Evidence map›Paper›PMID 33941504›Full record

ArticleEuropean urology focus2021

Computationally Derived Cribriform Area Index from Prostate Cancer Hematoxylin and Eosin Images Is Associated with Biochemical Recurrence Following Radical Prostatectomy and Is Most Prognostic in Gleason Grade Group 2.

Patrick Leo, Sacheth Chandramouli, Xavier Farré, Robin Elliott, Andrew Janowczyk, Kaustav Bera, Pingfu Fu, Nafiseh Janaki, Ayah El-Fahmawi, Mohammed Shahait and 12 more

Abstract read
In one paragraph

Article in European urology focus, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing 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

25 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. A Computational Pathology Model to Predict Docetaxel Benefit in Localized High-Risk and Metastatic Prostate Cancer.Clinical cancer research : an official journal of the American Association for Cancer Research · 2026
    Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. Review
  17. Artificial intelligence applications in prostate cancer.Prostate cancer and prostatic diseases · 2024
    Review
  18. Article
  19. Review
  20. 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

22 authors.

Patrick LeoDepartment of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA.
Sacheth ChandramouliDepartment of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA.
Xavier FarréPublic Health Agency of Catalonia, Lleida, Catalonia, Spain.
Robin ElliottDepartment of Pathology, University Hospitals Cleveland Medical Center, Cleveland, OH, USA.
Andrew JanowczykDepartment of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA; Department of Oncology, Lausanne University Hospital and Lausanne University, Lausanne, Switzerland.
Kaustav BeraDepartment of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA.
Pingfu FuDepartment of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, USA.
Nafiseh JanakiDepartment of Pathology, Harvard Medical School, Brigham and Women's Hospital, Boston, MA, USA.
Ayah El-FahmawiDepartment of Urology, Penn Presbyterian Medical Center, Philadelphia, PA, USA.
Mohammed ShahaitDepartment of Urology, Penn Presbyterian Medical Center, Philadelphia, PA, USA.
Jessica KimDepartment of Urology, Penn Presbyterian Medical Center, Philadelphia, PA, USA.
David LeeDepartment of Urology, Penn Presbyterian Medical Center, Philadelphia, PA, USA.
Kosj YamoahDepartment of Radiation Oncology, Moffitt Cancer Center, University of South Florida, Tampa, FL, USA.
Timothy R RebbeckT.H. Chan School of Public Health and Dana Farber Cancer Institute, Harvard University, Boston, MA, USA.
Francesca KhaniDepartments of Pathology and Laboratory Medicine and Urology, Weill Cornell Medicine, New York, NY, USA.
Brian D RobinsonDepartments of Pathology and Laboratory Medicine and Urology, Weill Cornell Medicine, New York, NY, USA.
Natalie N C ShihDepartment of Pathology, University of Pennsylvania, Philadelphia, PA, USA.
Michael FeldmanDepartment of Pathology, University of Pennsylvania, Philadelphia, PA, USA.
Sanjay GuptaDepartment of Urology, Case Western Reserve University, Cleveland, OH, USA; Louis Stokes Cleveland Veterans Administration Medical Center, Cleveland, OH, USA.
Jesse McKenneyDepartment of Anatomic Pathology, Cleveland Clinic, Cleveland, OH, USA.
Priti LalDepartment of Pathology, University of Pennsylvania, Philadelphia, PA, USA.
Anant MadabhushiDepartment of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA; Louis Stokes Cleveland Veterans Administration Medical Center, Cleveland, OH, USA. Electronic address: anant.madabhushi@case.edu.

Funding

Clinical and Translational Science Collaborative of ClevelandUL1TR002548 · NCATS · CASE WESTERN RESERVE UNIVERSITY · PI MCCOMSEY, GRACE A · 2018 to 2022
$35.5M
Pathology CoreU54CA254566 · NCI · CASE WESTERN RESERVE UNIVERSITY · PI WILLIS, JOSEPH EDWARD · 2020 to 2024
$5.0M
Computer-Assisted Histologic Evaluation of Cardiac Allograft RejectionR01HL151277 · NHLBI · UNIVERSITY OF PENNSYLVANIA · PI MADABHUSHI, ANANT, MARGULIES, KENNETH BER · 2020 to 2023
$3.2M
Oral Cavity Quantitative Histomorphometric Risk Classifier (OHbIC) in Oral Cavity Squamous Cell Carcinoma (OC-SCC)R01CA249992 · NCI · EMORY UNIVERSITY · PI LEWIS, JAMES, MADABHUSHI, ANANT · 2021 to 2025
$3.2M
Computerized histologic image predictor of cancer outcomeR01CA202752 · NCI · CASE WESTERN RESERVE UNIVERSITY · PI FELDMAN, MICHAEL D, GANESAN, SHRIDAR · 2016 to 2020
$3.1M
Quantitative Histomorphometric Risk Classifier (QuHbIC) in HPV + Oropharyngeal CarcinomaR01CA220581 · NCI · CASE WESTERN RESERVE UNIVERSITY · PI KOYFMAN, SHLOMO, LEWIS, JAMES · 2018 to 2023
$3.1M
Computerized Histologic Risk Predictor (CHiRP) for Early Stage Lung CancersR01CA216579 · NCI · EMORY UNIVERSITY · PI FU, PINGFU, LLOYD, MARK · 2018 to 2023
$3.1M
MR Fingerprinting and Computerized Decision Support for Prostate CancerR01CA208236 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI GULANI, VIKAS, PONSKY, LEE EVAN · 2017 to 2022
$3.0M
Pathology Image Informatics Platform for visualization, analysis and managementU24CA199374 · NCI · CASE WESTERN RESERVE UNIVERSITY · PI GURCAN, METIN NAFI, MADABHUSHI, ANANT · 2015 to 2019
$2.9M
Novel Radiomics for Predicting Response to Immunotherapy for Lung CancerR01CA257612 · NCI · EMORY UNIVERSITY · PI Anant Madabhushi, Vamsidhar Velcheti · 2021 to 2026
$2.7M
RadxTools for assessing tumor treatment response on imagingU01CA248226 · NCI · CASE WESTERN RESERVE UNIVERSITY · PI TIWARI, PALLAVI, VISWANATH, SATISH EASWAR · 2020 to 2022
$1.4M
HistoTools: A suite of digital pathology tools for quality control, annotation and dataset identificationU01CA239055 · NCI · CASE WESTERN RESERVE UNIVERSITY · PI JANOWCZYK, ANDREW ROBERT, MADABHUSHI, ANANT · 2019 to 2022
$1.0M
BLRD VA I01 BX004121BLRD VA IK6 BX006185NCATS NIH HHS UL1 TR002548NCI NIH HHS R01 CA202752NCI NIH HHS R01 CA208236NCI NIH HHS R01 CA216579NCI NIH HHS R01 CA220581NCI NIH HHS R01 CA249992NCI NIH HHS R01 CA257612NCI NIH HHS U01 CA239055NCI NIH HHS U01 CA248226NCI NIH HHS U24 CA199374NCI NIH HHS U54 CA254566NCRR NIH HHS C06 RR012463NHLBI NIH HHS R01 HL151277NIBIB NIH HHS R43 EB028736
6 · The paper itself

Abstract

backgroundThe presence of invasive cribriform adenocarcinoma (ICC), an expanse of cells containing punched-out lumina uninterrupted by stroma, in radical prostatectomy (RP) specimens has been associated with biochemical recurrence (BCR). However, ICC identification has only moderate inter-reviewer agreement.

objectiveTo investigate quantitative machine-based assessment of the extent and prognostic utility of ICC, especially within individual Gleason grade groups. DESIGN, SETTING, AND

participantsA machine learning approach was developed for ICC segmentation using 70 RP patients and validated in a cohort of 749 patients from four sites whose median year of surgery was 2007 and with median follow-up of 28 mo. ICC was segmented on one representative hematoxylin and eosin RP slide per patient and the fraction of tumor area composed of ICC, the cribriform area index (CAI), was measured. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: The association between CAI and BCR was measured in terms of the concordance index (c index) and hazard ratio (HR). RESULTS AND LIMITATIONS: CAI was correlated with BCR (c index 0.62) in the validation set of 411 patients with ICC morphology, especially those with Gleason grade group 2 cancer (n = 192; c index 0.66), and was less prognostic when patients without ICC were included (c index 0.54). A doubling of CAI in the group with ICC morphology was prognostic after controlling for Gleason grade, surgical margin positivity, preoperative prostate-specific antigen level, pathological T stage, and age (HR 1.19, 95% confidence interval 1.03-1.38; p = 0.018).

conclusionsAutomated image analysis and machine learning could provide an objective, quantitative, reproducible, and high-throughput method of quantifying ICC area. The performance of CAI for grade group 2 cancer suggests that for patients with little Gleason 4 pattern, the ICC fraction has a strong prognostic role. PATIENT SUMMARY: Machine-based measurement of a specific cell pattern (cribriform; sieve-like, with lots of spaces) in images of prostate specimens could improve risk stratification for patients with prostate cancer. In the future, this could help in expanding the criteria for active surveillance.

Indexed as

ProstateProstatic NeoplasmsEosine Yellowish-(YS)HematoxylinHumansMaleNeoplasm Recurrence, LocalPrognosisProstatectomyEosine Yellowish-(YS)HematoxylinBiochemical recurrenceCribriformDigital pathologyGleason gradingMachine learningProstate cancer

Identifiers

PMID33941504
PMCPMC8419103

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