Evidence map›Paper›PMID 40694783›Full record

ArticleJCO clinical cancer informatics2025

Computational Morphological Assessment of Bladder Cancer Tissue Is Prognostic of Recurrence and Overall Survival Following Transurethral Resection.

Patrick Leo, Behtash G Nezami, Mahmut Akgul, Naoto Tokuyama, Xavier Farré, Robin Elliott, Vidya S Viswanathan, Holly Harper, Gregory MacLennan, Anant Madabhushi

Abstract read
In one paragraph

Article in JCO clinical cancer informatics, 2025. 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

10 authors.

Patrick LeoDepartment of Biomedical Engineering, Case Western Reserve University, Cleveland, OH.ORCID 0000-0002-2248-0610
Behtash G NezamiNorthwestern University Feinberg School of Medicine, Chicago, IL.ORCID 0000-0002-6616-584X
Mahmut AkgulDepartment of Pathology, Albany Medical Center, Albany, NY.ORCID 0000-0003-0929-0940
Naoto TokuyamaDepartment of Biomedical Engineering, Emory University, Atlanta, GA.ORCID 0000-0002-7784-4901
Xavier FarréPublic Health Agency of Catalonia, Lleida, Spain.ORCID 0000-0001-8702-4643
Robin ElliottCarolinas Pathology Group, Charlotte, NC.
Vidya S ViswanathanDepartment of Biomedical Engineering, Emory University, Atlanta, GA.ORCID 0000-0003-1578-6248
Holly HarperDepartment of Pathology, University Hospitals Cleveland Medical Center, Cleveland, OH.ORCID 0009-0001-2783-0763
Gregory MacLennanDepartment of Pathology, University Hospitals Cleveland Medical Center, Cleveland, OH.
Anant MadabhushiDepartment of Biomedical Engineering, Emory University, Atlanta, GA.ORCID 0000-0002-5741-0399

Funding

Prostate Cancer Biomarker and Imaging Validation Alliance: Emory University, University of Alabama Birmingham, and University of Texas SouthwesternU01CA113913 · NCI · EMORY UNIVERSITY · PI Martin G. Sanda · 2005 to 2026
$16.4M
P-CARRS-BRAIN: Multi-domain (genetic, socio-behavioral, vascular) risk factors and prediction of Alzheimer’s Disease continuum in South Asians in IndiaR01AG089759 · NIA · EMORY UNIVERSITY · PI Suvarna Alladi, ALLAN I LEVEY · 2024 to 2026
$12.8M
KPMP Kidney Mapping and Atlas Project (KMAP)U01DK133090 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Jonathan Himmelfarb, Matthias Kretzler · 2022 to 2026
$10.4M
Spatial Transcriptomics Explorer (STE): An open-source resource for visualizing spatial gene expression dataU24CA274494 · NCI · SAGE BIONETWORKS · PI Jineta Banerjee, Susheel Varma · 2022 to 2026
$10.1M
Pathology CoreU54CA254566 · NCI · CASE WESTERN RESERVE UNIVERSITY · PI MADABHUSHI, ANANT · 2020 to 2024
$5.0M
Computational Pathology of Proteinuric DiseasesR01DK118431 · NIDDK · UNIVERSITY OF PENNSYLVANIA · PI BARISONI, LAURA MARIACHIARA, HODGIN, JEFFREY BENTON · 2018 to 2025
$3.6M
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
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
Prognostic and Predictive Digital Tissue Image Assay for Prostate CancerR01CA268287 · NCI · EMORY UNIVERSITY · PI GUPTA, SHILPA, LAL, PRITI · 2022 to 2025
$3.0M
RADIOMIC APPROACHES TO IMPROVE TARGETING FOR ATRIAL FIBRILLATION CATHETER ABLATIONR01HL158071 · NHLBI · CLEVELAND CLINIC LERNER COM-CWRU · PI BARNARD, JOHN, CHUNG, MINA KAY · 2021 to 2024
$2.9M
BLRD VA I01 BX004121BLRD VA I01 BX006020BLRD VA IK6 BX006185CSRD VA I01 CX002622CSRD VA I01 CX002776NCI NIH HHS R01 CA216579NCI NIH HHS R01 CA220581NCI NIH HHS R01 CA249992NCI NIH HHS R01 CA257612NCI NIH HHS R01 CA264017NCI NIH HHS R01 CA268287NCI NIH HHS U01 CA113913NCI NIH HHS U01 CA239055NCI NIH HHS U01 CA269181NCI NIH HHS U24 CA274494NCI NIH HHS U54 CA254566NHLBI NIH HHS R01 HL151277NHLBI NIH HHS R01 HL158071NIAID NIH HHS R01 AI175555NIA NIH HHS R01 AG089759NIDCR NIH HHS R21 DE032344NIDDK NIH HHS R01 DK118431NIDDK NIH HHS U01 DK133090NLM NIH HHS R01 LM013864
6 · The paper itself

Abstract

purposeCurrent risk assessment tools for bladder cancer following transurethral resection of the bladder tumor (TURBT) depend on pathological examination of resected tissue, with the consequent intra- and inter-reviewer variability. Improved prognostic tools could enable increased monitoring and aggressive interventions for high-risk patients while reducing the frequency of invasive testing for low-risk patients.

methodsWe present an automated tumor risk assessment method based on quantitative features of nuclear pleomorphism and polarity extracted from digitized hematoxylin and eosin slides and compared this model with pathologist grading. Our model, incorporating six features, was trained to estimate overall survival risk on n = 189 patients and validated for recurrence prognosis on an independent validation set of n = 151 patients.

resultsThe model had an accuracy of 0.73 (95% CI, 0.66 to 0.81) in identifying patients who would have recurrence within 5 years of surgery. Within the validation set was a consensus set of patients (n = 94) on which three pathologists independently assigned the same grade and a nonconsensus set (n = 57) where they did not. The model had similar performance in the consensus and nonconsensus set, with accuracies of 0.70 (95% CI, 0.61 to 0.80) and 0.78 (95% CI, 0.67 to 0.89), respectively, and was able to recapitulate pathologist scoring on the consensus set (accuracy = 0.76).

conclusionThe results of this study suggest the need to incorporate both computerized analysis and pathologist grading into post-TURBT treatment planning.

Indexed as

Neoplasm Recurrence, LocalUrinary Bladder NeoplasmsAgedAged, 80 and overCystectomyFemaleHumansMaleMiddle AgedNeoplasm GradingPrognosisRisk Assessment

Identifiers

PMID40694783
PMCPMC12303250

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.