Evidence map›Paper›PMID 31179052›Full record

ArticleJournal of thoracic disease2019

Quantitative FDG PET/CT may help risk-stratify early-stage non-small cell lung cancer patients at risk for recurrence following anatomic resection.

Stephanie Harmon, Christopher W Seder, Song Chen, Anne Traynor, Robert Jeraj, Justin D Blasberg

Abstract read
In one paragraph

Article in Journal of thoracic disease, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
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  3. Review
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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

6 authors.

Stephanie HarmonDepartment of Medical Physics, University of Wisconsin, Madison, WI, USA.
Christopher W SederDepartment of Thoracic and Cardiovascular Surgery, Rush University Medical Center, Chicago, IL, USA.
Song ChenDepartment of Medical Physics, University of Wisconsin, Madison, WI, USA.
Anne TraynorDepartment of Medical Physics, University of Wisconsin, Madison, WI, USA.
Robert JerajDepartment of Medical Physics, University of Wisconsin, Madison, WI, USA.
Justin D BlasbergDepartment of Surgery, Yale University, New Haven, CT, USA.

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
U.W. RADIOLOGICAL SCIENCES TRAINING PROGRAMT32CA009206 · NCI · UNIVERSITY OF WISCONSIN-MADISON · PI Bryan Patrick Bednarz · 1985 to 2026
$12.1M
NCATS NIH HHS UL1 TR001863NCI NIH HHS T32 CA009206
6 · The paper itself

Abstract

backgroundPreoperative identification of non-small cell lung cancer (NSCLC) patients at risk for disease recurrence has proven unreliable. The extraction of quantitative metrics from imaging based on tumor intensity and texture may enhanced disease characterization. This study evaluated tumor-specific

methodsSixty-four stage I/II NSCLC patients who underwent anatomic resection between 2001 and 2014 were examined. Pathologically or radiographic confirmed disease recurrence within 5 years of resection comprised the study group. Quantitative imaging metrics were extracted within the primary tumor volume. Squamous cell carcinoma (SCC) (N=27) and adenocarcinoma (AC) (N=41) patients were compared using a Wilcoxon signed-rank test. Associations between imaging and clinical variables with 5-year disease-free survival (DFS) and overall survival (OS) were evaluated by Cox proportional-hazards regression.

resultsClinical and pathologic characteristics were similar between recurrence (N=34) and patients achieving 5-year DFS (N=30). Standardized uptake value (SUV)

conclusionsSeveral imaging metrics correlate with increased risk for disease recurrence in early-stage NSCLC. The predictive ability of imaging was strongest when patients are stratified by histology. The incorporation of

Indexed as

clinical outcomeearly-stage non-small cell lung cancer (early-stage NSCLC)Positron emission tomography (PET)quantitative imagingsurgical resection

Identifiers

PMID31179052
PMCPMC6531752

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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.