ArticleCancer biomarkers : section A of Disease markers2023
Prediction for recurrent non-muscle invasive bladder cancer.
Article in Cancer biomarkers : section A of Disease markers, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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
1 citing paper in PubMed, 0 citations in OpenAlex.
- Derivation and validation of the SLNA score: a tumor size-location-number-apperance model to predict transurethral resection of bladder tumor (TURBT) complexity.Translational andrology and urology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Non-muscle invasive bladder cancer (NMIBC) has a high recurrence rate, which places a significant burden on both patients and the healthcare system. Hence, it holds significant importance to predict the recurrence risk following treatment for individuals diagnosed with non-muscle invasive bladder cancer (NMIBC). As new generation technologies continue to emerge, an increasing number of recurrence risk prediction tools are being developed and discovered. This article provides an overview of the primary recurrence risk prediction tools currently available, including the liquid biopsy, tissue biopsy, and risk prediction tables. Each of these tools is described in detail and illustrated with relevant examples. Furthermore, we conduct an analysis of the advantages and disadvantages of these tools. This article aims to enhance the reader's understanding of the current progress in recurrence prediction tools and encourage their practical utilization in the fields of precision medicine and public health.
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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.