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Dynamic Prediction of Resectability for Patients with Advanced Ovarian Cancer Undergoing Neo-Adjuvant Chemotherapy: Application of Joint Model for Longitudinal CA-125 Levels
SIMPLE SUMMARY: Neoadjuvant chemotherapy is used in patients with initially unresectable advanced ovarian cancer (AOC) to reduce the disease bulk. The CA-125 level depends on tumor burden changes. A joint model (JM) is a statistical tool used for dynamic prediction during follow-up. A JM of longitud...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9818430/ https://www.ncbi.nlm.nih.gov/pubmed/36612234 http://dx.doi.org/10.3390/cancers15010231 |
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author | Amroun, Koceila Chaltiel, Raphael Reyal, Fabien Kianmanesh, Reza Savoye, Aude-Marie Perrier, Marine Djerada, Zoubir Bouché, Olivier |
author_facet | Amroun, Koceila Chaltiel, Raphael Reyal, Fabien Kianmanesh, Reza Savoye, Aude-Marie Perrier, Marine Djerada, Zoubir Bouché, Olivier |
author_sort | Amroun, Koceila |
collection | PubMed |
description | SIMPLE SUMMARY: Neoadjuvant chemotherapy is used in patients with initially unresectable advanced ovarian cancer (AOC) to reduce the disease bulk. The CA-125 level depends on tumor burden changes. A joint model (JM) is a statistical tool used for dynamic prediction during follow-up. A JM of longitudinal CA-125 was assessed as a reliable predictive model for overall and free disease survivals. We developed a dynamic and individual model to predict complete resectability of AOC using patients’ and tumor characteristics combined with kinetics of CA-125 during neo-adjuvant chemotherapy. ABSTRACT: In patients with advanced ovarian cancer (AOC) receiving neoadjuvant chemotherapy (NAC), predicting the feasibility of complete interval cytoreductive surgery (ICRS) is helpful and may avoid unnecessary laparotomy. A joint model (JM) is a dynamic individual predictive model. The aim of this study was to develop a predictive JM combining CA-125 kinetics during NAC with patients’ and clinical factors to predict resectability after NAC in patients with AOC. A retrospective study included 77 patients with AOC treated with NAC. A linear mixed effect (LME) sub-model was used to describe the evolution of CA-125 during NAC considering factors influencing the biomarker levels. A Cox sub-model screened the covariates associated with resectability. The JM combined the LME sub-model with the Cox sub-model. Using the LME sub-model, we observed that CA-125 levels were influenced by the number of NAC cycles and the performance of paracentesis. In the Cox sub-model, complete resectability was associated with Performance Status (HR = 0.57, [0.34–0.95], p = 0.03) and the presence of peritoneal carcinomatosis in the epigastric region (HR = 0.39, [0.19–0.80], p = 0.01). The JM accuracy to predict complete ICRS was 88% [82–100] with a predictive error of 2.24% [0–2.32]. Using a JM of a longitudinal CA-125 level during NAC could be a reliable predictor of complete ICRS. |
format | Online Article Text |
id | pubmed-9818430 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-98184302023-01-07 Dynamic Prediction of Resectability for Patients with Advanced Ovarian Cancer Undergoing Neo-Adjuvant Chemotherapy: Application of Joint Model for Longitudinal CA-125 Levels Amroun, Koceila Chaltiel, Raphael Reyal, Fabien Kianmanesh, Reza Savoye, Aude-Marie Perrier, Marine Djerada, Zoubir Bouché, Olivier Cancers (Basel) Article SIMPLE SUMMARY: Neoadjuvant chemotherapy is used in patients with initially unresectable advanced ovarian cancer (AOC) to reduce the disease bulk. The CA-125 level depends on tumor burden changes. A joint model (JM) is a statistical tool used for dynamic prediction during follow-up. A JM of longitudinal CA-125 was assessed as a reliable predictive model for overall and free disease survivals. We developed a dynamic and individual model to predict complete resectability of AOC using patients’ and tumor characteristics combined with kinetics of CA-125 during neo-adjuvant chemotherapy. ABSTRACT: In patients with advanced ovarian cancer (AOC) receiving neoadjuvant chemotherapy (NAC), predicting the feasibility of complete interval cytoreductive surgery (ICRS) is helpful and may avoid unnecessary laparotomy. A joint model (JM) is a dynamic individual predictive model. The aim of this study was to develop a predictive JM combining CA-125 kinetics during NAC with patients’ and clinical factors to predict resectability after NAC in patients with AOC. A retrospective study included 77 patients with AOC treated with NAC. A linear mixed effect (LME) sub-model was used to describe the evolution of CA-125 during NAC considering factors influencing the biomarker levels. A Cox sub-model screened the covariates associated with resectability. The JM combined the LME sub-model with the Cox sub-model. Using the LME sub-model, we observed that CA-125 levels were influenced by the number of NAC cycles and the performance of paracentesis. In the Cox sub-model, complete resectability was associated with Performance Status (HR = 0.57, [0.34–0.95], p = 0.03) and the presence of peritoneal carcinomatosis in the epigastric region (HR = 0.39, [0.19–0.80], p = 0.01). The JM accuracy to predict complete ICRS was 88% [82–100] with a predictive error of 2.24% [0–2.32]. Using a JM of a longitudinal CA-125 level during NAC could be a reliable predictor of complete ICRS. MDPI 2022-12-30 /pmc/articles/PMC9818430/ /pubmed/36612234 http://dx.doi.org/10.3390/cancers15010231 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Amroun, Koceila Chaltiel, Raphael Reyal, Fabien Kianmanesh, Reza Savoye, Aude-Marie Perrier, Marine Djerada, Zoubir Bouché, Olivier Dynamic Prediction of Resectability for Patients with Advanced Ovarian Cancer Undergoing Neo-Adjuvant Chemotherapy: Application of Joint Model for Longitudinal CA-125 Levels |
title | Dynamic Prediction of Resectability for Patients with Advanced Ovarian Cancer Undergoing Neo-Adjuvant Chemotherapy: Application of Joint Model for Longitudinal CA-125 Levels |
title_full | Dynamic Prediction of Resectability for Patients with Advanced Ovarian Cancer Undergoing Neo-Adjuvant Chemotherapy: Application of Joint Model for Longitudinal CA-125 Levels |
title_fullStr | Dynamic Prediction of Resectability for Patients with Advanced Ovarian Cancer Undergoing Neo-Adjuvant Chemotherapy: Application of Joint Model for Longitudinal CA-125 Levels |
title_full_unstemmed | Dynamic Prediction of Resectability for Patients with Advanced Ovarian Cancer Undergoing Neo-Adjuvant Chemotherapy: Application of Joint Model for Longitudinal CA-125 Levels |
title_short | Dynamic Prediction of Resectability for Patients with Advanced Ovarian Cancer Undergoing Neo-Adjuvant Chemotherapy: Application of Joint Model for Longitudinal CA-125 Levels |
title_sort | dynamic prediction of resectability for patients with advanced ovarian cancer undergoing neo-adjuvant chemotherapy: application of joint model for longitudinal ca-125 levels |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9818430/ https://www.ncbi.nlm.nih.gov/pubmed/36612234 http://dx.doi.org/10.3390/cancers15010231 |
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