Evidence map›Paper›PMID 40762043›Full record

ReviewHistology and histopathology2026

Treatment strategies for locally advanced and metastatic urothelial carcinoma based on molecular profiles: A Review.

Mamoru Hashimoto, Ken Fukiage, Takafumi Minami, Marco Antonio De Velasco, Kazutoshi Fujita

Abstract readReview
PubMed Publisher
In one paragraph

Review in Histology and histopathology, 2026. 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
–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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

5 authors.

Mamoru HashimotoDepartment of Urology, Faculty of Medicine, Kindai University, Osaka, Japan.
Ken FukiageDepartment of Urology, Faculty of Medicine, Kindai University, Osaka, Japan.
Takafumi MinamiDepartment of Urology, Faculty of Medicine, Kindai University, Osaka, Japan.
Marco Antonio De VelascoDepartment of Urology, Faculty of Medicine, Kindai University, Osaka, Japan.
Kazutoshi FujitaDepartment of Urology, Faculty of Medicine, Kindai University, Osaka, Japan. kfujita@med.kindai.ac.jp.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Urothelial carcinoma (UC), which includes bladder carcinoma (accounting for 90-95% of cases) and upper urinary tract carcinoma (comprising 5-10%), is one of the most prevalent malignancies worldwide. For several decades, platinum-based chemotherapy has been the primary treatment modality for this disease. However, recent advancements have significantly transformed the therapeutic landscape for patients with UC. This transformation has been facilitated by the introduction of various treatment options, including immune checkpoint inhibitors targeting PD-L1 or PD-1, antibody-drug conjugates that target nectin-4 or trophoblast cell surface antigen 2 expressed on cancer cells, and fibroblast growth factor receptor (FGFR) inhibitors specifically indicated for Patients with UC with FGFR3 mutations. Although these novel therapies have demonstrated marked survival benefits for patients with locally advanced or metastatic UC, their efficacy can vary depending on the specific molecular profile present on cancer cells. In this review, we summarize the molecular classifications of UC and the corresponding treatment landscape associated with these classifications.

Indexed as

Carcinoma, Transitional CellUrinary Bladder NeoplasmsUrologic NeoplasmsBiomarkers, TumorHumansImmune Checkpoint InhibitorsMolecular Targeted TherapyBiomarkers, TumorImmune Checkpoint Inhibitors

Identifiers

PMID40762043

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.