Evidence map›Paper›PMID 33457281›Full record

ReviewTranslational andrology and urology2020

The evolving role of lymphadenectomy for bladder cancer: why, when, and how.

Vignesh T Packiam, Matvey Tsivian, Stephen A Boorjian

Abstract readReview
In one paragraph

Review in Translational andrology and urology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 2 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

8 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
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  8. 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

3 authors.

Vignesh T PackiamDepartment of Urology, Mayo Clinic, Rochester, MN, USA.
Matvey TsivianDepartment of Urology, Mayo Clinic, Rochester, MN, USA.
Stephen A BoorjianDepartment of Urology, Mayo Clinic, Rochester, MN, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Radical cystectomy (RC) represents a standard treatment for non-metastatic muscle-invasive and select high-risk non-muscle invasive bladder cancer. Lymphadenectomy performed at time of RC identifies nodal metastases in up to 25% of patients despite normal imaging. There has been an increasing utilization of pelvic lymph node dissection (PLND) with RC since 1950, and in fact lymph node dissection is now recommended in contemporary National Comprehensive Cancer Network (NCCN) guidelines. Benefits of removing of nodal disease include improved staging, guidance for adjuvant treatment, and potentially improved oncologic outcomes. Advantages of dissection have been suggested among both node-negative and node-positive patients. Numerous studies have attempted to define the optimal dissection characteristics of lymphadenectomy with regard to nodal yield and anatomic boundaries of dissection. The ideal extent of lymphadenectomy remains uncertain due to the retrospective and non-randomized nature of the majority of existing reports, which are thereby limited by significant confounding and selection bias. Two randomized controlled trials have investigated this issue, one of which LEA AUO AB 25/02 recently reported its outcomes, demonstrating no significant improvement in 5-year outcomes with an extended dissection. Meanwhile, the Southwest Oncology Group 1011 trial has completed enrollment and data are maturing. While current data preclude definitive recommendations, herein we review the why, when, and how to perform a PLND for bladder cancer.

Indexed as

Bladder cancerlymphadenectomylymph node dissectionradical cystectomy (RC)

Identifiers

PMID33457281
PMCPMC7807370

What OpenQuestion holds

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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.