Validation of three predictive models for suboptimal cytoreductive surgery in advanced ovarian cancer

Abstract The standard treatment for advanced ovarian cancer (AOC) is cytoreduction surgery and adjuvant chemotherapy. Tumor volume after surgery is a major prognostic factor for these patients. The ability to perform complete cytoreduction depends on the extent of disease and the skills of the surgi...

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Autores principales:	Antoni Llueca, María Teresa Climent, Javier Escrig, Paula Carrasco, Anna Serra, MUAPOS working group (Multidisciplinary Unit of Abdominal Pelvic Oncology Surgery)
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/14d9e3330efa4339868deed1dbc4ec94
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spelling	oai:doaj.org-article:14d9e3330efa4339868deed1dbc4ec942021-12-02T14:31:01ZValidation of three predictive models for suboptimal cytoreductive surgery in advanced ovarian cancer10.1038/s41598-021-86928-22045-2322https://doaj.org/article/14d9e3330efa4339868deed1dbc4ec942021-04-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-86928-2https://doaj.org/toc/2045-2322Abstract The standard treatment for advanced ovarian cancer (AOC) is cytoreduction surgery and adjuvant chemotherapy. Tumor volume after surgery is a major prognostic factor for these patients. The ability to perform complete cytoreduction depends on the extent of disease and the skills of the surgical team. Several predictive models have been proposed to evaluate the possibility of performing complete cytoreductive surgery (CCS). External validation of the prognostic value of three predictive models (Fagotti index and the R3 and R4 models) for predicting suboptimal cytoreductive surgery (SCS) in AOC was performed in this study. The scores of the 3 models were evaluated in one hundred and three consecutive patients diagnosed with AOC treated in a tertiary hospital were evaluated. Clinicopathological features were collected prospectively and analyzed retrospectively. The performance of the three models was evaluated, and calibration and discrimination were analyzed. The calibration of the Fagotti, R3 and R4 models showed odds ratios of obtaining SCSs of 1.5, 2.4 and 2.4, respectively, indicating good calibration. The discrimination of the Fagotti, R3 and R4 models showed an area under the ROC curve of 83%, 70% and 81%, respectively. The negative predictive values of the three models were higher than the positive predictive values for SCS. The three models were able to predict suboptimal cytoreductive surgery for advanced ovarian cancer, but they were more reliable for predicting CCS. The R4 model discriminated better because it includes the laparotomic evaluation of the peritoneal carcinomatosis index.Antoni LluecaMaría Teresa ClimentJavier EscrigPaula CarrascoAnna SerraMUAPOS working group (Multidisciplinary Unit of Abdominal Pelvic Oncology Surgery)Nature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-8 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Antoni Llueca María Teresa Climent Javier Escrig Paula Carrasco Anna Serra MUAPOS working group (Multidisciplinary Unit of Abdominal Pelvic Oncology Surgery) Validation of three predictive models for suboptimal cytoreductive surgery in advanced ovarian cancer
description	Abstract The standard treatment for advanced ovarian cancer (AOC) is cytoreduction surgery and adjuvant chemotherapy. Tumor volume after surgery is a major prognostic factor for these patients. The ability to perform complete cytoreduction depends on the extent of disease and the skills of the surgical team. Several predictive models have been proposed to evaluate the possibility of performing complete cytoreductive surgery (CCS). External validation of the prognostic value of three predictive models (Fagotti index and the R3 and R4 models) for predicting suboptimal cytoreductive surgery (SCS) in AOC was performed in this study. The scores of the 3 models were evaluated in one hundred and three consecutive patients diagnosed with AOC treated in a tertiary hospital were evaluated. Clinicopathological features were collected prospectively and analyzed retrospectively. The performance of the three models was evaluated, and calibration and discrimination were analyzed. The calibration of the Fagotti, R3 and R4 models showed odds ratios of obtaining SCSs of 1.5, 2.4 and 2.4, respectively, indicating good calibration. The discrimination of the Fagotti, R3 and R4 models showed an area under the ROC curve of 83%, 70% and 81%, respectively. The negative predictive values of the three models were higher than the positive predictive values for SCS. The three models were able to predict suboptimal cytoreductive surgery for advanced ovarian cancer, but they were more reliable for predicting CCS. The R4 model discriminated better because it includes the laparotomic evaluation of the peritoneal carcinomatosis index.
format	article
author	Antoni Llueca María Teresa Climent Javier Escrig Paula Carrasco Anna Serra MUAPOS working group (Multidisciplinary Unit of Abdominal Pelvic Oncology Surgery)
author_facet	Antoni Llueca María Teresa Climent Javier Escrig Paula Carrasco Anna Serra MUAPOS working group (Multidisciplinary Unit of Abdominal Pelvic Oncology Surgery)
author_sort	Antoni Llueca
title	Validation of three predictive models for suboptimal cytoreductive surgery in advanced ovarian cancer
title_short	Validation of three predictive models for suboptimal cytoreductive surgery in advanced ovarian cancer
title_full	Validation of three predictive models for suboptimal cytoreductive surgery in advanced ovarian cancer
title_fullStr	Validation of three predictive models for suboptimal cytoreductive surgery in advanced ovarian cancer
title_full_unstemmed	Validation of three predictive models for suboptimal cytoreductive surgery in advanced ovarian cancer
title_sort	validation of three predictive models for suboptimal cytoreductive surgery in advanced ovarian cancer
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/14d9e3330efa4339868deed1dbc4ec94
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Validation of three predictive models for suboptimal cytoreductive surgery in advanced ovarian cancer

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