ArticleJournal of the Royal Statistical Society. Series A, (Statistics in Society)2024
Grace periods in comparative effectiveness studies of sustained treatments.
Article in Journal of the Royal Statistical Society. Series A, (Statistics in Society), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed.
- Active Monitoring versus Surgical Excision for Atypical Ductal Hyperplasia.Cancer prevention research (Philadelphia, Pa.) · 2026Observational
- Continuing Glucagon-Like Peptide-1 Receptor Agonists Into the First Trimester of Pregnancy and Pregnancy Outcomes : A Target Trial Emulation Study Using Claims Information.Annals of internal medicine · 2026Observational
- Emulation of a Target Trial of Antihypertensive Medications on Weight Change.Journal of general internal medicine · 2026Observational
- Identifying and avoiding design related biases in observational studies using the target trial framework.BMJ medicine · 2026Article
- Demystifying Clone-Censor-Weighting to Studying Treatment Initiation Windows: An Example Using Publicly Available Synthetic Medicare Claims Data.Pharmacoepidemiology and drug safety · 2025Article
- A Review of Causal Inference Methods for Estimating the Effects of Exposure Change When Incident Exposure Is Unobservable.Current epidemiology reports · 2024Article
- A Bayesian framework for causal analysis of recurrent events with timing misalignment.Biometrics · 2024Article
- Synthesizing Subject-matter Expertise for Variable Selection in Causal Effect Estimation: A Case Study.Epidemiology (Cambridge, Mass.) · 2024Article
- Medication-Induced Weight Change Across Common Antidepressant Treatments : A Target Trial Emulation Study.Annals of internal medicine · 2024Observational
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
Researchers are often interested in estimating the effect of sustained use of a treatment on a health outcome. However, adherence to strict treatment protocols can be challenging for individuals in practice and, when non-adherence is expected, estimates of the effect of sustained use may not be useful for decision making. As an alternative, more relaxed treatment protocols which allow for periods of time off treatment (i.e. grace periods) have been considered in pragmatic randomized trials and observational studies. In this article, we consider the interpretation, identification, and estimation of treatment strategies which include grace periods. We contrast
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.