A radiologic-laparoscopic model to predict suboptimal (or complete and optimal) debulking surgery in advanced ovarian cancer: a pilot study

Introduction: Medical models assist clinicians in making diagnostic and prognostic decisions in complex situations. In advanced ovarian cancer, medical models could help prevent unnecessary exploratory surgery. We designed two models to predict suboptimal or complete and optimal cytoreductive surger...

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Autores: Llueca, A, Serra, A, Delgado, K, MAIOCCHI, A., Jativa, R, Gomez, L, Escrig, J
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2019
País:España
Institución: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:p7355
Acceso en línea:https://fisabio.portalinvestigacion.com/publicaciones/7355
Access Level:acceso abierto
Palabra clave:advanced ovarian cancer
medical model
peritoneal cancer index
cytoreductive surgery
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spelling A radiologic-laparoscopic model to predict suboptimal (or complete and optimal) debulking surgery in advanced ovarian cancer: a pilot studyLlueca, ASerra, ADelgado, KMAIOCCHI, A.Jativa, RGomez, LEscrig, Jadvanced ovarian cancermedical modelperitoneal cancer indexcytoreductive surgeryIntroduction: Medical models assist clinicians in making diagnostic and prognostic decisions in complex situations. In advanced ovarian cancer, medical models could help prevent unnecessary exploratory surgery. We designed two models to predict suboptimal or complete and optimal cytoreductive surgery in patients with advanced ovarian cancer. Methods: We collected clinical, pathological, surgical, and residual tumor data from 110 patients with advanced ovarian cancer. Computed tomographic and laparoscopic data from these patients were used to determine peritoneal cancer index (PCI) and lesion size score. These data were then used to construct two-by-two contingency tables and our two predictive models. Each model included three risk score levels; the R4 model also included operative PCI, while the R3 model did not. Finally, we used the original patient data to validate the models (narrow validation). Results: Our models predicted suboptimal or complete and optimal cytoreductive surgery with a sensitivity of 83% (R4 model) and 69% (R3 model). Our results also showed that PCI>20 was a major risk factor for unresectability. Conclusion: Our medical models successfully predicted suboptimal or complete and optimal cytoreductive surgery in 110 patients with advanced ovarian cancer. Our models are easy to construct, based on readily available laboratory test data, simple to use clinically, and could reduce unnecessary exploratory surgery in this patient group.DOVE MEDICAL PRESS LTD2019info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttps://fisabio.portalinvestigacion.com/publicaciones/7355International Journal of Womens HealthISSN: 11791411reponame: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:p73552026-06-11T12:45:17Z
dc.title.none.fl_str_mv A radiologic-laparoscopic model to predict suboptimal (or complete and optimal) debulking surgery in advanced ovarian cancer: a pilot study
title A radiologic-laparoscopic model to predict suboptimal (or complete and optimal) debulking surgery in advanced ovarian cancer: a pilot study
spellingShingle A radiologic-laparoscopic model to predict suboptimal (or complete and optimal) debulking surgery in advanced ovarian cancer: a pilot study
Llueca, A
advanced ovarian cancer
medical model
peritoneal cancer index
cytoreductive surgery
title_short A radiologic-laparoscopic model to predict suboptimal (or complete and optimal) debulking surgery in advanced ovarian cancer: a pilot study
title_full A radiologic-laparoscopic model to predict suboptimal (or complete and optimal) debulking surgery in advanced ovarian cancer: a pilot study
title_fullStr A radiologic-laparoscopic model to predict suboptimal (or complete and optimal) debulking surgery in advanced ovarian cancer: a pilot study
title_full_unstemmed A radiologic-laparoscopic model to predict suboptimal (or complete and optimal) debulking surgery in advanced ovarian cancer: a pilot study
title_sort A radiologic-laparoscopic model to predict suboptimal (or complete and optimal) debulking surgery in advanced ovarian cancer: a pilot study
dc.creator.none.fl_str_mv Llueca, A
Serra, A
Delgado, K
MAIOCCHI, A.
Jativa, R
Gomez, L
Escrig, J
author Llueca, A
author_facet Llueca, A
Serra, A
Delgado, K
MAIOCCHI, A.
Jativa, R
Gomez, L
Escrig, J
author_role author
author2 Serra, A
Delgado, K
MAIOCCHI, A.
Jativa, R
Gomez, L
Escrig, J
author2_role author
author
author
author
author
author
dc.subject.none.fl_str_mv advanced ovarian cancer
medical model
peritoneal cancer index
cytoreductive surgery
topic advanced ovarian cancer
medical model
peritoneal cancer index
cytoreductive surgery
description Introduction: Medical models assist clinicians in making diagnostic and prognostic decisions in complex situations. In advanced ovarian cancer, medical models could help prevent unnecessary exploratory surgery. We designed two models to predict suboptimal or complete and optimal cytoreductive surgery in patients with advanced ovarian cancer. Methods: We collected clinical, pathological, surgical, and residual tumor data from 110 patients with advanced ovarian cancer. Computed tomographic and laparoscopic data from these patients were used to determine peritoneal cancer index (PCI) and lesion size score. These data were then used to construct two-by-two contingency tables and our two predictive models. Each model included three risk score levels; the R4 model also included operative PCI, while the R3 model did not. Finally, we used the original patient data to validate the models (narrow validation). Results: Our models predicted suboptimal or complete and optimal cytoreductive surgery with a sensitivity of 83% (R4 model) and 69% (R3 model). Our results also showed that PCI>20 was a major risk factor for unresectability. Conclusion: Our medical models successfully predicted suboptimal or complete and optimal cytoreductive surgery in 110 patients with advanced ovarian cancer. Our models are easy to construct, based on readily available laboratory test data, simple to use clinically, and could reduce unnecessary exploratory surgery in this patient group.
publishDate 2019
dc.date.none.fl_str_mv 2019
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/7355
url https://fisabio.portalinvestigacion.com/publicaciones/7355
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 DOVE MEDICAL PRESS LTD
publisher.none.fl_str_mv DOVE MEDICAL PRESS LTD
dc.source.none.fl_str_mv International Journal of Womens Health
ISSN: 11791411
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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