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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

High mortality among patients hospitalized for drug-resistant tuberculosis with acquired second-line drug resistance and high HIV prevalence.

OBJECTIVES: We compared mortality between HIV-positive and HIV-negative South African adults with drug-resistant tuberculosis (DR-TB) and high incidence of acquired second-line drug resistance. METHODS: We performed a retrospective review of DR-TB patients with serial second-line TB drug susceptibility tests (2008-2015) who were hospitalized at a specialized TB hospital. We used Kaplan-Meier analysis and Cox models to examine associations with mortality. RESULTS: Of 245 patients, the median age was 33 years, 54% were male and 40% were HIV-positive, 96% of whom had ever received antiretroviral therapy (ART). At initial drug resistance detection, 99% of patients had resistance to at least rifampicin and isoniazid, and 18% had second-line drug resistance (fluoroquinolones and/or injectable drugs). At later testing, 88% of patients had acquired additional second-line drug resistance. Patient-initiated treatment interruptions (> 2 months) occurred in 47%. Mortality was 79%. Those with HIV had a shorter time to death (p = 0.02; log-rank): median survival time from DR-TB treatment initiation was 2.44 years [95% confidence interval (CI): 2.09-3.15] versus 3.99 years (95% CI: 3.12-4.75) for HIV-negative patients. HIV-positive patients who received ART within 6 months before DR-TB treatment had a higher mortality hazard than HIV-negative patients [adjusted hazard ratio (aHR) ratio = 1.82, 95% CI: 1.21-2.74]. By contrast, HIV-positive patients who did not receive ART within 6 months before DR-TB treatment did not have a significantly higher mortality hazard than HIV-negative patients (aHR = 1.09; 95% CI: 0.72-1.65), although those on ART had lower median CD4 counts than those not on ART (157 vs. 281 cells/µL, respectively; p = 0.02). CONCLUSIONS: A very high incidence of acquired second-line drug resistance and high overall mortality were observed, reinforcing the need to reduce the risk of acquired resistance and for more effective treatment.

The Role of External Genital Lesions in Human Immunodeficiency Virus Seroconversion Among Men Participating in a Multinational Study.

BACKGROUND: Studies in women have shown an increased risk of human immunodeficiency virus (HIV) acquisition with prior human papilloma virus (HPV) infection; however, few studies have been conducted among men. Our objective was to assess whether HPV-related external genital lesions (EGLs) increase risk of HIV seroconversion among men. METHODS: A total of 1379 HIV-negative men aged 18 to 70 years from the United States, Mexico, and Brazil were followed for up to 7 years and underwent clinical examination for EGLs and blood draws every 6 months. Human immunodeficiency virus seroconversion was assessed in archived serum. Cox proportional hazards and marginal structural models assessed the association between EGL status and time to HIV seroconversion. RESULTS: Twenty-nine participants HIV seroconverted during follow-up. Older age was associated with a lower hazard of HIV seroconversion. We found no significant difference in the risk of HIV seroconversion between men with and without EGLs (adjusted hazard ratio, 0.94; 95% confidence interval, 0.32-2.74). Stratified analyses focusing on men that have sex with men found no association between EGLs and HIV seroconversion risk (hazards ratio, 0.63; 95% confidence interval, 0.00-1.86). CONCLUSIONS: External genital lesions were not associated with higher risk for HIV seroconversion in this multinational population, although statistical power was limited as there were few HIV seroconversions. Results may differ in populations at higher risk for HIV.

Nonparametric estimation of Spearman's rank correlation with bivariate survival data.

We study rank-based approaches to estimate the correlation between two right-censored variables. With end-of-study censoring, it is often impossible to nonparametrically identify the complete bivariate survival distribution, and therefore it is impossible to nonparametrically compute Spearman's rank correlation. As a solution, we propose two measures that can be nonparametrically estimated. The first measure is Spearman's correlation in a restricted region. The second measure is Spearman's correlation for an altered but estimable joint distribution. We describe population parameters for these measures and illustrate how they are similar to and different from the overall Spearman's correlation. We propose consistent estimators of these measures and study their performance through simulations. We illustrate our methods with a study assessing the correlation between the time to viral failure and the time to regimen change among persons living with HIV in Latin America who start antiretroviral therapy.

Efficient odds ratio estimation under two-phase sampling using error-prone data from a multi-national HIV research cohort.

Persons living with HIV engage in routine clinical care, generating large amounts of data in observational HIV cohorts. These data are often error-prone, and directly using them in biomedical research could bias estimation and give misleading results. A cost-effective solution is the two-phase design, under which the error-prone variables are observed for all patients during Phase I, and that information is used to select patients for data auditing during Phase II. For example, the Caribbean, Central, and South America network for HIV epidemiology (CCASAnet) selected a random sample from each site for data auditing. Herein, we consider efficient odds ratio estimation with partially audited, error-prone data. We propose a semiparametric approach that uses all information from both phases and accommodates a number of error mechanisms. We allow both the outcome and covariates to be error-prone and these errors to be correlated, and selection of the Phase II sample can depend on Phase I data in an arbitrary manner. We devise a computationally efficient, numerically stable EM algorithm to obtain estimators that are consistent, asymptotically normal, and asymptotically efficient. We demonstrate the advantages of the proposed methods over existing ones through extensive simulations. Finally, we provide applications to the CCASAnet cohort.

Model-assisted analyses of longitudinal, ordinal outcomes with absorbing states.

Studies of critically ill, hospitalized patients often follow participants and characterize daily health status using an ordinal outcome variable. Statistically, longitudinal proportional odds models are a natural choice in these settings since such models can parsimoniously summarize differences across patient groups and over time. However, when one or more of the outcome states is absorbing, the proportional odds assumption for the follow-up time parameter will likely be violated, and more flexible longitudinal models are needed. Motivated by the VIOLET Study (Ginde et al), a parallel-arm, randomized clinical trial of Vitamin D3 in critically ill patients, we discuss and contrast several treatment effect estimands based on time-dependent odds ratio parameters, and we detail contemporary modeling approaches. In VIOLET, the outcome is a four-level ordinal variable where the lowest "not alive" state is absorbing and the highest "at-home" state is nearly absorbing. We discuss flexible extensions of the proportional odds model for longitudinal data that can be used for either model-based inference, where the odds ratio estimator is taken directly from the model fit, or for model-assisted inferences, where heterogeneity across cumulative log odds dichotomizations is modeled and results are summarized to obtain an overall odds ratio estimator. We focus on direct estimation of cumulative probability model (CPM) parameters using likelihood-based analysis procedures that naturally handle absorbing states. We illustrate the modeling procedures, the relative precision of model-based and model-assisted estimators, and the possible differences in the values for which the estimators are consistent through simulations and analysis of the VIOLET Study data.

The Impact of COVID-19 on the HIV Care Continuum in a Large Urban Southern Clinic.

Access to care is essential for people with HIV (PWH) but may have been affected during the COVID-19 pandemic. We conducted a retrospective cross-sectional study of adult PWH receiving care in a large southeastern comprehensive care clinic in the United States. Patients in care between January 1, 2017, and July 30, 2020, were included. Race/ethnicity, sex, HIV-1 RNA, CD4 + lymphocyte count were included as baseline covariates. Outcomes included clinic attendance, receipt of HIV-1 RNA PCR testing, and virologic suppression (HIV-1 RNA < 200 copies/mL); outpatient encounters included new patient encounters, follow-up visits, and mental health encounters. Total medical encounters, including telemedicine, decreased by 827 visits (33%) when comparing the second quarters of 2019 and 2020. New patient encounters decreased by 23.5% from 81 to 62 during this period. The second quarter of 2020 saw the lowest number of new patient visits since 2017. HIV-1 RNA testing and the proportion of patients with virologic suppression decreased during the pandemic (p < 0.001 for both). Total mental health encounters, on the other hand, increased by 14% during April-June 2020 compared to April-June 2019. Mental health electronic communications increased by 60% from 312 to 500 during the same period, with a 20% increase in medication refills. The COVID-19 pandemic affected outpatient visits, viral load surveillance, and virologic suppression but led to an increase in mental health encounters in a comprehensive care clinic setting.

Etiology of Persistent Microalbuminuria in Nigeria (P_MICRO study): protocol and study design.

BACKGROUND: Microalbuminuria is an independent risk factor for cardiovascular and kidney disease and a predictor of end organ damage, both in the general population and in persons with HIV (PWH). Microalbuminuria is also an important risk factor for mortality in PWH treated with antiretroviral therapy (ART). In the ongoing Renal Risk Reduction (R3) study in Nigeria, we identified a high prevalence of microalbuminuria confirmed by two measurements 4-8 weeks apart in ART-experienced, virologically suppressed PWH. Although Stage 1 or 2 hypertension and exposure to potentially nephrotoxic antiretroviral medications were common in R3 participants, other traditional risk factors for albuminuria and kidney disease, including diabetes, APOL1 high-risk genotype, and smoking were rare. Co-infection with endemic pathogens may also be significant contributors to albuminuria, but co-infections were not evaluated in the R3 study population. METHODS: In Aim 1, we will cross-sectionally compare the prevalence of albuminuria and established kidney disease risk factors in a cohort of PWH to age- and sex-matched HIV-negative adults presenting for routine care at the Aminu Kano Teaching Hospital in Kano, Nigeria. We will leverage stored specimens from 2500 R3 participants and enroll an additional 500 PLWH recently initiated on ART (≤ 24 months) and 750 age- and sex-matched HIV-negative adults to determine the contribution of HIV, hypertension, and other comorbid medical conditions to prevalent albuminuria. In Aim 2, we will follow a cohort of 1000 HIV-positive, ART-treated and 500 HIV-negative normoalbuminuric adults for 30 months to evaluate the incidence and predictors of albuminuria. DISCUSSION: The findings from this study will support the development of interventions to prevent or address microalbuminuria in PWH to reduce kidney and cardiovascular morbidity and mortality. Such interventions might include more intensive monitoring and treatment of traditional risk factors, the provision of renin-angiotensin aldosterone system or sodium-glucose cotransporter-2 inhibitors, consideration of changes in ART regimen, and screening and treatment for relevant co-infections.

Tuberculosis treatment intermittency in the continuation phase and mortality in HIV-positive persons receiving antiretroviral therapy.

BACKGROUND: Some tuberculosis (TB) treatment guidelines recommend daily TB treatment in both the intensive and continuation phases of treatment in HIV-positive persons to decrease the risk of relapse and acquired drug resistance. However, guidelines vary across countries, and treatment is given 7, 5, 3, or 2 days/week. The effect of TB treatment intermittency in the continuation phase on mortality in HIV-positive persons on antiretroviral therapy (ART), is not well-described. METHODS: We conducted an observational cohort study among HIV-positive adults treated for TB between 2000 and 2018 and after enrollment into the Caribbean, Central, and South America network for HIV epidemiology (CCASAnet; Brazil, Chile, Haiti, Honduras, Mexico and Peru). All received standard TB therapy (2-month initiation phase of daily isoniazid, rifampin or rifabutin, pyrazinamide ± ethambutol) and continuation phase of isoniazid and rifampin or rifabutin, administered concomitantly with ART. Known timing of ART and TB treatment were also inclusion criteria. Kaplan-Meier and Cox proportional hazards methods compared time to death between groups. Missing model covariates were imputed via multiple imputation. RESULTS: 2303 patients met inclusion criteria: 2003(87%) received TB treatment 5-7 days/week and 300(13%) 2-3 days/week in the continuation phase. Intermittency varied by site: 100% of patients from Brazil and Haiti received continuation phase treatment 5-7 days/week, followed by Honduras (91%), Peru (42%), Mexico (7%), and Chile (0%). The crude risk of death was lower among those receiving treatment 5-7 vs. 2-3 days/week (HR = 0.68; 95% CI = 0.51-0.91; P = 0.008). After adjusting for age, sex, CD4, ART use at TB diagnosis, site of TB disease (pulmonary vs. extrapulmonary), and year of TB diagnosis, mortality risk was lower, but not significantly, among those treated 5-7 days/week vs. 2-3 days/week (HR 0.75, 95%CI 0.55-1.01; P = 0.06). After also stratifying by study site, there was no longer a protective effect (HR 1.42, 95%CI 0.83-2.45; P = 0.20). CONCLUSIONS: TB treatment 5-7 days/week was associated with a marginally decreased risk of death compared to TB treatment 2-3 days/week in the continuation phase in multivariable, unstratified analyses. However, little variation in TB treatment intermittency within country meant the results could have been driven by other differences between study sites. Therefore, randomized trials are needed, especially in heterogenous regions such as Latin America.

Risk of Incident Diabetes Mellitus, Weight Gain, and Their Relationships With Integrase Inhibitor-Based Initial Antiretroviral Therapy Among Persons With Human Immunodeficiency Virus in the United States and Canada.

BACKGROUND: Integrase strand transfer inhibitor (INSTI)-based combination antiretroviral therapy (cART) is associated with greater weight gain among persons with human immunodeficiency virus (HIV), though metabolic consequences, such as diabetes mellitus (DM), are unclear. We examined the impact of initial cART regimen and weight on incident DM in a large North American HIV cohort (NA-ACCORD). METHODS: cART-naive adults (≥18 years) initiating INSTI-, protease inhibitor (PI)-, or nonnucleoside reverse transcriptase inhibitor (NNRTI)-based regimens from January 2007 through December 2017 who had weight measured 12 (±6) months after treatment initiation contributed time until clinical DM, virologic failure, cART regimen switch, administrative close, death, or loss to follow-up. Multivariable Cox regression yielded adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) for incident DM by cART class. Mediation analyses, with 12-month weight as mediator, similarly adjusted for all covariates. RESULTS: Among 22 884 eligible individuals, 47% started NNRTI-, 30% PI-, and 23% INSTI-based cART with median follow-up of 3.0, 2.3, and 1.6 years, respectively. Overall, 722 (3%) developed DM. Persons starting INSTIs vs NNRTIs had incident DM risk (HR, 1.17 [95% CI, .92-1.48]), similar to PI vs NNRTI initiators (HR, 1.27 [95% CI, 1.07-1.51]). This effect was most pronounced for raltegravir (HR, 1.42 [95% CI, 1.06-1.91]) vs NNRTI initiators. The INSTI-DM association was attenuated (HR, 1.03 [95% CI, .71-1.49] vs NNRTIs) when accounting for 12-month weight. CONCLUSIONS: Initiating first cART regimens with INSTIs or PIs vs NNRTIs may confer greater risk of DM, likely mediated through weight gain.