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Myelofibrosis and Survival Prognostic Models: A Journey between Past and Future
Among the myeloproliferative diseases, myelofibrosis is a widely heterogeneous entity characterized by a highly variable prognosis. In this context, several prognostic models have been proposed to categorize these patients appropriately. Identifying who deserves more invasive treatments, such as bon...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10053868/ https://www.ncbi.nlm.nih.gov/pubmed/36983189 http://dx.doi.org/10.3390/jcm12062188 |
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author | Duminuco, Andrea Nardo, Antonella Giuffrida, Gaetano Leotta, Salvatore Markovic, Uros Giallongo, Cesarina Tibullo, Daniele Romano, Alessandra Di Raimondo, Francesco Palumbo, Giuseppe A. |
author_facet | Duminuco, Andrea Nardo, Antonella Giuffrida, Gaetano Leotta, Salvatore Markovic, Uros Giallongo, Cesarina Tibullo, Daniele Romano, Alessandra Di Raimondo, Francesco Palumbo, Giuseppe A. |
author_sort | Duminuco, Andrea |
collection | PubMed |
description | Among the myeloproliferative diseases, myelofibrosis is a widely heterogeneous entity characterized by a highly variable prognosis. In this context, several prognostic models have been proposed to categorize these patients appropriately. Identifying who deserves more invasive treatments, such as bone marrow transplantation, is a critical clinical need. Age, complete blood count (above all, hemoglobin value), constitutional symptoms, driver mutations, and blast cells have always represented the milestones of the leading models still used worldwide (IPSS, DIPSS, MYSEC-PM). Recently, the advent of new diagnostic techniques (among all, next-generation sequencing) and the extensive use of JAK inhibitor drugs have allowed the development and validation of new models (MIPSS-70 and version 2.0, GIPSS, RR6), which are continuously updated. Finally, the new frontier of artificial intelligence promises to build models capable of drawing an overall survival perspective for each patient. This review aims to collect and summarize the existing standard prognostic models in myelofibrosis and examine the setting where each of these finds its best application. |
format | Online Article Text |
id | pubmed-10053868 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-100538682023-03-30 Myelofibrosis and Survival Prognostic Models: A Journey between Past and Future Duminuco, Andrea Nardo, Antonella Giuffrida, Gaetano Leotta, Salvatore Markovic, Uros Giallongo, Cesarina Tibullo, Daniele Romano, Alessandra Di Raimondo, Francesco Palumbo, Giuseppe A. J Clin Med Review Among the myeloproliferative diseases, myelofibrosis is a widely heterogeneous entity characterized by a highly variable prognosis. In this context, several prognostic models have been proposed to categorize these patients appropriately. Identifying who deserves more invasive treatments, such as bone marrow transplantation, is a critical clinical need. Age, complete blood count (above all, hemoglobin value), constitutional symptoms, driver mutations, and blast cells have always represented the milestones of the leading models still used worldwide (IPSS, DIPSS, MYSEC-PM). Recently, the advent of new diagnostic techniques (among all, next-generation sequencing) and the extensive use of JAK inhibitor drugs have allowed the development and validation of new models (MIPSS-70 and version 2.0, GIPSS, RR6), which are continuously updated. Finally, the new frontier of artificial intelligence promises to build models capable of drawing an overall survival perspective for each patient. This review aims to collect and summarize the existing standard prognostic models in myelofibrosis and examine the setting where each of these finds its best application. MDPI 2023-03-11 /pmc/articles/PMC10053868/ /pubmed/36983189 http://dx.doi.org/10.3390/jcm12062188 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Duminuco, Andrea Nardo, Antonella Giuffrida, Gaetano Leotta, Salvatore Markovic, Uros Giallongo, Cesarina Tibullo, Daniele Romano, Alessandra Di Raimondo, Francesco Palumbo, Giuseppe A. Myelofibrosis and Survival Prognostic Models: A Journey between Past and Future |
title | Myelofibrosis and Survival Prognostic Models: A Journey between Past and Future |
title_full | Myelofibrosis and Survival Prognostic Models: A Journey between Past and Future |
title_fullStr | Myelofibrosis and Survival Prognostic Models: A Journey between Past and Future |
title_full_unstemmed | Myelofibrosis and Survival Prognostic Models: A Journey between Past and Future |
title_short | Myelofibrosis and Survival Prognostic Models: A Journey between Past and Future |
title_sort | myelofibrosis and survival prognostic models: a journey between past and future |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10053868/ https://www.ncbi.nlm.nih.gov/pubmed/36983189 http://dx.doi.org/10.3390/jcm12062188 |
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