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Methodological Challenges in Biomedical HIV Prevention Trials (2008)

Chapter: 3 Design Considerations: Risk-Reduction Counseling

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Suggested Citation:"3 Design Considerations: Risk-Reduction Counseling." Institute of Medicine. 2008. Methodological Challenges in Biomedical HIV Prevention Trials. Washington, DC: The National Academies Press. doi: 10.17226/12056.
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3 Design Considerations: Risk-Reduction Counseling N umerous stakeholders have reached a consensus that investigators who work with at-risk, uninfected populations have an ethical obligation to provide behavioral risk-reduction counseling to par- ticipants in HIV prevention trials (UNAIDS, 2000, 2007). Yet determining the appropriate level or “standard” of risk-reduction intervention in bio- medical HIV prevention trials has been difficult. Two main reasons are the uncertainties about the effectiveness of specific behavioral interventions in reducing HIV infection risk in areas where many HIV prevention trials are conducted, and the uncertainties associated with adapting behavioral inter- ventions that have been shown to reduce risky behaviors or specific sexually transmitted infections (STIs) from one geographical or cultural setting to another. In addition, determining the appropriate standard risk-reduction intervention requires stakeholders to consider the sustainability and costs of the risk-reduction intervention. To help investigators address these dilemmas, this chapter first high- lights the ethical arguments for providing risk-reduction counseling to participants in an HIV prevention trial of a biomedical intervention. The next section then reviews findings from randomized, comparative studies of behavioral risk-reduction interventions in the United States and other countries, efforts to adapt these findings to different regions and cultural settings, and the need to evaluate the effectiveness of such adapted strat- egies in new settings. The final section argues for the incorporation of randomized comparisons of behavioral intervention strategies in late-stage biomedical intervention trial, highlights several ethical considerations that need to be addressed about the standard of behavioral risk-reduction inter- 88

DESIGN CONSIDERATIONS: RISK-REDUCTION COUNSELING 89 ventions in future HIV prevention trials, and makes recommendations for practice and research. Ethical Reasons for Risk-Reduction Counseling In discussions over the past decade about the ethics of vaccine trials, researchers, community representatives, human rights advocates, and ethi- cists reached broad agreement—based on several ethical principles, includ- ing beneficence, autonomy, and justice—that participants in clinical trials of HIV prevention interventions should receive risk-reduction counseling, and access to condoms and other means to reduce their risk of becoming infected with HIV (UNAIDS, 2000, p. 522). Ethicists have advanced three reasons for this obligation. As discussed by Lie et al. (2006): “The ethical requirements to provide counselling and condoms as part of HIV preventive trials . . . are based on the general requirements (1) to provide relevant information to participants in clinical trials, (2) not to impede or place any barriers on access to known preven- tive methods, and (3) to actively promote the use of known preventive methods” (p. 522). Ethicists have put forth several other considerations to justify provision of known prevention methods to participants. First, they argue that investi- gators must attempt to counterbalance any increased risk that participants will become HIV infected owing to disinhibition: that is, that they may engage in more risky behavior if they erroneously believe they are protected by the test intervention. Thus the duty to minimize risks in clinical trials dictates that investigators provide counseling on methods to prevent HIV infection (Lie et al., 2006). Second, some ethicists have suggested that providing such counseling to trial participants is a form of “justice as reciprocity.” That is, because participants contribute to the social good, they are owed recompense in the form of HIV prevention counseling and access to information and technolo- gies prevention methods that can reduce their risk of HIV infection (Lie et al., 2006). Finally, some ethicists have argued that participants should receive risk-reduction counseling prevention methods because of the “fundamental ethical requirement for any person to do what they can to help others in need” (Lie et al., 2006, p. 523). This Good Samaritan proposition imposes special duties on those who conduct clinical trials (Lie et al., 2006). However, despite widespread agreement that participants in clinical   ie et al. (2006) discuss these principles in their examination of the ethical obligation of re- L searchers to provide male circumcision as part of the prevention standard for HIV prevention trials, but these arguments also apply to risk-reduction counseling and condom promotion.

90 METHODOLOGICAL CHALLENGES IN HIV PREVENTION TRIALS trials should receive risk-reduction interventions, considerable uncertainty remains about what the nature and intensity of such interventions should be. Some ethicists have called for “high-quality counseling” (Wolf and Lo, 2001). UNAIDS and the World Health Organization (WHO) recommend a more comprehensive standard, suggesting that investigators should provide “appropriate counseling and access to all state of the art HIV risk-reduction methods . . . to participants throughout the duration of the biomedical HIV prevention trial” (UNAIDS, 2007, p. 47). UNAIDS and WHO also call for adding new HIV risk-reduction methods “based on consultation among all research stakeholders including the community, as they are scientifically validated or as they are approved by the relevant authorities” (UNAIDS, 2007, p. 47). Uncertainty about the appropriate standard of care in biomedical HIV prevention trials stems in part from ethical considerations. For example, should the standard risk-reduction intervention be the one shown to be most effective, regardless of cost or sustainability? The ethical uncertainties are compounded by the lack of definitive findings on the effectiveness of behavioral risk-reduction interventions in many of the resource-poor set- tings where biomedical HIV prevention trials are conducted. Investigators have conducted only a limited number of studies of the efficacy of behav- ioral risk-reduction interventions in these settings. Indeed, a significant amount of the research evaluating the efficacy of behavioral risk-reduction interventions has occurred in the United States. This limitation is com- pounded by the difficulty of extrapolating behavioral risk-reduction inter- ventions shown to be efficacious in one setting and population to different settings with different populations, risk behaviors, and cultural norms. In particular, behavioral risk-reduction interventions that have been shown to be efficacious in developed countries may not always be easily transfer- able to settings and populations in developing countries. Finally, there is uncertainty about the effectiveness of behavioral intervention strategies in reducing the risk of HIV infection. The next section reviews the evidence on the effectiveness of behavioral risk-reduction interventions in reducing risk behaviors, with an emphasis on sexual behaviors, the incidence of STIs, and incidence of HIV infection. Effectiveness of Behavioral Risk-Reduction Interventions Voluntary Counseling and Testing (VCT Programs) Voluntary counseling and testing (VCT) is widely used throughout the world to prevent HIV acquisition and transmission, and to identify indi- viduals for treatment or monitoring. A number of nonrandomized studies

DESIGN CONSIDERATIONS: RISK-REDUCTION COUNSELING 91 have assessed the impact of VCT on risky behavior, but results from ran- domized trials are limited. Perhaps the most definitive study of the effectiveness of VCT on reported risk behavior was that of the Voluntary HIV-1 Counseling and Testing Efficacy Study Group (2000), which conducted a trial of 3,120 individuals and 586 couples in Kenya, Tanzania, and Trinidad. Participants were randomized to receive VCT versus basic health information. The primary efficacy endpoint was self-reported unprotected intercourse with a nonprimary partner by the time of the 6-month study visit. The study showed that individuals assigned to VCT reported a signifi- cantly greater reduction in unprotected intercourse with a nonprimary part- ner than individuals assigned to basic health information (overall odds ratio [OR] = 0.68, 95% confidence interval [CI]: 0.56–0.82). In other analyses, the study showed that couples randomized to VCT reported significantly greater reductions in unprotected intercourse with each another than did couples randomized to basic health information. The study found no signifi- cant differences in reported unprotected intercourse between participants and unenrolled partners (OR = 1.09, 95% CI: 0.92–1.29). The trial also did not detect a beneficial impact from VCT on the incidence of STIs (OR = 0.80, 95% CI: 0.53–1.20), although the study was not designed for that endpoint. Although there is limited evidence of the effectiveness of VCT in reducing some sexual risk behaviors, overall the findings are mixed. This sentiment is echoed in a recent meta-analysis of VCT of behavioral risk- reduction interventions in developing countries based on papers published between 1990 and 2005, which included the VCT Study Group (2000) study and 6 nonrandomized studies (Allen et al., 1992; Muller et al., 1995; Wang et al., 2002; Farquhar et al., 2004; Kawichai et al., 2004; Matovu et al., 2005). Denison and colleagues (2007) found that the combined data from these showed a moderate effect of VCT on unprotected sex (OR = 1.69; 95% CI: 1.25–2.31) but VCT showed no significant effect on number of sex partners (OR = 1.22; 95% CI: 0.89–1.67). Randomized studies comparing the effect of different types of VCT on HIV incidence are very limited. Corbett et al. (2007) assessed the relative efficacy of two forms of VCT in Zimbabwe. The investigators found no evidence that more intensive VCT (rapid testing and counseling provided onsite) reduced HIV infection rates compared with standard VCT (provid- ing participants with prepaid vouchers for use with an external provider). Studies Evaluating Behavioral Risk-Reduction Interventions Numerous studies and meta-analyses have compared different behav- ioral risk-reduction interventions that aim to reduce the risk of HIV infec-

92 METHODOLOGICAL CHALLENGES IN HIV PREVENTION TRIALS tion or transmission. These studies have involved different populations, including injecting drug users, men who have sex with men (MSM), het- erosexuals, adolescents, ethnic and racial minorities, and HIV-infected indi- viduals. Most studies have used a behavioral endpoint, such as self-reported unprotected sex, but some have examined biological endpoints, including the acquisition of non-HIV STIs, and a few have used HIV infection. Meta- analyses of the behavioral risk-reduction interventions for these different populations have been reported by Copenhaver et al. (2006) for inject- ing drug users, Johnson et al. (2002) and Herbst et al. (2005) for MSM, Neumann et al. (2002) for heterosexuals, Mullen et al. (2002) for adoles- cents, Crepaz et al. (2007) for ethnic and racial minorities, and Johnson et al. (2005) for persons living with HIV. One of the earliest and most important trials of behavioral risk-reduction interventions was Project RESPECT, a randomized, controlled trial conducted at five public STI clinics in the United States. This study compared the efficacy of two personalized (“client-centered”) HIV/STI counseling interventions in increasing rates of condom use and reducing STIs among heterosexual clients (Kamb et al., 1998). The two test interventions were (1) enhanced counsel- ing, involving four visits and a total of 200 minutes of counseling; and (2) brief counseling, involving two visits and a total of 40 minutes of counseling. The study compared these interventions with a control arm given didactic prevention messages. The study found that self-reported condom use was significantly higher in subjects randomized to each of the counseling arms than in subjects randomized to the didactic message arm (P < 0.05 for each comparison). This was the first randomized trial to show that client-centered counseling could reduce the number of new STIs. After 6 months, 30 percent fewer subjects in the counseling arms than in the didactic arm had acquired new STIs (P < 0.01 for each comparison). The study found no significant dif- ferences between the more intense and less intense risk-reduction counsel- ing, so the investigators suggested that clinics provide the short counseling intervention. Lyles and colleagues (2007) recently conducted a systematic review of randomized and nonrandomized U.S.-based research from 2000 to 2004 on behavioral risk-reduction interventions, to identify those with the best evidence of efficacy in reducing HIV risk behaviors. Their review focused on behavioral risk-reduction interventions delivered to the individual or small group, and evaluated them in three domains: study design, implementation and analysis, and strength of evidence. To meet the strength-of-evidence criterion, a study had to have shown a statistically significant (P ≤ 0.05) positive effect for at least one outcome measure at least three months post-intervention, and no significant negative evidence for reducing HIV risk. A study also had to have a retention rate of

DESIGN CONSIDERATIONS: RISK-REDUCTION COUNSELING 93 70 percent, base its results on at least 50 participants per arm, and avoid any limitations considered a fatal flaw. One hundred behavioral intervention studies met the criteria for eligi- bility for review. Of those, 18 met the criteria for demonstrating a positive intervention effect, and were thus identified as “best evidence.” Fourteen of the studies targeted uninfected populations at risk for HIV. These were conducted among drug users (four studies), heterosexual adults (six stud- ies), MSM (two studies), and adolescents (two studies). All “best-evidence” behavioral risk-reduction interventions applied at least one theory or model on behavioral change. These included social cognitive theory, social learning theory, the AIDS risk-reduction model, the information-motivational-behavior model, and the theory of gender and power. Interventions were typically conducted in research sites (eight stud- ies), community or public areas (five studies), health care clinics (four stud- ies), HIV or STI clinics (three studies), or community-based agencies (three studies). Although the content of these interventions differed, most entailed building technical (such as condom use), personal, or interpersonal skills. The majority of the significant intervention effects were based on the endpoint of self-reported reduction of unprotected sexual intercourse (12 studies). Studies of the five interventions targeting injecting drug users also measured the effect on self-reported injection-related risk behaviors, such as frequency of injection or needle sharing with three of the five finding a reduction. Lyles and colleagues (2007) identified four randomized interventions that demonstrated a significant reduction in incident STIs: Baker and col- leagues (2003) compared the effect of two 16-session group interventions that provided skills training versus health education in 287 heterosexual women in Washington state. The endpoint was the development of an STI, including gonorrhea, mucopurulent cervicitis (including chlamydia), pelvic inflammatory disease, syphilis, HIV, or herpes simplex virus 2 (HSV-2). During follow-up, 18 of 104 women in the control group developed an STI, compared with 9 of 105 women in the skills-training group (P = 0.05), with mucopurulent cervicitis (14 cases) and HSV-2 (7 cases) the main STIs. No women in either arm became HIV infected. In the second study, DiClemente et al. (2004) conducted a randomized comparison of an intervention emphasizing ethnic and gender pride, HIV knowledge, communication, condom skills, and healthy relationships with a control emphasizing exercise and nutrition in 522 sexually experienced African American girls aged 14 to 18 in the U.S. South. STI infection (chlamydia, trichomonas, gonorrhea) at the study’s 6-month or 12-month assessment was a secondary endpoint. The authors reported a significantly lower risk of chlamydia in the experimental arm compared with the control arm (OR = 0.17, 95% CI: 0.03–0.92, P = 0.04).

94 METHODOLOGICAL CHALLENGES IN HIV PREVENTION TRIALS Third, Wingood and colleagues (2004) reported on a randomized trial of 366 women living with HIV in Alabama and Georgia. That study com- pared an intervention emphasizing gender pride, participants’ personal networks, knowledge of HIV transmission, communication and condom skills, and healthy relationships with a control arm receiving health promo- tion. A secondary endpoint of the trial was the occurrence of chlamydia or gonorrhea during the 12-month follow-up period. The intervention group experienced a significantly lower rate of chlamydia and gonorrhea than the control group (OR = 0.20, 95% CI: 0.1–0.6, P = 0.006). Finally, Shain and colleagues (2004) reported on a two-year randomized trial comparing standard and enhanced gender- and culture-specific coun- seling offered in small groups (to 209 and 232 women, respectively) with interactive STI counseling (249 women) in minority women from Texas. The primary endpoint—acquisition of chlamydia or gonorrhea—occurred significantly less often in the intervention groups (15.4 percent versus 39.8 percent, P = 0.004) during the entire follow-up period. Only a few randomized trials of behavioral interventions have evalu- ated HIV infection as the study endpoint. Lyles et al. (2007) reviewed one U.S.-based study that used HIV infection as the study endpoint: Project EXPLORE (HIVNET 015) compared the efficacy of an intense behavioral intervention to that of standard risk-reduction counseling among U.S. MSM (EXPLORE Study Team, 2004), with HIV infection as primary end- point and behavioral outcomes, including unprotected anal intercourse and unprotected anal intercourse with a serodiscordant partner, as secondary endpoints. (The control group received the “brief” counseling intervention recommended by the Project RESPECT trial noted above.) The study found that the rates of unprotected receptive anal intercourse with HIV-positive and unknown-status partners was 20.5 percent lower in the intervention arm than in the control arm (OR = 0.80, 95% CI: 0.71–0.89). The observed rate of HIV infection was 18.2 percent lower in the intervention group than in the standard group, but the difference was not statistically significant (95% CI for difference: –5% to +36%). Several behavioral intervention HIV prevention trials done outside the United States were designed and powered to assess HIV infection as an endpoint. Kamali et al. (2003) undertook a large community-level random- ized trial comparing the efficacy of a behavioral intervention alone, and a behavioral intervention plus STI control, with routine care in preventing HIV infection in 18 communities in Uganda. The study enrolled more than 40,000 subjects, of whom more than 300 became HIV infected. However, the study found no significant difference in HIV incidence between the behavioral counseling arm (incidence rate ratio = 0.94, 95% CI: 0.60–1.45, P = 0.72) or the behavioral-plus-STI arm (incidence rate ratio = 1.00,

DESIGN CONSIDERATIONS: RISK-REDUCTION COUNSELING 95 95% CI: 0.63–1.58, P = 0.98) and the control arm, although both interven- tions reduced the rate of specific non-HIV STIs. Ross and colleagues (2007) conducted a community-randomized trial in Tanzania that compared a specially designed program of behavioral and educational interventions with standard activities in school-aged youth, with HIV incidence as a primary endpoint. Few (5) seroconversions occurred among the young men, so the study could not adequately compare groups. Among young women, the study found no significant difference in HIV incidence between the intervention and control groups (Relative risk [RR] = 0.75, 95% CI: 0.34–1.66). Nor did it find significant differences between the interventions in either gender with respect to HSV-2 infection, the second primary endpoint. Gregson and colleagues (2007) reported the results of a cluster-random- ized trial in eastern Zimbabwe. The intervention group received targeted and population-level strategies to promote safer sexual behavior and to improve treatment of STIs that facilitate HIV. Both the intervention and control groups received standard government services plus social marketing of condoms. There was no evidence that the intervention communities had a lower risk of HIV infection, other STIs, or high-risk behaviors than the control communities (incidence rate ratio = 1.27, 95% CI: 0.92–1.75). Two additional behavioral risk-reduction trials using HIV endpoints are underway. First, the National Institute of Mental Health (NIMH) Col- laborative HIV/STD Prevention Trial is a community-level HIV prevention intervention study conducted in international settings, using behavioral outcomes and HIV infection as the primary study endpoints. The trial is evaluating the effectiveness of an intervention using a community popular opinion leader to convey HIV prevention messages to the community. The study phases consist of an ethnographic study, pilot studies, an epide- miological study, and a community-randomized trial. Results are not yet available. The second study, Project Accept (HPTN 043), is a community- randomized HIV prevention trial involving 34 communities in South Africa, Tanzania, and Zimbabwe, and 14 communities in Thailand (Morin et al., 2006). These communities are being randomized to receive either a com- munity-based HIV voluntary counseling and testing (CBVCT) intervention plus standard clinic-based VCT (SVCT), or SVCT alone. The CBVCT intervention aims to make VCT more available in community settings, to engage communities through outreach, and to provide posttest support. These strategies are designed to change community norms and reduce the risk of HIV infection among all members of a community, whether or not they participate directly in the intervention. This is the first international randomized, controlled phase 3 trial to determine the efficacy of a behav- ioral or social science intervention with HIV incidence as an endpoint.

96 METHODOLOGICAL CHALLENGES IN HIV PREVENTION TRIALS In sum, behavioral risk reduction interventions have lowered the inci- dence of specific self-reported sexual risk behaviors and specific non-HIV STIs. However, none of these strategies has yet shown a beneficial effect in reducing the incidence of HIV infection. Adapting Efficacious Behavioral Risk-Reduction Interventions If an intervention has been shown to be effective in one setting, it is important to adapt it for use by a diverse array of providers of HIV pre- vention services (NIH, 2007; Wingood and DiClemente, 2008). This often requires providers to enhance the acceptability of the intervention among a new target population. This is particularly true if an organization in a developing country would like to use an intervention designed in the United States or other developed countries. If providers do not pay attention to the cultural context and HIV-related risks of the new target population, the intervention may remain faithful to the underlying theoretical framework and core elements but lack relevance, sustainability, and acceptability. Researchers have recently developed several frameworks to guide the adaptation of a HIV behavioral intervention to a different setting. For example, the Centers for Disease Control and Prevention (CDC) has articu- lated the Map of Adaptation Process (MAP) (McKleroy et al., 2006). This approach includes an assessment phase, in which an organization evaluates the target population’s HIV risk, the appropriateness of the behavioral risk-reduction intervention, and the organization’s capacity to implement it. The assessment phase is followed by a preparation phase, in which the organization adapts the evidence-based intervention: then comes the imple- mentation phase, in which the organization pilots the adapted intervention. Other adaptation models take a more stringent approach, and encourage evaluating the adapted behavioral risk-reduction intervention as part of a phase 2B trial (Wingood and DiClemente, 2008). A number of studies have adapted behavioral HIV risk-reduction inter- ventions shown to be efficacious in developed countries to developing country settings. For example, Kalichman and colleagues (2005) relied on collaborative interdisciplinary workshops to adapt a brief theory-based HIV risk-reduction counseling intervention developed in the United States for use in an STI clinic in South Africa. Wingood and DiClemente (2008) used a process known as theatre testing to adapt an efficacious behav- ioral risk-reduction intervention developed in the United States. for young Zulu-speaking women in KwaZulu-Natal, South Africa. In theatre testing, facilitators implement the core elements of an intervention while integrating new materials and activities to enhance its cultural relevance and efficacy for the target population.

DESIGN CONSIDERATIONS: RISK-REDUCTION COUNSELING 97 However, behavioral risk reduction interventions that have been shown to be efficacious in one setting may not necessarily be efficacious in another. Thus, when adapting an HIV intervention to a new setting and population, investigators should evaluate its effectiveness in the new target population, and identify potential ways to enhance it. Evaluating Behavioral Risk-Reduction Interventions in the Context of a Biomedical Intervention Trial If definitive evidence on the effectiveness of behavioral risk-reduction interventions in settings where biomedical HIV prevention trials are planned were to become available, investigators would face questions on the cost and sustainability of integrating behavioral risk-reduction interventions into such trials. Unfortunately, as noted, researchers face considerable uncertainty about which behavioral risk-reduction interventions are most effective in many settings where biomedical HIV prevention trials occur. In the face of such uncertainty, it becomes critical to undertake research that may provide evidence on this question. Such studies are necessary because behavioral risk-reduction interventions will remain an important component of the overall HIV prevention effort regardless of the efficacy of biological approaches. The committee believes strongly that integrat- ing that research into a biomedical intervention trial provides an excellent opportunity to move forward on both fronts. Given such uncertainty, however, communities must participate in deci- sions regarding the conduct of trials, including the choice of behavioral interventions. UNAIDS and WHO have advocated that the “technique, frequency, and message content of counseling should be agreed upon by the community–government–investigator–sponsor partnership” (UNAIDS, 2007, p. 49). Chapter 6 explores specific study designs, such as factorial designs, for late-stage effectiveness trials of biomedical prevention interventions that also allow a comparative evaluation of two or more behavioral risk- reduction interventions. As noted, the choice of such strategies should reflect current knowledge about which strategies have been shown to be effective and can be adapted to the setting of the biomedical prevention trial, and which strategies the community, donors, researchers, and other relevant stakeholders consider feasible and sustainable. When two or more behavioral strategies are implemented during a biomedical intervention trial, they must satisfy principles of research ethics, just as the biomedical interventions must. The committee recognizes that the incorporation of a behavioral inter- vention comparison into a biomedical intervention trial will increase the tri- al’s logistical complexity. For example, if an individual and group behavioral

98 METHODOLOGICAL CHALLENGES IN HIV PREVENTION TRIALS intervention were provided by a site, it would create additional scheduling, training, and manpower responsibilities for the site. On the other hand, if some sites were randomized to evaluate one behavioral intervention while the rest were randomized to evaluate another, using the ideas of cluster ran- domization (Chapter 10), the additional logistical complexity to a site would be far less. For either scenario, careful site preparation should be adequate to allow the incorporation of an evaluation of behavioral interventions, and the potential gains from finding improved behavioral interventions would provide lasting benefits to the community. In addition to the need for clinical equipoise among these behav- ioral strategies, other critical ethical questions about the standard of care, costs and sustainability, and obligations of researchers must be answered. Although it is outside the scope of the committee’s review to address these issues, we highlight some of the critical questions below. Standard of Care • What is the minimal or standard behavioral intervention that the trial can ethically use as a control group? • Because most uninfected populations in developing countries do not receive individualized HIV behavioral counseling outside the context of a research study, what defines the “community standard” for risk-reduction counseling? • Can the trial ethically limit the counseling in a control group to the level already (nominally) provided in a particular community, when more intensive behavioral interventions have not been shown to be effective in reducing HIV infection risk in that context? Costs and Sustainability • What is the next course of action if an expensive behavioral risk- reduction intervention is shown to be highly efficacious in developed coun- tries, but is not sustainable in developing countries? Obligations of Researchers • What is the duty for those studying biomedical investigations to undertake concurrent investigations of behavioral risk-reduction interventions? • Should risk-reduction counseling that occurs during a biomedical HIV prevention trial be provided through an organization that is inde- pendent of the investigators? If the risk-reduction interventions were fully effective, none of the participants in the trial would become infected, and

DESIGN CONSIDERATIONS: RISK-REDUCTION COUNSELING 99 there could be no evaluation of the efficacy of the biomedical intervention. To address any possible conflict between the desires of researchers to pro- vide counseling and their wish to demonstrate benefits from the biomedical intervention, UNAIDS and WHO suggest investigators consider having an independent organization counsel participants as one way to minimize such conflicts (UNAIDS, 2000). There are no simple solutions to such complex challenges. The answers to these questions will in general vary with different intervention trials and over time. It is important, however, that in decisions about these issues be determined through a fair and transparent process. Daniels and Sabin have proposed a framework for setting priorities in resource allocation (Daniels and Sabin, 1997) which has also been applied to roll-out of ARVs (Daniels, 2005) and has bearing on the resolution of these questions. According to this framework, a fair process would dictate the following: • Decisions should be based on evidence, and reasons for those deci- sions should be contextually relevant. This requires that all stakeholders who will be affected by the priority-setting process have some say, so the effort to make decisions and set priorities takes into account a variety of values. • The rationale for decisions and disagreements must be publicly accessible. • Appeals must be allowed, so decisions can be reconsidered in light of new evidence or arguments. Such a priority-setting process could be useful in clinical research in determining whether specific interventions meet the needs of a community in a particular setting. SUMMARY In late-stage HIV prevention trials of biomedical interventions, investi- gators and donors also have an excellent and unique opportunity to evalu- ate and compare different behavioral risk-reduction interventions as part of the trial’s research objectives (see Chapter 10 for specific study designs). The identification of improved behavioral interventions will benefit at-risk populations even if the biomedical intervention being studied has no effi- cacy, and will potentiate its effectiveness if it does have efficacy. Recommendation 3-1: Given the lack of evidence on the effectiveness of behavioral risk-reduction interventions in settings where many HIV biomedical trials are planned, investigators planning such trials should

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102 METHODOLOGICAL CHALLENGES IN HIV PREVENTION TRIALS Lyles, C. M., L. S. Kay, N. Crepaz, J. H. Herbst, W. F. Passin, A. S. Kim, S. M. Rama, S. Thadiparthi, J. B. DeLuca, and M. M. Mullins. 2007. Best-evidence interventions: Findings from a systematic review of HIV behavioral interventions for U.S. populations at high risk, 2000–2004. American Journal of Public Health 97(1):133-143. Matovu, J. K., R. H. Gray, F. Makumbi, M. J. Wawer, D. Serwadda, G. Kigozi, N. K. Sewankambo, and F. Nalugoda. 2005. Voluntary HIV counseling and testing acceptance, sexual risk behavior and HIV incidence in Rakai, Uganda. AIDS 19(5):503-511. McKleroy, V. S., J. S. Galbraith, B. Cummings, P. Jones, C. Harshbarger, C. Collins, D. Gelaude, J. W. Carey, and A. Team. 2006. Adapting evidence-based behavioral interventions for new settings and target populations. AIDS Education and Prevention 18(4 Suppl A):59-73. Morin, S. F., G. Khumalo-Sakutukwa, E. D. Charlebois, J. Routh, K. Fritz, T. Lane, T. Vaki, A. Fiamma, and T. J. Coates. 2006. Removing barriers to knowing HIV status: Same-day mobile HIV testing in Zimbabwe. Journal of Acquired Immune Deficiency Syndromes 41(2):218-224. Mullen, P. D., G. Ramirez, D. Strouse, L. V. Hedges, and E. Sogolow. 2002. Meta-analysis of the effects of behavioral HIV prevention interventions on the sexual risk behavior of sexually experienced adolescents in controlled studies in the United States. Journal of Acquired Immune Deficiency Syndromes 30(Suppl 1):S94-S105. Muller, O., S. Sarangbin, K. Ruxrungtham, W. Sittitrai, and P. Phanuphak. 1995. Sexual risk behaviour reduction associated with voluntary HIV counselling and testing in HIV infected patients in Thailand. AIDS Care 7(5):567-572. Neumann, M. S., W. D. Johnson, S. Semaan, S. A. Flores, G. Peersman, L. V. Hedges, and E. Sogolow. 2002. Review and meta-analysis of HIV prevention intervention research for heterosexual adult populations in the United States. Journal of Acquired Immune Deficiency Syndromes 30(Suppl 1):S106-S117. NIH (National Institutes of Health). 2007. Conference on building the science of dissemina- tion and implementation in the service of public health. Bethesda, MD. Ross, D. A., J. Changalucha, A. I. Obasi, J. Todd, M. L. Plummer, B. Cleophas-Mazige, A. Anemona, D. Everett, H. A. Weiss, D. C. Mabey, H. Grosskurth, and R. J. Hayes. 2007. Biological and behavioural impact of an adolescent sexual health intervention in Tanzania: A community-randomized trial. AIDS 21(14):1943-1955. Shain, R. N., J. M. Piper, A. E. Holden, J. D. Champion, S. T. Perdue, J. E. Korte, and F. A. Guerra. 2004. Prevention of gonorrhea and chlamydia through behavioral inter- vention: Results of a two-year controlled randomized trial in minority women. Sexually Transmitted Diseases 31(7):401-408. UNAIDS. 2000. Ethical considerations in HIV preventive vaccine research. Geneva, Switzer- land: UNAIDS. UNAIDS. 2007. Ethical considerations in biomedical HIV prevention trials. Geneva, Swit- zerland: UNAIDS. Voluntary HIV-1 Counseling and Testing Efficacy Study Group. 2000. Efficacy of voluntary HIV-1 counselling and testing in individuals and couples in Kenya, Tanzania, and Trini- dad: A randomised trial. The Voluntary HIV-1 Counseling and Testing Efficacy Study Group. Lancet 356(9224):103-112. Wang, X., J. Ma, Z. Xu, H. Liu, Y. Zhang, and C. Han. 2002. Effectiveness of post-exposure prophylaxis using live attenuated hepatitis alpha vaccine (h(2) strain) among schoolchil- dren. Zhonghua Yi Xue Za Zhi 82(14):955-957. Wingood, G., and R. DiClemente. 2008. The ADAPT-ITT model: A novel method of adapting evidence-based HIV interventions. Journal of Acquired Immune Deficiency Syndromes 47(Suppl 1):S40-S46.

DESIGN CONSIDERATIONS: RISK-REDUCTION COUNSELING 103 Wingood, G. M., R. J. DiClemente, I. Mikhail, D. L. Lang, D. H. McCree, S. L. Davies, J. W. Hardin, E. W. Hook, 3rd, and M. Saag. 2004. A randomized controlled trial to reduce HIV transmission risk behaviors and sexually transmitted diseases among women living with HIV: The WILLOW program. Journal of Acquired Immune Deficiency Syn- dromes 37(Suppl 2):S58-S67. Wolf, L., and B. Lo. 2001. Ethical dimensions of HIV/AIDS. http://hivinsite.ucsf.edu/ InSite?page=kb-08-01-05#S2X (accessed December 12, 2007).

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The number of people infected with HIV or living with AIDS is increasing at unprecedented rates as various scientists, organizations, and institutions search for innovative solutions to combating and preventing the disease. At the request of the Bill & Melinda Gates Foundation, Methodological Challenges in Biomedical HIV Prevention Trials addresses methodological challenges in late-stage nonvaccine biomedical HIV prevention trials with a specific focus on microbicide and pre-exposure prophylaxis trials. This book recommends a number of ways to improve the design, monitoring, and analysis of late-stage clinical trials that evaluate nonvaccine biomedical interventions. The objectives include identifying a beneficial method of intervention, enhancing quantification of the impact, properly assessing the effects of using such an intervention, and reducing biases that can lead to false positive trial results.

According to Methodological Challenges in Biomedical HIV Prevention Trials, the need to identify a range of effective, practical, and affordable preventive strategies is critical. Although a large number of promising new HIV prevention strategies and products are currently being tested in late-stage clinical trials, these trials face a myriad of methodological challenges that slow the pace of research and limit the ability to identify and fully evaluate effective biomedical interventions.

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