ReviewBiomedicines2023
The Current Progress and Future Options of Multiple Therapy and Potential Biomarkers for Muscle-Invasive Bladder Cancer.
Review in Biomedicines, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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
7 citing papers in PubMed, 8 citations in OpenAlex.
- Bacterial nanoparticles as a potent and safe alternative to BCG for bladder cancer immunotherapy.Cancer gene therapy · 2026Article
- Progress in the application of combined detection of urinary tumor DNA and exosomes in the classification, staging, and clinical management of bladder cancer: a review.Frontiers in oncology · 2026Review
- Artificial intelligence-assisted diagnosis and histopathological grading of bladder cancer: current status, challenges, and future directions.Frontiers in digital health · 2026Review
- Review
- Construction of a column-line graphical model of poor outcome of neoadjuvant regimens for muscle-invasive bladder cancer based on NLR, dNLR and SII indicators.World journal of surgical oncology · 2025Article
- Bladder Cancer in Exosomal Perspective: Unraveling New Regulatory Mechanisms.International journal of nanomedicine · 2024Review
- The role of E3 ubiquitin ligases and deubiquitinases in bladder cancer development and immunotherapy.Frontiers in immunology · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Bladder cancer is a common disease in men and the elderly. Current treatment paradigms include radical resection of the bladder and lymph nodes or transurethral resection, both supported by chemotherapy and/or radiation. New modalities, such as illumination-based therapies are also being translationally pursued. However, while survival rates have increased due to combined therapies (particularly chemotherapy, radiation, immune checkpoint inhibitors, and surgery), a lack of diagnostic markers leads clinical professionals to rely on frequently invasive and expensive means of monitoring, such as magnetic resonance imaging or bladder cystoscopy. To improve real-time diagnostic capabilities, biomarkers that reflect both the metabolic and metastatic potential of tumor cells are needed. Furthermore, indicators of therapy resistance would allow for rapid changes in treatment to optimize survival outcomes. Fortunately, the presence of nanoscale extracellular vesicles in the blood, urine, and other peripheral fluids allow for proteomic, genomic, and transcriptomic analyses while limiting the invasiveness of frequent sampling. This review provides an overview of the pathogenesis and progression of bladder cancer, standard treatments and outcomes, some novel treatment studies, and the current status of biomarker and therapy development featuring exosome-based analysis and engineering.
Indexed as
Identifiers
What 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.