Evidence map›Paper›PMID 35877385›Full record

ArticleThe British journal of radiology2022

The potential of a nomogram combined PI-RADS v2.1 and contrast-enhanced ultrasound (CEUS) to reduce unnecessary biopsies in prostate cancer diagnostics.

Yunyun Liu, Shuai Wang, Li-Hua Xiang, Guang Xu, Lin Dong, Yikang Sun, Beibei Ye, Yifeng Zhang, Huixiong Xu

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in The British journal of radiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.7field-weighted citation impact, top 15% 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

8 citing papers in PubMed, 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

9 authors at 3 institutions in 1 country.

Yunyun LiuCenter of Minimally Invasive Treatment for Tumor, Department of Medical Ultrasound, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, China.
Shuai WangCenter of Minimally Invasive Treatment for Tumor, Department of Medical Ultrasound, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, China.
Li-Hua XiangCenter of Minimally Invasive Treatment for Tumor, Department of Medical Ultrasound, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, China.
Guang XuCenter of Minimally Invasive Treatment for Tumor, Department of Medical Ultrasound, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, China.
Lin DongCenter of Minimally Invasive Treatment for Tumor, Department of Medical Ultrasound, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, China.
Yikang SunShanghai Engineering Research Center of Ultrasound Diagnosis and Treatment, Shanghai, China.
Beibei YeCenter of Minimally Invasive Treatment for Tumor, Department of Medical Ultrasound, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, China.
Yifeng ZhangCenter of Minimally Invasive Treatment for Tumor, Department of Medical Ultrasound, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, China.
Huixiong XuShanghai Engineering Research Center of Ultrasound Diagnosis and Treatment, Shanghai, China.
Tongji University · CNShanghai Tenth People's Hospital · CNZhongshan Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo develop a nomogram prediction model based on Prostate Imaging Reporting and Data System v.2.1 (PI-RADS v2.1) and contrast-enhanced ultrasound (CEUS) for predicting prostate cancer (PCa) and clinically significant prostate cancer (csPCa) in males with prostate-specific antigen (PSA) 4-10 ng ml

methodsA total of 490 patients who underwent prostate biopsy for PSA 4-10 ng ml

resultsThe multivariate analysis revealed that features independently associated with PCa and csPCa were age, PI-RADS score and CEUS manifestations. Incorporating these factors, the nomogram achieved good discrimination performance of AUC 0.843 for PCa, 0.876 for csPCa in the pilot cohort, and 0.818 for PCa, 0.857 for csPCa in the validation cohort, respectively, and had well-fitted calibration curves. And the diagnostic performance of the nomogram was comparable to the model including all the parameters (

conclusionsThe nomogram prediction model based on age, PI-RADS v2.1 and CEUS achieved an optimal prediction of PCa and csPCa. Using this model, the PCa risk for an individual patient can be estimated, which can lead to a rational biopsy choice. ADVANCES IN KNOWLEDGE: This study gives an account of improving pre-biopsy risk stratification in males with "gray zone" PSA level through PI-RADS v2.1 and CEUS.

Indexed as

ProstateProstatic NeoplasmsBiopsyHumansMagnetic Resonance ImagingMaleNomogramsProstate-Specific AntigenRetrospective StudiesProstate-Specific Antigen

Identifiers

PMID35877385
PMCPMC9815734
OpenAlexW4287510466

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.