Changes in Magnetic Resonance Imaging Using the Prostate Cancer Radiologic Estimation of Change in Sequential Evaluation Criteria to Detect Prostate Cancer Progression for Men on Active Surveillance.

Active surveillance Fusion biopsy Multiparametric magnetic resonance imaging Prostate Cancer Radiologic Estimation of Change in Sequential Evaluation Prostate cancer

Journal

European urology oncology
ISSN: 2588-9311
Titre abrégé: Eur Urol Oncol
Pays: Netherlands
ID NLM: 101724904

Informations de publication

Date de publication:
04 2021
Historique:
received: 26 06 2020
revised: 07 09 2020
accepted: 17 09 2020
entrez: 19 4 2021
pubmed: 20 4 2021
medline: 23 11 2021
Statut: ppublish

Résumé

The ability of serial magnetic resonance imaging (MRI) to capture pathologic progression during active surveillance (AS) remains in question. To determine whether changes in MRI are associated with pathologic progression for patients on AS. From July 2007 through January 2020, we identified all patients evaluated for AS at our institution. Following confirmatory biopsy, a total of 391 patients who underwent surveillance MRI and biopsy at least once were identified (median follow-up of 35.6 mo, interquartile range 19.7-60.6). All MRI intervals were scored using the "Prostate Cancer Radiologic Estimation of Change in Sequential Evaluation" (PRECISE) criteria, with PRECISE scores =4 considered a positive change in MRI. A generalized estimating equation-based logistic regression analysis was conducted for all intervals with a PRECISE score of <4 to determine the predictors of Gleason grade group (GG) progression despite stable MRI. A total of 621 MRI intervals were scored by PRECISE and validated by biopsy. The negative predictive value of stable MRI (PRECISE score <4) was greatest for detecting GG1 to?=?GG3 disease (0.94 [0.91-0.97]). If 2-yr surveillance biopsy were performed exclusively for a positive change in MRI, 3.7% (4/109) of avoided biopsies would have resulted in missed progression from GG1 to?=?GG3 disease. Prostate-specific antigen (PSA) density (odds ratio 1.95 [1.17-3.25], p?=? 0.01) was a risk factor for progression from GG1 to =GG3 disease despite stable MRI. In patients with GG1 disease and stable MRI (PRECISE score <4) on surveillance, grade progression to?=?GG3 disease is not common. In patients with grade progression detected on biopsy despite stable MRI, elevated PSA density appeared to be a risk factor for progression to?=?GG3 disease. For patients with low-risk prostate cancer on active surveillance, the risk of progressing to grade group 3 disease is low with a stable magnetic resonance image (MRI) after 2?yr. Having higher prostate-specific antigen density increases the risk of progression, despite having a stable MRI.

Sections du résumé

BACKGROUND
The ability of serial magnetic resonance imaging (MRI) to capture pathologic progression during active surveillance (AS) remains in question.
OBJECTIVE
To determine whether changes in MRI are associated with pathologic progression for patients on AS.
DESIGN, SETTING, AND PARTICIPANTS
From July 2007 through January 2020, we identified all patients evaluated for AS at our institution. Following confirmatory biopsy, a total of 391 patients who underwent surveillance MRI and biopsy at least once were identified (median follow-up of 35.6 mo, interquartile range 19.7-60.6).
OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS
All MRI intervals were scored using the "Prostate Cancer Radiologic Estimation of Change in Sequential Evaluation" (PRECISE) criteria, with PRECISE scores =4 considered a positive change in MRI. A generalized estimating equation-based logistic regression analysis was conducted for all intervals with a PRECISE score of <4 to determine the predictors of Gleason grade group (GG) progression despite stable MRI.
RESULTS AND LIMITATIONS
A total of 621 MRI intervals were scored by PRECISE and validated by biopsy. The negative predictive value of stable MRI (PRECISE score <4) was greatest for detecting GG1 to?=?GG3 disease (0.94 [0.91-0.97]). If 2-yr surveillance biopsy were performed exclusively for a positive change in MRI, 3.7% (4/109) of avoided biopsies would have resulted in missed progression from GG1 to?=?GG3 disease. Prostate-specific antigen (PSA) density (odds ratio 1.95 [1.17-3.25], p?=? 0.01) was a risk factor for progression from GG1 to =GG3 disease despite stable MRI.
CONCLUSIONS
In patients with GG1 disease and stable MRI (PRECISE score <4) on surveillance, grade progression to?=?GG3 disease is not common. In patients with grade progression detected on biopsy despite stable MRI, elevated PSA density appeared to be a risk factor for progression to?=?GG3 disease.
PATIENT SUMMARY
For patients with low-risk prostate cancer on active surveillance, the risk of progressing to grade group 3 disease is low with a stable magnetic resonance image (MRI) after 2?yr. Having higher prostate-specific antigen density increases the risk of progression, despite having a stable MRI.

Identifiants

pubmed: 33867045
pii: S2588-9311(20)30144-9
doi: 10.1016/j.euo.2020.09.004
pmc: PMC9310665
mid: NIHMS1817406
pii:
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

227-234

Subventions

Organisme : Intramural NIH HHS
ID : Z01 BC011081
Pays : United States
Organisme : Intramural NIH HHS
ID : ZID BC011242
Pays : United States
Organisme : Intramural NIH HHS
ID : Z01 BC010655
Pays : United States
Organisme : CCR NIH HHS
ID : HHSN261200800001C
Pays : United States
Organisme : Intramural NIH HHS
ID : ZIA BC012062
Pays : United States
Organisme : NCI NIH HHS
ID : HHSN261200800001E
Pays : United States
Organisme : Intramural NIH HHS
ID : ZIE SC000853
Pays : United States

Commentaires et corrections

Type : CommentIn

Informations de copyright

Copyright © 2020. Published by Elsevier B.V.

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Auteurs

Luke P O'Connor (LP)

Urologic Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.

Alex Z Wang (AZ)

Urologic Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.

Nitin K Yerram (NK)

Urologic Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.

Lori Long (L)

Division of Cancer Treatment and Diagnosis, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.

Michael Ahdoot (M)

Urologic Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.

Amir H Lebastchi (AH)

Urologic Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.

Sandeep Gurram (S)

Urologic Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.

Johnathan Zeng (J)

Center for Interventional Oncology, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.

Stephanie A Harmon (SA)

Clinical Research Directorate, Frederick National Laboratory for Cancer Research sponsored by the National Cancer Institute, Bethesda, MD, USA.

Sherif Mehralivand (S)

Molecular Imaging Program, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.

Maria J Merino (MJ)

Laboratory of Pathology, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.

Howard L Parnes (HL)

Division of Cancer Prevention, National Cancer Institutes, National Institutes of Health, Bethesda, MD, USA.

Peter L Choyke (PL)

Molecular Imaging Program, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.

Joanna H Shih (JH)

Division of Cancer Treatment and Diagnosis, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.

Bradford J Wood (BJ)

Center for Interventional Oncology, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.

Baris Turkbey (B)

Molecular Imaging Program, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.

Peter A Pinto (PA)

Urologic Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA. Electronic address: pintop@mail.nih.gov.

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Classifications MeSH