ArticleJournal of statistical planning and inference2020
A single-index model with multiple-links.
Article in Journal of statistical planning and inference, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05025787 (EN20-01), which is not on this map. Cited by 4 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.
EN20-01: A 24 Week Study to Evaluate the Safety and Efficacy of CNTX-6970 in Subjects With Moderate to Severe Knee Osteoarthritis Pain.
Who cites it
4 citing papers in PubMed.
- A Single Index Model for Longitudinal Outcomes to Optimize Individual Treatment Decision Rules.Stat · 2022Article
- Development and Validation of a Treatment Benefit Index to Identify Hospitalized Patients With COVID-19 Who May Benefit From Convalescent Plasma.JAMA network open · 2022Article
- A constrained single-index regression for estimating interactions between a treatment and covariates.Biometrics · 2021Article
- Optimising treatment decision rules through generated effect modifiers: a precision medicine tutorial.BJPsych open · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
In a regression model for treatment outcome in a randomized clinical trial, a treatment effect modifier is a covariate that has an interaction with the treatment variable, implying that the treatment efficacies vary across values of such a covariate. In this paper, we present a method for determining a composite variable from a set of baseline covariates, that can have a nonlinear association with the treatment outcome, and acts as a composite treatment effect modifier. We introduce a parsimonious generalization of the
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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.