Identification of preclinical dementia according to ATN classification for stratified trial recruitment: A machine learning approach.

Introduction: The Amyloid/Tau/Neurodegeneration (ATN) framework was proposed to identify the preclinical biological state of Alzheimer's disease (AD). We investigated whether ATN phenotype can be predicted using routinely collected research cohort data.

Methods: 927 EPAD LCS cohort participants free of dementia or Mild Cognitive Impairment were separated into 5 ATN categories.

Relative Risk of Death in Bulgarian Cancer Patients during the Initial Waves of the COVID-19 Pandemic.

Background: The COVID-19 pandemic has led to millions of documented deaths worldwide, with diverse distribution among countries. Surprisingly, Bulgaria, a middle-income European Union member state, ranked highest in COVID-19 mortality. This study aims to assess whether Bulgarian cancer patients experienced a higher relative risk (RR) of death compared to the general Bulgarian population during the pandemic.

Detection of Alzheimer's Disease Using Logistic Regression and Clock Drawing Errors.

Alzheimer's disease is an incurable disorder that accounts for up to 70% of all dementia cases. While the prevalence of Alzheimer's disease and other types of dementia has increased by more than 160% in the last 30 years, the rates of undetected cases remain critically high. The present work aims to address the underdetection of Alzheimer's disease by proposing four logistic regression models that can be used as a foundation for community-based screening tools that do not require the participation of medical professionals.

Approximate Bayesian computation for the natural history of breast cancer, with application to data from a Milan cohort study.

We explore models for the natural history of breast cancer, where the main events of interest are the start of asymptomatic detectability of the disease (through screening) and the time of symptomatic detection (through symptoms). We develop several parametric specifications based on a cure rate structure, and present the results of the analysis of data collected as part of a motivating study from Milan. Participants in the study were part of a regional breast cancer screening program, and their ten-year trajectories were obtained from administrative data available from the Italian national health care system.

CYP2C19 and CYP2D6 Genotypes and Metabolizer Status Distribution in a Bulgarian Psychiatric Cohort.

CYP2D6 and CYP2C19 are enzymes of essential significance for the pharmacokinetics of a multitude of commonly used antidepressants, antipsychotics, antiemetics, β-blockers, opioids, antiestrogen, antacids, etc. Polymorphisms in the respective genes are well established as resulting in functional differences, which in turn can impact safety and efficacy. Importantly, the prevalence of genetic and variability differs drastically between populations.