Evidence map›Paper›PMID 28293631›Full record

ArticleBioMed research international2017

Urinary Biomarker Panel to Improve Accuracy in Predicting Prostate Biopsy Result in Chinese Men with PSA 4-10 ng/mL.

Yongqiang Zhou, Yun Li, Xiangnan Li, Minjun Jiang

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In one paragraph

Article in BioMed research international, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Diagnosis accuracy of PCA3 level in patients with prostate cancer: a systematic review with meta-analysis.International braz j urol : official journal of the Brazilian Society of Urology
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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

4 authors.

Yongqiang ZhouDepartment of Urology, The People's Hospital of Wujiang City, Suzhou, Jiangsu, China.
Yun LiDepartment of Urology, Shanghai Shibei Hospital of Jingan District, Shanghai, China.
Xiangnan LiDepartment of Anesthesiology, The Third People's Hospital of Yancheng, Yancheng, Jiangsu, China.
Minjun JiangDepartment of Urology, The People's Hospital of Wujiang City, Suzhou, Jiangsu, China.ORCID 0000-0002-0661-9272

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aims to evaluate the effectiveness and clinical performance of a panel of urinary biomarkers to diagnose prostate cancer (PCa) in Chinese men with PSA levels between 4 and 10 ng/mL. A total of 122 patients with PSA levels between 4 and 10 ng/mL who underwent consecutive prostate biopsy at three hospitals in China were recruited. First-catch urine samples were collected after an attentive prostate massage. Urinary mRNA levels were measured by quantitative real-time polymerase chain reaction (qRT-PCR). The predictive accuracy of these biomarkers and prediction models was assessed by the area under the curve (AUC) of the receiver-operating characteristic (ROC) curve. The diagnostic accuracy of PCA3, PSGR, and MALAT-1 was superior to that of PSA. PCA3 performed best, with an AUC of 0.734 (95% CI: 0.641, 0.828) followed by MALAT-1 with an AUC of 0.727 (95% CI: 0.625, 0.829) and PSGR with an AUC of 0.666 (95% CI: 0.575, 0.749). The diagnostic panel with age, prostate volume, % fPSA, PCA3 score, PSGR score, and MALAT-1 score yielded an AUC of 0.857 (95% CI: 0.780, 0.933). At a threshold probability of 20%, 47.2% of unnecessary biopsies may be avoided whereas only 6.2% of PCa cases may be missed. This urinary panel may improve the current diagnostic modality in Chinese men with PSA levels between 4 and 10 ng/mL.

Indexed as

AgedAlgorithmsBiomarkers, TumorBiopsyChinaHumansMaleMiddle AgedProbabilityProstateProstate-Specific AntigenProstatic NeoplasmsReal-Time Polymerase Chain ReactionRegression AnalysisReproducibility of ResultsROC CurveBiomarkers, TumorProstate-Specific Antigen

Identifiers

PMID28293631
PMCPMC5331314

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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.