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ABSTRACT There are limited options to estimate the treatment effects of variables which are continuous and measured at multiple time points, particularly if the true dose–response curve should be estimated as closely as possible. However, these situations may be of relevance: in pharmacology, one may be interested in how outcomes of people living with—and treated for—HIV, such as viral failure, would vary for time‐varying interventions such as different drug concentration trajectories. A challenge for doing causal inference with continuous interventions is that the positivity assumption is typically violated. To address positivity violations, we develop projection functions, which reweigh and redefine the estimand of interest based on functions of the conditional support for the respective interventions. With these functions, we obtain the desired dose–response curve in areas of enough support, and otherwise a meaningful estimand that does not require the positivity assumption. We develop g$$ g $$‐computation type plug‐in estimators for this case. Those are contrasted with g‐computation estimators which are applied to continuous interventions without specifically addressing positivity violations, which we propose to be presented with diagnostics. The ideas are illustrated with longitudinal data from HIV positive children treated with an efavirenz‐based regimen as part of the CHAPAS‐3 trial, which enrolled children <13$$ <13 $$ years in Zambia/Uganda. Simulations show in which situations a standard g‐computation approach is appropriate, and in which it leads to bias and how the proposed weighted estimation approach then recovers the alternative estimand of interest. [ABSTRACT FROM AUTHOR]

Objectives: The objective of this study is to assess the outcomes of children, adolescents and young adults with HIV reported as lost to follow‐up, correct mortality estimates for children, adolescents and young adults with HIV for unascertained outcomes in those loss to follow‐up (LTFU) based on tracing and linkage data separately using data from the International epidemiology Databases to Evaluate AIDS in Southern Africa. Methods: We included data from two different populations of children, adolescents and young adults with HIV; (1) clinical data from children, adolescents and young adults with HIV aged ≤24 years from Lesotho, Malawi, Mozambique, Zambia and Zimbabwe; (2) clinical data from children, adolescents and young adults with HIV aged ≤14 years from the Western Cape (WC) in South Africa. Outcomes of patients lost to follow‐up were available from (1) a tracing study and (2) linkage to a health information exchange. For both populations, we compared six methods for correcting mortality estimates for all children, adolescents and young adults with HIV. Results: We found substantial variations of mortality estimates among children, adolescents and young adults with HIV reported as lost to follow‐up versus those retained in care. Ascertained mortality was higher among lost and traceable children, adolescents and young adults with HIV and lower among lost and linkable than those retained in care (mortality: 13.4% [traced] vs. 12.6% [retained‐other Southern Africa countries]; 3.4% [linked] vs. 9.4% [retained‐WC]). A high proportion of lost to follow‐up children, adolescents and young adults with HIV had self‐transferred (21.0% and 47.0%) in the traced and linked samples, respectively. The uncorrected method of non‐informative censoring yielded the lowest mortality estimates among all methods for both tracing (6.0%) and linkage (4.0%) approaches at 2 years from ART start. Among corrected methods using ascertained data, multiple imputation, incorporating ascertained data (MI(asc.)) and inverse probability weighting with logistic weights were most robust for the tracing approach. In contrast, for the linkage approach, MI(asc.) was the most robust. Conclusions: Our findings emphasise that lost to follow‐up is non‐ignorable and both tracing and linkage improved outcome ascertainment: tracing identified substantial mortality in those reported as lost to follow‐up, whereas linkage did not identify out‐of‐facility deaths, but showed that a large proportion of those reported as lost to follow‐up were self‐transfers. [ABSTRACT FROM AUTHOR]

Objectives: Despite declining TB notifications in Southern Africa, TB‐related deaths remain high. We describe patient‐ and population‐level trends in TB‐related deaths in Eswatini over a period of 11 years. Methods: Patient‐level (retrospective cohort, from 2009 to 2019) and population‐level (ecological analysis, 2009–2017) predictors and rates of TB‐related deaths were analysed in HIV‐negative and HIV‐coinfected first‐line TB treatment cases and the population of the Shiselweni region. Patient‐level TB treatment data, and population and HIV prevalence estimates were combined to obtain stratified annual mortality rates. Multivariable Poisson regressions models were fitted to identify patient‐level and population‐level predictors of deaths. Results: Of 11,883 TB treatment cases, 1302 (11.0%) patients died during treatment: 210/2798 (7.5%) HIV‐negative patients, 984/8443 (11.7%) people living with HIV (PLHIV), and 108/642 (16.8%) patients with unknown HIV‐status. The treatment case fatality ratio remained above 10% in most years. At patient‐level, fatality risk was higher in PLHIV (aRR 1.74, 1.51–2.02), and for older age and extra‐pulmonary TB irrespective of HIV‐status. For PLHIV, fatality risk was higher for TB retreatment cases (aRR 1.38, 1.18–1.61) and patients without antiretroviral therapy (aRR 1.70, 1.47–1.97). It decreases with increasing higher CD4 strata and the programmatic availability of TB‐LAM testing (aRR 0.65, 0.35–0.90). At population‐level, mortality rates decreased 6.4‐fold (−147/100,000 population) between 2009 (174/100,000) and 2017 (27/100,000), coinciding with a decline in TB treatment cases (2785 in 2009 to 497 in 2017). Although the absolute decline in mortality rates was most pronounced in PLHIV (−826/100,000 vs. HIV‐negative: −23/100,000), the relative population‐level mortality risk remained higher in PLHIV (aRR 4.68, 3.25–6.72) compared to the HIV‐negative population. Conclusions: TB‐related mortality rapidly decreased at population‐level and most pronounced in PLHIV. However, case fatality among TB treatment cases remained high. Further strategies to reduce active TB disease and introduce improved TB therapies are warranted. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Introduction: The Treat‐All policy – antiretroviral therapy (ART) initiation irrespective of CD4 cell criteria – increases access to treatment. Many ART programmes, however, reported increasing attrition and viral failure during treatment expansion, questioning the programmatic feasibility of Treat‐All in resource‐limited settings. We aimed to describe and compare programmatic outcomes between Treat‐All and standard of care (SOC) in the public sectors of Eswatini. Methods: This is a prospective cohort study of ≥16‐year‐old HIV‐positive patients initiated on first‐line ART under Treat‐All and SOC in 18 health facilities of the Shiselweni region, from October 2014 to March 2016. SOC followed the CD4 350 and 500 cells/mm3 treatment eligibility thresholds. Kaplan‐Meier estimates were used to describe crude programmatic outcomes. Multivariate flexible parametric survival models were built to assess associations of time from ART initiation with the composite unfavourable outcome of all‐cause attrition and viral failure. Results: Of the 3170 patients, 1888 (59.6%) initiated ART under Treat‐All at a median CD4 cell count of 329 (IQR 168 to 488) cells/mm3 compared with 292 (IQR 161 to 430) (p < 0.001) under SOC. Although crude programme retention at 36 months tended to be lower under Treat‐All (71%) than SOC (75%) (p = 0.002), it was similar in covariate‐adjusted analysis (adjusted hazard ratio [aHR] 1.06, 95% CI 0.91 to 1.23). The hazard of viral suppression was higher for Treat‐All (aHR 1.12, 95% CI 1.01 to 1.23), while the hazard of viral failure was comparable (Treat‐All: aHR 0.89, 95% CI 0.53 to 1.49). Among patients with advanced HIV disease (n = 1080), those under Treat‐All (aHR 1.13, 95% CI 0.88 to 1.44) had a similar risk of an composite unfavourable outcome to SOC. Factors increasing the risk of the composite unfavourable outcome under both interventions were aged 16 to 24 years, being unmarried, anaemia, ART initiation on the same day as HIV care enrolment and CD4 ≤ 100 cells/mm3. Under Treat‐All only, the risk of the unfavourable outcome was higher for pregnant women, WHO III/IV clinical stage and elevated creatinine. Conclusions: Compared to SOC, Treat‐All resulted in comparable retention, improved viral suppression and comparable composite outcomes of retention without viral failure. [ABSTRACT FROM AUTHOR]

Objectives: This paper assesses patient- and population-level trends in TB notifications during rapid expansion of antiretroviral therapy in Eswatini which has an extremely high incidence of both TB and HIV.Methods: Patient- and population-level predictors and rates of HIV-associated TB were examined in the Shiselweni region in Eswatini from 2009 to 2016. Annual population-level denominators obtained from projected census data and prevalence estimates obtained from population-based surveys were combined with individual-level TB treatment data. Patient- and population-level predictors of HIV-associated TB were assessed with multivariate logistic and multivariate negative binomial regression models.Results: Of 11 328 TB cases, 71.4% were HIV co-infected and 51.8% were women. TB notifications decreased fivefold between 2009 and 2016, from 1341 to 269 cases per 100 000 person-years. The decline was sixfold in PLHIV vs. threefold in the HIV-negative population. Main patient-level predictors of HIV-associated TB were recurrent TB treatment (adjusted odds ratio [aOR] 1.40, 95% confidence interval [CI]: 1.19-1.65), negative (aOR 1.31, 1.15-1.49) and missing (aOR 1.30, 1.11-1.53) bacteriological status and diagnosis at secondary healthcare level (aOR 1.18, 1.06-1.33). Compared with 2009, the probability of TB decreased for all years from 2011 (aOR 0.69, 0.58-0.83) to 2016 (aOR 0.54, 0.43-0.69). The most pronounced population-level predictor of TB was HIV-positive status (adjusted incidence risk ratio 19.47, 14.89-25.46).Conclusions: This high HIV-TB prevalence setting experienced a rapid decline in TB notifications, most pronounced in PLHIV. Achievements in HIV-TB programming were likely contributing factors. [ABSTRACT FROM AUTHOR]

Objectives: To assess long‐term antiretroviral therapy (ART) outcomes during rapid HIV programme expansion in the public sector of Eswatini (formerly Swaziland). Methods: This is a retrospectively established cohort of HIV‐positive adults (≥16 years) who started first‐line ART in 25 health facilities in Shiselweni (Eswatini) between 01/2006 and 12/2014. Temporal trends in ART attrition, treatment expansion and ART coverage were described over 9 years. We used flexible parametric survival models to assess the relationship between time to ART attrition and covariates. Results: Of 24 772 ART initiations, 6% (n = 1488) occurred in 2006, vs. 13% (n = 3192) in 2014. Between these years, median CD4 cell count at ART initiation increased (113–265 cells/mm3). The active treatment cohort expanded 8.4‐fold, ART coverage increased 8.0‐fold (7.1% in 2006 vs. 56.8% in 2014) and 12‐month crude ART retention improved from 71% to 86%. Compared with the pre‐decentralisation period (2006–2007), attrition decreased by 5% (adjusted hazard ratio [aHR] 0.95, 95% confidence interval 0.88–1.02) during HIV‐TB service decentralisation (2008–2010), by 17% (aHR 0.83, 0.75–0.92) during service consolidation (2011–2012), and by 20% (aHR 0.80, 0.71–0.90) during further treatment expansion (2013–2014). The risk of attrition was higher for young age, male sex, pathological baseline haemoglobin and biochemistry results, more toxic drug regimens, WHO III/IV staging and low CD4 cell count; access to a telephone was protective. Conclusions: Programmatic outcomes improved during large expansion of the treatment cohort and increased ART coverage. Changes in ART programming may have contributed to better outcomes. [ABSTRACT FROM AUTHOR]

When estimating the average effect of a binary treatment (or exposure) on an outcome, methods that incorporate propensity scores, the G-formula, or targeted maximum likelihood estimation (TMLE) are preferred over naïve regression approaches, which are biased under misspecification of a parametric outcome model. In contrast propensity score methods require the correct specification of an exposure model. Double-robust methods only require correct specification of either the outcome or the exposure model. Targeted maximum likelihood estimation is a semiparametric double-robust method that improves the chances of correct model specification by allowing for flexible estimation using (nonparametric) machine-learning methods. It therefore requires weaker assumptions than its competitors. We provide a step-by-step guided implementation of TMLE and illustrate it in a realistic scenario based on cancer epidemiology where assumptions about correct model specification and positivity (ie, when a study participant had 0 probability of receiving the treatment) are nearly violated. This article provides a concise and reproducible educational introduction to TMLE for a binary outcome and exposure. The reader should gain sufficient understanding of TMLE from this introductory tutorial to be able to apply the method in practice. Extensive R-code is provided in easy-to-read boxes throughout the article for replicability. Stata users will find a testing implementation of TMLE and additional material in the Appendix S1 and at the following GitHub repository: https://github.com/migariane/SIM-TMLE-tutorial. [ABSTRACT FROM AUTHOR]

Many modern estimators require bootstrapping to calculate confidence intervals because either no analytic standard error is available or the distribution of the parameter of interest is nonsymmetric. It remains however unclear how to obtain valid bootstrap inference when dealing with multiple imputation to address missing data. We present 4 methods that are intuitively appealing, easy to implement, and combine bootstrap estimation with multiple imputation. We show that 3 of the 4 approaches yield valid inference, but that the performance of the methods varies with respect to the number of imputed data sets and the extent of missingness. Simulation studies reveal the behavior of our approaches in finite samples. A topical analysis from HIV treatment research, which determines the optimal timing of antiretroviral treatment initiation in young children, demonstrates the practical implications of the 4 methods in a sophisticated and realistic setting. This analysis suffers from missing data and uses the g-formula for inference, a method for which no standard errors are available. [ABSTRACT FROM AUTHOR]

Introduction: South Africa has the largest number of individuals living with HIV and the largest antiretroviral therapy (ART) programme worldwide. In September 2016, ART eligibility was extended to all 7.1 million HIV-positive South Africans. To ensure that further expansion of services does not compromise quality of care, long-term outcomes must be monitored. Few studies have reported long-term mortality in resource-constrained settings, where mortality ascertainment is challenging. Combining site records with data linked to the national vital registration system, sites in the International Epidemiology Databases to Evaluate AIDS Southern Africa collaboration can identify >95% of deaths in patients with civil identification numbers (IDs). This study used linked data to explore long-term mortality and viral suppression among adults starting ART in South Africa. Methods: The study was a cohort analysis of routine data on adults with IDs starting ART 2004-2015 in five large ART cohorts. Mortality was estimated overall and by gender using the Kaplan-Meier estimator and Cox's proportional hazards regression. Standardized mortality ratios (SMRs) were calculated by dividing observed numbers of deaths by numbers expected if patients had been HIV-negative. Viral suppression in patients with viral loads (VLs) in their last year of followup was the secondary outcome. Results: Among 72,812 adults followed for 350,376 person years (pyrs), the crude mortality rate was 3.08 (95% CI 3.02- 3.14)/100 pyrs. Patients were predominantly female (67%) and the percentage of men initiating ART did not increase. Cumulative mortality 12 years after ART initiation was 23.9% (33.4% male and 19.4% female). Mortality peaked in patients enrolling in 2007-2009 and was higher in men than women at all durations. Observed mortality rates were higher than HIVnegative mortality, decreasing with duration. By 48 months, observed mortality was close to that in the HIV-negative population, and SMRs were similar for all baseline CD4 strata. Three-quarters of patients had VLs in their last year, and 86% of these were virally suppressed. Conclusions: The South African ART programme has shown a remarkable ability to initiate and manage patients successfully over 12 years, despite rapid expansion. With further scale-up, testing and initiating men on ART must be a national priority. [ABSTRACT FROM AUTHOR]

Introduction: There is uncertainty regarding the completeness of death recording by civil registration and by health centres in South Africa. This paper aims to compare death recording by the two systems, in cohorts of South African patients receiving antiretroviral treatment (ART). Methods: Completeness of death recording was estimated using a capture–recapture approach. Six ART programmes linked their patient record systems to the vital registration system using civil identity document (ID) numbers and provided data comparing the outcomes recorded in patient files and in the vital registration. Patients were excluded if they had missing/invalid IDs or had transferred to other ART programmes. Results: After exclusions, 91,548 patient records were included. Of deaths recorded in patients files after 2003, 94.0% (95% CI: 93.3–94.6%) were recorded by civil registration, with completeness being significantly higher in urban areas, older adults and females. Of deaths recorded by civil registration after 2003, only 35.0% (95% CI: 34.2–35.8%) were recorded in patient files, with this proportion dropping from 60% in 2004–2005 to 30% in 2010 and subsequent years. Recording of deaths in patient files was significantly higher in children and in locations within 50 km of the health centre. When the information from the two systems was combined, an estimated 96.2% of all deaths were recorded (93.5% in children and 96.2% in adults). Conclusions: South Africa's civil registration system has achieved a high level of completeness in the recording of mortality. However, the fraction of deaths recorded by health centres is low and information from patient records is insufficient by itself to evaluate levels and predictors of ART patient mortality. Previously documented improvements in ART mortality over time may be biased if based only on data from patient records. [ABSTRACT FROM AUTHOR]

Introduction: Routine viral load (VL) monitoring is utilized to assess antiretroviral therapy (ART) adherence and virologic failure, and it is currently scaled‐up in many resource‐constrained settings. The first routine VL is recommended as late as six months after ART initiation for early detection of sub-optimal adherence. We aimed to assess the optimal timing of first VL measurement after initiation of ART. Methods: This was a retrospective, cohort analysis of routine monitoring data of adults enrolled at three primary care clinics in Khayelitsha, Cape Town, between January 2002 and March 2009. Primary outcomes were virologic failure and switch to second‐line ART comparing patients in whom first VL done was at three months (VL3M) and six months (VL6M) after ART initiation. Adjusted hazard ratios (aHR) were estimated using Cox proportional hazard models. Results: In total, 6264 patients were included for the time to virologic failure and 6269 for the time to switch to second-line ART analysis. Patients in the VL3M group had a 22% risk reduction of virologic failure (aHR 0.78, 95% CI 0.64–0.95; p = 0.016) and a 27% risk reduction of switch to second-line ART (aHR 0.73, 95% CI 0.58–0.92; p = 0.008) when compared to patients in the VL6M group. For each additional month of delay of the first VL measurement (up to nine months), the risk of virologic failure increased by 9% (aHR 1.09, 95% CI 1.02–1.15; p = 0.008) and switch to second-line ART by 13% (aHR 1.13, 95% CI 1.05–1.21; p < 0.001). Conclusions: A first VL at three months rather than six months with targeted adherence interventions for patients with high VL may improve long-term virologic suppression and reduce switches to costly second-line ART. ART programmes should consider the first VL measurement at three months after ART initiation. [ABSTRACT FROM AUTHOR]

Objectives To investigate the incidence of selected opportunistic infections ( OIs) and cancers and the role of a history of tuberculosis ( TB) as a risk factor for developing these conditions in HIV-infected patients starting antiretroviral treatment ( ART) in Southern Africa. Methods Five ART programmes from Zimbabwe, Zambia and South Africa participated. Outcomes were extrapulmonary cryptococcal disease (CM), pneumonia due to Pneumocystis jirovecii (PCP), Kaposi's sarcoma and Non-Hodgkin lymphoma. A history of TB was defined as a TB diagnosis before or at the start of ART. We used Cox models adjusted for age, sex, CD4 cell count at ART start and treatment site, presenting results as adjusted hazard ratios ( aHR) with 95% confidence intervals (CI). Results We analysed data from 175 212 patients enrolled between 2000 and 2010 and identified 702 patients with incident CM (including 205 with a TB history) and 487 with incident PCP (including 179 with a TB history). The incidence per 100 person-years over the first year of ART was 0.48 (95% CI 0.44-0.52) for CM, 0.35 (95% CI 0.32-0.38) for PCP, 0.31 (95% CI 0.29-0.35) for Kaposi's sarcoma and 0.02 (95% CI 0.01-0.03) for Non-Hodgkin lymphoma. A history of TB was associated with cryptococcal disease ( aHR 1.28, 95% CI 1.05-1.55) and Pneumocystis jirovecii pneumonia ( aHR 1.61, 95% CI 1.27-2.04), but not with Non-Hodgkin lymphoma ( aHR 1.09, 95% CI 0.45-2.65) or Kaposi's sarcoma ( aHR 1.02, 95% CI 0.81-1.27). Conclusions Our study suggests that there may be interactions between different OIs in HIV-infected patients. [ABSTRACT FROM AUTHOR]

Introduction: Stunting is a key issue for adolescents with perinatally acquired HIV (APH) that needs to be better understood. As part of the IeDEA multiregional consortium, we described growth evolution during adolescence for APH on antiretroviral therapy (ART). Methods: We included data from sub‐Saharan Africa, the Asia‐Pacific, and the Caribbean, Central and South America regions collected between 2003 and 2016. Adolescents on ART, reporting perinatally acquired infection or entering HIV care before 10 years of age, with at least one height measurement between 10 and 16 years of age, and followed in care until at least 14 years of age were included. Characteristics at ART initiation and at 10 years of age were compared by sex. Correlates of growth defined by height‐for‐age z‐scores (HAZ) between ages 10 and 19 years were studied separately for males and females, using linear mixed models. Results: Overall, 8737 APH were included, with 46% from Southern Africa. Median age at ART initiation was 8.1 years (interquartile range (IQR) 6.1 to 9.6), 50% were females, and 41% were stunted (HAZ<−2 SD) at ART initiation. Males and females did not differ by age and stunting at ART initiation, CD4 count over time or retention in care. At 10 years of age, 34% of males were stunted versus 39% of females (p < 0.001). Females had better subsequent growth, resulting in a higher prevalence of stunting for males compared to females by age 15 (48% vs. 25%) and 18 years (31% vs. 15%). In linear mixed models, older age at ART initiation and low CD4 count were associated with poor growth over time (p < 0.001). Those stunted at 10 years of age or at ART initiation had the greatest growth improvement during adolescence. Conclusions: Prevalence of stunting is high among APH worldwide. Substantial sex‐based differences in growth evolution during adolescence were observed in this global cohort, which were not explained by differences in age of access to HIV care, degree of immunosuppression or region. Other factors influencing growth differences in APH, such as differences in pubertal development, should be better documented, to guide further research and inform interventions to optimize growth and health outcomes among APH. [ABSTRACT FROM AUTHOR]