Evaluation of adherence to tenofovir treatment by hiv patients using drug concentrations in urine and standardized questionnaires

Abstract

Adherence to tenofovir-based antiretroviral therapy is crucial for treatment success. In this study, we evaluated tenofovir urine concentrations in a cohort of patients that answered standardized adherence questionnaires Morisky-Green and Brief Medication Questionnaire (BMQ). Adherence evaluations were related to the patients’ viral load. Among the 72 patients who completed the questionnaires, 70 provided urine samples, and 88.6% of them had an undetectable viral load. Among the patients who provided urine samples and completed the Morisky-Green questionnaire, 45.7% were categorized as having high adherence, 54.3% as medium adherence, and 2.9% as low adherence. Utilizing a ROC curve (area under the curve of 0.864, CI 95% 0.757-0.971), a tenofovir urinary concentration of 6288.5 ng/mL was established as the cutoff value to predict high adherence according to the BMQ. This cutoff demonstrated a sensitivity of 93% and specificity of 72% in predicting high adherence according to the BMQ, with 73.5% of patients enrolled in the study categorized as having high adherence. When comparing adherence levels determined by the BMQ and urinary concentration, a moderate kappa index was observed (0.677, p<0.01). The results suggest that urine tenofovir concentration measurement as a feasible and efficient strategy to monitor adherence during HIV treatment with this drug.

Keywords:
Tenofovir; HIV; Adherence; Tenofovir urine concentrations

INTRODUCTION

In 2022, it was estimated that approximately 39 million people were living with HIV (Human Immunodeficiency Virus), and out of these, only about 29.8 million people had access to antiretroviral therapy (UNAIDS, 2020). In Brazil, the pharmacological treatment of HIV infection follows the guidelines provided by the Clinical Protocol and Therapeutic Guidelines of the Ministry of Health, which consider the age and individual needs of each patient (Ministério da Saúde, 2024). Most treatment regimens consist of combined pills, typically a tablet containing 300 mg of tenofovir and 300 mg of lamivudine, combined with a 50 mg tablet of dolutegravir. This combination of anti- HIV drugs with different mechanisms of action aims to improve therapy outcomes, reducing both mortality and morbidity associated with HIV, lowering plasma viral RNA levels, and preventing viral transmission (Mugyenyi, 2004).

Tenofovir disoproxil fumarate (TDF) is a prodrug of tenofovir and is commonly included in most anti- HIV treatment regimens in Brazil. This drug exhibits well-established antiviral activity, but it is also associated with significant adverse effects, such as nephrotoxicity (Fernandez-Fernandez et al., 2011). The active metabolite of tenofovir, tenofovir diphosphate, inhibits the HIV-1 reverse transcriptase process by competing with the natural substrate deoxyadenosine 5'-triphosphate (Baheti et al., 2011). Once incorporated into the DNA chain, it disrupts the replication cycle of the virus, suppressing viral replication (Kearney, Flaherty, Shah, 2004).

In the realm of HIV pharmacotherapy, assessing medication adherence is paramount, as low adherence can lead to adverse outcomes, including elevated viral load, emergence of drug resistance, and progression of the disease (Rong, Feng, Perelson, 2007; Masikini, Mpondo, 2015). Conversely, patients demonstrating strong adherence to their prescribed treatment can successfully manage the disease, often achieving an undetectable viral load. It has been noted that when the viral load is undetectable, the risk of transmission is markedly diminished, and individuals in this state are considered non-transmissible (Siedner, Triant, 2019).

Given the importance of assessing medication adherence in the treatment of chronic diseases, numerous self-reported adherence questionnaires have been proposed (Nassar, Basheti, Saini, 2022). However, it is essential to recognize that self-reporting may be influenced by the patient's perception and the inclination to provide responses that align with healthcare professionals' expectations (Stirratt et al., 2015). Alternatively, several studies have explored the correlation between urinary concentrations of tenofovir and patient adherence to treatment. These studies have effectively estimated the timing of the patient's last dose by analyzing tenofovir concentrations in urine samples. Urinary concentrations exceeding 1000 ng/ mL indicate medication ingestion within the past 24 hours, while concentrations below 10 ng/mL suggest that the patient has not taken the medication for seven days or more (Koenig et al., 2017a; Lalley-Chareczko et al., 2020). This relationship between the last dose and urinary concentration is valuable for evaluating patient adherence, representing a more objective criterion compared to conventional methods like self-reporting and pill counting. Thus, urine collection provides a non-invasive and straightforward option for monitoring adherence, demonstrating promising and practical results for patient management (Moorthy et al., 2019).

Considering the aforementioned points, the objective of this study was to evaluate the feasibility of using tenofovir urine concentrations as an indicator of adherence and clinical response in HIV pharmacotherapy, comparing them with validated adherence questionnaires.

MATERIAL AND METHODS

Inclusion criteria and urine sample collection

The study received approval from the Research Ethics Committee of Feevale University (approval #5,448,391, approval date 06/03/2022). The cohort was formed through convenience sampling and consisted of patients undergoing treatment with tenofovir for HIV. Inclusion criteria comprised individuals aged 18 years and older, with a viral load result obtained within the last six months and undergoing HIV pharmacological treatment with tenofovir for a minimum of six months. Patient use of tenofovir was tracked by verifying the medication's dispensing through SICLOM (Sistema de Controle de Logística de Medicamentos). Spot urine samples were gathered, and interviews were conducted with patients at two HIV treatment reference centers located in the Brazilian cities of Novo Hamburgo and Sapiranga, spanning from July 2022 to April 2023. Patients who either did not respond to the questionnaire or failed to provide a urine sample were excluded from the study. No specific preparation was required from the patients for urine collection. Participation invitations were extended to patients either when their medications were dispensed or when their blood was drawn to viral load testing. Urine samples were subsequently collected within 24 hours of the expected time of medication intake, with a minimum volume of 10 mL. The samples were refrigerated immediately after collection and, within 2 hours, stored at -20 °C until analysis.

Determination of tenofovir concentrations in urine

Urinary tenofovir concentrations were measured using liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) according to Simiele et al., (2015) with minor modifications. The collected urine samples were centrifuged, and the supernatant was diluted at a 1:10 ratio (v/v) with a 0.1% formic acid in purified water, homogenized, and centrifuged at 10,000 g for 5 minutes at 4°C. Afterwards, the supernatant was transferred to an autosampler vial and a 2 µL aliquot was injected into an Acquity I-Class liquid chromatography system associated with a Xevo TQD triple quadrupole mass spectrometer. Chromatographic separation was performed on an Acquity HSS T3 column (100 x 2.1 mm, 1.7 µm). Mobile phase A was composed of purified water with 0.1% formic acid and mobile phase B was composed of acetonitrile with 0.1% formic acid. Elution was performed in gradient mode, with an initial mobile phase composed of 98% mobile phase A, maintained for 2 minutes, followed by a linear gradient to 70% A in 3.5 minutes, followed by a new linear gradient to 30% of A in 4 minutes. This condition was maintained until 4.5 min, with the return to initial conditions in 4.6 min. The mobile phase flow rate was 0.4 mL/min, and the column was maintained at 30°C. Tenofovir was detected by electrospray ionization in positive mode. The operating conditions of the mass spectrometer were capillary voltage of 5 kV, cone voltage of 50 V, source temperature of 250 °C, desolvation gas flow of 1000 L/h and curtain gas flow of 40 L/h. The monitored mass transitions were 288/136 (quantification) and 288/176 (qualification), with a collision energy of 25 V. The assay was linear between 10 and 50000 ng/mL. Intra- assay precision was 2.64-4.56%, intra-assay precision was 2.33-5.15%, and accuracy was 94.97-103.27%. The matrix effect, tested in the urine of 10 volunteers, ranged from -11.9 to 13%.

Patient interview

After signing an informed consent, participants were directed to a private room where they had access to a computer with internet to answer a series of socioeconomic questions, including: gender, education level, age, whether they were healthcare professionals and, if so, whether the infection was occupational, date of diagnosis, year of treatment initiation, frequency of viral load tests and the latest available result, whether they still had symptoms, whether they had changed medications and, if so, the reason for the change, whether they had interrupted treatment and, if so, whether it was due to a lack of medication in the SUS, whether they experienced adverse effects, what time they took their medication and whether they had changed that time. Additionally, they completed the Morisky-Green and Brief Medication Questionnaires, which will be presented below.

Morisky-Green therapeutic adherence questionnaire

We utilized the Morisky-Green questionnaire, which had been adapted and validated in Brazilian Portuguese (Ben et al., 2012). This questionnaire comprises four questions that patients answer with either 'yes' or 'no.' A score is assigned for each response, with 'yes' receiving one point and 'no' receiving zero points. Initially designed to assess therapeutic adherence in patients with hypertension, it is now widely employed for evaluating adherence across various medical conditions. Based on the total score, patients are categorized into three levels of adherence: high (0 points), medium (1-2 points), and low (3-4 points). For statistical analyses, patients with medium and low adherence were combined into one group for comparison with the high adherence group.

Brief Medication Questionnaire

The validated Brief Medication Questionnaire (BMQ) in Brazilian Portuguese was employed in this study (Ben et al., 2012). The BMQ focuses on the medications in use, their dosages, and is divided into three parts: 1) identification of potential barriers to adherence to the treatment regimen; 2) the patient's beliefs regarding the treatment's effectiveness; and 3) identification of any difficulties in remembering to take the medication. Adherence is assessed based on the scores obtained in these three areas. If any of the scores are equal to or higher than one, it indicates a potential for non-adherence to the treatment. Additionally, adherence is evaluated based on the total score of the questionnaire. A lack of positive answers suggests high adherence, two positive answers suggest probable low adherence, and three or more positive answers indicate low adherence. Similar to the Morisky-Green test, patients who presented any barrier to adherence were regrouped in the same category for comparison with patients adhering to the treatment.

HIV viral load

The individual HIV viral load data of the patients were retrieved from the SICLOM website, maintained by the Ministry of Health of Brazil. These results were then linked to the questionnaire responses based on their corresponding patient numbers. According to the classification provided on the website, patients were divided into two groups: undetectable and detectable viral load. The undetectable viral load group comprised patients with a viral load of <50 copies/mL. The detectable viral load group was further subdivided into two subgroups: values between 50 and 1000 copies/mL were reported as raw data, while values exceeding 1000 copies/mL were recorded as >1000 copies/mL.

Statistical analysis

Categorical variables were presented as frequency (N) and percentage (%). The normality of the data was assessed using the Shapiro-Wilk test. Correlation analysis was conducted to examine the relationship between tenofovir concentrations in urine using Pearson correlation. Urinary tenofovir levels were compared among groups of adherence, gender, and HIV viral load using Mann-Whitney or Kruskal-Wallis tests. Receiver- operator curves (ROC) curves were generated to assess the predictive ability of tenofovir urine concentrations for detecting adherence as determined by the Morisky- Green and BMQ questionnaires. Categorical variables were associated using Chi-square or Fisher's exact tests, and diagnostic agreement was evaluated by the Kappa coefficient. Statistical analysis was performed using SPSS 29.0 (IBM, New York, USA). A P-value of ≤ 0.05 was considered statistically significant.

RESULTS AND DISCUSSION

A total of 72 patients initially participated in the study. However, two patients did not provide urine samples and were consequently excluded from the analysis. Therefore, the final analysis included 70 valid participants. The average age of the participants was 42.4 years, with a minimum age of 18 and a maximum of 65 years. Among the respondents, 36 (51.4%) were male. The respondents' education levels varied significantly, with the majority (n=34) having studied up to 7 years (48.6%). Eighteen respondents had studied between 8 and 11 years (25.7%), and 17 patients had completed more than 12 years of education (24.3%). Only one respondent (1.4%) had studied for only one year (Table I).

Regarding treatment, the majority of patients commenced treatment shortly after diagnosis. However, there are variations in these numbers over the years, reflecting increased awareness of early treatment. Between 1991 and 2000, 7 patients (10%) were diagnosed with infection, but only 1 (1.4%) initiated treatment promptly. From 2001 to 2010, 18 patients (25.7%) were diagnosed, and 20 (28.6%) started treatment, including some who discovered their infection in the previous decade. In the period from 2011 to 2020, patients from other decades who were not on treatment finally began their treatment. Therefore, in addition to the 37 (52.9%) who discovered their infection, 41 (58.6%) initiated treatment. The remaining 8 participants (11.4%) were diagnosed between 2021 and 2022, and all of them promptly began treatment after diagnosis. The same behavioral profile was identified in both genders. This distribution can also be attributed to the increased availability of information about the infection in recent years, along with health education campaigns in Brazil.

As the standard treatment, the most prescribed regimen among the respondents was a combination tablet of Tenofovir 300 mg + Lamivudine 300 mg with a tablet of Dolutegravir 50 mg (74.3%). Others reported using different drug combinations, including Efavirenz 600 mg + Tenofovir 300 mg + Lamivudine 300 mg (12.9%); Tenofovir 300 mg + Lamivudine 300 mg + Ritonavir 100 mg + Darunavir 600 mg (4.3%); and Tenofovir 300 mg + Lamivudine 300 mg + Ritonavir 100 mg + Atazanavir 300 mg (2.9%). Finally, 5.7% were unable to provide information about the medications they use. Among the 70 interviewees, only 20% claimed to experience side effects from the medications.

TABLE I
Characterization of patients

Groups	Total	Gender
		Male	Female
	N = 70 (100.0%)	36 (51.4%)	34 (48.6%)
School years
1 to 3	1 (1.4%)	0 (0%)	1 (100%)
4 to 7	34 (48.6%)	15 (44.1)	19 (55.9%)
8 to 11	18 (25.7%)	11 (61.1)	7 (38.9%)
12 or more	17 (24.3%)	10 (58.8)	7 (41.2%)
Year of diagnosis
1991 to 2000	7 (10.0%)	4 (57.1%)	3 (42.9%)
2001 to 2010	18 (25.7%)	6 (33.3%)	12 (66.7%)
2011 to 2020	37 (52.9%)	21 (56.8%)	16 (43.2%)
2021 to 2022	8 (11.4%)	5 (62.5%)	3 (37.5%)
Year of beginning of HIV treatment
1991 to 2000	1 (1.4%)	1 (100.0%)	0 (0.0%)
2001 to 2010	20 (28.6%)	7 (35.0%)	13 (65.0%)
2011 to 2020	41 (58.6%)	23 (56.1%)	18 (43.9%)
2021 to 2022	8 (11.4%)	5 (62.5%)	3 (37.5%)
HIV pharmacotherapy
Tenofovir 300mg + Lamivudine 300mg (2-in-1 treatment) + Dolutegravir 50mg	52 (74%)	27 (51.9%)	25 (48.1%)
Tenofovir 300mg + Lamivudine 300mg + Efavirenz 600mg	9 (12.9%)	5 (55.6%)	4 (44.4%)
Tenofovir 300mg + Lamivudine 300mg + Ritonavir 100mg + Darunavir 600mg	3 (4.3%)	1 (33.3%)	2 (66.7%)
Tenofovir 300mg + Lamivudine 300mg + Ritonavir 100mg + Atazanavir 300mg	2 (2.9%)	0 (0.0%)	2 (100.0%)
Didn’t know	4 (5.7%)	3 (75.0%)	1 (25.0%)
HIV viral load
Undetectable (<50 copies/mL)	62 (88.6%)	32 (51.6%)	30 (48.4%)
50 e 1000 copies/mL	2 (2.9%)	0 (0.0%)	2 (100.0%)
>1000 copies/mL	6 (8.6%)	4 (66.7%)	2 (33.3%)
Adherence by Morisky Green
High	32 (45.7%)	21 (65.6%)	11 (34.4%)
Medium	36 (51.4%)	14 (38.9%%)	22 (61.1%)
Low	2 (2.9%)	1 (50.0%)	1 (50.0%)
Adherence by BMQ
Adherent	48 (68.6%)	28 (58.3%)	20 (41.7%)
Adhesion barrier	22 (31.4%)	8 (36.4%)	14 (63.6%)

The tenofovir urine concentrations, HIV viral load, and adherence scores obtained through standardized questionnaires from the study volunteers are presented in Table II. Tenofovir concentration results had a median of 14,363.5 ng/mL, ranging from a minimum detected concentration of 60.5 ng/mL to a maximum of 66,428.5 ng/mL. Tenofovir was not detected in the urine samples from two patients. The viral load of 88.6% of patients was undetectable, indicating successful viral suppression as the treatment goal. In 2.9% of patients, the viral load ranged between 50 and 1000 copies/mL, while the remaining 8.6% had viral load results above 1000 copies/mL.

In the Morisky-Green questionnaire, out of the 70 patients assessed, 45.7% were categorized as having high adherence, while the remaining participants were divided between medium adherence (54.3%) and low adherence (2.9%). Regarding BMQ adherence, 68.6% of patients scored zero points in the questionnaire, indicating adherence to the treatment. Among the remaining 31.4% of patients, 86.4% reported at least one type of adherence barrier, and 13.6% reported two types of barriers. Among those with adherence barriers, 84.2% reported a regimen barrier, 5.3% reported a belief barrier, and 10.5% reported a memory barrier. Among the patients with two barriers, 66.7% were classified as having a combined recall and regimen barrier, and 33.3% reported a belief and recall barrier.

When analyzing the adherence results of patients with undetectable levels of tenofovir in their urine (88.6%), two distinct scenarios were observed. Patient 1 had been diagnosed with HIV and began treatment at least one year before the study. He exhibited an undetectable viral load, indicating successful treatment, and demonstrated moderate adherence according to the Morisky-Green questionnaire and high adherence according to the BMQ. The undetectable viral load in this patient signifies effective viral suppression due to the treatment. However, the absence of tenofovir in the urine may suggest that the patient's last intake of medication was more than ten days ago, as noted in the study by Koenig et al. (2017a). In contrast, patient 2 had a viral load exceeding 1000 copies/mL, indicating treatment failure. This observation is supported by the scores obtained in the questionnaires, where patient 2 exhibited low adherence according to the Morisky- Green questionnaire and reported two barriers to adherence according to the BMQ. In this case, the detectable viral load may be attributed to a lack of treatment adherence on the part of the patient, as other patients who achieved viral suppression exhibited high levels of tenofovir in their urine, indicating treatment efficacy. However, it is important to note that viral suppression is not solely dependent on tenofovir in combined regimens. In addition to the effects of the medications, there is significant variability in response to antiretrovirals due to individual pharmacokinetic differences and viral biological variations. Another limitation of relating viral load to tenofovir urinary concentrations in this study is that viral load testing may reflect a past snapshot, as for some patients the sample collection for tenofovir quantification was performed at a different time than the blood collection for viral load evaluation.

However, it is important to note that viral suppression is not solely dependent on tenofovir in combined regimens. In addition to the effects of the medications, there is significant variability in response to antiretrovirals due to individual pharmacokinetic differences and viral biological variations. Another limitation of relating viral load to tenofovir urinary concentrations is that viral load testing may represent a snapshot of the past once, for some patients, the sample collection for tenofovir quantification was performed at a different time than the blood collection for viral load evaluation.

TABLE II
Tenofovir concentrations, Morisky-Green and BMQ scores, and viral load of patients

Patient	Tenofovir concentration (ng/mL)	Viral load (copies/mL)	Morisky-Green Score	BMQ Score
				Regimen	Beliefs	Remembering	Total Score
1	Not detected	<50	1	0	0	0	0
2	Not detected	>1000	2	1	0	1	2
3	60.5	<50	2	1	0	0	1
4	107.0	<50	1	1	0	0	1
5	129.0	<50	1	1	0	0	1
6	290.7	243	4	1	0	0	1
7	430.0	<50	1	1	0	0	1
8	678.0	<50	1	1	0	0	1
9	2541.5	<50	2	1	0	1	2
10	2962.0	<50	0	1	0	0	1
11	3153.3	<50	1	0	0	0	0
12	3379.6	<50	0	1	0	0	1
13	3614.4	>1000	1	0	0	1	1
14	3745.7	<50	0	1	0	0	1
15	4193.7	>1000	1	1	0	0	1
16	4281.3	<50	0	0	0	0	0
17	4396.1	<50	1	0	0	0	0
18	4454.4	<50	1	1	0	0	1
19	5618.1	<50	0	1	0	0	1
20	5946.0	<50	0	0	1	0	1
21	6631.0	<50	0	0	0	0	0
22	7363.3	<50	1	0	0	0	0
23	8122.0	<50	0	0	0	0	0
24	8183.8	<50	0	0	0	0	0
25	8342.0	<50	0	0	0	0	0
26	9160.0	<50	0	0	0	0	0
27	10200.0	<50	0	0	0	0	0
28	10538.3	<50	1	1	0	0	1
29	11156.0	>1000	3	0	0	0	0
30	11347.6	<50	1	0	0	1	1
31	11711.8	<50	1	1	0	0	1
32	11855.2	<50	1	0	0	0	0
33	12927.8	<50	1	0	0	0	0
34	13267.0	<50	1	0	0	0	0
35	13782.0	<50	0	0	0	0	0
36	14249.0	>1000	0	0	0	0	0
37	14478.0	<50	0	0	0	0	0
38	14556.5	<50	0	0	0	0	0
39	14648.0	<50	0	0	0	0	0
40	14675.2	<50	1	0	0	0	0
41	15351.0	<50	1	0	0	0	0
42	15868.2	<50	1	0	1	1	2
43	16002.0	<50	1	0	0	0	0
44	16386.5	<50	2	0	0	0	0
45	16579.0	<50	2	1	0	0	1
46	17391.8	<50	1	0	0	0	0
47	18433.0	<50	0	0	0	0	0
48	18476.0	<50	1	0	0	0	0
49	20621.0	<50	0	0	0	0	0
50	20778.0	<50	0	0	0	0	0
51	21097.4	<50	0	0	0	0	0
52	22592.0	>1000	0	0	0	0	0
53	23825.0	<50	0	0	0	0	0
54	24077.9	<50	1	0	0	0	0
55	24302.0	<50	0	0	0	0	0
56	25092.0	<50	0	0	0	0	0
57	25780.7	<50	0	0	0	0	0
58	26724.6	<50	0	0	0	0	0
59	27114.9	<50	0	0	0	0	0
60	27589.1	<50	1	0	0	0	0
61	29516.0	<50	0	0	0	0	0
62	30053.0	<50	0	0	0	0	0
63	30267.9	<50	2	0	0	0	0
64	31540.0	<50	1	0	0	0	0
65	36582.0	<50	0	0	0	0	0
66	41241.1	<50	1	0	0	0	0
67	42321.8	<50	1	0	0	0	0
68	57491.6	<50	1	1	0	0	1
69	59298.9	77	1	0	0	0	0
70	66428.5	<50	0	0	0	0	0

• Viral load: <50 = undetectable. Morisky-Green score: 0 = high adherence; 1 or 2 points = medium adherence; 3 or 4 points = low adherence. BQM total score: 0 = High adherence/adherent; if there is a score higher or equal to one, it indicates potential for non-adherence to treatment.

A summary of the statistical findings can be found in Table III. In order to evaluate the presence of high medication adherence (100% of the time) with any level of non-adherence, patients having medium or low adherence were combined into a single group for statistical analysis. This group was then compared to the high-adherence patients based on the questionnaire. When analyzing the results obtained from the Morisky-Green questionnaire and the corresponding tenofovir concentrations in urine, it was not possible to establish a direct relationship between adherence and concentrations. The analysis of variance between the high adherence group and the medium/low adherence groups, as observed in the Morisky-Green questionnaire, did not reveal any statistically significant differences when compared to tenofovir concentrations (p=0.224).

TABLE III
Evaluation of tenofovir concentrations in urine performed according to patient adherence groups, as classified using the Morisky-Green test and BMQ

Adherence evaluation questionnaire	Group	N(%)	Tenofovir concentrations (ng/mL)
			Median (25-75 percentiles)	p-value
BMQ	Adherence	48(68.6)	17391.85(11855.20; 26724.60)	0.000*
	Potential non-Adherence	22(31.4)	3745.70(554.00; 10942.95)
Morisky-Green	High Adherence	32(45.7)	14602.22(8137.45; 24894.50)	0.224
	Medium/Low Adherence	38(54.3)	12391.50(3759.22; 18204.96)

• ^*
  Significant at Mann-Whitney test (p<0.05)

Additionally, a chi-square analysis was conducted to compare the Morisky-Green responses with other data, such as HIV standard pharmacotherapy (2-in-1 treatment with dolutegravir), years of school, diagnostic information, and the presence of adverse effects. However, this analysis did not reveal any significant associations, as depicted in Table IV. It's essential to emphasize that relying solely on patient reports, pill counts, or viral load tests for evaluating adherence may offer a simplified approach, but it is not always effective. While the Morisky-Green test aids in assessing therapeutic adherence, it is susceptible to bias, as some patients may provide answers they perceive as correct rather than accurately reflecting their actual behavior (Ben et al., 2012b). Nevertheless, gender was observed to influence patients' adherence when compared to those classified as having high adherence according to the Morisky-Green questionnaire (Table III). Among the 32 patients in this category, 65.6% (n=21) were men, while women constituted the majority in the non-adherent group, accounting for 60.5% (n=23) out of the 38 patients (p=0.034).

TABLE IV
Chi-square p-values for the comparison of BMQ, Morisky-Green test, and tenofovir urinary concentrations among different patient groups based on their characteristics

Characteristic	BMQ	Morisky-Green	Tenofovir urine concentration above cut-off
Gender	0.088	0.034*	0.884
School years	0.437	0.565	0.636
Standard treatment	0.014*	0.319	0.113
Presence of adverse effects	0.020*	0.150	0.553
Year of diagnostic	0.872	0.992	0.333

• ^*
  Significant at chi-square tests; p<0.05.

When correlating tenofovir concentrations with the results obtained from the BMQ, a significant relationship was identified between patients classified as more adherent by the BMQ and those exhibiting high adherence based on urinary concentrations (p<0.001). The area under the ROC curve (Figure 1) was calculated as 0.864 (confidence interval 0.757-0.971), with a cutoff value of 6288.5 ng/mL. This cutoff value demonstrated a sensitivity of 93% and specificity of 72% in predicting high adherence according to the BMQ. The analysis of adherence using the BMQ in conjunction with patients having tenofovir concentrations above the cutoff showed a moderate kappa test index (value: 0.677, significance <0.01).

FIGURE 1
ROC curve considering BMQ adhesion and tenofovir urine concentrations.

Using the tenofovir urinary concentration cutoff of 6288.5 ng/mL to predict high adherence to tenofovir treatment, we found that 93.6% of adherent patients also had tenofovir concentrations above the cutoff. Among the 21 patients who were not classified as highly adherent and that reported barriers to adherence in the BMQ, 71.4% did not present tenofovir urinary concentration above the new cutoff. This comparison demonstrates a strong association between the BMQ test and the presence of high actual adherence to the trestment, both for adherent and non-adherent individuals.

Koenig et al. (2017a) classified patients into three groups based on urinary tenofovir concentrations. Patients who used the drug daily were classified as having high adherence, with a urinary concentration of >1,000 ng/mL of tenofovir. Patients who took tenofovir every other day were classified as having moderate adherence, with concentrations ranging from 10 to 1,000 ng/mL. Patients with concentrations <10 ng/ mL were classified as having low adherence. It was observed that tenofovir could be detected in the body for up to ten days in this group. Subsequently, Drain et al., (2020) validated urine tenofovir concentrations as a method of monitoring recent drug use, which was found to be more effective than plasma concentrations. However, they did not establish a specific cutoff value for their patients. The authors reported that tenofovir was detected in urine for more than two weeks in two patients after they had stopped taking the drug. In another study, Johnson et al., (2021) compared two formulations of tenofovir and established a cut-off for urinary tenofovir concentrations of 1500 ng/mL for detecting recent intake of the drug within the past five days. The cutoff value of 6288.50 ng/mL differs from the values established in previous studies (Koenig et al., 2017a; Drain et al., 2020; Johnson et al., 2021). However, those studies evaluated adherence during periods when patients did not take their medication, unlike the present study, which involved patients on continuous treatment without interruptions. Koenig et al. (2017b) found concentrations exceeding 10,000 ng/ mL in the group of patients who consistently took the drug daily, although they set their cutoff value for high adherence at >1000 ng/mL.

Upon analyzing adherence values using the BMQ and considering the types of pharmacotherapies employed, it becomes apparent that patients undergoing the standard 2-in-1 treatment with dolutegravir show higher adherence levels compared to those using tenofovir in combination with other medications (p=0.014) (Table IV). However, the standard 2-in-1 treatment with dolutegravir did not exhibit significant differences when compared to tenofovir concentrations (p=0.113). Additionally, it was observed that patients on the standard drug regimen experienced fewer adverse effects than those on alternative regimens (p=0.020). In assessing adherence using the BMQ, most patients demonstrated adherence to their treatment, with only a few reporting any barriers. The most frequently cited barrier was forgetting to take the medication on certain days, aligning with the findings of the Morisky-Green questionnaire. Forgetfulness remains one of the main obstacles faced by patients, resulting in an average adherence rate of 66.67%.

When utilizing standardized questionnaires to evaluate therapeutic adherence, it is anticipated that patients will truthfully report their medication-taking habits. However, our current study uncovered that this isn't always the case when comparing the Morisky- Green questionnaire results with other parameters. One potential explanation for this inconsistency, as mentioned earlier, is that patients might feel compelled to provide responses aligning with the interviewer's expectations rather than accurately reflecting their behavior. Another factor contributing to the absence of significant results in assessing adherence using the standardized Morisky-Green questionnaires is the lack of a specified time frame for the questions. The Morisky- Green questionnaire inquires whether the patient has ever forgotten to take their medication, without indicating a defined period. Consequently, a positive response automatically categorizes the patient as having medium adherence, even if the forgetfulness occurred a considerable time ago. This absence of a defined time frame introduces a memory barrier. In contrast, the BMQ addresses this limitation by incorporating a one- week recall period, leading to more reliable results. It's not uncommon for patients at the start of continuous treatment to encounter memory barriers, as they haven't yet established the habit of incorporating medication into their routine. However, with time, this practice tends to become more ingrained. In our study, none of the patients reported belief limitations regarding treatment, although a previous study conducted in Brazil in 2015 identified instances where patients intended to discontinue treatment on weekends to consume alcohol (Silva et al., 2015). This issue with the Morisky-Green questionnaire has been noted in other studies (Ben et al., 2012). In a study conducted by our research group evaluating adherence to fluoxetine treatment, no correlation was observed between the Morisky-Green questionnaire and the BMQ. Furthermore, no significant associations were found between adherence scores from the questionnaires and the plasma concentrations of the drug and its active metabolite (Raasch et al., 2022).

When healthcare professionals show genuine interest in helping the patient and supporting their treatment, it often leads to better adherence among patients who lack sufficient professional support (De Melo et al., 2022). It’s particularly significant for HIV patients, as many of them keep their diagnosis a secret even from their family members. Moreover, the public and free nature of the Brazilian healthcare service, along with the accessibility of medications, combined with the attention received during treatment, contributes to patient adherence. The present study observed that most patients had high concentrations of tenofovir in their urine, indicating good adherence, which is also reflected in their responses to the BMQ questionnaire. These positive outcomes may be attributed to the efforts of healthcare professionals in the medication dispensing process. Measuring tenofovir's urinary concentration, though a more expensive test, can provide more accurate interventions for patients who continue to have a high viral load despite reporting good adherence. In cases where urinary concentrations suggest high adherence but the viral load remains elevated, the healthcare professional can make necessary treatment adjustments to improve the patient's outcomes. The assay can be provided in reference centers and its costs for selected patients could be smaller than alternative treatments.

Our study has some limitations. Certain results may have been influenced by the small sample size and its convenience-based composition. Self-reported adherence in questionnaires is subject to recall bias, leading to some degree of imprecision in the estimates. There is no consensus in the literature regarding the ideal method for assessing treatment adherence, and the diversity of methods complicates comparisons with other studies. It is important to note that Ben et al., (2012) did not perform a cross-cultural adaptation of the Morisky- Green Medication Adherence Questionnaire (Morisky, Green, Levine, 1986), which may have impacted the instrument's predictive ability. Additionally, concerns have been raised regarding the validity of the Morisky- Green Medication Adherence Questionnaire. A newer eight-question version of the scale, different from the one validated by Ben et al., (2012), was retracted due to misleading results arising from deficiencies in its sensitivity and specificity.

CONCLUSION

Given that close patient follow-up and monitoring are known contributors to improving treatment adherence and fostering awareness of its importance, this study reveals that patients' urinary concentrations indicate a high level of adherence to HIV treatment, as demonstrated by undetectable HIV viral loads. Urinary tenofovir concentrations above the proposed cutoff of 6288.5 ng/mL were predictive of adherence to treatment, as evaluated by the BMQ, but not by the Morisky-Green questionnaire.

• CONFLICT OF INTEREST
  There are no conflicts of interest to report.
• FUNDING
  None.
• ETHICS APPROVAL
  The study received approval from the Research Ethics Committee of Feevale University (approval #5,448,391, approval date 06/03/2022).
• DATA AVAILABILITY
  Any raw data not presented in the manuscript will be provided upon request.

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Edited by

• Associated Editor:
  Tácio de Mendonça Lima

Publication Dates

• Publication in this collection
  16 Jan 2026
• Date of issue
  2025

History

• Received
  12 Apr 2024
• Accepted
  04 July 2024