Will a New NIH-Funded Study Tell Us Whether Immediate AIDS Treatment Slows HIV Transmission?

Each year in Sub-Saharan Africa there are about 2-million new cases of HIV infection, most of whom would not need antiretroviral therapy (ART) under current guidelines for 8 to 12 more years. Since donors have not managed to place on treatment more than about half of those needing it each year, the 8 to 12 year lag between infection and need for treatment has been seen as a breathing space. But a radical new idea discussed at last week’s Conference on HIV Pathogenesis, Treatment and Prevention in Cape Town, South Africa would start the 2-million newly infected people on ART within days or weeks of their infection.

Would immediate treatment work as a prevention strategy? At the IAS meeting, Dr. Anthony Fauci, Director of the National Institute of Allergy and Infectious Disease, told the South African Times that “[w]e will be doing research to determine the feasibility of several assumptions underlying [the immediate treatment strategy].” Now the University of North Carolina’s Institute for Global Health and Infectious Disease has announced that researchers William Miller and Audrey Pettifor have been awarded a $3.5 million, four-year research grant to test some of the assumptions flagged in Dr. Fauci’s conference talk.

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Mead Over

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The study will recruit 30 newly infected people for each of three comparison groups

As Pettifor explains on a local radio broadcast (helpfully flagged by the Kaiser Foundation’s Global Health News), the study will find and follow 90 HIV-infected Malawians who are in a 12 week window immediately after infection. The subjects will be randomly allocated to three groups or “arms” of the trial. The “control” arm will receive one session of standard post-test counseling, which includes advice on how to protect their partners from HIV infection. Patients in a second arm will also receive a more intense HIV prevention intervention, which includes five sessions of risk-reduction counseling. The third group of patients will receive not only the post-test counseling and the additional five sessions of prevention counseling, but also will immediately begin antiretroviral treatment. The question is whether the group beginning treatment transmits fewer HIV infections than either of the other two groups.

90 subjects seems like an awfully small sample

Doesn’t it seem that 90 subjects is an awfully small sample, especially when split three ways? While it is risky to try to second-guess the study’s peer reviewers without seeing the proposal they funded, one can raise some basic questions about the statistical challenge confronting the researchers based on the little that has so far been revealed.

Assume that even with post-test counseling the rate of new infections among the partners of high-risk adults in Malawi is about one per-cent per year. Then in order to justify enthusiasm for universal continent-wide HIV testing followed by immediate ART, we would want the infection rate among the partners of those getting ART to be reduced by at least half, say to half a percent per year. So the researchers would need a sample size large enough to reliably detect a difference of one half of a percent. How large would such a sample have to be?

Let’s say that we would want to be 90 percent sure that immediate treatment constitutes more effective prevention than either of the two alternatives before investing HIV prevention resources in this strategy. In the language of statisticians, this means we want the study to have a “statistical power” of 90 percent. If you have a copy of Stata, you can calculate the sample sizes necessary to have a 90% chance of finding a half a percentage point difference by just typing in the following command:

sampsi 0.005 0.01

The answer is that the immediate treatment group and each of the other groups of patients must have 6,650 HIV-negative partners. Since the adult infection rate in Malawi is about 25%, the total number of partners for all three groups would have to be at least: (3 * 6,650)/( 1 – 0.25) = 26,600. That’s a lot of people whom the researchers must convince to be tested after sex with their patients. And those who are HIV negative must consent to testing regularly for up to a year after that.

The sample size requirements are even worse if the intensive counseling arm works as one might hope it would. Suppose the control arm partners have an undiminished rate of new infections of one percent, and the intensive counseling arm has a reduced infection rate of only a half of a percent. In this case, to prove the superior effectiveness of ART, the researchers will have to show that the clients of the “counseling-plus-ART” group have an even smaller rate of new infections, say of a quarter of a percentage point per year. The sample size calculation in Stata can be done with the command, sampsi .005 0.0025, and yields a requirement of 13,348 subjects in each of the second and third arm of the study. This consideration increases to 45,000 the number of sexual partners who would have to be tested and followed ( = (13,348*2 + 6,650)/(1 - 0.25) ). Divided by 90 patients, the authors seem to be assuming that each patient will have on average at least 494 unique partners per year who (a) have no other infected partners and (b) return for testing for a full year after enrollment. These last two requirements might double or even triple the number of partners to be studied per patient, to 1,000 or 1,400 for each of the 90 recruited patients in the study.

By following the patients’ partners over more than one year, the sample size requirements can be reduced, but attrition problems are likely to increase. From where I sit, it seems that the chances of success would have been improved by aiming for perhaps five times as many newly HIV-infected subjects in order to reduce the number of sexual partners per subject to the more easily manageable range of 200 to 300 per subject.

It will be interesting to learn how the researchers have in fact designed their study, what the logic was of their design choices – and how successful they are at recruiting and following the number of patients and partners that they will need. But even if their work and that of other researchers supports the feasibility and effectiveness of immediate ART for prevention on a small scale, the intervention must meet two other tests proposed by Dr. Fauci: (1) feasibility of scale-up and (2) cost-effectiveness relative to alternative ways to prevent HIV infection or prolong life.

Given the four-year expected duration of the study and the difficulties I have suggested above, it seems to me that immediate treatment is years away from inclusion among the most promising tools for HIV prevention.