Self-transfers, Hospital Admissions and Mortality Among Children and Adolescents Lost to Follow-up From Antiretroviral Therapy Programs in the Western Cape, South Africa Between 2004 and 2019: Linkage to Provincial Records

BACKGROUND

Pediatric programs face a high rate of loss to follow-up (LTFU) among children and adolescents living with HIV (CAHIV). We assessed true outcomes and predictors of these among CAHIV who were LTFU using linkage to the Western Cape Provincial Health Data Centre at Western Cape sites of the International epidemiology Databases to Evaluate AIDS-Southern Africa collaboration.

METHODS

We examined factors associated with self-transfer, hospital admission and mortality using competing risks regression in a retrospective cohort of CAHIV initiating antiretroviral therapy <15 years old between 2004 and 2019 and deemed LTFU (no recorded visit at the original facility for ≥180 days from the last visit date before database closure and not known to have officially transferred out or deceased).

RESULTS

Of the 1720 CAHIV deemed LTFU, 802 (46.6%) had self-transferred and were receiving care elsewhere within the Western Cape, 463 (26.9%) had been hospitalized and 45 (2.6%) CAHIV had died. The overall rates of self-transfer, hospitalization, mortality and LTFU were 9.4 [95% confidence interval (CI): 8.8-10.1], 5.4 (95% CI: 5.0-6.0), 0.5 (95% CI: 0.4-0.7) and 4.8 (95% CI: 4.4-5.3) per 100 person-years respectively. Increasing duration on antiretroviral therapy before LTFU was associated with self-transfers while male sex, older age at last visit (≥10 years vs. younger) were associated with hospital admission and immune suppression at last visit was associated with 5 times higher mortality.

CONCLUSIONS

Nearly half of CAHIV classified as LTFU had self-transferred to another health facility, a quarter had been hospitalized and a small proportion had died.

Characterizing participants who respond to text, email, phone calls, or postcards in a SARS-CoV-2 prevalence study

INTRODUCTION

Multiple modalities and frequencies of contact are needed to maximize recruitment in many public health surveys. The purpose of this analysis is to characterize respondents to a statewide SARS-CoV-2 testing study whose participation followed either postcard, phone outreach or electronic means of invitation. In addition, we examine how participant characteristics differ based upon the number of contacts needed to elicit participation.

METHODS

This is a cross-sectional analysis of survey data collected from participants who were randomly selected to represent Indiana residents and were invited to be tested for Covid-19 in April 2020. Participants received invitations via postcard, text/emails, and/or robocalls/texts based upon available contact information. The modality, and frequency of contacts, that prompted participation was determined by when the notification was sent and when the participant responded and subsequently registered to participate in the study. Chi square analyses were used to determine differences between groups and significant findings were analyzed using multinomial logistic regression.

RESULTS

Respondents included 3,658 individuals and were stratified by postcards (7.9%), text/emails (26.5%), and robocalls/text (65.7%) with 19.7% registering after 1 contact, 47.9% after 2 contacts, and 32.4% after 3 contacts encouraging participation. Females made up 54.6% of the sample and responded at a higher rate for postcards (8.2% vs. 7.5%) and text/emails (28.1 vs. 24.6%) as compared to males (χ2 = 7.43, p = 0.025). Compared to males, females responded at a higher percentage after 1 contact (21.4 vs. 17.9%, χ2 = 7.6, p = 0.023). Those over 60 years responded most often after 2 contacts (χ2 = 27.5, p < 0.001) when compared to others at younger age groups. In regression analysis, participant sex (p = 0.036) age (p = 0.005), educational attainment (p = < 0.0001), and being motivated by "free testing" (p = 0.036) were correlated with participation in the prevalence study.

DISCUSSION

Researchers should be aware that the modality of contact as well as the number of prompts used could influence differential participation in public health studies. Our findings can inform researchers developing studies that rely on selective participation by study subjects. We explore how to increase participation within targeted demographic groups using specific modalities and examining frequency of contact.

Adaptation of the Client Diagnostic Questionnaire for East Africa

Research increasingly involves cross-cultural work with non-English-speaking populations, necessitating translation and cultural validation of research tools. This paper describes the process of translating and criterion validation of the Client Diagnostic Questionnaire (CDQ) for use in a multisite study in Kenya and Uganda. The English CDQ was translated into Swahili, Dholuo (Kenya) and Runyankole/Rukiga (Uganda) by expert translators. The translated documents underwent face validation by a bilingual committee, who resolved unclear statements, agreed on final translations and reviewed back translations to English. A diagnostic interview by a mental health specialist was used for criterion validation, and Kappa statistics assessed the strength of agreement between non-specialist scores and mental health professionals' diagnoses. Achieving semantic equivalence between translations was a challenge. Validation analysis was done with 30 participants at each site (median age 32.3 years (IQR = (26.5, 36.3)); 58 (64.4%) female). The sensitivity was 86.7%, specificity 64.4%, positive predictive value 70.9% and negative predictive value 82.9%. Diagnostic accuracy by the non-specialist was 75.6%. Agreement was substantial for major depressive episode and positive alcohol (past 6 months) and alcohol abuse (past 30 days). Agreement was moderate for other depressive disorders, panic disorder and psychosis screen; fair for generalized anxiety, drug abuse (past 6 months) and Post Traumatic Stress Disorder (PTSD); and poor for drug abuse (past 30 days). Variability of agreement between sites was seen for drug use (past 6 months) and PTSD. Our study successfully adapted the CDQ for use among people living with HIV in East Africa. We established that trained non-specialists can use the CDQ to screen for common mental health and substance use disorders with reasonable accuracy. Its use has the potential to increase case identification, improve linkage to mental healthcare, and improve outcomes. We recommend further studies to establish the psychometric properties of the translated tool.

Mortality Among HIV-Infected Adults on Antiretroviral Therapy in Southern Uganda

BACKGROUND

Monitoring and evaluation of clinical programs requires assessing patient outcomes. Numerous challenges complicate these efforts, the most insidious of which is loss to follow-up (LTFU). LTFU is a composite outcome, including individuals out of care, undocumented transfers, and unreported deaths. Incorporation of vital status information from routine patient outreach may improve the mortality estimates for those LTFU.

SETTINGS

We analyzed routinely collected clinical and patient tracing data for individuals (15 years or older) initiating antiretroviral treatment between January 2014 and December 2018 at 2 public HIV care clinics in greater Rakai, Uganda.

METHODS

We derived unadjusted mortality estimates using Kaplan-Meier methods. Estimates, adjusted for unreported deaths, applied weighting through the Frangakis and Rubin method to represent outcomes among LTFU patients who were successfully traced and for whom vital status was ascertained. Confidence intervals were determined through bootstrap methods.

RESULTS

Of 1969 patients with median age at antiretroviral treatment initiation of 31 years (interquartile range: 25-38), 1126 (57.2%) were female patients and 808 (41%) were lost. Of the lost patients, 640 patient files (79.2%) were found and reviewed, of which 204 (31.8%) had a tracing attempt. Within the electronic health records of the program, 28 deaths were identified with an estimated unadjusted mortality 1 year after antiretroviral treatment initiation of 2.5% (95% CI: 1.8% to 3.3%). Using chart review and patient tracing data, an additional 24 deaths (total 52) were discovered with an adjusted 1-year mortality of 3.8% (95% CI: 2.6% to 5.0%).

CONCLUSIONS

Data from routine outreach efforts by HIV care and treatment programs can be used to support plausible adjustments to estimates of client mortality. Mortality estimates without active ascertainment of vital status of LTFU patients may significantly underestimate program mortality.

Joint modeling of longitudinal and competing-risk data using cumulative incidence functions for the failure submodels accounting for potential failure cause misclassification through double sampling

Most of the literature on joint modeling of longitudinal and competing-risk data is based on cause-specific hazards, although modeling of the cumulative incidence function (CIF) is an easier and more direct approach to evaluate the prognosis of an event. We propose a flexible class of shared parameter models to jointly model a normally distributed marker over time and multiple causes of failure using CIFs for the survival submodels, with CIFs depending on the "true" marker value over time (i.e., removing the measurement error). The generalized odds rate transformation is applied, thus a proportional subdistribution hazards model is a special case. The requirement that the all-cause CIF should be bounded by 1 is formally considered. The proposed models are extended to account for potential failure cause misclassification, where the true failure causes are available in a small random sample of individuals. We also provide a multistate representation of the whole population by defining mutually exclusive states based on the marker values and the competing risks. Based solely on the assumed joint model, we derive fully Bayesian posterior samples for state occupation and transition probabilities. The proposed approach is evaluated in a simulation study and, as an illustration, it is fitted to real data from people with HIV.

Preswitch Regimens Influence the Rate of Weight Gain After Switch to Tenofovir Disoproxil Fumarate, Lamivudine, and Dolutegravir (TLD): Study From an East African Cohort

Background

Switching from non-nucleoside reverse transcriptase inhibitor (NNRTI)-based regimens to dolutegravir (DTG) has been associated with greater weight gain.

Methods

We conducted our analysis using a longitudinal cohort of people with HIV (PWH) in Western Kenya. We evaluated changes in the rate of weight gain among treatment-experienced, virally suppressed PWH who switched from NNRTI to tenofovir disoproxil fumarate, lamivudine, and dolutegravir (TLD). We modeled the weights pre- and postswitch using a 2-phase model with linear trend preswitch and an inverted exponential function postswitch. We estimated an 18-month excess weight gain by comparing the projected weight with that expected using the preswitch rate.

Results

A total of 18 662 individuals were included in our analysis, with 55% switching from efavirenz (EFV) and 45% from nevirapine (NVP). Of the studied individuals, 51% were female, and the median age and body mass index (BMI) were 51 years and 22 kg/m2, respectively. For the overall population, the rate of weight gain increased from 0.47 kg/year preswitch to 0.77 kg/year, with higher increases for females (0.57 kg/year to 0.96 kg/year) than males (0.34 kg/year to 0.62 kg/year). The rate of weight gain for individuals switching from EFV-based regimens significantly increased from 0.57 kg/year preswitch to 1.11 kg/year postswitch but remained stable at 0.35 kg/year preswitch vs 0.32 kg/year postswitch for individuals switching from NVP-based regimens.

Conclusions

Switching from NNRTI-based regimens to TLD is associated with a modest increase in the rate of weight gain, with the preswitch NNRTI being the key determinant of the amount of weight gain experienced postswitch.

Assessing HIV-infected patient retention in a program of differentiated care in sub-Saharan Africa: a G-estimation approach

Differentiated care delivery aims to simplify care of people living with HIV, reflect their preferences, reduce burdens on the healthcare system, maintain care quality and preserve resources. However, assessing program effectiveness using observational data is difficult due to confounding by indication and randomized trials may be infeasible. Also, benefits can reach patients directly, through enrollment in the program, and indirectly, by increasing quality of and accessibility to care. Low-risk express care (LREC), the program under evaluation, is a nurse-centered model which assigns patients stable on ART to a nurse every two months and a clinician every third visit, reducing annual clinician visits by two thirds. Study population is comprised of 16,832 subjects from 15 clinics in Kenya. We focus on patient retention in care based on whether the LREC program is available at a clinic and whether the patient is enrolled in LREC. We use G-estimation to assess the effect on retention of two "strategies": (i) program availability but no enrollment; (ii) enrollment at an available program; versus no program availability. Compared to no availability, LREC results in a non-significant increase in patient retention, among patients not enrolled in the program (indirect effect), while enrollment in LREC is associated with a significant extension of the time retained in care (direct effect). G-estimation provides an analytical framework useful to the assessment of similar programs using observational data.

The Effect of HIV Treatment Interruption on Subsequent Immunological Response

Recovery of CD4-positive T lymphocyte count after initiation of antiretroviral therapy (ART) has been thoroughly examined among people with human immunodeficiency virus infection. However, immunological response after restart of ART following care interruption is less well studied. We compared CD4 cell-count trends before disengagement from care and after ART reinitiation. Data were obtained from the East Africa International Epidemiology Databases to Evaluate AIDS (IeDEA) Collaboration (2001-2011; n = 62,534). CD4 cell-count trends before disengagement, during disengagement, and after ART reinitiation were simultaneously estimated through a linear mixed model with 2 subject-specific knots placed at the times of disengagement and treatment reinitiation. We also estimated CD4 trends conditional on the baseline CD4 value. A total of 10,961 patients returned to care after disengagement from care, with the median gap in care being 2.7 (interquartile range, 2.1-5.4) months. Our model showed that CD4 cell-count increases after ART reinitiation were much slower than those before disengagement. Assuming that disengagement from care occurred 12 months after ART initiation and a 3-month treatment gap, CD4 counts measured at 3 years since ART initiation would be lower by 36.5 cells/μL than those obtained under no disengagement. Given that poorer CD4 restoration is associated with increased mortality/morbidity, specific interventions targeted at better retention in care are urgently required.

Global HIV prevention, care and treatment services for children: a cross-sectional survey from the International Epidemiology Databases to Evaluate AIDS (IeDEA) consortium

OBJECTIVES

To assess access children with HIV have to comprehensive HIV care services, to longitudinally evaluate the implementation and scale-up of services, and to use site services and clinical cohort data to explore whether access to these services influences retention in care.

METHODS

A cross-sectional standardised survey was completed in 2014-2015 by sites providing paediatric HIV care across regions of the International Epidemiology Databases to Evaluate AIDS (IeDEA) consortium. We developed a comprehensiveness score based on the WHO's nine categories of essential services to categorise sites as 'low' (0-5), 'medium', (6-7) or 'high' (8-9). When available, comprehensiveness scores were compared with scores from a 2009 survey. We used patient-level data with site services to investigate the relationship between the comprehensiveness of services and retention.

RESULTS

Survey data from 174 IeDEA sites in 32 countries were analysed. Of the WHO essential services, sites were most likely to offer antiretroviral therapy (ART) provision and counselling (n=173; 99%), co-trimoxazole prophylaxis (168; 97%), prevention of perinatal transmission services (167; 96%), outreach for patient engagement and follow-up (166; 95%), CD4 cell count testing (126; 88%), tuberculosis screening (151; 87%) and select immunisation services (126; 72%). Sites were less likely to offer nutrition/food support (97; 56%), viral load testing (99; 69%) and HIV counselling and testing (69; 40%). 10% of sites rated 'low', 59% 'medium' and 31% 'high' in the comprehensiveness score. The mean comprehensiveness of services score increased significantly from 5.6 in 2009 to 7.3 in 2014 (p<0.001; n=30). Patient-level analysis of lost to follow-up after ART initiation estimated the hazard was highest in sites rated 'low' and lowest in sites rated 'high'.

CONCLUSION

This global assessment suggests the potential care impact of scaling-up and sustaining comprehensive paediatric HIV services. Meeting recommendations for comprehensive HIV services should remain a global priority.

Same-Day Antiretroviral Therapy Initiation as a Predictor of Loss to Follow-up and Viral Suppression Among People With Human Immunodeficiency Virus in Sub-Saharan Africa

BACKGROUND

Treat-All guidelines recommend initiation of antiretroviral therapy (ART) for all people with HIV (PWH) on the day of diagnosis when possible, yet uncertainty exists about the impact of same-day ART initiation on subsequent care engagement. We examined the association of same-day ART initiation with loss to follow-up and viral suppression among patients in 11 sub-Saharan African countries.

METHODS

We included ART-naive adult PWH from sites participating in the International epidemiology Databases to Evaluate AIDS (IeDEA) consortium who enrolled in care after Treat-All implementation and prior to January 2019. We used multivariable Cox regression to estimate the association between same-day ART initiation and loss to follow-up and Poisson regression to estimate the association between same-day ART initiation and 6-month viral suppression.

RESULTS

Among 29 017 patients from 63 sites, 18 584 (64.0%) initiated ART on the day of enrollment. Same-day ART initiation was less likely among those with advanced HIV disease versus early-stage disease. Loss to follow-up was significantly lower among those initiating ART ≥1 day of enrollment, compared with same-day ART initiators (20.6% vs 27.7%; adjusted hazard ratio: .66; 95% CI .57-.76). No difference in viral suppression was observed by time to ART initiation (adjusted rate ratio: 1.00; 95% CI: .98-1.02).

CONCLUSIONS

Patients initiating ART on the day of enrollment were more frequently lost to follow-up than those initiating later but were equally likely to be virally suppressed. Our findings support recent World Health Organization recommendations for providing tailored counseling and support to patients who accept an offer of same-day ART.

Weight Gain Among Treatment-Naïve Persons With HIV Receiving Dolutegravir in Kenya

BACKGROUND

Several recent studies have linked integrase strand transfer inhibitors (INSTI) with increased weight gain.

SETTING

The effects of sex on weight gain with dolutegravir (DTG)-based antiretroviral therapy (ART) among treatment-naïve participants in a lower-income, sub-Saharan population with high rates of pre-ART underweight and tuberculosis (TB) coinfection are unknown.

METHODS

Our analysis included treatment-naïve participants in Kenya and starting their first treatment regimen between January 1, 2015, and September 30, 2018. Participants were grouped into 2 cohorts based on the initial treatment regimen [DTG vs. nonnucleoside reverse transcriptase inhibitors (NNRTI)]. We modelled weight changes over time using a multivariable nonlinear mixed-effect model, with participant as a random effect. Logistic regression models were constructed to evaluate the association between different variables with extreme increase in body mass index (≥10% increase).

RESULTS

Seventeen thousand forty-four participants met our inclusion criteria. Sixty-two percent of participants were women, 6% were receiving active TB therapy, and 97% were on NNRTI-based regimens. Participants starting DTG-based regimens were more likely to gain weight when compared with participants starting NNRTI-based regimens. Female participants starting DTG-based regimens experienced the highest weight gain compared with other participants (mean gain of 6.1 kgs at 18 months). Female participants receiving DTG-based regimens, along with participants with lower CD4 cell counts, underweight at baseline, and those receiving active TB therapy were also at higher risk for extreme body mass index increase.

CONCLUSIONS

Our study in a lower-income sub-Saharan African population confirms higher weight gain with DTG-based regimens compared with traditional ART for treatment-naïve patients.

Site-Level Comprehensiveness of Care Is Associated with Individual Clinical Retention Among Adults Living with HIV in International Epidemiology Databases to Evaluate AIDS, a Global HIV Cohort Collaboration, 2000-2016

Retention in care (RIC) reduces HIV transmission and associated morbidity and mortality. We examined whether delivery of comprehensive services influenced individual RIC within the International epidemiology Databases to Evaluate AIDS (IeDEA) network. We collected site data through IeDEA assessments 1.0 (2000-2009) and 2.0 (2010-2016). Each site received a comprehensiveness score for service availability (1 = present, 0 = absent), with tallies ranging from 0 to 7. We obtained individual-level cohort data for adults with at least one visit from 2000 to 2016 at sites responding to either assessment. Person-time was recorded annually, with RIC defined as completing two visits at least 90 days apart in each calendar year. Multivariable modified Poisson regression clustered by site yielded risk ratios and predicted probabilities for individual RIC by comprehensiveness. Among 347,060 individuals in care at 122 sites with 1,619,558 person-years of follow-up, 69.8% of person-time was retained in care, varying by region from 53.8% (Asia-Pacific) to 82.7% (East Africa); RIC improved by about 2% per year from 2000 to 2016 (p = 0.012). Every site provided CD4+ count testing, and >90% of individuals received care at sites that provided combination antiretroviral therapy adherence measures, prevention of mother-to-child transmission, tuberculosis screening, HIV-related prevention, and community tracing services. In adjusted models, individuals at sites with more comprehensive services had higher probabilities of RIC (0.71, 0.74, and 0.83 for scores 5, 6, and 7, respectively; p = 0.019). Within IeDEA, greater site-level comprehensiveness of services was associated with improved individual RIC. Much work remains in exploring this relationship, which may inform HIV clinical practice and health systems planning.

Contraceptive implant use duration is not associated with breakthrough pregnancy among women living with HIV and using efavirenz: a retrospective, longitudinal analysis

Introduction

Contraceptive implants containing etonogestrel and levonorgestrel have emerged as popular contraceptive options among women in areas of high HIV burden in sub‐Saharan Africa. However, recent pharmacokinetic data have shown drug–drug interactions between implants and efavirenz‐containing antiretroviral therapy (ART), reducing the effectiveness of the implants. Here, we evaluated pregnancy incidence in 6‐month intervals following implant initiation among women using efavirenz and contraceptive implants to assess whether the risk of breakthrough pregnancy is higher after specific periods of implant use.

Methods

We used data from a retrospective longitudinal analysis of women living with HIV ages 18–45 years in western Kenya who attended HIV‐care facilities between 2011 and 2015. We used Cox proportional hazard models to compute hazard ratios (HRs) for breakthrough pregnancy by implant type and ART regimen. Depending on the model, we adjusted for socio‐demographic and clinical factors, programme, site and interaction between calendar time and ART regimen. We utilized inverse probability weights (IPWs) to account for three sampling phases (electronic medical record [EMR], chart review and phone interview) and calculated overall parameter estimates.

Results

Women contributed 14,768 woman‐years from the largest sampling phase (EMR). The median age was 31 years. Women used etonogestrel implants for 26–69% of the time and levonorgestrel implants for 7–31% of the time, depending on the sampling phase. Women used efavirenz, nevirapine or no ART for 27–33%, 40–46% and 15–26% of follow‐ups, respectively. When combining sampling phases, there was little evidence to suggest that the relative hazard of pregnancy among efavirenz‐containing ART users relative to nevirapine‐containing ART changed with length of time on implants: IPW‐adjusted HR of 3.1 (CI: [1.5; 6.4]) at 12 months, 3.4 (CI: [1.8; 6.3]) at 24 months, 3.8 (CI: [1.9; 7.7]) at 36 months and 4.2 (CI: [1.6; 11.1]) at 48 months (interaction p‐value = 0.88). Similarly, no significant change in HRs over time was found when comparing women not using ART to nevirapine‐containing ART users (interaction p‐value = 0.49).

Conclusions

We did not find evidence to suggest implants being more fallible from drug–drug interactions with efavirenz at later time intervals of implant use. Thus, we would not recommend shortening the duration of implant use or replacing implants sooner when concomitantly used with efavirenz.

Factors that differentiate COVID-19 vaccine intentions among Indiana parents: Implications for targeted vaccine promotion

Given low rates of uptake of the COVID-19 vaccine for children 12-17 and 5-11 years old, research is needed to understand parental behaviors and behavioral intentions related to COVID-19 vaccination for their children. In the state of Indiana, we conducted a non-random, online survey of parents or caregivers (N = 10,266) about their COVID-19 vaccine intentions or behaviors, demographic characteristics, and potential motivating reasons for getting the vaccine. In terms of behaviors/intentions, 44.8% of participants indicated they were vaccine acceptors (i.e., had already had their children vaccinated or would as soon as it was possible), 13.0% indicated they were vaccine hesitators (i.e., wanted to wait and see), and 42.2% indicated they were vaccine rejecters (i.e., would not vaccinate or only would if mandated). Compared to vaccine rejecters, vaccine hesitators were more likely to be motivated by perceptions of vaccine safety and efficacy, normative influences such as close friends/family who had been vaccinated and a recommendation from a provider, as well as if they were vaccinated themselves. These findings have implications for the development of targeted vaccine promotion strategies, such as social norms messaging and a focus on vaccine safety, in order to increase COVID-19 vaccination for eligible children.

Semiparametric marginal regression for clustered competing risks data with missing cause of failure

Clustered competing risks data are commonly encountered in multicenter studies. The analysis of such data is often complicated due to informative cluster size (ICS), a situation where the outcomes under study are associated with the size of the cluster. In addition, the cause of failure is frequently incompletely observed in real-world settings. To the best of our knowledge, there is no methodology for population-averaged analysis with clustered competing risks data with an ICS and missing causes of failure. To address this problem, we consider the semiparametric marginal proportional cause-specific hazards model and propose a maximum partial pseudolikelihood estimator under a missing at random assumption. To make the latter assumption more plausible in practice, we allow for auxiliary variables that may be related to the probability of missingness. The proposed method does not impose assumptions regarding the within-cluster dependence and allows for ICS. The asymptotic properties of the proposed estimators for both regression coefficients and infinite-dimensional parameters, such as the marginal cumulative incidence functions, are rigorously established. Simulation studies show that the proposed method performs well and that methods that ignore the within-cluster dependence and the ICS lead to invalid inferences. The proposed method is applied to competing risks data from a large multicenter HIV study in sub-Saharan Africa where a significant portion of causes of failure is missing.

Virologic non-suppression and early loss to follow up among pregnant and non-pregnant adolescents aged 15-19 years initiating antiretroviral therapy in South Africa: a retrospective cohort study

Introduction

Older adolescents aged 15–19 years continue to have high rates of loss to follow up (LTFU), and high rates of virologic non‐suppression (VNS) compared to younger adolescents and adults. Adolescent females are at risk of pregnancy, which puts those living with HIV at a dual vulnerability. Our study assessed the factors associated with VNS and LTFU in older adolescents (including pregnant females) who initiated antiretroviral therapy (ART) in South Africa.

Methods

We included adolescents aged 15–19 years initiating ART between 2004 and 2019, with ≥ one viral load (VL) measurement between 4 and 24.5 months, and ≥ 6 months follow‐up, from six South African cohorts of the International epidemiology Databases to Evaluate AIDS‐Southern Africa (IeDEA‐SA). We defined VNS as VL ≥400 copies/ml and LTFU as not being in care for ≥180 days from ART start and not known as transferred out of the clinic or dead in the first 24 months on ART. We examined factors associated with VNS and LTFU using Fine&Gray competing risk models.

Results

We included a total of 2733 adolescents, 415 (15.2%) males, median (IQR) age at ART start of 18.6 (17.3, 19.4) years. Among females, 585/2318 (25.2%) were pregnant. Over the 24‐month follow‐up, 424 (15.5%) of all adolescents experienced VNS: range (11.1% pregnant females and 20.5% males). Over half of all adolescents were LTFU before any other event could occur. The hazard of VNS reduced with increasing age and CD4 count above 200 cells/μl at ART initiation among all adolescents having adjusted for all measured patient characteristics [adjusted sub‐distribution hazard ratio (aSHR) 19 vs. 15 years: 0.50 (95% CI: 0.36, 0.68), aSHR: >500 vs. ≤200 cells/μl: 0.22 (95% CI: 0.16, 0.31)]. The effect of CD4 count persisted in pregnant females. Increasing age and CD4 count >200 cells/μl were risk factors for LTFU among all adolescents.

Conclusions

Older adolescents had a high risk of LTFU shortly after ART start and a low risk of VNS, especially those initiating treatment during pregnancy. Interventions addressing adherence and retention should be incorporated into adolescent‐friendly services to prevent VNS and LTFU and endeavour to trace lost adolescents as soon as they are identified.

Achieving consistency in measures of HIV-1 viral suppression across countries: derivation of an adjustment based on international antiretroviral treatment cohort data

INTRODUCTION

The third of the Joint United Nations Programme on HIV/AIDS (UNAIDS) 90-90-90 targets is to achieve a 90% rate of viral suppression (HIV viral load <1000 HIV-1 RNA copies/ml) in patients on antiretroviral treatment (ART) by 2020. However, some countries use different thresholds when reporting viral suppression, and there is thus a need for an adjustment to standardize estimates to the <1000 threshold. We aim to propose such an adjustment, to support consistent monitoring of progress towards the "third 90" target.

METHODS

We considered three possible distributions for viral loads in ART patients: Weibull, Pareto and reverse Weibull (imposing an upper limit but no lower limit on the log scale). The models were fitted to data on viral load distributions in ART patients in the International epidemiology Databases to Evaluate AIDS (IeDEA) collaboration (representing seven global regions) and the ART Cohort Collaboration (representing Europe), using separate random effects models for adults and children. The models were validated using data from the World Health Organization (WHO) HIV drug resistance report and the Brazilian national ART programme.

RESULTS

Models were calibrated using 921,157 adult and 37,431 paediatric viral load measurements, over 2010-2019. The Pareto and reverse Weibull models provided the best fits to the data, but for all models, the "shape" parameters for the viral load distributions differed significantly between regions. The Weibull model performed best in the validation against the WHO drug resistance survey data, while the Pareto model produced uncertainty ranges that were too narrow, relative to the validation data. Based on these analyses, we recommend using the reverse Weibull model. For example, if a country reports an 80% rate of viral suppression at <200 copies/ml, this model estimates the proportion virally suppressed at <1000 copies/ml is 88.3% (0.80^0.56 ), with uncertainty range 85.5-90.6% (0.80^0.70 -0.80^0.44 ).

CONCLUSIONS

Estimates of viral suppression can change substantially depending on the threshold used in defining viral suppression. It is, therefore, important that viral suppression rates are standardized to the same threshold for the purpose of assessing progress towards UNAIDS targets. We have proposed a simple adjustment that allows this, and this has been incorporated into UNAIDS modelling software.

Effects of National Adoption of Treat-All Guidelines on Pre-Antiretroviral Therapy (ART) CD4 Testing and Viral Load Monitoring After ART initiation: A Regression Discontinuity Analysis

BACKGROUND

The World Health Organization's Treat-All guidance recommends CD4 testing before initiating antiretroviral therapy (ART), and routine viral load (VL) monitoring (over CD4 monitoring) for patients on ART.

METHODS

We used regression discontinuity analyses to estimate changes in CD4 testing and VL monitoring among 547 837 ART-naive patients enrolling in human immunodeficiency virus (HIV) care during 2006-2018 at 225 clinics in 26 countries where Treat-All policies were adopted. We examined CD4 testing within 12 months before and VL monitoring 6 months after ART initiation among adults (≥20 years), adolescents (10-19 years), and children (0-9 years) in low/lower-middle-income countries (L/LMICs) and high/upper-middle-income countries (H/UMICs).

RESULTS

Treat-All adoption led to an immediate decrease in pre-ART CD4 testing among adults in L/LMICs, from 57.0% to 48.1% (-8.9 percentage points [pp]; 95% CI: -11.0, -6.8), and a small increase in H/UMICs, from 90.1% to 91.7% (+1.6pp; 95% CI: 0.2, 3.0), with no changes among adolescents or children; decreases in pre-ART CD4 testing accelerated after Treat-All adoption in L/LMICs. In L/LMICs, VL monitoring after ART initiation was low among all patients in L/LMICs before Treat-All; while there was no immediate change at Treat-All adoption, VL monitoring trends significantly increased afterwards. VL monitoring increased among adults immediately after Treat-All adoption, from 58.2% to 61.1% (+2.9pp; 95% CI: 0.5, 5.4), with no significant changes among adolescents/children.

CONCLUSIONS

While on-ART VL monitoring has improved in L/LMICs, Treat-All adoption has accelerated and disparately worsened suboptimal pre-ART CD4 monitoring, which may compromise care outcomes for individuals with advanced HIV.

Global HIV mortality trends among children on antiretroviral treatment corrected for under-reported deaths: an updated analysis of the International epidemiology Databases to Evaluate AIDS collaboration

INTRODUCTION

The Joint United Nations Programme on HIV/AIDS (UNAIDS) projections of paediatric HIV prevalence and deaths rely on the International epidemiology Databases to Evaluate AIDS (IeDEA) consortium for mortality estimates among children living with HIV (CHIV) receiving antiretroviral therapy (ART). Previous estimates, based on data through 2014, may no longer be accurate due to expanded paediatric HIV care and treatment eligibility, and the possibility of unreported deaths in CHIV considered lost to follow-up (LTFU). We therefore estimated all-cause mortality and its trends in CHIV (<15 years old) on ART using extended and new IeDEA data.

METHODS

We analysed (i) IeDEA observational data from CHIV in routine care globally, and (ii) novel data from an IeDEA tracing study that determined outcomes in a sample of CHIV after being LTFU in southern Africa. We included 45,711 CHIV on ART during 2004 to 2017 at 72 programmes in Africa, Asia-Pacific and Latin America. We used mixed effects Poisson regression to estimate mortality by age, sex, CD4 at ART start, time on ART, region and calendar year. For Africa, in an adjusted analysis that accounts for unreported deaths among those LTFU, we first modified the routine data by simulating mortality outcomes within six months after LTFU, based on a Gompertz survival model fitted to the tracing data (n = 221).

RESULTS

Observed mortality rates were 1.8 (95% CI: 1.7 to 1.9) and 9.4 (6.3 to 13.4) deaths per 100 person-years in the routine and tracing data, respectively. We found strong evidence of higher mortality at shorter ART durations, lower CD4 values, and in infancy. Averaging over covariate patterns, the adjusted mortality rate was 54% higher than the unadjusted rate. In unadjusted analyses, mortality reduced by an average 60% and 73% from 2005 to 2017, within and outside of Africa, respectively. In the adjusted analysis for Africa, this temporal reduction was 42%.

CONCLUSIONS

Mortality rates among CHIV have decreased substantially over time. However, when accounting for worse outcomes among those LTFU, mortality estimates increased and temporal improvements were slightly reduced, suggesting caution in interpreting analyses based only on programme data. The improved and updated IeDEA estimates on mortality among CHIV on ART support UNAIDS efforts to accurately model global HIV statistics.

Pregnancies among women living with HIV using contraceptives and antiretroviral therapy in western Kenya: a retrospective, cohort study

BACKGROUND

Preventing unintended pregnancies is paramount for women living with HIV (WLHIV). Previous studies have suggested that efavirenz-containing antiretroviral therapy (ART) reduces contraceptive effectiveness of implants, but there are uncertainties regarding the quality of the electronic medical record (EMR) data used in these prior studies.

METHODS

We conducted a retrospective, cohort study of EMR data from 2011 to 2015 among WLHIV of reproductive age accessing HIV care in public facilities in western Kenya. We validated a large subsample of records with manual chart review and telephone interviews. We estimated adjusted incidence rate ratios (aIRRs) with Poisson regression accounting for the validation sampling using inverse probability weighting and generalized raking.

RESULTS

A total of 85,324 women contributed a total of 170,845 women-years (w-y) of observation time; a subset of 5080 women had their charts reviewed, and 1285 underwent interviews. Among implant users, the aIRR of pregnancy for efavirenz- vs. nevirapine-containing ART was 1.9 (95% CI 1.6, 2.4) using EMR data only and 3.2 (95% CI 1.8, 5.7) when additionally using both chart review and interview validated data. Among efavirenz users, the aIRR of pregnancy for depomedroxyprogesterone acetate (DMPA) vs. implant use was 1.8 (95% CI 1.5, 2.1) in EMR only and 2.4 (95% CI 1.0, 6.1) using validated data.

CONCLUSION

Pregnancy rates are higher when contraceptive implants are concomitantly used with efavirenz-containing ART, though rates were similar to leading alternative contraceptive methods such as DMPA. Our data provides policymakers, program staff, and WLHIV greater confidence in guiding their decision-making around contraceptive and ART options. Our novel, 3-phase validation sampling provides an innovative tool for using routine EMR data to improve the robustness of data quality.

Compartmentalization of cerebrospinal fluid inflammation across the spectrum of untreated HIV-1 infection, central nervous system injury and viral suppression

OBJECTIVE

To characterize the evolution of central nervous system (CNS) inflammation in HIV-1 infection applying a panel of cerebrospinal fluid (CSF) inflammatory biomarkers to grouped subjects representing a broad spectrum of systemic HIV-1 immune suppression, CNS injury and viral control.

METHODS

This is a cross-sectional analysis of archived CSF and blood samples, assessing concentrations of 10 functionally diverse soluble inflammatory biomarkers by immunoassays in 143 HIV-1-infected subjects divided into 8 groups: untreated primary HIV-1 infection (PHI); four untreated groups defined by their blood CD4+ T lymphocyte counts; untreated patients presenting with subacute HIV-associated dementia (HAD); antiretroviral-treated subjects with ≥1 years of plasma viral suppression; and untreated elite controllers. Twenty HIV-1-uninfected controls were included for comparison. Background biomarkers included blood CD4+ and CD8+ T lymphocytes, CSF and blood HIV-1 RNA, CSF white blood cell (WBC) count, CSF/blood albumin ratio, CSF neurofilament light chain (NfL), and CSF t-tau.

FINDINGS

HIV-1 infection was associated with a broad compartmentalized CSF inflammatory response that developed early in its course and changed with systemic disease progression, development of neurological injury, and viral suppression. CSF inflammation in untreated individuals without overt HAD exhibited at least two overall patterns of inflammation as blood CD4+ T lymphocytes decreased: one that peaked at 200-350 blood CD4+ T cells/μL and associated with lymphocytic CSF inflammation and HIV-1 RNA concentrations; and a second that steadily increased through the full range of CD4+ T cell decline and associated with macrophage responses and increasing CNS injury. Subacute HAD was distinguished by a third inflammatory profile with increased blood-brain barrier permeability and robust combined lymphocytic and macrophage CSF inflammation. Suppression of CSF and blood HIV-1 infections by antiretroviral treatment and elite viral control were associated with reduced CSF inflammation, though not fully to levels found in HIV-1 seronegative controls.

How Many SARS-CoV-2-Infected People Require Hospitalization? Using Random Sample Testing to Better Inform Preparedness Efforts

CONTEXT

Existing hospitalization ratios for COVID-19 typically use case counts in the denominator, which problematically underestimates total infections because asymptomatic and mildly infected persons rarely get tested. As a result, surge models that rely on case counts to forecast hospital demand may be inaccurately influencing policy and decision-maker action.

OBJECTIVE

Based on SARS-CoV-2 prevalence data derived from a statewide random sample (as opposed to relying on reported case counts), we determine the infection-hospitalization ratio (IHR), defined as the percentage of infected individuals who are hospitalized, for various demographic groups in Indiana. Furthermore, for comparison, we show the extent to which case-based hospitalization ratios, compared with the IHR, overestimate the probability of hospitalization by demographic group.

DESIGN

Secondary analysis of statewide prevalence data from Indiana, COVID-19 hospitalization data extracted from a statewide health information exchange, and all reported COVID-19 cases to the state health department.

SETTING

State of Indiana as of April 30, 2020.

MAIN OUTCOME MEASURES

Demographic-stratified IHRs and case-hospitalization ratios.

RESULTS

The overall IHR was 2.1% and varied more by age than by race or sex. Infection-hospitalization ratio estimates ranged from 0.4% for those younger than 40 years to 9.2% for those older than 60 years. Hospitalization rates based on case counts overestimated the IHR by a factor of 10, but this overestimation differed by demographic groups, especially age.

CONCLUSIONS

In this first study of the IHR based on population prevalence, our results can improve forecasting models of hospital demand-especially in preparation for the upcoming winter period when an increase in SARS CoV-2 infections is expected.

Bayesian estimation of SARS-CoV-2 prevalence in Indiana by random testing

From 25 to 29 April 2020, the state of Indiana undertook testing of 3,658 randomly chosen state residents for the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus, the agent causing COVID-19 disease. This was the first statewide randomized study of COVID-19 testing in the United States. Both PCR and serological tests were administered to all study participants. This paper describes statistical methods used to address nonresponse among various demographic groups and to adjust for testing errors to reduce bias in the estimates of the overall disease prevalence in Indiana. These adjustments were implemented through Bayesian methods, which incorporated all available information on disease prevalence and test performance, along with external data obtained from census of the Indiana statewide population. Both adjustments appeared to have significant impact on the unadjusted estimates, mainly due to upweighting data in study participants of non-White races and Hispanic ethnicity and anticipated false-positive and false-negative test results among both the PCR and antibody tests utilized in the study.

Semiparametric regression on cumulative incidence function with interval-censored competing risks data and missing event types

Competing risk data are frequently interval-censored, that is, the exact event time is not observed but only known to lie between two examination time points such as clinic visits. In addition to interval censoring, another common complication is that the event type is missing for some study participants. In this article, we propose an augmented inverse probability weighted sieve maximum likelihood estimator for the analysis of interval-censored competing risk data in the presence of missing event types. The estimator imposes weaker than usual missing at random assumptions by allowing for the inclusion of auxiliary variables that are potentially associated with the probability of missingness. The proposed estimator is shown to be doubly robust, in the sense that it is consistent even if either the model for the probability of missingness or the model for the probability of the event type is misspecified. Extensive Monte Carlo simulation studies show good performance of the proposed method even under a large amount of missing event types. The method is illustrated using data from an HIV cohort study in sub-Saharan Africa, where a significant portion of events types is missing. The proposed method can be readily implemented using the new function ciregic_aipw in the R package intccr.

A semiparametric method for the analysis of outcomes during a gap in HIV care under incomplete outcome ascertainment

Objectives

Estimation of the cascade of HIV care is essential for evaluating care and treatment programs, informing policy makers and assessing targets such as 90-90-90. A challenge to estimating the cascade based on electronic health record concerns patients "churning" in and out of care. Correctly estimating this dynamic phenomenon in resource-limited settings, such as those found in sub-Saharan Africa, is challenging because of the significant death under-reporting. An approach to partially recover information on the unobserved deaths is a double-sampling design, where a small subset of individuals with a missed clinic visit is intensively outreached in the community to actively ascertain their vital status. This approach has been adopted in several programs within the East Africa regional IeDEA consortium, the context of our motivating study. The objective of this paper is to propose a semiparametric method for the analysis of competing risks data with incomplete outcome ascertainment.

Methods

Based on data from double-sampling designs, we propose a semiparametric inverse probability weighted estimator of key outcomes during a gap in care, which are crucial pieces of the care cascade puzzle.

Results

Simulation studies suggest that the proposed estimators provide valid estimates in settings with incomplete outcome ascertainment under a set of realistic assumptions. These studies also illustrate that a naïve complete-case analysis can provide seriously biased estimates. The methodology is applied to electronic health record data from the East Africa IeDEA Consortium to estimate death and return to care during a gap in care.

Conclusions

The proposed methodology provides a robust approach for valid inferences about return to care and death during a gap in care, in settings with death under-reporting. Ultimately, the resulting estimates will have significant consequences on program construction, resource allocation, policy and decision making at the highest levels.

Lower rates of ART initiation and decreased retention among ART-naïve patients who consume alcohol enrolling in HIV care and treatment programs in Kenya and Uganda

Objectives

Almost 13 million people are estimated to be on antiretroviral therapy in Eastern and Southern Africa, and their disease course and program effectiveness could be significantly affected by the concurrent use of alcohol. Screening for alcohol use may be important to assess the prevalence of alcohol consumption and its impact on patient and programmatic outcomes.

Methods

As part of this observational study, data on patient characteristics and alcohol consumption were collected on a cohort of 765 adult patients enrolling in HIV care in East Africa. Alcohol consumption was assessed with the AUDIT questionnaire at enrollment. Subjects were classified as consuming any alcohol (AUDIT score >0), hazardous drinkers (AUDIT score ≥8) and hyper drinkers (AUDIT score ≥16). The effects of alcohol consumption on retention in care, death and delays in antiretroviral therapy (ART) initiation were assessed through competing risk (Fine & Gray) models.

Results

Of all study participants, 41.6% consumed alcohol, 26.7% were classified as hazardous drinkers, and 16.0% as hyper drinkers. Depending on alcohol consumption classification, men were 3–4 times more likely to consume alcohol compared to women. Hazardous drinkers (median age 32.8 years) and hyper drinkers (32.7 years) were slightly older compared to non-hazardous drinkers (30.7 years) and non-hyper drinkers (30.8 years), (p-values = 0.014 and 0.053 respectively). Median CD4 at enrollment was 330 cells/μl and 16% were classified World Health Organization (WHO) stage 3 or 4. There was no association between alcohol consumption and CD4 count or WHO stage at enrollment. Alcohol consumption was associated with significantly lower probability of ART initiation (adjusted sub-distribution hazard ratio aSHR = 0.77 between alcohol consumers versus non-consumers; p-value = 0.008), and higher patient non-retention in care (aSHR = 1.77, p-value = 0.023).

Discussion

Alcohol consumption is associated with significant delays in ART initiation and reduced retention in care for patients enrolling in HIV care and treatment programs in East Africa. Consequently, interventions that target alcohol consumption may have a significant impact on the HIV care cascade.

Semiparametric regression and risk prediction with competing risks data under missing cause of failure

The cause of failure in cohort studies that involve competing risks is frequently incompletely observed. To address this, several methods have been proposed for the semiparametric proportional cause-specific hazards model under a missing at random assumption. However, these proposals provide inference for the regression coefficients only, and do not consider the infinite dimensional parameters, such as the covariate-specific cumulative incidence function. Nevertheless, the latter quantity is essential for risk prediction in modern medicine. In this paper we propose a unified framework for inference about both the regression coefficients of the proportional cause-specific hazards model and the covariate-specific cumulative incidence functions under missing at random cause of failure. Our approach is based on a novel computationally efficient maximum pseudo-partial-likelihood estimation method for the semiparametric proportional cause-specific hazards model. Using modern empirical process theory we derive the asymptotic properties of the proposed estimators for the regression coefficients and the covariate-specific cumulative incidence functions, and provide methodology for constructing simultaneous confidence bands for the latter. Simulation studies show that our estimators perform well even in the presence of a large fraction of missing cause of failures, and that the regression coefficient estimator can be substantially more efficient compared to the previously proposed augmented inverse probability weighting estimator. The method is applied using data from an HIV cohort study and a bladder cancer clinical trial.

Population Point Prevalence of SARS-CoV-2 Infection Based on a Statewide Random Sample - Indiana, April 25-29, 2020

Population prevalence of persons infected with SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19), varies by subpopulation and locality. U.S. studies of SARS-CoV-2 infection have examined infections in nonrandom samples (1) or seroprevalence in specific populations* (2), which are limited in their generalizability and cannot be used to accurately calculate infection-fatality rates. During April 25-29, 2020, Indiana conducted statewide random sample testing of persons aged ≥12 years to assess prevalence of active infection and presence of antibodies to SARS-CoV-2; additional nonrandom sampling was conducted in racial and ethnic minority communities to better understand the impact of the virus in certain racial and ethnic minority populations. Estimates were adjusted for nonresponse to reflect state demographics using an iterative proportional fitting method. Among 3,658 noninstitutionalized participants in the random sample survey, the estimated statewide point prevalence of active SARS-CoV-2 infection confirmed by reverse transcription-polymerase chain reaction (RT-PCR) testing was 1.74% (95% confidence interval [CI] = 1.10-2.54); 44.2% of these persons reported no symptoms during the 2 weeks before testing. The prevalence of immunoglobulin G (IgG) seropositivity, indicating past infection, was 1.09% (95% CI = 0.76-1.45). The overall prevalence of current and previous infections of SARS-CoV-2 in Indiana was 2.79% (95% CI = 2.02-3.70). In the random sample, higher overall prevalences were observed among Hispanics and those who reported having a household contact who had previously been told by a health care provider that they had COVID-19. By late April, an estimated 187,802 Indiana residents were currently or previously infected with SARS-CoV-2 (9.6 times higher than the number of confirmed cases [17,792]) (3), and 1,099 residents died (infection-fatality ratio = 0.58%). The number of reported cases represents only a fraction of the estimated total number of infections. Given the large number of persons who remain susceptible in Indiana, adherence to evidence-based public health mitigation and containment measures (e.g., social distancing, consistent and correct use of face coverings, and hand hygiene) is needed to reduce surge in hospitalizations and prevent morbidity and mortality from COVID-19.

A pseudo-likelihood method for estimating misclassification probabilities in competing-risks settings when true-event data are partially observed

Outcome misclassification occurs frequently in binary-outcome studies and can result in biased estimation of quantities such as the incidence, prevalence, cause-specific hazards, cumulative incidence functions, and so forth. A number of remedies have been proposed to address the potential misclassification of the outcomes in such data. The majority of these remedies lie in the estimation of misclassification probabilities, which are in turn used to adjust analyses for outcome misclassification. A number of authors advocate using a gold-standard procedure on a sample internal to the study to learn about the extent of the misclassification. With this type of internal validation, the problem of quantifying the misclassification also becomes a missing data problem as, by design, the true outcomes are only ascertained on a subset of the entire study sample. Although, the process of estimating misclassification probabilities appears simple conceptually, the estimation methods proposed so far have several methodological and practical shortcomings. Most methods rely on missing outcome data to be missing completely at random (MCAR), a rather stringent assumption which is unlikely to hold in practice. Some of the existing methods also tend to be computationally-intensive. To address these issues, we propose a computationally-efficient, easy-to-implement, pseudo-likelihood estimator of the misclassification probabilities under a missing at random (MAR) assumption, in studies with an available internal-validation sample. We present the estimator through the lens of studies with competing-risks outcomes, though the estimator extends beyond this setting. We describe the consistency and asymptotic distributional properties of the resulting estimator, and derive a closed-form estimator of its variance. The finite-sample performance of this estimator is evaluated via simulations. Using data from a real-world study with competing-risks outcomes, we illustrate how the proposed method can be used to estimate misclassification probabilities. We also show how the estimated misclassification probabilities can be used in an external study to adjust for possible misclassification bias when modeling cumulative incidence functions.

Weight-for-age distributions among children with HIV on antiretroviral therapy in the International epidemiology Databases to Evaluate AIDS (IeDEA) multiregional consortium

Objective

Pediatric antiretroviral therapy (ART) for children with HIV (CHIV) must be dosed appropriately for children’s changing weights as they grow. To inform accurate estimates of ART formulations and doses needed, we described weight-for-age distributions among CHIV on ART in the IeDEA global pediatric collaboration between 2004 and 2016, using data from six regions (East, West, Central, and Southern Africa, Asia–Pacific, and Central/South America and the Caribbean).

Results

Overall, 59,862 children contributed to the analysis. Age and weight data were available from 530,080 clinical encounters for girls and 537,894 for boys. For each one-year age stratum from 0 to 15 years, we calculated the proportion of children in each of the weight bands designated by the World Health Organization as relevant to pediatric ART formulations: 0 to  < 3 kg, 3 to  < 6 kg, 6 to  < 10 kg, 10 to  < 14 kg, 14 to  < 20 kg, 20 to  < 25 kg, 25 to  < 30 kg, 30 to  < 35 kg, 35 to  < 40 kg, 40 to  < 45 kg, 45 to  < 50 kg, 50 to  < 55 kg, 55 to  < 60 kg, and ≥ 60 kg. Data are reported for the entire cohort, as well as stratified by sex and IeDEA region, calendar year of ART use, and duration on ART at time of assessment (< 12 or ≥ 12 months), provided in data tables. These data are critical to improve the accuracy of forecasting and procurement of pediatric ART formulations as the pediatric HIV epidemic and pediatric HIV treatment strategies evolve.

Diagnostic and Prognostic Value of JC Virus DNA in Plasma in Progressive Multifocal Leukoencephalopathy

Background

Progressive multifocal leukoencephalopathy (PML) is a severe demyelinating disease caused by the polyomavirus JC (John Cunningham; JCV) that affects patients with impaired immune systems. While JCV-DNA detection in cerebrospinal fluid (CSF) is diagnostic of PML, the clinical significance of plasma JCV-DNA is uncertain.

Methods

We retrospectively analyzed plasma samples from PML patients that were drawn close to disease onset and from controls without PML. In PML patients, we compared plasma JCV-DNA detection and levels to clinical and laboratory parameters, and patient survival.

Results

JCV-DNA was detected in plasma of 49/103 (48%) patients with PML (20/24, 83%, human immunodeficiency virus [HIV] negative; 29/79, 37%, HIV-positive) and of 4/144 (3%) controls without PML (0/95 HIV-negative; 4/49, 8%, HIV-positive), yielding a diagnostic sensitivity and specificity of 48% and 97% (83% and 100% in HIV-negative; 37% and 92% in HIV-positive), respectively. Among 16 PML patients with undetectable CSF JCV-DNA, 4 (25%) had detectable plasma JCV-DNA. Plasma JCV-DNA levels were independently associated with CSF levels (P < .0001) and previous corticosteroid treatment (P = .012). Higher plasma JCV-DNA levels were associated with disease progression in HIV-negative patients (P = .005); in HIV-positive patients, there was an increased risk of progression only in those treated with combination antiretroviral therapy (cART; P < .0001).

Conclusions

Testing JCV-DNA in plasma might complement PML diagnosis, especially when CSF is unavailable or JCV-DNA not detectable in CSF. In addition, JCV-DNA plasma levels could be useful as a marker of disease progression in both HIV-negative and cART-treated, HIV-positive PML patients.

Nonparametric estimation of the cumulative incidence function under outcome misclassification using external validation data

Misclassification of outcomes or event types is common in health sciences research and can lead to serious bias when estimating the cumulative incidence functions in settings with competing risks. Recent work has shown how to estimate nonparametric cumulative incidence functions in the presence of nondifferential outcome misclassification when the misclassification probabilities are known. Here, we extend this approach to account for misclassification that is differential with respect to important predictors of the outcome using misclassification probabilities estimated from external validation data. Moreover, we propose a bootstrap approach in which the observations from both the main study data and the external validation study are resampled to allow the uncertainty in the misclassification probabilities to propagate through the analysis into the final confidence intervals, ensuring appropriate confidence interval coverage probabilities. The proposed estimator is shown to be uniformly consistent and simulation studies indicate that both the estimator and the standard error estimation approach perform well in finite samples. The methodology is applied to estimate the cumulative incidence of death and disengagement from HIV care in a large cohort of HIV infected individuals in sub-Saharan Africa, where a significant death underreporting issue leads to outcome misclassification. This analysis uses external validation data from a separate study conducted in the same country.

Changes in rapid HIV treatment initiation after national "treat all" policy adoption in 6 sub-Saharan African countries: Regression discontinuity analysis

BACKGROUND

Most countries have formally adopted the World Health Organization's 2015 recommendation of universal HIV treatment ("treat all"). However, there are few rigorous assessments of the real-world impact of treat all policies on antiretroviral treatment (ART) uptake across different contexts.

METHODS AND FINDINGS

We used longitudinal data for 814,603 patients enrolling in HIV care between 1 January 2004 and 10 July 2018 in 6 countries participating in the global International epidemiology Databases to Evaluate AIDS (IeDEA) consortium: Burundi (N = 11,176), Kenya (N = 179,941), Malawi (N = 84,558), Rwanda (N = 17,396), Uganda (N = 96,286), and Zambia (N = 425,246). Using a quasi-experimental regression discontinuity design, we assessed the change in the proportion initiating ART within 30 days of enrollment in HIV care (rapid ART initiation) after country-level adoption of the treat all policy. A modified Poisson model was used to identify factors associated with failure to initiate ART rapidly under treat all. In each of the 6 countries, over 60% of included patients were female, and median age at enrollment ranged from 32 to 36 years. In all countries studied, national adoption of treat all was associated with large increases in rapid ART initiation. Significant increases in rapid ART initiation immediately after treat all policy adoption were observed in Rwanda, from 44.4% to 78.9% of patients (34.5 percentage points [pp], 95% CI 27.2 to 41.7; p < 0.001), Kenya (25.7 pp, 95% CI 21.8 to 29.5; p < 0.001), Burundi (17.7 pp, 95% CI 6.5 to 28.9; p = 0.002), and Malawi (12.5 pp, 95% CI 7.5 to 17.5; p < 0.001), while no immediate increase was observed in Zambia (0.4 pp, 95% CI -2.9 to 3.8; p = 0.804) and Uganda (-4.2 pp, 95% CI -9.0 to 0.7; p = 0.090). The rate of rapid ART initiation accelerated sharply following treat all policy adoption in Malawi, Uganda, and Zambia; slowed in Kenya; and did not change in Rwanda and Burundi. In post hoc analyses restricted to patients enrolling under treat all, young adults (16-24 years) and men were at increased risk of not rapidly initiating ART (compared to older patients and women, respectively). However, rapid ART initiation following enrollment increased for all groups as more time elapsed since treat all policy adoption. Study limitations include incomplete data on potential ART eligibility criteria, such as clinical status, pregnancy, and enrollment CD4 count, which precluded the assessment of rapid ART initiation specifically among patients known to be eligible for ART before treat all.

CONCLUSIONS

Our analysis indicates that adoption of treat all policies had a strong effect on increasing rates of rapid ART initiation, and that these increases followed different trajectories across the 6 countries. Young adults and men still require additional attention to further improve rapid ART initiation.

Semiparametric competing risks regression under interval censoring using the R package intccr

BACKGROUND AND OBJECTIVE

Competing risk data are frequently interval-censored in real-world applications, that is, the exact event time is not precisely observed but is only known to lie between two time points such as clinic visits. This type of data requires special handling because the actual event times are unknown. To deal with this problem we have developed an easy-to-use open-source statistical software.

METHODS

An approach to perform semiparametric regression analysis of the cumulative incidence function with interval-censored competing risks data is the sieve maximum likelihood method based on B-splines. An important feature of this approach is that it does not impose restrictive parametric assumptions. Also, this methodology provides semiparametrically efficient estimates. Implementation of this methodology can be easily performed using our new R package intccr.

RESULTS

The R package intccr performs semiparametric regression analysis of the cumulative incidence function based on interval-censored competing risks data. It supports a large class of models including the proportional odds and the Fine-Gray proportional subdistribution hazards model as special cases. It also provides the estimated cumulative incidence functions for a particular combination of covariate values. The package also provides some data management functionality to handle data sets which are in a long format involving multiple lines of data per subject.

CONCLUSIONS

The R package intccr provides a convenient and flexible software for the analysis of the cumulative incidence function based on interval-censored competing risks data.

Research priorities to inform "Treat All" policy implementation for people living with HIV in sub-Saharan Africa: a consensus statement from the International epidemiology Databases to Evaluate AIDS (IeDEA)

INTRODUCTION

"Treat All" - the treatment of all people with HIV, irrespective of disease stage or CD4 cell count - represents a paradigm shift in HIV care that has the potential to end AIDS as a public health threat. With accelerating implementation of Treat All in sub-Saharan Africa (SSA), there is a need for a focused agenda and research to identify and inform strategies for promoting timely uptake of HIV treatment, retention in care, and sustained viral suppression and addressing bottlenecks impeding implementation.

METHODS

The Delphi approach was used to develop consensus around research priorities for Treat All implementation in SSA. Through an iterative process (June 2017 to March 2018), a set of research priorities was collectively formulated and refined by a technical working group and shared for review, deliberation and prioritization by more than 200 researchers, implementation experts, policy/decision-makers, and HIV community representatives in East, Central, Southern and West Africa.

RESULTS AND DISCUSSION

The process resulted in a list of nine research priorities for generating evidence to guide Treat All policies, implementation strategies and monitoring efforts. These priorities highlight the need for increased focus on adolescents, men, and those with mental health and substance use disorders - groups that remain underserved in SSA and for whom more effective testing, linkage and care strategies need to be identified. The priorities also reflect consensus on the need to: (1) generate accurate national and sub-national estimates of the size of key populations and describe those who remain underserved along the HIV-care continuum; (2) characterize the timeliness of HIV care and short- and long-term HIV care continuum outcomes, as well as factors influencing timely achievement of these outcomes; (3) estimate the incidence and prevalence of HIV-drug resistance and regimen switching; and (4) identify cost-effective and affordable service delivery models and strategies to optimize uptake and minimize gaps, disparities, and losses along the HIV-care continuum, particularly among underserved populations.

CONCLUSIONS

Reflecting consensus among a broad group of experts, researchers, policy- and decision-makers, PLWH, and other stakeholders, the resulting research priorities highlight important evidence gaps that are relevant for ministries of health, funders, normative bodies and research networks.

NONPARAMETRIC INFERENCE FOR MARKOV PROCESSES WITH MISSING ABSORBING STATE

This paper deals with the issue of nonparametric estimation of the transition probability matrix of a non-homogeneous Markov process with finite state space and partially observed absorbing state. We impose a missing at random assumption and propose a computationally efficient nonparametric maximum pseudolikelihood estimator (NPMPLE). The estimator depends on a parametric model that is used to estimate the probability of each absorbing state for the missing observations based, potentially, on auxiliary data. For the latter model we propose a formal goodness-of-fit test based on a residual process. Using modern empirical process theory we show that the estimator is uniformly consistent and converges weakly to a tight mean-zero Gaussian random field. We also provide methodology for simultaneous confidence band construction. Simulation studies show that the NPMPLE works well with small sample sizes and that it is robust against some degree of misspecification of the parametric model for the missing absorbing states. The method is illustrated using HIV data from sub-Saharan Africa to estimate the transition probabilities of death and disengagement from HIV care.

Adolescent pregnancy at antiretroviral therapy (ART) initiation: a critical barrier to retention on ART

INTRODUCTION

Adolescence and pregnancy are potential risk factors for loss to follow-up (LTFU) while on antiretroviral therapy (ART). We compared adolescent and adult LTFU after ART initiation to quantify the impact of age, pregnancy, and site-level factors on LTFU.

METHODS

We used routine clinical data for patients initiating ART as young adolescents (YA; 10 to 14 years), older adolescents (OA; 15 to 19 years) and adults (≥20 years) from 2000 to 2014 at 52 health facilities affiliated with the International epidemiology Databases to Evaluate AIDS (IeDEA) East Africa collaboration. We estimated cumulative incidence (95% confidence interval, CI) of LTFU (no clinic visit for ≥6 months after ART initiation) and identified patient and site-level correlates of LTFU, using multivariable Cox proportional hazards models for all patients as well as individual age groups.

RESULTS

A total of 138,387 patients initiated ART, including 2496 YA, 2955 OA and 132,936 adults. Of these, 55%, 78% and 66%, respectively, were female and 0.7% of YA, 22.3% of OA and 8.3% of adults were pregnant at ART initiation. Cumulative incidence of LTFU at five years was 26.6% (24.6 to 28.6) among YA, 44.1% (41.8 to 46.3) among OA and 29.3% (29.1 to 29.6) among adults. Overall, compared to adults, the adjusted hazard ratio, aHR, (95% CI) of LTFU for OA was 1.54 (1.41 to 1.68) and 0.77 (0.69 to 0.86) for YA. Compared to males, pregnant females had higher hazard of LTFU, aHR 1.20 (1.14 to 1.27), and nonpregnant women had lower hazard aHR 0.90 (0.88 to 0.93). LTFU hazard among the OA was primarily driven by both pregnant and nonpregnant females, aHR 2.42 (1.98 to 2.95) and 1.51 (1.27 to 1.80), respectively, compared to men. The LTFU hazard ratio varied by IeDEA program. Site-level factors associated with overall lower LTFU hazard included receiving care in tertiary versus primary-care clinics aHR 0.61 (0.56 to 0.67), integrated adult and adolescent services and food ration provision aHR 0.93 (0.89 to 0.97) versus nonintegrated clinics with food ration provision, having patient support groups aHR 0.77 (0.66 to 0.90) and group adherence counselling aHR 0.61 (0.57 to 0.67).

CONCLUSIONS

Older adolescents experienced higher risk of LTFU compared to YA and adults. Interventions to prevent LTFU among older adolescents are critically needed, particularly for female and/or pregnant adolescents.

Adherence to antiretroviral therapy in a clinical cohort of HIV-infected children in East Africa

OBJECTIVE

To describe antiretroviral therapy (ART) adherence and associated factors for a large HIV-infected pediatric cohort followed by sites of the East Africa International Epidemiologic Databases to Evaluate AIDS (IeDEA) consortium.

METHODS

This study utilized prospectively collected clinical data from HIV-infected children less than 13 years of age who initiated ART within 4 clinical care programs (with 26 clinical sites) in Kenya, Uganda, and Tanzania and were followed for up to 6 years. Programs used one of 3 adherence measures, including 7-day quantitative recall, 7-day categorical recall, and clinician pill assessments. We fit a hierarchical, three-level, logistic-regression model to examine adherence, with observations nested within patient, and patients within the 26 sites providing pediatric HIV data to this analysis.

RESULTS

In East Africa, 3,304 children, 52.0% male, were enrolled in care and were subsequently observed for a median of 92 weeks (inter-quartile range [IQR] 50.3-145.0 weeks). Median age at ART initiation was 5.5 years ([IQR] 3.0-8.5 years). "Good" adherence, as reported by each clinic's measures, was extremely high, remaining on average above 90% throughout all years of follow-up. Longer time on ART was associated with higher adherence (adjusted Odds Ratio-aOR-per log-transformed week on ART: 1.095, 95% Confidence Interval-CI-[1.052-1.150].) Patients enrolled in higher-volume programs exhibited higher rates of clinician-assessed adherence (aOR per log-500 patients: 1.174, 95% CI [1.108-1.245]). Significant site-level variability in reported adherence was observed (0.28), with even higher variability among patients (0.71). In a sub-analysis, being an orphan at the start of ART was strongly associated with lower ART adherence rates (aOR: 0.919, 95% CI [0.864-0.976]).

CONCLUSIONS

Self-reported adherence remained high over a median of 1.8 years in HIV care, but varied according to patient-level and site-level factors. Consistent adherence monitoring with validated measures and attention to vulnerable groups is recommended.

Increased prevalence of pregnancy and comparative risk of program attrition among individuals starting HIV treatment in East Africa

BACKGROUND

The World Health Organization now recommends initiating all pregnant women on life-long antiretroviral therapy (ART), yet there is limited information about the characteristics and program outcomes of pregnant women already on ART in Africa. Our hypothesis was that pregnant women comprised an increasing proportion of those starting ART, and that sub-groups of these women were at higher risk for program attrition.

METHODS AND FINDINGS

We used the International Epidemiology Databases to Evaluate AIDS- East Africa (IeDEA-EA) to conduct a retrospective cohort study including HIV care and treatment programs in Kenya, Uganda, and Tanzania. The cohort consecutively included HIV-infected individuals 13 years or older starting ART 2004-2014. We examined trends over time in the proportion pregnant, their characteristics and program attrition rates compared to others initiating and already receiving ART. 156,474 HIV-infected individuals (67.0% women) started ART. The proportion of individuals starting ART who were pregnant women rose from 5.3% in 2004 to 12.2% in 2014. Mean CD4 cell counts at ART initiation, weighted for annual program size, increased from 2004 to 2014, led by non-pregnant women (annual increase 20 cells/mm3) and men (17 cells/mm3 annually), with lower rates of change in pregnant women (10 cells/mm3 per year) (p<0.0001). There was no significant difference in the cumulative incidence of program attrition at 6 months among pregnant women starting ART and non-pregnant women. However, healthy pregnant women starting ART (WHO stage 1/2) had a higher rate of attrition rate (9.6%), compared with healthy non-pregnant women (6.5%); in contrast among women with WHO stage 3/4 disease, pregnant women had lower attrition (8.4%) than non-pregnant women (14.4%). Among women who initiated ART when healthy and remained in care for six months, subsequent six-month attrition was slightly higher among pregnant women at ART start (3.5%) compared to those who were not pregnant (2.4%), (absolute difference 1.1%, 95% CI 0.7%-1.5%).

CONCLUSIONS

Pregnant women comprise an increasing proportion of those initiating ART in Africa, and pregnant women starting ART while healthy are at higher risk for program attrition than non-pregnant women. As ART programs further expand access to healthier pregnant women, further studies are needed to better understand the drivers of loss among this high risk group of women to optimize retention.

Assessment of risk behaviors in patients with opioid prescriptions: A study of indiana's inspect data

BACKGROUND AND OBJECTIVES

Prescription Drug Monitoring Programs (PDMPs) can serve as screening tools and support the clinical decision-making process in patients receiving opioids. The objective of the study was to utilize 2014 INSPECT (Indiana's PDMP) data to identify factors that increase patients' likelihood to engage in opioid-related risk behaviors.

METHODS

Based on a literature review, four risk behaviors were identified: Receiving >90 morphine milligram equivalents (MME), having >4 opioid prescribers, obtaining opioids from >4 pharmacies, and concurrent use of opioids and benzodiazepines. Two binary logistic regression analyses (engaging in at least one risk behaviors; engaging in all four risk behaviors) and an ordinal regression analysis (engaging in 0-4 risk behaviors) were conducted to identify factors associated with these opioid-related risk behaviors.

RESULTS

Of the 1,538,120 unique opioid patients included in the study, 18.4% engaged in one, 5.3% in two, 1.6% in three, and .4% in all four risk behaviors. Depending on the model, prescribing a second monthly opioid increased patients' odds to engage in risk behaviors by a factor of 10 or more and prescribing two or more benzodiazepines annually increased the odds at least 13-fold.

CONCLUSIONS AND SCIENTIFIC SIGNIFICANCE

About one-fourth of all patients consuming opioids engaged in one or more risk behaviors; higher number of opioid prescriptions and addition of even a small number of benzodiazepine prescriptions dramatically increased these odds. PDMPs can be helpful in identifying opioid users at high-risk for misuse. This information could be used to target efforts to reduce the prescription drug epidemic. (Am J Addict 2017;26:822-829).

Observational Study of the Effect of Patient Outreach on Return to Care: The Earlier the Better

BACKGROUND

The burden of HIV remains heaviest in resource-limited settings, where problems of losses to care, silent transfers, gaps in care, and incomplete mortality ascertainment have been recognized.

METHODS

Patients in care at Academic Model Providing Access to Healthcare (AMPATH) clinics from 2001-2011 were included in this retrospective observational study. Patients missing an appointment were traced by trained staff; those found alive were counseled to return to care (RTC). Relative hazards of RTC were estimated among those having a true gap: missing a clinic appointment and confirmed as neither dead nor receiving care elsewhere. Sample-based multiple imputation accounted for missing vital status.

RESULTS

Among 34,522 patients lost to clinic, 15,331 (44.4%) had a true gap per outreach, 2754 (8.0%) were deceased, and 837 (2.4%) had documented transfers. Of 15,600 (45.2%) remaining without active ascertainment, 8762 (56.2%) with later RTC were assumed to have a true gap. Adjusted cause-specific hazard ratios (aHRs) showed early outreach (a ≤8-day window, defined by grid-search approach) had twice the hazard for RTC vs. those without (aHR = 2.06; P < 0.001). HRs for RTC were lower the later the outreach effort after disengagement (aHR = 0.86 per unit increase in time; P < 0.001). Older age, female sex (vs. male), antiretroviral therapy use (vs. none), and HIV status disclosure (vs. none) were also associated with greater likelihood of RTC, and higher enrollment CD4 count with lower likelihood of RTC.

CONCLUSION

Patient outreach efforts have a positive impact on patient RTC, regardless of when undertaken, but particularly soon after the patient misses an appointment.

Semiparametric regression on cumulative incidence function with interval-censored competing risks data

Many biomedical and clinical studies with time-to-event outcomes involve competing risks data. These data are frequently subject to interval censoring. This means that the failure time is not precisely observed but is only known to lie between two observation times such as clinical visits in a cohort study. Not taking into account the interval censoring may result in biased estimation of the cause-specific cumulative incidence function, an important quantity in the competing risks framework, used for evaluating interventions in populations, for studying the prognosis of various diseases, and for prediction and implementation science purposes. In this work, we consider the class of semiparametric generalized odds rate transformation models in the context of sieve maximum likelihood estimation based on B-splines. This large class of models includes both the proportional odds and the proportional subdistribution hazard models (i.e., the Fine-Gray model) as special cases. The estimator for the regression parameter is shown to be consistent, asymptotically normal and semiparametrically efficient. Simulation studies suggest that the method performs well even with small sample sizes. As an illustration, we use the proposed method to analyze data from HIV-infected individuals obtained from a large cohort study in sub-Saharan Africa. We also provide the R function ciregic that implements the proposed method and present an illustrative example. Copyright © 2017 John Wiley & Sons, Ltd.

Evaluating the Impact of a HIV Low-Risk Express Care Task-Shifting Program: A Case Study of the Targeted Learning Roadmap

In conducting studies on an exposure of interest, a systematic roadmap should be applied for translating causal questions into statistical analyses and interpreting the results. In this paper we describe an application of one such roadmap applied to estimating the joint effect of both time to availability of a nurse-based triage system (low risk express care (LREC)) and individual enrollment in the program among HIV patients in East Africa. Our study population is comprised of 16,513 subjects found eligible for this task-shifting program within 15 clinics in Kenya between 2006 and 2009, with each clinic starting the LREC program between 2007 and 2008. After discretizing follow-up into 90-day time intervals, we targeted the population mean counterfactual outcome (i. e. counterfactual probability of either dying or being lost to follow up) at up to 450 days after initial LREC eligibility under three fixed treatment interventions. These were (i) under no program availability during the entire follow-up, (ii) under immediate program availability at initial eligibility, but non-enrollment during the entire follow-up, and (iii) under immediate program availability and enrollment at initial eligibility. We further estimated the controlled direct effect of immediate program availability compared to no program availability, under a hypothetical intervention to prevent individual enrollment in the program. Targeted minimum loss-based estimation was used to estimate the mean outcome, while Super Learning was implemented to estimate the required nuisance parameters. Analyses were conducted with the ltmle R package; analysis code is available at an online repository as an R package. Results showed that at 450 days, the probability of in-care survival for subjects with immediate availability and enrollment was 0.93 (95% CI: 0.91, 0.95) and 0.87 (95% CI: 0.86, 0.87) for subjects with immediate availability never enrolling. For subjects without LREC availability, it was 0.91 (95% CI: 0.90, 0.92). Immediate program availability without individual enrollment, compared to no program availability, was estimated to slightly albeit significantly decrease survival by 4% (95% CI 0.03,0.06, p<0.01). Immediately availability and enrollment resulted in a 7 % higher in-care survival compared to immediate availability with non-enrollment after 450 days (95% CI-0.08,-0.05, p<0.01). The results are consistent with a fairly small impact of both availability and enrollment in the LREC program on incare survival.

Facility-Level Factors Influencing Retention of Patients in HIV Care in East Africa

Losses to follow-up (LTFU) remain an important programmatic challenge. While numerous patient-level factors have been associated with LTFU, less is known about facility-level factors. Data from the East African International epidemiologic Databases to Evaluate AIDS (EA-IeDEA) Consortium was used to identify facility-level factors associated with LTFU in Kenya, Tanzania and Uganda. Patients were defined as LTFU if they had no visit within 12 months of the study endpoint for pre-ART patients or 6 months for patients on ART. Adjusting for patient factors, shared frailty proportional hazard models were used to identify the facility-level factors associated with LTFU for the pre- and post-ART periods. Data from 77,362 patients and 29 facilities were analyzed. Median age at enrolment was 36.0 years (Interquartile Range: 30.1, 43.1), 63.9% were women and 58.3% initiated ART. Rates (95% Confidence Interval) of LTFU were 25.1 (24.7–25.6) and 16.7 (16.3–17.2) per 100 person-years in the pre-ART and post-ART periods, respectively. Facility-level factors associated with increased LTFU included secondary-level care, HIV RNA PCR turnaround time >14 days, and no onsite availability of CD4 testing. Increased LTFU was also observed when no nutritional supplements were provided (pre-ART only), when TB patients were treated within the HIV program (pre-ART only), and when the facility was open ≤4 mornings per week (ART only). Our findings suggest that facility-based strategies such as point of care laboratory testing and separate clinic spaces for TB patients may improve retention.

CD41 T cell recovery during suppression of HIV replication: an international comparison of the immunological efficacy of antiretroviral therapy in North America, Asia and Africa

BACKGROUND

Even among HIV-infected patients who fully suppress plasma HIV RNA replication on antiretroviral therapy, genetic (e.g. CCL3L1 copy number), viral (e.g. tropism) and environmental (e.g. chronic exposure to microbial antigens) factors influence CD4 recovery. These factors differ markedly around the world and therefore the expected CD4 recovery during HIV RNA suppression may differ globally.

METHODS

We evaluated HIV-infected adults from North America, West Africa, East Africa, Southern Africa and Asia starting non-nucleoside reverse transcriptase inhibitorbased regimens containing efavirenz or nevirapine, who achieved at least one HIV RNA level <500/ml in the first year of therapy and observed CD4 changes during HIV RNA suppression. We used a piecewise linear regression to estimate the influence of region of residence on CD4 recovery, adjusting for socio-demographic and clinical characteristics. We observed 28 217 patients from 105 cohorts over 37 825 person-years.

RESULTS

After adjustment, patients from East Africa showed diminished CD4 recovery as compared with other regions. Three years after antiretroviral therapy initiation, the mean CD4 count for a prototypical patient with a pre-therapy CD4 count of 150/ml was 529/ml [95% confidence interval (CI): 517–541] in North America, 494/ml (95% CI: 429–559) in West Africa, 515/ml (95% CI: 508–522) in Southern Africa, 503/ml (95% CI: 478–528) in Asia and 437/ml (95% CI: 425–449) in East Africa.

CONCLUSIONS

CD4 recovery during HIV RNA suppression is diminished in East Africa as compared with other regions of the world, and observed differences are large enough to potentially influence clinical outcomes. Epidemiological analyses on a global scale can identify macroscopic effects unobservable at the clinical, national or individual regional level.

Impact of and Correction for Outcome Misclassification in Cumulative Incidence Estimation

Cohort studies and clinical trials may involve multiple events. When occurrence of one of these events prevents the observance of another, the situation is called “competing risks”. A useful measure in such studies is the cumulative incidence of an event, which is useful in evaluating interventions or assessing disease prognosis. When outcomes in such studies are subject to misclassification, the resulting cumulative incidence estimates may be biased. In this work, we study the mechanism of bias in cumulative incidence estimation due to outcome misclassification. We show that even moderate levels of misclassification can lead to seriously biased estimates in a frequently unpredictable manner. We propose an easy to use estimator for correcting this bias that is uniformly consistent. Extensive simulations suggest that this method leads to unbiased estimates in practical settings. The proposed method is useful, both in settings where misclassification probabilities are known by historical data or can be estimated by other means, and for performing sensitivity analyses when the misclassification probabilities are not precisely known.

Marginal and Conditional Distribution Estimation from Double-Sampled Semi-Competing Risks Data

Informative dropout is a vexing problem for any biomedical study. Most existing statistical methods attempt to correct estimation bias related to this phenomenon by specifying unverifiable assumptions about the dropout mechanism. We consider a cohort study in Africa that uses an outreach program to ascertain the vital status for dropout subjects. These data can be used to identify a number of relevant distributions. However, as only a subset of dropout subjects were followed, vital status ascertainment was incomplete. We use semi-competing risk methods as our analysis framework to address this specific case where the terminal event is incompletely ascertained and consider various procedures for estimating the marginal distribution of dropout and the marginal and conditional distributions of survival. We also consider model selection and estimation efficiency in our setting. Performance of the proposed methods is demonstrated via simulations, asymptotic study, and analysis of the study data.

Estimation of mortality among HIV-infected people on antiretroviral treatment in East Africa: a sampling based approach in an observational, multisite, cohort study

BACKGROUND

Mortality in HIV-infected people after initiation of antiretroviral treatment (ART) in resource-limited settings is an important measure of the effectiveness and comparative effectiveness of the global public health response. Substantial loss to follow-up precludes accurate accounting of deaths and limits our understanding of effectiveness. We aimed to provide a better understanding of mortality at scale and, by extension, the effectiveness and comparative effectiveness of public health ART treatment in east Africa.

METHODS

In 14 clinics in five settings in Kenya, Uganda, and Tanzania, we intensively traced a sample of patients randomly selected using a random number generator, who were infected with HIV and on ART and who were lost to follow-up (>90 days late for last scheduled visit). We incorporated the vital status outcomes for these patients into analyses of the entire clinic population through probability-weighted survival analyses.

FINDINGS

We followed 34 277 adults on ART from Mbarara and Kampala in Uganda, Eldoret, and Kisumu in Kenya, and Morogoro in Tanzania. The median age was 35 years (IQR 30-42), 11 628 (34%) were men, and median CD4 count count before therapy was 154 cells per μL (IQR 70-234). 5780 patients (17%) were lost to follow-up, 991 (17%) were selected for tracing between June 10, 2011, and Aug 27, 2012, and vital status was ascertained for 860 (87%). With incorporation of outcomes from the patients lost to follow-up, estimated 3 year mortality increased from 3·9% (95% CI 3·6-4·2) to 12·5% (11·8-13·3). The sample-corrected, unadjusted 3 year mortality across settings was lowest in Mbarara (7·2%) and highest in Morogoro (23·6%). After adjustment for age, sex, CD4 count before therapy, and WHO stage, the sample-corrected hazard ratio comparing the settings with highest and lowest mortalities was 2·2 (95% CI 1·5-3·4) and the risk difference for death at 3 years was 11% (95% CI 5·0-17·7).

INTERPRETATION

A sampling-based approach is widely feasible and important to an understanding of mortality after initiation of ART. After adjustment for measured biological drivers, mortality differs substantially across settings despite delivery of a similar clinical package of treatment. Implementation research to understand the systems, community, and patients' behaviours driving these differences is urgently needed.

FUNDING

The US National Institutes of Health and President's Emergency Fund for AIDS Relief.