Prediction of suboptimal cytoreductive surgery in patients with advanced ovarian cancer based on preoperative and intraoperative determination of the peritoneal carcinomatosis index

Background: 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 in...

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Autores: Llueca, Antoni, SERRA, A., Rivadulla, Isabel, GÓMEZ, L., Escrig, Javier
Formato: artículo
Estado:Versión publicada
Fecha de publicación:2018
País:España
Recursos:Fundación para el Fomento de la Investigación Sanitaria y Biomédica de la Comunitat Valenciana (FISABIO)
Repositorio:r-FISABIO. Repositorio Institucional de Producción Científica
OAI Identifier:oai:fisabio.fundanetsuite.com:p3032
Acesso em linha:https://fisabio.portalinvestigacion.com/publicaciones/3032
Access Level:acceso abierto
Palavra-chave:Advanced ovarian cancer
Cytoreductive surgery
Peritoneal carcinomatosis index
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spelling Prediction of suboptimal cytoreductive surgery in patients with advanced ovarian cancer based on preoperative and intraoperative determination of the peritoneal carcinomatosis indexLlueca, AntoniSERRA, A.Rivadulla, IsabelGÓMEZ, L.Escrig, JavierAdvanced ovarian cancerCytoreductive surgeryPeritoneal carcinomatosis indexBackground: 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.BMC2018info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttps://fisabio.portalinvestigacion.com/publicaciones/3032World Journal of Surgical OncologyISSN: 14777819reponame:r-FISABIO. Repositorio Institucional de Producción Científicainstname:Fundación para el Fomento de la Investigación Sanitaria y Biomédica de la Comunitat Valenciana (FISABIO)Inglésinfo:eu-repo/semantics/openAccessoai:fisabio.fundanetsuite.com:p30322026-06-11T12:45:17Z
dc.title.none.fl_str_mv Prediction of suboptimal cytoreductive surgery in patients with advanced ovarian cancer based on preoperative and intraoperative determination of the peritoneal carcinomatosis index
title Prediction of suboptimal cytoreductive surgery in patients with advanced ovarian cancer based on preoperative and intraoperative determination of the peritoneal carcinomatosis index
spellingShingle Prediction of suboptimal cytoreductive surgery in patients with advanced ovarian cancer based on preoperative and intraoperative determination of the peritoneal carcinomatosis index
Llueca, Antoni
Advanced ovarian cancer
Cytoreductive surgery
Peritoneal carcinomatosis index
title_short Prediction of suboptimal cytoreductive surgery in patients with advanced ovarian cancer based on preoperative and intraoperative determination of the peritoneal carcinomatosis index
title_full Prediction of suboptimal cytoreductive surgery in patients with advanced ovarian cancer based on preoperative and intraoperative determination of the peritoneal carcinomatosis index
title_fullStr Prediction of suboptimal cytoreductive surgery in patients with advanced ovarian cancer based on preoperative and intraoperative determination of the peritoneal carcinomatosis index
title_full_unstemmed Prediction of suboptimal cytoreductive surgery in patients with advanced ovarian cancer based on preoperative and intraoperative determination of the peritoneal carcinomatosis index
title_sort Prediction of suboptimal cytoreductive surgery in patients with advanced ovarian cancer based on preoperative and intraoperative determination of the peritoneal carcinomatosis index
dc.creator.none.fl_str_mv Llueca, Antoni
SERRA, A.
Rivadulla, Isabel
GÓMEZ, L.
Escrig, Javier
author Llueca, Antoni
author_facet Llueca, Antoni
SERRA, A.
Rivadulla, Isabel
GÓMEZ, L.
Escrig, Javier
author_role author
author2 SERRA, A.
Rivadulla, Isabel
GÓMEZ, L.
Escrig, Javier
author2_role author
author
author
author
dc.subject.none.fl_str_mv Advanced ovarian cancer
Cytoreductive surgery
Peritoneal carcinomatosis index
topic Advanced ovarian cancer
Cytoreductive surgery
Peritoneal carcinomatosis index
description Background: 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.
publishDate 2018
dc.date.none.fl_str_mv 2018
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://fisabio.portalinvestigacion.com/publicaciones/3032
url https://fisabio.portalinvestigacion.com/publicaciones/3032
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv BMC
publisher.none.fl_str_mv BMC
dc.source.none.fl_str_mv World Journal of Surgical Oncology
ISSN: 14777819
reponame:r-FISABIO. Repositorio Institucional de Producción Científica
instname:Fundación para el Fomento de la Investigación Sanitaria y Biomédica de la Comunitat Valenciana (FISABIO)
instname_str Fundación para el Fomento de la Investigación Sanitaria y Biomédica de la Comunitat Valenciana (FISABIO)
reponame_str r-FISABIO. Repositorio Institucional de Producción Científica
collection r-FISABIO. Repositorio Institucional de Producción Científica
repository.name.fl_str_mv
repository.mail.fl_str_mv
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