Evidence map›Paper›PMID 35918269›Full record

ReviewEuropean urology focus2022

Optimal Selection of Patients with Genitourinary Cancers for Anti-PD1/PD-L1 Treatment with a Focus on Urothelial and Renal Cell Carcinoma.

Philip Zeuschner, Kerstin Junker

Abstract readReview
PubMed Publisher
In one paragraph

Review in European urology focus, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.1field-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

4 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Philip ZeuschnerDepartment of Urology and Pediatric Urology, Saarland University and Saarland Medical Center, Homburg, Germany.
Kerstin JunkerDepartment of Urology and Pediatric Urology, Saarland University and Saarland Medical Center, Homburg, Germany. Electronic address: kerstin.junker@uks.eu.
Saarland University · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite the recent approval of numerous immune checkpoint inhibitors (ICIs) for the treatment of genitourinary tumors, predictive biomarkers are still lacking. Different approaches are necessary, as the only approved biomarker for urothelial carcinoma (UC), namely PD-L1 immunostaining, has questionable predictive value. By contrast, tumor-infiltrating cells have been associated with therapy response in both UC and renal cell carcinoma. Tumor-derived gene signatures can further identify patients with pre-existing adaptive immunity. Whereas tumor mutation burden, DNA repair defects, and microsatellite instability are of some predictive value, the utility of single gene mutations has not yet been proved. As ICIs mainly target tumor metastases, analysis of primary tumors appears to be suboptimal. Circulating biomarkers reflecting tumor and systemic alterations in a more complex and dynamic manner are of great potential. The most promising approach is an analysis of complex tumor composition with concomitant consideration of the host immune status, which is also influenced by the gut microbiome. PATIENT SUMMARY: Immunotherapy is one of the treatment options for cancers of the urinary tract and kidney. We review the methods for measuring biomarkers that may predict which patients are most likely to respond to this treatment.

Indexed as

Carcinoma, Renal CellCarcinoma, Transitional CellKidney NeoplasmsUrinary Bladder NeoplasmsB7-H1 AntigenHumansImmune Checkpoint InhibitorsPatient SelectionB7-H1 AntigenImmune Checkpoint InhibitorsBiomarkerCheckpoint inhibitorGenitourinary canerKidney cancerTumor therapyUrothelial carcinoma

Identifiers

PMID35918269
OpenAlexW4288905900

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.