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 improvedthe prediction of clinical outcomes for myelodysplastic syndromes (MDS). The ArtificialIntelligence Prognostic Scoring System for MDS (AIPSS-MDS), based on classical clinicalparameters, has outperformed the IPSS, revised version (IPSS-R). For the first time, wevalidated the IPSS-M and other molecular prognostic models and compared them with theestablished 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 withMDS/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) predictedoverall survival better than the European MDS (EuroMDS; C-index: 0.72, AUC: 0.68) andMunich Leukemia Laboratory (MLL) (C-index: 0.70, AUC: 0.64) models. The IPSS-M prognosticdiscrimination 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 simplifiedlow- 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 wereupstaged, and 5% were downstaged (HR: 2.9; P =0.001). The AIPSS-MDS recategorized51% 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 prognosesthan the IPSS-R, EuroMDS, and MLL models. The AIPSS-MDS model is a valid optionfor assessing risks for all patients with MDS, especially in resource-limited centers wheremolecular testing is not currently a standard clinical practice. Fil: Lincango Yupanki, Marco Vinicio. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Medicina Experimental. Academia Nacional de Medicina de Buenos Aires. Instituto de Medicina Experimental; Argentina Fil: Andreoli, Verónica. Hospital Privado Universitario de Cordoba.; Argentina