STATISTICAL METHODS FOR DATA FROM CASE-COHORT STUDIES

In epidemiological studies and disease prevention trials, interest often lies in the relationship between certain disease endpoint and some exposure of interest. When the event is rare and/or some of the covariate information are quite expensive to collect for the entire cohort, case-cohort designs are widely used to reduce the financial cost of the study while achieving the same study goals. The case-cohort sampling scheme entails the random sampling of individuals, called the sub-cohort, along with all the cases. In the situation when the event rate is not low but resources are limited, the generalized case-cohort design is more appropriate, where only a fraction of cases are sampled along with the sub-cohort. In this dissertation, we consider two aspects of case-cohort studies. One is for statistical methods for the analysis of recurrent events and the other concerns power/sample size calculation for interaction test. Many methods for the analysis of data from case-cohort studies have been proposed in the literature. However, most of these methods are for either a single event or multitude of events of different types on the same subject. There has not been much work on the recurrent events data under case-cohort sampling scheme. Valid statistical methods that take into account the correlation between the events from the same individual needs to be developed. In this dissertation, the first two topics are related to recurrent events. We consider modeling the recurrent events using the rate model under the original and generalized case-cohort designs. The first topic considers the multiplicative rates model and the second topic considers additive rates models. For both types of the rate models, we propose weighted estimating equation approach for the parameter estimates for both sampling designs. We showed that the proposed estimators are consistent and asymptotically normally distributed. We conducted simulation studies to examine the performance of our proposed estimators in finite samples and they performed well. For the multiplicative rates model, we illustrated the proposed method to assess the relationship between prior measles infection and acute lower-respiratory-infections (ALRI) in a double-blinded randomized clinical trial, conducted in Brazil. We illustrated our proposed method for additive rates model to study the effect of FEV1 on the recurrence of pulmonary exacerbation in patients with cystic fibrosis. In the third topic, we address another aspect of the case-cohort design. All the previous work in the literature concern sample size and power calculation in case-cohort data for a dichotomized main effect. However, in certain situations, one might be interested in the association of a covariate and time to event response in different biomarker groups, which may be expensive to measure. We extend the existing idea for the single binary main effect to the interaction between the variable and the dichotomized biomarker in the presence of a rare event. We propose different power formulas based on the simplification of a generalized log-rank test for the case-cohort design. A cost efficiency formula comparing the case-cohort design to a simple random sample is derived. We examine the performance of the bounds based on the same test. Simulation studies are conducted to illustrate the efficiency for the case-cohort design. We illustrate the use of the formula based on information from the pooled databases of Lung Adjuvant Cisplatin Evaluation (LACE) and Cancer and Leukemia Group B (CALGB) 9633.Doctor of Philosoph

Round Efficient Byzantine Agreement from VDFs

Byzantine agreement (BA) is a fundamental primitive in distributed systems and has received huge interest as an important building block for blockchain systems. Classical byzantine agreement considers a setting where $n$ parties with fixed, known identities want to agree on an output in the presence of an adversary. Motivated by blockchain systems, the assumption of fixed identities is weakened by using a \emph{resource-based model}. In such models, parties do not have fixed known identities but instead have to invest some expensive resources to participate in the protocol. Prominent examples for such resources are computation (measured by, e.g., proofs-of-work) or money (measured by proofs-of-stake). Unlike in the classical setting where BA without trusted setup (e.g., a PKI or an unpredictable beacon) is impossible for $t \geq n/3$ corruptions, in such resource-based models, BA can be constructed for the optimal threshold of $t <n/2$. In this work, we investigate BA without a PKI in the model where parties have restricted computational resources. Concretely, we consider sequential computation modeled via computing a verifiable delay function (VDF) and establish the following results: Positive Result: We present the first protocol for BA with expected constant round complexity and termination under adaptive corruption, honest majority and without a PKI. Earlier work achieved round complexity $O(n\kappa^2)$ (CRYPTO\u2715) or $O(\kappa)$ (PKC\u2718), where $\kappa$ is the security parameter. Negative Result: We give the first lower bound on the communication complexity of BA in a model where parties have restricted computational resources. Concretely, we show that a multicast complexity of $O(\sqrt{n})$ is necessary even if the parties have access to a VDF oracle

Risk factors for mortality in adult patients with sickle cell disease: a meta-analysis of studies in North America and Europe

Although recent studies show an improved survival of children with sickle cell disease in the US and Europe, for adult patients mortality remains high. This study was conducted to evaluate the factors associated with mortality in adult patients following the approval of hydroxyurea. We first evaluated the association between selected variables and mortality at an academic center (University of North Carolina). Data sources were then searched for publications from 1998 to June 2016, with meta-analysis of eligible studies conducted in North America and Europe to evaluate the associations of selected variables with mortality in adult patients. Nine studies, combined with the UNC cohort (total n=3257 patients) met the eligibility criteria. Mortality was significantly associated with age (per 10-year increase in age) [7 studies, 2306 participants; hazard ratio (HR): 1.28; 95% confidence interval (CI): 1.10–1.50], tricuspid regurgitant jet velocity 2.5 m/s or more (5 studies, 1577 participants; HR: 3.03; 95%CI: 2.0–4.60), reticulocyte count (3 studies, 1050 participants; HR: 1.05; 95%CI: 1.01–1.10), log(N-terminal-pro-brain natriuretic peptide) (3 studies, 800 participants; HR: 1.68; 95%CI: 1.48–1.90), and fetal hemoglobin (7 studies, 2477 participants; HR: 0.97; 95%CI: 0.94–1.0). This study identifies variables associated with mortality in adult patients with sickle cell disease in the hydroxyurea era

Albuminuria Is Associated with Endothelial Dysfunction and Elevated Plasma Endothelin-1 in Sickle Cell Anemia

The pathogenesis of albuminuria in SCD remains incompletely understood. We evaluated the association of albuminuria with measures of endothelial function, and explored associations of both albuminuria and measures of endothelial function with selected biological variables (vascular endothelial growth factor [VEGF], endothelin-1 [ET-1], soluble fms-like tyrosine kinase-1 [sFLT-1], soluble vascular cell adhesion molecule-1 [soluble VCAM-1] and plasma hemoglobin)

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

Albuminuria Is Associated with Endothelial Dysfunction and Elevated Plasma Endothelin-1 in Sickle Cell Anemia.

BACKGROUND:The pathogenesis of albuminuria in SCD remains incompletely understood. We evaluated the association of albuminuria with measures of endothelial function, and explored associations of both albuminuria and measures of endothelial function with selected biological variables (vascular endothelial growth factor [VEGF], endothelin-1 [ET-1], soluble fms-like tyrosine kinase-1 [sFLT-1], soluble vascular cell adhesion molecule-1 [soluble VCAM-1] and plasma hemoglobin). METHODS:Spot urine measurements for albumin-creatinine ratio (UACR) and 24-hour urine protein were obtained. Endothelial function was assessed using brachial artery ultrasound with measurements of flow-mediated dilation (FMD), nitroglycerin-mediated dilation (NTMD) and hyperemic velocity. RESULTS:Twenty three subjects with varying degrees of albuminuria were evaluated. UACR was significantly correlated with FMD (ρ = -0.45, p = 0.031). In univariate analysis, UACR was correlated with VEGF (ρ = -0.49; 95% CI: -0.75 --0.1, p = 0.015), plasma hemoglobin (ρ = 0.50; 95% CI: 0.11-0.75, p = 0.013) and ET-1 (ρ = 0.40; 95% CI: -0.03-0.69, p = 0.06). Multivariable analysis showed significant associations of ET-1 (estimate: 455.1 [SE: 198.3], p = 0.02), VEGF (estimate: -1.1 [SE: 0.53], p = 0.04) and sFLT-1 (estimate: -1.14 [SE: 0.49], p = 0.02) with UACR. Only ET-1 (estimate: -8.03 [SE: 3.87], p = 0.04) was significantly associated with FMD in multivariable analyses. Finally, UACR was correlated with both 24-hour urine protein (ρ = 0.90, p < 0.0001) and urine aliquots for albumin-creatinine ratio obtained from the 24-hour urine collection (ρ = 0.97, p < 0.0001). CONCLUSION:This study provides more definitive evidence for the association of albuminuria with endothelial dysfunction in SCD. Elevated circulating levels of ET-1 may contribute to SCD-related glomerulopathy by mediating endothelial dysfunction

Scatter Plot and Regression Line Between Spot Urine Albumin-Creatinine Ratio and Urine Aliquot for Albumin-Creatinine Ratio: Urine albumin-creatinine ratio assessed by spot albumin-creatinine ratio is strongly correlated with urine aliquots for albumin-creatinine ratio obtained from the 24-hour urine collection (ρ = 0.97; 95% CI: 0.92–0.99, p < 0.0001).

<p>Scatter Plot and Regression Line Between Spot Urine Albumin-Creatinine Ratio and Urine Aliquot for Albumin-Creatinine Ratio: Urine albumin-creatinine ratio assessed by spot albumin-creatinine ratio is strongly correlated with urine aliquots for albumin-creatinine ratio obtained from the 24-hour urine collection (ρ = 0.97; 95% CI: 0.92–0.99, p < 0.0001).</p

Values of Measures of Endothelial Function Based on Albuminuria Category.

<p>Values of Measures of Endothelial Function Based on Albuminuria Category.</p

Scatter Plot and Regression Line Between Flow-Mediated Dilation and Albuminuria in Sickle Cell Anemia: Urine albumin-creatinine ratio is significantly correlated with FMD (ρ = -0.45; 95% CI: -0.72 –-0.04, p = 0.031).

<p>Scatter Plot and Regression Line Between Flow-Mediated Dilation and Albuminuria in Sickle Cell Anemia: Urine albumin-creatinine ratio is significantly correlated with FMD (ρ = -0.45; 95% CI: -0.72 –-0.04, p = 0.031).</p