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dc.contributor.authorLlueca, Antoni
dc.contributor.authorSerra Rubert, Anna
dc.contributor.authorRivadulla, Isabel
dc.contributor.authorGomez, Luis
dc.contributor.authorEscrig-Sos, Javier
dc.contributor.authorMUAPOS (Multidisciplinary Unit of Abdominal Pelvic Oncology Surgery)
dc.date.accessioned2018-05-17T18:32:32Z
dc.date.available2018-05-17T18:32:32Z
dc.date.issued2018
dc.identifier.citationLLUECA, Antoni, et al. Prediction of suboptimal cytoreductive surgery in patients with advanced ovarian cancer based on preoperative and intraoperative determination of the peritoneal carcinomatosis index. World journal of surgical oncology, 2018, vol. 16, núm. 1, p.37ca_CA
dc.identifier.issn1477-7819
dc.identifier.urihttp://hdl.handle.net/10234/174734
dc.description.abstractBackground The peritoneal carcinomatosis index (PCI) can be used to quantify the tumor burden in patients with advanced ovarian cancer. The aim of the present study was to establish a predictive model for suboptimal cytoreductive surgery (SCS) (residual tumor of > 1 cm) using preoperative and intraoperative determination of the PCI. Methods In total, 110 consecutive patients treated for advanced ovarian cancer during a 4-year period in our institution were assessed. Eighty of these patients were eligible for primary debulking surgery and thus included in the present study. All data were prospectively collected and retrospectively evaluated. We determined the PCI both preoperatively and intraoperatively and assessed postoperative complications. Results A PCI of > 20 was the best cut-off with which to predict a risk of SCS among all three diagnostic techniques assessed in this study (computed tomography, laparoscopy, and laparotomy). Intraoperative PCI determination was associated with the lowest risk of false negatives for SCS when detecting a PCI of < 20. The combination of preoperative computed tomography and laparoscopy, when both techniques predicted SCS, was associated with the lowest risk of false positives for SCS when detecting a PCI of > 20. Conclusion The combination of computed tomography and laparoscopy to obtain the PCI can help to determine which patients with advanced ovarian cancer are suitable for primary debulking surgery and which should undergo neoadjuvant chemotherapy.ca_CA
dc.format.extent7 p.ca_CA
dc.format.mimetypeapplication/pdfca_CA
dc.language.isoengca_CA
dc.publisherBioMed Centralca_CA
dc.relation.isPartOfWorld journal of surgical oncology, 2018, vol. 16, núm. 1, p.37ca_CA
dc.rights© The Author(s). 2018 This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.ca_CA
dc.rightsAtribución 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-sa/4.0/*
dc.subjectadvanced ovarian cancerca_CA
dc.subjectcytoreductive surgeryca_CA
dc.subjectperitoneal carcinomatosis indexca_CA
dc.titlePrediction of suboptimal cytoreductive surgery in patients with advanced ovarian cancer based on preoperative and intraoperative determination of the peritoneal carcinomatosis indexca_CA
dc.typeinfo:eu-repo/semantics/articleca_CA
dc.identifier.doihttps://doi.org/10.1186/s12957-018-1339-0
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessca_CA
dc.relation.publisherVersionhttps://wjso.biomedcentral.com/articles/10.1186/s12957-018-1339-0ca_CA
dc.contributor.funderThis work received financial support from de Medtronic University Chair for Training and Surgical Research (University Jaume I (UJI), Castellon, Spain).ca_CA
dc.type.versioninfo:eu-repo/semantics/publishedVersionca_CA


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This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Excepto si se señala otra cosa, la licencia del ítem se describe como: © The Author(s). 2018 This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.