Viral load monitoring of ART patients linked to lower death rate on treatment in southern Africa

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After three years on ART patients enrolled in four scale-up programmes with routine viral load monitoring in South Africa had a fifty percent lower death rate than patients in two public sector programmes in Malawi and Zambia where monitoring is based on CD4 cell counts, Olivia Keiser and colleagues from the International Epidemiological Databases to Evaluate AIDS in Southern Africa (IeDEA-SA) collaboration reported in a comparative studypublished in the advance online edition of AIDS.

In addition, three times as many in Malawi and Zambia were on a failing first-line regimen compared to those in South Africa.

An estimated six million people are now receiving ART in resource-poor settings. As access to ART continues to increase, so does the risk of treatment failure and switching to second-line regimens.

Glossary

second-line treatment

The second preferred therapy for a particular condition, used after first-line treatment fails or if a person cannot tolerate first-line drugs.

treatment failure

Inability of a medical therapy to achieve the desired results. 

retention in care

A patient’s regular and ongoing engagement with medical care at a health care facility. 

loss to follow up

In a research study, participants who drop out before the end of the study. In routine clinical care, patients who do not attend medical appointments and who cannot be contacted.

epidemiology

The study of the causes of a disease, its distribution within a population, and measures for control and prevention. Epidemiology focuses on groups rather than individuals.

Cost and logistics preclude the use of viral load monitoring to diagnose treatment failure in most of the public sector in resource-poor settings. So CD4 cell counts (immunologic) and clinical criteria, while shown to be poor predictors of virologic failure, are routinely used. This often results in unnecessary switching to second-line regimens or delays in switching when failure is undetected.

Delays in switching may contribute to the development of resistant strains that in turn can affect the choice and benefits of second-line treatment and ultimately long-term prognosis.

Studies have shown patients with access to viral load monitoring are more likely to switch to second-line regimens at a higher CD4 cell count than those without and less likely to acquire mutations conferring resistance.

The authors analysed data to compare switching to second-line regimens, loss to follow-up and death atART programmes in RSA where viral load monitoring and CD4 cell count is routinely done every three to six months to ART programmes in Malawi and Zambia where monitoring is based on CD4 cell counts with very limited access to viral load monitoring.

The IeDEA-SA is a collaboration of ART programmes in Southern Africa. Data is collected at the start of ART (at baseline) and at each follow-up visit with data transfer to the Universities of Cape Town, RSA and Berne, Switzerland.

The analysis included over 18,000 adults starting ART in RSA atprogrammes in Khayelitsha, Gugulethu and the Tygerberg clinic in Cape Town and the ThembaLethu clinic in Johannesburg and 80,937 patients from the Lighthouse clinic at Kamuzu Central Hospital, Lolongwe, Malawi and the Ministry of Health-Centre for Infectious Disease Research in Zambia (MoH-CIDRZ) programme in Lusaka.

All six public sector programmes trace patients lost to follow-up.

The authors looked at CD4 responses in sites with and without viral load monitoring. A multi-state model looked at the probability of switching to second-line regimens, death and loss to follow-up. All measurements were evaluated from six months after starting ART.

At three years death rates and loss to follow-up were higher in Zambia and Malawi than inSouth Africa 6.3% (95% CI: 6.0-6.5%) and 15.3% ( 95% CI:15.0-15.6%) compared to 4.3% (95% CI: 3.9-4.8%) and 9.2% (95% CI: 8.5-9.8%), respectively.

In South Africa 9.8% (95% CI: 9.1-10.5%) had switched at three years with 1.3% (95% CI: 0.9-1.6%) on a failing regimen. In Malawi and Zambia fewer had switched and more were on a failing regimen 2.1% (95% CI: 2.0-2.3%) and 3.7% (95% CI: 3.6-3.9%).

The authors note that while the treatment programmes may not be representative of all ART programmes in the three countries, the considerable sample size and range of clinics make the results applicable to many in a high HIV burden region.

The role of viral load monitoring in resource-poor settings continues to be debated, note the authors. The cost-effectiveness of viral load monitoring over CD4 monitoring in terms of lives saved has been questioned. These findings are based on clinical trials that assume patients switch when they meet the immunological criteria. In practice, as this study shows, this is rarely the case, the authors argue.

This study, they add, supports other findings that have shown routine viral load monitoring to be helpful in identifying patients for adherence interventions and promoting retention in care.

Those in South Africa had a lower median CD4 cell count at the start of ART (93 cells/mm3 compared to 132 cells/mm3) but higher after three years (425 cells/mm3 compared to 383 cells/mm3, p=<0.001). The higher death rates in those in programmes without viral load monitoring cannot be explained by differences in baseline characteristics, note the authors.

The authors conclude “Over three years of ART mortality was lower in South Africa than in Malawi or Zambia. The more favourable outcome in South Africa might be explained by viral load monitoring leading to earlier detection of treatment failure, adherence counselling and timelier switching to second-line ART.”

References

Keiser O et al. Outcomes of antiretroviral treatment in programmes with and without routine viral load monitoring in Southern Africa. Advance online edition of AIDS 25. DOI:10.1097/QAD.0b013e328349822f, 2011.