Time-dependent Cox regression and landmarking are the two most commonly used approaches for the analysis of time-dependent covariates in time-to-event data. The estimated effect of the time-dependent covariate in a landmarking analysis is based on the value of the time-dependent covariate at the landmark time point, after which the time-dependent covariate may change value. In this note we derive expressions for the (time-varying) regression coefficient of the time-dependent covariate in the landmark analysis, in terms of the regression coefficient and baseline hazard of the time-dependent Cox regression. These relations are illustrated using simulation studies and using the Stanford heart transplant data.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5711994 | PMC |
| http://dx.doi.org/10.1007/s12561-016-9157-9 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Psoas Muscle Index as an Independent Predictor of Survival in Patients with Hepatocellular Carcinoma Receiving Systemic Targeted Therapy.
Cancers (Basel)
January 2025
Department of Gastroenterology and internal Medicine, Graduate School of Medicine, Gifu University, 1-1 Yanagido, Gifu 501-1194, Japan.
Background: This study aimed to investigate the usefulness of the psoas muscle index (PMI) as an independent predictor of survival after systemic targeted therapy initiation in patients with hepatocellular carcinoma (HCC).
Method: In total, 214 patients with HCC who underwent systemic targeted therapy at the Gifu University Hospital were enrolled. The correlation between the PMI and the skeletal muscle index (SMI) was assessed using Pearson's correlation coefficient (PCC).
Quantitative Pupillometry Predicts Neurologic Deterioration in Patients with Large Middle Cerebral Artery Stroke.
Ann Neurol
January 2025
Department of Neurology, Boston Medical Center and Boston University Chobanian and Avedisian School of Medicine, Boston, MA, USA.
Objective: This study assesses whether longitudinal quantitative pupillometry predicts neurological deterioration after large middle cerebral artery (MCA) stroke and determines how early changes are detectable.
Methods: This prospective, single-center observational cohort study included patients with large MCA stroke admitted to Boston Medical Center's intensive care unit (2019-2024). Associations between time-to-neurologic deterioration and quantitative pupillometry, including Neurological Pupil Index (NPi), were assessed using Cox proportional hazards models with time-dependent covariates adjusted for age, sex, and Alberta Stroke Program Early CT Score.
Population pharmacokinetics and exposure-response analysis of durvalumab in combination with gemcitabine and cisplatin in patients with advanced biliary tract cancer.
Cancer Chemother Pharmacol
January 2025
Clinical Pharmacology & Quantitative Pharmacology, BioPharmaceuticals R&D, AstraZeneca, Waltham, MA, USA.
Purpose: Durvalumab in combination with gemcitabine/cisplatin has shown a favorable benefit-risk profile in the TOPAZ-1 study for advanced biliary tract cancers (BTC). This analysis evaluated the population pharmacokinetics (PopPK) of durvalumab, and exposure-response for efficacy and safety (ERES) of TOPAZ-1.
Methods: The PopPK model for durvalumab was updated using data from 5 previously analysed studies and TOPAZ-1.
Esophageal Candida Infection and Esophageal Cancer Risk in Patients With Achalasia.
JAMA Netw Open
January 2025
Department of Gastroenterology and Hepatology, Erasmus University Medical Center, Rotterdam, the Netherlands.
Importance: Patients with achalasia face a higher risk of developing esophageal cancer (EC), but the surveillance strategies for these patients remain controversial due to the long disease duration and the lack of identified risk factors.
Objective: To investigate the prevalence of esophageal Candida infection among patients with achalasia and to assess the association of Candida infection with EC risk within this population.
Design, Setting, And Participants: This retrospective cohort study included patients with achalasia diagnosed at or referred for treatment and monitoring to the Erasmus University Medical Center in Rotterdam, the Netherlands, between January 1, 1980, and May 31, 2024.
tdCoxSNN: Time-dependent Cox survival neural network for continuous-time dynamic prediction.
J R Stat Soc Ser C Appl Stat
January 2025
Department of Biostatistics and Health Data Science, School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA.
The aim of dynamic prediction is to provide individualized risk predictions over time, which are updated as new data become available. In pursuit of constructing a dynamic prediction model for a progressive eye disorder, age-related macular degeneration (AMD), we propose a time-dependent Cox survival neural network (tdCoxSNN) to predict its progression using longitudinal fundus images. tdCoxSNN builds upon the time-dependent Cox model by utilizing a neural network to capture the nonlinear effect of time-dependent covariates on the survival outcome.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!