Geno-Clinical Decision Model Accurately Predicts Diagnosis of Myelodysplastic Syndrome
Researchers sought to determine whether a machine learning-based model would be able to accurately predict the diagnoses of myeloid malignancies.
Researchers sought to determine whether a machine learning-based model would be able to accurately predict the diagnoses of myeloid malignancies.
Researchers sought to determine whether nonablative chemotherapy followed by HLA-mismatched allogeneic T-cell infusion would be safe and effective in older patients with AML or MDS.
Researchers sought to determine the role of PARP1 in the physiological and pathological effects in MDS and AML.
Patients received up to 8 cycles of AZA and up to 3 cycle of DLI with increasing T cell dosages.
Researchers sought to determine whether adding pevonedistat to azacitidine would improve outcomes for patients with higher-risk MDS, CMML, or AML.
Researchers sought to determine the effects of TERT rare variants in patients with myelodysplastic syndrome.
Researchers sought to determine whether detecting MRD with mutational analysis and FCM may aid in predicting disease progression following myeloablative allo-HSCT in patients with MDS.
Researchers sought to determine whether allo-HSCT would negate poorer outcomes in patients with MDS who have myelofibrosis.
Researchers sought to determine whether APVO436 would have a favorable safety profile in treating patients with relapsed/refractory AML or MDS.
Researchers sought to determine how the bone marrow microenvironment contributes to the etiology of myelodysplastic syndrome.