Casetti, Ilaria Carola

PURPOSE Chronic myelomonocytic leukemia (CMML) is a rare myeloid neoplasm characterized by clinical heterogeneity and is associated with poor outcomes. To date, limited molecular information has been incorporated into disease classification and risk stratification. We aimed to integrate genomic features into the clinical decision-making process for CMML. PATIENTS AND METHODS We analyzed a retrospective cohort of 3013 patients with CMML (training set) and a prospective population of 516 patients (validation set). Using an innovative framework for multimodal data analysis, we developed molecular-based disease taxonomy and prognostication. RESULTS Unsupervised clustering identified nine entities with distinct genomic features and outcomes ( P < .001), including splicing machinery, transcription factors, signal transduction and tyrosine kinase pathways aberrations, and high-risk molecular signatures. Notably, 15% of patients showed molecular/clinical overlap with other myeloid neoplasms. We integrated molecular and clinical information to build the international CMML Prognostic Scoring System (iCPSS), incorporating mutations in nine genes together with hematologic parameters and cytogenetic abnormalities. The iCPSS identified five groups with distinct probability of overall and leukemia-free survival in both training and validation cohorts ( P < .001), outperforming existing prognostic models. Importantly, 55% of patients were reassigned to higher or lower risk groups by the iCPSS. Decision analysis demonstrated that iCPSS could refine the optimal timing of allogeneic transplantation at the individual level; compared with conventional prognostic tools, iCPSS-based decision modeling changed transplantation strategy in 31% of cases, resulting in a significant gain-in-life expectancy for eligible patient population ( P < .001). A federated learning platform was implemented to enable continuous, privacy-preserving model update across multiple centers. CONCLUSION Molecular information improves CMML classification and prognostication, supports more effective clinical decision making, and potentially refines the design of clinical trials.

Background. Study of myeloid neoplasms (MN) has been rapidly transformed by genome characterization. Gene mutations have been reported to influence disease phenotype and risk of disease progression, and the evaluation of mutational status can provide valuable insights to improve the decision-making process. In this international study, we evaluated the clinical impact of mutational screening in patients with CMML, which is characterized by significant clinical and genomic heterogeneity, including a substantial proportion of patients with poor outcomes and unmet needs. Currently, only limited molecular information has been incorporated into CMML classification and prognostication. Methods. We retrospectively collected 3182 CMML patients. We used MOSAIC, an AI-based framework for multimodal analysis in rare cancers (PMID: 38875514) to develop innovative, molecular-based tools for classification and prognostication. An independent validation of the results on 516 prospectively collected patients was performed. Results. Bayesian Networs and Hierarchical Dirichlet Processes were used to identify genomic associations and define a CMML molecular classification. We identified 11 clusters with distinct clinical and genomic features, including splicing machinery, signal transduction and tyrosine kinase pathways aberrations, and high-risk molecular signatures (i.e., AML-like and TP53 mutations). Up to 15% of patients showed clear genomic overlap with other MN. Importantly, extensive multi-color flow cytometry on T lymphocytes, NK and myeloid cells (BD FACSymphony A5 Cell Analyzer) revealed specific immunologic and inflammation signatures associated with molecular subgroups. We then integrated molecular and clinical information to build an international CMML Prognostic Scoring System (iCPSS). We assessed the performance of different statistical and AI-based methods; L1-penalized Cox Model resulted as the best performing method. Selected features included hematological parameters (WBC, Hb, PLT and marrow blasts), cytogenetic abnormalities, and mutations in 10 genes (ASXL1, DNMT3A, EZH2, NRAS, RUNX1, SETBP1, STAG2, TET2, TP53, U2AF1). By Bayesian thresholds optimization, we identified 5 risk classes (i.e., very-low, low, intermediate, high and very-high) with median overall survival (OS) ranging from 99 to 9 months (P&lt;.001), and median leukemia-free survival (LFS) ranging from 210 to 18 months (P&lt;.001). iCPSS provided better patient discrimination across all clinical endpoints compared to currently available prognostic tools, with a Concordance Index (CI) for OS of 0.75 versus 0.62-0.64, respectively. Notably, compared to available scoring systems, up to 40% of patients were reassigned to higher or lower risk classes by the iCPSS. External validation on an independent prospective cohort confirmed that the performance of iCPSS is superior to existing prognostic models (CI for OS 0.71 vs 0.54-0.61, respectively) To demonstrate the clinical utility of iCPSS, we focused on 753 patients who underwent allogeneic stem cell transplantation (HSCT). In multivariable analysis, iCPSS stratified the probability of OS post-HSCT (P&lt;.001) and identified groups of patients with different probabilities of disease relapse, ranging from 9% to 62% (P&lt;.001). We employed a clinical- and genomic-based decision support system (PMID: 38723212) to determine the optimal timing of HSCT. Preliminary analyses indicated that higher-risk patients according to iCPSS (i.e., intermediate, high, and very high) benefit from an immediate HSCT strategy. Lower-risk patients (i.e., very low and low) had life expectancy maximized with delayed HSCT. Modeling decision analysis using iCPSS compared to conventional scores, resulted in a change in transplantation policy for a significant proportion of patients (up to 25%). Conclusion. Molecular information significantly improves the classification of CMML patients, providing a basis for refining diagnostic boundaries with other MN and for a more rational inclusion of patients in clinical trials. The iCPSS demonstrated superior performance over currently available scoring systems and improved HSCT decision making process.

Abstract Background Current risk stratification in Polycythemia Vera (PV), is designed to estimate the likelihood of thrombotic complications. In ECLAP large prospective study of 1638 PV cases diagnosed by Polycythemia Vera Study Group (PVSG) criteria, risk factors were age over 65 years and prior thrombotic events. After the JAK2V617F discovery, diagnosis has undergone substantial revision by the World Health Organization (WHO). Consequently, current risk factors determination should be described in patients diagnosed by the most recent recommendations and requires a large sample size with reliable and sufficiently long clinical course documentation. Accordingly, the current study includes 1545 patients with strictly WHO-defined PV diagnosed and followed-up in seven centers from Italy, Austria and the United States, belonging to the International Working Group for Myeloproliferative Neoplasm (MPN) Research and Treatment (IWG-MRT). Objective and design 1) Describe the rate of thrombosis in this population; 2) Report the sites and frequency of recurrences after a first arterial or venous event; 3) Identify separately risk factors for arterial versus venous thrombosis and develop practically useful prognostic models. Results 1. Presenting features The characteristics of the cohort recruited reflected well the heterogeneity of epidemiologic and clinical features that are found in the routine clinical practice of PV. Arterial and venous thrombosis history before or at diagnosis was documented in 246 (16%) and 114 (7.4%) patients, respectively. The frequencies of arterial and venous thrombosis were lower than those recorded in the ECLAP4 (27% and 11% respectively) but comparable to those reported in the recent Cyto-PV2 (arterial 17%, venous 12%) studies. The discrepancy might be partly related to earlier diagnosis in the post-ECLAP JAK2mutation era. 2. Thrombotic events after diagnosis Median follow-up was 6.9 years and treatment included aspirin (84%) and cytoreductive agents (73%), in addition to phlebotomy. Post-diagnosis total major thrombosis rate was 2.62% pt/yr, lower than reported in the ECLAP trial (4.4% pt/yr) but comparable to the Cyto-PV study (2.7% pt/yr) where management of cardiovascular risk factors was more intensive than in ECLAP. Arterial or venous thrombosis occurred in 184 (12%, rate: 1.59 % pts/yr) and 137 (9%, rate: 1.05 % pts/yr) patients, respectively. In addition, prior arterial events were associated in 75% of cases with subsequent arterial events and in the remaining 25% with venous thrombosis including splanchnic vein events. Moreover, patients with prior venous events had recurrences in venous district in 61% of cases and in the arterial district in 39%. 3. Risk factors for arterial versus venous thrombosis and prognostic models In multivariable analysis, arterial thrombosis was predicted by previous arterial event (HR 1.7, 95% CI 1.2-2.4), and hypertension (HR 1.6, 95% CI 1.2-2.2) while predictors of venous events were previous venous thrombosis (HR 2.6, 95% CI 1.5-4.4), and age ≥ 65 years (HR 1.7, 95% CI 1.2-2.5). We used the above-mentioned risk factors in order to develop prognostic models allowing to identify patients at different probability to develop arterial or venous thrombosis. For arterial thrombosis, the absence of previous arterial thrombosis and hypertension defined lower-risk (rate 1.27 % pts/yr) while the presence of one or both identified higher-risk patients (rate 2.04 % pts/yr). Previous venous event and/or age ≥ 65 years identified patients at higher risk of venous (rate 1.62 % pts/yr) thrombosis and, if absent, patients at lower risk (rate 0.78 % pts/yr). Conclusion The overall rate of thrombosis was half than in ECLAP and should be considered in future clinical trials. Of note, patients with a prior venous thrombosis had a more frequent subsequent recurrence in the venous district but a proportion of them (40%) had also arterial events; conversely, recurrences after previous arterial event were also registered in the leg and non-leg veins in 30 % of cases, indicating that in PV, venous and arterial thrombosis may share some common pathogenetic mechanisms. These findings may have practical implications and suggests antiplatelet therapy and anticoagulant therapy as the favorite choice to prevent arterial and venous thrombosis, respectively, but also suggests studies of antithrombotic drug combination. Disclosures No relevant conflicts of interest to declare.