development of the study
The Grupo Español para el Estudio Multifactorial de la Adherencia (GEEMA) Study enrolled 3004 non- selected HIV-infected patients who had initiated nelfinavir treatment in combination with other antiretroviral drugs between January 1998 and December 1999. Having initiated nelfinavir therapy was chosen as a criterion for inclusion as, at the time, the drug had only recently been licensed in Spain, thus facilitating the speedy enrollment of patients. The study was prospective, multi-centre (69 hospitals) and nationwide (Spain). All HIV-infected patients in Spain receive antiretroviral medication free of charge.
All patients were monitored when on routine clinical appointments. A structured interview was given, and the SMAQ administered by the patient's usual physician (and by the TAC in a sub-group of patients) at 3, 6 and 12 months from starting the new treatment. Sociodemographic information (age, sex, risk behaviour related to acquiring the infection, etc.), as well as clinical data (CDC classification of HIV infection, CD4 cell count, viral load) were collected. Information about previously prescribed drugs, and the drugs prescribed at the start of the study, including the reasons for starting HAART or changing from previous HAART, was also collected.
The following statistics were computed: the sensitivity of the SMAQ (rate of positive non-adherent patients as per the SMAQ versus true non-adherent patients); specificity (rate of adherent patients as per the SMAQ versus true adherent patients); and positive predictive value (the probability of a patient being truly non-adherent when the test shows him or her to be so). We also calculated the positive likelihood ratio and the corresponding 95% confidence interval (CI) . The standard used for comparison was the MEMS cap measure of adherence.
Either Fisher's exact test or the chi square trend test (Mantel–Haenszel) were used to test the degree of association of categorical variables. The effect of independent variables on viral load suppression (effectiveness) was assessed for the whole cohort, and for the subset of the protease inhibitor (PI)-naive patients, with multiple logistic regression analysis. The independent variables were: sex, age less than 40 years, baseline CD4 T cell count less than 200 × 106/l, baseline viral load greater than 5 log10, PI-experienced patients, and non-adherence as measured by the SMAQ. The dependent variable was: viral load suppression (< 500 copies/ml) after 12 months of HAART.
The internal consistency of the six items of the SMAQ was evaluated by means of Cronbach's alpha coefficient. Cohen's kappa test was used to compare the results the physicians and the TAC obtained using the SMAQ. All the data were processed on SAS statistical analysis software (SAS Institute, Cary, NC, USA). A value of P < 0.05 obtained in a two-tailed test was considered to be statistically significant.
The baseline profile of the 3004 patients included in the study is shown in Table 1. The participants were 72% men and the mean age was 35.8 years. Most had acquired HIV through intravenous drug use (65%). The median CD4 cell count was 270 × 106 cells/l and the median HIV-RNA level was 4.3 log10copies/ml. The educational level of the patients ranged from high school graduates (60%) to patients with no formal education (8%).
A comparison of the non-adherent patients detected by MEMS and by SMAQ among the 40 patients tested at month 3, is shown in Table 2. The percentage of non-adherent patients found by the SMAQ was 37.5%, in comparison with the 45% detected by MEMS. The sensitivity of the SMAQ in detecting non-adherent patients was found to be 72% (95% CI 58–86); specificity, 91% (95% CI 82–100); positive predictive value: 87% (95% CI 76–97); and positive likelihood ratio 7.94 (95% CI 6.44–9.45). The first evaluation of the SMAQ at month 3 incorporated 2528 patients; the reasons for the missing patients were: death: 21 (0.7%); adverse events: 104 (3.5%); progression: 36 (1.2%); and loss to follow-up: 315 (10.5%).
The relationship between the individual items of the SMAQ and the effectiveness of treatment at month 3 is shown in Table 3. Different responses to the items of the SMAQ coincided with different virological outcomes. Not all patients responded to all items and, according to the question, the percentage of patients categorized as non-adherent ranged from 15 to 30%. Defining adherence on the basis of the combined results of all the items, the percentage of non-adherent patients found was 36.6%.
The association of adherence, as measured by the SMAQ, and the virological outcome is shown in Table 4. A total of 1797 patients were evaluated at month 12; 642 were PI-naive, 805 were PI-experienced on salvage therapy, whereas 350 were PI-experienced, but had been changed to nelfinavir after an adverse event while on the previous therapy. Among the PI-naive subset, the results were: percentage of non-adherent patients, 29.4%, viral suppression (< 500 copies/ml) 71.8% [79% for adherent and 54.5% for non-adherent patients, odds ratio (OR) 3.06, 95% CI 2.1–4.5, P = 0.0001]. In the PI-experienced subset on salvage therapy, the results were: percentage of non-adherent patients 33%, viral suppression 39% (59% for adherent and 33% for non-adherent patients, OR 2.9, 95% CI 2.1–4;P = 0.0001).
Table 5 shows the results of the logistic regression analysis that takes viral suppression as the dependent variable. Age, sex, baseline viral load of over 5 log10/ml, and CD4 cell count of less than 200 × 106/l were not found to be significantly related to viral suppression; only non-adherence (OR 1.95; 95% CI 1.32–2.89;P = 0.0007) was associated with failing to achieve viral suppression in the PI-naive subset. However, in the cohort as a whole, the factors associated with failing to achieve viral suppression were: baseline viral load of over 5 log10/ml (OR 1.77; 95% CI 1.36–2.12); CD4 cell count of less than 200 × 106/l (OR 1.39; 95% CI 1.11–1.74); PI-experienced (OR 2.5; 95%CI 1.98–3.17); and non-adherence (OR 1.73; 95% CI 1.4–2.14).
The Cronbach's alpha internal consistency coefficient of the SMAQ was 0.75; 95% CI 0.73–0.76. The inter-observer reliability analysis (physicians and TAC) revealed an overall level of coincidence of 88.2% (kappa 0.74; 95% CI 0.69–0.79) for all patients evaluated at months 3, 6 and 12 by two observers (n = 1376).
The study includes a very large and highly representative sample of Spanish patients who received antiretroviral treatment for HIV. The percentage of men, and the percentage of patients who admitted having used drugs intravenuosly in our study (72 and 65%, respectively) are very similar to those reported in the National AIDS Report (80 and 65%, respectively) .
The SMAQ was compared with MEMS in 40 patients. We found sensitivity to be 72%, specificity 91%, positive predictive value 87%, and a positive likelihood ratio of 7.94. The results suggest that the SMAQ is a valid indicator of a patient's non-adherence to treatment. Although the sample represents only a small part of the total number of patients included in the study, the rate of non-adherence found by the SMAQ (37.5%) is not significantly different to that of the cohort as a whole (36.6%). Electronic measurement (MEMS) offers advantages over subjective or other objective forms of measurement. If used properly the technique provides additional information, beyond the simple number of pills taken ; that is, the time and date of pill bottle openings. Several studies have demonstrated electronic monitoring of adherence to be more sensitive for non-adherence than either pill counts or self-reporting, and that the results obtained by such measurement closely correlate to virological outcome [22,26,27]. The sensitivity of self-reporting, compared with MEMS, ranges from 60 to 80% [27–29]. Compared with an unannounced pill count, the sensitivity of patient self-reporting is 72% , and other self-reporting questionnaires show a sensitivity of 25% when compared with pharmacy pill counts .
Nevertheless, the results obtained by the SMAQ may be ascribed to the high prevalence of non-adherence in the population studied, especially with respect to the positive predictive value. It is likely that the performance of the test would be poorer in settings with better adherence rates. Even in such a favourable situation, the SMAQ was not found to be completely accurate, because it under-diagnosed cases of non-adherence by 28%. Notwithstanding, in our population the post-test probability of being non-adherent with a positive SMAQ was approximately 87% (approximately double the pre-test probability). Additional items, or a lower threshold for non-adherence, would certainly improve the sensitivity of the questionnaire. The SMAQ should be tested further before recommending its use in clinical practice.
Adherence, as measured by the SMAQ, showed a positive association with respect to the virological outcome. The percentage of PI-naive patients who achieved viral suppression was 79% for adherent patients, and 54.5% for non-adherent patients. Among the PI-experienced patients (on salvage therapy) these percentages were 59 and 33%, respectively. This is consistent with other studies that found that self-reported non-adherence was associated with poorer virological outcomes [17,32–36].
Compared with other variables (age, sex, baseline CD4 cell count, baseline viral load), non-adherence, as measured by the SMAQ, was the only significant predictor of virological failure (viral load > 500 copies/ml) at one year, with an odds ratio of 1.9 (95% CI 1.3–2.9) in the PI-naive subset of patients. The factors associated with the patients’ inability to achieve viral suppression in the global cohort were high viral load, low CD4 cell count, PI-experience and non-adherence. A variety of factors can contribute to the failure of antiretroviral therapy to suppress viral replication durably; viral resistance, potency of the regimen and pharmacokinetics should be added to the above mentioned factors . The results are comparable to those of other studies [18,26,33,38–40] using different, in general more complicated and more difficult to implement, tools to assess adherence, and highlight the usefulness of adherence measurement for the monitoring of HIV treatment.
The SMAQ showed sufficient internal consistency (Cronbach's alpha 0.75) and satisfactory reproducibility when tested by two different health providers (overall agreement of 88.2%, kappa 0.74). Such strict reliability criteria have not been reported by previous studies.
Multidimensional adherence measures usually apply a scale that is believed to reflect the dimensions of adherence/non-adherence. The missed-dose method is simpler; adherence is usually calculated as a percentage discrepancy score [(prescribed doses − missed doses)/(prescribed doses)]. The discordance of the different measures of self-reported adherence was highlighted by Gao and Nau , who studied 65 HIV patients with three different self-reporting methods. The investigators found the percentage of adherent patients not to be congruent: 29.2% with a Morisky-type scale, 78.5% if adherence is defined as the percentage of doses taken as prescribed over the past 2 days, and 95.4% over the past 2 weeks, with a cut-off value of 90%. Chesney et al.  developed a self-report instrument for use with Adult AIDS Clinical Trials. Of the 75 patients evaluated, 11% reported missing at least one dose the day before the interview, and 17% reported missing at least one dose during the previous 2 days; the test was self-administered to patients who had at least a sixth-grade level reading ability. The SMAQ integrates multidimensional and missed-dose measures; because the level of adherence required to achieve the greatest benefit in HIV infection is very high , a dichotomous adherent/non-adherent variable would appear to be valid. The cut-off value of 90–95% of prescribed doses, employed in the present study to distinguish adherence and non-adherence, was adopted by other researchers working in the area of HIV infection [12,26,31,41,43]. The SMAQ asks patients to indicate the number of missed doses over the past week, the past weekend, and the number of days without any medication at all over the past 3 months. Such evaluation is more likely to reflect the overall trend in patient medication adherence. The limitations of the test include recall and social desirability bias, common problems in all self-report surveys.
Recently, Liu et al.  demonstrated that three adherence measures (MEMS, pill counts, and interview) all have shortcomings that may be reduced by employing a combined measurement system. However, such a comprehensive adherence measure may prove unrealistic for application in clinical care and, in spite of flaws and errors, patient interview remains the most practical approach for clinicians . It is important to highlight that the SMAQ performed similarly to other more sophisticated adherence assessment tools.
The SMAQ may prove to be an adequate instrument for the assessment of adherence among HIV-infected patients; it shows adequate levels of sensitivity and specificity when compared with other more objective measures; it is reliable, showing sufficient internal consistency and reproducibility, easy to apply (under 5 min), inexpensive, and the results found correlate strongly with the virological outcome. It is, therefore, an instrument that may be used in the majority of clinical settings.
The authors gratefully acknowledge the contributions of Susana Traseira, Medical Manager (Roche, Spain), of the operational and coordination tasks of the GEEMA group, and José Javier García (CIBEST) for statistical advice.
1. Palella FJ, Delaney KM, Morman AC, Loveless MO, Fuhrer J, Satten GA. Declining morbidity and mortality among patients with advanced human immunodeficiency virus infection. HIV Outpatient Study Investigators.
N Engl J Med 1998, 338: 853–860.
2. Carpenter CCJ, Cooper DA, Fischl MA. et al
. Antiretroviral therapy in adults. Updated recommendations of the International AIDS Society – USA Panel.
JAMA 2000, 3: 381–391.
3. Williams A, Friedland G. Adherence, compliance, and HAART. AIDS Clin Care 1997, 9: 51–58.
4. Montaner JS, Reiss P, Cooper D. et al
. A randomized, double-blind trial comparing combinations of nevirapine, didanosine, and zidovudine for HIV-infected patients: the INCAS Trial. Italy, the Netherlands, Canada and Australia Study.
JAMA 1998, 279: 930–937.
5. Kaufmann D, Pantaleo G, Sudre P, Telenti A. CD4-cell count in HIV-1 infected individuals remaining viraemic with highly active antirretroviral therapy (HAART). Lancet 1998, 351: 723–724.
6. Fatkenheur G, Theisen A, Rockstroh J. et al
. Virological treatment failure of protease inhibitor therapy in an unselected cohort of HIV-infected patients. AIDS 1997, 11: F113–F116.
7. Cohen OJ, Fauci AS. Transmission of multidrug-resistant human immunodeficiency virus. The wake-up call.
N Engl J Med 1998, 339: 341–343.
8. Wainberg MA, Friedland GH. Public health implications of antiretroviral therapy and HIV drug resistance. JAMA 1998, 279: 1977–1983.
9. Sackett DL, Snow JC. The magnitude of compliance and non-compliance.
In:Compliance with therapeutic regimens.
Sackett DL, Haynes RB (editors). Baltimore: Johns Hopkins University Press; 1976. pp. 11–27.
10. Rodríguez-Rosado R, Jiménez-Nacher I, Soriano V, Anton P, Gonzalez-Lahoz J. Virological failure and adherence to antiretroviral therapy in HIV-infected patients. AIDS 1998, 12: 1112.1112.
11. López-Suárez A, del Álamo Fernández-Gutiérrez, Pérez Guzmán E, Girón-González JA. Adherence to the antiretroviral treatment in asymptomatic HIV-infected patients. AIDS 1998, 12: 685–686.
12. Tuldrà A, Ferrer MJ, R Fumaz C. et al
. Monitoring adherence to HIV-therapy. Arch Intern Med 1999, 159: 1376–1377.
13. Gallant JE, Block DS. Adherence to antiretroviral regimens in HIV-infected patients: results of a survey among physicians and patients. J Int Assoc Physician AIDS Care 1998, 4: 32–35.
14. Miller LG, Hays RD. Measuring adherence to antiretroviral medications in clinical trials. HIV Clin Trials 2000, 1: 36–46.
15. Rudd P. The measurement of compliance medication taking.
In:Developmental aspects of health compliance behavior.
Krasnegor NA, Epstein L, Johnson SB, Yaffe SJ (editors). Hilllsdale, NJ: Lawrence Erlbaum Associates; 1993. pp. 185–213.
16. Chesney MA, Ickovics J, Hecht FM, Sikipa G, Rabkin J. Adherence: a necessity for successful HIV combination therapy. AIDS 1999, 13 (Suppl. A) : S271–S278.
17. De Masi R, Tolson J, Pham S, et al
. Self-reported adherence to HAART and correlation with HIV RNA: initial results with the Patient Medication Adherence Questionnaire.
In:6th Conference on Retroviruses and Opportunistic Infections
. Chicago. January–February 1999 [Abstract 94].
18. Haubrich RH, Little SJ, Currier JS. et al
. The value of patient-reported adherence to antiretroviral therapy in predicting virologic and immunologic response. AIDS 1999, 13: 1099–1107.
19. Cinti SK. Adherence to antiretrovirals in HIV disease. AIDS Reader 2000, 10: 709–717.
20. Morisky DE, Green LW, Levine DM. Concurrent and predictive validity of a self-reported measure of medication adherence. Med Care 1986, 24: 67–74.
21. Samet JH, Libman H, Steger KA. et al
. Compliance with zidovudine therapy in patients infected with human immunodeficiency virus type 1: a cross-sectional study in a municipal hospital clinic. Am J Med 1992, 92: 495–502.
22. Kastrissios H, Suarez JR, Katzenstein D, Girard P, Sheiner LB, Blaschke TF. Characterising patterns of drug-taking behaviour with a multiple drug regimen in an AIDS clinical trial. AIDS 1998, 12: 2295–2303.
23. Sackett DL, Richardson WS, Rosenberg W, Haynes B. Evidence-based medicine: how to practice and teach EBM.
London: Churchill Livingstone; 1996.
24. Vigilancia Epidemiológica del SIDA en España. Centro Nacional de Estadística. Ministerio de Sanidad y Consumo. Informe semestral no. 2; 2000.
25. Cramer JA. Microelectronic systems for monitoring and enhancing patient compliance with medication regimens. Drugs 1995, 49: 321–327.
26. Paterson DL, Swindells S, Mohr J. et al
. Adherence to protease inhibitor therapy and outcomes in patients with HIV infection. Ann Intern Med 2000, 133: 21–30.
27. Arnsten JH, Demas PA, Farzadegan H. et al
. Antiretroviral therapy adherence and viral suppression in HIV-infected drug users: comparison of self-report and electronic monitoring. Clin Infect Dis 2001, 33: 1417–1423.
28. Melbourne KM, Gelekto SM, Brown SL. et al
. Medication adherence in patients with HIV infection: a comparison of two measurement methods
. AIDS Reader 1999, 9: 329–338.
29. Miller L, Liu H, Beck K, et al
. Providers’ estimates of adherence overestimate reports from Medication Event Monitoring System (MEMS) for patients on protease inhibitors (PIs).
In:6th Conference on Retroviruses and Opportunistic Infections
. Chicago, February 1999 [Abstract 97].
30. Bangsberg DR, Hecht FM, Clague H. et al
. Provider assesment of adherence to HIV antiretroviral therapy. J Acquir Immune Defic Syndr 2001, 26: 435–442.
31. Martín J, Escobar I, Rubio R. et al
. Study of the validity of a questionnaire to assess the adherence to therapy in patients infected by HIV. HIV Clin Trials 2001, 2: 31–37.
32. Bangsberg DR, Hech FM, Charlebois EC, et al
. Spontaneous adherence audits predict viral suppression in the REACH cohort.
In:6th Conference on Retroviruses and Opportunistic Infections
. Chicago, February 1999 [Abstract 93].
33. Duong M, Piroth L, Peytavin G. et al
. Value of patient self-report and plasma human immunodeficiency virus protease inhibitor level as markers of adherence to antiretroviral therapy: relationship to virologic response. Clin Infect Dis 2001, 33: 386–392.
34. Murri R, Ammassari A, Gallicano K. et al
. Patient-reported nonadherence to HAART is related to protease inhibitor levels. J Acquir Immune Defic Syndr 2000, 24: 123–128.
35. Le Moing V, Chene G, Carrieri MP. et al
. Clinical, biologic, and behavioral predictors of early immunologic and virologic response in HIV-infected patients initiating protease inhibitors. J Acquir Immune Defic Syndr 2001, 27: 372–376.
36. Knobel H, Carmona A, Grau S. et al
. Adherence and effectiveness of highly active antiretroviral therapy. Arch Intern Med 1998, 158: 1953.1953.
37. Deeks SG. Determinants of virologic response to antiretroviral therapy: implications for long-term strategies. Clin Infect Dis 2000, 30 (Suppl. 2) : S177–S184.
38. Bansberg 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: 357–366.
39. Nieuwkerk PT, Sprangers MAG, Burger DM, Hoetelmans RMW. et al
. Limited patient adherence of highly active antiretroviral therapy for HIV-1 infection in an observational cohort study. Arch Intern Med 2001, 161: 1962–1968.
40. Knobel H, Guelar A, Carmona A. et al
. Virologic outcome and predictors of virological failure on highly active antiretroviral therapy containing protease inhibitors in a cohort of HIV-infected patients. AIDS Patient Care STDs 2001, 15: 193–199.
41. Gao X, Nau DP. Congruence of three self-report measures of medication adherence among HIV patients. Ann Pharmacother 2000, 34: 1117–1122.
42. Chesney MA, Ickoviks JR, Chambers DB. et al
. Self-reported adherence to antiretroviral medications among participants in HIV clinical trials: the AACTG adherence instruments. AIDS Care 2000, 12: 255–266.
43. Tseng AL. Compliance issues in the treatment of HIV infection. Am J Health Syst Pharm 1998, 55: 1817–1824.
44. 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: 968–977.
45. Turner BJ, Hecht FM. Improving on a coin toss to predict patient adherence to medications. Ann Intern Med 2001, 134: 1004–1006.
Investigators of the GEEMA Study: Teresa Vázquez Castañón, Hospital Alvarez Buylla, Asturias; Ana Mariño Callejo, Hospital Arquitecto Marcide-Novoa Santos, La Coruña; Daniel Podzamczer Palter, Hospital Bellvitge, Barcelona; Ramón Canet, Hospital Can Misses, Ibiza; José Manuel Antunez Galvez, Hospital Carlos Haya, Málaga; Ma Victoria Gordillo, Hospital Carlos III, Madrid; Víctor Roca Arbones, Hospital Clínico San Carlos, Madrid; Luis Force, Hospital Consorcio Sanitario de Mataró, Barcelona; Jordi de Otero, Hospital Creu Roja, Barcelona; Isabel Gracia Marce, Hospital Creu Roja, Hospitalet, Barcelona; Ma José López Alvarez, Hospital de Calde, Lugo; José Luis Mostaza Fernández, Hospital del Bierzo, León; Hernando Knobel, Hospital del Mar, Barcelona; Luis Morano Amado, Hospital do Meixoeiro, Pontevedra; Josep Cucurull, Hospital Figueres, Gerona; Carlos Tornero Estébanez, Hospital Francesc de Borja, Gandia, Valencia; Julio Collazos, Hospital Galdakano, Vizcaya; Elisa Martínez Alfaro, Hospital General de Albacete, Albacete; Luis Caminal Montero, Hospital General de Asturias, Asturias; Jordi Uso Blasco, Hospital General de Castellón, Castellón; Elena Losada, Hospital General de Galicia, Santiago, Coruña; Enric Pedrol, Hospital General de Granollers, Barcelona; Manuel Rodríguez Zapata, Hospital General de Guadalajara, Guadalajara; Ester Dorca, Hospital General de Manresa, Barcelona; Alfredo Cano Sánchez, Hospital General de Murcia, Murcia; Josep Vilaró, Hospital General de Vic, Barcelona; Juan F. Lorenzo, Hospital General Yagüe, Burgos; Ma Luisa García-Alcalde, Hospital de Cabueñes, Asturias; Ignacio Suárez Lozano, Hospital Infanta Elena, Huelva; Javier Juega Puig, Hospital Juan Canalejo, La Coruña; José Joaquín Peraire Forner, Hospital Juan XXIII (Universitari Rovira I Virgili – Institut de Estudis Avançat), Tarragona; Pepe López Aldeguer, Hospital La Fe, Valencia; Juan González García, Hospital La Paz, Madrid; Francisco Pasquau Liaño, Hospital Marina Baixa, Villajoyosa, Alicante; Carmen Fariñas Alvarez, Hospital Marques de Valdecilla, Santander; Rafael Ojea de Castro, Hospital Montecelo, Pontevedra; Carlos Barros Aguado, Hospital de Móstoles, Madrid; David Dalmau, Hospital Mutua de Tarrasa, Barcelona; José A. Iribarren, Hospital Ntra. Sra. de Aránzazu, Guipúzcoa; Fernando Marcos Sánchez, Hospital Ntra. Sra. del Prado, Toledo; Eva León Jiménez, Hospital Ntra. Sra. de Valme, Sevilla; Manuel Cervantes, Hospital Parc Tauli, Barcelona; Manuel Camba Esteve, Hospital Policlinico Vigo, Pontevedra; Alberto Arranz Caso, Hospital Príncipe de Asturias, Madrid; Ricardo Rodríguez Real, Hospital Provincial Rebullón, Pontevedra; Joan Colomer, Hospital Provincial Sta. Caterina, Gerona; Teodoro Martín Jiménez, Hospital Puerta de Hierro, Madrid; Eugenio Pérez Guzmán, Hospital Puerta del Mar, Cádiz; Antonio Vergara de Campos, Hospital Puerto Real, Cádiz; José Luis Casado Osorio, Hospital Ramón y Cajal, Madrid; José Ma Kindelan Jaquotot, Hospital Reina Sofía, Córdoba; Ma José Tuya Moran, Hospital San Agustín, Asturias; José Ma Cuadrado Pastor, Hospital San Juan, Alicante; Antonio Delegido Sánchez, Hospital Sant Pau I Santa Tecla, Tarragona; Pere Domingo Pedrol, Hospital Sant Pau, Barcelona; Raúl Rodríguez Pérez, Hospital Santa María Nai- Cabaleiro Goas, Orense; Alberto Terrón Pernia, Hospital Sas de Jerez, Cádiz; Joseba Portu, Hospital Txagorritxu, Vitoria; Víctor Carcaba Fernández, Hospital Valle del Nalón, Asturias; Isabel Ruiz Camps, Hospital Valle Hebrón, Barcelona; Ismael Piñas Forcadell, Hospital Verge de la Cinta, Tarragona; Eduardo Rodríguez de Castro, Hospital Verge del Toro, Menorca; Paloma Geijo, Hospital Virgen de la Luz, Cuenca; Fernando Cuadra García-Tenorio, Hospital Virgen de la Salud, Toledo; Manuel Marquez Solero, Hospital Virgen de la Victoria, Málaga; Carlos Galera Peñaranda, Hospital Virgen de la Arrixaca, Murcia; Miguel Angel Colmenero Camacho, Hospital Virgen de la Macarena, Sevilla; José Adolfo García Henarejos, Hospital Virgen del Rosell, Murcia; Antonio Ocampo, Hospital Xeral Xies, Vigo.
Treatment adherence counsellors: Josefina Cardona, Hospital Can Misses, Ibiza; Francisca Cordero, Hospital Carlos Haya, Málaga; Beatriz Wolgeschafen Torres, Hospital Carlos III, Madrid; Ma José Gámir Pérez, Hospital Clínico San Carlos, Madrid; Visi Jiménez, Hospital Creu Roja, Hospitalet, Barcelona; Alexia Carmona, Hospital del Mar, Barcelona; Rosa Soler Arnau, Hospital General De Granollers, Barcelona; José Domingo Pedreira Andrade, Hospital Juan Canalejo, Coruña; Emilio Monte Boquet, Hospital La Fe, Valencia; Emilia Condes Moreno, Hospital de Mostoles, Madrid; María Sanjaume, Hospital Mutua de Tarrasa, Barcelona; Adoración Torres, Hospital Parc Tauli, Barcelona; Rosario García Juarez, Hospital Puerta del Mar, Cádiz; Ma de los Angeles Martín Martín, Hospital Puerto Real, Cádiz; Raquel Sabido, Hospital Ramón y Cajal, Madrid; Aureliana Segador Gómez, Hospital Reina Sofía, Córdoba; Angels Fontanet, Hospital Sant Pau, Barcelona; Ma de los Angeles Muñoz Arenillas, Hospital Sas de Jerez, Cádiz; Rosa López, Hospital Valle Hebrón, Barcelona; Isabel Domínguez, Hospital Virgen de la Victoria, Málaga; Carmen Buendia, Hospital Virgen del Rosell, Murcia.