Evidence map›Paper›PMID 37521002›Full record

ArticleThe annals of applied statistics2022

AN OMNIBUS TEST FOR DETECTION OF SUBGROUP TREATMENT EFFECTS VIA DATA PARTITIONING.

Yifei Sun, Xuming He, Jianhua Hu

Open access · greenAbstract read
In one paragraph

Article in The annals of applied statistics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.5field-weighted citation impact, top 33% of its field
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 1 country.

Yifei SunDepartment of Biostatistics, Columbia University.
Xuming HeDepartment of Statistics, University of Michigan.
Jianhua HuDepartment of Biostatistics, Columbia University.
Columbia University · USUniversity of Michigan–Ann Arbor · US

Funding

Tumor Biology and Microenvironment ProgramP30CA013696 · NCI · COLUMBIA UNIV NEW YORK MORNINGSIDE · PI Parisa Tehranifar · 1985 to 2026
$115.3M
Project 2 MeasurementU19AG033655 · NIA · JOHNS HOPKINS UNIVERSITY · PI Abhay Moghekar · 2014 to 2026
$51.5M
Transformed Esophageal Epithelial Cells and the Tumor MicroenvironmentP01CA098101 · NCI · UNIVERSITY OF PENNSYLVANIA · PI NAKAGAWA, HIROSHI · 2003 to 2023
$31.7M
Biomarkers of Cognitive Decline among Normal Individuals: The BIOCARD cohortU01AG033655 · NIA · JOHNS HOPKINS UNIVERSITY · PI ALBERT, MARILYN S. · 2009 to 2013
$11.2M
(PQ10) Enhancing responses to immune checkpoint blockade in melanoma via modulation of the microbiomeR01CA219896 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI WARGO, JENNIFER A. · 2018 to 2022
$2.2M
Novel analysis of association between microbiome and treatment infection in AMLR01AI143886 · NIAID · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI HU, JIANHUA · 2019 to 2023
$2.0M
NCI NIH HHS P01 CA098101NCI NIH HHS P30 CA013696NCI NIH HHS R01 CA219896NIAID NIH HHS R01 AI143886NIA NIH HHS U01 AG033655NIA NIH HHS U19 AG033655
6 · The paper itself

Abstract

Late-stage clinical trials have been conducted primarily to establish the efficacy of a new treatment in an intended population. A corollary of population heterogeneity in clinical trials is that a treatment might be effective for one or more subgroups, rather than for the whole population of interest. As an example, the phase III clinical trial of panitumumab in metastatic colorectal cancer patients failed to demonstrate its efficacy in the overall population, but a subgroup associated with tumor KRAS status was found to be promising (Peeters et al. (

Indexed as

Bootstrapclinical trialsdata partitioninghigh-dimensional covariatessubgroup treatment effect

Identifiers

PMID37521002
PMCPMC10381789
OpenAlexW4297333769

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.