MOSAIC: An Artificial Intelligence-Based Framework for Multimodal Analysis, Classification, and Personalized Prognostic Assessment in Rare Cancers.

PURPOSE: Rare cancers constitute over 20% of human neoplasms, often affecting patients with unmet medical needs. The development of effective classification and prognostication systems is crucial to improve the decision-making process and drive innovative treatment strategies. We have created and implemented MOSAIC, an artificial intelligence (AI)-based framework designed for multimodal analysis, classification, and personalized prognostic assessment in rare cancers. Clinical validation was performed on myelodysplastic syndrome (MDS), a rare hematologic cancer with clinical and genomic heterogeneities. METHODS: We analyzed 4,427 patients with MDS divided into training and validation cohorts. Deep learning methods were applied to integrate and impute clinical/genomic features. Clustering was performed by combining Uniform Manifold Approximation and Projection for Dimension Reduction + Hierarchical Density-Based Spatial Clustering of Applications with Noise (UMAP + HDBSCAN) methods, compared with the conventional Hierarchical Dirichlet Process (HDP). Linear and AI-based nonlinear approaches were compared for survival prediction. Explainable AI (Shapley Additive Explanations approach [SHAP]) and federated learning were used to improve the interpretation and the performance of the clinical models, integrating them into distributed infrastructure. RESULTS: UMAP + HDBSCAN clustering obtained a more granular patient stratification, achieving a higher average silhouette coefficient (0.16) with respect to HDP (0.01) and higher balanced accuracy in cluster classification by Random Forest (92.7% ± 1.3% and 85.8% ± 0.8%). AI methods for survival prediction outperform conventional statistical techniques and the reference prognostic tool for MDS. Nonlinear Gradient Boosting Survival stands in the internal (Concordance-Index [C-Index], 0.77; SD, 0.01) and external validation (C-Index, 0.74; SD, 0.02). SHAP analysis revealed that similar features drove patients' subgroups and outcomes in both training and validation cohorts. Federated implementation improved the accuracy of developed models. CONCLUSION: MOSAIC provides an explainable and robust framework to optimize classification and prognostic assessment of rare cancers. AI-based approaches demonstrated superior accuracy in capturing genomic similarities and providing individual prognostic information compared with conventional statistical methods. Its federated implementation ensures broad clinical application, guaranteeing high performance and data protection.

Single-cell transcriptional profile of CD34+ hematopoietic progenitor cells from del(5q) myelodysplastic syndromes and impact of lenalidomide.

While myelodysplastic syndromes with del(5q) (del(5q) MDS) comprises a well-defined hematological subgroup, the molecular basis underlying its origin remains unknown. Using single cell RNA-seq (scRNA-seq) on CD34+ progenitors from del(5q) MDS patients, we have identified cells harboring the deletion, characterizing the transcriptional impact of this genetic insult on disease pathogenesis and treatment response. Interestingly, both del(5q) and non-del(5q) cells present similar transcriptional lesions, indicating that all cells, and not only those harboring the deletion, may contribute to aberrant hematopoietic differentiation. However, gene regulatory network (GRN) analyses reveal a group of regulons showing aberrant activity that could trigger altered hematopoiesis exclusively in del(5q) cells, pointing to a more prominent role of these cells in disease phenotype. In del(5q) MDS patients achieving hematological response upon lenalidomide treatment, the drug reverts several transcriptional alterations in both del(5q) and non-del(5q) cells, but other lesions remain, which may be responsible for potential future relapses. Moreover, lack of hematological response is associated with the inability of lenalidomide to reverse transcriptional alterations. Collectively, this study reveals transcriptional alterations that could contribute to the pathogenesis and treatment response of del(5q) MDS.

Treatment of post-allogeneic hematopoietic stem cell transplant cytopenias with sequential doses of multipotent mesenchymal stromal/stem cells.

BACKGROUND AIMS: Cytopenias after allogeneic stem cell transplantation (allo-SCT) are a common complication, the underlying pathogenic mechanisms of which remain incompletely understood. Multipotent mesenchymal stromal/stem cell (MSC) therapy has been successfully employed in the treatment of immune-related disorders and can aid in the restoration of the hematopoietic niche. METHODS: A phase II clinical trial to assess the efficacy and safety of administering four sequential doses of ex-vivo expanded bone marrow MSCs from a third-party donor to patients with persistent severe cytopenias after allo-SCT was performed. RESULTS: The overall response rate on day 90 was 75% among the 27 evaluable patients (comprising 12 complete responses, 8 partial responses, and 7 with no response). The median time to respond was 14.5 days. Responses were observed across different profiles, including single or multiple affected lineages, primary or secondary timing, and potential immune-mediated or post-infectious pathophysiology versus idiopathic origin. With a median follow-up for surviving patients of 85 months after MSC infusion, 53% of patients are alive. Notably, no adverse events related to MSC therapy were reported. CONCLUSIONS: In summary, the sequential infusion of third-party MSCs emerges as a viable and safe therapeutic option, exhibiting potential benefits for patients experiencing cytopenias following allo-SCT.

Personalized Timing for Allogeneic Stem-Cell Transplantation in Hematologic Neoplasms: A Target Trial Emulation Approach Using Multistate Modeling and Microsimulation.

PURPOSE: Decision about the optimal timing of a treatment procedure in patients with hematologic neoplasms is critical, especially for cellular therapies (most including allogeneic hematopoietic stem-cell transplantation [HSCT]). In the absence of evidence from randomized trials, real-world observational data become beneficial to study the effect of the treatment timing. In this study, a framework to estimate the expected outcome after an intervention in a time-to-event scenario is developed, with the aim of optimizing the timing in a personalized manner. METHODS: Retrospective real-world data are leveraged to emulate a target trial for treatment timing using multistate modeling and microsimulation. This case study focuses on myelodysplastic syndromes, serving as a prototype for rare cancers characterized by a heterogeneous clinical course and complex genomic background. A cohort of 7,118 patients treated according to conventional available treatments/evidence across Europe and United States is analyzed. The primary clinical objective is to determine the ideal timing for HSCT, the only curative option for these patients. RESULTS: This analysis enabled us to identify the most appropriate time frames for HSCT on the basis of each patient's unique profile, defined by a combination relevant patients' characteristics. CONCLUSION: The developed methodology offers a structured framework to address a relevant clinical issue in the field of hematology. It makes several valuable contributions: (1) novel insights into how to develop decision models to identify the most favorable HSCT timing, (2) evidence to inform clinical decisions in a real-world context, and (3) the incorporation of complex information into decision making. This framework can be applied to provide medical insights for clinical issues that cannot be adequately addressed through randomized clinical trials.

Clinical and Genomic-Based Decision Support System to Define the Optimal Timing of Allogeneic Hematopoietic Stem-Cell Transplantation in Patients With Myelodysplastic Syndromes.

PURPOSE: Allogeneic hematopoietic stem-cell transplantation (HSCT) is the only potentially curative treatment for patients with myelodysplastic syndromes (MDS). Several issues must be considered when evaluating the benefits and risks of HSCT for patients with MDS, with the timing of transplantation being a crucial question. Here, we aimed to develop and validate a decision support system to define the optimal timing of HSCT for patients with MDS on the basis of clinical and genomic information as provided by the Molecular International Prognostic Scoring System (IPSS-M). PATIENTS AND METHODS: We studied a retrospective population of 7,118 patients, stratified into training and validation cohorts. A decision strategy was built to estimate the average survival over an 8-year time horizon (restricted mean survival time [RMST]) for each combination of clinical and genomic covariates and to determine the optimal transplantation policy by comparing different strategies. RESULTS: Under an IPSS-M based policy, patients with either low and moderate-low risk benefited from a delayed transplantation policy, whereas in those belonging to moderately high-, high- and very high-risk categories, immediate transplantation was associated with a prolonged life expectancy (RMST). Modeling decision analysis on IPSS-M versus conventional Revised IPSS (IPSS-R) changed the transplantation policy in a significant proportion of patients (15% of patient candidate to be immediately transplanted under an IPSS-R-based policy would benefit from a delayed strategy by IPSS-M, whereas 19% of candidates to delayed transplantation by IPSS-R would benefit from immediate HSCT by IPSS-M), resulting in a significant gain-in-life expectancy under an IPSS-M-based policy (P = .001). CONCLUSION: These results provide evidence for the clinical relevance of including genomic features into the transplantation decision making process, allowing personalizing the hazards and effectiveness of HSCT in patients with MDS.

Germline assessment for alloHSCT candidates over 50 years: A 'Fast-Track' screening in myeloid neoplasms.

Patients aged 50 or above diagnosed with myeloid neoplasms (MNs) are typically not candidates for germline testing. However, approximately 8% carry pathogenic germline variants. Allogeneic haematopoietic stem cell transplantation (alloHSCT) remains an option for those aged over 50; neglecting germline testing could mask the risk for relative donor cell-derived MN. We propose a germline-augmented somatic panel (GASP), combining MN predisposition genes with a myeloid somatic panel for timely germline variant identification when initial testing is not indicated. Out of our 133 whole-exome-sequenced MN cases aged over 50 years, 9% had pathogenic/likely variants. GASP detected 92%, compared to 50% with somatic-only panel. Our study highlights the relevance of germline screening in MN, particularly for alloHSCT candidates without established germline-testing recommendations.

Hematopoietic stem cells with granulo-monocytic differentiation state overcome venetoclax sensitivity in patients with myelodysplastic syndromes.

The molecular mechanisms of venetoclax-based therapy failure in patients with acute myeloid leukemia were recently clarified, but the mechanisms by which patients with myelodysplastic syndromes (MDS) acquire secondary resistance to venetoclax after an initial response remain to be elucidated. Here, we show an expansion of MDS hematopoietic stem cells (HSCs) with a granulo-monocytic-biased transcriptional differentiation state in MDS patients who initially responded to venetoclax but eventually relapsed. While MDS HSCs in an undifferentiated cellular state are sensitive to venetoclax treatment, differentiation towards a granulo-monocytic-biased transcriptional state, through the acquisition or expansion of clones with STAG2 or RUNX1 mutations, affects HSCs' survival dependence from BCL2-mediated anti-apoptotic pathways to TNFα-induced pro-survival NF-κB signaling and drives resistance to venetoclax-mediated cytotoxicity. Our findings reveal how hematopoietic stem and progenitor cell (HSPC) can eventually overcome therapy-induced depletion and underscore the importance of using close molecular monitoring to prevent HSPC hierarchical change in MDS patients enrolled in clinical trials of venetoclax.

Difficulties on the access to innovative targeted therapies for lung cancer in Spain

Purpose Spanish Lung Cancer Group (SLCG) conducted a review to analyze the barriers to access to innovative targeted therapies for non-small cell lung cancer (NSCLC) in clinical practice in Spain. Methods Review all relevant content published on websites of European Commission, European Medicines Agency, and Spanish Agency of Medicines and Medical Products regarding the authorization and access to oncology treatments. Results More than 20 targeted therapies are available to treat different molecular alterations in patients with NSCLC. European Commission has approved treatments for genomic alterations involving the following genes: ALK, RET, ROS1, EGFR, BRAF, NTRK, KRAS, MET. However, the availability of these therapies in Spain is not complete, as innovative treatments are not reimbursed or funded late, with only five of these alterations currently covered by National Health System. Conclusion SLCG considers imperative to improve the access in Spain to innovative treatments for NSCLC to reduce inequity across European countries (AU)

Validation of the Artificial Intelligence Prognostic Scoring System for Myelodysplastic Syndromes in chronic myelomonocytic leukaemia: A novel approach for improved risk stratification.

Chronic myelomonocytic leukaemia (CMML) is a rare haematological disorder characterized by monocytosis and dysplastic changes in myeloid cell lineages. Accurate risk stratification is essential for guiding treatment decisions and assessing prognosis. This study aimed to validate the Artificial Intelligence Prognostic Scoring System for Myelodysplastic Syndromes (AIPSS-MDS) in CMML and to assess its performance compared with traditional scores using data from a Spanish registry (n = 1343) and a Taiwanese hospital (n = 75). In the Spanish cohort, the AIPSS-MDS accurately predicted overall survival (OS) and leukaemia-free survival (LFS), outperforming the Revised-IPSS score. Similarly, in the Taiwanese cohort, the AIPSS-MDS demonstrated accurate predictions for OS and LFS, showing superiority over the IPSS score and performing better than the CPSS and molecular CPSS scores in differentiating patient outcomes. The consistent performance of the AIPSS-MDS across both cohorts highlights its generalizability. Its adoption as a valuable tool for personalized treatment decision-making in CMML enables clinicians to identify high-risk patients who may benefit from different therapeutic interventions. Future studies should explore the integration of genetic information into the AIPSS-MDS to further refine risk stratification in CMML and improve patient outcomes.

Outcomes and effect of somatic mutations after erythropoiesis stimulating agents in patients with lower-risk myelodysplastic syndromes.

Background: Erythropoiesis stimulating agents (ESAs) are the first-line therapy in patients with lower-risk myelodysplastic syndromes (LR-MDS). Some predictive factors for ESAs response have been identified. Type and number of somatic mutations have been associated with prognosis and response to therapies in MDS patients. Objectives: The objective was to evaluate the outcomes after ESAs in patients with LR-MDS and to address the potential predictive value of somatic mutations in ESAs-treated patients. Design: Multi-center retrospective study of a cohort of 722 patients with LR-MDS included in the SPRESAS (Spanish Registry of Erythropoietic Stimulating Agents Study) study. Retrospective analysis of 65 patients with next generation sequencing (NGS) data from diagnosis. Methods: ESAs' efficacy and safety were evaluated in patients receiving ESAs and best supportive care (BSC). To assess the potential prognostic value of somatic mutations in erythroid response (ER) rate and outcome, NGS was performed in responders and non-responders. Results: ER rate for ESAs-treated patients was 65%. Serum erythropoietin (EPO) level <200 U/l was the only variable significantly associated with a higher ER rate (odds ratio, 2.45; p = 0.036). Median overall survival (OS) in patients treated with ESAs was 6.7 versus 3.1 years in patients receiving BSC (p < 0.001). From 65 patients with NGS data, 57 (87.7%) have at least one mutation. We observed a trend to a higher frequency of ER among patients with a lower number of mutated genes (40.4% in <3 mutated genes versus 22.2% in ⩾3; p = 0.170). The presence of ⩾3 mutated genes was also significantly associated with worse OS (hazard ratio, 2.8; p = 0.015), even in responders. A higher cumulative incidence of acute myeloid leukemia progression at 5 years was also observed in patients with ⩾3 mutated genes versus <3 (33.3% and 10.7%, respectively; p < 0.001). Conclusion: This large study confirms the beneficial effect of ESAs and the adverse effect of somatic mutations in patients with LR-MDS.

Difficulties on the access to innovative targeted therapies for lung cancer in Spain.

PURPOSE: Spanish Lung Cancer Group (SLCG) conducted a review to analyze the barriers to access to innovative targeted therapies for non-small cell lung cancer (NSCLC) in clinical practice in Spain. METHODS: Review all relevant content published on websites of European Commission, European Medicines Agency, and Spanish Agency of Medicines and Medical Products regarding the authorization and access to oncology treatments. RESULTS: More than 20 targeted therapies are available to treat different molecular alterations in patients with NSCLC. European Commission has approved treatments for genomic alterations involving the following genes: ALK, RET, ROS1, EGFR, BRAF, NTRK, KRAS, MET. However, the availability of these therapies in Spain is not complete, as innovative treatments are not reimbursed or funded late, with only five of these alterations currently covered by National Health System. CONCLUSION: SLCG considers imperative to improve the access in Spain to innovative treatments for NSCLC to reduce inequity across European countries.

Imetelstat in patients with lower-risk myelodysplastic syndromes who have relapsed or are refractory to erythropoiesis-stimulating agents (IMerge): a multinational, randomised, double-blind, placebo-controlled, phase 3 trial.

BACKGROUND: Unmet medical needs remain in patients with red blood cell transfusion-dependent (RBC-TD) lower-risk myelodysplastic syndromes (LR-MDS) who are not responding to or are ineligible for erythropoiesis-stimulating agents (ESAs). Imetelstat, a competitive telomerase inhibitor, showed promising results in a phase 2 trial. We aimed to compare the RBC transfusion independence (RBC-TI) rate with imetelstat versus placebo in patients with RBC-TD LR-MDS. METHODS: In phase 3 of IMerge, a double-blind, placebo-controlled trial conducted in 118 sites including university hospitals, cancer centres, and outpatient clinics in 17 countries, patients (aged ≥18 years) with ESA-relapsed, ESA-refractory, or ESA-ineligible LR-MDS (low or intermediate-1 risk disease as per International Prognostic Scoring System [IPSS] criteria) were randomly assigned via a computer-generated schedule (2:1) to receive imetelstat 7·5 mg/kg or placebo, administered as a 2-h intravenous infusion, every 4 weeks until disease progression, unacceptable toxic effects, or withdrawal of consent. Randomisation was stratified by previous RBC transfusion burden and IPSS risk group. Patients, investigators, and those analysing the data were masked to group assignment. The primary endpoint was 8-week RBC-TI, defined as the proportion of patients without RBC transfusions for at least 8 consecutive weeks starting on the day of randomisation until subsequent anti-cancer therapy, if any. Primary efficacy analyses were performed in the intention-to-treat population, and safety analyses were conducted in patients who received at least one dose of trial medication or placebo. This trial is registered with ClinicalTrials.gov (NCT02598661; substudy active and recruiting). FINDINGS: Between Sept 11, 2019, and Oct 13, 2021, 178 patients were enrolled and randomly assigned (118 to imetelstat and 60 to placebo). 111 (62%) were male and 67 (38%) were female. 91 (77%) of 118 patients had discontinued treatment by data cutoff in the imetelstat group versus 45 (75%) in the placebo group; a further one patient in the placebo group did not receive treatment. Median follow-up was 19·5 months (IQR 12·0-23·4) in the imetelstat group and 17·5 months (12·1-22·7) in the placebo group. In the imetelstat group, 47 (40% [95% CI 30·9-49·3]) patients had an RBC-TI of at least 8 weeks versus nine (15% [7·1-26·6]) in the placebo group (rate difference 25% [9·9 to 36·9]; p=0·0008). Overall, 107 (91%) of 118 patients receiving imetelstat and 28 (47%) of 59 patients receiving placebo had grade 3-4 treatment-emergent adverse events. The most common treatment-emergent grade 3-4 adverse events in patients taking imetelstat were neutropenia (80 [68%] patients who received imetelstat vs two [3%] who received placebo) and thrombocytopenia (73 [62%] vs five [8%]). No treatment-related deaths were reported. INTERPRETATION: Imetelstat offers a novel mechanism of action with durable transfusion independence (approximately 1 year) and disease-modifying activity for heavily transfused patients with LR-MDS who are not responding to or are ineligible for ESAs. FUNDING: Janssen Research & Development before April 18, 2019, and Geron Corporation thereafter.

Machine Learning Improves Risk Stratification in Myelodysplastic Neoplasms: An Analysis of the Spanish Group of Myelodysplastic Syndromes.

Myelodysplastic neoplasms (MDS) are a heterogeneous group of hematological stem cell disorders characterized by dysplasia, cytopenias, and increased risk of acute leukemia. As prognosis differs widely between patients, and treatment options vary from observation to allogeneic stem cell transplantation, accurate and precise disease risk prognostication is critical for decision making. With this aim, we retrieved registry data from MDS patients from 90 Spanish institutions. A total of 7202 patients were included, which were divided into a training (80%) and a test (20%) set. A machine learning technique (random survival forests) was used to model overall survival (OS) and leukemia-free survival (LFS). The optimal model was based on 8 variables (age, gender, hemoglobin, leukocyte count, platelet count, neutrophil percentage, bone marrow blast, and cytogenetic risk group). This model achieved high accuracy in predicting OS (c-indexes; 0.759 and 0.776) and LFS (c-indexes; 0.812 and 0.845). Importantly, the model was superior to the revised International Prognostic Scoring System (IPSS-R) and the age-adjusted IPSS-R. This difference persisted in different age ranges and in all evaluated disease subgroups. Finally, we validated our results in an external cohort, confirming the superiority of the Artificial Intelligence Prognostic Scoring System for MDS (AIPSS-MDS) over the IPSS-R, and achieving a similar performance as the molecular IPSS. In conclusion, the AIPSS-MDS score is a new prognostic model based exclusively on traditional clinical, hematological, and cytogenetic variables. AIPSS-MDS has a high prognostic accuracy in predicting survival in MDS patients, outperforming other well-established risk-scoring systems.

Mutational Profile Enables the Identification of a High-Risk Subgroup in Myelodysplastic Syndromes with Isolated Trisomy 8.

Trisomy 8 (+8) is the most frequent trisomy in myelodysplastic syndromes (MDS) and is associated with clinical heterogeneity and intermediate cytogenetic risk when found in isolation. The presence of gene mutations in this group of patients and the prognostic significance has not been extensively analyzed. Targeted deep sequencing was performed in a cohort of 79 MDS patients showing isolated +8. The most frequently mutated genes were: TET2 (38%), STAG2 (34.2%), SRSF2 (29.1%) and RUNX1 (26.6%). The mutational profile identified a high-risk subgroup with mutations in STAG2, SRSF2 and/or RUNX1, resulting in shorter time to acute myeloid leukemia progression (14 months while not reached in patients without these mutations, p < 0.0001) and shorter overall survival (23.7 vs. 46.3 months, p = 0.001). Multivariate analyses revealed the presence of mutations in these genes as an independent prognostic factor in MDS showing +8 isolated (HR: 3.1; p < 0.01). Moreover, 39.5% and 15.4% of patients classified as low/intermediate risk by the IPSS-R and IPSS-M, respectively, were re-stratified as a high-risk subgroup based on the mutational status of STAG2, SRSF2 and RUNX1. Results were validated in an external cohort (n = 2494). In summary, this study validates the prognosis significance of somatic mutations shown in IPSS-M and adds STAG2 as an important mutated gene to consider in this specific subgroup of patients. The mutational profile in isolated +8 MDS patients could, therefore, offer new insights for the correct management of patients with a higher risk of leukemic transformation.

Efficacy of Lorlatinib in Treatment-Naive Patients With ALK-Positive Advanced NSCLC in Relation to EML4::ALK Variant Type and ALK With or Without TP53 Mutations.

INTRODUCTION: Lorlatinib, a third-generation ALK tyrosine kinase inhibitor, improved outcomes compared with crizotinib in patients with previously untreated ALK-positive advanced NSCLC in the phase 3 CROWN study. Here, we investigated response correlates using plasma circulating tumor DNA (ctDNA) and tumor tissue profiling. METHODS: ALK fusions and ALK with or without TP53 mutations were assessed by next-generation sequencing. End points included objective response rate (ORR), duration of response, and progression-free survival (PFS) by blinded independent central review on the basis of EML4::ALK variants and ALK with or without TP53 or other mutation status. RESULTS: ALK fusions were detected in the ctDNA of 62 patients in the lorlatinib arm and 64 patients in the crizotinib arm. ORRs were numerically higher with lorlatinib versus crizotinib for EML4::ALK variant 1 (v1; 80.0% versus 50.0%) and variant 2 (v2; 85.7% versus 50.0%) but were similar between the arms for variant 3 (v3; 72.2% versus 73.9%). Median PFS in the lorlatinib arm was not reached for EML4::ALK v1 and v2 and was 33.3 months for v3; in the crizotinib arm, median PFS was 7.4 months, not reached, and 5.5 months, respectively. ORRs and PFS were improved with lorlatinib versus crizotinib regardless of TP53 mutation status and in patients harboring preexisting bypass pathway resistance alterations. In the lorlatinib arm, PFS was lower in patients who had a co-occurring TP53 mutation. Results from ctDNA analysis were similar to those observed with tumor tissue samples. CONCLUSIONS: Patients with untreated ALK-positive advanced NSCLC derived greater clinical benefits, with higher ORRs and potentially longer PFS, when treated with lorlatinib compared with crizotinib, independent of EML4::ALK variant or ALK mutations, TP53 mutations, or bypass resistance alterations.

Synthetic Data Generation by Artificial Intelligence to Accelerate Research and Precision Medicine in Hematology.

PURPOSE: Synthetic data are artificial data generated without including any real patient information by an algorithm trained to learn the characteristics of a real source data set and became widely used to accelerate research in life sciences. We aimed to (1) apply generative artificial intelligence to build synthetic data in different hematologic neoplasms; (2) develop a synthetic validation framework to assess data fidelity and privacy preservability; and (3) test the capability of synthetic data to accelerate clinical/translational research in hematology. METHODS: A conditional generative adversarial network architecture was implemented to generate synthetic data. Use cases were myelodysplastic syndromes (MDS) and AML: 7,133 patients were included. A fully explainable validation framework was created to assess fidelity and privacy preservability of synthetic data. RESULTS: We generated MDS/AML synthetic cohorts (including information on clinical features, genomics, treatment, and outcomes) with high fidelity and privacy performances. This technology allowed resolution of lack/incomplete information and data augmentation. We then assessed the potential value of synthetic data on accelerating research in hematology. Starting from 944 patients with MDS available since 2014, we generated a 300% augmented synthetic cohort and anticipated the development of molecular classification and molecular scoring system obtained many years later from 2,043 to 2,957 real patients, respectively. Moreover, starting from 187 MDS treated with luspatercept into a clinical trial, we generated a synthetic cohort that recapitulated all the clinical end points of the study. Finally, we developed a website to enable clinicians generating high-quality synthetic data from an existing biobank of real patients. CONCLUSION: Synthetic data mimic real clinical-genomic features and outcomes, and anonymize patient information. The implementation of this technology allows to increase the scientific use and value of real data, thus accelerating precision medicine in hematology and the conduction of clinical trials.

Real-World Validation of Molecular International Prognostic Scoring System for Myelodysplastic Syndromes.

PURPOSE: Myelodysplastic syndromes (MDS) are heterogeneous myeloid neoplasms in which a risk-adapted treatment strategy is needed. Recently, a new clinical-molecular prognostic model, the Molecular International Prognostic Scoring System (IPSS-M) was proposed to improve the prediction of clinical outcome of the currently available tool (Revised International Prognostic Scoring System [IPSS-R]). We aimed to provide an extensive validation of IPSS-M. METHODS: A total of 2,876 patients with primary MDS from the GenoMed4All consortium were retrospectively analyzed. RESULTS: IPSS-M improved prognostic discrimination across all clinical end points with respect to IPSS-R (concordance was 0.81 v 0.74 for overall survival and 0.89 v 0.76 for leukemia-free survival, respectively). This was true even in those patients without detectable gene mutations. Compared with the IPSS-R based stratification, the IPSS-M risk group changed in 46% of patients (23.6% and 22.4% of subjects were upstaged and downstaged, respectively).In patients treated with hematopoietic stem cell transplantation (HSCT), IPSS-M significantly improved the prediction of the risk of disease relapse and the probability of post-transplantation survival versus IPSS-R (concordance was 0.76 v 0.60 for overall survival and 0.89 v 0.70 for probability of relapse, respectively). In high-risk patients treated with hypomethylating agents (HMA), IPSS-M failed to stratify individual probability of response; response duration and probability of survival were inversely related to IPSS-M risk.Finally, we tested the accuracy in predicting IPSS-M when molecular information was missed and we defined a minimum set of 15 relevant genes associated with high performance of the score. CONCLUSION: IPSS-M improves MDS prognostication and might result in a more effective selection of candidates to HSCT. Additional factors other than gene mutations can be involved in determining HMA sensitivity. The definition of a minimum set of relevant genes may facilitate the clinical implementation of the score.

Consensus proposal for revised International Working Group 2023 response criteria for higher-risk myelodysplastic syndromes.

Myelodysplastic syndromes/myelodysplastic neoplasms (MDS) are associated with variable clinical presentations and outcomes. The initial response criteria developed by the International Working Group (IWG) in 2000 have been used in clinical practice, clinical trials, regulatory reviews, and drug labels. Although the IWG criteria were revised in 2006 and 2018 (the latter focusing on lower-risk disease), limitations persist in their application to higher-risk MDS (HR-MDS) and their ability to fully capture the clinical benefits of novel investigational drugs or serve as valid surrogates for longer-term clinical end points (eg, overall survival). Further, issues related to the ambiguity and practicality of some criteria lead to variability in interpretation and interobserver inconsistency in reporting results from the same sets of data. Thus, we convened an international panel of 36 MDS experts and used an established modified Delphi process to develop consensus recommendations for updated response criteria that would be more reflective of patient-centered and clinically relevant outcomes in HR-MDS. Among others, the IWG 2023 criteria include changes in the hemoglobin threshold for complete remission (CR), the introduction of CR with limited count recovery and CR with partial hematologic recovery as provisional response criteria, the elimination of marrow CR, and specific recommendations for the standardization of time-to-event end points and the derivation and reporting of responses. The updated criteria should lead to a better correlation between patient-centered outcomes and clinical trial results in an era of multiple emerging new agents with novel mechanisms of action.

First-line nivolumab plus ipilimumab for metastatic non-small cell lung cancer, including patients with ECOG performance status 2 and other special populations: CheckMate 817.

BACKGROUND: CheckMate 817, a phase 3B study, evaluated flat-dose nivolumab plus weight-based ipilimumab in patients with metastatic non-small cell lung cancer (NSCLC). Here, in this research, we report on first-line treatment in patients with Eastern Cooperative Oncology Group (ECOG) performance status (PS) 0-1 (cohort A) and special populations (cohort A1: ECOG PS 2; or ECOG PS 0-1 with untreated brain metastases, renal impairment, hepatic impairment, or controlled HIV infection). METHODS: Cohorts A and A1 received nivolumab 240 mg every 2 weeks plus ipilimumab 1 mg/kg every 6 weeks. The primary endpoint was the incidence of grade 3-4 and grade 5 immune-mediated adverse events (IMAEs; adverse events (AEs) deemed potentially immune-related, occurring <100 days of last dose, and treated with immune-modulating medication (except endocrine events)) and treatment-related select AEs (treatment-related AEs with potential immunological etiology requiring frequent monitoring/intervention, reported between first dose and 30 days after the last dose) in cohort A; efficacy endpoints were secondary/exploratory. In cohort A1, safety/efficacy assessment was exploratory. RESULTS: The most common grade 3-4 IMAEs were pneumonitis (5.1%), diarrhea/colitis (4.9%), and hepatitis (4.6%) in cohort A (N=391) and diarrhea/colitis (3.5%), hepatitis (3.5%), and rash (3.0%) in cohort A1 (N=198). The most common grade 3-4 treatment-related select AEs were hepatic (5.9%), gastrointestinal (4.9%), and pulmonary (4.6%) events in cohort A and gastrointestinal (4.0%), skin (3.5%), and endocrine (3.0%) events in cohort A1. No grade 5 IMAEs or treatment-related select AEs occurred. Treatment-related deaths occurred in 4 (1.0%) and 3 (1.5%) patients in cohorts A and A1, respectively. Three-year overall survival (OS) rates were 33.7% and 20.5%, respectively. CONCLUSIONS: Flat-dose nivolumab plus weight-based ipilimumab was associated with manageable safety and durable efficacy in cohort A, consistent with data from phase 3 metastatic NSCLC studies. Special populations of cohort A1 including patients with ECOG PS 2 or ECOG PS 0-1 with untreated brain metastases had manageable treatment-related toxicity and clinically meaningful 3-year OS rate. TRIAL REGISTRATION NUMBER: NCT02869789.

Improved benefit of continuing luspatercept therapy: sub-analysis of patients with lower-risk MDS in the MEDALIST study.

Red blood cell transfusion independence (RBC-TI) is an important goal in treating lower-risk myelodysplastic syndromes with ring sideroblasts. In the phase 3 MEDALIST study, RBC-TI of ≥ 8 weeks was achieved by significantly more luspatercept- versus placebo-treated patients in the first 24 weeks of treatment. In this post hoc analysis, we evaluated RBC transfusion units and visits based on patients' baseline transfusion burden level and the clinical benefit of luspatercept treatment beyond week 25 in initial luspatercept nonresponders (patients who did not achieve RBC-TI ≥ 8 weeks by week 25) but continued luspatercept up to 144 weeks. RBC transfusion burden, erythroid response, serum ferritin levels, and hemoglobin levels relative to baseline were evaluated. Through week 25, fewer RBC transfusion units and visits were observed in luspatercept-treated patients versus placebo, regardless of baseline transfusion burden. This continued through 144 weeks of luspatercept treatment, particularly in patients with low baseline transfusion burden. Sixty-eight patients were initial nonresponders at week 25 but continued treatment; most (81%) received the maximum dose of luspatercept (1.75 mg/kg). Sixteen percent achieved RBC-TI for ≥ 8 weeks during weeks 25-48, 26% had reduced RBC transfusion burden, 10% achieved an erythroid response, 44% had reduced serum ferritin, and hemoglobin levels increased an average of 1.3 g/dL from baseline. These data have implications for clinical practice, as transfusion units and visits are less in luspatercept-treated patients through week 25 regardless of baseline transfusion burden, and continuing luspatercept beyond week 25 can potentially provide additional clinical benefits for initial nonresponders. Trial registration: NCT02631070.