Biostatistic

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...

The mean residual lifetime (MRL) of a unit in a population at a given time t , is the average remaining lifetime among those population units still alive at the time t . In some applications, it is reasonable to assume that MRL function is a decreasing function over time. Thus, one natural way to improve the estimation of MRL function is to use this assumption in estimation process. In this paper, we develop an MRL estimator in ranked set sampling (RSS) which, enjoys the monotonicity property. We prove that it is a strongly uniformly consistent estimator of true MRL function...

BACKGROUND: OpenAI's Chat Generative Pre-trained Transformer 4.0 (ChatGPT-4), an emerging artificial intelligence (AI)-based large language model (LLM), has been receiving increasing attention from the medical research community for its innovative 'Data Analyst' feature. We aimed to compare the capabilities of ChatGPT-4 against traditional biostatistical software (i.e. SAS, SPSS, R) in statistically analysing epidemiological research data. METHODS: We used a data set from the China Health and Nutrition Survey, comprising 9317 participants and 29 variables (e...

Immuno-oncology involves the study of approaches which harness the patient's immune system to fight malignancies. Immuno-oncology, as with every other biomedical and clinical research field as well as clinical operations, is in the midst of technological revolutions, which vastly increase the amount of available data. Recent advances in artificial intelligence and machine learning (AI/ML) have received much attention in terms of their potential to harness available data to improve insights and outcomes in many areas including immuno-oncology...

Prediction models are everywhere in clinical medicine. We use them to assign a diagnosis or a prognosis, and there is a continuous effort to develop better prediction models. It is important to understand the fundamentals of prediction modeling, and here we describe nine steps to develop and validate a clinical prediction model with the intention of implementing it in clinical practice: Determine if there is a need for a new prediction model; define the purpose and intended use for the model; assess the quality and quantity of the data you wish to develop the model on; develop the model using sound statistical methods; generate risk predictions on the probability scale (0-100%); evaluate the performance of the model in terms of discrimination, calibration, and clinical utility; validate the model using bootstrapping to correct for the apparent optimism in performance; validate the model on external datasets to assess the generalizability and transportability of the model; and finally publish the model so that it can be implemented or validated by others...

Blood-based diagnostics for lung cancer support the diagnosis, estimation of prognosis, prediction, and monitoring of therapy response in lung cancer patients. The clinical utility of serum tumor markers has considerably increased due to developments in serum protein tumor markers analytics and clinical biomarker studies, the exploration of preanalytical and influencing conditions, the interpretation of biomarker combinations and individual biomarker kinetics, as well as the implementation of biostatistical models...

BACKGROUND: Psychrophilic bacteria can survive in a unique living environment. OBJECTIVE: To explore the mechanism of low temperature adaptation and the physiological function of thermophilic metabolic genes. METHOD: Serratia marcescens strain F13 stored in microbial laboratory was cultured at 5∘C, 10∘C and 25∘C respectively, and the obtained strains were sequenced by high-throughput transcriptome. Serratia marcescens strain CAV1761 was used as the reference strain...

BACKGROUND: Interventional clinical studies conducted in the regulated drug research environment are designed using International Council for Harmonisation (ICH) regulatory guidance documents: ICH E6 (R2) Good Clinical Practice-scientific guideline, first published in 2002 and last updated in 2016. This document provides an international ethical and scientific quality standard for designing and conducting trials that involve the participation of human subjects. Recently, there has been heightened awareness of the importance of integrated research platform trials (IRPs) designed to evaluate multiple therapies simultaneously...

BACKGROUND: Differences in the prognosis after colorectal cancer (CRC) by socioeconomic position (SEP) have been reported previously; however, most studies focused on survival differences at a particular time since diagnosis. We quantified the lifetime impact of CRC and its variation by SEP, using individualised income to conceptualise SEP. METHODS: Data included all adults with a first-time diagnosis of colon or rectal cancers in Sweden between 2008 and 2021. The analysis was done separately for colon and rectal cancers using flexible parametric models...

A large-scale outbreak of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) occurred in Shanghai, China, in early December 2022. To study the incidence and characteristics of otitis media with effusion (OME) complicating SARS-CoV-2, we collected 267 middle ear effusion (MEE) samples and 172 nasopharyngeal (NP) swabs from patients. The SARS-CoV-2 virus was detected by RT-PCR targeting. The SARS-CoV-2 virus, angiotensin-converting enzyme 2 (ACE2), and transmembrane serine protease 2 (TMPRSS2) expression in human samples was examined via immunofluorescence...

A genome, composed of a precisely ordered sequence of four nucleotides (ATCG), encompasses a multitude of specific genome features like AAA motif. Mutations occurring within a genome disrupt the sequential order and composition of these features, thereby influencing the evolutionary trajectories and yielding variants. The evolutionary relatedness between a variant and its ancestor can be estimated by assessing evolutionary distances across a spectrum of genome features. This study develops a novel, alignment-free algorithm that considers both the sequential order and composition of genome features, enabling computation of the Fréchet distance (Fr) across multiple genome features to quantify the evolutionary status of a variant...

BACKGROUND: Doctoral recipients of public health play pivotal roles in the support and leadership of the public health industry and academic research. We conducted this study to assess and track the long-term career outcomes of public health PhDs (PHPhD). METHODS: We linked data from the Survey of Doctorate Recipients to the Survey of Earned Doctorates and tracked the long-term career outcomes and job placements of PHPhD from 2001 to 2017. Logistic regression and ordinary least squares regression models were used to model career outcomes and behavioral characteristics...

Genetic association studies for brain connectivity phenotypes have gained prominence due to advances in noninvasive imaging techniques and quantitative genetics. Brain connectivity traits, characterized by network configurations and unique biological structures, present distinct challenges compared to other quantitative phenotypes. Furthermore, the presence of sample relatedness in the most imaging genetics studies limits the feasibility of adopting existing network-response modeling. In this article, we fill this gap by proposing a Bayesian network-response mixed-effect model that considers a network-variate phenotype and incorporates population structures including pedigrees and unknown sample relatedness...

Biostatistics is foundational to public health research and Canada has a history of high impact contributions both in seminal methodological advances and in the rigorous application of methods for the design or analysis of public health studies. In this article, we provide a brief and personal review of selected contributions from Canadian biostatisticians to fields such as survival and life history analysis, sampling, clinical trial methodology, environmental risk assessment, infectious disease epidemiology, and early work on prediction...

Linear and generalized linear scalar-on-function modeling have been commonly used to understand the relationship between a scalar response variable (e.g. continuous, binary outcomes) and functional predictors. Such techniques are sensitive to model misspecification when the relationship between the response variable and the functional predictors is complex. On the other hand, support vector machines (SVMs) are among the most robust prediction models but do not take account of the high correlations between repeated measurements and cannot be used for irregular data...

INTRODUCTION: Skills in critical appraisal of medical literature are compulsory to achieve in medical practice. This step is the third step of the evidence-based medicine process whose main role is to bridge a gap between scientific evidence and practice. Acquiring skills in critical appraisal of the literature has been reported to be challenging for the trainees with different limits according to their levels, backgrounds or specialties. AIM: To assess the limits and factors influencing the practice of appraising literature of different students from the same faculty...