Peripheral blood haploidentical hematopoietic cell transplantation for patients aged 70 years and over with acute myeloid leukemia or high-risk myelodysplastic syndrome.
Samia HarbiLouison Brac de la PerriereBenjamin BouchacourtSylvain GarciazThomas PagliardiniBoris CalmelsMaud CecileAnne-Charlotte LeflochYosr HicheriMarie-Anne HospitalSabine FürstClaude LemarieCécile BraticevicFaezeh LegrandElena BekrievaPierre Jean WeillerChristian ChabanonNorbert VeyDidier BlaiseRaynier DevillierPublished in: Bone marrow transplantation (2023)
Haploidentical stem cell transplantation (Haplo-SCT) using non-myeloablative conditioning regimen (NMAC) has extended the feasibility of allogeneic transplantation, notably in older patients. However, there is few data specifically focusing on patients aged 70 years and over with AML and MDS. Thus the benefit of transplantation in this population is still debated. Here we report our single center experience of peripheral blood Haplo-SCT with NMAC and post-transplantation cyclophosphamide in AML and MDS patients aged 70 years and over. We analyzed 50 patients (27 AML, 23 MDS) with a median age of 72 years (70-77), 12/50 (24%) with active disease at Haplo-SCT. Cumulative incidence of grade 3-4 acute and moderate or severe chronic GVHD were 6% and 25%, respectively. Non-relapse mortality (NRM) at day +100 was 0%. NRM, relapse, PFS and OS at 3 years were 16%, 18%, 66%, and 69%, respectively. Among patients who were disease free at 2 years post Haplo-SCT, 88% are living without immunosuppressive treatment. Peripheral blood Haplo-SCT is feasible in selected AML/MDS patients over 70 years, without any early NRM. It produces long-term disease control and survival. Thus, age by itself should not be considered as a formal barrier to Haplo-SCT.
Keyphrases
- stem cell transplantation
- acute myeloid leukemia
- peripheral blood
- end stage renal disease
- ejection fraction
- chronic kidney disease
- newly diagnosed
- prognostic factors
- allogeneic hematopoietic stem cell transplantation
- stem cells
- risk factors
- machine learning
- intensive care unit
- cell therapy
- cardiovascular events
- artificial intelligence
- big data
- drug induced