Evidence map›Paper›PMID 40159431›Full record

Observational studyCancer2025

International multispecialty expert physician preoperative identification of extranodal extension in patients with oropharyngeal cancer using computed tomography: Prospective blinded human inter-observer performance evaluation.

Onur Sahin, Serageldin Kamel, Kareem A Wahid, Cem Dede, Nicolette Taku, Renjie He, Mohamed A Naser, Christina S Sharafi, Antti Mäkitie, Benjamin H Kann and 37 more

Abstract readObservational Study
PubMed Full text at PMC Publisher
In one paragraph

Observational study in Cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
–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

8 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Review
  4. Review
  5. Review
  6. Review
  7. Article
  8. Prediction of extranodal extension in head and neck squamous cell carcinoma by CT images using an evolutionary learning model.Cancer imaging : the official publication of the International Cancer Imaging Society · 2023
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

47 authors.

Onur SahinThe University of Texas MD Anderson Cancer Center, Houston, Texas, USA.ORCID https://orcid.org/0000-0003-2191-5659
Serageldin KamelThe University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Kareem A WahidThe University of Texas MD Anderson Cancer Center, Houston, Texas, USA.ORCID https://orcid.org/0000-0002-0503-0175
Cem DedeThe University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Nicolette TakuThe University of Texas MD Anderson Cancer Center, Houston, Texas, USA.ORCID https://orcid.org/0000-0003-2710-9404
Renjie HeThe University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Mohamed A NaserThe University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Christina S SharafiThe University of Texas MD Anderson Cancer Center, Houston, Texas, USA.ORCID https://orcid.org/0000-0002-7560-2204
Antti MäkitieUniversity of Helsinki and Helsinki University Hospital, Helsinki, Finland.
Benjamin H KannBrigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts, USA.
Kimmo KaskiAalto University, Espoo, Finland.
Jaakko SahlstenAalto University, Espoo, Finland.
Joel JaskariAalto University, Espoo, Finland.
Moran AmitThe University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Gregory M ChronowskiThe University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Eduardo M DiazThe University of Texas MD Anderson Cancer Center, Houston, Texas, USA.ORCID https://orcid.org/0000-0001-7268-5166
Adam S GardenThe University of Texas MD Anderson Cancer Center, Houston, Texas, USA.ORCID https://orcid.org/0000-0001-7926-2641
Ryan P GoepfertThe University of Texas MD Anderson Cancer Center, Houston, Texas, USA.ORCID https://orcid.org/0000-0002-3291-841X
Jeffrey P GuenetteBrigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts, USA.ORCID https://orcid.org/0000-0002-4684-5469
G Brandon GunnThe University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Jussi HirvonenTampere University, Faculty of Medicine and Health Technology and Tampere University Hospital, Tampere, Finland.
Frank HoebersBrigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts, USA.
Katherine A HutchesonThe University of Texas MD Anderson Cancer Center, Houston, Texas, USA.ORCID https://orcid.org/0000-0003-3710-5706
Nandita Guha-ThakurtaThe University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Jason JohnsonThe University of Texas MD Anderson Cancer Center, Houston, Texas, USA.ORCID https://orcid.org/0000-0001-7724-5784
Diana KayaThe University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Shekhar D KhanparaThe University of Texas MD Anderson Cancer Center, Houston, Texas, USA.ORCID https://orcid.org/0000-0002-9127-196X
Kristofer NymanUniversity of Helsinki and Helsinki University Hospital, Helsinki, Finland.ORCID https://orcid.org/0000-0003-4150-3141
Stephen Y LaiThe University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Miriam LangoThe University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Kim O LearnedThe University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Anna LeeThe University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Carol M LewisThe University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Anastasios ManiakasThe University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Amy C MorenoThe University of Texas MD Anderson Cancer Center, Houston, Texas, USA.ORCID https://orcid.org/0000-0001-6762-6807
Jeffrey N MyersThe University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Jack PhanThe University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Kristen B PytyniaThe University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
David I RosenthalThe University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Vlad C SandulacheDepartment of Otolaryngology Head and Neck Surgery, Baylor College of Medicine, Houston, Texas, USA.
Dawid SchellingerhoutThe University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Shalin J ShahThe University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Andrew G SikoraThe University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Abdallah S R MohamedThe University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Melissa M ChenThe University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Clifton D FullerThe University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Multidisciplinary Oropharyngeal Cancer Extra‐Nodal Extension (OPC ENE) Assessment Working Group

Funding

Tumor Evolution and Metastasis ProgramP30CA016672 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI DIANE BODURKA · 1985 to 2026
$290.8M
Image Guided Cancer Therapy Training ProgramT32CA261856 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Kristy Brock, Clifton David Fuller · 2022 to 2026
$1.2M
Development of an artificial intelligence-driven, imaging-based platform for pretreatment identification of extranodal extension in head and neck cancerK08DE030216 · NIDCR · BRIGHAM AND WOMEN'S HOSPITAL · PI KANN, BENJAMIN HARRIS · 2021 to 2025
$841k
Rapid Anatomic and Quantitative MR Imaging of the Skull Base and FaceK08EB034299 · NIBIB · BRIGHAM AND WOMEN'S HOSPITAL · PI Jeffrey P Guenette · 2024 to 2026
$574k
Probabilistic Deep Learning Cervical Lymph-Node Auto-Segmentation For Imaging-enhanced Evaluation of Extracapsular Extension Risk (PDL-CLASIFIER)R03DE033550 · NIDCR · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI FULLER, CLIFTON DAVID, NASER, MOHAMED · 2024 to 2025
$499k
Multiparametric Magnetic Resonance Imaging Artificial Intelligence Pipeline for Oropharyngeal Cancer Radiotherapy Treatment GuidanceF31DE031502 · NIDCR · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI WAHID, KAREEM · 2021 to 2023
$68k
Academy of Finland 345449American Legion Auxiliary Fellowship in Cancer ResearchCare and Equity in Radiology Research Academic Fellowship through the Association of University RadiologistsCharles and Daneen Stiefel Center for Head and Neck Cancer Oropharyngeal Cancer Research ProgramDr. John J. Kopchick Fellowship through The University of Texas MD Anderson UTHealth Graduate School of Biomedical SciencesFinska LäkaresällskapetImage Guided Cancer Therapy T32 Training Program Fellowship T32CA261856MD Anderson Cancer CenterNational Institute of Biomedical Imaging and Bioengineering K08 Grant K08EB034299NCI NIH HHS P30 CA016672NCI NIH HHS P30CA016672NCI NIH HHS T32 CA261856NIBIB NIH HHS K08 EB034299NIDCR NIH HHS F31 DE031502NIDCR NIH HHS K08 DE030216NIDCR NIH HHS R03 DE033550NIHNIH/National Institute for Dental and Craniofacial Research F31 Fellowship F31DE031502NIH/National Institute for Dental and Craniofacial Research K08 Grant K08DE030216NIH/NCI Cancer Center Support Grant Image-Guided Biologically-Informed Therapy ProgramNIH/NIDCR R03 Grant R03DE033550Program in Image-Guided Cancer TherapySigrid Jusélius Foundation
6 · The paper itself

Abstract

backgroundPathologic extranodal extension (pENE) is a crucial prognostic factor in oropharyngeal cancer (OPC), but determining pENE from imaging has high inter-observer variability. The role of clinician specialty in the accuracy of imaging-detected extranodal extension (iENE) remains unclear. The purpose of this study is to assess the influence of clinician specialty on the accuracy of preoperative iENE detection in human papillomavirus (HPV)-positive OPC using computed tomography (CT) imaging.

methodsThis prospective observational study evaluated pretherapy CT images from 24 HPV-positive OPC patients (30 scans, including duplicates). Thirty-four expert observers (11 radiologists, 12 surgeons, 11 radiation oncologists) assessed iENE and reported radiologic criteria and confidence. Ground-truth pENE status was confirmed pathologically. Accuracy, sensitivity, specificity, area under the receiver operating characteristic curve, and Brier scores were compared across specialties. Logistic regression determined significant predictors of pENE, whereas Fleiss' kappa measured interobserver agreement.

resultsMedian accuracy was 0.57 (95% CI, 0.39-0.73), with no specialty showing performance beyond chance (median area under the receiver operating characteristic curve, 0.64). Minor differences were noted: surgeons had lower Brier scores (0.26 vs. 0.33, p < .01) and higher sensitivity (0.69 vs. 0.48) compared to radiologists and oncologists. Predictive signs included indistinct capsular contour and nodal necrosis. Interobserver agreement was weak (κ < 0.6).

conclusionsDiagnostic performance for iENE on CT in HPV-positive OPC remains poor across specialties, with high variability and low accuracy. These findings highlight the need for automated systems or improved imaging methods to enhance iENE assessments.

Indexed as

Extranodal ExtensionOropharyngeal NeoplasmsTomography, X-Ray ComputedAdultAgedFemaleHumansMaleMiddle AgedObserver VariationPapillomavirus InfectionsPreoperative CareProspective StudiesROC Curveextranodal extensionobserver variabilityoropharyngeal cancer

Identifiers

PMID40159431
PMCPMC12067423

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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.