Good prediction of treatment responses to neoadjuvant chemoradiotherapy for esophageal cancer based on preoperative inflammatory status and tumor glucose metabolism

Abstract To develop a tool for predicting pathologic complete response (pCR) after neoadjuvant chemoradiotherapy (neoCRT) in patients with esophageal cancer by combining inflammatory status and tumor glucose metabolic activity. This study included 127 patients with locally advanced esophageal cancer...

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Autores principales:	Chuan Li, Jing-Wei Lin, Hui-Ling Yeh, Cheng-Yen Chuang, Chien-Chih Chen
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/7a5992de286f47048f47f7d4a15cc6cb
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spelling	oai:doaj.org-article:7a5992de286f47048f47f7d4a15cc6cb2021-12-02T17:51:29ZGood prediction of treatment responses to neoadjuvant chemoradiotherapy for esophageal cancer based on preoperative inflammatory status and tumor glucose metabolism10.1038/s41598-021-90753-y2045-2322https://doaj.org/article/7a5992de286f47048f47f7d4a15cc6cb2021-06-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-90753-yhttps://doaj.org/toc/2045-2322Abstract To develop a tool for predicting pathologic complete response (pCR) after neoadjuvant chemoradiotherapy (neoCRT) in patients with esophageal cancer by combining inflammatory status and tumor glucose metabolic activity. This study included 127 patients with locally advanced esophageal cancer who had received neoCRT followed by esophagectomy from 2007 to 2016. We collected their neutrophil–lymphocyte ratio (NLR) and standardized uptake value (SUV) obtained from fluorodeoxyglucose positron emission tomography (PET/CT) before and after neoCRT. Univariate and multivariate logistic regression analyses were performed to identify potential predictive factors for pCR. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of predictors were calculated. Between pCR and non-pCR groups, there were no statistically significant differences in patient characteristics, such as sex, age, site, and clinical T/N stage. Multivariate analyses identified four independent predictors for pCR, including pre-OP NLR < 5.4 [OR 11.179; 95% CI 8.385–13.495; p = 0.003], NLR change (ΔNLR) < 3 [OR 4.891; 95% CI 2.274–9.180; p = 0.005], changes in SUV (ΔSUV) > 7.2 [OR 3.033; 95% CI 1.354–6.791; p = 0.007], and SUV changes ratio (ΔSUV ratio) > 58% [OR 3.585; 95% CI 1.576–8.152; p = 0.002]. ΔNLR had the highest accuracy and NPV (84.3% and 90.3%, respectively). Combined factors of ΔNLR < 3 and ΔSUV ratio > 58% had the best PPV for pCR (84.8%). Inflammatory status (ΔNLR) and tumor glucose metabolic activity (ΔSUV ratio), when considered together, constitute a promising low-invasive tool with high efficacy for prediction of treatment response before surgery.Chuan LiJing-Wei LinHui-Ling YehCheng-Yen ChuangChien-Chih ChenNature 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 Chuan Li Jing-Wei Lin Hui-Ling Yeh Cheng-Yen Chuang Chien-Chih Chen Good prediction of treatment responses to neoadjuvant chemoradiotherapy for esophageal cancer based on preoperative inflammatory status and tumor glucose metabolism
description	Abstract To develop a tool for predicting pathologic complete response (pCR) after neoadjuvant chemoradiotherapy (neoCRT) in patients with esophageal cancer by combining inflammatory status and tumor glucose metabolic activity. This study included 127 patients with locally advanced esophageal cancer who had received neoCRT followed by esophagectomy from 2007 to 2016. We collected their neutrophil–lymphocyte ratio (NLR) and standardized uptake value (SUV) obtained from fluorodeoxyglucose positron emission tomography (PET/CT) before and after neoCRT. Univariate and multivariate logistic regression analyses were performed to identify potential predictive factors for pCR. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of predictors were calculated. Between pCR and non-pCR groups, there were no statistically significant differences in patient characteristics, such as sex, age, site, and clinical T/N stage. Multivariate analyses identified four independent predictors for pCR, including pre-OP NLR < 5.4 [OR 11.179; 95% CI 8.385–13.495; p = 0.003], NLR change (ΔNLR) < 3 [OR 4.891; 95% CI 2.274–9.180; p = 0.005], changes in SUV (ΔSUV) > 7.2 [OR 3.033; 95% CI 1.354–6.791; p = 0.007], and SUV changes ratio (ΔSUV ratio) > 58% [OR 3.585; 95% CI 1.576–8.152; p = 0.002]. ΔNLR had the highest accuracy and NPV (84.3% and 90.3%, respectively). Combined factors of ΔNLR < 3 and ΔSUV ratio > 58% had the best PPV for pCR (84.8%). Inflammatory status (ΔNLR) and tumor glucose metabolic activity (ΔSUV ratio), when considered together, constitute a promising low-invasive tool with high efficacy for prediction of treatment response before surgery.
format	article
author	Chuan Li Jing-Wei Lin Hui-Ling Yeh Cheng-Yen Chuang Chien-Chih Chen
author_facet	Chuan Li Jing-Wei Lin Hui-Ling Yeh Cheng-Yen Chuang Chien-Chih Chen
author_sort	Chuan Li
title	Good prediction of treatment responses to neoadjuvant chemoradiotherapy for esophageal cancer based on preoperative inflammatory status and tumor glucose metabolism
title_short	Good prediction of treatment responses to neoadjuvant chemoradiotherapy for esophageal cancer based on preoperative inflammatory status and tumor glucose metabolism
title_full	Good prediction of treatment responses to neoadjuvant chemoradiotherapy for esophageal cancer based on preoperative inflammatory status and tumor glucose metabolism
title_fullStr	Good prediction of treatment responses to neoadjuvant chemoradiotherapy for esophageal cancer based on preoperative inflammatory status and tumor glucose metabolism
title_full_unstemmed	Good prediction of treatment responses to neoadjuvant chemoradiotherapy for esophageal cancer based on preoperative inflammatory status and tumor glucose metabolism
title_sort	good prediction of treatment responses to neoadjuvant chemoradiotherapy for esophageal cancer based on preoperative inflammatory status and tumor glucose metabolism
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/7a5992de286f47048f47f7d4a15cc6cb
work_keys_str_mv	AT chuanli goodpredictionoftreatmentresponsestoneoadjuvantchemoradiotherapyforesophagealcancerbasedonpreoperativeinflammatorystatusandtumorglucosemetabolism AT jingweilin goodpredictionoftreatmentresponsestoneoadjuvantchemoradiotherapyforesophagealcancerbasedonpreoperativeinflammatorystatusandtumorglucosemetabolism AT huilingyeh goodpredictionoftreatmentresponsestoneoadjuvantchemoradiotherapyforesophagealcancerbasedonpreoperativeinflammatorystatusandtumorglucosemetabolism AT chengyenchuang goodpredictionoftreatmentresponsestoneoadjuvantchemoradiotherapyforesophagealcancerbasedonpreoperativeinflammatorystatusandtumorglucosemetabolism AT chienchihchen goodpredictionoftreatmentresponsestoneoadjuvantchemoradiotherapyforesophagealcancerbasedonpreoperativeinflammatorystatusandtumorglucosemetabolism
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Good prediction of treatment responses to neoadjuvant chemoradiotherapy for esophageal cancer based on preoperative inflammatory status and tumor glucose metabolism

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