This article presents an overview of statistical methods for the analysis of discrete failure
times with competing events. We describe the most commonly used modeling approaches …

Background External validation of prognostic models is necessary to assess the accuracy
and generalizability of the model to new patients. If models are validated in a setting in …

Background: The global COVID-19 epidemic remains severe, with the cumulative global
death toll reaching more than 207,170 as of May 2, 2020. Purpose: Our research objective is …

We aimed to evaluate the external performance of prediction models for all-cause dementia
or AD in the general population, which can aid selection of high-risk individuals for clinical …

Event prediction is the ability of anticipating future events, ie, future real-world occurrences,
and aims to support the user in deciding on actions that change future events towards a …

Background Prognostic models are becoming increasingly relevant in clinical trials as
potential surrogate endpoints, and for patient management as clinical decision support tools …

Elderly patients are at a high risk of suffering from postoperative death. Personalized
strategies to improve their recovery after intervention are therefore urgently needed. A …

In this article, we present the development of the proportional odds hazard model for
discrete time-to-event data. In this work, inferences about the model's parameters were …

Background Hemorrhagic fever with renal syndrome (HFRS) is a zoonotic disease caused
by hantavirus infection. Patients with severe HFRS may develop multiple organ failure or …

Evaluating risk factors for mortality in local populations such as adult patients admitted on
mechanical ventilation in intensive care units (ICU) may provide support for the …