Free online tool may help doctors make treatment decisions for HIV-positive patients with drug resistance

Michael Carter
Published: 20 January 2011

UK investigators have developed an online resource that can help doctors select the most effective combination of anti-HIV drugs for patients with extensive experience of antiretroviral therapy. Evaluated in two studies published in the January edition of AIDS Patient Care and STDs, suggestions made by the tool led to doctors changing their initial treatment decision in a third of cases. Physicians found the resource easy to use, and the majority said that they would consider using it in the future.

An updated version of the resource, the HIV Treatment Response Prediction System (HIV-TRePS), is now freely available on the internet, and is based on a computer model that includes information gathered from 65,000 HIV-positive patients across the world.

Doctors enter information about their patients, including resistance to HIV drugs, antiretroviral treatment history, CD4 cell count, and viral load. The programme then suggests the five combinations of drugs which are likely to be most effective.

“HIV-TRePS is an innovative and important tool to improve the health of people with HIV”, said Dr Julio Montaner of the British Columbia Centre for Excellence in HIV/AIDS. His clinic was involved in the development of the resource.

There are now 25 antiretroviral drugs available and the goal of HIV therapy is an undetectable viral load. However, many patients do not achieve this outcome and selecting the best combination of drugs for patients with extensive experience of therapy anti-HIV medications, especially if they have drug resistance, can be difficult.

A group of investigators therefore came together to develop a computer model that could accurately predict responses to antiretroviral therapy. The UK-based researchers collaborated with HIV physicians in 15 different countries.

Initial analysis showed that a programme could help doctors make treatment decisions. But before making the models available the investigators wished to test their “potential utility in clinical practice.”

Two studies were designed. It was intended to recruit 150 patients to a prospective study. However, only ten individuals were recruited to the study when it was stopped early because of the introduction of three new drugs (etravirine, maraviroc and raltegravir) that provide important options for heavily treated patients.

The second study was retrospective and reviewed 104 cases.  In both studies, doctors entered into the model the genotypic resistance profiles of their patients, together with HIV treatment histories, viral load and CD4 cell count.

Doctors were also asked to input the combination of drugs they were considering for their patients.

Five treatment combinations most likely to suppress viral load were then suggested by HIV-TRePS. The 24 physicians who participated in the study then entered the therapy they actually prescribed, and results showed that in a third of cases they changed their initial treatment decision after using the programme.

In only five instances did the doctors actually use a combination suggested by the programme. In the other 33 cases, doctors amended the recommendation to take into account patient preference, their own judgment, and tolerability.

Nevertheless, after using the programme doctors were more likely to prescribe a regimen that consisted of only three drugs.

“Review of the report led to physicians to reflect on their treatment decisions and the final decision reached was improved as a result – with fewer drugs and a superior predicted response,” comment the investigators.

Physicians found the programme easy to use.  Most said it was “quite useful” (22%) or  “satisfactory” in making treatment decisions, a 30% reported they would use it “often,” and 48% “sometimes.” Only one doctor indicated that he would never use it, and this was because the individual provided care to patients whose treatment was straightforward.

“The encouraging results indicate that the system is easy to use and has potential to provide significant benefits in terms of simplicity and acceptability of therapy, the virologic response to that therapy and its costs,” conclude the researchers, who believe the results warrant "further development and clinical study."

An updated version of the system has been made available, and an experiment tool for resource limited settings tool that does not require resistance data is being developed.

Reference

Larder BA et al. Clinical evaluation of the potential utility of computational modelling as an HIV treatment selection tool by physicians with considerable HIV experience. AIDS Patient Care and STDs, 25: 29-36, 2011 (the study abstract is available here).