A Semiparametric Two-Sample Density Ratio Model With a Change Point.

The logistic regression model for a binary outcome with a continuous covariate can be expressed equivalently as a two-sample density ratio model for the covariate. Utilizing this equivalence, we study a change-point logistic regression model within the corresponding density ratio modeling framework. We investigate estimation and inference methods for the density ratio model and develop maximal score-type tests to detect the presence of a change point.

Estimation of standardized real-time fatality rate for ongoing epidemics.

Background: The fatality rate is a crucial metric for guiding public health policies during an ongoing epidemic. For COVID-19, the age structure of the confirmed cases changes over time, bringing a substantial impact on the real-time estimation of fatality. A 'spurious decrease' in fatality rate can be caused by a shift in confirmed cases towards younger ages even if the fatalities remain unchanged across different ages.

Partly linear single-index cure models with a nonparametric incidence link function.

In cancer studies, it is commonplace that a fraction of patients participating in the study are , such that not all of them will experience a recurrence, or death due to cancer. Also, it is plausible that some covariates, such as the treatment assigned to the patients or demographic characteristics, could affect both the patients' survival rates and cure/incidence rates. A common approach to accommodate these features in survival analysis is to consider a mixture cure survival model with the incidence rate modeled by a logistic regression model and latency part modeled by the Cox proportional hazards model.

Survival analysis with a random change-point.

Contemporary works in change-point survival models mainly focus on an unknown universal change-point shared by the whole study population. However, in some situations, the change-point is plausibly individual-specific, such as when it corresponds to the telomere length or menopausal age. Also, maximum-likelihood-based inference for the fixed change-point parameter is notoriously complicated.

A semiparametric joint model for cluster size and subunit-specific interval-censored outcomes.

Clustered data frequently arise in biomedical studies, where observations, or subunits, measured within a cluster are associated. The cluster size is said to be informative, if the outcome variable is associated with the number of subunits in a cluster. In most existing work, the informative cluster size issue is handled by marginal approaches based on within-cluster resampling, or cluster-weighted generalized estimating equations.

A novel method to monitor COVID-19 fatality rate in real-time, a key metric to guide public health policy.

An accurate estimator of the real-time fatality rate is warranted to monitor the progress of ongoing epidemics, hence facilitating the policy-making process. However, most of the existing estimators fail to capture the time-varying nature of the fatality rate and are often biased in practice. A simple real-time fatality rate estimator with adjustment for reporting delays is proposed in this paper using the fused lasso technique.

A sequential test to compare the real-time fatality rates of a disease among multiple groups with an application to COVID-19 data.

Infectious diseases, such as the ongoing COVID-19 pandemic, pose a significant threat to public health globally. Fatality rate serves as a key indicator for the effectiveness of potential treatments or interventions. With limited time and understanding of novel emerging epidemics, comparisons of the fatality rates in real-time among different groups, say, divided by treatment, age, or area, have an important role to play in informing public health strategies.

Nested logistic regression models and ΔAUC applications: Change-point analysis.

The area under the receiver operating characteristic curve (AUC) is one of the most popular measures for evaluating the performance of a predictive model. In nested models, the change in AUC (ΔAUC) can be a discriminatory measure of whether the newly added predictors provide significant improvement in terms of predictive accuracy. Recently, several authors have shown rigorously that ΔAUC can be degenerate and its asymptotic distribution is no longer normal when the reduced model is true, but it could be the distribution of a linear combination of some random variables [1,2].

Heterogeneous toroidal spiral particles for islet encapsulation.

Transplantable cell encapsulation systems present a promising approach to deliver a therapeutic solution from hormone-producing cells for the treatment of endocrine diseases like type 1 diabetes. However, the development of a broadly effective and safe transplantation system has been challenging. While some current micro-sized capsules have been optimized for adequate nutrient and metabolic transport, they lack the robustness and retrievability for the clinical safety translation that macro-devices may offer.

Marginal analysis of current status data with informative cluster size using a class of semiparametric transformation cure models.

This research is motivated by a periodontal disease dataset that possesses certain special features. The dataset consists of clustered current status time-to-event observations with large and varying cluster sizes, where the cluster size is associated with the disease outcome. Also, heavy censoring is present in the data even with long follow-up time, suggesting the presence of a cured subpopulation.

Heterogeneous Polymeric Particles Encapsulating Human T cells for Controlled Activation, Proliferation, and Delivery.

We report a particulate cell delivery platform, toroidal spiral particles (TSPs), for continuous cell activation, expansion, and local sustained release. Biocompatible TSPs, generated by a self-assembly process of polymeric droplet sedimentation in an aqueous solution and subsequent polymer solidification, possess many engineering design flexibilities to manipulate the microenvironment of the cells to control cell proliferation, migration, and release kinetics. These millimeter-size particles with desired mechanical and physicochemical properties may be potentially used for adoptive cellular therapy (ACT) delivery by a minimally invasive procedure to the tumor mass.

Analysis of clustered interval-censored data using a class of semiparametric partly linear frailty transformation models.

A flexible class of semiparametric partly linear frailty transformation models is considered for analyzing clustered interval-censored data, which arise naturally in complex diseases and dental research. This class of models features two nonparametric components, resulting in a nonparametric baseline survival function and a potential nonlinear effect of a continuous covariate. The dependence among failure times within a cluster is induced by a shared, unobserved frailty term.

Survival analysis with change-points in covariate effects.

We apply a maximal likelihood ratio test for the presence of multiple change-points in the covariate effects based on the Cox regression model. The covariate effect is assumed to change smoothly at one or more unknown change-points. The number of change-points is inferred by a sequential approach.

Testing for change-point in the covariate effects based on the Cox regression model.

Models with change-point in covariates have wide applications in cancer research with the response being the time to a certain event. A Cox model with change-point in covariate is considered at which the pattern of the change-point effects can be flexibly specified. To test for the existence of the change-point effects, three statistical tests, namely, the maximal score, maximal normalized score, and maximal Wald tests are proposed.

Clinical implications of recent exodontia before diagnosis of gingival squamous cell carcinoma: A new classification.

Background: The purpose of this study was to clarify the clinical implications of cases with recent dental extractions to establish a new classification of gingival squamous cell carcinoma (SCC).

Methods: A total of 156 patients were enrolled in this study. The subjects were divided into 3 groups: type I (dentate; n = 46), type II (edentulous; n = 55), and type III (dental extraction; n = 55).