Evidence map›Paper›PMID 40109853›Full record

ReviewOncology research2025

Biomarkers for predicting bladder cancer therapy response.

Ioana Maria Mihai, Gang Wang

Abstract readReview
In one paragraph

Review in Oncology research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Review
  5. 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

2 authors.

Ioana Maria MihaiDepartment of Pathology and Laboratory Medicine, British Columbia Cancer Vancouver Centre, Vancouver, BC V5Z 4E6, Canada.
Gang WangDepartment of Pathology and Laboratory Medicine, British Columbia Cancer Vancouver Centre, Vancouver, BC V5Z 4E6, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The advent of precision medicine has underscored the importance of biomarkers in predicting therapy response for bladder cancer, a malignancy marked by considerable heterogeneity. This review critically examines the current landscape of biomarkers to forecast treatment outcomes in bladder cancer patients. We explore a range of biomarkers, including genetic, epigenetic, proteomic, and transcriptomic indicators, from multiple sample sources, including urine, tumor tissue and blood, assessing their efficacy in predicting responses to chemotherapy, immunotherapy, and targeted therapies. Despite promising developments, the translation of these biomarkers into clinical practice faces significant challenges, such as variability in biomarker performance, the necessity for large-scale validation studies, and the integration of biomarker testing into routine clinical workflows. We also highlight the need for standardized methodologies and robust assays to ensure consistency and reliability. Future directions point towards longitudinal studies and the development of combination biomarker panels to enhance predictive accuracy. This review emphasizes the transformative potential of predictive biomarkers in improving patient outcomes and advocates for continued collaborative efforts to overcome existing barriers in this rapidly evolving field.

Indexed as

Biomarkers, TumorUrinary Bladder NeoplasmsHumansPrecision MedicinePrognosisProteomicsTreatment OutcomeBiomarkers, TumorBlood biomarkersGenetic and epigenetic indicatorsPrecision medicineTissue biomarkersUrine biomarkers

Identifiers

PMID40109853
PMCPMC11915070

What Socratic 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 Socratic graph.