Victor DeGruttola

Biomarkers and surrogate endpoints: Preferred definitions and conceptual framework*

genome are dramatically reshaping the research and development pathways for drugs, vaccines, and diagnostics. The growth in the number of molecular entities entering the drug development pipeline has accelerated as a consequence of powerful discovery and screening technologies such as combinatorial chemistry, mass spectrometry, high throughput screening, celland tissue-based DNA microarrays, and proteomic approaches.1 As a consequence, there is an escalating number of therapeutic candidates, which has caused the need for new technologies and strategies to streamline the process to make safe and effective therapies available to patients. One approach to the achievement of more expeditious and informative therapeutic research is the use of precise clinical measurement tools to determine disease progression and the effects of interventions (drugs, surgery, and vaccines). For example, gene-based approaches such as single nucleotide polymorphism maps are now being developed to distinguish the molecular and cellular basis for variations in clinical response to therapy.2 Another approach is the use of a wide array of analytical tools to assess biological parameters, which are referred to as biomarkers. Biomarker measurements can help explain empirical results of clinical trials by relating the effects of interventions on molecular and cellular pathways to clinical responses. In doing so, biomarkers provide an avenue for researchers to gain a mechanistic understanding of the differences in clinical response that may be influenced by uncontrolled variables (for example, drug metabolism). There are a variety of ways that biomarker measurements can aid in the development and evaluation of COMMENTARY

Modeling the Relationship of Survival to Longitudinal Data Measured with Error. Applications to Survival and CD4 Counts in Patients with AIDS

Abstract A question that has received a great deal of attention in evaluating new treatments in acquired immune deficiency syndrome (AIDS) clinical trials is that of finding a good surrogate marker for clinical progression. The identification of such a marker may be useful in assessing the efficacy of new therapies in a shorter period. The number of CD4-lymphocyte counts has been proposed as such a potential marker for human immune virus (HIV) trials because of its observed correlation with clinical outcome. But to evaluate the role of CD4 counts as a potential surrogate marker, we must better understand the relationship of clinical outcome to an individuals CD4 count history over time. The Cox proportional hazards regression model is used to study the relationship between CD4 counts as a time-dependent covariate and survival. Because the CD4 counts are measured only periodically and with substantial measurement error and biological variation, standard methods for estimating the parameters in the Cox mod...

Use of Changes in Plasma Levels of Human Immunodeficiency Virus Type 1 RNA to Assess the Clinical Benefit of Antiretroviral Therapy

Data from 1330 human immunodeficiency virus type 1 (HIV-1)-infected patients enrolled in seven antiretroviral treatment trials were analyzed to characterize the clinical benefit of treatment-mediated reductions in plasma HIV-1 RNA levels. The risk of a new AIDS-defining event or death was reduced proportionally to the magnitude of the reduction of the HIV-1 RNA level during the first 6 months of therapy. Pretherapy HIV-1 RNA levels were prognostic independently of on-therapy levels. In addition, the reduction in risk associated with any given reduction of the level of HIV-1 RNA did not vary by pretherapy level. Having either a reduction in HIV-1 RNA level or an increase in CD4+ lymphocyte count, or both, was associated with a delay in clinical disease progression. This indicates that patient prognosis should be assessed using both HIV-1 RNA and CD4+ lymphocyte responses to therapy.

INFECTIOUSNESS OF HIV BETWEEN MALE HOMOSEXUAL PARTNERS

To estimate the risk of transmission of HIV per receptive anal sexual contact, 329 homosexually-active men, representing 155 sexual partnerships, were enrolled into a study. Information on HIV infection status and sexual behavior within and outside the primary relationship was collected. Of these 329 men, 24 had AIDS and 31 had ARC. Of the 155 couples, 35 consisted of partners that were both HIV +; 62 of partners that were both HIV-; and 58 were discordant. A binomial model was fit to data obtained in the first visit to estimate per contact risk of HIV transmission. Assuming a constant risk of transmission per sexual contact between infected and uninfected partners, the estimated risk is about 5 to 30 per 1000 receptive anal exposures to ejaculate. Although the average risk of HIV transmission per sexual contact appears to be low, there appears to be great variability in infectivity. To model this variability over time and across individuals, more complex models must be fit to longitudinal studies of sexual partners.

Five-year outcomes of initial patients treated in Botswana's National Antiretroviral Treatment Program

Background: Antiretroviral treatment (ART) initiatives have now been established in many sub-Saharan African countries showing early benefits. To date, few results are available concerning long-term clinical outcomes in these treatment programs. Methods: Response to ART is described in the first HIV-1C-infected adults enrolled in the Botswana Antiretroviral Treatment Program in 2002. Data analysis was conducted on available longitudinal data up to 1st April 2007. Results: Six hundred thirty-three severely immunodeficient patients with a median CD4+ cell count of 67 cells/μl were initiated on non-nucleoside reverse transcriptase inhibitor-based combination ART and followed for a median of 41.9 months. The median CD4+ cell count increases were 169, 302, and 337 cells/μl at 1, 3, and 5 years, respectively. The percentages of patients with a viral load of less than 400 copies/ml at 1, 3, and 5 years were 91.3, 90.1, and 98.3%, respectively. Seventy-five percent of patients did not miss a single, or missed only one, monthly ART pickup per year with a mean pickup rate of 92.5%. The Kaplan–Meier survival estimates [95% confidence interval (CI)] at 1, 3, and 5 years were 82.7% (81.2 and 84.3%), 79.3% (77.6 and 81.0%), and 79.0% (77.3 and 80.7%), respectively. At 6 months, the risk of treatment modification for anemia was 6.94% (5.9 and 8.0%) for cutaneous hypersensitivity reactions, 1.3% (0.8 and 1.7%), and 1.1% (0.7 and 1.6%) for hepatotoxicity. Conclusion: This initial group of adults on ART in Botswana had excellent sustained immunologic, virologic, and clinical outcomes for up to 5 years of follow-up with low mortality among those surviving into the second year of ART.

Treatment with Amprenavir Alone or Amprenavir with Zidovudine and Lamivudine in Adults with Human Immunodeficiency Virus Infection

Amprenavir is a human immunodeficiency virus (HIV) protease inhibitor with a favorable pharmacokinetic profile and good in vitro activity. Ninety-two lamivudine- and protease inhibitor-naive individuals with >/=50 CD4 cells/mm3 and >/=5000 HIV RNA copies/mL were assigned amprenavir (1200 mg) alone or with zidovudine (300 mg) plus lamivudine (150 mg), all given every 12 h. After a median follow-up of 88 days, the findings of a planned interim review resulted in termination of the amprenavir monotherapy arm. Among 85 subjects with confirmed plasma HIV RNA determination, 15 of 42 monotherapy versus 1 of 43 triple-therapy subjects had an HIV RNA increase above baseline or 1 log10 above nadir (P=.0001). For subjects taking triple therapy at 24 weeks, the median decrease in HIV RNA was 2.04 log10 copies/mL, and 17 (63%) of 27 evaluable subjects had <500 HIV RNA copies/mL. Treatment with amprenavir, zidovudine, and lamivudine together reduced the levels of HIV RNA significantly more than did amprenavir monotherapy.

The Setpoint Study (ACTG A5217): Effect of Immediate Versus Deferred Antiretroviral Therapy on Virologic Set Point in Recently HIV-1–Infected Individuals

BACKGROUND The benefits of antiretroviral therapy during early human immunodeficiency virus type 1 (HIV-1) infection remain unproved. METHODS A5217 study team randomized patients within 6 months of HIV-1 seroconversion to receive either 36 weeks of antiretrovirals (immediate treatment [IT]) or no treatment (deferred treatment [DT]). Patients were to start or restart antiretroviral therapy if they met predefined criteria. The primary end point was a composite of requiring treatment or retreatment and the log(10) HIV-1 RNA level at week 72 (both groups) and 36 (DT group). RESULTS At the June 2009 Data Safety Monitoring Board (DSMB) review, 130 of 150 targeted participants had enrolled. Efficacy analysis included 79 individuals randomized ≥72 weeks previously. For the primary end point, the IT group at week 72 had a better outcome than the DT group at week 72 (P = .005) and the DT group at week 36 (P = .002). The differences were primarily due to the higher rate of progression to needing treatment in the DT group (50%) versus the IT (10%) group. The DSMB recommended stopping the study because further follow-up was unlikely to change these findings. CONCLUSIONS Progression to meeting criteria for antiretroviral initiation in the DT group occurred more frequently than anticipated, limiting the ability to evaluate virologic set point. Antiretrovirals during early HIV-1 infection modestly delayed the need for subsequent treatment. CLINICAL TRIALS REGISTRATION NCT00090779.

Human immunodeficiency virus type 1 RNA level and CD4 count as prognostic markers and surrogate end points: A meta-analysis

Objective: To evaluate treatment-mediated changes in HIV-1 RNA and CD3 count as prognostic markers and surrogate end points for disease progression (AIDS/death). Methods: Data from 13,045 subjects in all 16 randomized trials comparing nucleoside analogue reverse transcriptase inhibitors and having HIV-1 RNA measurements at 24 weeks were obtained. A total of 3146 subjects had HIV-1 RNA and CD3 count determinations at 24 weeks after starting treatment. Results: At Week 24, the percentage of subjects experiencing an HIV-1 RNA decrease of >1 log(10) copies/ml or a CD4 count increase of >33% was similar (22% vs 25%). Changes in both markers at Week 24 mere significant independent predictors of AIDS/death: across trials, the average reduction in hazard was 51% per 1 log(10) HIV-1 RNA copies/ml decrease (95% confidence interval: 41%, 59%) and 20% per 33% CD4 count increase (17%, 24%). In univariate analyses, the hazard ratio for AIDS/death in randomized treatment comparisons was significantly associated with differences between treatments in mean area under the curve of HIV-1 RNA changes to Weeks 8 and 24 (AUCMB) and mean CD3 change at Week 24, but, in multivariate analysis, only mean CD4 change was significant. Conclusions: Change in HIV-1 RNA, particularly using AUCMB, and in CD4 count should be measured to aid patient management and evaluation of treatment activity in clinical trials. However, short-term changes in these markers are imperfect as surrogate end points for long-term clinical outcome because two randomized treatment comparisons may show similar differences between treatments in marker changes but not similar differences in progression to AIDS/death.

Methods for Investigation of the Relationship between Drug-Susceptibility Phenotype and Human Immunodeficiency Virus Type 1 Genotype with Applications to AIDS Clinical Trials Group 333

Use of human immunodeficiency virus (HIV) drug-resistance testing in therapeutic decision making may be aided by understanding the relationship between results of genotypic and drug-susceptibility phenotypic assays. We investigated this relationship by applying 3 different statistical methods-cluster analysis, recursive partitioning, and linear discriminant analysis-to results for 72 patients followed in the Adult AIDS Clinical Trials Group (ACTG) protocol 333. ACTG 333 was a multicenter, randomized trial comparing 2 formulations of saquinavir (SQV) to indinavir (IDV) in patients with extensive hard-gel SQV experience. Data include protease amino acid sequences and 50% inhibitory concentrations for SQV and IDV at baseline. The 3 methods give similar results showing the association of mutations at codons 10, 63, 71, and 90 with in vitro resistance to IDV and SQV. Recursive partitioning is especially useful because it can identify interactions among mutations at different codons and accommodates many types of data as well as missing observations.

Modeling the Progression of HIV Infection

Abstract Statistical modeling of the progression of markers of HIV infection is complicated by three problems: (1) the times of infection are generally unknown; (2) the follow-up of infected patients is generally much shorter than the average time from infection to AIDS; and (3) the repeated measures of the markers are correlated. The marker we study in this article is T-helper cell count. As a consequence of these three problems, it is difficult to distinguish between different models for the decline in T-helper cell count over time for HIV-infected individuals. Some investigators have proposed that the decline is gradual until shortly before the onset of AIDS, yet available data do not reject models of a fairly constant decline over the entire latency period between HIV infection and onset of AIDS. The ability to discriminate between models can be enhanced by incorporating information about the distributions of the times of seroconversion (development of measurable antibodies) among HIV seropositive ind...