Validation of the Revised 2022 European LeukemiaNet Risk Stratification in Adult Patients with Acute Myeloid Leukemia.

In 2022, the European LeukemiaNet (ELN) risk stratification for patients with AML has been updated. We aimed to validate the prognostic value of the 2022 ELN classification (ELN22) evaluating 1,570 newly diagnosed AML patients (median age, 56 years) treated with cytarabine-based intensive chemotherapy regimens. As compared to the 2017 ELN classification (ELN17), allocating 595 (38%), 413 (26%) and 562 (36%) patients to the favorable, intermediate and adverse risk category, ELN22 risk was favorable, intermediate, and adverse in 575 (37%), 410 (26%), and 585 (37%) patients, respectively.

Synthetic Data Generation in Hematology - Paving the Way for OMOP and FHIR Integration.

This study advances the utility of synthetic study data in hematology, particularly for Acute Myeloid Leukemia (AML), by facilitating its integration into healthcare systems and research platforms through standardization into the Observational Medical Outcomes Partnership (OMOP) and Fast Healthcare Interoperability Resources (FHIR) formats. In our previous work, we addressed the need for high-quality patient data and used CTAB-GAN+ and Normalizing Flow (NFlow) to synthesize data from 1606 patients across four multicenter AML clinical trials. We published the generated synthetic cohorts, that accurately replicate the distributions of key demographic, laboratory, molecular, and cytogenetic variables, alongside patient outcomes, demonstrating high fidelity and usability.

How to customize common data models for rare diseases: an OMOP-based implementation and lessons learned.

Background: Given the geographical sparsity of Rare Diseases (RDs), assembling a cohort is often a challenging task. Common data models (CDM) can harmonize disparate sources of data that can be the basis of decision support systems and artificial intelligence-based studies, leading to new insights in the field. This work is sought to support the design of large-scale multi-center studies for rare diseases.

Optimization of Starch-Tannin Adhesives for Solid Wood Gluing.

Bio-based solutions for solid timber gluing have always been a very sensitive topic in wood technology. In this work, we optimize the gluing conditions of a starch-tannin formulation, which allows high performance in dry conditions and resistance to water dipping for 3 h, allowing for the D2 classification to be reached according to EN 204. It was observed that the starch-tannin formulations enhanced their performance by increasing the heating temperature, achieving satisfactory results at 140 °C for 13 min.