This retrospective analysis of data from multiple HIV/AIDs treatment sites is not unique in exploring the factors associated with TF in patients from Asmara, Eritrea. The study discovers a catalogue of TF risk factors in addition the study also highlights that cases had a profoundly lower immune response to treatment and significantly shorter duration on cART in contrast to controls. Specifically, the data suggests that TDF+EFV-based-cART appeared more effective than non-TDF-based regimens (AZT+3TC, ABC+3TC, and D4T+3TC). In general, these findings align with previous studies which suggested that DRMs to TDF are limited  and that its safety record is relatively good . Importantly, reports suggest that the efficacy of AZT, D4T, and ABC-based cART has been compromised by the emergence of DRMs in the region . In addition, studies on NVP-based cART vs EFV-based ART have suggested that the former is marginally less efficacious . However, our analysis did not uncover such associations.
Multiple explanations can be invoked to explain why TDF+EFV-based cART is less associated with TF. First, adverse effects (vomiting, diarrhea, among others) associated with AZT, ABC, and D4T may potentially compromise treatment or account for differences in adherence rates. Importantly, a study in Kenya demonstrated that TDF had a lower drug change rate (1.9 per 100 person-years) compared to D4T (27 per 100 person-years)  – the changes were largely attributed to adverse drug reactions (mostly lipodystrophy and polyneuropathy). Interestingly, adverse drug reactions were a prominent reason for changes in initial cART in this setting. Another possibility with far-reaching implications is the presence of resistance mutations (RMs). Incredibly, research suggests that ≥ 50 - 90% of patients experiencing virologic failure on first-line cART with viral count > 1000 copies/ml have NNRTI resistance [20,21]. In particular, patients in SSA with first-line TF to NNRTI + NRTIs often present with the M184V mutation (associated with NRTIs - 3TC/FTC) and the K103N mutation (NNRTIs) [22,23]. Resistance testing is not part of the treatment protocol in Eritrea as drug resistance survey (DRS) conducted in 2017 revealed RM less than 10% among newly diagnosed, which is less than the WHO threshold for routine resistance assay.
However, indirect evidence of the potential role of DRMs was noted in this study. First, large proportions of patients (77.4%) were on 3TC-based regimens and sub-optimal response to treatment in patients who were switched to 3TC-based regimens was also noted. More importantly, patients were placed on failing regimens for an extended duration of time. Petersen et al. demonstrated that delayed second-line ART switch has been associated with the emergence of DRMs . A different line of evidence that points to the possible presence of DRMs was the observed relationship between prior antiretroviral drug use (PAU) and VF. In general, prior exposure to ART – regardless of viral load count – has been linked to an increased likelihood of VF . Others have also suggested that the increased risk of TF observed in patients with PAU is largely attributable to pre-treatment drug resistance (PDR) . According to this report, HIV-infected adults in SSA starting first-line NNRTI-based cART and have a history of PAU, i.e. ART or single dose Nevirapine (sdNVP) for PMTCT, were more likely to have VF . In addition, Cutrell and Jodlowski described that in the absence of resistance testing, it’s prudent to assume resistance to drug regimens with a relatively low genetic barriers to resistance, such as EFV, 3TC, FTC, Raltegravir, or Elvitegravir, if these agents were part of a previously failing regimen . Therefore, the use of differentiated, non-NNRTI-based empiric first-line therapy has been recommended in such patients. However, this is impractical in Eritrea due to the limited range of ART available. Regardless, the extensive use of 3TC in patients with poor response to initial cART or with PAU should be reconsidered.
Furthermore, similar to other studies in the region [26, 27], we noted that sub-optimal adherence to cART was a principal contributor to VF. Sub-optimal adherence can lead to high healthcare costs, poor patients outcomes (increased HIV-related morbidity and mortality), the emergence of DRMs, and increased community HIV transmission . Numerous studies have demonstrated that even in high-functioning health systems, adherence to cART remains a major obstacle in HIV/AIDS treatment programs . For instance, a recent study in Ethiopia suggested that the likelihood of VF was 5.4 fold higher among those who had poor adherence . Likewise, poor adherence to cART as a correlate of VF was reported by investigators in Kenya  and Ethiopia [26,27]. In summary, we can maintain that despite the relative heterogeneity of study designs and the diverse nature of backgrounds studied in SSA; inadequate adherence to cART is a ubiquitous contributor to TF in the region. Multiple socio-demographic, environmental, and behavioral factors are known to influence sub-optimal adherence. These include older age, living conditions/situation, stigma, early-stage HIV infection, comorbid mental health conditions, DRMs, adverse drug effects, DDIs, poor tolerability, polypharmacy drug stock-outs and substance use . To understand and address the challenges associated with sub-optimal cART adherence, a better appreciation of the relevant determinants is required. Unfortunately, it can be argued that while most studies in the region highlight the importance of sub-optimal adherence to cART; its determinants are poorly described. In this regard, the study corroborates the findings of a recent meta-analysis which identified toxicity as a prominent cause of poor adherence, 58% (95% CI: 46, 69%; Range: 14.4–88.5%) . Beyond these issues, concerns regarding the diagnostic accuracy of self-reported adherence data have been highlighted . That being said, the inability to obtain a reliable quantification of the adherence process over time, can thus be a barrier to intervention. These concerns are highly relevant in this setting.
By most accounts, the problem of poor adherence to cART in treatment programs in SSA is formidable. However, success has been demonstrated for mitigation efforts that prioritize the integration of adherence interventions as part of routine clinical care. In the United States , cART adherence is discussed at every visit, and patients triaged as poor adherers are promptly referred for counseling or enhanced adherence intervention or support . Alternatively, some authors support the idea that chronic non-cART adherers should be placed on regimens with a higher barrier to resistance - boosted protease inhibitors (PI) or Dolutegravir (DTG) . In SSA, the latter option will require expansion of cART choices. This has important cost implications which severely limit its practicality in settings like Eritrea.
Further, we demonstrated that low CD4+ cell count (baseline CD4+ cell count of <50 and ≤100 cells/ µl) were associated with increased odds of VF. Comparable results have been reported in Ethiopia [26,33–35], and Kenya , among others. To explain this relationship, the inverse relationship between CD4+ cell count and viral replication at specific stages of the disease has been invoked . In addition, a low CD4+ cell count is a marker of advanced disease, hence the potential presence of HIV-defining infections. In important respects, the foregoing discussion underscores the fact that delayed/late diagnosis/presentation (919 (87.0%) presented late) is one of the biggest problems facing HIV treatment programs in Asmara, Eritrea. Admittedly, problems related to study design may undermine the accuracy of the late presentation estimates. Either way, we believe that our estimates are largely reliable. Apart from CD4+ cell count, surrogate pointers to the late presentation as a major problem in this setting can be gleaned from several associations in the bivariate analysis. These include the proportion of patients with WHO Stage III and IV disease at baseline, baseline functional status, comorbidities, and the inverse relationship between time of HIV diagnosis and initiation of cART. Predictably, some of these factors emerged as predictors of VF in the multivariable model. Overall, we can conclude that the observed gap between HIV diagnosis and treatment for some patients requires particular scrutiny since it can compound the problem of late presentation.
Previous studies have shown that late entry to care is harmful in multiple ways - worse prognosis, shorter survival, and less benefit from cART [37,38]. Documented factors associated with late presentation include male gender, older age, stigma, poor mental health , low-risk perception, discrimination, lack of spousal HIV status disclosure, lower-income, poor social support, level of education, lack of awareness about the need for early HIV, access to testing and treatment sites, limited investments in community, and structural interventions [37 - 44]. Thus, drivers of late presentation are from diverse domains (economic, social, demographic, geographic, and psychosocial) and are undeniably complex and contextualized. As such, no two jurisdictions share the same complement of factors. This argument underscores the importance of local data. Unfortunately, the factors associated with late presentation are under-described in Eritrea. Thus, efforts to improve early HIV diagnosis (e.g. mobile- and home-based testing and counseling), early linkage to chronic HIV care centers, and timely initiation to cART should be prioritized. Formulation of new treatment models for late presenters should also be addressed (particularly CD4+ cell count ≤200 cells/μl and/or WHO clinical stage III and IV). There is strong evidence from the region indicating that intervention models mandating weekly or bi-weekly contact with care sites can work. These models are generally credited with early identification and treatment of opportunistic infections (OIs) and reductions in morbidity and mortality.
To further understand the relationship between treatment and immunological response. We considered it important to evaluate the kinetics of CD4+ cell count at specified intervals. In the process, we noted some outstanding points. Immunological recovery (> 500 cells/mm3) was generally poor in a majority of patients (cases: 14% vs Control: 28%), who achieved it after 36 months of treatment. This was contrary to the conclusions in a recent review which noted that achievement of sustained virologic suppression with cART is typically associated with a steady increase in peripheral blood CD4+ cell count recovery (>500 cells/ µl) . They also noted that ~ 15–20% of patients, particularly late presenters who start therapy at CD4+ cell count (< 200 cells/ µl) will plateau at a CD4+ cell count below the immunological recovery threshold. More importantly, we also demonstrated that the increment rate of CD4+ cells/ µl /month differed significantly between cases and controls – a finding that is by no means unique . However, the overall CD4+ cells/ µl /month was substantially less than what is recommended by some investigators/or guidelines. For instance, some studies concluded that CD4+ cell count gains <100 cells/μl/year can be used to identify patients at risk of hard endpoints such as AIDS, serious non-AIDS events, and death .
Finally, we have to note that our model suggests that Cotrimoxazole prophylaxis (CPT) was a predictor of virologic failure. This finding counteract with results from a study conducted in Ethiopia . In their opinion, the relationship was potentially linked to the fact that CPT boosts the immune status of patients in that CPT directly prevents opportunistic infections, and leads to the reduction in the incidence of virologic failure associated with different causes. However, in this jurisdiction, we think that the most plausible explanation relates to the fact that patients experiencing VF are more likely to present with OIs and are thus more likely to be placed on Cotrimoxazole prophylaxis by clinicians. Therefore, the finding merely raises questions regarding triggers for Cotrimoxazole prophylaxis.
Strengths and limitations of the Study
To the best of our knowledge, our study is the first to evaluate the factors associated with virologic failure in Eritrea. Regardless, it has several limitations. First, the study uses secondary data collected retrospectively. This approach has been associated with the incompleteness of clinical data. Moreover, underreporting/missing data elements can lead to biases – particularly if they are systemic. Secondly, the contribution of HIV drug resistance to VF was not assessed. Lastly, adherence information was largely based on self-report. However, recall and social desirability bias may undermine the reliability of this approach. Despite these limitations, we would like to highlight some strengths: first, information on a large number of variables including demographic information; care entry point; prior exposure to cART; date of HIV diagnosis; date of cART initiation and subsequent treatment history; and clinical outcomes were collected. The availability of this information permitted an in-depth analysis of multiple secondary objectives. Second, the sample size was fairly large for multiple variables thereby strengthening the robustness of our results.