Evidence map›Paper›PMID 28217754›Full record

ReviewTranslational gastroenterology and hepatology2017

N staging system: tumor-node-metastasis and future perspectives.

Federica Galli, Laura Ruspi, Alessandro Marzorati, Matteo Lavazza, Giuseppe Di Rocco, Luigi Boni, Gianlorenzo Dionigi, Stefano Rausei

Abstract readReview
In one paragraph

Review in Translational gastroenterology and hepatology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
–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

7 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. 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

8 authors.

Federica GalliDivision of General Surgery, Department of Surgical Sciences, University of Insubria, Varese, Italy.
Laura RuspiDivision of General Surgery, Department of Surgical Sciences, University of Insubria, Varese, Italy.
Alessandro MarzoratiDivision of General Surgery, Department of Surgical Sciences, University of Insubria, Varese, Italy.
Matteo LavazzaDivision of General Surgery, Department of Surgical Sciences, University of Insubria, Varese, Italy.
Giuseppe Di RoccoDivision of General Surgery, Department of Surgical Sciences, University of Insubria, Varese, Italy.
Luigi BoniDivision of General Surgery, Department of Surgical Sciences, University of Insubria, Varese, Italy.
Gianlorenzo DionigiDivision of General Surgery, Department of Surgical Sciences, University of Insubria, Varese, Italy.
Stefano RauseiDivision of General Surgery, Department of Surgical Sciences, University of Insubria, Varese, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The correct staging of disease, with an exact definition of the extent of cancer at the diagnosis, is crucial in the planning of a specific treatment and in the assessment of real chances of cure. Cancer staging systems are expected to be accurate in the description of the severity of a patient's tumor on the basis of the extent of the primary neoplasm and of its spread, thus giving clinician tools to estimate prognosis and providing objective parameters to compare groups of patients in clinical studies. This last point is of wide importance in evaluating successful treatment strategies in oncology, and this is one of the issues that contributed to the development of stage-adapted therapies.

Indexed as

gastric cancer staginglymph node in gastric cancerTumor-node-metastasis staging system (TNM staging system)

Identifiers

PMID28217754
PMCPMC5313289

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.