ArticleBiomarker insights2007
Biomarkers in bladder cancer: present status and perspectives.
Article in Biomarker insights, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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
4 citing papers in PubMed, 10 citations in OpenAlex.
- Artificial intelligence-assisted diagnosis and histopathological grading of bladder cancer: current status, challenges, and future directions.Frontiers in digital health · 2026Review
- The S100 protein family in bladder cancer: mechanisms, clinical value, and targeted therapeutic prospects.Frontiers in oncology · 2025Review
- Long-term validation of a molecular progression-associated gene classifier for prediction of muscle invasion in primary non-muscle-invasive bladder cancer.Oncology letters · 2017Article
- USP28 is a potential prognostic marker for bladder cancer.Tumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine · 2014Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Bladder cancers are a mixture of heterogeneous cell populations, and numerous factors are likely to be involved in dictating their recurrence, progression and the patient's survival. For any candidate prognostic marker to have considerable clinical relevance, it must add some predictive capacity beyond that offered by conventional clinical and pathologic parameters. Here, the current situation in bladder cancer research with respect to identification of suitable prognostic markers is reviewed. A number of individual molecular markers that might predict bladder cancer recurrence and progression have been identified but many are not sufficiently sensitive or specific for the whole spectrum of bladder cancer diseases seen in routine clinical practice. These limitations have led to interest in other molecular parameters that could enable more accurate prognosis for bladder cancer patients. Of particular interest is the epigenetic silencing of tumor suppressor genes. Since the methylation of these genes can correlate with a poor prognosis, the methylation profile may represent a new bio-marker that indicates the risk of transitional cell carcinoma development. In addition, bladder cancer research is likely to be revolutionized by high-throughput molecular technologies, which allow rapid and global gene expression analysis of thousands of tumor samples. Initial studies employing these technologies have considerably expanded our ability to classify bladder cancers with respect to their survivability. Future microarray analyses are likely to reveal particular gene expression signatures that predict the likelihood of bladder cancer progression and recurrence, as well as patient's survival and responsiveness to different anti-cancer therapies, with great specificity and sensitivity.
Indexed as
Identifiers
19662195PMC2717839W1564335190What 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.