Abstract: Background: The invention of Next Generation Sequencing (NGS) has spurred research into human diseases, especially in the field of malignancy. In acute myeloid leukemia (AML), a plethora of novel alterations have been identified, including mutations in epigenetic regulator genes (e.g. IDH1, IDH2, DNMT3A), genes coding for proteins of the cohesin complex (e.g. SMC1A, SMC3, STAG2) and spliceosome genes (e.g. SF3B1, U2AF1). Although the diagnostic and prognostic implications of many of these alterations are not yet clear, there is increasing evidence that several of them might have major implications for understanding the disease biology or for patient-treatment. Thus, there is increasing need to reliably detect these mutations in large patient groups in clinically relevant time-frames and at an affordable cost. Due to the large number of genes to be screened, amplicon-based NGS represents an attractive detection method. Although, several assays have been reported, integrating different numbers of genes, it is currently unclear whether they really allow reliable detection of alterations in a reproducible way. Here we report our results from a round robin comparison of the detection of known AML-variants using a highly multiplexed, single tube assay coamplifying a total of 568 amplicons covering 54 entire genes or hot spot gene regions involved in leukemia (TruSight Myeloid sequencing panel; Illumina), with respect to the sensitivity, reproducibility and quantitative accuracy. Material and Methods: Ten European laboratories routinely involved in molecular AML diagnostics participated in this study. All groups performed two sequencing runs, each containing 8 samples. These samples were centrally aliquoted and distributed, the analyses were done in a blinded fashion. Six out of the 8 samples on each run were derived from a set of 9 samples composed of DNA isolated from the blasts of 18 different newly diagnosed AML patients mixed at a 1:1 ratio, with 50 ng of DNA being used for the library preparation. Three of these 9 samples were analyzed in replicate in separate runs by each group. The remaining two samples were a commercial test DNA containing 10 known single nucleotide variants (SNV) or insertion/deletion (InDel) alterations with defined variant allele frequencies (VAF) between 4 and 25% and DNA derived from the OCI-AML3 AML cell line (mutant for DNMT3A and NPM1). Sequencing was performed on MiSeq NGS systems (Illumina) using 2x151 bp-runs. Sequencing data were analyzed by all laboratories using the VariantStudio software (Illumina), with the threshold for mutation calling set at 3%. Results: Analysis of data quality indicated that 85% of the samples met the predefined acceptance criteria ( 〉 =95% amplicons with at least 500 reads/amplicon), the median coverage was 7379 reads/amplicon (range 0-47403 reads). Of the 9 mutations present in the positive control, 7 were called at least once in the two replicates by all labs, two mutations with a VAF of 5% were missed by 1 and 4 participants, respectively. Overall, the VAF calls for this sample showed a high level of accuracy across the participants (median coefficient of variation 5%, range 0-22.5%) as well as excellent intra- and inter-laboratory reproducibility (Fig.1). In total, the 9 primary leukemic samples contained 43 known variants in 19 genes, including all commonly mutated genes in AML, i.e. CEBPA, DNMT3A,RUNX1, NPM1, FLT3, WT1. For these samples, the sensitivity was 95.7%. Based on the entire data set (positive control and leukemic samples), the calculated sensitivity of the assay for known variants with an expected VAF 〉 =5% was 93.3%. The rate of non-calls was slightly higher for InDels (14/179; 7.8%) than for SNVs (25/407; 6.1%; P=.47). Two 57-bp long insertions in FLT3 exons 14/15 were not called, which is expected due to the specifications of the assay (max. detectable InDel length 〈 =25 bps). The standard deviation of VAF estimates for the primary leukemic samples was 1.7% with a mean CV of 0.094. Conclusions: This inter-laboratory comparison shows a high sensitivity and impressive quantitative accuracy of NGS-based characterization for known variants down to a minor VAF of 5%. Although additional optimization in individual parameters might be necessary, these initial results clearly indicate that rapid comprehensive molecular characterization of patient samples appears feasible, even in the clinical setting. Figure 1 Figure 1. Disclosures Thiede: AgenDix GmbH: Equity Ownership, Research Funding; Illumina: Research Support, Research Support Other. Bullinger:Illumina: Research Support Other. Hernández-Rivas:Illumina: Research Support Other. Heuser:Illumina: Research Support Other. Preudhomme:Illumina: Research Support Other. Lo Coco:Illumina: Research Support Other. Martinelli:Illumina: Research Support Other. Schuh:Illumina: Research Support Other. Enjuanes:Illumina: Research Support Other. Lea:Illumina: Research Support Other. Schlesinger:Illumina: Employment.

Abstract: Background: Recently, the oral multitargeted small molecule FLT3 inhibitor midostaurin (M) was approved for treatment of FLT3-mutated AML in combination with standard chemotherapy. In the international RATIFY (NCT00651261) trial, addition of M led to superior overall and event-free survival compared to placebo, thus defining a new standard of care in this AML subset (Stone RM et al. NEJM 2017). Although not powered for subgroup analyses, M showed consistent effects across all FLT3 mutation strata [tyrosine kinase domain (TKD); internal tandem duplication (ITD) with low (0.05-0.7; ITDlow) or high ( 〉 0.7; ITDhigh) allelic ratio] suggesting significant off-target activity beyond FLT3 inhibition. Aim: We aimed to comprehensively profile the mutational landscape of FLT3 mutated (FLT3mut) AML in a large, well characterized cohort of patients (pts) treated within the RATIFY trial using a high-throughput targeted sequencing (HTS) approach. Methods: HTS was performed on the entire coding region of 262 genes involved in hematologic malignancies including 20 genes that encode kinases targeted by M (M kinome, MK). Pretreatment peripheral blood (PB; 14%) or bone marrow (BM; 86%) specimens were available from 475 (66%) of 717 FLT3mut AML RATIFY pts. Libraries were prepared using SureSelectXT custom solutions (Agilent). Paired-end sequencing was carried out on a HiSeq platform (Illumina). FLT3 mutation (mut) status was available for all pts [TKD: 24%; ITD: 76% (ITDlow: 45%; ITDhigh:31%)], and cytogenetic data for 454 pts (96%). Results: An average sequencing depth of 978x was obtained for all pts. In sum, 1815 mut (missense: 49%; indels: 40%; nonsense: 7%; other: 3%) were identified with a mean of 3.8 mut per pt (FLT3 strata; TKD: 4; ITDlow: 4; ITDhigh: 3.6).Overall, recurrent mut ( 〉 5% of all pts) were found in NPM1 (61%), DNMT3A (39%), WT1 (21%), TET2 (12%), RUNX1 (11%), NRAS (11%), PTPN11 (9%), ASXL1 (8%), IDH1 (8%), IDH2 (7%; R140 only), and SMC1A (6%). In contrast, TP53 (1%) and biallelic CEPBA (1%) mut were rare events. This was also true for aberrations of the MK (7% in total) with KIT (2%), MAP3K11 (1%), and NTRK3 (1%) being most frequently mutated. When stratified according to FLT3mut type, mut in NRAS (24% vs 7%, p 〈 .0001), SMC1A (10% vs 4%, p=.02), and KIT (4% vs 1%, p=.02) occurred significantly more often in TKD than ITD groups, respectively, whereas WT1 (13% vs 24%, p=.018) was more frequently co-mutated in the ITD group. In general, pts in the TKD group had significantly more mut in genes encoding for cohesin (TKD: 29% vs ITD: 16%, p=.004) and signaling (TKD: 40% vs ITD: 24%, p=.001) proteins compared to ITD pts, who had significantly more mut in transcription genes (TKD: 37% vs ITD: 48%, p=.03). Based on the mut and cytogenetic data, we next sought to assign all FLT3mut pts to the 11 recently defined molecular AML classes (Papaemmanuil E et al. NEJM 2016). The majority fell into two classes, namely the NPM1 (N; 62%) and the chromatin-spliceosome (CS; 15%) classes, underscoring the significance of FLT3mut as the driver in these particular genomic classes. Other class-defining lesions were rare or absent in this cohort [inv(16): 2%; t(8;21): 2%; t(11q23;x): 2%; t(6;9): 1%, TP53-aneuploidy: 1%; CEBPAbiallelic: 1%; IDH2R172: 0%]. In 14% of all pts categorization was not possible (no or 〉 1 class-defining lesion), emphasizing the need for further refinement of this classification. When focusing on these two groups, N and CS had comparable FLT3mut patterns (TKD: 24% vs 21%; ITDlow: 44% vs 45%; ITDhigh: 32% vs 33%), whereas N more frequently correlated with a normal karyotype (N: 91% vs CS: 63%). With respect to clinical characteristics, no differences between N and CS in terms of age, white blood cells, platelets, PB and BM blasts, as well as history of MDS were observed. Conclusion: In this comprehensive sequencing approach, we could further delineate the molecular pattern of FLT3mut AML. Here, FLT3-ITD and -TKD groups exhibited remarkable differences in cooperating pathways, highlighting distinct biologic features in the leukemogenesis of FLT3mut AML. Overall, mut of MK genes were rare events, not fully explaining the complexity of M off-target effects. Understanding the underlying disease mechanism will potentially provide useful information on prognosis and prediction of response to M. Further analyses including correlation with clinical outcome are ongoing. Support: U10CA180821, U10CA180861, U10CA180882, U24CA196171 Disclosures Bullinger: Janssen: Speakers Bureau; Jazz Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Bristol-Myers Squibb: Speakers Bureau; Pfizer: Speakers Bureau; Sanofi: Research Funding, Speakers Bureau; Amgen: Honoraria, Speakers Bureau; Bayer Oncology: Research Funding. Gathmann:Novartis: Employment. Larson:Ariad/Takeda: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding; Novartis: Consultancy, Research Funding; BristolMyers Squibb: Consultancy, Research Funding. Medeiros:Genentech: Employment; Celgene: Consultancy, Research Funding. Tallman:ADC Therapeutics: Research Funding; AROG: Research Funding; BioSight: Other: Advisory board; Orsenix: Other: Advisory board; AbbVie: Research Funding; Daiichi-Sankyo: Other: Advisory board; Cellerant: Research Funding. Tiecke:Novartis: Employment. Pallaud:Novartis: Employment. Ehninger:Cellex Gesellschaft fuer Zellgewinnung mbH: Employment, Equity Ownership; GEMoaB Monoclonals GmbH: Employment, Equity Ownership; Bayer: Research Funding. Ganser:Novartis: Membership on an entity's Board of Directors or advisory committees. Stone:Otsuka: Consultancy; Jazz: Consultancy; Cornerstone: Consultancy; Fujifilm: Consultancy; Arog: Consultancy, Research Funding; Pfizer: Consultancy; Sumitomo: Consultancy; Novartis: Consultancy, Research Funding; Ono: Consultancy; Orsenix: Consultancy; Merck: Consultancy; Argenx: Other: Data and Safety Monitoring Board; AbbVie: Consultancy; Agios: Consultancy, Research Funding; Amgen: Consultancy; Astellas: Consultancy; Celgene: Consultancy, Other: Data and Safety Monitoring Board, Steering Committee. Thiede:AgenDix: Other: Ownership; Novartis: Honoraria, Research Funding. Döhner:AROG Pharmaceuticals: Research Funding; Celgene: Consultancy, Honoraria, Research Funding; AROG Pharmaceuticals: Research Funding; Pfizer: Research Funding; Bristol Myers Squibb: Research Funding; Novartis: Consultancy, Honoraria, Research Funding; Celator: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Astellas: Consultancy, Honoraria; Bristol Myers Squibb: Research Funding; Sunesis: Consultancy, Honoraria, Research Funding; Astellas: Consultancy, Honoraria; Novartis: Consultancy, Honoraria, Research Funding; Astex Pharmaceuticals: Consultancy, Honoraria; Astex Pharmaceuticals: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Jazz: Consultancy, Honoraria; Pfizer: Research Funding; Seattle Genetics: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria; Agios: Consultancy, Honoraria; Celator: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Agios: Consultancy, Honoraria; Seattle Genetics: Consultancy, Honoraria; Sunesis: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria; Jazz: Consultancy, Honoraria.

Abstract: Introduction: Internal tandem duplication of the FLT3 gene (FLT3-ITD), resulting in duplication of 3 to more than hundreds of nucleotides, are present in approximately 25% of adults with newly diagnosed AML. Several studies have shown that ITD mutations are associated with poor prognosis due to a high relapse rate, in particular in case of a high mutant to wild-type allele ratio and/or insertion site in the beta1-sheet of the tyrosine kinase domain-1 (beta1-sheet). Aims: To investigate the relationship between ITD insertion site and patient outcome, Roche 454 next generation sequencing (NGS) was performed in 452/555 (81.4%) FLT3-ITD positive patients (pts) enrolled into the RATIFY trial (NCT00651261). Results: NGS identified 908 ITDs with up to 9 ITDs per case (1 ITD: n=210, 46.5%; 2 ITDs: n=131, 29.0%; 3 ITDs: n=58, 12.8%; 4 ITDs: n=24, 5.3%; 5 ITDs: n=18, 4.0%; 6 ITDs: n=3, 0.7%; 7 ITDs: n=7, 1.5%; 9 ITDs: n=1, 0.2%). Median ITD-size was 45 nucleotides (range, 6-246); all ITDs were in-frame with direct head-to-tail orientation. According to the 4 functional groups, 488 ITDs (53.7%) were located within the juxtamembrane domain (JMD), 155 ITDs (17.1%) within the hinge region, 211 ITDs (23.2%) within the beta1-sheet, and 54 ITDs (5.9%) 3´of beta1-sheet. ITD size strongly correlated with insertion site, in that the more C-terminal the insertion site, the longer the size of the inserted fragment (P 〈 .001). In 242 pts (53.5%) featuring multiple ITD clones, 698 concurrent integration sites were delineated, with coexistent integration sites within JMD being the most frequent interaction (37%) followed by JMD and beta1-sheet (13.5%), and within beta1-sheet (7.8%). NPM1 mutations (NPM1mut) were present in 203/358 pts (56.7%). Correlation of ITD insertion site with NPM1mut revealed a significantly lower incidence of NPM1mut in pts with insertion located within the hinge region (50/106, 47.2% vs 153/252, 60.7%; P=.02) and 3´of beta1-sheet (14/41, 34.1% vs 189/317, 59.6%; P=.002), whereas NPM1mut were significantly more frequent in pts with insertions affecting JMD (143/235, 60.9% vs 60/123, 48.8%; P=.03). Clinical characteristics differing among the 4 functional ITD groups were gender and WBC. Pts with insertions 3´of beta1-sheet were predominantly male (28/46, 60.9% vs 178/406, 43.8%; P=.03); pts with JMD insertions exhibited lower WBC (median 36.5 vs 52.7 x109/L; P=.03). Complete remission (CR) was achieved within 60 days in 248/452 pts (54.9%). To evaluate the impact of ITD insertion site on response to induction, a logistic regression model was used. ITD insertion sites were categorized in (i) only in beta1-sheet, (ii) in beta1-sheet and other sites, and (iii) outside the beta1-sheet. Other variables were ITD mutant to wild-type allelic ratio (fragment analysis, cutoff at 0.5), number of ITDs per patient, log2 of WBC counts, age, NPM1mut, and midostaurin treatment. In this model, only number of ITDs predicted lower CR rate (OR, 0.72; 95% CI, 0.57-0.90), while NPM1mut was a favorable marker for CR (OR, 2.69; 95% CI, 1.70-4.28). Median follow-up for survival was 60.6 months (mo); median event free survival (EFS) and overall survival (OS) were 3.9 mo and 24.4 mo, respectively. The 4-year EFS and OS rates were 21.0% (95% CI, 17.2%-24.8%) and 42.6% (95% CI, 37.9%-47.4%), respectively. Survival analysis according to categorized insertion site groups showed that pts exhibiting insertion exclusively in the beta1-sheet had significantly inferior OS (P=.014) compared to the other two groups. Multivariate models for OS and EFS including hematopoietic stem-cell transplantation (HSCT) as a time-dependent covariate revealed WBC counts as unfavorable and NPM1mut as favorable for both endpoints; further unfavorable factors were older age and exclusive insertion in the beta1-sheet (HR, 1.49; 95% CI, 1.01-2.20) for OS and number of ITDs (HR, 1.15; 95% CI, 1.04-1.28) for EFS; HSCT was a favorable factor only for EFS (HR, 0.66; 95% CI, 0.44-0.99). Midostaurin treatment was associated with in trend improved EFS (HR, 0.81; 95% CI, 0.63-1.03) and OS (HR, 0.77; 95% CI, 0.57-1.02). Conclusions: In this large cohort of 452 FLT3-ITD mutated AML treated within the RATIFY trial the negative prognostic impact of beta1-sheet insertion site of FLT3-ITD could be confirmed. Further analyses to investigate potential predictive effects of midostaurin treatment are ongoing. Support: U10CA180821, U10CA180882, U24CA196171, (CCSRI) #704970. Disclosures Du: Novartis: Employment. Gathmann:Novartis: Employment. Larson:Ariad/Takeda: Consultancy, Research Funding; Novartis: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding; BristolMyers Squibb: Consultancy, Research Funding. Medeiros:Celgene: Consultancy, Research Funding; Genentech: Employment. Tallman:Orsenix: Other: Advisory board; Cellerant: Research Funding; AROG: Research Funding; AbbVie: Research Funding; BioSight: Other: Advisory board; Daiichi-Sankyo: Other: Advisory board; ADC Therapeutics: Research Funding. Tiecke:Novartis: Employment. Pallaud:Novartis: Employment. de Witte:Amgen: Consultancy, Research Funding; Novartis: Research Funding; Celgene: Honoraria, Research Funding. Niederwieser:Novartis: Research Funding; Miltenyi: Speakers Bureau. Ehninger:Bayer: Research Funding; GEMoaB Monoclonals GmbH: Employment, Equity Ownership; Cellex Gesellschaft fuer Zellgewinnung mbH: Employment, Equity Ownership. Ganser:Novartis: Membership on an entity's Board of Directors or advisory committees. Bullinger:Bristol-Myers Squibb: Speakers Bureau; Jazz Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Amgen: Honoraria, Speakers Bureau; Pfizer: Speakers Bureau; Bayer Oncology: Research Funding; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen: Speakers Bureau; Sanofi: Research Funding, Speakers Bureau. Döhner:Pfizer: Research Funding; Jazz: Consultancy, Honoraria; Novartis: Consultancy, Honoraria, Research Funding; Sunesis: Consultancy, Honoraria, Research Funding; AbbVie: Consultancy, Honoraria; Seattle Genetics: Consultancy, Honoraria; Celator: Consultancy, Honoraria; Seattle Genetics: Consultancy, Honoraria; Astex Pharmaceuticals: Consultancy, Honoraria; Sunesis: Consultancy, Honoraria, Research Funding; Jazz: Consultancy, Honoraria; AROG Pharmaceuticals: Research Funding; Astellas: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Astellas: Consultancy, Honoraria; Bristol Myers Squibb: Research Funding; AROG Pharmaceuticals: Research Funding; Agios: Consultancy, Honoraria; Celator: Consultancy, Honoraria; Astex Pharmaceuticals: Consultancy, Honoraria; Bristol Myers Squibb: Research Funding; Amgen: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Agios: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Novartis: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria; Pfizer: Research Funding. Thiede:Novartis: Honoraria, Research Funding; AgenDix: Other: Ownership.

Abstract: Introduction: Mutations localized in the tyrosine kinase domain activation loop of FLT3 (FLT3-TKD), representing point mutations in codon D835/I836 and rarely deletions of codon I836, induce constitutive tyrosine phosphorylation and activation of the receptor tyrosine kinase similarly to FLT3 internal tandem duplication (ITD) mutations. However, the prognostic role of FLT3-TKD in AML, particularly in the presence of NPM1 mutations, is not well established. The phase 3 RATIFY trial [NCT00651261; Stone et al. N Engl J Med. 2017] showed that in combination with standard chemotherapy, midostaurin (PKC412) improved survival outcomes across all 3 FLT3 stratification subgroups (ITD high allelic ratio [≥ 0.7] , ITD low allelic ratio [ 〈 0.7], and TKD) vs placebo in patients with newly diagnosed FLT3-mutated AML. Here, we evaluated the prognostic impact of FLT3-TKD and NPM1 mutations in a post hoc analysis from the RATIFY trial. Methods: In RATIFY, newly diagnosed patients with AML 18-60 years old were randomly assigned to receive midostaurin or placebo together with standard induction and consolidation therapy followed by 12 28-day cycles of maintenance therapy with midostaurin or placebo. FLT3-TKD mutation was detected by PCR and capillary electrophoresis at 9 reference laboratories. Patients were categorized as NPM1 mutated (mut) or NPM1 wild-type (WT) using PCR. Efficacy outcomes included complete remission (CR), overall survival (OS), event-free survival (EFS) and disease-free survival (DFS). EFS and DFS analyses were performed considering CR within a 60-day window. P values presented have not been adjusted for multiplicity. Results: Of the total randomized 162 FLT3-TKD patients, 134 with available NPM1 data had consented for exploratory analysis and thus were included in this study (see Table for subgroup distribution). Overall, 47.8% of patients were male, and the median age was 49 years (95% CI, 45.5-51.1 years). The median white blood cell (WBC) count was higher in patients with NPM1-mut than in patients with NPM1-WT (34.1 vs 15.5 × 109/L, P = .0011). CR rates (during the first 60 days) were higher in patients with FLT3-TKD/NPM1-mut vs FLT3-TKD/NPM1-WT (66% vs 53%); however, this was driven by the higher rate of CR in the midostaurin arm (76% NPM1-mut vs 44% NPM1-WT) rather than the placebo arm (53% NPM1-mut vs 60% NPM1-WT). The overall CR rate (regardless of NPM1 genotype) was 64% for midostaurin and 56% for placebo in FLT3-TKD patients. The prognostic effect of the NPM1 mutation concurrent with FLT3-TKD was seen for all endpoints consistently with hazard ratios (HRs) around 0.50 or lower (Figures 1 and 2 and Table). Overall (regardless of treatment) OS, EFS, and DFS estimates at 3 years were 73% vs 52%, 48% vs 25%, and 74% vs 47%, respectively, in patients with FLT3-TKD/NPM1-mut vs FLT3-TKD/NPM1-WT. Whereas the HRs for midostaurin vs placebo were 0.73 for both OS and EFS, the impact of treatment on outcomes varied between the individual NPM1/TKD subgroups and was not consistently observed when endpoints were censored at stem cell transplant (SCT) (Table). It should be noted that the number of patients in each subgroup was small and therefore the HRs with 95% CIs should be interpreted with caution. Multivariate analyses in these FLT3-TKD patients revealed that NPM1 genotype was an independent prognostic factor for OS, EFS and DFS (2-sided P 〈 .05), whereas study drug, age, sex, WBC at baseline and SCT (no/yes) did not reach this level of significance in the Cox model. Conclusions: This post hoc analysis of the FLT3-TKD patient subset in the RATIFY trial showed the high prognostic value of NPM1 mutational status. Whereas midostaurin showed an overall benefit in the FLT3-TKD patients for OS, EFS, CR and DFS, the impact of treatment on outcome varied between the individual NPM1 subgroups within these FLT3-TKD patients and was not consistently observed.Further analyses using additional endpoints and additional multivariate analyses are planned. Support: U10CA180821, U10CA180882, U10CA180820, U10CA180791, U10CA180888, U10CA180863, (CCSRI) #704970, U24CA196171; ClinicalTrials.gov Identifier: NCT00651261 Disclosures Voso: Celgene: Research Funding, Speakers Bureau. Larson:Ariad/Takeda: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding; Novartis: Consultancy, Research Funding; BristolMyers Squibb: Consultancy, Research Funding. Heuser:Janssen: Consultancy; Pfizer: Consultancy, Honoraria, Research Funding; Novartis: Consultancy, Honoraria, Research Funding; StemLine Therapeutics: Consultancy; Astellas: Research Funding; BergenBio: Research Funding; Karyopharm: Research Funding; Bayer Pharma AG: Consultancy, Research Funding; Tetralogic: Research Funding; Sunesis: Research Funding; Daiichi Sankyo: Research Funding. Wei:Novartis: Honoraria, Other: Advisory committee, Research Funding, Speakers Bureau; Pfizer: Honoraria, Other: Advisory committee; Amgen: Honoraria, Other: Advisory committee, Research Funding; Abbvie: Honoraria, Other: Advisory board, Research Funding, Speakers Bureau; Servier: Consultancy, Honoraria, Other: Advisory committee, Research Funding; Celgene: Honoraria, Other: Advisory committee, Research Funding. Brandwein:Lundbeck: Consultancy; Celgene: Consultancy; Pfizer: Consultancy; Novartis: Consultancy; Boehringer Ingelheim: Consultancy, Research Funding. de Witte:Novartis: Research Funding; Amgen: Consultancy, Research Funding; Celgene: Honoraria, Research Funding. Medeiros:Celgene: Consultancy, Research Funding; Genentech: Employment. Tallman:Cellerant: Research Funding; Orsenix: Other: Advisory board; BioSight: Other: Advisory board; ADC Therapeutics: Research Funding; AROG: Research Funding; AbbVie: Research Funding; Daiichi-Sankyo: Other: Advisory board. Schlenk:Pfizer: Research Funding, Speakers Bureau. Ganser:Novartis: Membership on an entity's Board of Directors or advisory committees. Cheng:Novartis: Employment. Gathmann:Novartis: Employment. Tiecke:Novartis: Employment. Thiede:AgenDix: Other: Ownership; Novartis: Honoraria, Research Funding. Döhner:AbbVie: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Seattle Genetics: Consultancy, Honoraria; Celator: Consultancy, Honoraria; Sunesis: Consultancy, Honoraria, Research Funding; Bristol Myers Squibb: Research Funding; Novartis: Consultancy, Honoraria, Research Funding; Seattle Genetics: Consultancy, Honoraria; AROG Pharmaceuticals: Research Funding; Sunesis: Consultancy, Honoraria, Research Funding; Astellas: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria; AROG Pharmaceuticals: Research Funding; Celator: Consultancy, Honoraria; Astex Pharmaceuticals: Consultancy, Honoraria; Bristol Myers Squibb: Research Funding; Agios: Consultancy, Honoraria; Agios: Consultancy, Honoraria; Astellas: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Astex Pharmaceuticals: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Jazz: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Jazz: Consultancy, Honoraria; Pfizer: Research Funding; Pfizer: Research Funding; Novartis: Consultancy, Honoraria, Research Funding. Stone:Otsuka: Consultancy; Argenx: Other: Data and Safety Monitoring Board; Amgen: Consultancy; Agios: Consultancy, Research Funding; Orsenix: Consultancy; Ono: Consultancy; Novartis: Consultancy, Research Funding; Astellas: Consultancy; Arog: Consultancy, Research Funding; Merck: Consultancy; Cornerstone: Consultancy; Fujifilm: Consultancy; Jazz: Consultancy; Celgene: Consultancy, Other: Data and Safety Monitoring Board, Steering Committee; Pfizer: Consultancy; Sumitomo: Consultancy; AbbVie: Consultancy.

Abstract: The results from the RATIFY trial (ClinicalTrials.gov: NCT00651261; CALGB 10603) showed that midostaurin combined with standard chemotherapy significantly improved outcomes in patients with FMS-like tyrosine kinase 3 (FLT3)–mutated acute myeloid leukemia (AML), compared with placebo. In this post hoc subgroup analysis from the trial, we evaluated the impact of midostaurin in 163 patients with FLT3-tyrosine kinase domain (TKD) mutations. At a median follow-up of 60.7 months (95% CI, 55.0-70.8), the 5-year event-free survival (EFS) rate was significantly higher in patients treated with midostaurin than in those treated with placebo (45.2% vs 30.1%; P = .044). A trend toward improved disease-free survival was also observed with midostaurin (67.3% vs 53.4%; P = .089), whereas overall survival (OS) was similar in the 2 groups. Patients with AML and NPM1mut/FLT3-TKDmut or core binding factor (CBF)–rearranged/FLT3-TKDmut genotypes had significantly prolonged OS with or without censoring at hematopoietic cell transplantation (HCT), compared with NPM1WT/CBF-negative AMLs. The multivariable model for OS and EFS adjusted for allogeneic HCT in first complete remission as a time-dependent covariable, revealed NPM1 mutations and CBF rearrangements as significant favorable factors. These data show that NPM1 mutations or CBF rearrangements identify favorable prognostic groups in patients with FLT3-TKD AMLs, independent of other factors, also in the context of midostaurin treatment.