Evidence map›Paper›PMID 38711959›Full record

ArticleAdvances in radiation oncology2024

Predictive Value of Multiparametric Magnetic Resonance Imaging in Risk Group Stratification of Prostate Adenocarcinoma.

Benjamin T Bonebrake, Elsa Parr, Linda My Huynh, Brendan Coutu, Neil Hansen, Benjamin Teply, Charles Enke, Chad Lagrange, Michael Baine

Abstract read
In one paragraph

Article in Advances in radiation oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

Benjamin T BonebrakeUniversity of Nebraska Medical Center College of Medicine, Omaha, Nebraska.
Elsa ParrMayo Clinic Department of Radiation Oncology, Rochester, Minnesota.
Linda My HuynhUniversity of Nebraska Medical Center College of Medicine, Omaha, Nebraska.
Brendan CoutuSparrow Health System, Lansing, Michigan.
Neil HansenUniversity of Nebraska Medical Center, Omaha, Nebraska.
Benjamin TeplyUniversity of Nebraska Medical Center, Omaha, Nebraska.
Charles EnkeUniversity of Nebraska Medical Center, Omaha, Nebraska.
Chad LagrangeUniversity of Nebraska Medical Center, Omaha, Nebraska.
Michael BaineUniversity of Nebraska Medical Center, Omaha, Nebraska.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: The aim of this study was to further assess the clinical utility of multiparametric magnetic resonance imaging (MP-MRI) in prostate cancer (PC) staging following 2023 clinical guideline changes, both as an independent predictor of high-stage (>T3a) or high-risk PC and when combined with patient characteristics. Methods and Materials: The present study was a retrospective review of 171 patients from 2008 to 2018 who underwent MP-MRI before radical prostatectomy at a single institution. The accuracy of clinical staging was compared between conventional staging and MP-MRI-based clinical staging. Sensitivity, specificity, positive predictive value, and negative predictive value were compared, and receiver operating characteristic curves were generated. Linear regression analyses were used to calculate concordance (C-statistic). Results: Of the 171 patients, final pathology revealed 95 (55.6%) with T2 disease, 62 (36.3%) with T3a disease, and 14 (8.2%) with T3b disease. Compared with conventional staging, MP-MRI-based staging demonstrated significantly increased accuracy in identifying T3a disease, intermediate risk, and high/very-high-risk PC. When combined with clinical characteristics, MP-MRI-based staging improved the area under the curve from 0.753 to 0.808 ( Conclusions: MP-MRI improved the identification of T3a PC, intermediate-risk PC, and high- or very-high-risk PC. Further, when combined with clinical characteristics, MP-MRI-based staging significantly improved risk stratification, compared with conventional staging. These findings represent further evidence to support the integration of MP-MRI into prostate adenocarcinoma clinical staging guidelines.

Identifiers

PMID38711959
PMCPMC11070813

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