Evidence map›Paper›PMID 39143249›Full record

ArticleEuropean radiology2025

Are there features that can predict the unresectability of pleural mesothelioma?

Maria Mayoral, Jose Arimateia Batista Araujo-Filho, Kay See Tan, Eduardo Ortiz, Prasad S Adusumilli, Valerie Rusch, Marjorie Zauderer, Michelle S Ginsberg

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Article in European radiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Maria MayoralDepartment of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA. mayoralm@mskcc.org.ORCID http://orcid.org/0000-0003-0108-3226
Jose Arimateia Batista Araujo-FilhoDepartment of Radiology, Hospital Sirio-Libanes, 91 Dona Adma Jafet street, São Paulo, 01308-050, Brazil.
Kay See TanDepartment of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA.
Eduardo OrtizDepartment of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA.
Prasad S AdusumilliDepartment of Surgery, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA.
Valerie RuschDepartment of Surgery, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA.
Marjorie Zauderer *Department of Medical Oncology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA.
Michelle S Ginsberg *Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThe current clinical staging of pleural mesothelioma (PM) is often discordant with the pathologic staging. This study aimed to identify clinical and radiological features that could help predict unresectability in PM.

methodsTwenty-two descriptive radiologic features were retrospectively evaluated on preoperative computed tomography (CT) and/or positron emission tomography/CT (PET/CT) performed in patients with presumably resectable PM who underwent surgery. Measurements of maximum and sum pleural thickness at three levels of the thorax (upper, middle, and lower) were taken and stratified based on the cutpoints provided by the International Association for the Study of Lung Cancer (IASLC). Clinical and radiological features, including clinical-stage, were compared between resectable and unresectable tumors by univariate analysis and logistic regression modeling.

resultsOf 133 patients, 69/133 (52%) had resectable and 64/133 (48%) had unresectable PM. Asbestos exposure (p = 0.005), neoadjuvant treatment (p = 0.001), clinical T-stage (p < 0.0001), all pleural thickness measurements (p < 0.05), pleural thickness pattern (p < 0.0001) and degree (p = 0.033), lung invasion (p = 0.004), extrapleural space obliteration (p < 0.0001), extension to subphrenic space (p = 0.0004), and two combination variables representing extensive diaphragmatic contact and/or chest wall involvement (p = 0.002) and mediastinal invasion (p < 0.0001) were significant predictors at univariate analysis. At multivariable analysis, all models achieved a strong diagnostic performance (area under the curve (AUC) > 0.8). The two best-performing models were one that included the upper-level maximum pleural thickness, extrapleural space obliteration, and mediastinal infiltration (AUC = 0.876), and another that integrated clinical variables and radiological assessment through the clinical T-stage (AUC = 0.879).

conclusionSelected clinical and radiologic features, including pleural thickness measurements, appear to be strong predictors of unresectability in PM. CLINICAL RELEVANCE STATEMENT: A more accurate prediction of unresectability in the preoperative assessment of patients with pleural mesothelioma may avoid unnecessary surgery and prompt initiation of nonsurgical treatments. KEY POINTS: About half of pleural mesothelioma patients are reported to receive an incorrect disease stage preoperatively. Eleven features identified as predictors of unresectability were included in strongly performing predictive models. More accurate preoperative staging will help clinicians and patients choose the most appropriate treatments.

Indexed as

Lung NeoplasmsMesotheliomaPleural NeoplasmsPositron Emission Tomography Computed TomographyTomography, X-Ray ComputedAdultAgedAged, 80 and overFemaleHumansMaleMesothelioma, MalignantMiddle AgedNeoplasm StagingRetrospective StudiesMesotheliomaNeoplasm stagingThoracic wallTomography

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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.