Venetoclax (VEN) combined with azacitidine (AZA) or decitabine (DEC) has been approved for older adults with acute myeloid leukemia (AML) unfit for intensive chemotherapy based on the pivotal VIALE-A trial. However, this trial only compared AZA + VEN with AZA monotherapy. Therefore, we compared the outcomes of consecutive older adults (65 years or older) with newly diagnosed AML who received DEC (n = 230) or DEC + VEN (n = 74) after propensity score matching to construct a one-to-one matched cohort by the nearest neighbor algorithm. The median overall survival was longer in the DEC + VEN group than in the DEC group (13.4 months vs. 8.3 months, p = 0.01). The median event-free survivals were 8.6 and 5.8 months in the DEC + VEN and DEC groups, respectively (p = 0.02). The response rate (complete response, complete response with incomplete hematologic recovery, and morphologic leukemia-free state) was significantly higher in the DEC + VEN group than in the DEC group (70.3% vs. 24.3%, p < 0.01). The 30-day (2.7% vs. 9.5%, p = 0.17) and 60-day (9.5% vs. 18.9%, p = 0.16) mortality rates did not differ between the two groups, nor did the median hospitalization and transfusion rates (hospitalization: 23 days vs. 21 days, p = 0.20; red blood cells: 3.2 units/month vs. 3.5 units/month, p = 0.73; platelets: 2.7 units/month vs. 2.3 units/months, p = 0.48). Of those who received DEC + VEN and became leukemia-free, 29% underwent allogeneic stem cell transplantation and had excellent survival outcomes (one-year survival: 79.4%; one-year non-relapse mortality: 13.3%). This study is the first to provide real-world evidence that DEC + VEN has superior outcomes to DEC monotherapy.

The Philadelphia-negative myeloproliferative neoplasms (MPNs) are divided in three major groups: polycythemia vera (PV), essential thrombocythemia (ET), and primary myelofibrosis (PMF). The 2016 WHO classification incorporates also prefibrotic PMF (pre-PMF) and overt PMF. This study aimed to discriminate the clinical features, genetic alterations, and outcomes in patients with prefibrotic, overt PMF, and secondary MF (SMF). This study included 229 patients with diagnosed myelofibrosis (MF). Among 229 patients, 67 (29%), 122 (53%), and 40 (18%) were confirmed as SMF, overt PMF, and pre-PMF, respectively. The JAK2 V617F mutation was differentially distributed in SMF and PMF, contradictory to CALR and MPL mutations. Regarding nondriver mutations, the occurrence of ASXL1 mutations differed between PMF and SMF or pre-PMF. The three-year overall survival was 91.5%, 85.3%, and 94.8% in SMF, overt PMF, and pre-PMF groups. Various scoring systems could discriminate the overall survival in PMF but not in SMF and pre-PMF. Still, clinical features including anemia and thrombocytopenia were poor prognostic factors throughout the myelofibrosis, whereas mutations contributed differently. Molecular grouping by wild-type SF3B1 and SRSF2/RUNX1/U2AF1/ASXL1/TP53 mutations showed inferior progression-free survival (PFS) in PMF, SMF, and pre-PMF. We determined the clinical and genetic features related to poor prognosis in myelofibrosis.

Recently, the combination of VEN-HMA has been shown to achieve durable responses in patients with both newly diagnosed (ND) and R/R-AML. We retrospectively evaluated the post-allo-HCT outcomes of 50 patients who received VEN-HMA therapy. In total, 10 were ND and 40 were R/R and, at the time of HCT, the median age was 53 years. In the ND- and R/R-AML groups, the percentage of patients who achieved CR/CRi or MLFS was 90% and 92.5%, respectively. In all, after a median follow-up of 13.7 months, the probabilities of overall survival (OS), relapse-free survival (RFS), cumulative incidence of relapse (CIR), and nonrelapse mortality (NRM) at 1 year were 63.7%, 59.3%, 28.5%, and 12.2%, respectively. In addition, the cumulative incidences of grade II–IV acute graft-versus-host disease (GVHD) and moderate–severe chronic GVHD at 1 year were 28.4% and 37.4%, respectively. In multivariate analysis, the factors associated with a statistically significant impact on OS were VEN-HMA cycle (p = 0.021), ELN risk group (p = 0.041), and the response to VEN-HMA therapy before allo-HCT (p = 0.003). Although 80% of our patients had R/R-AML and 30% underwent a second allo-HCT, our data still suggest that allo-HCT following VEN-HMA therapy is a safe and effective treatment option.

Background/Objectives: Follicular lymphoma (FL) and marginal zone lymphoma (MZL) are low-grade B-cell lymphomas (LGBCLs) with indolent clinical courses but a lifelong risk of histologic transformation (HT) to aggressive lymphomas, particularly diffuse large B-cell lymphoma. Predicting HT can be challenging due to class imbalances and the inherent complexity of time-dependent events. While there are current prognostic indices for survival, they do not specifically address HT risk. This study aimed to develop and validate survival-based and traditional classification machine-learning models to predict HT in cohorts. Methods: Using a multicenter retrospective dataset (n = 1068), survival models (Cox proportional hazards, Lasso-Cox, Random Survival Forest, Gradient-boosted Cox [GBM-Cox], eXtreme Gradient Boosting [XGBoost]-Cox), and classification models (Logistic regression, Lasso logistic, Random Forest, Gradient Boosting, XGBoost) were compared. The best-performing survival models—XGBoost-Cox, Lasso-Cox, and GBM-Cox—were assessed on an independent test set (n = 92). Model sensitivity was maximized using optimal binary risk cutoff points based on Youden’s index. Results: Survival models showed superior predictive performance than classical classifiers, with XGBoost-Cox exhibiting the highest mean accuracy (85.3%), time-dependent area under the curve (0.795), sensitivity (98%), specificity (83.9%), and concordance index (0.836). Incorporating next-generation sequencing (NGS) data improved model accuracy and specificity, indicating that genetic factors improve HT prediction. Principal component analysis revealed distinct gene mutation patterns associated with HT risk, highlighting DNA-repair genes such as TP53, BLM, and RAD50. Conclusions: This study highlights the clinical value of survival-based machine-learning methods integrated with NGS data to personalize HT risk stratification for patients with FL and MZL.

We evaluated the prognostic efficiency of the European Leukemia Net (ELN) 2017 criteria on the post-transplant outcomes of 174 patients with intermediate (INT; n = 108, 62%) or adverse (ADV) risk (n = 66, 38%) of acute myeloid leukemia; these patients had received the first allogeneic hematopoietic stem-cell transplantation (HSCT) at remission. After a median follow-up period of 18 months, the 2 year OS, RFS, and CIR after HSCT were estimated to be 58.6% vs. 64.4% (p = 0.299), 50.5% vs. 53.7% (p = 0.533), and 26.9% vs. 36.9% (p = 0.060) in the INT and ADV risk groups, respectively. Compared to the ELN 2017 stratification, pre-HSCT WT1 levels (cutoff: 250 copies/10⁴ ABL) more effectively segregated the post-HSCT outcomes of INT risk patients compared to ADV risk patients regarding their 2 year OS (64.2% vs. 51.5%, p = 0.099), RFS (59.4% vs. 32.4%, p = 0.003), and CIR (18.9% vs. 60.0% p < 0.001). Indeed, high WT1 levels were more prominent in INT risk patients than in ADV risk patients. Notably, FLT3-ITD had the greatest impact on post-HSCT outcomes among all the ELN 2017 criteria components; patients in the FLT3-ITD mutant subgroups exhibited the worst outcomes regardless of their allelic ratios or NPM1 status compared to the pre-HSCT WT1 level of other INT and ADV risk patients.