Evidence map›Paper›PMID 34757450›Full record

ArticleEuropean radiology2022

Pre-operative radiomics model for prognostication in resectable pancreatic adenocarcinoma with external validation.

Gerard M Healy, Emmanuel Salinas-Miranda, Rahi Jain, Xin Dong, Dominik Deniffel, Ayelet Borgida, Ali Hosni, David T Ryan, Nwabundo Njeze, Anne McGuire and 6 more

Abstract readMulticenter Study
PubMed Publisher
In one paragraph

Article in European radiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.

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

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

  1. Artificial Intelligence in Pancreatic Imaging: A Systematic Review.United European gastroenterology journal · 2025
    Pooled it
  2. Review
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  12. A clinical-radiomics nomogram based on dual-layer spectral detector CT to predict cancer stage in pancreatic ductal adenocarcinoma.Cancer imaging : the official publication of the International Cancer Imaging Society · 2024
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  13. Article
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  15. Preoperative prediction of early recurrence in resectable pancreatic cancer integrating clinical, radiologic, and CT radiomics features.Cancer imaging : the official publication of the International Cancer Imaging Society · 2024
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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

16 authors.

Gerard M HealyJoint Department of Medical Imaging, University Health Network, Sinai Health System and Women's College Hospital, University of Toronto, Toronto, ON, Canada.
Emmanuel Salinas-MirandaLunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, Canada.
Rahi JainDepartment of Biostatistics, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada.
Xin DongLunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, Canada.
Dominik DeniffelLunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, Canada.
Ayelet BorgidaDepartment of Medical Oncology and Hematology, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada.
Ali HosniRadiation Medicine Program, Princess Margaret Cancer Centre, Department of Radiation Oncology, University of Toronto, Toronto, ON, Canada.
David T RyanDepartment of Radiology, St Vincent's University Hospital, Dublin, Ireland.
Nwabundo NjezeNational Surgical Centre for Pancreatic Cancer, St. Vincent's University Hospital, Dublin, Ireland.
Anne McGuireNational Surgical Centre for Pancreatic Cancer, St. Vincent's University Hospital, Dublin, Ireland.
Kevin C ConlonNational Surgical Centre for Pancreatic Cancer, St. Vincent's University Hospital, Dublin, Ireland.
Jonathan D DoddDepartment of Radiology, St Vincent's University Hospital, Dublin, Ireland.
Edmund Ronan RyanDepartment of Radiology, St Vincent's University Hospital, Dublin, Ireland.
Robert C GrantDepartment of Medical Oncology and Hematology, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada.
Steven GallingerLunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, Canada.
Masoom A HaiderJoint Department of Medical Imaging, University Health Network, Sinai Health System and Women's College Hospital, University of Toronto, Toronto, ON, Canada. mahaider@radfiler.com.ORCID http://orcid.org/0000-0002-7165-8315

Funding

Deutsche Forschungsgemeinschaft DE 3207/1-1
6 · The paper itself

Abstract

objectivesIn resectable pancreatic ductal adenocarcinoma (PDAC), few pre-operative prognostic biomarkers are available. Radiomics has demonstrated potential but lacks external validation. We aimed to develop and externally validate a pre-operative clinical-radiomic prognostic model.

methodsRetrospective international, multi-center study in resectable PDAC. The training cohort included 352 patients (pre-operative CTs from five Canadian hospitals). Cox models incorporated (a) pre-operative clinical variables (clinical), (b) clinical plus CT-radiomics, and (c) post-operative TNM model, which served as the reference. Outcomes were overall (OS)/disease-free survival (DFS). Models were assessed in the validation cohort from Ireland (n = 215, CTs from 34 hospitals), using C-statistic, calibration, and decision curve analyses.

resultsThe radiomic signature was predictive of OS/DFS in the validation cohort, with adjusted hazard ratios (HR) 2.87 (95% CI: 1.40-5.87, p < 0.001)/5.28 (95% CI 2.35-11.86, p < 0.001), respectively, along with age 1.02 (1.01-1.04, p = 0.01)/1.02 (1.00-1.04, p = 0.03). In the validation cohort, median OS was 22.9/37 months (p = 0.0092) and DFS 14.2/29.8 (p = 0.0023) for high-/low-risk groups and calibration was moderate (mean absolute errors 7%/13% for OS at 3/5 years). The clinical-radiomic model discrimination (C = 0.545, 95%: 0.543-0.546) was higher than the clinical model alone (C = 0.497, 95% CI 0.496-0.499, p < 0.001) or TNM (C = 0.525, 95% CI: 0.524-0.526, p < 0.001). Despite superior net benefit compared to the clinical model, the clinical-radiomic model was not clinically useful for most threshold probabilities.

conclusionA multi-institutional pre-operative clinical-radiomic model for resectable PDAC prognostication demonstrated superior net benefit compared to a clinical model but limited clinical utility at external validation. This reflects inherent limitations of radiomics for PDAC prognostication, when deployed in real-world settings. KEY POINTS: • At external validation, a pre-operative clinical-radiomics prognostic model for pancreatic ductal adenocarcinoma (PDAC) outperformed pre-operative clinical variables alone or pathological TNM staging. • Discrimination and clinical utility of the clinical-radiomic model for treatment decisions remained low, likely due to heterogeneity of CT acquisition parameters. • Despite small improvements, prognosis in PDAC using state-of-the-art radiomics methodology remains challenging, mostly owing to its low discriminative ability. Future research should focus on standardization of CT protocols and acquisition parameters.

Indexed as

AdenocarcinomaCarcinoma, Pancreatic DuctalPancreatic NeoplasmsCanadaHumansInfantRetrospective StudiesExternal validationPancreatic adenocarcinomaPre-operativeRadiomicsSurvival

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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.