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Predictors of early mortality risk in patients with epithelial ovarian cancer
BACKGROUND: To improve the overall survival of epithelial ovarian cancer (EOC) patients, a more precise risk identification after completion of standard treatment will enhance patients' follow‐up surveillance and the use of individualized targeted therapy. AIM: This study explored the potential...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9260216/ https://www.ncbi.nlm.nih.gov/pubmed/35821892 http://dx.doi.org/10.1002/hsr2.717 |
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author | Okunade, Kehinde S. John‐Olabode, Sarah Ohazurike, Ephraim O. Soibi‐Harry, Adaiah Osunwusi, Benedetto Anorlu, Rose I. |
author_facet | Okunade, Kehinde S. John‐Olabode, Sarah Ohazurike, Ephraim O. Soibi‐Harry, Adaiah Osunwusi, Benedetto Anorlu, Rose I. |
author_sort | Okunade, Kehinde S. |
collection | PubMed |
description | BACKGROUND: To improve the overall survival of epithelial ovarian cancer (EOC) patients, a more precise risk identification after completion of standard treatment will enhance patients' follow‐up surveillance and the use of individualized targeted therapy. AIM: This study explored the potential risk predictors of early mortality in EOC patients who had standard treatment with debulking surgery and chemotherapy. METHODS: The study included 93 EOC patients who had standard treatment and were followed up between January 2011 and December 2020. The sociodemographic, clinical, and laboratory data of patients with EOC including the update on their 3‐year follow‐up status were retrospectively collected and analyzed. Early mortality is defined as the death of a patient within 3 years of completion of standard treatment. Patients' data were computed using descriptive statistics and the associations between patients' factors and the risk of early mortality were tested using the binary logistic regression model. RESULTS: Early deaths occurred in 36 (38.7%) of patients with EOC. In the final multivariate analyses, early tumor relapse within 6‐months of treatment completion was the only independent risk factor that predicts early mortality in EOC patients (risk ratio = 8.6, 95% confidence interval: 3.3–24.5, p < 0.01). CONCLUSION: Our study suggests that early tumor relapse may be a useful surrogate of early mortality in EOC. However, our findings should be interpreted with caution pending further corroboration through an adequately powered, prospective multicenter study. |
format | Online Article Text |
id | pubmed-9260216 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-92602162022-07-11 Predictors of early mortality risk in patients with epithelial ovarian cancer Okunade, Kehinde S. John‐Olabode, Sarah Ohazurike, Ephraim O. Soibi‐Harry, Adaiah Osunwusi, Benedetto Anorlu, Rose I. Health Sci Rep Original Research BACKGROUND: To improve the overall survival of epithelial ovarian cancer (EOC) patients, a more precise risk identification after completion of standard treatment will enhance patients' follow‐up surveillance and the use of individualized targeted therapy. AIM: This study explored the potential risk predictors of early mortality in EOC patients who had standard treatment with debulking surgery and chemotherapy. METHODS: The study included 93 EOC patients who had standard treatment and were followed up between January 2011 and December 2020. The sociodemographic, clinical, and laboratory data of patients with EOC including the update on their 3‐year follow‐up status were retrospectively collected and analyzed. Early mortality is defined as the death of a patient within 3 years of completion of standard treatment. Patients' data were computed using descriptive statistics and the associations between patients' factors and the risk of early mortality were tested using the binary logistic regression model. RESULTS: Early deaths occurred in 36 (38.7%) of patients with EOC. In the final multivariate analyses, early tumor relapse within 6‐months of treatment completion was the only independent risk factor that predicts early mortality in EOC patients (risk ratio = 8.6, 95% confidence interval: 3.3–24.5, p < 0.01). CONCLUSION: Our study suggests that early tumor relapse may be a useful surrogate of early mortality in EOC. However, our findings should be interpreted with caution pending further corroboration through an adequately powered, prospective multicenter study. John Wiley and Sons Inc. 2022-07-07 /pmc/articles/PMC9260216/ /pubmed/35821892 http://dx.doi.org/10.1002/hsr2.717 Text en © 2022 The Authors. Health Science Reports published by Wiley Periodicals LLC. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made. |
spellingShingle | Original Research Okunade, Kehinde S. John‐Olabode, Sarah Ohazurike, Ephraim O. Soibi‐Harry, Adaiah Osunwusi, Benedetto Anorlu, Rose I. Predictors of early mortality risk in patients with epithelial ovarian cancer |
title | Predictors of early mortality risk in patients with epithelial ovarian cancer |
title_full | Predictors of early mortality risk in patients with epithelial ovarian cancer |
title_fullStr | Predictors of early mortality risk in patients with epithelial ovarian cancer |
title_full_unstemmed | Predictors of early mortality risk in patients with epithelial ovarian cancer |
title_short | Predictors of early mortality risk in patients with epithelial ovarian cancer |
title_sort | predictors of early mortality risk in patients with epithelial ovarian cancer |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9260216/ https://www.ncbi.nlm.nih.gov/pubmed/35821892 http://dx.doi.org/10.1002/hsr2.717 |
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