Evidence map›Paper›PMID 33209682›Full record

ArticleTranslational andrology and urology2020

Development and validation of a nomogram for predicting prostate cancer in men with prostate-specific antigen grey zone based on retrospective analysis of clinical and multi-parameter magnetic resonance imaging/transrectal ultrasound fusion-derived data.

Zhimin Ding, Huaiyu Wu, Di Song, Hongtian Tian, Xiuqin Ye, Weiyu Liang, Yang Jiao, Jintao Hu, Jinfeng Xu, Fajin Dong

Open access · diamondAbstract read
In one paragraph

Article in Translational andrology and urology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
0.6field-weighted citation impact, top 26% of its field
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

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.

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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

10 authors at 2 institutions in 1 country.

Zhimin DingDepartment of Ultrasound, The Second Clinical Medical College, Jinan University, The First Affiliated Hospital, Southern University of Science and Technology (Shenzhen People's Hospital), Shenzhen Medical Ultrasound Engineering Center, Shenzhen, China.
Huaiyu WuDepartment of Ultrasound, The Second Clinical Medical College, Jinan University, The First Affiliated Hospital, Southern University of Science and Technology (Shenzhen People's Hospital), Shenzhen Medical Ultrasound Engineering Center, Shenzhen, China.
Di SongDepartment of Ultrasound, The Second Clinical Medical College, Jinan University, The First Affiliated Hospital, Southern University of Science and Technology (Shenzhen People's Hospital), Shenzhen Medical Ultrasound Engineering Center, Shenzhen, China.
Hongtian TianDepartment of Ultrasound, The Second Clinical Medical College, Jinan University, The First Affiliated Hospital, Southern University of Science and Technology (Shenzhen People's Hospital), Shenzhen Medical Ultrasound Engineering Center, Shenzhen, China.
Xiuqin YeDepartment of Ultrasound, The Second Clinical Medical College, Jinan University, The First Affiliated Hospital, Southern University of Science and Technology (Shenzhen People's Hospital), Shenzhen Medical Ultrasound Engineering Center, Shenzhen, China.
Weiyu LiangDepartment of Ultrasound, The Second Clinical Medical College, Jinan University, The First Affiliated Hospital, Southern University of Science and Technology (Shenzhen People's Hospital), Shenzhen Medical Ultrasound Engineering Center, Shenzhen, China.
Yang JiaoDepartment of Ultrasound, The Second Clinical Medical College, Jinan University, The First Affiliated Hospital, Southern University of Science and Technology (Shenzhen People's Hospital), Shenzhen Medical Ultrasound Engineering Center, Shenzhen, China.
Jintao HuDepartment of Pathology, The Second Clinical Medical College, Jinan University, The First Affiliated Hospital, Southern University of Science and Technology (Shenzhen People's Hospital), Shenzhen, China.
Jinfeng XuDepartment of Ultrasound, The Second Clinical Medical College, Jinan University, The First Affiliated Hospital, Southern University of Science and Technology (Shenzhen People's Hospital), Shenzhen Medical Ultrasound Engineering Center, Shenzhen, China.
Fajin DongDepartment of Ultrasound, The Second Clinical Medical College, Jinan University, The First Affiliated Hospital, Southern University of Science and Technology (Shenzhen People's Hospital), Shenzhen Medical Ultrasound Engineering Center, Shenzhen, China.
Jinan University · CNSouthern University of Science and Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundUrologists face a dilemma when deciding whether prostate biopsy is required for patients with prostate-specific antigen (PSA) levels in the grey zone (4 to 10 ng/mL).

methodsWe retrospectively analyzed data from consecutive patients with PSA levels in grey zone, who underwent targeted multiparametric magnetic resonance imaging (MP-MRI)/transrectal ultrasound (TRUS) fusion biopsy with elastography between November 2017 and December 2019 in our hospital. The patientse data including age, PSA, fPSA (free PSA), fPSA/PSA, PSA density (PSAD), prostate volume, elastography Q-analysis score (EQS), and prostate imaging-reporting and data system (PI-RADS) score were collected. The nomogram was built using logistic regression and the final cohort of patients was randomly divided into a training cohort (70%) and a validation cohort (30%) by R software. The models were evaluated by receiver operating characteristic curve (ROC) analysis and calibration curve analysis. The nomogram was constructed from the best model.

resultsThe final study cohort consisted of 155 patients (training cohort, 109 patients; validation cohort, 46 patients) with PSA in the grey zone, of which 36 patients were pathologically diagnosed with PCa. The EQS model, -EQS model, +EQS model were built. The +EQS model that consisted of fPSA/PSA, EQS, and PI-RADS score had the best PCa diagnostic accuracy (development and validation, 0.783 and 0.781) and probability score (development and validation, 0.939

conclusionsElastography and pre-biopsy MP-MRI has clinical significance for patients with PSA in the grey zone. The new nomogram, which is based on pre biopsy data including serological analysis, PI-RADS score, and EQS, can be helpful for clinical decision-making to avoid unnecessary biopsy.

Indexed as

elastographyimage fusionmulti-parameter magnetic resonance imagingprediction modelProstate cancer (PCa)

Identifiers

PMID33209682
PMCPMC7658138
OpenAlexW3093051419

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

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.