Evidence map›Paper›PMID 40996609›Full record

ArticleInternational urology and nephrology2026

Liquid biopsy based on multi-targeted capture of urinary tumor DNA combined with machine learning to detect urothelial carcinoma: a multicenter prospective study.

Chaozhi Tang, Tianlong Wang, Huarong Luo, Jingdong Xue, Miaojun Zhu, Zhe Hong, Fang Ding, Fengwu Zhang, Yihao Zhu, Ruoying Tan and 1 more

Abstract readMulticenter Study
PubMed Publisher
In one paragraph

Article in International urology and nephrology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
–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

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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

11 authors.

Chaozhi Tang *Department of Urology, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai, 200120, China.
Tianlong Wang *Department of Urology, Shanghai Eighth People's Hospital, Shanghai, 200235, China.
Huarong Luo *Department of Urology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, 200065, China.
Jingdong XueDepartment of Urology, Shanghai Eighth People's Hospital, Shanghai, 200235, China. xuejingdong@126.com.
Miaojun ZhuShanghai Biovuetech Co., Ltd, Shanghai, 200063, China.
Zhe HongDepartment of Urology, Fudan University Shanghai Cancer Center, Shanghai, 200032, China.
Fang DingPhysical Examination Center, Shanghai Eighth People's Hospital, Shanghai, 200235, China.
Fengwu ZhangShanghai Biovuetech Co., Ltd, Shanghai, 200063, China.
Yihao ZhuShanghai Biovuetech Co., Ltd, Shanghai, 200063, China.
Ruoying TanShanghai Biovuetech Co., Ltd, Shanghai, 200063, China. roy.tan@biovuetech.cn.
Denglong WuDepartment of Urology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, 200065, China. wudenglong2009@tongji.edu.cn.

Funding

Shanghai Eighth People's Hospital Research Project SHBY202513Shanghai Xuhui medical research project SHXH202220Shanghai Xuhui medical research project SHXH202336
6 · The paper itself

Abstract

purposeDiagnostics for urothelial carcinoma have low sensitivity, thereby negatively impacting diagnostic outcomes. Herein, we present Biovue

methodsThe study involved 63 patients with malignant urothelial carcinoma, 13 patients with benign lesions, 115 patients with urinary symptoms, and 106 healthy participants undergoing physical check-ups. Detection was performed using real-time fluorescence quantitative polymerase chain reaction. Biovue

resultsThe optional model demonstrated high diagnostic efficacy in distinguishing patients with high-grade urothelial carcinoma from non-patients. In the validation set, the receiver operating characteristic curve, sensitivity, specificity, accuracy, and positive and negative predictive values were 96.1% (95% CI 89.3-100), 94.7%, 99.1%, 98.5%, 94.7%, and 99.1%, respectively. For distinguishing patients with early-stage urothelial carcinoma from non-patients, the values in the training set were 91.7% (95% CI 84.2-99.1), 80%, 98.3%, 95.1%, 90.9%, and 95.8%, and those in the validation set were 92.5% (95% CI 86.6-98.4%), 80%, 95.7%, 93%, 80%, and 95.7%, respectively. The study's limitations include a relatively small cohort size, restricted regional diversity and a lack of long-term follow-up data to assess disease progression and treatment outcomes.

conclusionsIn summary, Biovue

Indexed as

Carcinoma, Transitional CellDNA, NeoplasmMachine LearningUrinary Bladder NeoplasmsUrologic NeoplasmsAdultAgedBiomarkers, TumorDNA MethylationFemaleHumansLiquid BiopsyMaleMiddle AgedPolymorphism, Single NucleotideProspective StudiesBiomarkers, TumorDNA, NeoplasmDiagnostic modelLiquid biopsyMachine learningMethylationMutationUrine DNAUrothelial carcinoma

Identifiers

PMID40996609

What OpenQuestion holds

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Registered trials

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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.