ArticleBiostatistics (Oxford, England)2015
A discrete-time survival model with random effects for designing and analyzing repeated low-dose challenge experiments.
Article in Biostatistics (Oxford, England), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Optimal designs for discrete-time survival models with random effects.Lifetime data analysis · 2021Article
- The role of specialized hospital units in infection and mortality risk reduction among patients with hematological cancers.PloS one · 2019Article
- A method to address between-subject heterogeneity for identification of principal surrogate markers in repeated low-dose challenge HIV vaccine studies.Statistics in medicine · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Repeated low-dose (RLD) challenge designs are important in HIV vaccine research. Current methods for RLD designs rely heavily on an assumption of homogeneous risk of infection among animals, which, upon violation, can lead to invalid inferences and underpowered study designs. We propose to fit a discrete-time survival model with random effects that allows for heterogeneity in the risk of infection among animals and allows for predetermined challenge dose changes over time. Based on this model, we derive likelihood ratio tests and estimators for vaccine efficacy. A two-stage approach is proposed for optimizing the RLD design under cost constraints. Simulation studies demonstrate good finite sample properties of the proposed method and its superior performance compared to existing methods. We illustrate the application of the heterogeneous infection risk model on data from a real simian immunodeficiency virus vaccine study using Rhesus Macaques. The results of our study provide useful guidance for future RLD experimental design.
Indexed as
Identifiers
What OpenQuestion holds
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.