Biostatistic

The class of doubly robust (DR) functionals studied by Rotnitzky et al. (2021) is of central importance in economics and biostatistics. It strictly includes both (i) the class of mean-square continuous functionals that can be written as an expectation of an affine functional of a conditional expectation studied by Chernozhukov et al. (2022b) and the class of functionals studied by Robins et al. (2008). The present state-of-the-art estimators for DR functionals <mml:math xmlns:mml="https://www.w3.org/1998/Math/MathML"><mml:mi>ψ</mml:mi></mml:math> are double-machine-learning (DML) estimators (Chernozhukov et al...

There is an increasing interest in the use of joint models for the analysis of longitudinal and survival data. While random effects models have been extensively studied, these models can be hard to implement and the fixed effect regression parameters must be interpreted conditional on the random effects. Copulas provide a useful alternative framework for joint modeling. One advantage of using copulas is that practitioners can directly specify marginal models for the outcomes of interest. We develop a joint model using a Gaussian copula to characterize the association between multivariate longitudinal and survival outcomes...

Few systematic comparisons of methods for constructing survival trees and forests exist in the literature. Importantly, when the goal is to predict a survival time or estimate a survival function, the optimal choice of method is unclear. We use an extensive simulation study to systematically investigate various factors that influence survival forest performance - forest construction method, censoring, sample size, distribution of the response, structure of the linear predictor, and presence of correlated or noisy covariates...

BACKGROUND: A number of recommendations for the teaching of biostatistics have been published to date, however, student opinion on them has not yet been studied. For this reason, the aim of the manuscript was to find out the opinions of medical students at universities in Poland on two forms of teaching biostatistics, namely traditional and practical, as well as to indicate, on the basis of the results obtained, the related educational recommendations. METHODS: The study involved a group of 527 students studying at seven medical faculties in Poland, who were asked to imagine two different courses...

CRISPR genome engineering and single-cell RNA sequencing have accelerated biological discovery. Single-cell CRISPR screens unite these two technologies, linking genetic perturbations in individual cells to changes in gene expression and illuminating regulatory networks underlying diseases. Despite their promise, single-cell CRISPR screens present considerable statistical challenges. We demonstrate through theoretical and real data analyses that a standard method for estimation and inference in single-cell CRISPR screens-"thresholded regression"-exhibits attenuation bias and a bias-variance tradeoff as a function of an intrinsic, challenging-to-select tuning parameter...

The WHO African Region had 81 million people with chronic hepatitis B in 2019, which remains a silent killer. Hepatitis B virus (HBV), hepatitis delta virus (HDV), and HIV can be transmitted from the mother to child. If the HBV infection is acquired at infancy, it may lead to chronic hepatitis B in 90% of the cases. WHO reports that 6.4 million children under 5 years live with chronic hepatitis B infection worldwide. The prevention of mother-to-child transmission (PMTCT) of HBV is therefore critical in the global elimination strategy of viral hepatitis as we take lessons from PMTCT of HIV programs in Africa...

No abstract text is available yet for this article.

Computed tomography (CT) has been a powerful diagnostic tool since its emergence in the 1970s. Using CT data, 3D structures of human internal organs and tissues, such as blood vessels, can be reconstructed using professional software. This 3D reconstruction is crucial for surgical operations and can serve as a vivid medical teaching example. However, traditional 3D reconstruction heavily relies on manual operations, which are time-consuming, subjective, and require substantial experience. To address this problem, we develop a novel semiparametric Gaussian mixture model tailored for the 3D reconstruction of blood vessels...

Impulse noised outliers are data points that differ significantly from other observations. They are generally removed from the data set through local regression or the Kalman filter algorithm. However, these methods, or their generalizations, are not well suited when the number of outliers is of the same order as the number of low-noise data (often called nominal measurement ). In this article, we propose a new model for impulsed noise outliers. It is based on a hierarchical model and a simple linear Gaussian process as with the Kalman Filter...

Despite the increasing relevance of statistics in health sciences, teaching styles in higher education are remarkably similar across disciplines: lectures covering the theory and methods, followed by application and computer exercises in given data sets. This often leads to challenges for students in comprehending fundamental statistical concepts essential for medical research. To address these challenges, we propose an engaging learning approach-DICE (design, interpret, compute, estimate)-aimed at enhancing the learning experience of statistics in public health and epidemiology...

There is an obligation among those teaching epidemiology to incorporate principles of equity, diversity, and inclusion (EDI) into the curriculum. While there is a well-established literature related to teaching epidemiology, this literature rarely addresses critical aspects of EDI. To our knowledge, there is no working group or central point of discussion and learning for incorporating EDI into epidemiology teaching in Canada. To address this gap, we convened a workshop entitled "Incorporating EDI into the epidemiology and biostatistics curriculum and classroom...

BACKGROUND: The One Health (OH) approach recognises that humans, animals, plants, and the environment are interrelated, and therefore seeks to facilitate collaboration, communication, coordination, and capacity building between relevant stakeholders to achieve a healthier ecosystem. This calls for integrating OH into established governance, policy, health, education, and community structures, and requires OH professionals equipped with the necessary inter and trans-disciplinary skillset...

BACKGROUND: Ulcerative colitis (UC) is an immune-mediated chronic inflammatory condition with a worldwide distribution. Although the etiology of this disease is still unknown, the understanding of the role of the microbiota is becoming increasingly strong. AIM: To investigate the predictive power of the gut microbiota for the diagnosis of UC in a cohort of newly diagnosed treatment-naïve Saudi children with UC. METHODS: The study population included 20 children with a confirmed diagnosis of UC and 20 healthy controls...

INTRODUCTION: Influenza, a globally significant respiratory illness with pandemic potential, affects around 1 billion individuals annually, leading to increased risk for severe illness and mortality. Despite recommendations from the WHO Strategic Advisory Group of Experts on Immunization (SAGE) and MoH prioritization, influenza vaccination coverage rate among HCWs in Kyrgyzstan remains low, ranging between 16 % and 46 % over the past five years. Understanding the Knowledge, Attitudes, and Practices (KAP) dynamics of HCWs regarding influenza vaccinations, both before and during the COVID-19 pandemic is crucial for refining national strategies and institutional approaches to enhance vaccination coverage rates in this important risk group...

Many cohort studies in survival analysis have imbedded in them subcohorts consisting of incident cases and prevalent cases. Instead of analysing the data from the incident and prevalent cohorts alone, there are surely advantages to combining the data from these two subcohorts. In this paper, we discuss a survival function nonparametric maximum likelihood estimator (NPMLE) using both length-biased right-censored prevalent cohort data and right-censored incident cohort data. We establish the asymptotic properties of the survival function NPMLE and utilize the NPMLE to estimate the distribution for time spent in a Montreal area hospital...

Individual level models are a class of mechanistic models that are widely used to infer infectious disease transmission dynamics. These models incorporate individual level covariate information accounting for population heterogeneity and are generally fitted in a Bayesian Markov chain Monte Carlo (MCMC) framework. However, Bayesian MCMC methods of inference are computationally expensive for large data sets. This issue becomes more severe when applied to infectious disease data collected from spatially heterogeneous populations, as the number of covariates increases...

No abstract text is available yet for this article.

BACKGROUND: Electronic health records (EHR) are increasingly used for studying multimorbidities. However, concerns about accuracy, completeness, and EHRs being primarily designed for billing and administration raise questions about the consistency and reproducibility of EHR-based multimorbidity research. METHODS: Utilizing phecodes to represent the disease phenome, we analyzed pairwise comorbidity strengths using a dual logistic regression approach and constructed multimorbidity as an undirected weighted graph...

The study of treatment effects is often complicated by noncompliance and missing data. In the one-sided noncompliance setting where of interest are the complier and noncomplier average causal effects, we address outcome missingness of the latent missing at random type (LMAR, also known as latent ignorability). That is, conditional on covariates and treatment assigned, the missingness may depend on compliance type. Within the instrumental variable (IV) approach to noncompliance, methods have been proposed for handling LMAR outcome that additionally invoke an exclusion restriction-type assumption on missingness, but no solution has been proposed for when a non-IV approach is used...

Mediation analysis is appealing for its ability to improve understanding of the mechanistic drivers of causal effects, but real-world data complexities challenge its successful implementation, including (i) the existence of post-exposure variables that also affect mediators and outcomes (thus, confounding the mediator-outcome relationship), that may also be (ii) multivariate, and (iii) the existence of multivariate mediators. All three challenges are present in the mediation analysis we consider here, where our goal is to estimate the indirect effects of receiving a Section 8 housing voucher as a young child on the risk of developing a psychiatric mood disorder in adolescence that operate through mediators related to neighborhood poverty, the school environment, and instability of the neighborhood and school environments, considered together and separately...