Evidence map›Paper›PMID 24400243›Full record

ArticleResearch and reports in urology2013

Pelvic lymph node dissection in the context of radical cystectomy: a thorough insight into the connection between patient, surgeon, pathologist and treating institution.

Roland Seiler, George N Thalmann, Pascal Zehnder

Open access · goldAbstract read
In one paragraph

Article in Research and reports in urology, 2013. 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
0.9field-weighted citation impact, top 23% 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, 6 citations in OpenAlex.

  1. Article
  2. 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

3 authors at 1 institution in 1 country.

Roland SeilerDepartment of Urology, University of Bern, Bern, Switzerland.
George N ThalmannDepartment of Urology, University of Bern, Bern, Switzerland.
Pascal ZehnderDepartment of Urology, University of Bern, Bern, Switzerland.
University of Bern · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pelvic lymph node dissection (PLND) in patients with bladder cancer varies widely in extent, technique employed, and pathological workup of specimens. The present paper provides an overview of the existing evidence regarding the effectiveness of PLND and elucidates the interactions between patient, surgeon, pathologist, and treating institution as well as their cumulative impact on the final postoperative lymph node (LN) staging. Bladder cancer patients undergoing radical cystectomy with extended PLND appear to have better oncologic outcomes compared to patients undergoing radical cystectomy and limited PLND. Attempts have been made to define and assess the quality of PLND according to the number of lymph nodes identified. However, lymph node counts depend on multiple factors such as patient characteristics, surgical template, pathological workup, and institutional policies; hence, meticulous PLND within a defined and uniformly applied extended template appears to be a better assurance of quality than absolute lymph node counts. Nevertheless, the prognosis of the patients can be partially predicted with findings from the histopathological evaluation of the PLND specimen, such as the number of positive lymph nodes, extracapsular extension, and size of the largest LN metastases. Therefore, particular prognostic parameters should be addressed within the pathological report to guide the urologist in terms of patient counseling.

Indexed as

bladder canceroutcomepathological workuppostoperative staging

Identifiers

PMID24400243
PMCPMC3826931
OpenAlexW2149862287

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.