Evidence map›Paper›PMID 41168440›Full record

ReviewNature reviews. Urology2026

Optimizing local control in the surgical management of bladder cancer.

Martin Egger, Vincent D D'Andrea, Clara Steiner, Nnamdi O Onochie, Timothy N Clinton, Chong-Xian Pan, Adam S Kibel, Cheryl T Lee, Kent W Mouw, Matthew Mossanen

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature reviews. Urology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

1 citing paper in PubMed.

  1. 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

10 authors.

Martin EggerDana-Farber Cancer Institute, Boston, MA, USA. megger@broadinstitute.org.ORCID http://orcid.org/0000-0003-2803-1143
Vincent D D'AndreaDana-Farber Cancer Institute, Boston, MA, USA.
Clara SteinerDana-Farber Cancer Institute, Boston, MA, USA.ORCID http://orcid.org/0009-0008-8640-1636
Nnamdi O OnochieDana-Farber Cancer Institute, Boston, MA, USA.
Timothy N ClintonDana-Farber Cancer Institute, Boston, MA, USA.
Chong-Xian PanDana-Farber Cancer Institute, Boston, MA, USA.
Adam S KibelDana-Farber Cancer Institute, Boston, MA, USA.
Cheryl T LeeDepartment of Urology, The Ohio State University Medical Center, Columbus, OH, USA.
Kent W MouwDana-Farber Cancer Institute, Boston, MA, USA.ORCID http://orcid.org/0000-0001-7939-7343
Matthew MossanenDana-Farber Cancer Institute, Boston, MA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Bladder cancer is a highly prevalent disease in the Western World, and the treatment paradigm is actively evolving. For decades, the most commonly used standard of care for localized muscle-invasive disease has been neoadjuvant chemotherapy followed by open radical cystectomy with urinary diversion. Considering the high postoperative morbidity of this procedure, efforts have focused on improving patient outcomes. Over the past decade, substantial advances have been introduced in imaging, prehabilitation, perioperative care, robotic surgery and organ-sparing techniques. Bladder preservation after complete clinical response to neoadjuvant treatment or after trimodal treatment is increasingly being implemented. In addition, novel biomarkers are increasingly being used to monitor treatment response and select patients for adequate therapy. Last, innovative approaches, such as intraoperative imaging, sentinel lymph-node biopsy or the use of artificial intelligence, are currently under investigation.

Indexed as

CystectomyUrinary Bladder NeoplasmsHumansNeoadjuvant TherapyRobotic Surgical Procedures

Identifiers

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.