Marco Lincango, Verónica Andreoli, Hernán García Rivello, Andrea Bender, Ana I Catalán, Marilina Rahhal, Rocío Delamer, Mariana Asinari, Adrián Mosquera Orgueira, María Belén Castro, María José Mela Osorio, Alicia Navickas, Sofia Grille, Evangelina Agriello, Jorge Arbelbide, Ana Lisa Basquiera, Carolina B Belli
{"title":"评估下一代测序时代骨髓增生异常综合征非分子预后系统的相关性。","authors":"Marco Lincango, Verónica Andreoli, Hernán García Rivello, Andrea Bender, Ana I Catalán, Marilina Rahhal, Rocío Delamer, Mariana Asinari, Adrián Mosquera Orgueira, María Belén Castro, María José Mela Osorio, Alicia Navickas, Sofia Grille, Evangelina Agriello, Jorge Arbelbide, Ana Lisa Basquiera, Carolina B Belli","doi":"10.3343/alm.2024.0089","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>The Molecular International Prognostic Scoring System (IPSS-M) has improved the prediction of clinical outcomes for myelodysplastic syndromes (MDS). The Artificial Intelligence Prognostic Scoring System for MDS (AIPSS-MDS), based on classical clinical parameters, has outperformed the IPSS, revised version (IPSS-R). For the first time, we validated the IPSS-M and other molecular prognostic models and compared them with the established IPSS-R and AIPSS-MDS models using data from South American patients.</p><p><strong>Methods: </strong>Molecular and clinical data from 145 patients with MDS and 37 patients with MDS/myeloproliferative neoplasms were retrospectively analyzed.</p><p><strong>Results: </strong>Prognostic power evaluation revealed that the IPSS-M (Harrell's concordance [C]-index: 0.75, area under the receiver operating characteristic curve [AUC]: 0.68) predicted overall survival better than the European MDS (EuroMDS; C-index: 0.72, AUC: 0.68) and Munich Leukemia Laboratory (MLL) (C-index: 0.70, AUC: 0.64) models. The IPSS-M prognostic discrimination was similar to that of the AIPSS-MDS model (C-index: 0.74, AUC: 0.66) and outperformed the IPSS-R model (C-index: 0.70, AUC: 0.61). Considering simplified low- and high-risk groups for clinical management, after restratifying from IPSS-R (57% and 32%, respectively, hazard ratio [HR]: 2.8; <i>P</i>=0.002) to IPSS-M, 12.6% of patients were upstaged, and 5% were downstaged (HR: 2.9; <i>P</i>=0.001). The AIPSS-MDS recategorized 51% of the low-risk cohort as high-risk, with no patients being downstaged (HR: 5.6; <i>P</i><0.001), consistent with most patients requiring disease-modifying therapy.</p><p><strong>Conclusions: </strong>The IPSS-M and AIPSS-MDS models provide more accurate survival prognoses than the IPSS-R, EuroMDS, and MLL models. The AIPSS-MDS model is a valid option for assessing risks for all patients with MDS, especially in resource-limited centers where molecular testing is not currently a standard clinical practice.</p>","PeriodicalId":8421,"journal":{"name":"Annals of Laboratory Medicine","volume":" ","pages":""},"PeriodicalIF":4.0000,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Assessing the Relevance of Non-molecular Prognostic Systems for Myelodysplastic Syndrome in the Era of Next-Generation Sequencing.\",\"authors\":\"Marco Lincango, Verónica Andreoli, Hernán García Rivello, Andrea Bender, Ana I Catalán, Marilina Rahhal, Rocío Delamer, Mariana Asinari, Adrián Mosquera Orgueira, María Belén Castro, María José Mela Osorio, Alicia Navickas, Sofia Grille, Evangelina Agriello, Jorge Arbelbide, Ana Lisa Basquiera, Carolina B Belli\",\"doi\":\"10.3343/alm.2024.0089\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>The Molecular International Prognostic Scoring System (IPSS-M) has improved the prediction of clinical outcomes for myelodysplastic syndromes (MDS). The Artificial Intelligence Prognostic Scoring System for MDS (AIPSS-MDS), based on classical clinical parameters, has outperformed the IPSS, revised version (IPSS-R). For the first time, we validated the IPSS-M and other molecular prognostic models and compared them with the established IPSS-R and AIPSS-MDS models using data from South American patients.</p><p><strong>Methods: </strong>Molecular and clinical data from 145 patients with MDS and 37 patients with MDS/myeloproliferative neoplasms were retrospectively analyzed.</p><p><strong>Results: </strong>Prognostic power evaluation revealed that the IPSS-M (Harrell's concordance [C]-index: 0.75, area under the receiver operating characteristic curve [AUC]: 0.68) predicted overall survival better than the European MDS (EuroMDS; C-index: 0.72, AUC: 0.68) and Munich Leukemia Laboratory (MLL) (C-index: 0.70, AUC: 0.64) models. The IPSS-M prognostic discrimination was similar to that of the AIPSS-MDS model (C-index: 0.74, AUC: 0.66) and outperformed the IPSS-R model (C-index: 0.70, AUC: 0.61). Considering simplified low- and high-risk groups for clinical management, after restratifying from IPSS-R (57% and 32%, respectively, hazard ratio [HR]: 2.8; <i>P</i>=0.002) to IPSS-M, 12.6% of patients were upstaged, and 5% were downstaged (HR: 2.9; <i>P</i>=0.001). The AIPSS-MDS recategorized 51% of the low-risk cohort as high-risk, with no patients being downstaged (HR: 5.6; <i>P</i><0.001), consistent with most patients requiring disease-modifying therapy.</p><p><strong>Conclusions: </strong>The IPSS-M and AIPSS-MDS models provide more accurate survival prognoses than the IPSS-R, EuroMDS, and MLL models. The AIPSS-MDS model is a valid option for assessing risks for all patients with MDS, especially in resource-limited centers where molecular testing is not currently a standard clinical practice.</p>\",\"PeriodicalId\":8421,\"journal\":{\"name\":\"Annals of Laboratory Medicine\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":4.0000,\"publicationDate\":\"2024-07-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Annals of Laboratory Medicine\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.3343/alm.2024.0089\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MEDICAL LABORATORY TECHNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annals of Laboratory Medicine","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.3343/alm.2024.0089","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MEDICAL LABORATORY TECHNOLOGY","Score":null,"Total":0}
Assessing the Relevance of Non-molecular Prognostic Systems for Myelodysplastic Syndrome in the Era of Next-Generation Sequencing.
Background: The Molecular International Prognostic Scoring System (IPSS-M) has improved the prediction of clinical outcomes for myelodysplastic syndromes (MDS). The Artificial Intelligence Prognostic Scoring System for MDS (AIPSS-MDS), based on classical clinical parameters, has outperformed the IPSS, revised version (IPSS-R). For the first time, we validated the IPSS-M and other molecular prognostic models and compared them with the established IPSS-R and AIPSS-MDS models using data from South American patients.
Methods: Molecular and clinical data from 145 patients with MDS and 37 patients with MDS/myeloproliferative neoplasms were retrospectively analyzed.
Results: Prognostic power evaluation revealed that the IPSS-M (Harrell's concordance [C]-index: 0.75, area under the receiver operating characteristic curve [AUC]: 0.68) predicted overall survival better than the European MDS (EuroMDS; C-index: 0.72, AUC: 0.68) and Munich Leukemia Laboratory (MLL) (C-index: 0.70, AUC: 0.64) models. The IPSS-M prognostic discrimination was similar to that of the AIPSS-MDS model (C-index: 0.74, AUC: 0.66) and outperformed the IPSS-R model (C-index: 0.70, AUC: 0.61). Considering simplified low- and high-risk groups for clinical management, after restratifying from IPSS-R (57% and 32%, respectively, hazard ratio [HR]: 2.8; P=0.002) to IPSS-M, 12.6% of patients were upstaged, and 5% were downstaged (HR: 2.9; P=0.001). The AIPSS-MDS recategorized 51% of the low-risk cohort as high-risk, with no patients being downstaged (HR: 5.6; P<0.001), consistent with most patients requiring disease-modifying therapy.
Conclusions: The IPSS-M and AIPSS-MDS models provide more accurate survival prognoses than the IPSS-R, EuroMDS, and MLL models. The AIPSS-MDS model is a valid option for assessing risks for all patients with MDS, especially in resource-limited centers where molecular testing is not currently a standard clinical practice.
期刊介绍:
Annals of Laboratory Medicine is the official journal of Korean Society for Laboratory Medicine. The journal title has been recently changed from the Korean Journal of Laboratory Medicine (ISSN, 1598-6535) from the January issue of 2012. The JCR 2017 Impact factor of Ann Lab Med was 1.916.