Evidence map›Paper›PMID 26587927›Full record

ArticleAJR. American journal of roentgenology2015

Prostate Cancer: Utility of Whole-Lesion Apparent Diffusion Coefficient Metrics for Prediction of Biochemical Recurrence After Radical Prostatectomy.

Andrew B Rosenkrantz, Justin M Ream, Paul Nolan, Henry Rusinek, Fang-Ming Deng, Samir S Taneja

Open access · greenAbstract read
In one paragraph

Article in AJR. American journal of roentgenology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
4.1field-weighted citation impact, top 5% 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

16 citing papers in PubMed, 47 citations in OpenAlex.

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  11. Background, current role, and potential applications of radiogenomics.Journal of magnetic resonance imaging : JMRI · 2018
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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

6 authors at 1 institution in 1 country.

Andrew B Rosenkrantz1 Department of Radiology, Center for Biomedical Imaging, NYU School of Medicine, NYU Langone Medical Center, 660 First Ave, 3rd Fl, New York, NY 10016.
Justin M Ream1 Department of Radiology, Center for Biomedical Imaging, NYU School of Medicine, NYU Langone Medical Center, 660 First Ave, 3rd Fl, New York, NY 10016.
Paul Nolan1 Department of Radiology, Center for Biomedical Imaging, NYU School of Medicine, NYU Langone Medical Center, 660 First Ave, 3rd Fl, New York, NY 10016.
Henry Rusinek1 Department of Radiology, Center for Biomedical Imaging, NYU School of Medicine, NYU Langone Medical Center, 660 First Ave, 3rd Fl, New York, NY 10016.
Fang-Ming Deng2 Department of Pathology, NYU School of Medicine, NYU Langone Medical Center, New York, NY.
Samir S Taneja3 Department of Urology, Division of Urologic Oncology, NYU School of Medicine, NYU Langone Medical Center, New York, NY.
NYU Langone Health · US

Funding

Vaccine FacilityP30CA016087 · NCI · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI ADRIANA HEGUY · 1985 to 2026
$83.1M
NCI NIH HHS P30 CA016087
6 · The paper itself

Abstract

objectiveThe purpose of this study was to investigate the additional value of whole-lesion histogram apparent diffusion coefficient (ADC) metrics, when combined with standard pathologic features, in prediction of biochemical recurrence (BCR) after radical prostatectomy for prostate cancer. MATERIALS AND

methodsThe study included 193 patients (mean age, 61 ± 7 years) who underwent 3-T MRI with DWI (b values, 50 and 1000 s/mm(2)) before prostatectomy. Histogram metrics were derived from 3D volumes of interest encompassing the entire lesion on ADC maps. Pathologic features from radical prostatectomy and subsequent BCR were recorded for each patient. The Fisher exact test and Mann-Whitney test were used to compare ADC-based metrics and pathologic features between patients with and patients without BCR. Stepwise logistic regression analysis was used to construct multivariable models for prediction of BCR, which were assessed by ROC analysis.

resultsBCR occurred in 16.6% (32/193) of patients. Variables significantly associated with BCR included primary Gleason grade, Gleason score, extraprostatic extension, seminal vesicle invasion, positive surgical margin, preoperative prostate-specific antigen level, MRI tumor volume, mean whole-lesion ADC, entropy ADC, and mean ADC of the bottom 10th, 10-25th, and 25-50th percentiles (p ≤ 0.019). Significant independent predictors of BCR at multivariable analysis were primary Gleason grade, extraprostatic extension, mean of the bottom 10th percentile ADC, and entropy ADC (p = 0.002-0.037). The AUC of this multivariable model was 0.94 for prediction of BCR; the AUC of pathologic features alone was 0.89 (p = 0.001).

conclusionA model integrating whole-lesion ADC metrics had significantly higher performance for prediction of BCR than did standard pathologic features alone and may help guide postoperative prognostic assessments and decisions regarding adjuvant therapy.

Indexed as

ProstatectomyAdultAgedAged, 80 and overContrast MediaDiffusion Magnetic Resonance ImagingHumansMaleMiddle AgedNeoplasm GradingNeoplasm InvasivenessNeoplasm Recurrence, LocalProstatic NeoplasmsContrast Mediaapparent diffusion coefficientDWIMRIprostate cancerradical prostatectomy

Identifiers

PMID26587927
PMCPMC4691847
OpenAlexW2204612330

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.