ReviewAbdominal radiology (New York)2025
Precise vesical wall staging of bladder cancer in the era of precision medicine: has it been fulfilled?
Review in Abdominal radiology (New York), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
3 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Application Value of Radiomics-Based Machine Learning for Preoperative Risk Stratification of Bladder Cancer: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2026Pooled it
- Interpretable machine learning models for bladder cancer overall survival prediction development and external validation via SEER database and Chinese cohort analysis.Discover oncology · 2026Article
- Multimodal artificial intelligence in urologic precision oncology: from algorithm to translational medicine (a systemized narrative review).Frontiers in oncology · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Urinary bladder cancer is a global disease that poses medical and socioeconomic challenges to patients and healthcare systems. Predicting detrusor invasiveness and pathological grade of bladder cancer by the radiologist is imperative for informed decision-making and effective patient-tailored therapy. Cystoscopy and TURBT are the current gold standard for preoperative histologic diagnosis and local pathological staging but are compromised by their intrusiveness, under-sampling, and staging inaccuracies. Over the last few decades, incredible imaging technology advancements have enabled radiologists to progress in these grading and staging tasks. MRI has become widely accepted as a noninvasive alternative. It supplements morphologic data with functional insights into the tumor microenvironment, enhancing tumor characterization and predicting the detrusor's histologic grade and invasiveness status. Radiomics is a promising field that helps radiologists achieve higher accuracies in bladder cancer staging, re-staging, and direct treating teams to potential management readjustments. Such knowledge leaps hold promise for personalized management of bladder cancer in a precision medicine era.
Indexed as
Identifiers
39725735What OpenQuestion holds
Registered trials
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.