When the final model was stratified by duration of virological failure or program; or restricted to those known to be ART naive or with prior viral suppression, the direction of associations remained the same (see Tables, Supplemental Digital Content 2–5, http://links.lww.com/QAI/A345).
In this large multicentre ART program in South Africa, despite 6 monthly virological monitoring and guidelines recommending a switch after confirmed virological failure, rates of switching to second-line ART were low. Many patients experienced extended periods of viremia after virological failure, in part, due to relatively infrequent VL monitoring and clinic visits. However, other factors including delayed clinic attendance, VL (magnitude and trend), and patients’ immune status seemed to influence health care workers’ decisions regarding when to switch regimens.
Although current program guidelines advise intensifying adherence interventions and switching regimens if a second VL remains high,23,26 this rarely happened in practice. Instead, after a second raised VL, many patients experienced prolonged periods of viremia with the rate of viral resuppression on first-line ART approaching the rate of switching to second-line ART. By the end of follow-up, nearly a quarter of patients remaining on first-line ART were virologically suppressed. Others report high levels of viral resuppression after a single raised VL,25,28–31 however, these results highlight that even after a second raised viral load, viral resuppression remains possible due to, for example, a change in patients adherence behavior or removal of a drug interaction. Excluding nonadherence as a cause of viremia is challenging; current adherence measurement tools are inadequate,32 and strategies to improve adherence can take time and are often context specific requiring multidimensional interventions.33 These difficulties may be compounded by weaknesses in the health care system, for example, out-of-date patient contact details lack of an appointment system, or outreach workers may create delays in detecting and tracing patients with raised viral loads or missed appointments.34
When deciding to switch to second-line ART, health care workers seem to use the magnitude and trend in VLs, prior ART experience, and clinic attendance to evaluate the probability of resistance as opposed to nonadherence. As reported elsewhere, patients with high VLs were more likely to switch regimens35–37; although there is a suggestion in our study that health care workers were less likely to switch patients with a VL >5 log10 as compared with 4–5 log10, perhaps recognizing that these patients have a lower likelihood of resistance and may be nonadherent.38–40 Patients whose VL had fallen to 400–1000 copies per milliliter or whose VL had declined by >50%, suggesting improved adherence, and patients with delayed clinic attendance who were likely to have run out of medication were less likely to be switched. A decision not to switch patients in whom adherence interventions are working or where clinic appointments have been missed seems rational.
Patients with a low CD4 count were more likely to switch to second-line ART, confirming findings from other studies.5,35–37,41 A low CD4 count may reflect immunological progression occurring as a result of viral replication due to treatment interruption, nonadherence, or resistance.42,43 There is no consistent relationship between current CD4 count and odds of detecting resistance.38,40 This may in part relate to the mutations studied; M184V, a mutation which emerges early, has been associated with higher concurrent CD4 count,44,45 whereas some46,47 but not all studies44,48 have demonstrated an association between low CD4 count and thymidine analogue mutations. Regardless of the reason, patients with a low CD4 count are at high risk of short-term clinical progression,19,49 and it may be this factor in itself which prompts a decision to switch to second-line ART.
The frequency of clinic visits contributes to prolonged viremia, with results from 1 visit only available to influence decision-making at the subsequent visit. One-fifth of patients had no record of clinic attendance after confirmed virological failure, therefore, health care workers had no opportunity to assess and instigate appropriate interventions. Interestingly, duration of viremia at the time of visit was not associated with switching regimens, but number of visits was. Regardless of duration of viremia, health care workers may require repeated visits to exclude alternative causes of viremia and ensure that the patient is engaged in care.
Rates of switching and resuppression varied markedly between clinics, supporting observations by others.4,36,50 This heterogeneity was not accounted for by the individual-level or clinic-level variables measured. Others have demonstrated the role of contextual and program factors on the timing of ART initiation,51 however, their influence on the timing of the switch decision is not fully understood.52 Factors such as variations in workload, available adherence support measures within the clinic, procedures for tracing of patients who have missed appointments, and the influence of contextual factors on individual health care workers and patients decision-making regarding virological failure need explored.
Although other studies in resource-limited settings have reported on rates and predictors of switching, these are largely from specialist centers and describe rates of switching after initiation of first-line ART, evaluating predictors either from this time point or at 6 months.4,53–55 In contrast, our analysis describes rates of switching in patients with virological failure and explores determinants of switching at the time decisions are made, that is, at the clinic visit. By taking this approach, rather than a time-to-event analysis, we have avoided the potential bias introduced by competing risks of viral resuppression and interval censoring due to frequency of visits. Although some visit records may be missing, we do not believe this will introduce bias but rather weaken associations.
This study was conducted using routine program data, and although reasons for stopping treatment including switching regimens were available, reasons for continuing a failing regimen were not. We were unable to fully explore the role nonadherence might have on the timing of the switch decision as our only available measure of nonadherence was patients’ self-report. This is recognized to be a suboptimal measure32 and was often missing. In addition other factors, not captured in routine reporting, may affect decision-making, for example, patient’s readiness to switch regimens, health care workers’ concerns regarding limited future regimens, and experience in prescribing second-line ART, or health system factors.52–54,56–58 Finally, some patients may have switched to a protease inhibitor for reasons other than treatment failure, for example, toxicity. In a study using the same cohort, the majority of patients switched to second-line ART whilst viremic did so for treatment failure;59 we therefore believe there is minimal misclassification in our outcome measurement.
Given the large numbers of people living with HIV in sub-Saharan Africa, the need for life-long treatment, the high cost of second-line and third-line drugs, and limited resources, it is vital that the currently available ART regimens are used effectively. These results highlight that even in programs with access to virological monitoring, health care workers encounter difficulties in determining which patients are likely to have resistance and should switch regimens and which need further adherence support. Current tools for measuring nonadherence are inadequate32 and alternative approaches, including targeted resistance testing, warrants further investigation.60 For some patients, attempts to improve nonadherence will be unsuccessful; patients will remain viremic and at risk of resistance accumulation. Switching such patients to a boosted protease inhibitor-based regimen, which is more tolerant of nonadherence, is one strategy; however, the cost-effectiveness in resource-limited settings needs explored. Evidence to support decisions, together with clear algorithms for the management of virological failure, particularly where there is ongoing suboptimal adherence are needed; this becomes particularly pertinent in light of increasing task-shifting of HIV care to nurses and field workers.
The authors would like to thank the patients and health care teams at the participating sites and the staff at Aurum Institute for their assistance with this study.
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