Hormonal Contraception and Risk of Cardiometabolic Disease in Women with HIV.

Objective: We sought to determine the association of hormonal contraception (HC) and cardiometabolic outcomes among women with human immunodeficiency virus (HIV). Methods: We included women with HIV aged 18-45 years in clinical care in the Southeastern United States between 1998 and 2018. Oral and injectable HC use was captured from medication records. Our outcomes included incident cardiovascular/thrombotic disease (CVD) (atherosclerosis, hypertension, cerebrovascular disease, thrombosis, and heart failure) and incident metabolic disorders (diabetes, dyslipidemia, obesity, and non-alcoholic steatohepatitis). We excluded women with prevalent conditions. We used multivariable marginal structural models to examine time-varying current and cumulative HC use and cardiometabolic outcomes in separate analyses, adjusting for age, race, smoking, time-varying comorbidities, CD4 cell count, HIV RNA, and antiretroviral use. Women with HC exposure were compared with women without HC exposure. Results: Among the 710 women included, 201 women (28%) used HC. CVD analyses included 603 women without prevalent CVD and 93 incident events; metabolic analyses included 365 women without prevalent metabolic disease and 150 incident events. Current and cumulative oral HC use was associated with increased odds of CVD, though this was not statistically significant (adjusted odds ratio [aOR] = 2.08, [95% confidence interval (CI): 0.80-5.43] and aOR = 1.24 [95% CI: 0.96-1.60] per year of use, respectively). Oral HC was not associated with risk of incident metabolic disorders. Depot medroxyprogesterone acetate (DMPA) was not associated with risk of incident CVD. Current and cumulative DMPA use was significantly associated with decreased odds of incident metabolic disorders (aOR = 0.48 [95% CI: 0.23, 1.00] and aOR = 0.65 [95% CI: 0.42-1.00] per year of use, respectively). Conclusion: Our results suggest that cardiovascular risk should be considered when selecting contraception for women with HIV.

Clinical outcomes and risk factors for immune recovery and all-cause mortality in Latin Americans living with HIV with virological success: a retrospective cohort study.

INTRODUCTION: Immune reconstitution following antiretroviral therapy (ART) initiation is crucial to prevent AIDS and non-AIDS-related comorbidities. Patients with suppressed viraemia who fail to restore cellular immunity are exposed to an increased risk of morbidity and mortality during long-term follow-up, although the underlying mechanisms remain poorly understood. We aim to describe clinical outcomes and factors associated with the worse immune recovery and all-cause mortality in people living with HIV (PLWH) from Latin America following ART initiation. METHODS: Retrospective cohort study using the CCASAnet database: PLWH ≥18 years of age at ART initiation using a three drug-based combination therapy and with medical follow-up for ≥24 months after ART initiation and undetectable viral load were included. Patients were divided into four immune recovery groups based on rounded quartiles of increase in CD4 T-cell count at 2 years of treatment (<150, [150, 250), [250, 350] and >350 cells/mm3 ). Primary outcomes included all-cause mortality, AIDS-defining events and non-communicable diseases that occurred >2 years after ART initiation. Factors associated with an increase in CD4 T-cell count at 2 years of treatment were evaluated using a cumulative probability model with a logit link. RESULTS: In our cohort of 4496 Latin American PLWH, we found that patients with the lowest CD4 increase (<150) had the lowest survival probability at 10 years of follow-up. Lower increase in CD4 count following therapy initiation (and remarkably not a lower baseline CD4 T-cell count) and older age were risk factors for all-cause mortality. We also found that older age, male sex and higher baseline CD4 T-cell count were associated with lower CD4 count increase following therapy initiation. CONCLUSIONS: Our study shows that PLWH with lower increases in CD4 count have lower survival probabilities. CD4 increase during follow-up might be a better predictor of mortality in undetectable PLWH than baseline CD4 count. Therefore, it should be included as a routine clinical variable to assess immune recovery and overall survival.

Piloting Safety and Stabilization: A Multi-component Trauma Intervention to Improve HIV Viral Suppression, Retention in Care, and Post-traumatic Stress Disorder in a Southern United States HIV Service Organization.

In this observational study, we assessed the extent to which a community-created pilot intervention, providing trauma-informed care for persons with HIV (PWH), affected HIV care retention and viral suppression among PWH attending an HIV Services Organization in the Southern US. PWH with trauma exposure and/or trauma symptoms (N = 166) were offered a screening and referral to treatment (SBIRT) session. Per self-selection, 30 opted-out, 29 received SBIRT-Only, 25 received SBIRT-only but reported receiving other behavioral health care elsewhere, and 82 participated in the Safety and Stabilization (S&S) Intervention. Estimates from multivariable logistic regression analyses indicated S&S Intervention participants had increased retention in HIV care (adjusted odds ratio [aOR] 5.46, 95% CI 1.70-17.50) and viral suppression (aOR 17.74, 95% CI 1.83-172), compared to opt-out participants. Some evidence suggested that PTSD symptoms decreased for intervention participants. A randomized controlled trial is needed to confirm findings.

Associations Between Gestational Weight Gain, Gestational Diabetes, and Childhood Obesity Incidence.

INTRODUCTION: Excessive maternal gestational weight gain (GWG) is strongly correlated with childhood obesity, yet how excess maternal weight gain and gestational diabetes mellitus (GDM) interact to affect early childhood obesity is poorly understood. The purpose of this study was to investigate whether overall and trimester-specific maternal GWG and GDM were associated with obesity in offspring by age 6 years. METHODS: A cohort of 10,335 maternal-child dyads was established from electronic health records. Maternal weights at conception and delivery were estimated from weight trajectory fits using functional principal components analysis. Kaplan-Meier curves and Cox regression, together with generalized raking, examined time-to-childhood-obesity. RESULTS: Obesity diagnosed prior to age 6 years was estimated at 19.7% (95% CI: 18.3, 21.1). Maternal weight gain during pregnancy was a strong predictor of early childhood obesity (p < 0.0001). The occurrence of early childhood obesity was lower among mothers with GDM compared with those without diabetes (adjusted hazard ratio = 0.58, p = 0.014). There was no interaction between maternal weight gain and GDM (p = 0.55). Higher weight gain during the first trimester was associated with lower risk of early childhood obesity (p = 0.0002) whereas higher weight gain during the second and third trimesters was associated with higher risk (p < 0.0001). DISCUSSION: Results indicated total and trimester-specific maternal weight gain was a strong predictor of early childhood obesity, though obesity risk by age 6 was lower for children of mothers with GDM. Additional research is needed to elucidate underlying mechanisms directly related to trimester-specific weight gain and GDM that impede or protect against obesity prevalence during early childhood.

Excessive maternal gestational weight gain (GWG) and gestational diabetes mellitus (GDM) have been linked to childhood obesity. Yet, research on how excessive total and trimester-specific GWG and GDM interact to affect early childhood obesity remains inconclusive. This study found that inadequate weight gain in the first trimester and excessive weight gain in the second and third trimester were associated with higher risks of childhood obesity by age 6. No significant interaction between maternal GWG and GDM was noted suggesting that these two important maternal conditions do not have a combined effect on the risk of early childhood obesity.

Three-phase generalized raking and multiple imputation estimators to address error-prone data.

Validation studies are often used to obtain more reliable information in settings with error-prone data. Validated data on a subsample of subjects can be used together with error-prone data on all subjects to improve estimation. In practice, more than one round of data validation may be required, and direct application of standard approaches for combining validation data into analyses may lead to inefficient estimators since the information available from intermediate validation steps is only partially considered or even completely ignored. In this paper, we present two novel extensions of multiple imputation and generalized raking estimators that make full use of all available data. We show through simulations that incorporating information from intermediate steps can lead to substantial gains in efficiency. This work is motivated by and illustrated in a study of contraceptive effectiveness among 83 671 women living with HIV, whose data were originally extracted from electronic medical records, of whom 4732 had their charts reviewed, and a subsequent 1210 also had a telephone interview to validate key study variables.

Characterizing residential mobility among people with HIV in Tennessee and its impact on HIV care outcomes.

OBJECTIVE: Our objective was to assess the prevalence and patterns of mobility among people with HIV (PWH) in Tennessee and its impact on HIV care outcomes. DESIGN: Retrospective cohort study. METHODS: We combined residential address and HIV surveillance data from PWH in Tennessee from 2016 to 2018. Using Poisson regression, we estimated associations between in-state mobility (change in address or total miles moved) in 1 year and outcomes in the subsequent year; retention: having two CD4 + /HIV RNA values (labs) in a calendar year at least 3 months apart, loss to follow-up (LTFU): having labs at baseline but not the subsequent year, and viral suppression: HIV RNA less than 200 copies/ml. We applied a kernel density estimator to origin-destination address lines to visualize mobility patterns across demographic subgroups. RESULTS: Among 17 428 PWH [median age 45 years (interquartile range; IQR 34-53)], 6564 (38%) had at least one move. Median miles moved was 8.9 (IQR 2.6-143.4)). We observed in-state movement between major cities (Chattanooga, Knoxville, Memphis and Nashville) and out-of-state movement to and from Georgia and Florida. Having at least one in-state move was associated with a decreased likelihood of retention [adjusted relative risk (aRR) = 0.91; 95% confidence interval (CI) 0.88-0.95], and an increased risk of LTFU (aRR = 1.17; 95% CI 1.04-1.31, two to three moves vs. none). Greater distance moved in-state was associated with decreased retention and increased LTFU (aRR = 0.53; 95% CI 0.49-0.58, aRR = 2.52; 95% CI 2.25-2.83, respectively for 1000 vs. 0 miles). There was no association between mobility and viral suppression. CONCLUSION: Mobility is common among PWH in Tennessee and is associated with initial poor engagement in HIV care.

Training the next generation of Biostatisticians in West Africa: The Vanderbilt Nigeria Biostatistics Training Program (VN-BioStat).

Biomedical HIV research is growing in West Africa, but biostatistical expertise is lagging. The Vanderbilt-Nigeria Biostatistics Training Program (VN-BioStat) seeks to establish a research and training platform for biostatisticians doing HIV-related research in Nigeria. The objectives of the program are: 1) Host two Nigerian data scientists per year (a total of 10 over 5 years) at Vanderbilt University Medical Center to gain hands-on biostatistics training and experience via one-year fellowships. Eligible trainees will be junior investigators with PhDs or nearing completion of their PhDs in statistics or related fields, including mathematics and computer science. 2) Conduct annual workshops in Nigeria to provide biostatistics training. Trainees will undertake biostatistics coursework and hands-on training and participate in mentorship as biostatisticians involved in HIV research. Trainees will be at Vanderbilt for a full year and be part of an active biostatistics department. They will be immersed in a dry-lab HIV biostatistics project in collaboration with a Nigerian HIV research project and lead a methodologically focused research project. They will also participate in a one-month research training/grant writing program in Nashville. The VN-BioStat program will build on the existing momentum of ongoing initiatives to enhance research capacity in Nigeria by developing biostatistics leadership. VN-BioStat trainees will interact with investigators from Nigeria to provide collaborative biostatistical assistance with study design and data analysis, thus gaining real-world experience that will benefit the trainees and the broader research community in Nigeria.

Lessons learned from over a decade of data audits in international observational HIV cohorts in Latin America and East Africa.

Introduction: Routine patient care data are increasingly used for biomedical research, but such "secondary use" data have known limitations, including their quality. When leveraging routine care data for observational research, developing audit protocols that can maximize informational return and minimize costs is paramount. Methods: For more than a decade, the Latin America and East Africa regions of the International epidemiology Databases to Evaluate AIDS (IeDEA) consortium have been auditing the observational data drawn from participating human immunodeficiency virus clinics. Since our earliest audits, where external auditors used paper forms to record audit findings from paper medical records, we have streamlined our protocols to obtain more efficient and informative audits that keep up with advancing technology while reducing travel obligations and associated costs. Results: We present five key lessons learned from conducting data audits of secondary-use data from resource-limited settings for more than 10 years and share eight recommendations for other consortia looking to implement data quality initiatives. Conclusion: After completing multiple audit cycles in both the Latin America and East Africa regions of the IeDEA consortium, we have established a rich reference for data quality in our cohorts, as well as large, audited analytical datasets that can be used to answer important clinical questions with confidence. By sharing our audit processes and how they have been adapted over time, we hope that others can develop protocols informed by our lessons learned from more than a decade of experience in these large, diverse cohorts.

Spearman-like correlation measure adjusting for covariates in bivariate survival data.

We propose an extension of Spearman's correlation for censored continuous and discrete data that permits covariate adjustment. Previously proposed nonparametric and semiparametric Spearman's correlation estimators require either nonparametric estimation of the bivariate survival surface or parametric assumptions about the dependence structure. In practice, nonparametric estimation of the bivariate survival surface is difficult, and parametric assumptions about the correlation structure may not be satisfied. Therefore, we propose a method that requires neither and uses only the marginal survival distributions. Our method estimates the correlation of probability-scale residuals, which has been shown to equal Spearman's correlation when there is no censoring. Because this method relies only on marginal distributions, it tends to be less variable than the previously suggested nonparametric estimators, and the confidence intervals are easily constructed. Although under censoring, it is biased for Spearman's correlation as our simulations show, it performs well under moderate censoring, with a smaller mean squared error than nonparametric approaches. We also extend it to partial (adjusted), conditional, and partial-conditional correlation, which makes it particularly relevant for practical applications. We apply our method to estimate the correlation between time to viral failure and time to regimen change in a multisite cohort of persons living with HIV in Latin America.

Rank intraclass correlation for clustered data.

Clustered data are common in biomedical research. Observations in the same cluster are often more similar to each other than to observations from other clusters. The intraclass correlation coefficient (ICC), first introduced by R. A. Fisher, is frequently used to measure this degree of similarity. However, the ICC is sensitive to extreme values and skewed distributions, and depends on the scale of the data. It is also not applicable to ordered categorical data. We define the rank ICC as a natural extension of Fisher's ICC to the rank scale, and describe its corresponding population parameter. The rank ICC is simply interpreted as the rank correlation between a random pair of observations from the same cluster. We also extend the definition when the underlying distribution has more than two hierarchies. We describe estimation and inference procedures, show the asymptotic properties of our estimator, conduct simulations to evaluate its performance, and illustrate our method in three real data examples with skewed data, count data, and three-level ordered categorical data.

Analyzing clustered continuous response variables with ordinal regression models.

Continuous response data are regularly transformed to meet regression modeling assumptions. However, approaches taken to identify the appropriate transformation can be ad hoc and can increase model uncertainty. Further, the resulting transformations often vary across studies leading to difficulties with synthesizing and interpreting results. When a continuous response variable is measured repeatedly within individuals or when continuous responses arise from clusters, analyses have the additional challenge caused by within-individual or within-cluster correlations. We extend a widely used ordinal regression model, the cumulative probability model (CPM), to fit clustered, continuous response data using generalized estimating equations for ordinal responses. With the proposed approach, estimates of marginal model parameters, cumulative distribution functions , expectations, and quantiles conditional on covariates can be obtained without pretransformation of the response data. While computational challenges arise with large numbers of distinct values of the continuous response variable, we propose feasible and computationally efficient approaches to fit CPMs under commonly used working correlation structures. We study finite sample operating characteristics of the estimators via simulation and illustrate their implementation with two data examples. One studies predictors of CD4:CD8 ratios in a cohort living with HIV, and the other investigates the association of a single nucleotide polymorphism and lung function decline in a cohort with early chronic obstructive pulmonary disease.

Inverse Probability Weights for Quasicontinuous Ordinal Exposures With a Binary Outcome: Method Comparison and Case Study.

Inverse probability weighting (IPW), a well-established method of controlling for confounding in observational studies with binary exposures, has been extended to analyses with continuous exposures. Methods developed for continuous exposures may not apply when the exposure is quasicontinuous because of irregular exposure distributions that violate key assumptions. We used simulations and cluster-randomized clinical trial data to assess 4 approaches developed for continuous exposures-ordinary least squares (OLS), covariate balancing generalized propensity scores (CBGPS), nonparametric covariate balancing generalized propensity scores (npCBGPS), and quantile binning (QB)-and a novel method, a cumulative probability model (CPM), in quasicontinuous exposure settings. We compared IPW stability, covariate balance, bias, mean squared error, and standard error estimation across 3,000 simulations with 6 different quasicontinuous exposures, varying in skewness and granularity. In general, CBGPS and npCBGPS resulted in excellent covariate balance, and npCBGPS was the least biased but the most variable. The QB and CPM approaches had the lowest mean squared error, particularly with marginally skewed exposures. We then successfully applied the IPW approaches, together with missing-data techniques, to assess how session attendance (out of a possible 15) in a partners-based clustered intervention among pregnant couples living with human immunodeficiency virus in Mozambique (2017-2022) influenced postpartum contraceptive uptake.

Variation in missed doses and reasons for discontinuation of anti-tuberculosis drugs during hospital treatment for drug-resistant tuberculosis in South Africa.

BACKGROUND: Updated World Health Organization (WHO) treatment guidelines prioritize all-oral drug-resistant tuberculosis (DR-TB) regimens. Several poorly tolerated drugs, such as amikacin and para-aminosalicylic acid (PAS), remain treatment options for DR-TB in WHO-recommended longer regimens as Group C drugs. Incomplete treatment with anti-TB drugs increases the risk of treatment failure, relapse, and death. We determined whether missed doses of individual anti-TB drugs, and reasons for their discontinuation, varied in closely monitored hospital settings prior to the 2020 WHO DR-TB treatment guideline updates. METHODS: We collected retrospective data on adult patients with microbiologically confirmed DR-TB between 2008 and 2015 who were selected for a study of acquired drug resistance in the Western Cape Province of South Africa. Medical records through mid-2017 were reviewed. Patients received directly observed treatment during hospitalization at specialized DR-TB hospitals. Incomplete treatment with individual anti-TB drugs, defined as the failure to take medication as prescribed, regardless of reason, was determined by comparing percent missed doses, stratified by HIV status and DR-TB regimen. We applied a generalized mixed effects model. RESULTS: Among 242 patients, 131 (54%) were male, 97 (40%) were living with HIV, 175 (72%) received second-line treatment prior to first hospitalization, and 191 (79%) died during the study period. At initial hospitalization, 134 (55%) patients had Mycobacterium tuberculosis with resistance to rifampicin and isoniazid (multidrug-resistant TB [MDR-TB]) without resistance to ofloxacin or amikacin, and 102 (42%) had resistance to ofloxacin and/or amikacin. Most patients (129 [53%]) had multiple hospitalizations and DST changes occurred in 146 (60%) by the end of their last hospital discharge. Incomplete treatment was significantly higher for amikacin (18%), capreomycin (18%), PAS (17%) and kanamycin (16%) than other DR-TB drugs (P<0.001), including ethionamide (8%), moxifloxacin (7%), terizidone (7%), ethambutol (7%), and pyrazinamide (6%). Among the most frequently prescribed drugs, second-line injectables had the highest rates of discontinuation for adverse events (range 0.56-1.02 events per year follow-up), while amikacin, PAS and ethionamide had the highest rates of discontinuation for patient refusal (range 0.51-0.68 events per year follow-up). Missed doses did not differ according to HIV status or anti-TB drug combinations. CONCLUSION: We found that incomplete treatment for second-line injectables and PAS during hospitalization was higher than for other anti-TB drugs. To maximize treatment success, interventions to improve person-centered care and mitigate adverse events may be necessary in cases when PAS or amikacin (2020 WHO recommended Group C drugs) are needed.

Relationships Between Patient Race and Residential Race Context With Missed Human Immunodeficiency Virus Care Visits in the United States, 2010-2015.

BACKGROUND: Racial inequities exist in retention in human immunodeficiency virus (HIV) care and multilevel analyses are needed to contextualize and address these differences. Leveraging data from a multisite clinical cohort of people with HIV (PWH), we assessed the relationships between patient race and residential characteristics with missed HIV care visits. METHODS: Medical record and patient-reported outcome (PRO; including mental health and substance-use measures) data were drawn from 7 participating Center for AIDS Research Network of Integrated Clinical Systems (CNICS) sites including N = 20 807 PWH from January 2010 through December 2015. Generalized estimating equations were used to account for nesting within individuals and within census tracts in multivariable models assessing the relationship between race and missed HIV care visits, controlling for individual demographic and health characteristics and census tract characteristics. RESULTS: Black PWH resided in more disadvantaged census tracts, on average. Black PWH residing in census tracts with higher proportion of Black residents were more likely to miss an HIV care visit. Non-Black PWH were less likely to miss a visit regardless of where they lived. These relationships were attenuated when PRO data were included. CONCLUSIONS: Residential racial segregation and disadvantage may create inequities between Black PWH and non-Black PWH in retention in HIV care. Multilevel approaches are needed to retain PWH in HIV care, accounting for community, healthcare setting, and individual needs and resources.

Cryptococcal Meningitis and Clinical Outcomes in Persons With Human Immunodeficiency Virus: A Global View.

BACKGROUND: Cryptococcal meningitis (CM) is a major cause of morbidity and mortality in persons with human immunodeficiency virus (HIV; PWH). Little is known about CM outcomes and availability of diagnostic and treatment modalities globally. METHODS: In this retrospective cohort study, we investigated CM incidence and all-cause mortality in PWH in the International Epidemiology Databases to Evaluate AIDS cohort from 1996 to 2017. We estimated incidence using quasi-Poisson models adjusted for sex, age, calendar year, CD4 cell count (CD4), and antiretroviral therapy (ART) status. Mortality after CM diagnosis was examined using multivariable Cox models. A site survey from 2017 assessed availability of CM diagnostic and treatment modalities. RESULTS: Among 518 852 PWH, there were 3857 cases of CM with an estimated incidence of 1.54 per 1000 person-years. Mortality over a median of 2.6 years of post-CM diagnosis follow-up was 31.6%, with 29% lost to follow-up. In total, 2478 (64%) were diagnosed with CM after ART start with a median of 253 days from ART start to CM diagnosis. Older age (hazard [HR], 1.31 for 50 vs 35 years), lower CD4 (HR, 1.15 for 200 vs 350 cells/mm3), and earlier year of CM diagnosis (HR, 0.51 for 2015 vs 2000) were associated with higher mortality. Of 89 sites, 34% reported access to amphotericin B; 12% had access to flucytosine. CONCLUSIONS: Mortality after CM diagnosis was high. A substantial portion of CM cases occurred after ART start, though incidence and mortality may be higher than reported due to ascertainment bias. Many sites lacked access to recommended CM treatment.

Multiwave validation sampling for error-prone electronic health records.

Electronic health record (EHR) data are increasingly used for biomedical research, but these data have recognized data quality challenges. Data validation is necessary to use EHR data with confidence, but limited resources typically make complete data validation impossible. Using EHR data, we illustrate prospective, multiwave, two-phase validation sampling to estimate the association between maternal weight gain during pregnancy and the risks of her child developing obesity or asthma. The optimal validation sampling design depends on the unknown efficient influence functions of regression coefficients of interest. In the first wave of our multiwave validation design, we estimate the influence function using the unvalidated (phase 1) data to determine our validation sample; then in subsequent waves, we re-estimate the influence function using validated (phase 2) data and update our sampling. For efficiency, estimation combines obesity and asthma sampling frames while calibrating sampling weights using generalized raking. We validated 996 of 10,335 mother-child EHR dyads in six sampling waves. Estimated associations between childhood obesity/asthma and maternal weight gain, as well as other covariates, are compared to naïve estimates that only use unvalidated data. In some cases, estimates markedly differ, underscoring the importance of efficient validation sampling to obtain accurate estimates incorporating validated data.

Correlated depressive symptoms within seroconcordant, expectant partners living with HIV in Zambézia Province, Mozambique: a cross-sectional study.

Approximately 15% of people with HIV in sub-Saharan Africa have comorbid depression, which impacts treatment outcomes. We describe predictors of baseline depressive symptoms in 1079 female and 1079 male participants in a cluster-randomized trial in Zambézia Province, Mozambique from November 2017 to December 2020. We modeled each partners' depressive symptoms (Patient Health Questionnaire-9 [PHQ-9]) using proportional odds models adjusted for enrollment date, age, body mass index [BMI], partner's PHQ-9 score, district, relationship status, education, occupation, WHO HIV clinical stage, and antiretroviral therapy use history. A post hoc analysis assessed covariate-adjusted rank correlation between partner depressive symptoms. Females were younger than males (median 23 vs. 28 years) and more likely to report no education (20.7% vs. 7.9%). Approximately 10% screened positive for depression (PHQ-9 score ≥ 10). Partner depressive symptoms were predictive of higher participant PHQ-9 scores. A male partner PHQ-9 score of 10 (versus 5) increased the odds that the female partner would have a higher PHQ-9 score (adjusted odds ratio: 7.25, 95% Confidence Interval [CI]: 5.43-9.67). Partner PHQ-9 scores were highly correlated after covariate adjustment (Spearman's rho 0.65, 95% CI 0.57-0.72). Interventions aimed to reduce depressive symptoms and improve HIV-related outcomes during pregnancy should address both partners' depressive symptoms.

The Vanderbilt Nigeria Biostatistics Training Program (VN-BioStat): Results from a Skills Workshop.

The Vanderbilt-Nigeria Biostatistics Training Program (VN-BioStat) aims to establish a research and training platform for biostatisticians doing HIV-related research in Nigeria, including enhancing mid-level biostatistics capacity through annual workshops. This paper describes findings from the inaugural workshop in Kano, Nigeria. Participants were surveyed before and after the workshop to assess their self-perceived familiarity with and confidence in their abilities to use statistical software and apply specific statistical techniques, as well as to gather feedback regarding the conduct of the workshop and future topic areas. Of the 23 participants enrolled in the workshop, 22 (96%) completed both pre- and post-workshop assessments. In both pre-workshop and post-workshop surveys, participants ranked their confidence in statistical skills using Likert scales. Scores were transformed to a 0-100 scale, and averages computed. Participants also shared open-ended feedback about the workshop and suggested future topic areas. Before the training, the average participant reported having either a "beginner" (30% of participants) or "moderate" (43%) level of familiarity with R. Many participants (65%) rated themselves as having "moderate" or "expert" familiarity with SPSS. Pre-workshop averages for confidence ranged from 26 to 64, with lowest confidence in "expanding continuous covariates in regression models and interpret results" and highest confidence in "fitting and interpreting results from a linear regression model". Post-workshop averages for confidence were all above 70. The lowest post-workshop score (74) was for "fit and interpret results from a semiparametric linear transformation model". The greatest increase in confidence was observed in "expanding continuous covariates in regression models using splines and interpreting results" and the lowest increase was in "fitting and interpreting results from a linear regression model." Participants offered positive feedback on instructor effectiveness (4.9/5) and overall course quality (4.9/5). While the overall course was rated on a 0-100 scale as "moderately difficult" (mean ± SD: 40.5 ± 17.5), the participants felt the course was highly organized (87.7 ± 17.8), and the information was moderately easy to learn (81.9 ± 15.9). Suggestions for future workshops included providing supplementary resources for out-of-classroom learning and releasing codes in advance to enhance participants' preparation. Among suggestions for future workshop topics, 80% of respondents listed survival analysis. Lessons learned provide insight into how short-term training opportunities can be leveraged to build biostatistics capacity in similar settings.

Asymptotic Properties for Cumulative Probability Models for Continuous Outcomes.

Regression models for continuous outcomes frequently require a transformation of the outcome, which is often specified a priori or estimated from a parametric family. Cumulative probability models (CPMs) nonparametrically estimate the transformation by treating the continuous outcome as if it is ordered categorically. They thus represent a flexible analysis approach for continuous outcomes. However, it is difficult to establish asymptotic properties for CPMs due to the potentially unbounded range of the transformation. Here we show asymptotic properties for CPMs when applied to slightly modified data where bounds, one lower and one upper, are chosen and the outcomes outside the bounds are set as two ordinal categories. We prove the uniform consistency of the estimated regression coefficients and of the estimated transformation function between the bounds. We also describe their joint asymptotic distribution, and show that the estimated regression coefficients attain the semiparametric efficiency bound. We show with simulations that results from this approach and those from using the CPM on the original data are very similar when a small fraction of the data are modified. We reanalyze a dataset of HIV-positive patients with CPMs to illustrate and compare the approaches.

Mean Coronary Cross-Sectional Area as a Measure of Arterial Remodeling Using Noncontrast CT Imaging in Persons With HIV.

Background Persons with HIV have a higher prevalence of coronary artery disease compared with their HIV-negative counterparts. Earlier identification of subclinical atherosclerosis may provide a greater opportunity for cardiovascular disease risk reduction. We investigated coronary cross-sectional area (CorCSA) by noncontrasted computed tomography imaging as a noninvasive measure of arterial remodeling among virally suppressed persons with HIV. Methods and Results We assessed 105 persons with HIV with a spectrum of cardiometabolic health. All participants underwent computed tomography imaging to assess the mean corCSA of the proximal left anterior descending artery and 28 participants underwent additional coronary computed tomography angiography. Partial Spearman rank correlations adjusted for cardiovascular disease risk factors were used to assess relationships of corCSA with anthropometric measurements, HIV-related factors, and plasma cytokines. Mean corCSA measured by noncontrast computed tomography and coronary computed tomography angiography were strongly correlated (ρ=0.91, P<0.0001). Higher mean corCSA was present in those with coronary artery calcium (P=0.005) and it correlated with participants' atherosclerotic cardiovascular disease risk score (ρ=0.35, P=0.01). After adjusting for established cardiovascular disease risk factors, we observed an inverse relationship between corCSA and CD4+ T-cell count (ρ=-0.2, P=0.047). Removal of age from the model strengthened the relationships between corCSA and antiretroviral therapy duration (from ρ=0.19, P=0.08 to ρ=0.3, P=0.01). CorCSA was also inversely correlated with plasma IL-10 (ρ=-0.25, P=0.03) but had no relationship with IL-6 (ρ=0.11, P=0.4) or IL-1ß (ρ=0.08, P=0.5). Conclusions Positive coronary arterial remodeling, an imaging marker of subclinical atherosclerosis, is associated with a lower CD4 T-cell count, lower circulating IL-10, and possibly a longer antiretroviral therapy duration in persons with HIV. Registration Clinicaltrials.gov; Unique identifier: NCT04451980.