Cumulative All-Cause Mortality in Diverse Hispanic/Latino Adults : A Prospective, Multicenter Cohort Study.

BACKGROUND: All-cause mortality among diverse Hispanic/Latino groups in the United States and factors underlying mortality differences have not been examined prospectively. OBJECTIVE: To describe cumulative all-cause mortality (and factors underlying differences) by Hispanic/Latino background, before and during the COVID-19 pandemic. DESIGN: Prospective, multicenter cohort study. SETTING: Hispanic Community Health Study/Study of Latinos. PARTICIPANTS: 15 568 adults aged 18 to 74 years at baseline (2008 to 2011) of Central American, Cuban, Dominican, Mexican, Puerto Rican, South American, and other backgrounds from the Bronx, New York; Chicago, Illinois; Miami, Florida; and San Diego, California. MEASUREMENTS: Sociodemographic, acculturation-related, lifestyle, and clinical factors were assessed at baseline, and vital status was ascertained through December 2021 (969 deaths; 173 444 person-years of follow-up). Marginally adjusted cumulative all-cause mortality risks (11-year before the pandemic and 2-year during the pandemic) were examined using progressively adjusted Cox regression. RESULTS: Before the pandemic, 11-year cumulative mortality risks adjusted for age and sex were higher in the Puerto Rican and Cuban groups (6.3% [95% CI, 5.2% to 7.6%] and 5.7% [CI, 5.0% to 6.6%], respectively) and lowest in the South American group (2.4% [CI, 1.7% to 3.5%]). Differences were attenuated with adjustment for lifestyle and clinical factors. During the pandemic, 2-year cumulative mortality risks adjusted for age and sex ranged from 1.1% (CI, 0.6% to 2.0%; South American) to 2.0% (CI, 1.4% to 3.0%; Central American); CIs overlapped across groups. With adjustment for lifestyle factors, 2-year cumulative mortality risks were highest in persons of Central American and Mexican backgrounds and lowest among those of Puerto Rican and Cuban backgrounds. LIMITATION: Lack of data on race and baseline citizenship status; correlation between Hispanic/Latino background and site. CONCLUSION: Differences in prepandemic mortality risks across Hispanic/Latino groups were explained by lifestyle and clinical factors. Mortality patterns changed during the pandemic, with higher risks in persons of Central American and Mexican backgrounds than in those of Puerto Rican and Cuban backgrounds. PRIMARY FUNDING SOURCE: National Institutes of Health.

Persistent albuminuria and chronic kidney disease in adults with sickle cell anaemia: Results from a multicenter natural history study.

Clinical and laboratory correlates of chronic kidney disease (CKD) in sickle cell anaemia remain incompletely defined. In a multicenter cohort study, we evaluated the prevalence of persistent albuminuria (PA) and characteristics associated with PA, albumin-creatinine ratio (ACR) and decreased estimated glomerular filtration rate (eGFR) using logistic, linear and multinomial regression models, respectively. Of 269 participants (median age: 30 years; 57.2% females), the prevalence of PA was 35.7%. Using baseline ACR values of <100 and ≥100 mg/g, the probabilities of PA were 30.0% and 94.6%, respectively. In multivariable logistic regression analyses, male sex (ß = 0.80 [SE = 0.36], p = 0.024) and ACE inhibitors/ARBs use (ß = 1.54 [SE = 0.43], p < 0.001) were associated with higher likelihoods of PA, while higher haemoglobin (ß = -0.33 [SE = 0.13], p = 0.009) and HbF (ß = -0.04 [SE = 0.02], p = 0.041) were associated with lower likelihoods of PA. In multivariable multinomial regression analyses, older age (ß = 0.06 [SE = 0.02], p = 0.004) and higher alkaline phosphatase (ß = 0.01 [SE = 0.00], p = 0.004) were associated with higher odds of having eGFR 60-90 versus eGFR>90 mL/min/1.73 m2 using the cystatin C-based CKD-EPI-2012 equation. Additionally, higher systolic blood pressure (ß = 0.11 [SE = 0.03], p = 0.001) and blood urea nitrogen (ß = 0.45 [SE = 0.12], p < 0.001) were associated with higher odds, while higher haemoglobin (ß = -1.22 [SE = 0.43], p = 0.004) was associated with lower odds of having eGFR<60 versus eGFR>90 mL/min/1.73 m2. PA and decreased eGFR are associated with measures of disease severity and comorbid conditions (Clinicaltrials.gov Identifier: NCT03277547).

Association of biomarkers of endothelial function, coagulation activation and kidney injury with persistent albuminuria in sickle cell anaemia.

Persistent albuminuria (PA) is common in sickle cell anaemia (SCA). With the association of chronic kidney disease (CKD) with increased mortality, biomarkers that predict its development or progression are needed. We evaluated the association of select biomarkers with PA in adults with SCA using Kruskal-Wallis rank-sum test and logistic regression models, with adjustment for multiple testing. Of 280 subjects, 100 (35.7%) had PA. Median plasma levels of soluble vascular cell adhesion molecule-1 (VCAM-1) (1176.3 vs. 953.4 ng/mL, false discovery rate [FDR] q-value <0.003), thrombin-antithrombin complex (5.5 vs. 4.7 ng/mL, FDR q-value = 0.04), and urinary angiotensinogen (AGT) (12.2 vs. 5.3 ng/mg, FDR q-value <0.003), urinary nephrin (30.6 vs. 27.2 ng/mg, FDR q-value = 0.04), and urinary kidney injury molecule-1 (KIM-1) (0.8 vs. 0.5 ng/mg, FDR q-value <0.003), normalized to urine creatinine, were significantly higher in subjects with PA. In multivariable analysis, only urinary AGT (odds ratio = 1.058, FDR q-value <0.0001) remained a significant predictor of PA. In addition, soluble VCAM-1 (FDR q-value <0.0001), D-dimer (FDR q-value <0.0001), urinary AGT (FDR q-value <0.0001), KIM-1 (FDR q-value <0.0001), and nephrin (FDR q-value <0.0001) were significantly associated with urine albumin-creatinine ratio in multivariable analyses. Longitudinal studies to evaluate the predictive capacity of biomarkers for the development and progression of CKD in SCA are warranted.

Efficient estimation for left-truncated competing risks regression for case-cohort studies.

The case-cohort study design provides a cost-effective study design for a large cohort study with competing risk outcomes. The proportional subdistribution hazards model is widely used to estimate direct covariate effects on the cumulative incidence function for competing risk data. In biomedical studies, left truncation often occurs and brings extra challenges to the analysis. Existing inverse probability weighting methods for case-cohort studies with competing risk data not only have not addressed left truncation, but also are inefficient in regression parameter estimation for fully observed covariates. We propose an augmented inverse probability-weighted estimating equation for left-truncated competing risk data to address these limitations of the current literature. We further propose a more efficient estimator when extra information from the other causes is available. The proposed estimators are consistent and asymptotically normally distributed. Simulation studies show that the proposed estimator is unbiased and leads to estimation efficiency gain in the regression parameter estimation. We analyze the Atherosclerosis Risk in Communities study data using the proposed methods.

Associations of Anxiety Symptoms With 6-Year Blood Pressure Changes and Incident Hypertension: Results From the Hispanic Community Health Study/Study of Latinos.

BACKGROUND: Despite the high burden of anxiety and hypertension in Hispanic/Latino adults, little is known about their association in this population. PURPOSE: To examine the associations of anxiety symptoms with 6-year changes in blood pressure (BP) and incident hypertension in Hispanic/Latino adults. METHODS: We examined data from a probability sample of 10,881 Hispanic/Latino persons aged 18-74 who attended visits 1 (V1; 2008-2011) and 2 (V2; 2014-2017) of the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), a prospective cohort study. Anxiety symptoms were assessed at V1 using the 10-item Spielberger Trait Anxiety Scale (M = 17.1; Range = 10-40) and dichotomized using a cut-point of 20, the highest quartile in this cohort. BP was measured at both visits using a standardized protocol. RESULTS: Adults with elevated anxiety symptoms had a 1.02 mm Hg greater increase in systolic (p = .02) and a 0.75 mm Hg greater increase in diastolic BP (p = .02) over 6.1 years than those with lower symptoms, after adjusting for sociodemographic and clinical covariates. These associations differed by sex. Elevated anxiety was associated with a greater increase in systolic and diastolic BP in men only. Among persons without hypertension at V1 (N = 7,412), those with elevated anxiety symptoms at V1 had a 22% higher incidence of hypertension (p = .02) 6.1 years later. CONCLUSIONS: Our findings underscore the importance of screening for and treating elevated anxiety symptoms to help prevent hypertension. Further research on the role of sex and underlying mechanisms is warranted.

This study investigated the relationship between anxiety symptoms and changes in blood pressure, as well as the incidence of hypertension among Hispanic/Latino adults over time. Using data from 10,881 Hispanic/Latino adults who participated in the Hispanic Community Health Study/Study of Latinos, we found that men, but not women, with elevated anxiety symptoms experienced a greater increase in both systolic and diastolic blood pressure over a 6-year period compared to those with lower symptoms. Additionally, among 7,412 participants who were free of hypertension at baseline, individuals with elevated anxiety symptoms developed hypertension at a higher rate after 6 years of follow-up compared to those with lower symptoms. These findings suggest that anxiety symptoms play a role in the development of hypertension among Hispanic/Latino adults, underscoring the importance of screening for and addressing elevated anxiety to potentially prevent hypertension.

Improved mortality prediction for pediatric acute liver failure using dynamic prediction strategy.

OBJECTIVES: To develop and validate a prediction tool for pediatric acute liver failure (PALF) mortality risks that captures the rapid and heterogeneous clinical course for accurate and updated prediction. METHODS: Data included 1144 participants with PALF enrolled during three phases of the PALF registry study over 15 years. Using joint modeling, we built a dynamic prediction tool for mortality by combining longitudinal trajectories of multiple laboratory and clinical variables. The predictive performance for 7-day and 21-day mortality was assessed using the area under curve (AUC) through cross-validation and split-by-time validation. RESULTS: We constructed a prognostic joint model that combines the temporal trajectories of international normalized ratio, total bilirubin, hepatic encephalopathy, platelet count, and serum creatinine. Dynamic prediction using updated information improved predictive performance over static prediction using the information at enrollment (Day 0) only. In cross-validation, AUC increased from 0.784 to 0.887 when measurements obtained between Days 1 and 2 were incorporated. AUC remained similar when we used the earlier subset of the sample for training and the later subset for testing. CONCLUSIONS: Serial measurements of five variables in the first few days of PALF capture the dynamic clinical course of the disease and improve risk prediction for mortality. Continuous disease monitoring and updating risk prognosis are beneficial for timely and judicious medical decisions.

Dynamic risk score modeling for multiple longitudinal risk factors and survival.

Modeling disease risk and survival using longitudinal risk factor trajectories is of interest in various clinical scenarios. The capacity to build a prognostic model using the trajectories of multiple longitudinal risk factors, in the presence of potential dependent censoring, would enable more informed, personalized decision making. A dynamic risk score modeling framework is proposed for multiple longitudinal risk factors and survival in the presence of dependent censoring, where both events depend on participants' post-baseline clinical progression and form a competing risks structure. The model requires relatively few random effects regardless of the number of longitudinal risk factors and can therefore accommodate multiple longitudinal risk factors in a parsimonious manner. The proposed method performed satisfactorily in extensive simulation studies. It is further applied to the motivating registry study on pediatric acute liver failure to model death using the trajectories of multiple clinical and biochemical markers. Once established, the model yields an easily calculable longitudinal risk score that can be used for disease monitoring among future patients.

Sleep duration and brain MRI measures: Results from the SOL-INCA MRI study.

INTRODUCTION: Sleep duration has been associated with dementia and stroke. Few studies have evaluated sleep pattern-related outcomes of brain disease in diverse Hispanics/Latinos. METHODS: The SOL-INCA (Study of Latinos-Investigation of Neurocognitive Aging) magnetic resonance imaging (MRI) study recruited diverse Hispanics/Latinos (35-85 years) who underwent neuroimaging. The main exposure was self-reported sleep duration. Our main outcomes were total and regional brain volumes. RESULTS: The final analytic sample included n = 2334 participants. Increased sleep was associated with smaller brain volume (ßtotal_brain  = -0.05, p < 0.01) and consistently so in the 50+ subpopulation even after adjusting for mild cognitive impairment status. Sleeping >9 hours was associated with smaller gray (ßcombined_gray  = -0.17, p < 0.05) and occipital matter volumes (ßoccipital_gray  = -0.18, p < 0.05). DISCUSSION: We found that longer sleep duration was associated with lower total brain and gray matter volume among diverse Hispanics/Latinos across sex and background. These results reinforce the importance of sleep on brain aging in this understudied population. HIGHLIGHTS: Longer sleep was linked to smaller total brain and gray matter volumes. Longer sleep duration was linked to larger white matter hyperintensities (WMHs) and smaller hippocampal volume in an obstructive sleep apnea (OSA) risk group. These associations were consistent across sex and Hispanic/Latino heritage groups.

Collectrin (Tmem27) deficiency in proximal tubules causes hypertension in mice and a TMEM27 variant associates with blood pressure in males in a Latino cohort.

Collectrin (Tmem27), an angiotensin-converting enzyme 2 homologue, is a chaperone of amino acid transporters in the kidney and endothelium. Global collectrin knockout (KO) mice have hypertension, endothelial dysfunction, exaggerated salt sensitivity, and diminished renal blood flow. This phenotype is associated with altered nitric oxide and superoxide balance and increased proximal tubule (PT) Na+/H+ exchanger isoform 3 (NHE3) expression. Collectrin is located on the X chromosome where genome-wide association population studies have largely been excluded. In the present study, we generated PT-specific collectrin KO (PT KO) mice to determine the precise contribution of PT collectrin in blood pressure homeostasis. We also examined the association of human TMEM27 single-nucleotide polymorphisms with blood pressure traits in 11,926 Hispanic Community Health Study/Study of Latinos (HCHS/SOL) Hispanic/Latino participants. PT KO mice exhibited hypertension, and this was associated with increased baseline NHE3 expression and diminished lithium excretion. However, PT KO mice did not display exaggerated salt sensitivity or a reduction in renal blood flow compared with control mice. Furthermore, PT KO mice exhibited enhanced endothelium-mediated dilation, suggesting a compensatory response to systemic hypertension induced by deficiency of collectrin in the PT. In HCHS/SOL participants, we observed sex-specific single-nucleotide polymorphism associations with diastolic blood pressure. In conclusion, loss of collectrin in the PT is sufficient to induce hypertension, at least in part, through activation of NHE3. Importantly, our model supports the notion that altered renal blood flow may be a determining factor for salt sensitivity. Further studies are needed to investigate the role of the TMEM27 locus on blood pressure and salt sensitivity in humans.NEW & NOTEWORTHY The findings of our study are significant in several ways: 1) loss of an amino acid chaperone in the proximal tubule is sufficient to cause hypertension, 2) the results in global and proximal tubule-specific collectrin knockout mice support the notion that vascular dysfunction is required for salt sensitivity or that impaired renal tubule function causes hypertension but is not sufficient to cause salt sensitivity, and 3) our study is the first to implicate a role of collectrin in human hypertension.

Childhood and Life-Course Socioeconomic Position and Cognitive Function in the Adult Population of the Hispanic Community Health Study/Study of Latinos.

The Hispanic/Latino population experiences socioeconomic adversities across the lifespan and is at greater risk of cognitive impairment, yet little is known about the role of life-course socioeconomic position (SEP) in cognitive function in this population. Using baseline data (2008-2011) from adults (aged 45-74 years) of the Hispanic Community Health Study/Study of Latinos, we assessed the association between childhood SEP and socioeconomic mobility with cognitive function, and whether this association was mediated by midlife SEP. Childhood SEP was assessed using parental education. An index combining participants' education and household income represented midlife SEP. Socioeconomic mobility was categorized as stable low, downward or upward mobility, and stable high-SEP. Cognitive function measures were modeled using survey linear regression with inverse-probability weighting, accounting for covariates. We used mediation analysis to estimate the indirect effect of childhood SEP on cognition through midlife SEP. High childhood SEP was associated with global cognition in adulthood (coefficient for parental education beyond high school vs. less than high school = 0.26, 95% confidence interval: 0.15, 0.37). This association was partially mediated through midlife SEP (indirect effect coefficient = 0.16, 95% confidence interval: 0.15, 0.18). Low SEP through the life course was associated with the lowest cognitive function. This study provides evidence that life-course SEP influences cognitive performance in adulthood.

Time to cancer treatment and reproductive outcomes after fertility preservation among adolescent and young adult women with cancer.

BACKGROUND: Fertility preservation (FP) may be underused after cancer diagnosis because of uncertainty around delays to cancer treatment and subsequent reproductive success. METHODS: Women aged 15 to 39 years diagnosed with cancer between 2004 and 2015 were identified from the North Carolina Central Cancer Registry. Use of assisted reproductive technology (ART) after cancer diagnosis between 2004 and 2018 (including FP) was assessed through linkage to the Society for Assisted Reproductive Technology. Linear regression was used to examine time to cancer treatment among women who did (n = 95) or did not (n = 469) use FP. Modified Poisson regression was used to estimate risk ratios (RRs) and 95% CIs for pregnancy and birth based on timing of ART initiation relative to cancer treatment (n = 18 initiated before treatment for FP vs n = 26 initiated after treatment without FP). RESULTS: The median time to cancer treatment was 9 to 33 days longer among women who used FP compared with women who did not, matched on clinical factors. Women who initiated ART before cancer treatment may be more likely to have a live birth given pregnancy compared with women who initiated ART after cancer treatment (age-adjusted RR, 1.47; 95% CI, 0.98-2.23), though this may be affected by the more frequent use of gestational carriers in the former group (47% vs 20% of transfer cycles, respectively). CONCLUSIONS: FP delayed gonadotoxic cancer treatment by up to 4.5 weeks, a delay that would not be expected to alter prognosis for many women. Further study of the use of gestational carriers in cancer populations is warranted to better understand its effect on reproductive outcomes.

A Genome-wide Association Study Discovers 46 Loci of the Human Metabolome in the Hispanic Community Health Study/Study of Latinos.

Variation in levels of the human metabolome reflect changes in homeostasis, providing a window into health and disease. The genetic impact on circulating metabolites in Hispanics, a population with high cardiometabolic disease burden, is largely unknown. We conducted genome-wide association analyses on 640 circulating metabolites in 3,926 Hispanic Community Health Study/Study of Latinos participants. The estimated heritability for 640 metabolites ranged between 0%-54% with a median at 2.5%. We discovered 46 variant-metabolite pairs (p value < 1.2 × 10-10, minor allele frequency ≥ 1%, proportion of variance explained [PEV] mean = 3.4%, PEVrange = 1%-22%) with generalized effects in two population-based studies and confirmed 301 known locus-metabolite associations. Half of the identified variants with generalized effect were located in genes, including five nonsynonymous variants. We identified co-localization with the expression quantitative trait loci at 105 discovered and 151 known loci-metabolites sets. rs5855544, upstream of SLC51A, was associated with higher levels of three steroid sulfates and co-localized with expression levels of SLC51A in several tissues. Mendelian randomization (MR) analysis identified several metabolites associated with coronary heart disease (CHD) and type 2 diabetes. For example, two variants located in or near CYP4F2 (rs2108622 and rs79400241, respectively), involved in vitamin E metabolism, were associated with the levels of octadecanedioate and vitamin E metabolites (gamma-CEHC and gamma-CEHC glucuronide); MR analysis showed that genetically high levels of these metabolites were associated with lower odds of CHD. Our findings document the genetic architecture of circulating metabolites in an underrepresented Hispanic/Latino community, shedding light on disease etiology.

A Gene-Acculturation Study of Obesity Among US Hispanic/Latinos: The Hispanic Community Health Study/Study of Latinos.

OBJECTIVE: In the United States, Hispanic/Latino adults face a high burden of obesity; yet, not all individuals are equally affected, partly due in part to this ethnic group's marked sociocultural diversity. We sought to analyze the modification of body mass index (BMI) genetic effects in Hispanic/Latino adults by their level of acculturation, a complex biosocial phenomenon that remains understudied. METHODS: Among 11,747 Hispanic/Latinos adults in the Hispanic Community Health Study/Study of Latinos aged 18 to 76 years from four urban communities (2008-2011), we a) tested our hypothesis that the effect of a genetic risk score (GRS) for increased BMI may be exacerbated by higher levels of acculturation and b) examined if GRS acculturation interactions varied by gender or Hispanic/Latino background group. All genetic modeling controlled for relatedness, age, gender, principal components of ancestry, center, and complex study design within a generalized estimated equation framework. RESULTS: We observed a GRS increase of 0.34 kg/m 2 per risk allele in weighted mean BMI. The estimated main effect of GRS on BMI varied both across acculturation level and across gender. The difference between high and low acculturation ranged from 0.03 to 0.23 kg/m 2 per risk allele, but varied across acculturation measure and gender. CONCLUSIONS: These results suggest the presence of effect modification by acculturation, with stronger effects on BMI among highly acculturated individuals and female immigrants. Future studies of obesity in the Hispanic/Latino community should account for sociocultural environments and consider their intersection with gender to better target obesity interventions.

Risk Factors for Cardiovascular Disease: Knowledge Gained from the Hispanic Community Health Study/Study of Latinos.

PURPOSE OF REVIEW: The Hispanic Community Health Study/Study of Latinos (HCHS/SOL) has made important contributions on the prevalence of and factors associated with cardiovascular disease (CVD) risk factors among diverse Hispanic/Latino adults in the US. This article summarizes the knowledge gained thus far on major CVD risk factors from this landmark study. RECENT FINDINGS: HCHS/SOL demonstrated the sizeable burdens of CVD risk in all major Hispanic/Latino groups in the US, as well as the marked variations in prevalence of hypertension, hypercholesterolemia, diabetes, obesity, and smoking by sex and background. It also identified sociodemographic, lifestyle, and sociocultural characteristics associated with risk factors. HCHS/SOL has yielded an expanding body of literature on characteristics associated with adverse CVD risk factors in this population. Long-term follow-up of this cohort will shed further light on the observed heterogeneity in CVD risk across Hispanic/Latino groups and identify specific risk/protective factors driving these variations.

Estimated quadratic inference function for correlated failure time data.

An estimated quadratic inference function method is proposed for correlated failure time data with auxiliary covariates. The proposed method makes efficient use of the auxiliary information for the incomplete exposure covariates and preserves the property of the quadratic inference function method that requires the covariates to be completely observed. It can improve the estimation efficiency and easily deal with the situation when the cluster size is large. The proposed estimator which minimizes the estimated quadratic inference function is shown to be consistent and asymptotically normal. A chi-squared test based on the estimated quadratic inference function is proposed to test hypotheses about the regression parameters. The small-sample performance of the proposed method is investigated through extensive simulation studies. The proposed method is then applied to analyze the Study of Left Ventricular Dysfunction (SOLVD) data as an illustration.

Additive subdistribution hazards regression for competing risks data in case-cohort studies.

In survival data analysis, a competing risk is an event whose occurrence precludes or alters the chance of the occurrence of the primary event of interest. In large cohort studies with long-term follow-up, there are often competing risks. Further, if the event of interest is rare in such large studies, the case-cohort study design is widely used to reduce the cost and achieve the same efficiency as a cohort study. The conventional additive hazards modeling for competing risks data in case-cohort studies involves the cause-specific hazard function, under which direct assessment of covariate effects on the cumulative incidence function, or the subdistribution, is not possible. In this paper, we consider an additive hazard model for the subdistribution of a competing risk in case-cohort studies. We propose estimating equations based on inverse probability weighting methods for the estimation of the model parameters. Consistency and asymptotic normality of the proposed estimators are established. The performance of the proposed methods in finite samples is examined through simulation studies and the proposed approach is applied to a case-cohort dataset from the Sister Study.

Improving trial generalizability using observational studies.

Complementary features of randomized controlled trials (RCTs) and observational studies (OSs) can be used jointly to estimate the average treatment effect of a target population. We propose a calibration weighting estimator that enforces the covariate balance between the RCT and OS, therefore improving the trial-based estimator's generalizability. Exploiting semiparametric efficiency theory, we propose a doubly robust augmented calibration weighting estimator that achieves the efficiency bound derived under the identification assumptions. A nonparametric sieve method is provided as an alternative to the parametric approach, which enables the robust approximation of the nuisance functions and data-adaptive selection of outcome predictors for calibration. We establish asymptotic results and confirm the finite sample performances of the proposed estimators by simulation experiments and an application on the estimation of the treatment effect of adjuvant chemotherapy for early-stage non-small-cell lung patients after surgery.

Nonparametric estimation of marked survival data in the presence of dependent censoring.

We consider nonparametrically estimating the joint distribution of a survival time and mark variable, where the survival time is subject to right censoring and the mark variable is only observed when the survival time is not censored. The possibility of dependent censoring is allowed for using inverse probability of censoring weights. The proposed estimator is shown to be consistent and asymptotically normal. Finite sample behavior of the proposed methods are investigated via simulation study. Finally, we illustrate the nonparametric estimator from a recent HIV vaccine efficacy trial.

Modeling longitudinal change in biomarkers using data from a complex survey sampling design: An application to the Hispanic Community Health Study/Study of Latinos.

In observational cohort studies, there is frequently interest in modeling longitudinal change in a biomarker (ie, physiological measure indicative of metabolic dysregulation or disease; eg, blood pressure) in the absence of treatment (ie, medication), and its association with modifiable risk factors expected to affect health (eg, body mass index). However, individuals may start treatment during the study period, and consequently biomarker values observed while on treatment may be different than those that would have been observed in the absence of treatment. If treated individuals are excluded from analysis, then effect estimates may be biased if treated individuals differ systematically from untreated individuals. We addressed this concern in the setting of the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), an observational cohort study that employed a complex survey sampling design to enable inference to a finite target population. We considered biomarker values measured while on treatment to be missing data, and applied missing data methodology (inverse probability weighting (IPW) and doubly robust estimation) to this problem. The proposed methods leverage information collected between study visits on when individuals started treatment, by adapting IPW and doubly robust approaches to model the treatment mechanism using survival analysis methods. This methodology also incorporates sampling weights and uses a bootstrap approach to estimate standard errors accounting for the complex survey sampling design. We investigated variance estimation for these methods, conducted simulation studies to assess statistical performance in finite samples, and applied the methodology to model temporal change in blood pressure in HCHS/SOL.

Comparisons of statistical methods for handling attrition in a follow-up visit with complex survey sampling.

Design-based analysis, which accounts for the design features of the study, is commonly used to conduct data analysis in studies with complex survey sampling, such as the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). In this type of longitudinal study, attrition has often been a problem. Although there have been various statistical approaches proposed to handle attrition, such as inverse probability weighting (IPW), non-response cell weighting (NRCW), multiple imputation (MI), and full information maximum likelihood (FIML) approach, there has not been a systematic assessment of these methods to compare their performance in design-based analyses. In this article, we perform extensive simulation studies and compare the performance of different missing data methods in linear and generalized linear population models, and under different missing data mechanism. We find that the design-based analysis is able to produce valid estimation and statistical inference when the missing data are handled appropriately using IPW, NRCW, MI, or FIML approach under missing-completely-at-random or missing-at-random missing mechanism and when the missingness model is correctly specified or over-specified. We also illustrate the use of these methods using data from HCHS/SOL.