ArticleThe AAPS journal2017
Kernel-Based Visual Hazard Comparison (kbVHC): a Simulation-Free Diagnostic for Parametric Repeated Time-to-Event Models.
Article in The AAPS journal, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed.
- Reproducibility in pharmacometrics applied in a phase III trial of BCG-vaccination for COVID-19.Scientific reports · 2023Trial
- Impact of Event-Related Treatment Modifications in Exposure-Response Analyses of Repeated Time-to-Event Data.CPT: pharmacometrics & systems pharmacology · 2026Article
- Relationship between Dose, Factor IX Activity Levels and Bleeding Probability for rIX-FP Prophylaxis in Hemophilia B: A Repeated Time-to-Event Analysis.Clinical pharmacology and therapeutics · 2025Article
- Risk Factors for COVID-19 and Respiratory Tract Infections during the Coronavirus Pandemic.Vaccines · 2024Article
- Relationship between factor VIII levels and bleeding for rFVIII-SingleChain in severe hemophilia A: A repeated time-to-event analysis.CPT: pharmacometrics & systems pharmacology · 2023Article
- Finding the right hazard function for time-to-event modeling: A tutorial and Shiny application.CPT: pharmacometrics & systems pharmacology · 2022Article
- Postoperative breakthrough pain in paediatric cardiac surgery not reduced by increased morphine concentrations.Pediatric research · 2021Article
- Covariates in Pharmacometric Repeated Time-to-Event Models: Old and New (Pre)Selection Tools.The AAPS journal · 2018Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Repeated time-to-event (RTTE) models are the preferred method to characterize the repeated occurrence of clinical events. Commonly used diagnostics for parametric RTTE models require representative simulations, which may be difficult to generate in situations with dose titration or informative dropout. Here, we present a novel simulation-free diagnostic tool for parametric RTTE models; the kernel-based visual hazard comparison (kbVHC). The kbVHC aims to evaluate whether the mean predicted hazard rate of a parametric RTTE model is an adequate approximation of the true hazard rate. Because the true hazard rate cannot be directly observed, the predicted hazard is compared to a non-parametric kernel estimator of the hazard rate. With the degree of smoothing of the kernel estimator being determined by its bandwidth, the local kernel bandwidth is set to the lowest value that results in a bootstrap coefficient of variation (CV) of the hazard rate that is equal to or lower than a user-defined target value (CV
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.