Evidence map›Paper›PMID 26909130›Full record

ReviewWorld journal of gastrointestinal oncology2016

Endoscopic approach to the diagnosis of pancreatic cystic tumor.

Yoshiaki Kawaguchi, Tetsuya Mine

Open access · hybridAbstract readReview
In one paragraph

Review in World journal of gastrointestinal oncology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.1field-weighted citation impact, top 21% 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

3 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. Novel Biomarkers for Pancreatic Cysts.Digestive diseases and sciences · 2017
    Review
  3. 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

2 authors at 1 institution in 2 countries.

Yoshiaki KawaguchiYoshiaki Kawaguchi, Tetsuya Mine, Department of Gastroenterology, Tokai University School of Medicine, Isehara 259-1193, Japan.
Tetsuya MineYoshiaki Kawaguchi, Tetsuya Mine, Department of Gastroenterology, Tokai University School of Medicine, Isehara 259-1193, Japan.
Tokai University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Because of the aging of the population, prevalence of medical checkups, and advances in imaging studies, the number of pancreatic cystic lesions detected has increased. Once these lesions are detected, neoplastic cysts should be differentiated from non-neoplastic cysts. Furthermore, because of the malignant potential of some neoplastic pancreatic cysts, further differentiation between benign and malignant cysts should be made regardless of their size. Although endoscopic ultrasound (EUS) has a very high diagnostic performance for pancreatic cystic lesions among the various imaging modalities, EUS findings alone are insufficient for the differentiation of pancreatic cysts and diagnosis of malignancy. In addition, cytology by EUS-guided fine-needle aspiration (FNA) has a high specificity but a low sensitivity for diagnosing malignancy in pancreatic cystic tumors. The levels of amylase, lipase, and tumor markers in pancreatic cystic fluid are considered auxiliary parameters for diagnosis of benign and malignant cysts, and a definitive diagnosis of malignancy using these parameters is difficult. Thus, in addition to EUS, cytology by EUS-FNA, and cystic fluid analysis, new techniques based on EUS-guided through-the-needle imaging, such as confocal laser endomicroscopy and cystoscopy, have been explored in recent years.

Indexed as

CytologyEndoscopic retrograde cholangiopancreatographyEndoscopic ultrasoundEndoscopic ultrasound-needle aspirationPancreatic cystic tumor

Identifiers

PMID26909130
PMCPMC4753166
OpenAlexW2282178610

What OpenQuestion holds

Textmetadata
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.