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Background: The external validity of the randomized controlled trial (RCT) refers to the extent to which the results of the RCT apply to the relevant, non-trial population and is impacted by its eligibility criteria, its organization, and its delivery of the intervention. Here, we compared the outcomes of mortality and hospitalization between an RCT and a cohort study that concurrently enrolled HIV-exposed uninfected (HEU) newborns in Botswana. Methods: The Mpepu Study (the RCT) was a clinical trial which determined that co-trimoxazole (CTX) provided no survival benefit for HEUs, allowing both arms of the RCT to be used. The Maikaelelo study (the cohort study) was a prospective observational study that enrolled HEU newborns with telephone follow-up and no in-person visits. Rates of death and hospitalization in the pooled population, were modeled using cox-proportional hazards models for time to death or time to first hospitalization, with study setting (RCT vs. cohort study) as an independent variable. The causal effect of study setting on morbidity and mortality was obtained through a treatment effects approach. Results: In total, 4,010 infants were included; 1,306 were enrolled into the cohort study and 2,704 were enrolled into the RCT. No significant differences in mortality were observed between the two study settings (HR: 1.28, 95% CI: 0.76, 2.13), but RCT participants had a lower risk of hospitalization (HR: 0.72, 95% CI: 0.58, 0.89) that decreased with age. However, RCT participants had a higher risk of hospitalization within the first six months of life. The causal risk difference in hospitalizations attributable to the RCT setting was -0.03 (95% CI: -0.05, -0.01). Conclusions: Children in an RCT with rigorous application of national standard of care guidelines experienced a significantly lower risk of hospitalization than children participating in a cohort study that did not alter clinical care. Future research is needed to further investigate outcome disparities when real-world results fail to mirror those achieved in a clinical trial. Trial registration The Mpepu Trial was funded by the U.S. National Institutes of Health (No. NCT01229761) and the Maikaelelo Study was funded primarily by the U.S. Centers for Disease Control and Prevention (32AI007433-21).
The data for this analysis originates from two studies in Botswana: the Mpepu Trial (Clinical Trial No. {“type”:”clinical-trial”,”attrs”:{“text”:”NCT01229761″,”term_id”:”NCT01229761″}}NCT01229761), a randomized clinical trial, and the Maikaelelo Study, a prospective observational cohort study that captured data using telephone follow-up. Below, we briefly describe the designs of each study and in Additional File 1, we describe the relevant considerations of each study and its execution. The Mpepu Trial was a double-blind, randomized, placebo-controlled trial in which 2,848 HEU infants enrolled within the first 34 days of life between June 2011 and April 2015 and randomized to receive CTX or placebo [10]. Women with documented HIV-1-infection were recruited from public antenatal clinics or maternity wards in southern Botswana between the 26th week of pregnancy up to 34 days postpartum. The study was conducted in an area of Botswana without malaria transmission. Recruitment took place in Gaborone (urban setting), Molepolole (large village), and Lobatse (town). Mothers who elected to breastfeeding their infants gave consent to be randomly assigned to breastfeeding for 6 months (the recommended duration in Botswana) or 12 months (the duration recommended by WHO). Breastfed children were allocated by factorial randomization to CTX vs. Placebo and to 6 vs. 12 months of breastfeeding. The trial was stopped for futility as the data and safety monitoring board concluded a low likelihood of benefit with CTX. The Maikaelelo Study was an observational cohort study that enrolled mother-infant pairs from five public hospital maternity wards in Botswana, including Francistown (urban setting), Mochudi (large village), Ramotswa (village), Maun (town), and Kanye (large village). Between January 2012 and March 2013, the Maikaelelo study enrolled 1,499 HIV-infected and 1,501 HIV-negative mothers and their 3,033 infants, of which 1,515 were HEU [11]. In the primary analysis of Maikaelelo, HIV-exposed children with unknown infection were considered HIV-uninfected. A combined dataset of children enrolled in the Mpepu Trial and the Maikaelelo Study was created. Infants were included if they were HEU, as determined by the definitions of the respective study. To be conservative in the approach, infants whose HIV status was unknown by the end of the study period were excluded. Infants were excluded from the analysis if they died or were hospitalized prior to enrollment. Infants were also excluded from the analysis if maternal HIV treatment during pregnancy was missing. Infants from the Mpepu Study who were not randomized (and therefore did not enroll into the trial) were also excluded. Infants who died or were hospitalized within 30 days of birth were excluded from the analysis to ensure comparability between trials given their different enrollment strategies. Finally, events among infants in Maikaelelo that occurred after 547 days or 18 months (the length of follow-up in Mpepu) were excluded from the analysis. Given the non-overlapping clinical sites in Botswana from which these children were enrolled, an indicator variable was used to adjust for sites in large urban settings (Francistown and Gaborone) compared to sites in more rural or peri-urban settings (Maun, Ramotswa, Mochudi, Kanye, Lobatse, and Molepolole). Since both studies collected comparable socioeconomic data, a socioeconomic score was created ranging from 0 to 7, with 0 corresponding to lower socioeconomic status and 7 corresponding to a higher socioeconomic status. This score was a summation of the scores of maternal education (from none/primary to secondary to university), household access to electricity (from no access to access), source of water (from not piped into the home to piped into the home), and housing structure (from no stable housing, to informal housing, to mixed formal/informal, and to formal housing). Outcomes of interest were death and hospitalization as binary outcomes, as well as time to death and time to first hospitalization. Covariates included in all analyses were study setting (RCT vs. cohort study), sex, categorized site (Francistown/Gaborone vs. Other), socioeconomic status, breastfeeding strategy (ever breastfed vs. exclusively formula fed), maternal HIV treatment during pregnancy (none vs. zidovudine (ZDV) only vs. three-drug regimen), and low birthweight status (< 2500 g). To understand the relationship between study setting (RCT vs. cohort study), time, and either of the outcomes of death or hospitalization, two Cox proportional hazards model were fit modeling either time to death or time to first hospitalization from 1–18 months, adjusted for the aforementioned covariates including study setting as an independent variable. Where the proportional hazards assumption was thought to be violated, an interaction term between the study setting variable and the analysis time was generated. An interaction term between the natural logarithm of analysis time and study setting was modeled using restricted cubic spline transformations to visually assess the changes in the hazard ratio over time. The causal effect of study setting was obtained through an inverse probability-weighted estimator, and inferences were made with 100 replications of the bootstrapped standard errors. The results of this approach report two coefficients: the potential-outcome mean (POM) which is the risk of the outcome had all children been enrolled into the cohort study and the average treatment effect (ATE) which is the average difference in risk between the potential risk had all children been enrolled into the cohort study and the potential risk had all children been enrolled into the RCT. The treatment effects estimator attempts to make the treatment variable (study setting (RCT vs. cohort study)) and outcome variable (morbidity or mortality) independent after conditioning on the covariates of type of site (urban vs. non-urban), socioeconomic status, breastfeeding status, ARV strategy during pregnancy, and low-birthweight [12]. The function was implemented using the teffects ipw command in Stata. Sensitivity analyses were also conducted in which infants who died or were hospitalized within 30 days of enrollment into either study were excluded to determine whether these inferences held even after excluding the earlier effects of study setting.
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