Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao ZENODOarrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
ZENODO
Dataset . 2021
Data sources: Datacite
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
ZENODO
Dataset . 2021
Data sources: Datacite
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
ZENODO
Dataset . 2021
Data sources: ZENODO
versions View all 2 versions
addClaim

Dataset related to article "Risk of Covert Submucosal Cancer in Patients With Granular Mixed Laterally Spreading Tumors"

Authors: Ferdinando D'Amico; Amaldo Amato; Andrea Iannone; Cristina Trovato; Chiara Romana; Stefano Angeletti; Roberta Maselli; +21 Authors

Dataset related to article "Risk of Covert Submucosal Cancer in Patients With Granular Mixed Laterally Spreading Tumors"

Abstract

This record contains raw data related to article “Risk of Covert Submucosal Cancer in Patients With Granular Mixed Laterally Spreading Tumors" Background and aims: Granular mixed laterally spreading tumors (GM-LSTs) have an intermediate level of risk for submucosal invasive cancer (SMICs) without clear signs of invasion (covert); the optimal resection method is uncertain. We aimed to determine the risk of covert SMIC in GM-LSTs based on clinical and endoscopic factors. Methods: We collected data from 693 patients (50.6% male; median age, 69 years) with colorectal GM-LSTs, without signs of invasion, who underwent endoscopic resection (74.2%) or endoscopic submucosal dissection (25.2%) at 7 centers in Italy from 2016 through 2019. We performed multivariate and univariate analyses to identify demographic and endoscopic factors associated with risk of SMIC. We developed a multivariate model to calculate the number needed to treat (NNT) to detect 1 SMIC. Results: Based on pathology analysis, 66 patients (9.5%) had covert SMIC. In multivariate analyses, increased risk of covert SMIC were independently associated with increasing lesion size (odds ratio per mm increase, 1.02, 95% CI, 1.01-1.03; P = .003) and rectal location (odds ratio, 2.85; 95% CI, 1.48-5.48; P = .012). A logistic regression model based on lesion size (with a cutoff of 40 mm) and rectal location identified patients with covert SMIC with 47.0% sensitivity, 82.6% specificity, and an area under the curve of 0.69. The NNT to identify 1 patient with a rectal SMIC smaller than 4 cm was 20; the NNT to identify 1 patient with a rectal SMIC of 4 cm or more was 5. Conclusions: In an analysis of data from 693 patients, we found the risk of covert SMIC in patients with GM-LSTs to be approximately 10%. GM-LSTs of 4 cm or more and a rectal location are high risk and should be treated by en-bloc resection. ClinicalTrials.gov, Number: NCT03836131.

Keywords

Colon Cancer, Prognostic Factor, Stratification, Outcome

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
    OpenAIRE UsageCounts
    Usage byUsageCounts
    visibility views 3
  • 3
    views
    Powered byOpenAIRE UsageCounts
Powered by OpenAIRE graph
Found an issue? Give us feedback
visibility
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
0
Average
Average
Average
3
Related to Research communities
Cancer Research