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.

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.

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.

Evaluation of the outcomes of newly diagnosed patients with high-risk myelodysplastic syndrome according to the initial therapeutical strategies chosen in usual clinical practice.

Myelodysplastic syndromes (MDS) are a heterogeneous group of diseases without a care standard and show variability in treatment outcomes. This Spanish, observational, prospective study ERASME (CEL-SMD-2012-01) assessed the evolution of newly diagnosed and treatment-naïve high-risk MDS patients (according to IPPS-R). 204 patients were included: median age 73.0 years, 54.4% males, 69.6% 0-1 ECOG, and 94.6% with comorbidities. Active treatment was the most common strategy (52.0%) vs. stem cell transplantation (25.5%) and supportive care/watchful-waiting (22.5%). Overall (median) event-free survival was 7.9 months (9.1, 8.3, and 5.3); progression-free survival: 10.1 months (12.9, 12.8, and 4.3); and overall survival: 13.8 months (15.4, 14.9; 8.4), respectively, with significant differences among groups. Adverse events (AEs) of ≥3 grade were reported in 72.6% of patients; serious AEs reported in 60.6%. 33.1% of patients died due to AEs. Three patients developed second primary malignant neoplasms (median: 8.2 months). Our study showed better outcomes in patients receiving active therapy early after diagnosis.

The transcription factor DDIT3 is a potential driver of dyserythropoiesis in myelodysplastic syndromes.

Myelodysplastic syndromes (MDS) are hematopoietic stem cell (HSC) malignancies characterized by ineffective hematopoiesis, with increased incidence in older individuals. Here we analyze the transcriptome of human HSCs purified from young and older healthy adults, as well as MDS patients, identifying transcriptional alterations following different patterns of expression. While aging-associated lesions seem to predispose HSCs to myeloid transformation, disease-specific alterations may trigger MDS development. Among MDS-specific lesions, we detect the upregulation of the transcription factor DNA Damage Inducible Transcript 3 (DDIT3). Overexpression of DDIT3 in human healthy HSCs induces an MDS-like transcriptional state, and dyserythropoiesis, an effect associated with a failure in the activation of transcriptional programs required for normal erythroid differentiation. Moreover, DDIT3 knockdown in CD34+ cells from MDS patients with anemia is able to restore erythropoiesis. These results identify DDIT3 as a driver of dyserythropoiesis, and a potential therapeutic target to restore the inefficient erythroid differentiation characterizing MDS patients.

Prognostic impact of micromegakaryocytes in primary myelodysplastic syndromes.

Micromegakaryocytes (microMKs) are considered a myelodysplastic feature of myeloid neoplasms in adults, with an adverse prognosis connotation. However, this notion in MDS has not been well proved. In our cohort of 287 MDS, patients with microMKs showed lower overall survival (OS) (HR, 2.12; 95% CI, 1.47-3.06; p = 0.000036) and higher risk of acute myeloid leukemia (AML) evolution (HR, 4.8; 95% CI, 2.9-11.01; p = 0.00021). Results were validated with an independent cohort. In multivariate analysis, the presence of microMKs maintained its independent association with OS (HR, 1.54, 95% CI, 1.13-2.1, p = 0.0059) and AML transformation (HR, 2.28, 95% CI, 1.2-4.4, p = 0.014). Moreover, by adding 1 point to the IPSS-R score in patients with microMKs, we improved the IPSS-R accuracy. Interestingly, adding that 1-point, 29% of intermediate IPSS-R risk group patients were upgraded to the high-risk group. In summary, we confirmed that the presence of microMKs implies worse outcomes in MDS and suggested a modification improving IPSS-R.

Outcomes of patients with chronic myelomonocytic leukaemia treated with non-curative therapies: a retrospective cohort study.

BACKGROUND: Approval of hypomethylating agents in patients with chronic myelomonocytic leukaemia is based on trials done in patients with myelodysplastic syndromes. We aimed to investigate whether hypomethylating agents provide a benefit in subgroups of patients with chronic myelomonocytic leukaemia compared with other treatments. METHODS: For this retrospective cohort study, data were retrieved between Nov 30, 2017, and Jan 5, 2019, from 38 centres in the USA and Europe. We included non-selected, consecutive patients diagnosed with chronic myelomonocytic leukaemia, who received chronic myelomonocytic leukaemia-directed therapy. Patients with acute myeloid leukaemia according to 2016 WHO criteria at initial diagnosis (ie, ≥20% blasts in the bone marrow or peripheral blood) or with unavailability of treatment data were excluded. Outcomes assessed included overall survival, time to next treatment, and time to transformation to acute myeloid leukaemia. Analyses were adjusted by age, sex, platelet count, and Chronic myelomonocytic leukaemia-Specific Prognostic Scoring System (CPSS). Patients were grouped by first received treatment with either hydroxyurea, hypomethylating agents, or intensive chemotherapy, and stratified by risk according to blast count, French-American-British subtype, CPSS, WHO 2016 subtype, and the eligibility criteria of the DACOTA trial (NCT02214407). FINDINGS: 949 patients diagnosed with chronic myelomonocytic leukaemia between April 13, 1981, and Oct 26, 2018, were included. Median follow-up was 23·4 months (IQR 11·5-42·3) from diagnosis and 16·2 months (6·6-31·6) from start of first-line treatment. 412 (43%) of 949 patients received hypomethylating agents as first treatment, 391 (41%) hydroxyurea, and 83 (9%) intensive chemotherapy. Adjusted median overall survival for patients treated with hydroxyurea versus hypomethylating agents was 15·6 months (95% CI 13·1-17·3) versus 20·7 months (17·9-23·4); hazard ratio (HR) 1·39 (1·17-1·65; p=0·0002) and 14·0 months (9·8-17·2) versus 20·7 months (17·9-23·4; HR 1·55 [1·16-2·05]; p=0·0027) for those treated with intensive chemotherapy versus hypomethylating agents. In patients with myeloproliferative chronic myelomonocytic leukaemia (myeloproliferative CMML), median overall survival was 12·6 months (10·7-15·0) versus 17·6 months (14·8-21·5; HR 1·38 [1·12-1·70]; p=0·0027) for patients treated with hydroxyurea versus hypomethylating agents, and 12·3 months (8·4-16·6) versus 17·6 months (14·8-21·5; HR 1·44 [1·02-2·03]; p=0·040) for intensive chemotherapy versus hypomethylating agents. Hypomethylating agents did not confer an overall survival advantage for patients classified as having lower-risk disease (ie, myelodysplastic chronic myelomonocytic leukaemia with <10% blasts, CMML-0, or lower-risk CPSS). INTERPRETATION: These data suggest hypomethylating agents as the preferred therapy for patients with higher-risk chronic myelomonocytic leukaemia and those with myeloproliferative CMML. Our findings also suggest that CPSS is a valuable tool to identify patients who are most likely to benefit from hypomethylating agents. Further evidence from prospective cohorts would be desirable. FUNDING: The Austrian Group for Medical Tumor Therapy.