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Gender Differences in Adherence and Response to Antiretroviral Treatment in the Stratall Trial in Rural District Hospitals in Cameroon

Boullé, Charlotte PhD*; Kouanfack, Charles MD, PhD; Laborde-Balen, Gabrièle MSc*; Boyer, Sylvie PhD‡,§,‖; Aghokeng, Avelin F. PhD*; Carrieri, Maria P. PhD‡,§,‖; Kazé, Serge MD; Dontsop, Marlise MD, MSc; Mben, Jean-Marc MD; Koulla-Shiro, Sinata MD; Peytavin, Gilles PharmD, PhD¶,#; Spire, Bruno MD, PhD‡,§,‖; Delaporte, Eric MD, PhD*,**; Laurent, Christian PhD*for the Stratall ANRS 12110ESTHER Study Group

JAIDS Journal of Acquired Immune Deficiency Syndromes: July 1st, 2015 - Volume 69 - Issue 3 - p 355–364
doi: 10.1097/QAI.0000000000000604
Epidemiology and Prevention

Background: Evidence of gender differences in antiretroviral treatment (ART) outcomes in sub-Saharan Africa is conflicting. Our objective was to assess gender differences in (1) adherence to ART and (2) virologic failure, immune reconstitution, mortality, and disease progression adjusting for adherence.

Methods: Cohort study among 459 ART-naive patients followed up 24 months after initiation in 2006–2010 in 9 rural district hospitals. Adherence to ART was assessed using (1) a validated tool based on multiple patient self-reports and (2) antiretroviral plasma concentrations. The associations between gender and the outcomes were assessed using multivariate mixed models or accelerated time failure models.

Results: One hundred thirty-five patients (29.4%) were men. At baseline, men were older, had higher body mass index and hemoglobin level, and received more frequently efavirenz than women. Gender was not associated with self-reported adherence (P = 0.872, 0.169, and 0.867 for moderate adherence, low adherence, and treatment interruption, respectively) or with antiretroviral plasma concentrations (P = 0.549 for nevirapine/efavirenz). In contrast, male gender was associated with virologic failure [odds ratio: 2.18, 95% confidence interval (CI): 1.31 to 3.62, P = 0.003], lower immunologic reconstitution (coefficient: −58.7 at month 24, 95% CI: −100.8 to −16.6, P = 0.006), and faster progression to death (time ratio: 0.30, 95% CI: 0.12 to 0.78, P = 0.014) and/or to World Health Organization stage 4 event (time ratio: 0.27, 95% CI: 0.09 to 0.79, P = 0.017).

Conclusions: Our study provides important evidence that African men are more vulnerable to ART failure than women and that the male vulnerability extends beyond adherence issues. Additional studies are needed to determine the causes for this vulnerability to optimize HIV care. However, personalized adherence support remains crucial.

Supplemental Digital Content is Available in the Text.

*Institut de Recherche pour le Développement, University Montpellier 1, UMI 233 TransVIHMI, Montpellier, France;

Central Hospital, Yaoundé, Cameroon;

INSERM, U912 (SESSTIM), Marseille, France;

§University Aix Marseille, IRD, UMR-S912, Marseille, France;

ORS PACA, Observatoire Régional de la Santé Provence Alpes Côte d'Azur, Marseille, France;

AP-HP, Hôpital Bichat-Claude Bernard, Laboratoire de Pharmaco-Toxicologie, Paris, France;

#IAME, UMR 1137, University Paris Diderot, Sorbonne Paris Cité and INSERM, Paris, France; and

**Department of Infectious and Tropical Diseases, University Hospital, Montpellier, France.

Correspondence to: Charlotte Boullé, PhD, Institut de Recherche pour le Développement (UMI 233), 911 Avenue Agropolis, BP 64501, 34394 Montpellier Cedex 5, France (e-mail: charlotte.boulle@ird.fr).

Supported by grants from the French National Agency for Research on AIDS and Viral Hepatitis (ANRS 12110) and Ensemble pour une Solidarité Thérapeutique Hospitalière En Réseau (ESTHER).

Presented in part at the Seventh Conférence Internationale Francophone VIH/Hépatites AFRAVIH 2014, April 27–30, 2014, Montpellier, France.

The authors have no conflicts of interest to disclose.

Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal's Web site (www.jaids.com).

C.L., C.K., and E.D. designed and coordinated the Stratall trial. C.K. and G.L.-B. coordinated the implementation of the trial. G.L.-B., S.B., M.P.C., S.K., M.D., J.-M.M., and B.S. contributed to data collection. A.F.A. and G.P. did the main laboratory analyses. C.B. and C.L. designed the gender substudy and wrote the first draft of the manuscript. C.B. did the statistical analyses of the gender substudy. All authors contributed to the interpretation of data and reviewed the manuscript.

Members of the Stratall ANRS 12110/ESTHER Study Group are listed in Acknowledgments.

Received September 22, 2014

Accepted December 17, 2014

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INTRODUCTION

In sub-Saharan Africa, women are more vulnerable to HIV infection than men; the former accounted for approximately 57% of all people living with HIV in the region according to the UNAIDS 2013 estimates.1 In this region, most infections occur through heterosexual transmission.2 Female vulnerability to HIV infection is related to biologic and social factors3,4 and is being addressed through specific actions for “Women, Girls, and Gender Equality” recommended by UNAIDS.5

Nonetheless, gender inequalities are not confined to women. Men have less access to antiretroviral treatment (ART) than women. By the end of 2011, men accounted for 44% of the people eligible for ART in the African region but represented only 36% of those receiving ART.6 Several factors can explain this male underrepresentation: men are less likely to use voluntary HIV testing,7 have a poorer health-seeking behavior,8 and have a higher opportunity cost of visiting treatment center (because they are more likely than women to have paid jobs).9 As a consequence, they are also enrolled into care at a more advanced HIV disease stage with lower CD4 cell counts.10–16

Once on ART, men are more often lost to follow-up and experience greater mortality than their female counterparts, independently of their delayed initiation of treatment.11,13,15,17–20 Although a few studies did not show gender differences in immunovirologic response to ART,18,21,22 others showed poorer outcomes in men than in women.15,23–40 Whether a poorer adherence of men to ART is the main determinant of the male vulnerability to therapeutic failure is unclear because data are limited and conflicting.15,21,22,25,29–31,33,41 We therefore assessed gender differences in adherence to ART in patients followed up in rural district hospitals in Cameroon using (1) a validated tool that distinguishes different levels of adherence and treatment interruptions based on multiple patient self-reports and (2) antiretroviral plasma concentrations. We then assessed gender differences in virologic failure, immune reconstitution, mortality, and disease progression in these patients after adjustment for adherence.

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PATIENTS AND METHODS

Study Population

We performed a cohort study among 459 ART-naive patients followed up between 2006 and 2010 in the Stratall trial. This trial was initially designed to compare the effectiveness and safety of an exclusively clinical monitoring strategy with those of a clinical plus laboratory monitoring strategy (including HIV viral load and CD4 cell count). The National Ethics Committee of Cameroon and the Institutional Ethics Committee of the French Institut de Recherche pour le Développement approved the protocol. All patients provided written informed consent. The methods have been described extensively elsewhere.42 Briefly, patients were eligible if they were ≥18 years and had HIV-1 infection and World Health Organization (WHO) stage 3 or 4 or WHO stage 2 with a total lymphocyte count of <1200 cells per microliter. Included patients were followed up in 9 district hospitals for 24 months after ART initiation.

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Procedures

Clinical visits were scheduled at weeks 0 and 2, months 1 and 3, and every 3 months thereafter. Patients who did not attend scheduled appointments were telephoned or visited at home. Patients could also attend clinics whenever they felt unwell. Clinical staging of HIV disease was based on the 2006 WHO classification.43 The first-line antiretroviral regimen included 2 nucleoside reverse transcriptase inhibitors plus 1 nonnucleoside reverse transcriptase inhibitor.

Adherence to ART was primarily measured through face-to-face questionnaires administrated by community health workers at months 1, 3, 6, and every 6 months thereafter using a validated scale constructed to limit both recall and social desirability bias.44,45 This tool includes 14 questions related to pills taken during the previous 4 days (patients were asked to list, for each antiretroviral drug, the daily number of prescribed pills they had taken during each of the 4 days before the visit) and to how well patients respected the dosing schedule during the previous 4 days and during the previous 4 weeks. Another item, focusing on the occurrence of treatment interruptions lasting more than 2 consecutive days during the previous 4 weeks, was also included in the questionnaire.46 Patients were classified into 4 adherence categories using a validated algorithm45: (1) “high adherence” if they had both taken 100% of their prescribed drug doses in the previous 4 days and completely adhered to the prescription schedules in the previous 4 weeks, (2) “moderate adherence” if they had taken 80%–99% of prescribed drug doses during the previous 4 days or had globally adhered to the prescription schedules in the previous 4 weeks (but had never interrupted treatment for >2 consecutive days), (3) “low adherence” if they had taken <80% of the doses prescribed during the previous 4 days or reported to have not fully respected the prescription during the previous 4 weeks (but had never interrupted treatment for >2 consecutive days), and (4) “treatment interruption” if they had interrupted treatment at least once for >2 consecutive days during the previous 4 weeks (regardless of their adherence scores). In addition, patients were asked by physicians or nurses at each clinical visit to detail the number of pills taken during the previous 7 days. Data collected in this way 28 days before and 7 days after each face-to-face questionnaire visit were then used to identify patients who reported lower adherence than that declared in the face-to-face questionnaires and reclassify them accordingly. This allowed the sensitivity of the score for moderate adherence, low adherence, and treatment interruption patterns to be increased.

We also assessed adherence by measurement of antiretroviral plasma concentrations at month 6 using Ultra Performance Liquid Chromatography combined with tandem mass spectrometry (Waters Corporation, Milford, MA) as previously described.47 Measurements were performed at the Laboratory of Pharmaco-Toxicology of the Bichat-Claude Bernard Hospital in Paris. Limit of quantification for each drug (zidovudine, stavudine, lamivudine, nevirapine, and efavirenz) was 10 ng/mL. Adherence in previous week(s) was judged adequate if the plasma concentration reached 3000 ng/mL for nevirapine and 1000 ng/mL for efavirenz corresponding to their efficacy thresholds. According to their long half lives (approximately 30 hours for nevirapine and 50 hours for efavirenz), plasma concentrations above the respective thresholds mean adequate adherence at least in previous 6–9 and 10–15 days for nevirapine and efavirenz, respectively.

Plasma HIV RNA (RealTime HIV-1 assay; Abbott Molecular, Des Plaines, IL) and CD4 cell count (FACSCount device; Becton Dickinson, Mountain View, CA) were recorded at baseline and every 6 months thereafter. Genotypic mutations associated with antiretroviral drug resistance (Abbott Viroseq assay; Celera Diagnostics, Alameda, CA) were assessed when the viral load was ≥5000 copies per milliliter on 2 consecutive samples or when the patient's last viral load was above this threshold. If resistance was detected in those samples, the corresponding baseline samples were also tested to detect primary resistances. Mutations were classified as minor or major using the French agency for research on AIDS (ANRS) consensus statements on antiretroviral drug resistance.48 Viral load, CD4 cell count, and resistance testing were performed in Yaoundé in a reference HIV laboratory accredited by the WHO for HIV resistance testing and registered to the Centers for Disease Control and Prevention and Quality Assessment and Standardization for Immunological measures relevant to HIV/AIDS external quality control programs for viral load and CD4 cell count, respectively.

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Statistical Analyses

Continuous variables were summarized using medians and interquartile ranges (IQRs), and when necessary were categorized using their median or standard cutoffs to preserve statistical power. The Mann–Whitney rank sum test was used to compare their distributions between women and men. Categorical variables were summarized using percentages and compared between both genders using the χ2 test or, when sample sizes were too small, the Fisher exact test.

The association of gender with outcomes was assessed as follows: (1) ART adherence using multinomial mixed regressions with the “high adherence” category as the reference for the dependent variable; (2) virologic failure (≥40 copies/mL) using mixed logistic regressions; (3) CD4 cell count evolution from ART initiation using mixed linear regressions; (4) mortality, disease progression to death or to a new or recurrent WHO stage 4 event, or the emergence of resistances using accelerated failure time models based on the lognormal distribution because Schoenfeld residuals in Cox analyses rejected the proportional hazards hypothesis. All variables associated with the outcomes with P < 0.25 in univariate analyses were entered in the multivariate models and a manual stepwise backward approach was used to determine the final models. Plausible interactions with gender were also tested. Analyses were systematically adjusted for age (≤37 versus >37 years), body mass index (≤20 versus >20 kg/m2), hemoglobin level (≤10 versus >10 g/dL), and antiretroviral regimen (nevirapine versus efavirenz) because those variables differed between women and men at the time of ART initiation (Table 1). Analyses were also systematically adjusted for adherence level.

TABLE 1

TABLE 1

The 4-level adherence score was validated against the achievement of virologic suppression (<40 copies/mL) using a mixed logistic regression. All analyses were conducted using Stata 12.1 (StataCorp, College Station, TX).

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RESULTS

Study Population and Follow-up

Of the 459 patients, 135 (29.4%) were men. At the time of ART initiation, men were significantly older than women (median 42 versus 35 years), had a higher body mass index (20.4 versus 19.9 kg/m2), and a higher hemoglobin level (10.1 versus 9.5 g/dL) and were less likely to receive nevirapine as part of their antiretroviral regimen (65.2% versus 76.9%). In contrast, both genders were comparable of HIV disease stage, CD4 cell count, viral load, renal and hepatic functions, monitoring strategy, and intake of cotrimoxazole prophylaxis (Table 1).

The median follow-up time was 23.9 months for men (IQR: 12.8–24.2) and 24.0 months for women (IQR: 23.3–24.3, P = 0.025). Fourteen men (10.4%) and 24 women (7.4%) were lost to follow-up (P = 0.352).

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Adherence to ART

The 4-level adherence score was associated with the achievement of virologic suppression (68.9% in the “high adherence” group, 66.1% in the “moderate adherence” group, 50.0% in the “low adherence” group, and 39.1% in the “treatment interruption” group; P < 0.001). As shown in Figure 1, men and women had comparable adherence behaviors over the study period. In multivariate analysis, gender was not associated with adherence [adjusted odds ratio (aOR): 1.03, 95% confidence interval (CI): 0.73 to 1.45, P = 0.872; aOR: 0.55, 95% CI: 0.24 to 1.29, P = 0.169; and aOR: 1.04, 95% CI: 0.66 to 1.63, P = 0.867 for moderate adherence, low adherence, and treatment interruption, respectively) after adjustment for age, body mass index, viral load, hemoglobin level, nevirapine use, and follow-up time point (Table 2).

FIGURE 1

FIGURE 1

TABLE 2

TABLE 2

Antiretroviral plasma concentrations at month 6 were as expected and comparable between men and women (Table 3). Specifically, 84 men (80.0%) and 224 women (83.0%, P = 0.549) had adequate concentrations of either nevirapine (>3000 ng/mL) or efavirenz (>1000 ng/mL). Concentrations below these thresholds were associated with lower self-reported adherence (P < 0.001); the proportion of patients with such low concentrations was 12.9% (n = 29) in those who were highly adherent, 20.4% (n = 21) in those who were moderately adherent, 25.0% (n = 2) in those who were poorly adherent, and 62.5% (n = 10) in patients who had interrupted their treatment at least once for more than 2 consecutive days. Concentrations below these thresholds were also associated with a concomitant virologic failure, as 52.2% of those with low concentrations had concomitant virologic failure as compared with 37.3% of those with high concentrations (P = 0.028).

TABLE 3

TABLE 3

In those patients with efavirenz concentration <1000 ng/mL, men had higher concentrations (median: 712 ng/mL, IQR: 629–752) than women (334 ng/mL, IQR: 80–625, P = 0.023). In contrast, there were no differences in concentrations between men and women in those with nevirapine concentrations <3000 ng/mL. Only 5 men and 9 women had undetectable concentrations for all the drugs included in their regimens.

Finally, 52.4% of men and 52.0% of women (P = 0.951) simultaneously reported high adherence and had adequate concentrations of nevirapine or efavirenz.

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Virologic Failure

Viral loads above 40 copies per milliliter were seen in 47.6% (50/105), 44.4% (44/99), 37.6% (35/93), and 44.3% (39/88) of men after 6, 12, 18, and 24 months of ART, respectively. In women, these proportions were 37.3% (101/271), 33.6% (88/262), 28.2% (72/255), and 28.6% (71/248), respectively. Male gender was significantly associated with a higher probability of virologic failure in univariate analysis (odds ratio: 2.05, 95% CI: 1.23 to 3.40, P = 0.006). By multivariate analysis, male gender remained independently associated with virologic failure (aOR: 2.18, 95% CI: 1.31 to 3.62, P = 0.003), after adjustment for age, body mass index, CD4 cell count, viral load, hemoglobin level, antiretroviral regimen, follow-up time point, and adherence (Table 4).

TABLE 4-a

TABLE 4-a

TABLE 4-b

TABLE 4-b

Two patients with primary resistances at inclusion and another infected with a group O virus were excluded from the analysis of the emergence of HIV drug resistance. A total of 59 patients had viral loads ≥5000 copies per milliliter on 2 consecutive samples or on their last available sample. Resistance testing was performed on the samples of all these patients. Resistance emerged in 12 men (9.0%) and 33 women (10.2%). The corresponding incidence rate was 6.2 per 100 person-years (95% CI: 3.5 to 11.0) and 6.4 per 100 person-years (95% CI: 4.5 to 9.0), respectively. Gender was not associated with the emergence of resistance in univariate analysis [time ratio (TR): 0.98, 95% CI: 0.60 to 1.62, P = 0.950] or in multivariate analysis [adjusted time ratio (aTR): 0.86, 95% CI: 0.51 to 1.44, P = 0.558; see Table S1, Supplemental Digital Content, http://links.lww.com/QAI/A661]. There were no differences between both genders at the time of resistance emergence in number of nonnucleoside reverse transcriptase inhibitor–associated mutations (median 2 IQR: 1–3 in men versus 1 IQR: 1–2 in women, P = 0.397), nucleoside reverse transcriptase inhibitor–associated mutations (median 0 IQR: 0–1 in men versus 0 IQR: 0–0 in women, P = 0.625), or the M184V mutation [9 (75%) of 12 men versus 20 (61%) of 33 women, P = 0.419].

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Immune Reconstitution

The median increase in CD4 cell count from ART initiation was 157 cells per microliter (IQR: 62–232) at month 6, 131 cells per microliter (IQR: 57–206) at month 12, 209 cells per microliter (IQR: 98–262) at month 18, and 184 cells per microliter (IQR: 77–288) at month 24 in men. In women, the median increase was 163 cells per microliter (IQR: 66–260), 173 cells per microliter (IQR: 89–261), 203 cells per microliter (IQR: 100–321), and 244 cells per microliter (IQR: 114–351), respectively. By univariate analysis, male gender was associated with a lower CD4 recovery (β: −35.1, 95% CI: −66.4 to −3.9, P = 0.028). By multivariate analysis, there was a significant interaction between gender and follow-up time point, meaning that the trajectory of CD4 recovery differed between men and women. On average, men gained 25.3 (95% CI: −15.7 to 66.3, P = 0.227) fewer CD4 cells than their female counterparts at month 12, 20.2 (95% CI: −20.9 to 61.2, P = 0.335) fewer CD4 cells at month 18, and 58.7 (95% CI: 16.6 to 100.8, P = 0.006) fewer CD4 cells at month 24, after adjustment for age, body mass index, hemoglobin level, antiretroviral regimen, and adherence (Table 4).

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Survival

Thirty-two men (23.7%) and 44 women (13.6%) died. Mortality rate was 15.4 per 100 person-years (95% CI: 10.9 to 21.8) in men and 8.1 per 100 person-years (95% CI: 6.0 to 10.8) in women. Survival in men was 85.0%, 83.4%, 78.5%, and 75.1% at months 6, 12, 18, and 24, respectively. In women, survival was 89.3%, 88.6%, 86.9%, and 85.9%, respectively. By univariate analysis, male gender was associated with a lower survival (TR: 0.25, 95% CI: 0.08 to 0.79, P = 0.018). The multivariate analysis confirmed this finding (aTR: 0.30, 95% CI: 0.12 to 0.78, P = 0.014) after adjustment for age, body mass index, hemoglobin level, antiretroviral regimen, and adherence (Table 4).

In men, most deaths were related to infectious diseases (n = 23, 71.9%) including pulmonary infections (n = 11), enterocolitis (n = 4), cryptococcosis (n = 3), sepsis (n = 2), fulminant hepatitis B (n = 1), oesophageal candidosis (n = 1), and malaria (n = 1). Noninfectious causes of death included anemia (n = 2), hepatocellular carcinoma (n = 2), wasting syndrome (n = 2), Kaposi sarcoma (n = 1), and stroke (n = 1). In women, infectious causes of death (n = 35, 79.5%) included pulmonary (n = 12) and extrapulmonary (n = 3) tuberculosis, enterocolitis (n = 9), encephalopathy (n = 7), sepsis (n = 3), and chronic diarrhea (n = 1). Noninfectious causes of death included anemia (n = 2), Kaposi sarcoma (n = 2), wasting syndrome (n = 1), psychosis (n = 1), and rupture of oesophageal varices (n = 1).

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Disease Progression

Thirty-seven men (27.4%) and 55 women (17.0%) had disease progression to death or to a WHO stage 4 event. The incidence rate of disease progression was 18.6 per 100 person-years (95% CI: 13.5 to 25.6) in men and 10.4 per 100 person-years (95% CI: 8.0 to 13.6) in women. Survival without WHO stage 4 event after 6, 12, 18, and 24 months of treatment was 82.0%, 79.6%, 74.7%, and 71.3% in men and 86.8%, 85.5%, 83.5%, and 82.5% in women, respectively. Male gender was significantly associated with a faster disease progression in both univariate analysis (TR: 0.30, 95% CI: 0.10 to 0.88, P = 0.028) and multivariate analysis (aTR: 0.27, 95% CI: 0.09 to 0.79, P = 0.017; Table 4).

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DISCUSSION

This study in rural district hospitals in Cameroon showed a higher risk of ART failure in men than in women. Importantly, the worse therapeutic response in men was not related to a gender difference in adherence to ART. The vulnerability of men was also not related to a difference in HIV disease stage at the time of treatment initiation.

Our findings add to the growing body of evidence to suggest that men who access ART in sub-Saharan Africa are more at risk of therapeutic failure than women, independently of their later initiation of treatment.11,13,15,17–20,23–40,49 Moreover, we studied a wide range of ART outcomes, including virologic failure, immune reconstitution, mortality, and disease progression, and all results were concordant. In contrast, the previous studies only focused on some of these outcomes. It is worth noting that some studies did not show gender differences in therapeutic failure but that, to our knowledge, no studies have found a higher risk of failure in women in this setting.12,18,21,22,50,51

A crucial finding of our study is that adherence to ART did not explain the male vulnerability to therapeutic failure. Indeed, there was no gender difference in adherence and the analyses of ART effectiveness were adjusted for adherence. Although the measurement of adherence is subject to biases, the validity of our finding seemed good. First, our data on patient self-reported adherence were obtained using a validated questionnaire constructed to limit both recall and social desirability bias.44,45 In addition, the sensitivity to detect nonadherent behaviors was improved by incorporating adherence data reported to physicians or nurses at the clinical visits. Because the patterns of adherence are major determinants of ART effectiveness, we used an adherence scale that distinguishes different levels of adherence and treatment interruptions. Studies have indeed shown that low adherence and treatment interruptions for more than 2 days are independently associated with increased risk of therapeutic failure.46 Second, the absence of gender difference in adherence was observed with both the patient self-reports and the measurement of antiretroviral plasma concentrations. Third, the data from self-reports were associated with those from plasma concentrations. Finally, the data from both methods were associated with virologic effectiveness. A gender difference in reporting adherence was unlikely as suggested by the comparable antiretroviral plasma concentrations between men and women.

Altogether, our findings highlighted the higher risk of therapeutic failure in men independently of their adherence behaviors. Similarly, a cross-sectional survey in Cameroon had found a worse immunologic response in men despite a better adherence to ART.33 In Tanzania, where men were less likely to adhere to clinical visits than women (adherence to ART was unfortunately not reported), mortality and immunologic failure remained higher in men when the analyses were restricted to the period of good adherence for all patients.15 Although they did not compare adherence between men and women, other studies found that men were more at risk of therapeutic failure after adjustment for adherence.25,30,31 In contrast, the higher mortality in South African men observed in univariate analysis did not persist after adjustment for adherence and baseline characteristics; in this study, men were less likely to have a pharmacy-claim adherence above 80% than women.41

Gender differences in pharmacokinetic and pharmacodynamic profiles of antiretroviral drugs might explain the vulnerability of men to ART failure.52,53 Higher concentrations of antiretroviral drugs, which favour the ART efficacy,54,55 have thus been observed in women than in men. However, antiretroviral plasma concentrations in our study were comparable between men and women (although the former had higher bodyweight and body mass index).

The vulnerability of men to ART failure could also be related to intrinsic biologic differences between both genders. Because male hormones downregulate the thymic function,56 men may have a lesser ability to regenerate their CD4 stock while on ART. Also, Mathad et al57 suggested that men had a less favorable immune profile before ART with significantly higher C-reactive protein, lipopolysaccharide, and soluble CD14 than women. Other experts suggested differential immune senescence and CCR5 expression.

A strength of our study is that it was performed in a large cohort with regular follow-up and record of adherence, biologic and clinical data. The proportion of patients lost to follow-up was also limited and comparable between men and women. In contrast, in addition to the limitation related to the difficulty for measuring adherence as underlined above, the fact that our data were recorded in the context of a trial may give rise to a problem of representativeness of our study population and procedures. Specifically, people participating in a trial may tend to be more adherent to ART than patients followed up in the routine clinical setting. Nevertheless, the main demographic and medical characteristics, and the adherence behaviors of our patients, were comparable with those followed up in the Cameroonian national AIDS program, and our study procedures incorporated the good clinical practices required in such settings.33 Regarding the analysis of resistance, the statistical power was relatively low because 45 patients only developed resistance. This may have limited our ability to find statistical associations, for instance between low adherence and resistance because the number of patients with low adherence was especially small. Finally, although liver profiles were comparable between men and women, it could have been interesting to know the patients' status regarding the chronic viral hepatitis B and/or C.

In conclusion, this study provides important evidence that African men are more vulnerable to ART failure than women and that the male vulnerability extends beyond adherence issues. Additional studies are needed to determine the causes for this male vulnerability, including by investigating biologic/hormonal hypotheses, to optimize HIV care. However, personalized adherence support remains crucial.

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ACKNOWLEDGMENTS

The authors thank all the patients and staff of the district hospitals who participated in the study.

Stratall ANRS 12110/ESTHER Study Group:

M. Biwolé-Sida, C. Kouanfack, and S. Koulla-Shiro (Central Hospital, Yaoundé, Cameroon); A. Bourgeois, E. Delaporte, C. Laurent, and M. Peeters (IRD, University Montpellier 1, UMI 233, Montpellier, France); G. Laborde-Balen (French Ministry of Foreign Affairs, Yaoundé, Cameroon); M. Dontsop, S. Kazé, and J.-M. Mben (IRD, Yaoundé, Cameroon); A. Aghokeng, M.G. Edoul, E. Mpoudi-Ngolé, and M. Tongo (Virology Laboratory, IMPM/CREMER/IRD-UMI 233, Yaoundé, Cameroon); S. Boyer, M.P. Carrieri, F. Marcellin, J.-P. Moatti, and B. Spire (INSERM, IRD, University Marseille, UMR 912, Marseille, France); C. Abé, S.-C. Abega, C.-R. Bonono, H. Mimcheu, S. Ngo Yebga, and C. Paul Bile (IRSA, Catholic University of Central Africa, Yaoundé, Cameroon); S. Abada, T. Abanda, J. Baga, P. Bilobi Fouda, P. Etong Mve, G. Fetse Tama, H. Kemo, A. Ongodo, V. Tadewa, and H.D. Voundi (District Hospital, Ayos, Cameroon); A. Ambani, M. Atangana, J.-C. Biaback, M. Kennedy, H. Kibedou, F. Kounga, M. Maguip Abanda, E. Mamang, A. Mikone, S. Tang, E. Tchuangue, S. Tchuenko, and D. Yakan (District Hospital, Bafia, Cameroon); J. Assandje, S. Ebana, D. Ebo'o, D. Etoundi, G. Ngama, P. Mbarga Ango, J. Mbezele, G. Mbong, C. Moung, N. Ekotto, G. Nguemba Balla, G. Ottou, and M. Tigougmo (District Hospital, Mbalmayo, Cameroon); R. Beyala, B. Ebene, C. Effemba, F. Eyebe, M.-M. Hadjaratou, T. Mbarga, M. Metou, M. Ndam, B. Ngoa, E.B. Ngock, and N. Obam (District Hospital, Mfou, Cameroon); A.M. Abomo, G. Angoula, E. Ekassi, Essama, J.J. Lentchou, I. Mvilongo, J. Ngapou, F. Ntokombo, V. Ondoua, R. Palawo, S. Sebe, E. Sinou, D. Wankam, and I. Zobo (District Hospital, Monatélé, Cameroon); B. Akono, A.L. Ambani, L. Bilock, R. Bilo'o, J. Boombhi, F.X. Fouda, M. Guitonga, R. Mad'aa, D.R. Metou'ou, S. Mgbih, A. Noah, M. Tadena, and Ntcham (District Hospital, Nanga Eboko, Cameroon); G. Ambassa Elime, A.A. Bonongnaba, E. Foaleng, R.M. Heles, R. Messina, O. Nana Ndankou, S.A. Ngono, D. Ngono Menounga, S.S. Sil, L. Tchouamou, and B. Zambou (District Hospital, Ndikinimeki, Cameroon); R. Abomo, J. Ambomo, C. Beyomo, P. Eloundou, C. Ewole, J. Fokom, M. Mvoto, M. Ngadena, R. Nyolo, C. Onana, and A. Oyie (District Hospital, Obala, Cameroon); P. Antyimi, S. Bella Mbatonga, M. Bikomo, Y. Molo Bodo, S. Ndi Ntang, P. Ndoudoumou, L. Ndzomo, S.O. Ngolo, M. Nkengue, Nkoa, and Y. Tchinda (District Hospital, Sa'a, Cameroon).

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REFERENCES

1. UNAIDS. Global Report: UNAIDS Report on the Global AIDS Epidemic. 2013. Available at: http://www.unaids.org/en/resources/campaigns/globalreport2013/globalreport/. Accessed September 22, 2014.
2. WHO, UNAIDS, UNICEF. Progress Report 2011: Global HIV/AIDS Response. 2011. Available at: http://www.who.int/hiv/pub/progress_report2011/en/. Accessed September 22, 2014.
3. Dunkle KL, Jewkes RK, Brown HC, et al.. Gender-based violence, relationship power, and risk of HIV infection in women attending antenatal clinics in South Africa. Lancet. 2004;363:1415–1421.
4. Padian NS, Shiboski SC, Glass SO, et al.. Heterosexual transmission of human immunodeficiency virus (HIV) in northern California: results from a ten-year study. Am J Epidemiol. 1997;146:350–357.
5. UNAIDS. UNAIDS Action Framework: Adressing Women, Girls, Gender Equality and HIV. 2009. Available at: http://www.unfpa.org/webdav/site/global/shared/documents/publications/2010/unaids_action_framework.pdf. Accessed September 22, 2014.
6. WHO; UNICEF; UNAIDS. Global Update on HIV Treatment 2013: Results, Impact and Opportunities. 2013. Available at: http://www.who.int/hiv/pub/progressreports/update2013/en/. Accessed September 22, 2014.
7. Laurent C. Commentary: HIV testing in low- and middle-income countries: an urgent need for scaling up. J Public Health Policy. 2013;34:17–21.
8. Skovdal M, Campbell C, Madanhire C, et al.. Masculinity as a barrier to men's use of HIV services in Zimbabwe. Global Health. 2011;7:13.
9. Wouters E, Heunis C, Ponnet K, et al.. Who is accessing public-sector anti-retroviral treatment in the Free State, South Africa? An exploratory study of the first three years of programme implementation. BMC Public Health. 2010;10:387.
10. Muula AS, Ngulube TJ, Siziya S, et al.. Gender distribution of adult patients on highly active antiretroviral therapy (HAART) in Southern Africa: a systematic review. BMC Public Health. 2007;7:63.
11. Braitstein P, Boulle A, Nash D, et al.. Gender and the use of antiretroviral treatment in resource-constrained settings: findings from a multicenter collaboration. J Womens Health (Larchmt). 2008;17:47–55.
12. Cornell M, Myer L, Kaplan R, et al.. The impact of gender and income on survival and retention in a South African antiretroviral therapy programme. Trop Med Int Health. 2009;14:722–731.
13. Taylor-Smith K, Tweya H, Harries A, et al.. Gender differences in retention and survival on antiretroviral therapy of HIV-1 infected adults in Malawi. Malawi Med J. 2010;22:49–56.
14. Cornell M, McIntyre J, Myer L. Men and antiretroviral therapy in Africa: our blind spot. Trop Med Int Health. 2011;16:828–829.
15. Hawkins C, Chalamilla G, Okuma J, et al.. Sex differences in antiretroviral treatment outcomes among HIV-infected adults in an urban Tanzanian setting. AIDS. 2011;25:1189–1197.
16. Mills EJ, Bakanda C, Birungi J, et al.. Male gender predicts mortality in a large cohort of patients receiving antiretroviral therapy in Uganda. J Int AIDS Soc. 2011;14:52.
17. Kigozi IM, Dobkin LM, Martin JN, et al.. Late-disease stage at presentation to an HIV clinic in the era of free antiretroviral therapy in Sub-Saharan Africa. J Acquir Immune Defic Syndr. 2009;52:280–289.
18. Ferradini L, Jeannin A, Pinoges L, et al.. Scaling up of highly active antiretroviral therapy in a rural district of Malawi: an effectiveness assessment. Lancet. 2006;367:1335–1342.
19. May M, Boulle A, Phiri S, et al.. Prognosis of patients with HIV-1 infection starting antiretroviral therapy in sub-Saharan Africa: a collaborative analysis of scale-up programmes. Lancet. 2010;376:449–457.
20. Ochieng-Ooko V, Ochieng D, Sidle JE, et al.. Influence of gender on loss to follow-up in a large HIV treatment programme in western Kenya. Bull World Health Organ. 2010;88:681–688.
21. De Beaudrap P, Thiam M, Diouf A, et al.. Risk of virological failure and drug resistance during first and second-line antiretroviral therapy in a 10-year cohort in Senegal: results from the ANRS 1215 cohort. J Acquir Immune Defic Syndr. 2013;62:381–387.
22. Datay MI, Boulle A, Mant D, et al.. Associations with virologic treatment failure in adults on antiretroviral therapy in South Africa. J Acquir Immune Defic Syndr. 2010;54:489–495.
23. Muwonga J, Edidi S, Butel C, et al.. Resistance to antiretroviral drugs in treated and drug-naive patients in the Democratic Republic of Congo. J Acquir Immune Defic Syndr. 2011;57(suppl 1):S27–S33.
24. Kipp W, Alibhai A, Saunders LD, et al.. Gender differences in antiretroviral treatment outcomes of HIV patients in rural Uganda. AIDS Care. 2010;22:271–278.
25. DART Virology Group and Trial Team. Virological response to a triple nucleoside/nucleotide analogue regimen over 48 weeks in HIV-1-infected adults in Africa. AIDS. 2006;20:1391–1399.
26. Mosha F, Muchunguzi V, Matee M, et al.. Gender differences in HIV disease progression and treatment outcomes among HIV patients one year after starting antiretroviral treatment (ART) in Dar es Salaam, Tanzania. BMC Public Health. 2013;13:38.
27. Penot P, Héma A, Bado G, et al.. The vulnerability of men to virologic failure during antiretroviral therapy in a public routine clinic in Burkina Faso. J Int AIDS Soc. 2014;17:18646.
28. Cornell M, Schomaker M, Garone DB, et al.. Gender differences in survival among adult patients starting antiretroviral therapy in South Africa: a multicentre cohort study. PLoS Med. 2012;9:e1001304.
29. Fox MP, Cutsem GV, Giddy J, et al.. Rates and predictors of failure of first-line antiretroviral therapy and switch to second-line ART in South Africa. J Acquir Immune Defic Syndr. 2012;60:428–437.
30. Nachega JB, Hislop M, Dowdy DW, et al.. Efavirenz versus nevirapine-based initial treatment of HIV infection: clinical and virological outcomes in Southern African adults. AIDS. 2008;22:2117–2125.
31. Toure S, Kouadio B, Seyler C, et al.. Rapid scaling-up of antiretroviral therapy in 10,000 adults in Côte d'Ivoire: 2-year outcomes and determinants. AIDS. 2008;22:873–882.
32. Maman D, Pujades-Rodriguez M, Subtil F, et al.. Gender differences in immune reconstitution: a multicentric cohort analysis in sub-Saharan Africa. PLoS One. 2012;7:e31078.
33. Boyer S, Eboko F, Camara M, et al.. Scaling up access to antiretroviral treatment for HIV infection: the impact of decentralization of healthcare delivery in Cameroon. AIDS. 2010;24(suppl 1):S5–S15.
34. McGuire M, Pinoges L, Kanapathipillai R, et al.. Treatment initiation, program attrition and patient treatment outcomes associated with scale-up and decentralization of HIV care in rural Malawi. PLoS One. 2012;7:e38044.
35. Sempa JB, Kiragga AN, Castelnuovo B, et al.. Among patients with Sustained viral suppression in a resource-limited setting, CD4 gains are continuous although gender-based differences occur. PLoS One. 2013;8:e73190.
36. Nash D, Katyal M, Brinkhof MW, et al.. Long-term immunologic response to antiretroviral therapy in low-income countries: a collaborative analysis of prospective studies. AIDS. 2008;22:2291–2302.
37. Auld AF, Mbofana F, Shiraishi RW, et al.. Four-Year treatment outcomes of adult patients enrolled in Mozambique's rapidly expanding antiretroviral therapy program. PLoS One. 2011;6:e18453.
38. Maskew M, Brennan AT, Westreich D, et al.. Gender differences in mortality and CD4 count response among virally suppressed HIV-positive patients. J Womens Health (Larchmt). 2013;22:113–120.
39. Martinson NA, Gupte N, Msandiwa R, et al.. CD4 and viral load Dynamics in antiretroviral-naive HIV-infected adults from Soweto, South Africa: a prospective cohort. PLoS One. 2014;9:e96369.
40. Anude CJ, Eze E, Onyegbutulem HC, et al.. Immuno-virologic outcomes and immuno-virologic discordance among adults alive and on anti-retroviral therapy at 12 months in Nigeria. BMC Infect Dis. 2013;13:113.
41. Nachega JB, Hislop M, Dowdy DW, et al.. Adherence to highly active antiretroviral therapy assessed by pharmacy claims predicts survival in HIV-infected South African adults. J Acquir Immune Defic Syndr. 2006;43:78–84.
42. Laurent C, Kouanfack C, Laborde-Balen G, et al.. Monitoring of HIV viral loads, CD4 cell counts, and clinical assessments versus clinical monitoring alone for antiretroviral therapy in rural district hospitals in Cameroon (Stratall ANRS 12110/ESTHER): a randomised non-inferiority trial. Lancet Infect Dis. 2011;11:825–833.
43. WHO. WHO Case Definitions of HIV for Surveillance and Revised Clinical Staging and Immunological Classification of HIV-Related Disease in Adults and Children. 2006. Available at: http://www.who.int/hiv/pub/vct/hivstaging/en/. Accessed September 22, 2014.
44. Meresse M, Carrieri MP, Laurent C, et al.. Time patterns of adherence and long-term virological response to non-nucleoside reverse transcriptase inhibitor regimens in the Stratall ANRS 12110/ESTHER trial in Cameroon. Antivir Ther. 2013;18:29–37.
45. Meresse M, March L, Kouanfack C, et al.. Patterns of adherence to antiretroviral therapy and HIV drug resistance over time in the Stratall ANRS 12110/ESTHER trial in Cameroon. HIV Med. 2014;15:478–487.
46. Oyugi JH, Byakika-Tusiime J, Ragland K, et al.. Treatment interruptions predict resistance in HIV-positive individuals purchasing fixed-dose combination antiretroviral therapy in Kampala, Uganda. AIDS. 2007;21:965–971.
47. Jung BH, Rezk NL, Bridges AS, et al.. Simultaneous determination of 17 antiretroviral drugs in human plasma for quantitative analysis with liquid chromatography-tandem mass spectrometry. Biomed Chromatogr. 2007;21:1095–1104.
48. French National Agency for Research on AIDS and Viral Hepatitis. HIV-1 genotypic drug resistance interpretation's algorithms. Available at: http://www.hivfrenchresistance.org/2012/tab1.html. Accessed September 22, 2014.
49. Stringer JSA, Zulu I, Sinkala M, et al.. Rapid scale-up of antiretroviral therapy at primary care Sites in Zambia. JAMA. 2006;296:782–793.
50. Weidle PJ, Malamba S, Mwebaze R, et al.. Assessment of a pilot antiretroviral drug therapy programme in Uganda: patients' response, survival, and drug resistance. Lancet. 2002;360:34–40.
51. Seyler C, Anglaret X, Dakoury-Dogbo N, et al.. Medium-term survival, morbidity and immunovirological evolution in HIV-infected adults receiving antiretroviral therapy, Abidjan, Côte d'Ivoire. Antivir Ther. 2003; 8:385–393.
52. Gandhi M, Aweeka F, Greenblatt RM, et al.. Sex differences in pharmacokinetics and pharmacodynamics. Annu Rev Pharmacol Toxicol. 2004;44:499–523.
53. Ofotokun I, Chuck SK, Hitti JE. Antiretroviral pharmacokinetic profile: a review of sex differences. Gend Med. 2007;4:106–119.
54. Veldkamp AI, Weverling GJ, Lange JM, et al.. High exposure to nevirapine in plasma is associated with an improved virological response in HIV-1-infected individuals. AIDS. 2001;15:1089–1095.
55. Marzolini C, Telenti A, Decosterd LA, et al.. Efavirenz plasma levels can predict treatment failure and central nervous system side effects in HIV-1-infected patients. AIDS. 2001;15:71.
56. Nancy J, Olsen WJK. Evidence that androgens modulate human thymic T cell output. J Invest Med. 2011;59:32.
57. Mathad JS, Gupte N, Balagopal A, et al.. Sex-related inflammatory marker changes pre- and post-ART initiation. In: Conference on Retroviruses and Opportunistic Infection. 2014:853. Available at: http://croiconference.org/sites/all/abstracts/853.pdf. Accessed September 22, 2014.
Keywords:

HIV; sub-Saharan Africa; gender; antiretroviral treatment; outcomes

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