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The preoperative prognostic nutritional index is a predictive and prognostic factor of high-grade serous ovarian cancer

BACKGROUND: The aim of our study was to investigate whether an inflammation-based prognostic score, the prognostic nutritional index (PNI), was associated with clinical characteristics and prognosis in patients with high-grade serous ovarian cancer (HGSC). METHODS: We retrospectively investigated 87...

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Autores principales: Feng, Zheng, Wen, Hao, Ju, Xingzhu, Bi, Rui, Chen, Xiaojun, Yang, Wentao, Wu, Xiaohua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6131794/
https://www.ncbi.nlm.nih.gov/pubmed/30200903
http://dx.doi.org/10.1186/s12885-018-4732-8
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author Feng, Zheng
Wen, Hao
Ju, Xingzhu
Bi, Rui
Chen, Xiaojun
Yang, Wentao
Wu, Xiaohua
author_facet Feng, Zheng
Wen, Hao
Ju, Xingzhu
Bi, Rui
Chen, Xiaojun
Yang, Wentao
Wu, Xiaohua
author_sort Feng, Zheng
collection PubMed
description BACKGROUND: The aim of our study was to investigate whether an inflammation-based prognostic score, the prognostic nutritional index (PNI), was associated with clinical characteristics and prognosis in patients with high-grade serous ovarian cancer (HGSC). METHODS: We retrospectively investigated 875 patients who underwent primary staging or debulking surgery for HGSC between April 2005 and June 2013 at our institution. None of these patients received neoadjuvant chemotherapy. Preoperative PNI was calculated as serum albumin (g/L) + 0.005 × lymphocyte count (per mm(3)). The optimal PNI cutoff value for overall survival (OS) was identified using the online tool “Cutoff Finder”. Clinical characteristics and PNI were compared with chi-square or Fisher’s exact tests, as appropriate. The impact of PNI on OS was analyzed using the Kaplan–Meier method and Cox proportional hazards model. RESULTS: The median (range) PNI was 46.2 (29.2–67.7). The 45.45 cutoff value discriminated patients into the high-PNI and low-PNI groups. A low preoperative PNI was associated with an advanced FIGO stage, increased CA125 level, more extensive ascites, residual disease and platinum resistance. For univariate analyses, a high PNI was associated with increased OS (p < 0.001). In multivariate analyses, the PNI remained an independent predictor of OS as a continuous variable (p = 0.021) but not as dichotomized groups (p = 0.346). CONCLUSION: Our study demonstrated that the PNI could be a predictive and prognostic parameter for HGSC.
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spelling pubmed-61317942018-09-13 The preoperative prognostic nutritional index is a predictive and prognostic factor of high-grade serous ovarian cancer Feng, Zheng Wen, Hao Ju, Xingzhu Bi, Rui Chen, Xiaojun Yang, Wentao Wu, Xiaohua BMC Cancer Research Article BACKGROUND: The aim of our study was to investigate whether an inflammation-based prognostic score, the prognostic nutritional index (PNI), was associated with clinical characteristics and prognosis in patients with high-grade serous ovarian cancer (HGSC). METHODS: We retrospectively investigated 875 patients who underwent primary staging or debulking surgery for HGSC between April 2005 and June 2013 at our institution. None of these patients received neoadjuvant chemotherapy. Preoperative PNI was calculated as serum albumin (g/L) + 0.005 × lymphocyte count (per mm(3)). The optimal PNI cutoff value for overall survival (OS) was identified using the online tool “Cutoff Finder”. Clinical characteristics and PNI were compared with chi-square or Fisher’s exact tests, as appropriate. The impact of PNI on OS was analyzed using the Kaplan–Meier method and Cox proportional hazards model. RESULTS: The median (range) PNI was 46.2 (29.2–67.7). The 45.45 cutoff value discriminated patients into the high-PNI and low-PNI groups. A low preoperative PNI was associated with an advanced FIGO stage, increased CA125 level, more extensive ascites, residual disease and platinum resistance. For univariate analyses, a high PNI was associated with increased OS (p < 0.001). In multivariate analyses, the PNI remained an independent predictor of OS as a continuous variable (p = 0.021) but not as dichotomized groups (p = 0.346). CONCLUSION: Our study demonstrated that the PNI could be a predictive and prognostic parameter for HGSC. BioMed Central 2018-09-10 /pmc/articles/PMC6131794/ /pubmed/30200903 http://dx.doi.org/10.1186/s12885-018-4732-8 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Feng, Zheng
Wen, Hao
Ju, Xingzhu
Bi, Rui
Chen, Xiaojun
Yang, Wentao
Wu, Xiaohua
The preoperative prognostic nutritional index is a predictive and prognostic factor of high-grade serous ovarian cancer
title The preoperative prognostic nutritional index is a predictive and prognostic factor of high-grade serous ovarian cancer
title_full The preoperative prognostic nutritional index is a predictive and prognostic factor of high-grade serous ovarian cancer
title_fullStr The preoperative prognostic nutritional index is a predictive and prognostic factor of high-grade serous ovarian cancer
title_full_unstemmed The preoperative prognostic nutritional index is a predictive and prognostic factor of high-grade serous ovarian cancer
title_short The preoperative prognostic nutritional index is a predictive and prognostic factor of high-grade serous ovarian cancer
title_sort preoperative prognostic nutritional index is a predictive and prognostic factor of high-grade serous ovarian cancer
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6131794/
https://www.ncbi.nlm.nih.gov/pubmed/30200903
http://dx.doi.org/10.1186/s12885-018-4732-8
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