JOURNAL ARTICLE

Surgery for pleural mesothelioma in multimodality setting: comparison between surgical techniques in a high-volume centre.

  • Published In: European Journal of Cardio-Thoracic Surgery, 2024, v. 66, n. 6. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Faccioli, Eleonora; Dell'Amore, Andrea; Lorenzoni, Giulia; Schiavon, Marco; Canu, Gianluca; Pasello, Giulia; Zambello, Giovanni; Sepulcri, Matteo; Sambataro, Viola; Labella, Francesco; Giraudo, Chiara; Gregori, Dario; Calabrese, Fiorella; Rea, Federico 3 of 3

Abstract

This article focuses on comparing two surgical techniques—extra-pleural pneumonectomy (EPP) and (extended) pleurectomy decortication [(E)PD]—for treating pleural mesothelioma (PM) within a multimodal treatment setting at a high-volume center. Analyzing data from 254 patients treated between 1994 and 2022, the study found no significant differences in long-term overall survival or recurrence rates between EPP and (E)PD, although EPP was associated with higher 90-day mortality. Pre-operative total lung capacity (TLC) was identified as a significant prognostic factor linked to reduced risk of death and recurrence, while disease burden predicted recurrence risk. The findings suggest that both surgical options remain viable when performed in expert centers with careful patient selection, emphasizing the importance of prognostic factors to optimize treatment outcomes in PM.

Additional Information

  • Source:European Journal of Cardio-Thoracic Surgery. 2024/12, Vol. 66, Issue 6, p1
  • Document Type:Article
  • Subject Area:Health and Medicine
  • Publication Date:2024
  • ISSN:1010-7940
  • DOI:10.1093/ejcts/ezae431
  • Accession Number:181897244
  • Copyright Statement:Copyright of European Journal of Cardio-Thoracic Surgery is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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