Post induction molecular MRD identifies patients with NPM1 AML who benefit from allogeneic transplant in first remission.
Jad OthmanNicola PotterAdam IveyJelena JovanovicManohursingh RunglallSylvie D FreemanAmanda Frances GilkesIan ThomasSean J JohnsonJoanna CanhamJames Durrell CavenaghPanagiotis KottaridisClaire ArnoldHans Beier OmmenUlrik Malthe OvergaardMike DennisAlan K BurnettCharlotte S Wilhelm-BenartziRichard DilonNigel H RussellPublished in: Blood (2024)
Selection of patients with NPM1 mutated AML for allogeneic transplant in 1st complete remission (CR1-allo) remains controversial due to a lack of robust data. Consequently, some centres consider baseline FLT3-ITD an indication for transplant and others rely on measurable residual disease (MRD) status. Using prospective data from the UK NCRI AML17 and AML19 studies, we examined the impact of CR1-allo according to peripheral blood NPM1 MRD status measured by RT-qPCR after 2 courses of induction chemotherapy. Of 737 patients achieving remission, MRD was positive in 19%. CR1-allo was performed in 46% of MRD+ and 17% of MRD- patients. We observed significant heterogeneity of overall survival (OS) benefit from CR1-allo according to MRD status, with substantial OS advantage for MRD+ patients (3y OS with CR1-allo 61% vs 24% without, HR 0.39, 95%CI 0.24-0.64, p<0.001) but no benefit for MRD- patients (3y OS 79% vs 82%, HR 0.82, 95%CI 0.50-1.33, p=0.4). Restricting analysis to patients with co-existing FLT3-ITD, again CR1-allo only improved OS for MRD+ patients (3y OS 45% vs 18%; compared to 83% vs 76% if MRD-); no interaction with FLT3 allelic ratio was observed. Post-induction molecular MRD reliably identifies those patients who benefit from allogeneic transplant in first remission. AML17 ISRCTN55675535 AML19 ISRCTN78449203.
Keyphrases
- acute myeloid leukemia
- end stage renal disease
- ejection fraction
- newly diagnosed
- chronic kidney disease
- stem cell transplantation
- prognostic factors
- peripheral blood
- peritoneal dialysis
- machine learning
- squamous cell carcinoma
- acute lymphoblastic leukemia
- genome wide
- big data
- low dose
- artificial intelligence
- locally advanced