HIV Prevention Among Men Who Have Sex With Men: Tenofovir Alafenamide Combination Preexposure Prophylaxis Versus Placebo.

BACKGROUND: While noninferiority of tenofovir alafenamide and emtricitabine (TAF/FTC) as preexposure prophylaxis (PrEP) for the prevention of human immunodeficiency virus (HIV) has been shown, interest remains in its efficacy relative to placebo. We estimate the efficacy of TAF/FTC PrEP versus placebo for the prevention of HIV infection. METHODS: We used data from the DISCOVER and iPrEx trials to compare TAF/FTC to placebo. DISCOVER was a noninferiority trial conducted from 2016 to 2017. iPrEx was a placebo-controlled trial conducted from 2007 to 2009. Inverse probability weights were used to standardize the iPrEx participants to the distribution of demographics and risk factors in the DISCOVER trial. To check the comparison, we evaluated whether risk of HIV infection in the shared tenofovir disoproxil fumarate and emtricitabine (TDF/FTC) arms was similar. RESULTS: Notable differences in demographics and risk factors occurred between trials. After standardization, the difference in risk of HIV infection between the TDF/FTC arms was near zero. The risk of HIV with TAF/FTC was 5.8 percentage points lower (95% confidence interval [CI], -2.0% to -9.6%) or 12.5-fold lower (95% CI, .02 to .31) than placebo standardized to the DISCOVER population. CONCLUSIONS: There was a reduction in HIV infection with TAF/FTC versus placebo across 96 weeks of follow-up. CLINICAL TRIALS REGISTRATION: NCT02842086 and NCT00458393.

Transportability Without Positivity: A Synthesis of Statistical and Simulation Modeling.

Studies designed to estimate the effect of an action in a randomized or observational setting often do not represent a random sample of the desired target population. Instead, estimates from that study can be transported to the target population. However, transportability methods generally rely on a positivity assumption, such that all relevant covariate patterns in the target population are also observed in the study sample. Strict eligibility criteria, particularly in the context of randomized trials, may lead to violations of this assumption. Two common approaches to address positivity violations are restricting the target population and restricting the relevant covariate set. As neither of these restrictions is ideal, we instead propose a synthesis of statistical and simulation models to address positivity violations. We propose corresponding g-computation and inverse probability weighting estimators. The restriction and synthesis approaches to addressing positivity violations are contrasted with a simulation experiment and an illustrative example in the context of sexually transmitted infection testing uptake. In both cases, the proposed synthesis approach accurately addressed the original research question when paired with a thoughtfully selected simulation model. Neither of the restriction approaches was able to accurately address the motivating question. As public health decisions must often be made with imperfect target population information, model synthesis is a viable approach given a combination of empirical data and external information based on the best available knowledge.

Leveraging External Validation Data: The Challenges of Transporting Measurement Error Parameters.

Approaches to address measurement error frequently rely on validation data to estimate measurement error parameters (e.g., sensitivity and specificity). Acquisition of validation data can be costly, thus secondary use of existing data for validation is attractive. To use these external validation data, however, we may need to address systematic differences between these data and the main study sample. Here, we derive estimators of the risk and the risk difference that leverage external validation data to account for outcome misclassification. If misclassification is differential with respect to covariates that themselves are differentially distributed in the validation and study samples, the misclassification parameters are not immediately transportable. We introduce two ways to account for such covariates: (1) standardize by these covariates or (2) iteratively model the outcome. If conditioning on a covariate for transporting the misclassification parameters induces bias of the causal effect (e.g., M-bias), the former but not the latter approach is biased. We provide proof of identification, describe estimation using parametric models, and assess performance in simulations. We also illustrate implementation to estimate the risk of preterm birth and the effect of maternal HIV infection on preterm birth. Measurement error should not be ignored and it can be addressed using external validation data via transportability methods.

Fusing trial data for treatment comparisons: Single vs multi-span bridging.

While randomized controlled trials (RCTs) are critical for establishing the efficacy of new therapies, there are limitations regarding what comparisons can be made directly from trial data. RCTs are limited to a small number of comparator arms and often compare a new therapeutic to a standard of care which has already proven efficacious. It is sometimes of interest to estimate the efficacy of the new therapy relative to a treatment that was not evaluated in the same trial, such as a placebo or an alternative therapy that was evaluated in a different trial. Such dual-study comparisons are challenging because of potential differences between trial populations that can affect the outcome. In this article, two bridging estimators are considered that allow for comparisons of treatments evaluated in different trials, accounting for measured differences in trial populations. A "multi-span" estimator leverages a shared arm between two trials, while a "single-span" estimator does not require a shared arm. A diagnostic statistic that compares the outcome in the standardized shared arms is provided. The two estimators are compared in simulations, where both estimators demonstrate minimal empirical bias and nominal confidence interval coverage when the identification assumptions are met. The estimators are applied to data from the AIDS Clinical Trials Group 320 and 388 to compare the efficacy of two-drug vs four-drug antiretroviral therapy on CD4 cell counts among persons with advanced HIV. The single-span approach requires weaker identification assumptions and was more efficient in simulations and the application.

Higher-order evidence.

Higher-order evidence is evidence about evidence. Epidemiologic examples of higher-order evidence include the settings where the study data constitute first-order evidence and estimates of misclassification comprise the second-order evidence (e.g., sensitivity, specificity) of a binary exposure or outcome collected in the main study. While sampling variability in higher-order evidence is typically acknowledged, higher-order evidence is often assumed to be free of measurement error (e.g., gold standard measures). Here we provide two examples, each with multiple scenarios where second-order evidence is imperfectly measured, and this measurement error can either amplify or attenuate standard corrections to first-order evidence. We propose a way to account for such imperfections that requires third-order evidence. Further illustrations and exploration of how higher-order evidence impacts results of epidemiologic studies is warranted.

"Like fighting a fire with a water pistol": A qualitative study of the work experiences of critical care nurses during the COVID-19 pandemic.

AIM: To understand the experience of critical care nurses during the COVID-19 pandemic, through the application of the Job-Demand-Resource model of occupational stress. DESIGN: Qualitative interview study. METHODS: Twenty-eight critical care nurses (CCN) working in ICU in the UK NHS during the COVID-19 pandemic took part in semi-structured interviews between May 2021 and May 2022. Interviews were guided by the constructs of the Job-Demand Resource model. Data were analysed using framework analysis. RESULTS: The most difficult job demands were the pace and amount, complexity, physical and emotional effort of their work. Prolonged high demands led to CCN experiencing emotional and physical exhaustion, burnout, post-traumatic stress symptoms and impaired sleep. Support from colleagues and supervisors was a core job resource. Sustained demands and impaired physical and psychological well-being had negative organizational consequences with CCN expressing increased intention to leave their role. CONCLUSIONS: The combination of high demands and reduced resources had negative impacts on the psychological well-being of nurses which is translating into increased consideration of leaving their profession. IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE: The full impacts of the pandemic on the mental health of CCN are unlikely to resolve without appropriate interventions. IMPACT: Managers of healthcare systems should use these findings to inform: (i) the structure and organization of critical care workplaces so that they support staff to be well, and (ii) supportive interventions for staff who are carrying significant psychological distress as a result of working during and after the pandemic. These changes are required to improve staff recruitment and retention. REPORTING METHOD: We used the COREQ guidelines for reporting qualitative studies. PATIENT AND PUBLIC CONTRIBUTION: Six CCN provided input to survey content and interview schedule. Two authors and members of the study team (T.S. and S.C.) worked in critical care during the pandemic.

Clinical Differences in Dogs with Enterococcal Bacteriuria Compared with Other Bacteriuria: A Retrospective, Case-Control Study.

A retrospective case-control study was performed to determine the clinical differences between dogs with enterococcal bacteriuria (n = 96 cases) and control dogs with any other bacteriuria (n = 288). More dogs with nonenterococcal bacteriuria demonstrated lower urinary tract clinical signs such as hematuria, pollakiuria, and stranguria (40% versus 27%, P = .02). Recessed vulva (odds ratio [OR] 2.5, 95% confidence interval [CI] 1.4-4.2, P < .001), hyperadrenocorticism (OR 0.149, 95% CI 0.004-0.066, P = .03), chronic kidney disease (OR 2.29, 95% CI 1.14-4.51, P = .01), and myelopathy (OR 5.77, 95% CI 3.07-10.82, P < .001) were more common in dogs with enterococcal bacteriuria. Enterococcus spp. cases were more likely to have polymicrobial growth than controls (OR 28.52; 95% CI 12.63-69.62, P ≤ .001). Pugs (OR 7.4, 95% CI 2.6-19.9, P < .001), bearded collies (OR 24.3, 95% CI 2.9-205.5, P = .003), and Saint Bernards (OR 17.3, CI 1.9-154.4, P = .01) had increased odds of enterococcal growth compared with mixed-breed dogs. In the control (but not the case) population, there was an association between resolution of clinical signs and administration of antimicrobials (P = .01). The signalment, clinical signs, comorbidities, and response to therapy in dogs with enterococcal bacteriuria are different from dogs with other bacteriuria.

Assessment of a virtual disaster preparedness and response simulation compared to previous in-person iterations: successful translation of the Penndemic framework.

Collaborative learning has documented benefits. Restrictions because of the COVID-19 pandemic prevented in-person collaborative experiences, therefore creating a pathway for online ones. An inter-university team previously created and published a novel framework that fosters collaborative learning for emergency/disaster preparedness and uses scenarios that attract student participation from a spectrum of disciplines. Here, we detail the implementation and evaluation of this framework in a virtual setting. Analysis of pre- and post-surveys from the virtual event revealed similar results to the previous in-person iterations. Results for both in-person and virtual events demonstrated that students had higher confidence and interest in emergency/disaster preparedness and interprofessional teamwork after participation. Implementation of this framework in a virtual setting can facilitate a positive student learning experience and inter-university collaboration.

Evaluating Clinic-Based Interventions to Reduce Racial Differences in Mortality Among People With Human Immunodeficiency Virus in the United States.

BACKGROUND: Mortality remains elevated among Black versus White adults receiving human immunodeficiency virus (HIV) care in the United States. We evaluated the effects of hypothetical clinic-based interventions on this mortality gap. METHODS: We computed 3-year mortality under observed treatment patterns among >40 000 Black and >30 000 White adults entering HIV care in the United States from 1996 to 2019. We then used inverse probability weights to impose hypothetical interventions, including immediate treatment and guideline-based follow-up. We considered 2 scenarios: "universal" delivery of interventions to all patients and "focused" delivery of interventions to Black patients while White patients continued to follow observed treatment patterns. RESULTS: Under observed treatment patterns, 3-year mortality was 8% among White patients and 9% among Black patients, for a difference of 1 percentage point (95% confidence interval [CI], .5-1.4). The difference was reduced to 0.5% under universal immediate treatment (95% CI, -.4% to 1.3%) and to 0.2% under universal immediate treatment combined with guideline-based follow-up (95% CI, -1.0% to 1.4%). Under the focused delivery of both interventions to Black patients, the Black-White difference in 3-year mortality was -1.4% (95% CI, -2.3% to -.4%). CONCLUSIONS: Clinical interventions, particularly those focused on enhancing the care of Black patients, could have significantly reduced the mortality gap between Black and White patients entering HIV care from 1996 to 2019.

Illustration of 2 Fusion Designs and Estimators.

"Fusion" study designs combine data from different sources to answer questions that could not be answered (as well) by subsets of the data. Studies that augment main study data with validation data, as in measurement-error correction studies or generalizability studies, are examples of fusion designs. Fusion estimators, here solutions to stacked estimating functions, produce consistent answers to identified research questions using data from fusion designs. In this paper, we describe a pair of examples of fusion designs and estimators, one where we generalize a proportion to a target population and one where we correct measurement error in a proportion. For each case, we present an example motivated by human immunodeficiency virus research and summarize results from simulation studies. Simulations demonstrate that the fusion estimators provide approximately unbiased results with appropriate 95% confidence interval coverage. Fusion estimators can be used to appropriately combine data in answering important questions that benefit from multiple sources of information.

Missing Outcome Data in Epidemiologic Studies.

Missing data are pandemic and a central problem for epidemiology. Missing data reduce precision and can cause notable bias. There remain too few simple published examples detailing types of missing data and illustrating their possible impact on results. Here we take an example randomized trial that was not subject to missing data and induce missing data to illustrate 4 scenarios in which outcomes are 1) missing completely at random, 2) missing at random with positivity, 3) missing at random without positivity, and 4) missing not at random. We demonstrate that accounting for missing data is generally a better strategy than ignoring missing data, which unfortunately remains a standard approach in epidemiology.

A Per-Protocol Analysis Using Inverse-Probability-of-Censoring Weights in a Randomized Trial of Initial Protease Inhibitor Versus Nonnucleoside Reverse Transcriptase Inhibitor Regimens in Children.

Protocol adherence may influence measured treatment effectiveness in randomized controlled trials. Using data from a multicenter trial (Europe and the Americas, 2002-2009) of children with human immunodeficiency virus type 1 who had been randomized to receive initial protease inhibitor (PI) versus nonnucleoside reverse transcriptase inhibitor (NNRTI) antiretroviral therapy regimens, we generated time-to-event intention-to-treat (ITT) estimates of treatment effectiveness, applied inverse-probability-of-censoring weights to generate per-protocol efficacy estimates, and compared shifts from ITT to per-protocol estimates across and within treatment arms. In ITT analyses, 263 participants experienced 4-year treatment failure probabilities of 41.3% for PIs and 39.5% for NNRTIs (risk difference = 1.8% (95% confidence interval (CI): -10.1, 13.7); hazard ratio = 1.09 (95% CI: 0.74, 1.60)). In per-protocol analyses, failure probabilities were 35.6% for PIs and 29.2% for NNRTIs (risk difference = 6.4% (95% CI: -6.7, 19.4); hazard ratio = 1.30 (95% CI: 0.80, 2.12)). Within-arm shifts in failure probabilities from ITT to per-protocol analyses were 5.7% for PIs and 10.3% for NNRTIs. Protocol nonadherence was nondifferential across arms, suggesting that possibly better NNRTI efficacy may have been masked by differences in within-arm shifts deriving from differential regimen forgiveness, residual confounding, or chance. A per-protocol approach using inverse-probability-of-censoring weights facilitated evaluation of relationships among adherence, efficacy, and forgiveness applicable to pediatric oral antiretroviral regimens.

Optimizing Treatment for Human Immunodeficiency Virus to Improve Clinical Outcomes Using Precision Medicine.

In first-line antiretroviral therapy (ART) for human immunodeficiency virus (HIV) treatment, some subgroups of patients may respond better to an efavirenz-based regimen than an integrase strand transfer inhibitor (InSTI)-based regimen, or vice versa, due to patient characteristics modifying treatment effects. Using data based on nearly 16,000 patients from the North American AIDS Cohort Collaboration on Research and Design from 2009-2016, statistical methods for precision medicine were employed to estimate an optimal treatment rule that minimizes the 5-year risk of the composite outcome of acquired immune deficiency syndrome (AIDS)-defining illnesses, serious non-AIDS events, and all-cause mortality. The treatment rules considered were functions that recommend either an efavirenz- or InSTI-based regimen conditional on baseline patient characteristics such as demographic information, laboratory results, and health history. The estimated 5-year risk under the estimated optimal treatment rule was 10.0% (95% confidence interval (CI): 8.6, 11.3), corresponding to an absolute risk reduction of 2.3% (95% CI: 0.9, 3.8) when compared with recommending an efavirenz-based regimen for all patients and 2.6% (95% CI: 1.0, 4.2) when compared with recommending an InSTI-based regimen for all. Tailoring ART to individual patient characteristics may reduce 5-year risk of the composite outcome compared with assigning all patients the same drug regimen.

When Does Differential Outcome Misclassification Matter for Estimating Prevalence?

BACKGROUND: When accounting for misclassification, investigators make assumptions about whether misclassification is "differential" or "nondifferential." Most guidance on differential misclassification considers settings where outcome misclassification varies across levels of exposure, or vice versa. Here, we examine when covariate-differential misclassification must be considered when estimating overall outcome prevalence. METHODS: We generated datasets with outcome misclassification under five data generating mechanisms. In each, we estimated prevalence using estimators that (a) ignored misclassification, (b) assumed misclassification was nondifferential, and (c) allowed misclassification to vary across levels of a covariate. We compared bias and precision in estimated prevalence in the study sample and an external target population using different sources of validation data to account for misclassification. We illustrated use of each approach to estimate HIV prevalence using self-reported HIV status among people in East Africa cross-border areas. RESULTS: The estimator that allowed misclassification to vary across levels of the covariate produced results with little bias for both populations in all scenarios but had higher variability when the validation study contained sparse strata. Estimators that assumed nondifferential misclassification produced results with little bias when the covariate distribution in the validation data matched the covariate distribution in the target population; otherwise estimates assuming nondifferential misclassification were biased. CONCLUSIONS: If validation data are a simple random sample from the target population, assuming nondifferential outcome misclassification will yield prevalence estimates with little bias regardless of whether misclassification varies across covariates. Otherwise, obtaining valid prevalence estimates requires incorporating covariates into the estimators used to account for misclassification.

Sensitivity Analyses for Means or Proportions with Missing Outcome Data.

We describe an approach to sensitivity analysis introduced by Robins et al (1999), for the setting where the outcome is missing for some observations. This flexible approach focuses on the relationship between the outcomes and missingness, where data can be missing completely at random, missing at random given observed data, or missing not at random. We provide examples from HIV that include the sensitivity of the estimation of a mean and proportion under different missingness mechanisms. The approach illustrated provides a method for examining how the results of epidemiologic studies might shift as a function of bias due to missing data.

Disparities in Fatal Occupational Injury Rates in North Carolina, 1978-2017: Comparing Nonmanagerial Employees to Managers.

BACKGROUND: We examined fatal occupational injuries among private-sector workers in North Carolina during the 40-year period 1978-2017, comparing the occurrence of fatal injuries among nonmanagerial employees to that experienced by managers. METHODS: We estimated a standardized fatal occupational injury ratio by inverse probability of exposure weighting, taking nonmanagerial workers as the target population. When this ratio measure takes a value greater than unity it signals settings in which nonmanagerial employees are not provided as safe a work environment as that provided for managers. RESULTS: Across all industries, nonmanagerial workers in North Carolina experienced fatal occupational injury rates 8.2 (95% CI = 7.0, 10.0) times the rate experienced by managers. Disparities in fatal injury rates between managers and the employees they supervise were greatest in forestry, rubber and metal manufacturing, wholesale trade, fishing and extractive industries, and construction. CONCLUSIONS: The results may help focus discussion about workplace safety between labor and management upon equity, with a goal of providing a work environment for nonmanagerial employees as safe as the one provided for managers.

Accounting for nonmonotone missing data using inverse probability weighting.

Inverse probability weighting can be used to correct for missing data. New estimators for the weights in the nonmonotone setting were introduced in 2018. These estimators are the unconstrained maximum likelihood estimator (UMLE) and the constrained Bayesian estimator (CBE), an alternative if UMLE fails to converge. In this work we describe and illustrate these estimators, and examine performance in simulation and in an applied example estimating the effect of anemia on spontaneous preterm birth in the Zambia Preterm Birth Prevention Study. We compare performance with multiple imputation (MI) and focus on the setting of an observational study where inverse probability of treatment weights are used to address confounding. In simulation, weighting was less statistically efficient at the smallest sample size and lowest exposure prevalence examined (n = 1500, 15% respectively) but in other scenarios statistical performance of weighting and MI was similar. Weighting had improved computational efficiency taking, on average, 0.4 and 0.05 times the time for MI in R and SAS, respectively. UMLE was easy to implement in commonly used software and convergence failure occurred just twice in >200 000 simulated cohorts making implementation of CBE unnecessary. In conclusion, weighting is an alternative to MI for nonmonotone missingness, though MI performed as well as or better in terms of bias and statistical efficiency. Weighting's superior computational efficiency may be preferred with large sample sizes or when using resampling algorithms. As validity of weighting and MI rely on correct specification of different models, both approaches could be implemented to check agreement of results.

The potential role of veterinary technicians in promoting antimicrobial stewardship.

BACKGROUND: A core principle of antimicrobial stewardship (AMS) in veterinary settings is the need for engagement of all stakeholders; however, no studies have addressed the role of veterinary technicians in AMS specifically. The objective of this study was to qualitatively assess knowledge, opinions, and practices related to AMS among technicians. Semi-structured interviews were conducted with 33 veterinary technicians with varied backgrounds, experience and roles. Interviews centered on participants work experience and interactions with their employer, perceptions of antimicrobial resistance and overuse in veterinary medicine, observed application of AMS principles, opinions on potential opportunities for technicians to contribute to AMS and concomitant potential barriers to these opportunities. Transcripts of interviews were coded thematically by two authors, then organized into a hierarchical framework, and the characterization of codes was compared across different categories of respondents. RESULTS: Most veterinary technicians were knowledgeable about antimicrobial drugs but could not provide a complete definition of antimicrobial resistance or AMS. Most veterinary technicians could identify examples of antimicrobial misuse. Participants identified areas of client education and discussion with veterinarians as potential areas to contribute to AMS. Barriers identified included hierarchical structures of veterinary practices and time-constraints. Most participants expressed a personal interest in participating in AMS. CONCLUSIONS: There is a possible appetite among some veterinary technicians to participate in AMS and they already play applicable roles in practices. Barriers such as educational needs, hierarchical structures of veterinary practices and time constraints will need to be addressed if technicians are included in AMS efforts.

Developmental outcomes for survivors of placental laser photocoagulation for the management of twin-to-twin transfusion syndrome.

BACKGROUND: Fetoscopic laser coagulation of placental anastomoses reverses the pathological process in twin-to-twin transfusion syndrome, thereby increasing survival, but there are a paucity of studies addressing long-term neurodevelopmental outcome of survivors. This study aimed to ascertain the presence of neurodevelopmental disabilities in child survivors of monochorionic pregnancies managed by placental laser photocoagulation in the Australian state of Victoria. METHODS: All pregnancies undergoing placental laser photocoagulation with the Victorian Fetal Therapy Service between 2006-2017 were included. Information on each surviving child, including demographics, perinatal course, and developmental progress was collected from parents, and consent was sought to complete the Child Behaviour Checklist. Interviewers evaluated whether this information was consistent with a diagnosis of any of 14 neurodevelopmental conditions. A three-tiered outcome measure was allocated for each child: (1) unimpaired or developmentally normal, (2) mild or moderate neurological impairment, or (3) severe neurological impairment. Clinical predictors for adverse outcome were identified. RESULTS: Of 116 pregnancies (113 twin, 3 triplet), 96 (83%) resulted in 1 + surviving fetuses. 57/113 (50%) twin pregnancies resulted in 2 survivors, 36 (32%) in 1 survivor, and 20 (18%) in no survivors. Of the 235 fetuses, 154 (65.5%) survived to follow-up. Survival increased from 59% in 2006-2008 to 73% in 2015-2017. 90/154 (58%) survivors were followed up at a mean age of 7.5 [SD 3.0] years. Based on parental interview and Child Behaviour Checklist data, 28/90 (31%) participants were assessed as having neurodevelopmental impairment, 27 of mild-moderate severity and 1 severe. Speech/language disorders, attention deficit (hyperactivity) disorders, and fine motor impairment were most common. Neonatal length of stay conferred the highest risk of impairment. CONCLUSION: Substantial variation exists between fetal therapy services in the type and length of neonatal follow-up following fetoscopic laser coagulation, contributing to a lack of data on long-term outcomes. The findings from this study support increasingly urgent calls to undertake systematic and sustained follow-up of fetoscopic laser coagulation survivors until school age. Information from this study may assist parents in their decision-making when offered fetal surgery. Importantly, it highlights a group for targeted surveillance and early intervention.

The pregnant traveller: An overview of common preventable infections.

Pregnant travellers are often unaware of the various infections that can be acquired during travel and that pregnant people may be at increased risk of severe disease compared to their non-pregnant counterparts. Pregnant people often seek pre-travel counselling from their obstetrician or primary care physicians, who may not be well versed in travel medicine. This paper aims to provide information for maternity care providers regarding important travel-related food, water and mosquito-borne illnesses, including their prevention and treatment methods, equipping maternity care providers to confidently counsel prospective travellers during pregnancy.