Uptake of antiretroviral treatment and viral suppression among men who have sex with men and transgender women in sub-Saharan Africa in an observational cohort study: HPTN 075
INTERNATIONAL JOURNAL OF INFECTIOUS DISEASES
2021; 104: 465?70
Evaluation of Phylogenetic Methods for Inferring the Direction of Human Immunodeficiency Virus (HIV) Transmission: HIV Prevention Trials Network (HPTN) 052.
Clinical infectious diseases : an official publication of the Infectious Diseases Society of America
2021; 72 (1): 30?37
HPTN 075 enrolled men who have sex with men (MSM) and transgender women (TGW) in sub-Saharan Africa. Persons in HIV care or on antiretroviral treatment (ART) were not eligible to enroll. We evaluated antiretroviral (ARV) drug use, viral suppression, and drug resistance in this cohort over a 12-month follow-up period.Assessments included 64 participants with HIV (39 MSM, 24 TGW, and one gender not specified). ARV drugs were detected using a qualitative assay. Viral load (VL) and drug resistance testing were performed using commercial assays.Over 12 months, the proportion of participants using ARV drugs increased from 28.1% to 59.4% and the proportion with VLs <400 copies/mL increased from 21.9% to 57.8%. The rate of ART failure (detection of drugs without viral suppression) was similar at screening and 12 months (12.0% and 11.1%, respectively) and was similar among MSM and TGW. Two participants developed HIV drug resistance during follow-up.Over 12 months, ARV drug use in the cohort more than doubled and viral suppression increased nearly threefold without a significant increase in ART failure or drug resistance. These results suggest that ART can be successfully scaled up for HIV prevention and treatment in this high-risk population.
View details for DOI 10.1016/j.ijid.2020.12.085
View details for Web of Science ID 000632937400024
View details for PubMedID 33440260
View details for PubMedCentralID PMC8091139
Measuring Surrogacy in Clinical Research With an Application to Studying Surrogate Markers for HIV Treatment-as-Prevention
STATISTICS IN BIOSCIENCES
2020; 12 (3): 295?323
Phylogenetic analysis can be used to assess human immunodeficiency virus (HIV) transmission in populations. We inferred the direction of HIV transmission using whole-genome HIV sequences from couples with known linked infection and known transmission direction.Complete next-generation sequencing (NGS) data were obtained for 105 unique index-partner sample pairs from 32 couples enrolled in the HIV Prevention Trials Network (HPTN) 052 study (up to 2 samples/person). Index samples were obtained up to 5.5 years before partner infection; partner samples were obtained near the time of seroconversion. The bioinformatics method, phyloscanner, was used to infer transmission direction. Analyses were performed using samples from individual sample pairs, samples from all couples (1 sample/person; group analysis), and all available samples (multisample group analysis). Analysis was also performed using NGS data from defined regions of the HIV genome (gag, pol, env).Using whole-genome NGS data, transmission direction was inferred correctly (index to partner) for 98 of 105 (93.3%) of the individual sample pairs, 99 of 105 (94.3%) sample pairs using group analysis, and 31 of the 32 couples (96.9%) using multisample group analysis. There were no cases where the incorrect transmission direction (partner to index) was inferred. The accuracy of the method was higher with greater time between index and partner sample collection. Pol region sequences performed better than env or gag sequences for inferring transmission direction.We demonstrate the potential of a phylogenetic method to infer the direction of HIV transmission between 2 individuals using whole-genome and pol NGS data.
View details for DOI 10.1093/cid/ciz1247
View details for PubMedID 31922537
View details for PubMedCentralID PMC7823077
Introduction to Special Issue on 'Statistical Methods for HIV/AIDS Research'
STATISTICS IN BIOSCIENCES
2020; 12 (3): 263?66
The feasibility of recruiting and retaining men who have sex with men and transgender women in a multinational prospective HIV prevention research cohort study in sub-Saharan Africa (HPTN 075)
JOURNAL OF THE INTERNATIONAL AIDS SOCIETY
2020; 23: e25600
In clinical research, validated surrogate markers are highly desirable in study design, monitoring, and analysis, as they do not only reduce the required sample size and follow-up duration, but also facilitate scientific discoveries. However, challenges exist to identify a reliable marker. One particular statistical challenge arises on how to measure and rank the surrogacy of potential markers quantitatively. We review the main statistical methods for evaluating surrogate markers. In addition, we suggest a new measure, the so-called "population surrogacy fraction of treatment effect," or simply the p-measure, in the setting of clinical trials. The p-measure carries an appealing population impact interpretation and supplements the existing statistical measures of surrogacy by providing "absolute" information. We apply the new measure along with other prominent measures to the HIV Prevention Trial Network 052 Study, a landmark trial for HIV/AIDS treatment-as-prevention.
View details for DOI 10.1007/s12561-019-09244-4
View details for Web of Science ID 000585702200004
View details for PubMedID 33737982
View details for PubMedCentralID PMC7962622
Persistence of oral pre-exposure prophylaxis (PrEP) among adolescent girls and young women initiating PrEP for HIV prevention in Kenya
AIDS CARE-PSYCHOLOGICAL AND SOCIO-MEDICAL ASPECTS OF AIDS/HIV
Men who have sex with men (MSM) and transgender women (TGW) in sub-Saharan Africa (SSA) are profoundly affected by HIV with high HIV prevalence and incidence. This population also faces strong social stigma and legal barriers, potentially impeding participation in research. To date, few multi-country longitudinal HIV research studies with MSM/TGW have been conducted in SSA. Primary objective of the HIV Prevention Trials Network (HPTN) 075 study was to assess feasibility of recruiting and retaining a multinational prospective cohort of MSM/TGW in SSA for HIV prevention research.HPTN 075, conducted from 2015 to 2017, was designed to enroll 400 MSM/TGW at four sites in SSA (100 per site: Kisumu, Kenya; Blantyre, Malawi; Cape Town, South Africa; and Soweto, South Africa). The number of HIV-positive persons was capped at 20 per site; HIV-positive persons already in care were excluded from participation. The one-year study included five biobehavioural assessments. Community-based input and risk mitigation protocols were included in study design and conduct.Of 624 persons screened, 401 were enrolled. One in five participants was classified as transgender. Main reasons for ineligibility included: (a) being HIV positive after the cap was reached (29.6%); (b) not reporting anal intercourse with a man in the preceding three months (20.6%); and (c) being HIV positive and already in care (17.5%). Five (1.2%) participants died during the study (unrelated to study participation). 92.9% of the eligible participants (368/396) completed the final study visit and 86.1% participated in all visits. The main, overlapping reasons for early termination included being (a) unable to adhere to the visit schedule, predominantly because of relocation (46.4%), and (b) unable to contact the participant (32.1%). Participants reported strong motivation to participate and few participation barriers. Four participants reported social harms (loss of confidentiality and sexual harassment by study staff) that were successfully addressed.HPTN 075 successfully enrolled a multinational sample of MSM/TGW in SSA in a prospective HIV prevention research study with a high retention rate and few documented social harms. This supports the feasibility of conducting large-scale research trials in this population to address its urgent, unmet HIV prevention needs.
View details for DOI 10.1002/jia2.25600
View details for Web of Science ID 000576983100009
View details for PubMedID 33000911
View details for PubMedCentralID PMC7527761
Trial designs for evaluating combination HIV prevention approaches
HIV RESEARCH & CLINICAL PRACTICE
2020; 21 (2-3): 72?82
The Determined, Resilient, Empowered, AIDS-free, Mentored, and Safe (DREAMS) Initiative aims to reduce HIV infections among adolescent girls and young women (AGYW) in Africa. Oral pre-exposure prophylaxis (PrEP) is offered through DREAMS in Kenya to eligible AGYW in high burden counties including Kisumu and Homa Bay. This study examines PrEP persistence among AGYW in high burden community-based PrEP delivery settings. We evaluated PrEP persistence among AGYW in the DREAMS PrEP program in Kisumu and Homa Bay using survival analysis and programmatic PrEP refill data collected between March through December 2017. Among 1,259 AGYW who initiated PrEP during the study period, the median persistence time in the program was 56 days (95% CI: 49-58 days) and the proportion who persisted 3 months later was 37% (95% CI: 34-40%). Persistence varied by county (p?0.001), age at PrEP initiation (p?=?0.002), marital status (p?=?0.008), transactional sex (p?=?0.002), gender-based violence (GBV) experience (p?=?0.009) and current school attendance (p?=?0.001) at DREAMS enrollment. Persistence did not vary with orphan status, food insecurity, condom use, age at first sexual encounter or engagement in age-disparate sex at DREAMS enrollment. Targeted strategies are needed to improve AGYW retention in the PrEP program.
View details for DOI 10.1080/09540121.2020.1822505
View details for Web of Science ID 000571280600001
View details for PubMedID 32951437
View details for PubMedCentralID PMC7981281
Healthcare-related stigma among men who have sex with men and transgender women in sub-Saharan Africa participating in HIV Prevention Trials Network (HPTN) 075 study
AIDS CARE-PSYCHOLOGICAL AND SOCIO-MEDICAL ASPECTS OF AIDS/HIV
2020; 32 (8): 1052?60
Combination HIV prevention approaches that include both biomedical and non-biomedical interventions often hold greater promise to improve health outcomes and reduce the risk of HIV transmission.Evaluate the relative properties of four leading candidate trial designs - 'single-factor', 'multi-arm', 'all-in-one', and 'factorial' designs - for assessing individual and/or combination prevention intervention approaches.Monte-Carlo simulations are conducted, assuming a putative combination approach could choose its components from two candidate biomedical interventions, i.e. Treatment-as-Prevention (TasP) and Pre-exposure Prophylaxis (PrEP), and three candidate behavioral interventions, i.e. linkage-to-care, counseling, and use of condoms. Various scenarios for individual components' effect sizes, their possible interaction, and the sample size based on real clinical studies are considered.The all-in-one and factorial designs used to assess a combination approach and the multi-arm design used to assess multiple individual components are consistently more powerful than single-factor designs. The all-in-one design is powerful when the individual components are effective without negative interaction, while the factorial design is more consistently powerful across a broad array of settings.The multi-arm design is useful for evaluating single factor regimens, while the all-in-one and factorial designs are sensitive in assessing the overall efficacy when there is interest in combining individual component regimens anticipated to have complementary mechanisms. The factorial design is a preferred approach when assessing combination regimens due to its favorable power properties and since it is the only design providing direct insights about the contribution of individual components to the combination approach's overall efficacy and about potential interactions.
View details for DOI 10.1080/25787489.2020.1798083
View details for Web of Science ID 000555063900001
View details for PubMedID 32698705
View details for PubMedCentralID PMC7608072
On a Statistical Transmission Model in Analysis of the Early Phase of COVID-19 Outbreak
STATISTICS IN BIOSCIENCES
2021; 13 (1): 1?17
ABSTRACT The inability to access health services when needed is a critical barrier to HIV prevention, treatment and care among men who have sex with men (MSM) and transgender women (TGW). Using data collected in HPTN 075, we explored factors associated with any experienced healthcare-related stigma. HPTN 075 was a cohort study to assess the feasibility of recruiting and retaining MSM and TGW in clinical trials in sub-Saharan Africa. Of 401 MSM and TGW enrolled at four sites (Kisumu, Kenya; Blantyre, Malawi; Cape Town, Soweto, South Africa) 397 contributed to the analysis (79.9% cis-gender and 20.1% TGW). Of these, (45.3%; 180/397) reported one or more of healthcare-related stigma experiences. Most frequently reported experiences included fear to seek healthcare services (36.3%) and avoiding seeking such services because of the discovery of MSM status (29.2%). Few men and TGW (2.5%) reported having been denied health services because of having sex with men. In multivariable analysis, more participants in Soweto [adjusted odds ratio (AOR)?=?2.60] and fewer participants in Blantyre (AOR?=?0.27) reported any healthcare-related stigma experiences, in comparison to participants in Kisumu. MSM and TGW that did not have a supportive gay community to rely on were more likely to report any healthcare-related stigma experiences (AOR?=?1.46), whereas MSM and TGW who reported high social support and who never had engaged in transactional sex were less likely to report such experiences (AOR?=?0.76 and AOR?=?0.43, respectively). Our results suggest that encouraging support groups for MSM and TGW as well as training and sensitizing healthcare staff, and the general community, on MSM and TGW health issues and cultural competence may reduce stigma, improve access to healthcare, which could ultimately reduce HIV transmission.
View details for DOI 10.1080/09540121.2020.1776824
View details for Web of Science ID 000542822200001
View details for PubMedID 32500722
View details for PubMedCentralID PMC7368806
A regularized estimation approach for case-cohort periodic follow-up studies with an application to HIV vaccine trials
2020; 62 (5): 1176?91
Since December 2019, a disease caused by a novel strain of coronavirus (COVID-19) had infected many people and the cumulative confirmed cases have reached almost 180,000 as of 17, March 2020. The COVID-19 outbreak was believed to have emerged from a seafood market in Wuhan, a metropolis city of more than 11 million population in Hubei province, China. We introduced a statistical disease transmission model using case symptom onset data to estimate the transmissibility of the early-phase outbreak in China, and provided sensitivity analyses with various assumptions of disease natural history of the COVID-19. We fitted the transmission model to several publicly available sources of the outbreak data until 11, February 2020, and estimated lock down intervention efficacy of Wuhan city. The estimated
was between 2.7 and 4.2 from plausible distribution assumptions of the incubation period and relative infectivity over the infectious period. 95% confidence interval of
were also reported. Potential issues such as data quality concerns and comparison of different modelling approaches were discussed.
View details for DOI 10.1007/s12561-020-09277-0
View details for Web of Science ID 000523054500001
View details for PubMedID 32292527
View details for PubMedCentralID PMC7113380
Methods for generalized change-point models: with applications to human immunodeficiency virus surveillance and diabetes data
STATISTICS IN MEDICINE
2020; 39 (8): 1167?82
This paper discusses regression analysis of the failure time data arising from case-cohort periodic follow-up studies, and one feature of such data, which makes their analysis much more difficult, is that they are usually interval-censored rather than right-censored. Although some methods have been developed for general failure time data, there does not seem to exist an established procedure for the situation considered here. To address the problem, we present a semiparametric regularized procedure and develop a simple algorithm for the implementation of the proposed method. In addition, unlike some existing procedures for similar situations, the proposed procedure is shown to have the oracle property, and an extensive simulation is conducted and it suggests that the presented approach seems to work well for practical situations. The method is applied to an HIV vaccine trial that motivated this study.
View details for DOI 10.1002/bimj.201900180
View details for Web of Science ID 000514617400001
View details for PubMedID 32080888
View details for PubMedCentralID PMC7768636
Adjusted time-varying population attributable hazard in case-control studies
STATISTICAL METHODS IN MEDICAL RESEARCH
2020; 29 (1): 243?57
In many epidemiological and biomedical studies, the association between a response variable and some covariates of interest may change at one or several thresholds of the covariates. Change-point models are suitable for investigating the relationship between the response and covariates in such situations. We present change-point models, with at least one unknown change-point occurring with respect to some covariates of a generalized linear model for independent or correlated data. We develop methods for the estimation of the model parameters and investigate their finite-sample performances in simulations. We apply the proposed methods to examine the trends in the reported estimates of the annual percentage of new human immunodeficiency virus (HIV) diagnoses linked to HIV-related medical care within 3 months after diagnosis using HIV surveillance data from the HIV prevention trial network 065 study. We also apply our methods to a dataset from the Pima Indian diabetes study to examine the effects of age and body mass index on the risk of being diagnosed with type 2 diabetes.
View details for DOI 10.1002/sim.8469
View details for Web of Science ID 000510844600001
View details for PubMedID 31997385
View details for PubMedCentralID PMC7260994
On a Shape-Invariant Hazard Regression Model with application to an HIV Prevention Study of Mother-to-Child Transmission
STATISTICS IN BIOSCIENCES
2020; 12 (3): 340?52
Population attributable fraction is a widely used measure for quantifying the disease burden associated with a modifiable exposure of interest at the population level. It has been extended to a time-varying measure, population attributable hazard function, to provide additional information on when and how the exposure's impact varies over time. However, like the classic population attributable fraction, the population attributable hazard is generally biased if confounders are present. In this article, we provide a natural definition of adjusted population attributable hazard to take into account the effects of confounders, and its alternative that is identifiable from case-control studies under the rare disease assumption. We propose a novel estimator, which combines the odds ratio estimator from logistic regression model, and the conditional density function estimator of the exposure and confounding variables distribution given the failure times of cases or the current times of controls from a kernel smoother. We show that the proposed estimators are consistent and asymptotically normal with variance that can be estimated empirically from the data. Simulation studies demonstrate that the proposed estimators perform well in finite sample sizes. Finally, we illustrate the method by an analysis of a case-control study of colorectal cancer. Supplementary materials for this article are available online.
View details for DOI 10.1177/0962280219831725
View details for Web of Science ID 000508982300017
View details for PubMedID 30799773
View details for PubMedCentralID PMC7261419
In survival analysis, Cox model is widely used for most clinical trial data. Alternatives include the additive hazard model, the accelerated failure time (AFT) model and a more general transformation model. All these models assume that the effects for all covariates are on the same scale. However, it is possible that for different covariates, the effects are on different scales. In this paper, we propose a shape-invariant hazard regression model that allows us to estimate the multiplicative treatment effect with adjustment of covariates that have non-multiplicative effects. We propose moment-based inference procedures for the regression parameters. We also discuss the risk prediction and the goodness of fit test for our proposed model. Numerical studies show good finite sample performance of our proposed estimator. We applied our method to the HIVNET 012 study, a milestone trial of single-dose nevirapine in prevention of mother-to-child transmission of HIV. From the HIVNET 012 data analysis, single-dose nevirapine treatment is shown to improve 18-month infant survival significantly with appropriate adjustment of the maternal CD4 counts and the virus load.
View details for DOI 10.1007/s12561-019-09260-4
View details for Web of Science ID 000491530600002
View details for PubMedID 33312265
View details for PubMedCentralID PMC7730855