Evidence map›Paper›PMID 38173833›Full record

ReviewFrontiers in oncology2023

Antibody-drug conjugates in urinary tumors: clinical application, challenge, and perspectives.

Keqiang Li, Guoqing Xie, Xiyue Deng, Yu Zhang, Zhankui Jia, Zhenlin Huang

Abstract readReview
In one paragraph

Review in Frontiers in oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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

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

6 authors.

Keqiang Li *Department of Urology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
Guoqing Xie *Department of Urology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
Xiyue DengDepartment of Urology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
Yu ZhangDepartment of Urology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
Zhankui JiaDepartment of Urology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
Zhenlin HuangDepartment of Urology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Urinary tumors primarily consist of kidney, urothelial, and prostate malignancies, which pose significant treatment challenges, particularly in advanced stages. Antibody-drug conjugates (ADCs) have emerged as a promising therapeutic approach, combining monoclonal antibody specificity with cytotoxic chemotherapeutic payloads. This review highlights recent advancements, opportunities, and challenges in ADC application for urinary tumors. We discuss the FDA-approved ADCs and other novel ADCs under investigation, emphasizing their potential to improve patient outcomes. Furthermore, we explore strategies to address challenges, such as toxicity management, predictive biomarker identification, and resistance mechanisms. Additionally, we examine the integration of ADCs with other treatment modalities, including immune checkpoint inhibitors, targeted therapies, and radiation therapy. By addressing these challenges and exploring innovative approaches, the development of ADCs may significantly enhance therapeutic options and outcomes for patients with advanced urinary tumor.

Indexed as

ADCbladderkidneyprostateurinary tumorsurothelial cancer

Identifiers

PMID38173833
PMCPMC10761427

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.