Timing of onset of menses after GnRH agonist treatment for central precocious puberty.

Objectives: To understand possible predictors of the onset of menses after gonadotropin-releasing hormone agonist treatment cessation in girls with central precocious puberty (CPP).

Methods: This exploratory post hoc analysis of a phase 3 and 4 trial of girls with CPP treated with once-monthly intramuscular leuprolide acetate examined onset of menses after treatment completion using a time-to-event analysis. Pretreatment and end-of-treatment chronologic age (CA), bone age (BA)/CA ratio, and Tanner breast stage; pretreatment menses status; and end-of-treatment BA and body mass index (BMI) were studied as potential factors influencing the onset of menses.

Characterizing attitudes related to future child-bearing in young women diagnosed with early-stage breast cancer.

Purpose: This study characterizes attitudes and decision-making around the desire for future children in young women newly diagnosed with early-stage breast cancer and assesses how clinical factors and perceived risk may impact these attitudes.

Methods: This is a prospective study in women < 45 years with newly diagnosed stage 1-3 breast cancer. Patients completed a REDCap survey on fertility and family-building in the setting of hypothetical risk scenarios.

Impact of COVID-19 containment and closure policies on tropospheric nitrogen dioxide: A global perspective.

The containment and closure policies adopted in attempts to contain the spread of the 2019 coronavirus disease (COVID-19) have impacted nearly every aspect of our lives including the environment we live in. These influences may be observed when evaluating changes in pollutants such as nitrogen dioxide (NO), which is an important indicator for economic, industrial, and other anthropogenic activities. We utilized a data-driven approach to analyze the relationship between tropospheric NO and COVID-19 mitigation measures by clustering regions based on pollution levels rather than constraining the study units by predetermined administrative boundaries as pollution knows no borders.

New Metrics for Assessing the State Performance in Combating the COVID-19 Pandemic.

Previous research has noted that many factors greatly influence the spread of COVID-19. Contrary to explicit factors that are measurable, such as population density, number of medical staff, and the daily test rate, many factors are not directly observable, for instance, culture differences and attitudes toward the disease, which may introduce unobserved heterogeneity. Most contemporary COVID-19 related research has focused on modeling the relationship between explicitly measurable factors and the response variable of interest (such as the infection rate or the death rate).

Phased Implementation of COVID-19 Vaccination: Rapid Assessment of Policy Adoption, Reach and Effectiveness to Protect the Most Vulnerable in the US.

The US and the rest of the world have suffered from the COVID-19 pandemic for over a year. The high transmissibility and severity of this virus have provoked governments to adopt a variety of mitigation strategies. Some of these previous measures, such as social distancing and mask mandates, were effective in reducing the case growth rate yet became economically and administratively difficult to enforce as the pandemic continued.

The Impact of Policy Measures on Human Mobility, COVID-19 Cases, and Mortality in the US: A Spatiotemporal Perspective.

Social distancing policies have been regarded as effective in containing the rapid spread of COVID-19. However, there is a limited understanding of policy effectiveness from a spatiotemporal perspective. This study integrates geographical, demographical, and other key factors into a regression-based event study framework, to assess the effectiveness of seven major policies on human mobility and COVID-19 case growth rates, with a spatiotemporal emphasis.

On symmetric semiparametric two-sample problem.

We consider a two-sample problem where data come from symmetric distributions. Usual two-sample data with only magnitudes recorded, arising from case-control studies or logistic discriminant analyses, may constitute a symmetric two-sample problem. We propose a semiparametric model such that, in addition to symmetry, the log ratio of two unknown density functions is modeled in a known parametric form.