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A novel scoring system integrating molecular abnormalities with IPSS-R can improve the risk stratification in patients with MDS

BACKGROUND: The treatment strategies for Myelodysplastic Syndromes (MDS) are usually based on the risk stratification system. However, few risk signatures which integrate the revised international prognostic scoring system (IPSS-R) with gene mutations can be easily applied in the real world. METHODS...

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Autores principales: Gu, Siyu, Xia, Jingya, Tian, Yulu, Zi, Jie, Ge, Zheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7866647/
https://www.ncbi.nlm.nih.gov/pubmed/33549060
http://dx.doi.org/10.1186/s12885-021-07864-y
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author Gu, Siyu
Xia, Jingya
Tian, Yulu
Zi, Jie
Ge, Zheng
author_facet Gu, Siyu
Xia, Jingya
Tian, Yulu
Zi, Jie
Ge, Zheng
author_sort Gu, Siyu
collection PubMed
description BACKGROUND: The treatment strategies for Myelodysplastic Syndromes (MDS) are usually based on the risk stratification system. However, few risk signatures which integrate the revised international prognostic scoring system (IPSS-R) with gene mutations can be easily applied in the real world. METHODS: The training cohort of 63 MDS patients was conducted at Zhongda Hospital of Southeast University from January 2013 to April 2020. The validation cohort of 141 MDS patients was obtained from GSE129828. The mutation scoring system was based on the number of mutations and a unique favorable prognostic factor, which is SF3B1 mutation. Univariate Cox, multivariate Cox, and LASSO regression analyses were used to determine the significant factors that influenced the overall survival. The receiver operating characteristic curve (ROC) was used to evaluate the efficiency of the prognostic model. RESULTS: A novel risk scoring system we named “mutation combined with revised international prognostic scoring system (MIPSS-R)” was developed based on the results derived from multivariate analysis which assigned points to the IPSS-R and the mutation scores according to their relative statistical weight. Based on the quintile of the new scores, patients were divided into five risk levels. The Kaplan-Meier curves showed the superiority of MIPSS-R in separating patients from different groups, comparing with IPSS-R both in the training cohort (p = 1.71e-08 vs. p = 1.363e-04) and validation cohort (p = 1.788e-04 vs. p = 2.757e-03). The area under the ROC of MIPSS-R was 0.79 in the training cohort and 0.62 in the validation cohort. The retrospective analysis of our house patients showed that the risk levels of 57.41% of patients would adjust according to MIPSS-R. After changing risk levels, 38.71% of patients would benefit from treatment strategies that MIPSS-R recommends. CONCLUSION: A mutation scoring system was conducted based on the number of mutations and a unique favorable prognostic factor. MIPSS-R, the novel integral risk stratification system was developed by integrating IPSS-R and the mutation scores, which is more effective on prognosis and treatment guidance for MDS patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-021-07864-y.
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spelling pubmed-78666472021-02-08 A novel scoring system integrating molecular abnormalities with IPSS-R can improve the risk stratification in patients with MDS Gu, Siyu Xia, Jingya Tian, Yulu Zi, Jie Ge, Zheng BMC Cancer Research Article BACKGROUND: The treatment strategies for Myelodysplastic Syndromes (MDS) are usually based on the risk stratification system. However, few risk signatures which integrate the revised international prognostic scoring system (IPSS-R) with gene mutations can be easily applied in the real world. METHODS: The training cohort of 63 MDS patients was conducted at Zhongda Hospital of Southeast University from January 2013 to April 2020. The validation cohort of 141 MDS patients was obtained from GSE129828. The mutation scoring system was based on the number of mutations and a unique favorable prognostic factor, which is SF3B1 mutation. Univariate Cox, multivariate Cox, and LASSO regression analyses were used to determine the significant factors that influenced the overall survival. The receiver operating characteristic curve (ROC) was used to evaluate the efficiency of the prognostic model. RESULTS: A novel risk scoring system we named “mutation combined with revised international prognostic scoring system (MIPSS-R)” was developed based on the results derived from multivariate analysis which assigned points to the IPSS-R and the mutation scores according to their relative statistical weight. Based on the quintile of the new scores, patients were divided into five risk levels. The Kaplan-Meier curves showed the superiority of MIPSS-R in separating patients from different groups, comparing with IPSS-R both in the training cohort (p = 1.71e-08 vs. p = 1.363e-04) and validation cohort (p = 1.788e-04 vs. p = 2.757e-03). The area under the ROC of MIPSS-R was 0.79 in the training cohort and 0.62 in the validation cohort. The retrospective analysis of our house patients showed that the risk levels of 57.41% of patients would adjust according to MIPSS-R. After changing risk levels, 38.71% of patients would benefit from treatment strategies that MIPSS-R recommends. CONCLUSION: A mutation scoring system was conducted based on the number of mutations and a unique favorable prognostic factor. MIPSS-R, the novel integral risk stratification system was developed by integrating IPSS-R and the mutation scores, which is more effective on prognosis and treatment guidance for MDS patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-021-07864-y. BioMed Central 2021-02-06 /pmc/articles/PMC7866647/ /pubmed/33549060 http://dx.doi.org/10.1186/s12885-021-07864-y Text en © The Author(s) 2021 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. 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 in a credit line to the data.
spellingShingle Research Article
Gu, Siyu
Xia, Jingya
Tian, Yulu
Zi, Jie
Ge, Zheng
A novel scoring system integrating molecular abnormalities with IPSS-R can improve the risk stratification in patients with MDS
title A novel scoring system integrating molecular abnormalities with IPSS-R can improve the risk stratification in patients with MDS
title_full A novel scoring system integrating molecular abnormalities with IPSS-R can improve the risk stratification in patients with MDS
title_fullStr A novel scoring system integrating molecular abnormalities with IPSS-R can improve the risk stratification in patients with MDS
title_full_unstemmed A novel scoring system integrating molecular abnormalities with IPSS-R can improve the risk stratification in patients with MDS
title_short A novel scoring system integrating molecular abnormalities with IPSS-R can improve the risk stratification in patients with MDS
title_sort novel scoring system integrating molecular abnormalities with ipss-r can improve the risk stratification in patients with mds
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7866647/
https://www.ncbi.nlm.nih.gov/pubmed/33549060
http://dx.doi.org/10.1186/s12885-021-07864-y
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