Evidence map›Paper›PMID 26782807›Full record

ArticleAmerican journal of surgery2016

Significance of preoperative radiographic pancreatic density in predicting pancreatic fistula after surgery for pancreatic neuroendocrine tumors.

Yasmine Assadipour, Saïd C Azoury, Nicholas N Schaub, Young Hong, Robert Eil, Suzanne M Inchauste, Seth M Steinberg, Aradhana M Venkatesan, Steven K Libutti, Marybeth S Hughes

Open access · greenAbstract read
In one paragraph

Article in American journal of surgery, 2016. 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
0.1field-weighted citation impact, top 44% 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, 7 citations in OpenAlex.

  1. Article
  2. Review
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

10 authors at 4 institutions in 2 countries.

Yasmine AssadipourSurgery Branch, Center for Cancer Research, National Cancer Institute, Bethesda, MD.
Saïd C AzourySurgery Branch, Center for Cancer Research, National Cancer Institute, Bethesda, MD; Thoracic and Gastrointestinal Oncology Branch, Center for Cancer Research, National Cancer Institute, Bethesda, MD.
Nicholas N SchaubSurgery Branch, Center for Cancer Research, National Cancer Institute, Bethesda, MD.
Young HongSurgery Branch, Center for Cancer Research, National Cancer Institute, Bethesda, MD.
Robert EilSurgery Branch, Center for Cancer Research, National Cancer Institute, Bethesda, MD.
Suzanne M InchausteSurgery Branch, Center for Cancer Research, National Cancer Institute, Bethesda, MD.
Seth M SteinbergBiostatistics and Data Management Section, Center for Cancer Research, National Cancer Institute, Bethesda, MD.
Aradhana M VenkatesanRadiology and Imaging Sciences NIH Clinical Center, National Institutes of Health, Bethesda, MD.
Steven K LibuttiDepartment of Surgery, Albert Einstein College of Medicine, Montefiore Medical Center, Bronx, NY.
Marybeth S HughesSurgery Branch, Center for Cancer Research, National Cancer Institute, Bethesda, MD; Thoracic and Gastrointestinal Oncology Branch, Center for Cancer Research, National Cancer Institute, Bethesda, MD. Electronic address: hughesm@mail.nih.gov.
National Cancer Institute · USAlbert Einstein College of Medicine · USNational Cancer Institute · MYNational Institutes of Health Clinical Center · US

Funding

Office of Collaborative BiostatisticsZIDSC007202 · NCI · DIVISION OF CLINICAL SCIENCES - NCI · PI CHOO-WOSOBA, HYOYOUNG · 2009 to 2025
$14.5M
Project 4: New Approaches to Improving the Effectiveness of Radionuclide Targeted Treatments in Neuroendocrine TumorsP50CA174521 · NCI · UNIVERSITY OF IOWA · PI ODORISIO, THOMAS · 2015 to 2021
$13.2M
BIOSTATISTICS AND DATA MANAGEMENT SECTIONZ01SC007202 · SC · DIVISION OF CLINICAL SCIENCES - NCI · PI STEINBERG, SETH M · 1996 to 2008
$1.5M
Intramural NIH HHS Z01 SC007202Intramural NIH HHS Z99 CA999999NCI NIH HHS P50 CA174521
6 · The paper itself

Abstract

backgroundPostoperative pancreatic fistula remains the most severe and worrisome complication after surgery. Predictive preoperative assessment remains challenging. The authors examine the role of pancreatic computed tomography density in predicting postoperative pancreatic fistula after surgery for pancreatic neuroendocrine tumors.

methodsA single institutional retrospective review of pancreatic surgery for neuroendocrine tumors between 1998 and 2010 was conducted. Preoperative contrast-enhanced computed tomography scans were reviewed, with mean region of interest measurements of pancreatic parenchymal density obtained from 10-mm thick axial computed tomography images.

resultsA total of 119 patients were identified: 59 with enucleations and 60 with resections. Decreased preoperative pancreatic density was significantly associated with an increased grade of postoperative pancreatic fistula (P < .01). Subgroup analyses revealed that decreased gland density was associated with increased grade of postoperative pancreatic fistula in the resection (P < .01) but not in the enucleation group (P = .34).

conclusionsA significant association between postoperative pancreatic fistula grade and preoperative pancreatic computed tomography density is observed in patients undergoing resection for pancreatic neuroendocrine tumors.

Indexed as

AdultFemaleHumansIncidenceIntraoperative CareMaleMiddle AgedNeuroendocrine TumorsPancreasPancreatectomyPancreatic FistulaPancreatic NeoplasmsPancreaticoduodenectomyPostoperative ComplicationsPredictive Value of TestsPrognosisNeuroendocrine tumorsPancreatic enucleationPancreatic fistulaPancreaticoduodenectomyPancreatic resection

Identifiers

PMID26782807
PMCPMC7480190
OpenAlexW2192299621

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.