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Blood prognostic predictors of treatment response for patients with papillary thyroid cancer

Background: Papillary thyroid cancer (PTC) is a very common malignant disease with high morbidity. We needed some pretreatment indicators to help us predict prognosis and guide treatment. We conducted a study about some pretreatment prognostic indicators. Methods: This clinical study recruited 705 p...

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Autores principales: Liu, Xiangxiang, Huang, Zhongke, He, Xianghui, Zheng, Xiangqian, Jia, Qiang, Tan, Jian, Fan, Yaguang, Lou, Cen, Meng, Zhaowei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Portland Press Ltd. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7578621/
https://www.ncbi.nlm.nih.gov/pubmed/33015713
http://dx.doi.org/10.1042/BSR20202544
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author Liu, Xiangxiang
Huang, Zhongke
He, Xianghui
Zheng, Xiangqian
Jia, Qiang
Tan, Jian
Fan, Yaguang
Lou, Cen
Meng, Zhaowei
author_facet Liu, Xiangxiang
Huang, Zhongke
He, Xianghui
Zheng, Xiangqian
Jia, Qiang
Tan, Jian
Fan, Yaguang
Lou, Cen
Meng, Zhaowei
author_sort Liu, Xiangxiang
collection PubMed
description Background: Papillary thyroid cancer (PTC) is a very common malignant disease with high morbidity. We needed some pretreatment indicators to help us predict prognosis and guide treatment. We conducted a study about some pretreatment prognostic indicators. Methods: This clinical study recruited 705 postoperative PTC patients (211 males, 494 females). Clinical data before radioactive iodine (RAI) treatment were collected. Patients’ response to therapy were classified into two categories: ‘Good Prognosis Group’ (GPG) and ‘Poor Prognosis Group’ (PPG), according to ‘2015 American Thyroid Association Guidelines’. Differences of indicators between different prognosis groups were compared. Odds ratios (ORs) were calculated by univariate/multiple binary logistic regression models. Difference of body mass index (BMI) changes before and after RAI treatment between different prognosis groups was also compared. Results: A total of 546 (77.45%) belonged to GPG, and 159 (22.55%) belonged to PPG. Platelet (PLT), neutrophil (NEUT), PLT subgroups, and combination of red blood cell distribution width (RDW) and BMI (COR-BMI) were different between two prognosis groups. The significance of the difference between the two groups of BMI disappeared after the Bonferroni correction. PLT and PLT subgroups had detrimental effects on the risk of PPG; T stage had a positive effect on the risk of PPG. PLT subgroup showed a detrimental effect on the risk of PPG when we included additional covariates. Conclusions: We found that lower pretreatment PLT levels may indicate a poor prognosis for PTC. The relationship between platelet-derived growth factor (PDGF) and radiation sensitivity may be the key to this association.
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spelling pubmed-75786212020-10-27 Blood prognostic predictors of treatment response for patients with papillary thyroid cancer Liu, Xiangxiang Huang, Zhongke He, Xianghui Zheng, Xiangqian Jia, Qiang Tan, Jian Fan, Yaguang Lou, Cen Meng, Zhaowei Biosci Rep Cancer Background: Papillary thyroid cancer (PTC) is a very common malignant disease with high morbidity. We needed some pretreatment indicators to help us predict prognosis and guide treatment. We conducted a study about some pretreatment prognostic indicators. Methods: This clinical study recruited 705 postoperative PTC patients (211 males, 494 females). Clinical data before radioactive iodine (RAI) treatment were collected. Patients’ response to therapy were classified into two categories: ‘Good Prognosis Group’ (GPG) and ‘Poor Prognosis Group’ (PPG), according to ‘2015 American Thyroid Association Guidelines’. Differences of indicators between different prognosis groups were compared. Odds ratios (ORs) were calculated by univariate/multiple binary logistic regression models. Difference of body mass index (BMI) changes before and after RAI treatment between different prognosis groups was also compared. Results: A total of 546 (77.45%) belonged to GPG, and 159 (22.55%) belonged to PPG. Platelet (PLT), neutrophil (NEUT), PLT subgroups, and combination of red blood cell distribution width (RDW) and BMI (COR-BMI) were different between two prognosis groups. The significance of the difference between the two groups of BMI disappeared after the Bonferroni correction. PLT and PLT subgroups had detrimental effects on the risk of PPG; T stage had a positive effect on the risk of PPG. PLT subgroup showed a detrimental effect on the risk of PPG when we included additional covariates. Conclusions: We found that lower pretreatment PLT levels may indicate a poor prognosis for PTC. The relationship between platelet-derived growth factor (PDGF) and radiation sensitivity may be the key to this association. Portland Press Ltd. 2020-10-21 /pmc/articles/PMC7578621/ /pubmed/33015713 http://dx.doi.org/10.1042/BSR20202544 Text en © 2020 The Author(s). https://creativecommons.org/licenses/by/4.0/ This is an open access article published by Portland Press Limited on behalf of the Biochemical Society and distributed under the Creative Commons Attribution License 4.0 (CC BY).
spellingShingle Cancer
Liu, Xiangxiang
Huang, Zhongke
He, Xianghui
Zheng, Xiangqian
Jia, Qiang
Tan, Jian
Fan, Yaguang
Lou, Cen
Meng, Zhaowei
Blood prognostic predictors of treatment response for patients with papillary thyroid cancer
title Blood prognostic predictors of treatment response for patients with papillary thyroid cancer
title_full Blood prognostic predictors of treatment response for patients with papillary thyroid cancer
title_fullStr Blood prognostic predictors of treatment response for patients with papillary thyroid cancer
title_full_unstemmed Blood prognostic predictors of treatment response for patients with papillary thyroid cancer
title_short Blood prognostic predictors of treatment response for patients with papillary thyroid cancer
title_sort blood prognostic predictors of treatment response for patients with papillary thyroid cancer
topic Cancer
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7578621/
https://www.ncbi.nlm.nih.gov/pubmed/33015713
http://dx.doi.org/10.1042/BSR20202544
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