Evidence map›Paper›PMID 31821541›Full record

ArticleCancer2020

Reply to Appropriate considerations of "rural" in National Cancer Data Base analyses.

John Virostko, Anna Capasso, Thomas E Yankeelov, Boone Goodgame

Abstract readLetterComment
PubMed Full text at PMC Publisher
In one paragraph

Article in Cancer, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

John VirostkoDepartments of Diagnostic Medicine and Oncology and LIVESTRONG Cancer Institutes, University of Texas at Austin, Austin, Texas.ORCID 0000-0003-3413-8801
Anna CapassoDepartment of Oncology and LIVESTRONG Cancer Institutes, University of Texas at Austin, Austin, Texas.
Thomas E YankeelovDepartments of Diagnostic Medicine, Oncology, and Biomedical Engineering, LIVESTRONG Cancer Institutes, and Institute for Computational Engineering and Sciences, University of Texas at Austin, Austin, Texas.
Boone GoodgameDepartments of Oncology and Internal Medicine and LIVESTRONG Cancer Institutes, University of Texas at Austin, Austin, Texas.ORCID 0000-0003-3199-6544

Funding

Quantitative MRI for Predicting Response of Breast Cancer to Neoadjuvant TherapyU01CA142565 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI KARCZMAR, GREGORY S., NANDA, RITA · 2010 to 2019
$4.5M
Image Driven Multi-Scale Modeling to Predict Treatment Response in Breast CancerU01CA174706 · NCI · VANDERBILT UNIVERSITY · PI QUARANTA, VITO, YANKEELOV, THOMAS E · 2013 to 2018
$2.5M
Integrating Quantitative Imaging and Biophysical Models to Predict Tumor GrowthR21CA169387 · NCI · VANDERBILT UNIVERSITY · PI YANKEELOV, THOMAS E · 2013 to 2014
$368k
NCI NIH HHS R21 CA169387NCI NIH HHS U01 CA142565NCI NIH HHS U01 CA174706
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

Colorectal NeoplasmsData ManagementHumansRural Population

Identifiers

PMID31821541
PMCPMC7069778

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.