ArticleBiometrics2021
A constrained single-index regression for estimating interactions between a treatment and covariates.
Article in Biometrics, 2021. 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 5 papers, 1 of them a synthesis that pooled it.
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
5 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Prospective individual patient data meta-analysis: Evaluating convalescent plasma for COVID-19.Statistics in medicine · 2021Pooled it
- A sparse additive model for treatment effect-modifier selection.Biostatistics (Oxford, England) · 2022Trial
- Facilitating Heterogeneous Effect Estimation via Statistically Efficient Categorical Modifiers.Journal of the American Statistical Association · 2026Article
- 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 single-index model with a surface-link for optimizing individualized dose rules.Journal of computational and graphical statistics : a joint publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America · 2022Article
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
We consider a single-index regression model, uniquely constrained to estimate interactions between a set of pretreatment covariates and a treatment variable on their effects on a response variable, in the context of analyzing data from randomized clinical trials. We represent interaction effect terms of the model through a set of treatment-specific flexible link functions on a linear combination of the covariates (a single index), subject to the constraint that the expected value given the covariates equals 0, while leaving the main effects of the covariates unspecified. We show that the proposed semiparametric estimator is consistent for the interaction term of the model, and that the efficiency of the estimator can be improved with an augmentation procedure. The proposed single-index regression provides a flexible and interpretable modeling approach to optimizing individualized treatment rules based on patients' data measured at baseline, as illustrated by simulation examples and an application to data from a depression clinical trial.
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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.