Evidence map›Paper›PMID 36973367›Full record

ArticleProstate cancer and prostatic diseases2023

Optimizing detection of clinically significant prostate cancer through nomograms incorporating mri, clinical features, and advanced serum biomarkers in biopsy naïve men.

Mohammad R Siddiqui, Eric V Li, Sai K S R Kumar, Anna Busza, Jasmine S Lin, Ashorne K Mahenthiran, Jonathan A Aguiar, Parth V Shah, Brandon Ansbro, Jordan M Rich and 8 more

Abstract read
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Article in Prostate cancer and prostatic diseases, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
8.0field-weighted citation impact, top 2% 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

22 citing papers in PubMed, 31 citations in OpenAlex.

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  11. Prostate cancer detection: achieving an optimal balance.Prostate cancer and prostatic diseases · 2025
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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

18 authors at 2 institutions in 1 country.

Mohammad R Siddiqui *Department of Urology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA. mohammad.siddiqui2@northwestern.edu.ORCID 0000-0001-8196-5864
Eric V Li *Department of Urology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
Sai K S R KumarDepartment of Urology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.ORCID 0000-0002-3577-3543
Anna BuszaDepartment of Urology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
Jasmine S LinDepartment of Urology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
Ashorne K MahenthiranDepartment of Urology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.ORCID 0000-0003-3409-2460
Jonathan A AguiarDepartment of Urology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
Parth V ShahDepartment of Urology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
Brandon AnsbroDepartment of Urology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
Jordan M RichDepartment of Urology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
Soliman A S MoatazDepartment of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
Mary-Kate KeeterDepartment of Urology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
Quan MaiDepartment of Urology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
Xinlei MiDepartment of Preventative Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
Jeffrey J TosoianDepartment of Urology, Vanderbilt University, Nashville, TN, USA.
Edward M SchaefferDepartment of Urology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.ORCID 0000-0003-0699-1899
Hiten D PatelDepartment of Urology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
Ashley E RossDepartment of Urology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.ORCID 0000-0001-7044-9688
Northwestern University · USVanderbilt University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo develop nomograms that predict the detection of clinically significant prostate cancer (csPCa, defined as ≥GG2 [Grade Group 2]) at diagnostic biopsy based on multiparametric prostate MRI (mpMRI), serum biomarkers, and patient clinicodemographic features. MATERIALS AND

methodsNomograms were developed from a cohort of biopsy-naïve men presenting to our 11-hospital system with prostate specific antigen (PSA) of 2-20 ng/mL who underwent pre-biopsy mpMRI from March 2018-June 2021 (n = 1494). The outcomes were the presence of csPCa and high-grade prostate cancer (defined as ≥GG3 prostate cancer). Using significant variables on multivariable logistic regression, individual nomograms were developed for men with total PSA, % free PSA, or prostate health index (PHI) when available. The nomograms were both internally validated and evaluated in an independent cohort of 366 men presenting to our hospital system from July 2021-February 2022.

results1031 of 1494 men (69%) underwent biopsy after initial evaluation with mpMRI, 493 (47.8%) of whom were found to have ≥GG2 PCa, and 271 (26.3%) were found to have ≥GG3 PCa. Age, race, highest PIRADS score, prostate health index when available, % free PSA when available, and PSA density were significant predictors of ≥GG2 and ≥GG3 PCa on multivariable analysis and were used for nomogram generation. Accuracy of nomograms in both the training cohort and independent cohort were high, with areas under the curves (AUC) of ≥0.885 in the training cohort and ≥0.896 in the independent validation cohort. In our independent validation cohort, our model for ≥GG2 prostate cancer with PHI saved 39.1% of biopsies (143/366) while only missing 0.8% of csPCa (1/124) with a biopsy threshold of 20% probability of csPCa.

conclusionsHere we developed nomograms combining serum testing and mpMRI to help clinicians risk stratify patients with elevated PSA of 2-20 ng/mL who are being considered for biopsy. Our nomograms are available at https://rossnm1.shinyapps.io/MynMRIskCalculator/ to aid with biopsy decisions.

Indexed as

Prostatic NeoplasmsBiopsyHumansImage-Guided BiopsyMagnetic Resonance ImagingMaleNomogramsProstate-Specific AntigenProstate-Specific Antigen

Identifiers

PMID36973367
OpenAlexW4361002504

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.