Evidence map›Paper›PMID 38488892›Full record

ArticleWorld journal of urology2024

The impact of the relationship between lesion diameter and total core length on the detection rate of clinically significant prostate cancer for PI-RADS 3 lesions.

Emrah Yakut

Open access · hybridAbstract read
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Article in World journal of urology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.3field-weighted citation impact, top 21% 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

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 3 citations in OpenAlex.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

1 author at 1 institution in 1 country.

Emrah YakutDepartment of Urology, Yuksek Ihtisas University, İşçi Blokları, 1588. Cd. No: 18/A, 06520, Çankaya, Ankara, Turkey. dremrahyakut@gmail.com.ORCID http://orcid.org/0000-0001-8635-9185
Çankaya University · TR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe aim of our study was to determine the effect of total core length (TCL) for prostate imaging reporting and data system (PI-RADS) 3 lesions to facilitate clinically significant prostate cancer (csPCa) detection based on the lesion diameter. MATERIALS AND

methodsA total of 149 patients with at least 1 lesion with a PI-RADS 3 were evaluated retrospectively. The lesions with diameters of < 1 cm were categorized as small lesions and lesions of ≥ 1 cm were categorized as large lesions. The lengths of biopsy cores from PI-RADS 3 lesions were summed for each lesion separately, and TCL was calculated. The relationship between TCL and csPCa was analyzed separately for the small and large groups with multiple logistic regression analyses.

resultsA total of 208 lesions were detected by multiparametric magnetic resonance imaging (MpMRI) in 149 males included in the study. The mean TCL was 44.68 mm (26-92) and the mean lesion diameter was 10.73 mm (4-27) in PIRADS 3 lesions. For small diameter lesions (< 1 cm), the odds of finding clinically insignificant prostate cancer (ciPCa) increase by 1.67 times if TCL increases by one unit. Hence, increasing TCL for small lesions only increases the odds of ciPCa detection. For large diameter lesions (≥ 1 cm), if TCL increases by one unit, the odds of finding ciPCa increase 1.13 times and the odds of finding csPCa increases1.16 times. Accordingly, large lesions are more likely to have both csPCa and ciPCa as TCL increases.

conclusionsOur study showed that for PI-RADS 3 lesions, both more csPCa and more ciPCa were detected as TCL increased. However, in lesions with a size of < 1 cm, only ciPCa was detected more frequently as TCL increased. In conclusion, taking more and longer biopsy cores in PI-RADS 3 lesions below 1 cm does not contribute to the detection of csPCa.

Indexed as

Multiparametric Magnetic Resonance ImagingProstatic NeoplasmsBiopsyHumansImage-Guided BiopsyMagnetic Resonance ImagingMaleRetrospective StudiesClinically significant prostate cancerLesion diameterMultiparametric magnetic resonance imagingProstate fusion biopsyTotal core length

Identifiers

PMID38488892
PMCPMC10942878
OpenAlexW4392864305

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LicenceCC BY
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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.