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Some causal parameters are defined on subgroups of the observed data, such as the average treatment effect on the treated and variations thereof. We explain how such parameters can be defined through parameters in a marginal structural (working) model. We illustrate how existing software can be used for doubly robust effect estimation of those parameters. Our proposal for confidence interval estimation is based on the delta method. All concepts are illustrated by estimands and data from the data challenge of the 2022 American Causal Inference Conference., Observational Studies, 9 (3)

Supplemental Digital Content is Available in the Text., Background: The lack of acute and early HIV infection (AEHI) diagnosis and care contributes to high HIV incidence in resource-limited settings. We aimed to assess the yield of AEHI, predict and diagnose AEHI, and describe AEHI care outcomes in a public sector setting in Eswatini. Setting: This study was conducted in Nhlangano outpatient department from March 2019 to March 2020. Methods: Adults at risk of AEHI underwent diagnostic testing for AEHI with the quantitative Xpert HIV-1 viral load (VL) assay. AEHI was defined as the detection of HIV-1 VL on Xpert and either an HIV-seronegative or HIV-serodiscordant third-generation antibody-based rapid diagnostic test (RDT) result. First, the cross-sectional analysis obtained the yield of AEHI and established a predictor risk score for the prediction of AEHI using Lasso logistic regression. Second, diagnostic accuracy statistics described the ability of the fourth-generation antibody/p24 antigen–based Alere HIV-Combo RDT to diagnose AEHI (vs Xpert VL testing). Third, we described acute HIV infection care outcomes of AEHI-positive patients using survival analysis. Results: Of 795 HIV-seronegative/HIV-serodiscordant outpatients recruited, 30 (3.8%, 95% confidence interval: 2.6% to 5.3%) had AEHI. The predictor risk score contained several factors (HIV-serodiscordant RDT, women, feeling at risk of HIV, swollen glands, and fatigue) and had sensitivity and specificity of 83.3% and 65.8%, respectively, to predict AEHI. The HIV-Combo RDT had sensitivity and specificity of 86.2% and 99.9%, respectively, to diagnose AEHI. Of 30 AEHI-positive patients, the 1-month cumulative treatment initiation was 74% (95% confidence interval: 57% to 88%), and the 3-month viral suppression (

Background: Medication-related osteonecrosis of the jaw (MRONJ) is a potentially severe complication of mainly antiresorptive drugs. We evaluated the frequency of dentoalveolar pathologies in patients scheduled for antiresorptive therapy in a ‘real-world’ setting, also including patients with poor oral health potentially requiring tooth extractions and/or other dentoalveolar surgery. This approach is in contrast to the setting of recent randomized trials with restrictive exclusion criteria. Patients & methods: We prospectively included patients suffering from solid tumors with osseous metastases or multiple myeloma. Screening for dentoalveolar pathologies was done prior to initiation of antiresorptive therapy at the specialized MRONJ clinic of the University Hospital for Cranio-Maxillofacial and Oral Surgery, Innsbruck, Austria. Results: 119 subjects could be included. In 76 patients (63.9%), a dental focus was revealed including deep caries (24.4% of patients), chronic apical periodontitis (26.9%), periodontal disease (45.8%), root remnants (16%), jaw cysts (2.5%), partially impacted teeth (5.0%) and peri-implantitis (5.0%). Conclusion: Considering the high number of dentoalveolar pathologies (63.9%), systematic dental focus screening prior to initiation of antiresorptive therapy is of utmost importance to lower the risk for MRONJ.

The notion that an independent central bank reduces a country’s inflation is a controversial hypothesis. To date, it has not been possible to satisfactorily answer this question because the complex macroeconomic structure that gives rise to the data has not been adequately incorporated into statistical analyses. We develop a causal model that summarizes the economic process of inflation. Based on this causal model and recent data, we discuss and identify the assumptions under which the effect of central bank independence on inflation can be identified and estimated. Given these and alternative assumptions, we estimate this effect using modern doubly robust effect estimators, i.e., longitudinal targeted maximum likelihood estimators. The estimation procedure incorporates machine learning algorithms and is tailored to address the challenges associated with complex longitudinal macroeconomic data. We do not find strong support for the hypothesis that having an independent central bank for a long period of time necessarily lowers inflation. Simulation studies evaluate the sensitivity of the proposed methods in complex settings when certain assumptions are violated and highlight the importance of working with appropriate learning algorithms for estimation., Journal of Causal Inference, 9 (1), ISSN:2193-3685, ISSN:2193-3677

After failure of first-line antiretroviral therapy (ART) in the public sector, delayed or missed second-line ART switch is linked with poor outcomes in patients with advanced HIV.We investigated delayed or missed second-line ART switch after confirmed virologic failure in the largest private sector HIV cohort in Africa.We included HIV-infected adults with confirmed virologic failure after 6 months of nonnucleoside reverse-transcriptase inhibitor-based ART. We estimated the effect of timing of switch on the hazard of death using inverse probability of treatment weighting of marginal structural models. We adjusted for time-dependent confounding of CD4 count, viral load, and visit frequency.Five thousand seven hundred forty-eight patients (53% female) with confirmed virologic failure met inclusion criteria; the median age was 40 [interquartile range (IQR): 35-47], advanced HIV was present in 48% and the prior duration of nonnucleoside reverse-transcriptase inhibitor-based ART was 1083 days (IQR: 665-1770). Median time to confirmation of virologic failure and to second-line switch was 196 (IQR: 136-316) and 220 days (IQR: 65-542), respectively. Switching to second-line ART after confirmed failure compared with remaining on first-line ART reduced risk of subsequent death [adjusted hazard ratio: 0.47 (95% confidence interval: 0.36 to 0.63)]. Compared with patients who experienced delayed switch, those switched immediately had a lower risk of death, regardless of CD4 cell count.Delayed or missed switch to second-line ART after confirmed first-line ART failure is common in the South African private sector and associated with mortality. Novel interventions to minimize switch delay should be tested and not limited to those with advanced disease at treatment failure.

In Chaps. 2 and 3 we discussed how to analyse a single variable using graphs and summary statistics.

A data set may contain many variables and observations. However, we are not always interested in each of the measured values but rather in a summary which interprets the data.

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/��l 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/��l: 0.22 (95% CI: 0.16, 0.31)]. The effect of CD4 count persisted in pregnant females. Increasing age and CD4 count >200 cells/��l 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.

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.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.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).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.Ce document évalue les tendances des notifications de la tuberculose (TB) à l’échelle des patients et de la population lors de l'expansion rapide du traitement antirétroviral à Eswatini, où l'incidence de la TB et du VIH est extrêmement élevée. MÉTHODES: Les prédicteurs et les taux de TB associée au VIH à l’échelle des patients et de la population ont été examinés dans la région de Shiselweni à Eswatini de 2009 à 2016. Les dénominateurs annuels à l’échelle de la population obtenus à partir des données de recensement projetées et des estimations de la prévalence obtenues à partir d'enquêtes de population ont été combinés avec des données de traitement de la TB à l’échelle individuel. Les prédicteurs de la TB associée au VIH à l’échelle du patient et de la population ont été évalués à l'aide de modèles de régression logistique multivariée et binomiale négative multivariée. RÉSULTATS: Sur 11.328 cas de TB, 71,4% étaient coinfectés par le VIH et 51,8% étaient des femmes. Les notifications de TB ont été réduites de 5,0 fois entre 2009 et 2016, passant de 1.341 à 269 cas par 100.000 personnes-années. Le déclin était de 6,0 fois chez les PVVIH contre 3,0 fois dans la population négative pour le VIH. Les principaux prédicteurs de la TB associée au VIH à l’échelle des patients étaient les traitements antituberculeux récurrents (rapport de cotes ajusté [aOR] 1,40; intervalle de confiance à 95% [IC]: 1,19 à 1,65), un statut bactériologique négatif (aOR: 1,31; 1,15 à 1,49) et manquant (aOR: 1,30; 1,11 à 1,53) et le diagnostic au niveau des soins de santé secondaires (AOR 1,18; 1,06 à 1,33). Par rapport à 2009, la probabilité de contracter la TB a diminué pour toutes les années, de 2011 (aOR: 0,69; 0,58 à 0,83) à 2016 (aOR: 0,5; 0,43 à 0,69). Le prédicteur le plus prononcé de la TB à l’échelle de la population était le statut VIH-positif (rapport de risque d'incidence ajusté: 19,47; 14,89 à 25,46).Ce contexte de prévalence élevée de la TB-VIH a connu un déclin rapide du nombre de notifications de TB, plus prononcé chez les PVVIH. Les réalisations dans la programmation VIH-TB étaient probablement des facteurs contributifs.

(1) Background: The Austrian supply of COVID-19 vaccine is limited for now. We aim to provide evidence-based guidance to the authorities in order to minimize COVID-19-related hospitalizations and deaths in Austria. (2) Methods: We used a dynamic agent-based population model to compare different vaccination strategies targeted to the elderly (65 ≥ years), middle aged (45–64 years), younger (15–44 years), vulnerable (risk of severe disease due to comorbidities), and healthcare workers (HCW). First, outcomes were optimized for an initially available vaccine batch for 200,000 individuals. Second, stepwise optimization was performed deriving a prioritization sequence for 2.45 million individuals, maximizing the reduction in total hospitalizations and deaths compared to no vaccination. We considered sterilizing and non-sterilizing immunity, assuming a 70% effectiveness. (3) Results: Maximum reduction of hospitalizations and deaths was achieved by starting vaccination with the elderly and vulnerable followed by middle-aged, HCW, and younger individuals. Optimizations for vaccinating 2.45 million individuals yielded the same prioritization and avoided approximately one third of deaths and hospitalizations. Starting vaccination with HCW leads to slightly smaller reductions but maximizes occupational safety. (4) Conclusion: To minimize COVID-19-related hospitalizations and deaths, our study shows that elderly and vulnerable persons should be prioritized for vaccination until further vaccines are available.

The aim of this study was to compare the effectiveness of barbed versus smooth sutures for soft tissue closure of exposed jawbone sites in medication-related osteonecrosis of the jaw (MRONJ) patients. Exposed necrotic jawbone sites surgically managed by intraoral soft tissue closure were evaluated. Either barbed sutures (Stratafix™ or V-Loc™) together with Prolene® or Vicryl® sutures were used. We estimated the effect of barbed sutures (BS) with Prolene® compared to smooth sutures (Vicryl®) on the hazard rate of intraoral soft tissue dehiscence using a multivariate Cox regression model within a target trial framework, adjusting for relevant confounders. In total, 306 operations were performed in 188 sites. In the primary analysis 182 sites without prior surgery were included. Of these, 113 sites developed a dehiscence during follow-up. 84 sites were operated using BS and Prolene®. A total of 222 sites were operated with Vicryl® (control group). In the BS group, the median time to event (i.e., dehiscence) was 148 days (interquartile range (IQR), 42–449 days) compared to 15 days (IQR, 12–52 days) in the control group. The hazard rate of developing intraoral dehiscence was 0.03 times (95%-confidence interval (CI): 0.01, 0.14, p &lt, 0.001) lower for BS patients compared to the control group. Within the limits of a retrospective study, BS showed a high success rate and are therefore recommended for soft tissue closure of exposed jawbone sites in MRONJ patients. Additional studies are warranted to further evaluate this novel application of BS.

Rapid initiation of antiretroviral therapy (ART) is recommended for people living with human immunodeficiency virus (HIV), with the option to start treatment on the day of diagnosis (same-day ART). However, the effect of same-day ART remains unknown in realistic public sector settings. We established a cohort of ≥16-year-old patients who initiated first-line ART under a treat-all policy in Nhlangano (Eswatini) during 2014–2016, either on the day of HIV care enrollment (same-day ART) or 1–14 days thereafter (early ART). Directed acyclic graphs, flexible parametric survival analysis, and targeted maximum likelihood estimation (TMLE) were used to estimate the effect of same-day-ART initiation on a composite unfavorable treatment outcome (loss to follow-up, death, viral failure, treatment switch). Of 1,328 patients, 839 (63.2%) initiated same-day ART. The adjusted hazard ratio of the unfavorable outcome was higher, 1.48 (95% confidence interval: 1.16, 1.89), for same-day ART compared with early ART. TMLE suggested that after 1 year, 28.9% of patients would experience the unfavorable outcome under same-day ART compared with 21.2% under early ART (difference: 7.7%; 1.3%–14.1%). This estimate was driven by loss to follow-up and varied over time, with a higher hazard during the first year after HIV care enrollment and a similar hazard thereafter. We found an increased risk with same-day ART. A limitation was that possible silent transfers that were not captured.

We regret that this article is behind a paywall., Background and objectives: Adolescents living with perinatally acquired HIV (ALPHIV) on antiretroviral therapy (ART) have been noted to have poorer adherence, retention and virologic control compared to adolescents with nonperinatally acquired HIV, children or adults. We aimed to describe and examine factors associated with longitudinal virologic response during early adolescence. Design: A retrospective cohort study Methods: We included ALPHIV who initiated ART before age 9.5 years in South African cohorts of the International epidemiology Database to Evaluate AIDS-Southern Africa (IeDEA-SA) collaboration (2004–2016); with viral load (VL) values

Classical epidemiology has focused on the control of confounding, but it is only recently that epidemiologists have started to focus on the bias produced by colliders. A collider for a certain pair of variables (e.g. an outcome Y and an exposure A) is a third variable (C) that is caused by both. In a directed acyclic graph (DAG), a collider is the variable in the middle of an inverted fork (i.e. the variable C in A → C ← Y). Controlling for, or conditioning an analysis on a collider (i.e. through stratification or regression) can introduce a spurious association between its causes. This potentially explains many paradoxical findings in the medical literature, where established risk factors for a particular outcome appear protective. We use an example from non-communicable disease epidemiology to contextualize and explain the effect of conditioning on a collider. We generate a dataset with 1000 observations, and run Monte-Carlo simulations to estimate the effect of 24-h dietary sodium intake on systolic blood pressure, controlling for age, which acts as a confounder, and 24-h urinary protein excretion, which acts as a collider. We illustrate how adding a collider to a regression model introduces bias. Thus, to prevent paradoxical associations, epidemiologists estimating causal effects should be wary of conditioning on colliders. We provide R code in easy-to-read boxes throughout the manuscript, and a GitHub repository [https://github.com/migariane/ColliderApp] for the reader to reproduce our example. We also provide an educational web application allowing real-time interaction to visualize the paradoxical effect of conditioning on a collider [http://watzilei.com/shiny/collider/].

A primary concern of an antibody-based HIV-1 therapy is the virus' ability to rapidly escape antibody responses. Therefore, we investigated the relationships between antibody neutralization sensitivity, viral phenotype, and infectivity in 13 subtype C viruses using a HeLa transfectant-based assay. We observed that the seven tier 3 viruses exhibited higher infectivity than the tier 2 viruses, suggesting that higher neutralization resistance did not have a substantial entry cost. There was no relationship between neutralization resistance and susceptibility to entry inhibitors Maraviroc, PSC RANTES, or the fusion inhibitor T20, indicating that neutralization resistance may not alter these inhibitor target sites. By analyzing glycosylation patterns in 82 subtype C viruses, we found that the presence of an N-linked glycan motif at position N413 and its absence at N332 were the most important predictors of neutralization resistance. In a set of 200 subtype C viruses, tier 3 strains were more resistant than tier 2 or 1B viruses to several broadly neutralizing monoclonal antibodies targeting three different epitopes. This suggests that it is unlikely that resistance to antibodies targeting a single epitope drives overall resistance. In the context of an antibody-based intervention, highly resistant viruses with increased infectivity, circulating in the population, could hinder HIV-1 control since entry of tier 3 viruses is not always selected against. Therefore, for any long-term antibody-based intervention to be globally relevant, it must elicit responses that limit the occurrence of resistance.

The causal effect of an intervention (treatment/exposure) on an outcome can be estimated by: i) specifying knowledge about the data-generating process; ii) assessing under what assumptions a target quantity, such as for example a causal odds ratio, can be identified given the specified knowledge (and given the measured data); and then, iii) using appropriate statistical estimation techniques to estimate the desired parameter of interest. As regression is the cornerstone of statistical analysis, it seems obvious to ask: is it appropriate to use estimated regression parameters for causal effect estimation? It turns out that using regression for effect estimation is possible, but typically requires more assumptions than competing methods. This manuscript provides a comprehensive summary of the assumptions needed to identify and estimate a causal parameter using regression and, equally important, discusses the resulting implications for statistical practice.

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

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.

Introduction The World Health Organization recommends the Treat‐All policy of immediate antiretroviral therapy (ART) initiation, but questions persist about its feasibility in resource‐poor settings. We assessed the feasibility of Treat‐All compared with standard of care (SOC) under routine conditions. Methods This prospective cohort study from southern Eswatini followed adults from HIV care enrolment to ART initiation. Between October 2014 and March 2016, Treat‐All was offered in one health zone and SOC according to the CD4 350 and 500 cells/mm3 treatment eligibility thresholds in the neighbouring health zone, each of which comprised one secondary and eight primary care facilities. We used Kaplan–Meier estimates, multivariate flexible parametric survival models and standardized survival curves to compare ART initiation between the two interventions. Results Of the 1726 (57.3%) patients enrolled under Treat‐All and 1287 (42.7%) under SOC, cumulative three‐month ART initiation was higher under Treat‐All (91%) than SOC (74%; p

Longitudinal targeted maximum likelihood estimation (LTMLE) has very rarely been used to estimate dynamic treatment effects in the context of time-dependent confounding affected by prior treatment when faced with long follow-up times, multiple time-varying confounders, and complex associational relationships simultaneously. Reasons for this include the potential computational burden, technical challenges, restricted modeling options for long follow-up times, and limited practical guidance in the literature. However, LTMLE has desirable asymptotic properties, ie, it is doubly robust, and can yield valid inference when used in conjunction with machine learning. It also has the advantage of easy-to-calculate analytic standard errors in contrast to the g-formula, which requires bootstrapping. We use a topical and sophisticated question from HIV treatment research to show that LTMLE can be used successfully in complex realistic settings, and we compare results to competing estimators. Our example illustrates the following practical challenges common to many epidemiological studies: (1) long follow-up time (30 months); (2) gradually declining sample size; (3) limited support for some intervention rules of interest; (4) a high-dimensional set of potential adjustment variables, increasing both the need and the challenge of integrating appropriate machine learning methods; and (5) consideration of collider bias. Our analyses, as well as simulations, shed new light on the application of LTMLE in complex and realistic settings: We show that (1) LTMLE can yield stable and good estimates, even when confronted with small samples and limited modeling options; (2) machine learning utilized with a small set of simple learners (if more complex ones cannot be fitted) can outperform a single, complex model, which is tailored to incorporate prior clinical knowledge; and (3) performance can vary considerably depending on interventions and their support in the data, and therefore critical quality checks should accompany every LTMLE analysis. We provide guidance for the practical application of LTMLE.

ObjectivesWe extend the method of Significant Zero Crossings of Derivatives (SiZer) to address within-subject correlations of repeatedly collected longitudinal biomarker data and the computational aspects of the methodology when analyzing massive biomarker databases. SiZer is a powerful visualization tool for exploring structures in curves by mapping areas where the first derivative is increasing, decreasing or does not change (plateau) thus exploring changes and normalization of biomarkers in the presence of therapy.MethodsWe propose a penalized spline SiZer (PS-SiZer) which can be expressed as a linear mixed model of the longitudinal biomarker process to account for irregularly collected data and within-subject correlations. Through simulations we show how sensitive PS-SiZer is in detecting existing features in longitudinal data versus existing versions of SiZer. In a real-world data analysis PS-SiZer maps are used to map areas where the first derivative of weight change after antiretroviral therapy (ART) start is significantly increasing, decreasing or does not change, thus exploring the durability of weight increase after the start of therapy. We use weight data repeatedly collected from persons living with HIV initiating ART in five regions in the International Epidemiologic Databases to Evaluate AIDS (IeDEA) worldwide collaboration and compare the durability of weight gain between ART regimens containing and not containing the drug stavudine (d4T), which has been associated with shorter durability of weight gain.ResultsThrough simulations we show that the PS-SiZer is more accurate in detecting relevant features in longitudinal data than existing SiZer variants such as the local linear smoother (LL) SiZer and the SiZer with smoothing splines (SS-SiZer). In the illustration we include data from 185,010 persons living with HIV who started ART with a d4T (53.1%) versus non-d4T (46.9%) containing regimen. The largest difference in durability of weight gain identified by the SiZer maps was observed in Southern Africa where weight gain in patients treated with d4T-containing regimens lasted 52.4 weeks compared to 94.4 weeks for those with non-d4T-containing regimens. In the other regions, persons receiving d4T-containing regimens experienced weight gains lasting 51-61 weeks versus 59-77 weeks in those receiving non-d4T-based regimens.DiscussionPS-SiZer, a SiZer variant, can handle irregularly collected longitudinal data and within-subject correlations and is sensitive in detecting even subtle features in biomarker curves.

BackgroundLittle is known about the functional relationship of delaying second-line treatment initiation for HIV-positive patients and mortality, given a patient’s immune status.MethodsWe included 7255 patients starting antiretroviral therapy between 2004-2017, from 9 South African cohorts, with virological failure and complete baseline data. We estimated the impact of switch time on the hazard of death using inverse probability of treatment weighting (IPTW) of marginal structural models. The non-linear relationship between month of switch and the 5-year survival probability, stratified by CD4 count at failure, was estimated with targeted maximum likelihood estimation (TMLE). We adjusted for measured time-varying confounding by CD4 count, viral load and visit frequency.Results5-year mortality was estimated as 10.5% (2.2%; 18.8%) for immediate switch and as 26.6% (20.9%; 32.3%) for no switch (49.9% if CD4 count3). The hazard of death was estimated to be 0.40 (95%CI: 0.33-0.48) times lower if everyone had been switched immediately compared to never. The shorter the delay in switching, the lower the hazard of death, e.g. delaying 30-60 days reduced the hazard 0.52 (0.41-0.65) times, and 60-120 days 0.56 (0.47-0.66) times.ConclusionsEarly treatment switch is particularly important for patients with low CD4 counts at failure.

Little is known about the functional relationship of delaying second-line treatment initiation for human immunodeficiency virus–positive patients and mortality, given a patient’s immune status. We included 7,255 patients starting antiretroviral therapy during 2004–2017, from 9 South African cohorts, with virological failure and complete baseline data. We estimated the impact of switch time on the hazard of death using inverse probability of treatment weighting of marginal structural models. The nonlinear relationship between month of switch and the 5-year survival probability, stratified by CD4 count at failure, was estimated with targeted maximum likelihood estimation. We adjusted for measured time-varying confounding by CD4 count, viral load, and visit frequency. Five-year mortality was estimated to be 10.5% (95% CI: 2.2, 18.8) for immediate switch and to be 26.6% (95% CI: 20.9, 32.3) for no switch (51.1% if CD4 count was

To assess long-term antiretroviral therapy (ART) outcomes during rapid HIV programme expansion in the public sector of Eswatini (formerly Swaziland).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.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/mmProgrammatic outcomes improved during large expansion of the treatment cohort and increased ART coverage. Changes in ART programming may have contributed to better outcomes.Evaluer les résultats du traitement antirétroviral (ART) à long terme durant l'expansion rapide du programme de lutte contre le VIH dans le secteur public d'Eswatini (anciennement Swaziland). MÉTHODES: Il s'agit d'une cohorte établie de manière rétrospective d'adultes VIH positifs (≥ 16 ans) qui ont commencé un ART de première ligne dans 25 établissements de santé à Shiselweni (Eswatini) entre janvier 2006 et décembre 2014. Les tendances temporelles de l'attrition dans l’ART, de l'extension de la couverture ART ont été décrites sur 9 ans. Nous avons utilisé des modèles de survie paramétriques flexibles pour évaluer la relation entre le temps écoulé avant l'attrition dans l’ART et les covariables. RÉSULTATS: Sur 24.772 initiations à l’ART, 6% (n = 1.488) ont eu lieu en 2006 contre 13% (n = 3.192) en 2014. Entre ces années, le nombre médian de cellules CD4 au début du traitement ART a augmenté (113 à 265 cellules/mmLes résultats programmatiques se sont améliorés au cours de l'expansion importante de la cohorte de traitement et de l'augmentation de la couverture ART. Les changements apportés au programme ART peuvent avoir contribué à de meilleurs résultats.

Background: Managing virologic failure (VF) in HIV-infected children is especially difficult in resource-limited settings, given limited availability of alternative drugs, concerns around adherence, and the development of HIV resistance mutations. We aimed to evaluate 4 management strategies for children following their first episode of VF by comparing their immunologic and virologic outcomes. Methods: We included children (< 16 years of age) with VF from 8 International Epidemiologic Database to Evaluate AIDS Southern Africa cohorts, initiating combination antiretroviral therapy (cART) between 2004 and 2010, who followed one of the 4 management strategies: continuing on their failing regimen; switching to a second-line regimen; switching to a holding regimen (either lamivudine monotherapy or other non-cART regimen); discontinuing all ART. We compared the effect of management strategy on the 52-week change in CD4% and log10VL from VF, using inverse probability weighting of marginal structural linear models. Results: Nine hundred eighty-two patients were followed over 54,168 weeks. Relative to remaining on a failing regimen, switching to second-line showed improved immunologic and virologic responses 52 weeks after VF with gains in CD4% of 1.5% (95% confidence interval [CI], 0.2–2.8) and declines in log10VL of -1.4 copies/mL (95% CI, -2.0, -0.8), while switching to holding regimens or discontinuing treatment had worse immunologic (-5.4% (95% CI, -12.1, 1.3) and -5.6% (95% CI, -15.4, 4.1) and virologic outcomes (0.2 (95% CI, -3.6, 4.1) and 0.8 (95% CI, -0.6, 2.1), respectively. Conclusions: The results provide useful guidance for managing children with VF. Consideration should be given to switching children failing first-line cART to second-line, given the improved virologic and immune responses when compared with other strategies.

International audience; 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

ObjectivesWe extend the method of Significant Zero Crossings of Derivatives (SiZer) to address within-subject correlations of repeatedly collected longitudinal biomarker data and the computational aspects of the methodology when analyzing massive biomarker databases. SiZer is a powerful visualization tool for exploring structures in curves by mapping areas where the first derivative is increasing, decreasing or does not change (plateau) thus exploring changes and normalization of biomarkers in the presence of therapy.MethodsWe propose a penalized spline SiZer (PS-SiZer) which can be expressed as a linear mixed model of the longitudinal biomarker process to account for irregularly collected data and within-subject correlations. Through simulations we show how sensitive PS-SiZer is in detecting existing features in longitudinal data versus existing versions of SiZer. In a real-world data analysis PS-SiZer maps are used to map areas where the first derivative of weight change after antiretroviral therapy (ART) start is significantly increasing, decreasing or does not change, thus exploring the durability of weight increase after the start of therapy. We use weight data repeatedly collected from persons living with HIV initiating ART in five regions in the International Epidemiologic Databases to Evaluate AIDS (IeDEA) worldwide collaboration and compare the durability of weight gain between ART regimens containing and not containing the drug stavudine (d4T), which has been associated with shorter durability of weight gain.ResultsThrough simulations we show that the PS-SiZer is more accurate in detecting relevant features in longitudinal data than existing SiZer variants such as the local linear smoother (LL) SiZer and the SiZer with smoothing splines (SS-SiZer). In the illustration we include data from 185,010 persons living with HIV who started ART with a d4T (53.1%) versus non-d4T (46.9%) containing regimen. The largest difference in durability of weight gain identified by the SiZer maps was observed in Southern Africa where weight gain in patients treated with d4T-containing regimens lasted 59.9 weeks compared to 133.8 weeks for those with non-d4T-containing regimens. In the other regions, persons receiving d4T-containing regimens experienced weight gains lasting 38-62 weeks versus 55-93 weeks in those receiving non-d4T-based regimens.DiscussionPS-SiZer, a SiZer variant, can handle irregularly collected longitudinal data and within-subject correlations and is sensitive in detecting even subtle features in biomarker curves.