DART study shows HIV treatment without lab monitoring safe, effective in Africa

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Antiretroviral treatment can be delivered safely without laboratory monitoring in sub-Saharan Africa, say the investigators of the DART study, presented this morning at the Fifth International AIDS Society Conference on HIV Pathogenesis, Treatment and Prevention in Cape Town.

The study, coordinated by the United Kingdom’s Medical Research Council and sponsored by the UK Department for International Development and the Rockefeller Foundation, demonstrated only a small difference in rates of death and serious illness between patients randomised to receive laboratory monitoring and those who received clinical monitoring and so switched to second-line treatment only on the basis of clinical symptoms.

DART was designed to test whether a lack of laboratory monitoring would result in significantly worse treatment outcomes for people taking antiretroviral drugs in resource-limited settings. CD4 cell count monitoring is difficult in many resource-limited settings due to lack of laboratory infrastructure.

Glossary

cost-effective

Cost-effectiveness analyses compare the financial cost of providing health interventions with their health benefit in order to assess whether interventions provide value for money. As well as the cost of providing medical care now, analyses may take into account savings on future health spending (because a person’s health has improved) and the economic contribution a healthy person could make to society.

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.

toxicity

Side-effects.

p-value

The result of a statistical test which tells us whether the results of a study are likely to be due to chance and would not be confirmed if the study was repeated. All p-values are between 0 and 1; the most reliable studies have p-values very close to 0. A p-value of 0.001 means that there is a 1 in 1000 probability that the results are due to chance and do not reflect a real difference. A p-value of 0.05 means there is a 1 in 20 probability that the results are due to chance. When a p-value is 0.05 or below, the result is considered to be ‘statistically significant’. Confidence intervals give similar information to p-values but are easier to interpret. 

first-line therapy

The regimen used when starting treatment for the first time.

Researchers from Uganda, Zimbabwe and the United Kingdom found that the difference in outcomes only became apparent after the second year of treatment in the five-year study, leading them to conclude that clinical monitoring alone is feasible during the first two years of treatment, and that CD4 counts should be reserved for monitoring treatment beyond this point.

The results of the DART study are likely to stoke the growing controversy over the best way to monitor HIV treatment in resource-limited settings. In the past year, there have been growing calls to incorporate viral load monitoring into treatment programmes, both in order to detect failure of first-line treatment early and in order to determine whether patients apparently failing treatment on the basis of recent declines in CD4 count are genuine cases of treatment failure.

However, trial investigator Professor James Hakim of the University of Zimbabwe told delegates that it would be possible to treat up to one-third more patients with antiretroviral drugs if laboratory monitoring were limited to the use of CD4 counts after the second year of treatment.

Indeed, for the use of regular CD4 counting to be cost-effective in Uganda, one of the trial sites, the cost per test would have to come down to $3.80 per test, said Professor Charles Gilks of Imperial College, London. The current cost of each test, the trial investigators calculated, is near to $9.

The DART trial randomised 3316 adults in Uganda and Zimbabwe to clinically driven monitoring (CDM) or to laboratory and clinical monitoring (LCM). Individuals were eligible to join the trial if they had symptomatic HIV disease (World Health Organization stage 2, 3 or 4) and a CD4 cell count below 200 cells/mm3, with no prior experience of antiretroviral treatment and no clinical or laboratory abnormalities contraindicating treatment.

All participants received clinical and laboratory monitoring, but the results of CD4 and other blood tests were only returned to clinicians in respect of patients in the laboratory and clinical monitoring arm, except when a patient had a grade 4 laboratory abnormality such as severely elevated liver enzymes or severe anaemia: in this case those results would be supplied to clinicians in respect of patients in the clinical monitoring arm.

Three-quarters of participants in the study received a first-line regimen of AZT/3TC (dosed as Combivir, donated by Glaxo SmithKline) and tenofovir (Viread. The remainder received either Combivir plus nevirapine (Viramune) (16%) or Combivir plus abacavir (Ziagen) (9%).

A sub-study within DART, which recruited patients with a separate informed-consent procedure, compared first-line treatment with abacavir or nevirapine. Participants were assigned to nevirapine or abacavir by randomisation and dosing was double-blinded in order to assess the safety of the two drugs in a resource-limited setting. (Results of this randomised sub-study have been reported previously, and showed a trend towards fewer toxicity-related discontinuations during the first 24 weeks of the study in the abacavir group.)

Patients were switched to second-line treatment if they experienced a new WHO stage 4 clinical event in the clinical monitoring arm, and on the basis of CD4 declines or WHO stage 4 clinical events in the clinical and laboratory monitoring arm.

After just short of five years of follow-up (median 4.9 years), final analysis of the trial shows patients who received clinical monitoring alone were around 30% more likely to develop a new WHO stage 4 event or die, but the absolute difference in terms of numbers was so small that 130 people would need to receive CD4 monitoring for a year to prevent one additional death.

Overall, survival in the study was 'excellent', investigators said, with 87% of the clinical monitoring group and 90% of the laboratory and clinical monitoring group alive after five years of treatment. This survival record compares favourably with results from some treatment cohort studies in sub-Saharan Africa, although it is hard to draw direct comparisons due to different statistical methods used.

There were 459 new events or deaths in the clinical monitoring arm (28%) compared to 356 (22%) in the clinical and laboratory monitoring arm, an absolute difference of 1.7 events per 100 person years of follow-up (95%CI +0.87 to +2.54/100 PY). The hazard ratio was 1.31 [1.14 to 1.51], p=0.0001).

The study found no significant difference in rates of toxicity between the two arms, whether measured as time to first serious adverse event (HR=1.12[0.94 to 1.31];p=0.20), grade 4 toxicity (HR=1.08[0.97 to 1.20];p=0.18) or ART-modifying toxicity (HR=1.01[0.88 to 1.16];p=0.85).

Cost-effectiveness

A separate cost-effectiveness analysis, presented by Professor Charles Gilks of Imperial College on behalf of Antonietta Medina-Lara, assessed the median cost of treatment and monitoring for patients in each study arm. While the cost of first-line treatment was similar in the two arms ($1451 vs $1470), the cost of second-line treatment was lower in the clinical monitoring arm due to a lower rate of switching. CD4 monitoring was estimated to cost $175 year, but the more substantial expenditure was for laboratory toxicity monitoring, which amounted to $699 in the laboratory and clinical monitoring arm.

The researchers calculated the extra cost of the life-years gained by using the laboratory and clinical monitoring approach as opposed to clinical monitoring (the incremental cost-effectiveness ratio) by dividing the incremental average cost by the incremental average survival.

The researchers calculated that after statistical adjustment the incremental cost-effectiveness ratio of the laboratory and clinical monitoring arm was $9,016 per life-year gained.

“This is clearly way outside what would normally be considered to be cost-effective,” said Professor Gilks, pointing out that the WHO Commission on Macroeconomics and Health has proposed that any intervention with an incremental cost-effectiveness of more than three times GDP per capita would not be considered cost-effective. GDP per capita in Uganda is around $400 a year.

Even if the monitoring package was reduced to use of CD4 counts after the second year of therapy, the incremental cost-effectiveness ratio would be $2146, while inputting the lowest available costs into the model (as opposed to the actual health service costs accrued in the trial) would reduce the ratio to $1693.

The price of a CD4 test, including laboratory reagents and staff time, would have to fall to $3.78 or less for antiretroviral management with quarterly CD4 counting after the first year to be cost-effective, Professor Gilks said. If and first - and second-line drug costs fell substantially when compared with the prices used in this study, the cost of CD4 counts would have fall even further to make their use cost-effective.

Dr Peter Mugyenyi of the Joint Clinical Research Centre in Uganda said that the results of the trial should not be used to downgrade spending on laboratories. “We need more support, not less support for laboratories, but the results of DART show where laboratory resources need to be optimally applied.”

Asked how the DART investigators would respond to calls for viral load monitoring to be made more widely available in resource-limited settings, Professor Gilks said that policy makers needed evidence about laboratory monitoring before making spending decisions.

“There is only one study – the Home Based AIDS Care study – which has looked at viral load and the results are still pending publication two years after the study was completed.

“If you have such a benefit from clinically driven monitoring alone and only a small extra benefit from CD4 counts, how much extra benefit would you get from more expensive viral load testing?”