Rowe, Jacob M.

Abstract Copy Number Alterations (CNAs), including chromosomal gains and losses, shape the genetics and clinical management of acute myeloid leukemia (AML), particularly in complex karyotypes (e.g. CK-AML). Traditionally, AML associated CNAs have been studied using cytogenetic approaches, i.e., karyotyping, that are limited in resolution and sensitivity. Here, low-coverage, sparse whole genome sequencing followed by machine learning applied to over 600 AML patient samples (ECOG-ARCIN trials: E1900, E3999) reveals novel genetic, biologic, and clinical correlates in AML disease. We find that multi-variate Cox-regression analysis applied to the data identifies select patients exhibiting focal and cryptic hemizygous deletions at 17q, 21q, and 3p, in otherwise diploid genomes, associate with inferior survival compared to other patients (median overall survival; OS = 65.5 compared to 421 days, Chi-square test pval=6x10-11), independent of factors such as age, treatment, and karyotype complexity status. In addition, we confirm that amplifications at 11q23, encoding the KM2TA gene, are associated with inferior outcome, and further identify unique breakpoint event features as well as transcriptional signatures suggestive of distinctive KM2TA-translocation independent biology. Applying machine learning approaches to the data, more specifically Non-negative Matrix Factorization (NMF), we develop a prognostic model that captures clinically adverse, cryptic variation such as focal 5q deletions, missed by conventional chromosome analysis and thereby, adds novel, complementary information to traditional, cytogenetic based risk-stratification (e.g. ELN). The model also associates gain of chromosome 8 in Intermediate risk patients with worse outcome compared to other Intermediate risk patients (median OS = 186 compared to 446 days, Chi-square test pval=0.005) and identifies a subgroup of patients within the adverse risk category that lack deletions on chromosomes 5, 7, and 17, and that fare better than the rest of the adverse risk patients (median OS = 188 compared to 97.5 days, Chi-square test pval=0.02), likely reflecting previously identified “atypical” CK-AML patients. Last, we develop a prognostic classifier based on a combination of Neural-Network and Random-Forest based learning, that predicts disease outcome with high accuracy and is based on a three genomic feature list on chromosome bands 5q31.2, 7q31.33, and 8q24, suggesting potential for clinical implementation. Altogether, our results show that low coverage, sparse whole genome sequencing combined with advanced learning methods can be applied clinically to support the diagnosis and clinical management of AML disease as well as serve as a powerful tool to further a basic understanding of the genetics and biology of CNAs in myeloid neoplasms and other cancers.

Abstract Background: The addition of the CD19/CD3 bispecific T-cell engager, blinatumomab, to standard consolidation chemotherapy in adults with ALL who achieved a measurable residual disease negative (MRDneg) remission (CR), demonstrated an improvement in 3-year overall survival (OS, 85% vs 68%, HR 0.41, P=0.002) and 3-year relapse-free survival (RFS, 80% vs 64%, HR 0.53) compared to conventional chemotherapy in the ECOG-ACRIN E1910 study (Litzow et al, NEJM 2024). Given the complex therapy in this study, treatment delays and modifications are expected. We herein explored the impact of such delays on patient outcomes. Methods: In the phase 3 ECOG-ACRIN E1910 trial (NCT02003222), adults aged 30-70 years with newly diagnosedALL who had achieved MRDneg CR following induction and intensification were randomized to consolidation chemotherapy with blinatumomab (blina arm) or chemotherapy alone (chemo arm). We examined the association between the timing of the initiation of maintenance therapy and OS and RFS. The expected duration of consolidation was 252 days vs 126 days for patients on the blina and chemo arms, respectively. For this analysis, participants were classified into two groups (no/short delay or long delay) depending on whether they started on time/before or after the median time between the beginning of consolidation and start of maintenance therapy for their treatment group (medians: 335 days, range, 181-457 days vs 176 days, range, 139-265 days for blina and chemo arms, respectively). Multivariate analyses of OS and RFS were performed to examine the effect of no/short delay vs. long delay in starting maintenance. Patients were stratified according to their assigned consolidation treatment arm, and the models were further adjusted for age, sex, white blood cell count, platelets, hemoglobin, peripheral blood blasts, bone marrow blasts, performance status and genetic-genomic risk at diagnosis. Results: Of the 488 patients enrolled, 224 MRDneg patients were randomized to consolidation chemotherapy with or without blinatumomab and 135 of the 224 went on to maintenance therapy on study (N= 66 on blina arm and 69 on chemo arm, respectively). The median follow-up from the time of maintenance registration was 43.4 months. There were no significant differences in baseline characteristics between patients in either arm who experienced no/short delay or long delay. In the blina group, 60 of 66 patients (90.9%) received all 8 cycles of consolidation therapy of which 31 (45.6%) had long delays. Sixty-eight of 69 patients on the chemo arm (98.5%) received all cycles of consolidation therapy, of which 34 (50%) had a long delay. Strikingly, patients who had a long delay before initiation of maintenance had a significant improvement in OS in multivariate analysis compared to patients who had no/short delay (HR 0.31, 95% CI: 0.11-0.91; P =0.03). However, within each treatment group, OS benefit did not reach statistical significance (blina arm: HR 0.04, 95% CI: 0.001-1.64; P =0.09; chemo arm: HR 0.32, 95% CI: 0.08-1.38; P =0.13). Similar results were observed for RFS in multivariate analysis (HR 0.40, 95% CI: 0.16-1.01; P =0.05), though this impact on improved RFS was noted in the chemo arm but not in blinatumomab treated patients (blina arm: HR 0.56, 95% CI: 0.10-3.24; P =0.52; chemo arm: HR 0.19, 95% CI: 0.04-0.83; P=0.03). Additionally, patients who had no/short delay before starting maintenance experienced a longer median duration of maintenance treatment (blina arm, 548 days; chemo arm, 708 days) compared to patients who had a long delay (blina arm 488 days; chemo arm 598 days) before initiation of maintenance (P=0.0008). Conclusion: In the phase 3 randomized ECOG-ACRIN E1910 clinical trial, long delays between initiation of consolidation therapy and start of maintenance therapy were associated with improved OS compared to no/short delays. However, within each treatment group (blina or chemo), no significant difference of OS was observed. We postulate that these longer delays allowed more patients to receive all of the recommended protocol-assigned therapy thereby resulting in improved survival. Furthermore, patients who had no/short delays had a significantly longer duration of maintenance therapy. These data indicate that treatment delays during consolidation do not worsen survival. Further studies are being done to better understand why patients with long delays had better overall survival.

Abstract Introduction Nadir bone marrow biopsies (BM Bx) are routinely performed around day 14 to assess early response to AML intensive induction therapy. The presence of residual disease prompts initiation of reinduction therapy, often with another cycle of intensive chemotherapy. Whether there are characteristics of nadir BM Bx that predict for response to intensive reinduction is unknown. To evaluate this, we analyzed data from ECOG-ACRIN clinical trials in AML of intensive induction chemotherapy with nadir biopsy information available to determine predictors of outcomes after reinduction. Methods We included patients from ECOG-ACRIN E1900 (Fernandez NEJM 2009) and arm A of E2906 (Foran ASH 2015) who received induction therapy with daunorubicin and cytarabine (7+3), had residual disease (blasts ≥5% or cellularity ≥20%) at nadir BM Bx and received reinduction chemotherapy. Nadir BM Bx characteristics that were evaluated included blast percentage and cellularity as well as both absolute and relative (percentage change, e.g. 20% to 10% = -50%) differences calculated between diagnosis and nadir for each parameter. Complete remission (CR) after reinduction therapy, disease free survival (DFS) and overall survival (OS) were outcomes for all analyses. Logistic regression models were used to evaluate associations with CR, and Cox proportional hazards models were used for DFS and OS. For models evaluating changes in blast percentage or cellularity as predictors, baseline blast percentage or cellularity was included as a covariate, respectively. Results Of 1013 patients identified, 750 (74%) had a nadir biopsy, 233 (23%) had evidence of residual disease, received reinduction therapy, and were included in the primary analysis. The median age was 58 and 42% were female. Cytogenetic risk category (by ELN2017) was adverse in 31%, intermediate in 66% and favorable in 3%. The median nadir BM Bx blast was 30% (range 0 to +97%) and cellularity was 20% (0 to +100%). The median absolute difference in blast percentage between baseline and nadir BM Bx was -15% (-95% to +66%) with a median relative difference of -36% (-100% to +400%). After reinduction, 118 patients (52%) achieved a CR. Neither absolute difference in blast percentage (OR 0.99, 95%CI 0.98-1.00, p=0.20) nor relative difference (OR 1.00, 95%CI 0.99-1.00, p=0.33) predicted CR. There was similarly no association with DFS (HR = 1.00, 95%CI: 0.99-1.01, p=0.65) or OS (HR = 1.00, 95%CI 0.99-1.01, p=0.76). Blast reduction ≥50% similarly did not predict these outcomes. We also evaluated the impact of any reduction in blast percentage (responders) from baseline to nadir and again found no association with CR (OR 1.65, 95%CI 0.90-3.03, p=0.11). Similarly, there was no association with DFS (HR 0.74, 95%CI 0.51-1.09, p=0.13) or OS (HR 0.81, 95%CI 0.58-1.13, p=0.21) in responders vs nonresponders. No association with CR, DFS or OS were identified when performing the same analysis in intermediate and adverse cytogenetic subgroups. We found no association with CR when nadir cellularity was assessed as a continuous variable (OR 0.99, 95%CI 0.98-1.00, p=0.10) or by relative difference (OR 0.99, 95%CI 0.99-1.00, p=0.10). There was a trend towards association with absolute reduction in cellularity from baseline to nadir and CR (OR 0.99, 95%CI 0.98-1.00, p=0.06). No association was identified between relative difference in cellularity and DFS and OS, nor was there an association among cytogenetic risk subgroups with any outcome. Discussion In intensively treated patients with residual disease at nadir BM Bx (i.e. day 14) who received intensive reinduction, the likelihood of achieving a CR was not influenced by the magnitude of disease reduction nor the extent of disease at the time of nadir biopsy. Similarly, there were no nadir biopsy features that predicted DFS or OS after intensive reinduction therapy. Given alternative reinduction therapies such as hypomethylating agents and venetoclax are available, these results suggest that the decision to attempt a second intensive induction cycle following the unequivocal presence of residual disease should not be influenced by characteristics of the nadir BM Bx. Although patient-specific factors such as patient fitness may favor a switch to less intensive options, these results support consideration of intensive reinduction therapy in patients with residual disease at nadir biopsy, even without changes in blasts or cellularity.

Introduction: Based on a donor versus no-donor analysis, UKALLXII/E2993 showed a survival benefit for adults with acute lymphoblastic leukemia (ALL) who underwent allogeneic hematopoietic cell transplantation (alloHCT) in first complete remission (CR1) compared to consolidation/maintenance chemotherapy alone. The follow-up phase 3 E1910 trial (NCT02003222) randomized BCR::ABL1-negative B-lineage ALL patients (pts) aged 30-70 years in measurable residual disease (MRD)-negative CR1 after intensification to conventional chemotherapy (CC) +/- blinatumomab (blin) and demonstrated significantly improved overall survival (OS) with blin (Litzow, NEJM 2024). The current exploratory subgroup analysis evaluates outcomes of MRD-negative pts randomized on E1910 who underwent alloHCT on trial. Methods: Among pts enrolled on E1910, pts in MRD-negative CR1 by 6-color flow cytometry after intensification who were randomized to CC +/- blin and subsequently underwent alloHCT were identified. We compared baseline characteristics, MRD status post induction, relapse-free survival (RFS) and OS using the Kaplan-Meier method and the two-sided log-rank test and Cox model. A multivariable analysis was performed with alloHCT included as a time-varying covariate as well as a landmark analysis comparing the outcome of pts with unfavorable risk on the CC + blin arm who underwent alloHCT versus those who did not. Results: Of 224 MRD-negative randomized pts, 44 underwent alloHCT on trial: 22 in each arm. The median time from randomization to transplant was 3.2 months (mos). The median follow-up from initial registration was 57.8 mos. Baseline demographics including age (median 55 years), gender (53% male), race (89% white) and ethnicity (89% non-Hispanic/Latino) were equally distributed. Compared to CC + blin, the median peripheral blood white cell (WBC) count and blast percentage at diagnosis were higher in the CC arm at 6,640 vs 3,740/uL and 55 vs 9%, respectively, while median marrow blast percentage and overall unfavorable risk as defined in E1910 (55% vs 64%) were similar. Of the 44 MRD-negative pts who proceeded to alloHCT on study, 77% in the CC arm and 64% in the CC+ blin arm were MRD-negative after induction. Myeloablative conditioning was given to the majority of pts (68% CC arm and 73% CC+blin arm) and the most common graft versus host disease prophylaxis was tacrolimus-based on both arms. Among the 44 pts who underwent alloHCT, the observed hazard ratio (HR) comparing relative risk of death between pts randomized to CC+blin or CC only was 0.59 (95% CI: 0.12-2.11) with a 3-year OS rate of 82% versus 71% and the HR comparing relative risk of relapse/death was 0.52 (CI: 0.15-1.79) with a 3-year RFS rate of 82% versus 67%. For patients with unfavorable risk, 3-year OS and 3-year RFS in each treatment arm were both 71% versus 65%. Among 50 pts with unfavorable risk in MRD-negative CR after intensification who were randomized to CC + blin, a landmark analysis performed at 5 mos post randomization showed 3-year OS and RFS rates of 71% versus 90% and 71% versus 86% between the 14 pts who underwent alloHCT and those who did not, respectively. Receipt of alloHCT was a time-varying covariate in a multivariable analysis with gender, WBC count, platelets, hemoglobin, peripheral blood blasts, bone marrow blasts, performance status, and combined molecular risk category. Age, CD20 status, rituximab use, and intention to receive alloHCT were used as stratification factors. In the entire cohort of MRD-negative pts who were randomized, there was a significant association between improved OS and the receipt of CC+blin vs CC alone (HR 0.46, 95% CI: 0.26 - 0.82; p=0.009), better performance status of 0-1 vs ≥2 and favorable vs unfavorable risk ALL. In contrast, the receipt of alloHCT had no significant effect on OS (HR 1.00, 95% CI: 0.49 - 2.01). Conclusions: Within the constraints of small numbers, this exploratory subgroup analysis demonstrates that in pts with newly diagnosed BCR::ABL1-negative B-ALL treated on E1910 who achieved MRD-negativity after intensification, alloHCT outcomes did not appear to be different with or without blin in consolidation. In a multivariate analysis of all MRD-negative pts, receipt of blin but not alloHCT was associated with improved OS. Further investigation is warranted to characterize the relative benefit of blinatumomab in pts receiving alloHCT in frontline consolidation.

Background There is limited prospective or comparative data evaluating the HRQoL impact of intensive chemotherapy (IC) in older adults (age ≥60 years) with AML. In the recent EA E2906 phase 3 study of '7&3' (daunorubicin & cytarabine) vs. clofarabine (CLO), a putative lower intensity therapy, we incorporated a prospective patient-reported outcomes (PRO) assessment of HRQoL and fatigue to understand treatment impact from the patients' (pts) perspective. Methods E2906 study design and results have been presented previously [n=727, med. age 68 years (range 60-86), randomized 1:1 to ‘standard’ ‘7&3‘ & high dose cytarabine (Arm A) vs. single agent CLO (Arm B), as remission induction (Step 1) and consolidation (Step 2), respectively]. There was no difference in composite complete remission (CCR, 50%) or 30-day mortality rates (8.5%), and in primary analysis CLO was inferior for Overall Survival. HRQoL was a key secondary protocol endpoint. PROs assessed HRQoL and leukemia-specific symptoms and concerns using Functional Assessment of Cancer Therapy-Leukemia scale (FACT-Leu), & Fatigue using FACT-Fatigue subscale. PROs were administered at prespecified time points: (1) Baseline; (2) Cycle 1 at nadir (approx. Day 15); (3) End of Step 1 restaging (approx. D 40); (4) Beginning of Step 2 (1 st consolidation, approx. D 45); and (5) 2 nd cycle consolidation/End Step 2 (approx. D 60). The FACT-Leu Trial Outcome Index ( TOI) was calculated by summing physical well-being, functional well-being, and leukemia-specific concerns subscales to create a single composite score. Higher TOI scores correspond to better HRQoL. The primary endpoint was to evaluate TOI difference from randomization to day 30 after induction therapy between arms, evaluated using Wilcoxon rank sum test. We also compared Clinically Meaningful differences (CMiD) in TOI (defined as patient change ≥½ standard deviation from baseline TOI) between arms, using the X2 test. Pts not completing at least 2 assessment forms (including baseline) were excluded. Testing of constructs of Physical Well-being (PWB), Functional, Leukemia & Fatigue scales demonstrated high Cronbach's a values (a >0.7) except for PWB (a=0.672) at a single time point (End of Step 2). Results Baseline TOI was available for n=489, and 364 pts (n=182 each Arm) were evaluable in this planned analysis. Evaluating CMiD during Cycle 1 induction, pts in Arm B were less likely to experience ‘Worse’ TOI score (32% vs. 40.7%, Arm A), more likely to maintain stable TOI scores (49.1% vs. 39%, Arm A), and had a similar proportion of ‘Better’ TOI scores (20.3%, A vs. 18.9%, B) although differences were not significant (p=0.1389). Conversely in cycle 1 consolidation, more patients in Arm A experienced Better TOI (45.1% vs. 29.2%, Arm B), fewer had stable TOI (45.1% vs. 58.3%, Arm B), and rates of ‘Worse’ TOI were similar (9.8%, A vs 12.5%, Arm B), again differences were not significant (p=0.2616). There was no difference in Fatigue scores between Arms (p=0.49). We evaluated whether TOI and Fatigue scores could predict the ability to complete protocol therapy. In univariate analysis baseline TOI (p=0.0059) and Fatigue (p=0.0057) were associated with Step 1 completion, however on multivariate analysis (adjusting for age, sex, and Arm) were no longer significant [TOI, Odds Ratio (OR) 1.03 (0.98-1.08, p=0.27); Fatigue, OR 1.03 (0.96-1.11, p=0.42)]. There was a borderline association of TOI with Step 2 completion [TOI OR 1.10 (1.00-1.23, p=0.06)]. Using a multivariable linear mixed effects model, we observed similar and significant changes in TOI scores in both Arms, demonstrating the effect of IC & CLO on HRQoL (Figure). Comparing to baseline, TOI scores decreased significantly at C1 induction nadir (-4.0873, p<0.0001), and increased by 5.0762 (p=0.0004) at end Step 1, by 6.9047 at cycle 1 consolidation (p<0.0001), and by 11.4601 (p<0.0001) at end Step 2. Differences were mainly apparent in those who achieved CCR, and there was significant attrition in PRO responses in non-CCR pts. Conclusions Older adults experienced significant improvement in HRQoL after nadir regardless of therapy, and those achieving CCR report significantly higher scores. We did not observe differences in leukemia specific HRQoL or fatigue between treatment Arms (7&3 vs. CLO). Patient-reported HRQoL & Fatigue was not predictive of completion of protocol therapy. These results serve as a benchmark for expectations with IC in older adults.

AbstractBackgroundObesity (body mass index [BMI] ≥30 kg/m2) is an important epidemiological risk factor for developing acute myeloid leukemia (AML). Therefore, the authors studied the association of obesity with clinical and genetic phenotype and its impact on outcome in adults with AML.MethodsThe authors analyzed BMI in 1088 adults who were receiving intensive remission induction and consolidation therapy in two prospective, randomized therapeutic clinical trials of the Eastern Cooperative Oncology Group‐American College of Radiology Imaging Network: E1900 (ClinicalTrials.gov identifier NCT00049517; patients younger than 60 years) and E3999 (ClinicalTrials.gov identifier NCT00046930; patients aged 60 years or older).ResultsObesity was prevalent at diagnosis (33%) and, compared with nonobesity, was associated with intermediate‐risk cytogenetics group (p = .008), poorer performance status (p = .01), and a trend toward older age (p = .06). Obesity was not associated with somatic mutations among a selected 18‐gene panel that was tested in a subset of younger patients. Obesity was not associated with clinical outcome (including complete remission, early death, or overall survival), and the authors did not identify any patient subgroup that had inferior outcomes based on BMI. Obese patients were significantly more likely to receive <90% of the intended daunorubicin dose despite protocol specification, particularly in the E1900 high‐dose (90 mg/m2) daunorubicin arm (p = .002); however, this did not correlate with inferior overall survival on multivariate analysis (hazard ratio, 1.39; 95% confidence interval, 0.90–2.13; p = .14).ConclusionsObesity is associated with unique clinical and disease‐related phenotypic features in AML and may influence physician treatment decisions regarding daunorubicin dosing. However, the current study demonstrates that obesity is not a factor in survival, and strict adherence to body surface area‐based dosing is not necessary because dose adjustments do not affect outcomes.

Abstract Introduction: Allogeneic stem cell transplantation (alloSCT) is the most effective post remission anti-leukemia strategy. However, the associated toxicity is a barrier for its routine adoption as standard of care in older adults. Studies of AML patients who underwent alloSCT are mainly retrospective as randomized controlled trials comparing transplantation to non-transplantation are very difficult to conduct. We herein present prospective data from a randomized controlled phase III study, E2906, designed to compare two intensive chemotherapy arms. Patients who achieved remission and had a donor were to proceed to alloSCT after induction or first consolidation, at investigator discretion. Non-transplanted patients received 2 cycles of consolidation and then underwent a second randomization between observation and decitabine maintenance. Herein are reported all patients who received alloSCT either on protocol during first remission (CR1) or at other post induction time-points. Patients and Methods: Enrolled to E2906 study were 727 AML patients age 60 years and over. AlloSCT was performed in 166 patients, of whom 71 received alloSCT as part of the study and 95 received alloSCT off protocol. 105 patients (66/71 on protocol, 39/95 off protocol) received alloSCT at CR1/CRi1/LFS1 (CR: 92, CRi: 9 LFS: 4). Patients were followed for a median of 33.6 months from diagnosis and 29.1 months from transplant. No patients received decitabine maintenance prior to alloSCT. Overall survival (OS) is defined as the time from allo transplant to death from any cause, with follow-up censored at the date of last contact. Disease free survival (DFS) is defined as the time from alloSCT transplant to relapse or death of any cause. The censored follow-up time for patients without relapse or death information is the date of last contact. Kaplan-Meier estimates were used to estimate OS and DFS. DFS and OS were compared between subgroups using log rank tests. A cumulative incidence analysis, with death without prior relapse as competing events, was performed to evaluate the subgroup effect on time to relapse after transplant. Results: Patient characteristics of those who received alloSCT at CR1/CRi1/LFS1 are similar to the general distribution of AML patients eligible for intensive chemotherapy. Median age was 66 years, 52% were male and 88% with ECOG PS of 0-1. Cytogenetic data were available for 85 patients of whom 26% presented with unfavorable cytogenetics. Minimal residual disease (MRD) status prior to alloSCT was available for 44 patients of whom 19 (43%) achieved a MRD negative state. Long-term OS and DFS rates for all 105 patients who underwent alloSCT at CR1/CRi1/LFS1 are encouraging (Figure 1). OS and DFS at two years were 56.4% and 53.6% and 49.4%, 45.6% and 42.9%, 39% at 3 and 4 years, respectively. Age above or below 65 years, gender, induction regimen (3+7 or clofarabine) and MRD status prior to transplantation had no impact on outcome. Survival curves by intermediate or adverse cytogenetic risk are not significantly different. The numbers of patients with CRi1 or LFS1 are too small to compare with patients in CR1. Nevertheless, 36/38 patients that were alive and remain in first remission at the time of data cutoff, are patients who achieved CR1 and only 2/38 are patients transplanted at CRi1 or LFS1. Notably, the non-relapse mortality (NRM) was not significantly different for patients less or over 65 years. NRM at 6 months and 2 years for patients over and under 65 years of age were 4.4%, 8.4% and 15.6%, 24.0% respectively. Relapse during the first year post alloSCT is the main barrier for longer survival, particularly in patients with adverse cytogenetics and MRD positivity prior to transplantation (Figure 2). Conclusions: Fit older patients, including those over age 65, who undergo an alloSCT in CR1, can expect a 4-year survival of 43% with an acceptable NRM rate. The NRM was, surprisingly, not higher than for a typically younger cohort of AML. Relapse within one year after transplant is the major limitation to prolonged survival and this finding reflects the biology of the leukemia in these patients. In this patient population, novel post remission strategies should either be complimentary to alloSCT or competitive with updated outcome of alloSCT. Figure 1 Figure 1. Disclosures Ofran: Medison Israel: Consultancy; Janssen: Consultancy; Pfizer: Consultancy; Astellas: Consultancy; AbbVie: Consultancy. Claxton: Astellas: Other: Clinical Trial; Novartis: Research Funding; Astex: Research Funding; Cyclacel: Research Funding; Daiichi Sankyo: Research Funding; Incyte: Research Funding. Tallman: Syros: Membership on an entity's Board of Directors or advisory committees; Kura: Membership on an entity's Board of Directors or advisory committees; NYU Grand Rounds: Honoraria; Innate Pharma: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees; Biosight: Membership on an entity's Board of Directors or advisory committees; Roche: Membership on an entity's Board of Directors or advisory committees; Jazz Pharma: Membership on an entity's Board of Directors or advisory committees; Oncolyze: Membership on an entity's Board of Directors or advisory committees; KAHR: Membership on an entity's Board of Directors or advisory committees; Orsenix: Membership on an entity's Board of Directors or advisory committees; Daiichi-Sankyo: Membership on an entity's Board of Directors or advisory committees; Abbvie: Membership on an entity's Board of Directors or advisory committees; Amgen: Research Funding; Rafael Pharmaceuticals: Research Funding; Glycomimetics: Research Funding; Biosight: Research Funding; Orsenix: Research Funding; Abbvie: Research Funding; Mayo Clinic: Honoraria; UC DAVIS: Honoraria; Northwell Grand Rounds: Honoraria; NYU Grand Rounds: Honoraria; Danbury Hospital Tumor Board: Honoraria; Acute Leukemia Forum: Honoraria; Miami Leukemia Symposium: Honoraria; New Orleans Cancer Symposium: Honoraria; ASH: Honoraria; NCCN: Honoraria. Melnick: Constellation: Consultancy; Epizyme: Consultancy; Daiichi Sankyo: Research Funding; Sanofi: Research Funding; Janssen Pharmaceuticals: Research Funding; KDAC Pharma: Membership on an entity's Board of Directors or advisory committees. Levine: Prelude: Membership on an entity's Board of Directors or advisory committees; Ajax: Membership on an entity's Board of Directors or advisory committees; Zentalis: Membership on an entity's Board of Directors or advisory committees; Mission Bio: Membership on an entity's Board of Directors or advisory committees; QIAGEN: Membership on an entity's Board of Directors or advisory committees; Gilead: Honoraria; Lilly: Honoraria; Morphosys: Consultancy; Janssen: Consultancy; Incyte: Consultancy; Astellas: Consultancy; Imago: Membership on an entity's Board of Directors or advisory committees; Auron: Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria; Celgene: Research Funding; Roche: Honoraria, Research Funding; C4 Therapeutics: Membership on an entity's Board of Directors or advisory committees; Isoplexis: Membership on an entity's Board of Directors or advisory committees. Lazarus: Bristol Myer Squibb: Membership on an entity's Board of Directors or advisory committees. Luger: Syros: Honoraria; Agios: Honoraria; Daiichi Sankyo: Honoraria; Jazz Pharmaceuticals: Honoraria; Brystol Myers Squibb: Honoraria; Acceleron: Honoraria; Astellas: Honoraria; Pfizer: Honoraria; Onconova: Research Funding; Celgene: Research Funding; Biosight: Research Funding; Hoffman LaRoche: Research Funding; Kura: Research Funding. Foran: gamida: Honoraria; aptose: Research Funding; syros: Honoraria; boehringer ingelheim: Research Funding; kura: Research Funding; takeda: Research Funding; abbvie: Research Funding; trillium: Research Funding; revolution medicine: Honoraria; certara: Honoraria; actinium: Research Funding; OncLive: Honoraria; pfizer: Honoraria; servier: Honoraria; bms: Honoraria; novartis: Honoraria; taiho: Honoraria; sanofi aventis: Honoraria; h3bioscience: Research Funding; aprea: Research Funding; sellas: Research Funding; stemline: Research Funding. Litzow: Jazz: Other: Advisory Board; AbbVie: Research Funding; Omeros: Other: Advisory Board; Amgen: Research Funding; Actinium: Research Funding; Astellas: Research Funding; Pluristem: Research Funding; Biosight: Other: Data monitoring committee.

Abstract Introduction Several studies reported that AML patients who remain in long-term remission after allogeneic transplant (allo-HCT) or autologous transplant (auto-HCT) have a shorter life expectancy, compared to the general population. However, little is known about the life expectancy of adult long-term survivors of AML who were treated with chemotherapy without HCT and, there have been no comparisons with survival among the general population. The current study reports on the life expectancy of AML patients who survived 3 years in complete remission (CR) after treatment without HCT, and compared this to the gender- and age-matched normal population. At 3 years in CR, the incidence of recurrence is exceedingly low (3%; Watts JM, Leuk Res 2014) minimizing the impact of relapse on the long-term survival. Methods Between 1984 and 2008, 3,012 patients, aged 15 years and older, with untreated AML entered 9 consecutive, phase II and III, ECOG-ACRIN trials (E3483, PC486, E3489, E1490, E3993, E4995, E3997, E3999, E1900). Patients in CR and relapse-free at 3 years are included in the analysis . Minimal cytogenetic information was available in the early protocols (E1490, E3483, PC486). A Kaplan-Meier plot was generated for the three groups, allo, auto and no HCT, censoring for patients alive at last contact. Univariate and multivariate cox proportional hazard regression models were generated, considering death as an event. For comparison of long-term outcomes, patients were grouped together by age and matched to a normative population mortality rate. Subjects were also grouped by gender and treatment allowing for separate analysis of these groups with the no HCT group as the main group of interest. The normative population comparator of expected deaths was derived using mortality rates from United State CDC life table data. The median year was derived by calculating the person-years for each calendar year that patients were followed. To calculate the expected deaths for each age group, person-years was calculated by tabulating the years lived in each age group for all subjects. Each year of follow-up for AML patient was counted as one person year, and the tabulated bin corresponded with their age at the time. Person-years was then multiplied by the matching mortality rate. Chi-square statistics were derived using expected and observed deaths and then summed for each gender and treatment. The final comparison was of mortality rates since diagnosis in the 3-year alive and relapse-free AML patient population vs the normative population. To produce plots of mortality from diagnosis, person-years was tabulated for every year since diagnosis by treatment. The person-years were tabulated into 2-year bins. The US life tables from the CDC were used to generate a population mortality rate from diagnosis. Results A total of 503 adult AML patients in 3 year CR with a mean age of 42.9 years (15-79) were identified; 78 underwent allo, 110 auto and 315 did not undergo transplantation. The patients in the groups differed in age (p&lt;.001) and cytogenetics (p=.01). The multivariate model showed equivalent hazards of death to the 3 groups. Observed deaths and person-years were given by age group, gender, and treatment group and each were matched to a mortality rate from the United State CDC life table data that matched the median year of each treatment group. A chi square test for each group compared the derived expected to observed deaths. In every treatment group, patients had a shorter survival compared to their age- and gender- matched general population (p-value of 0.004 for the auto-HCT and &lt;0.001 for both allo-HSCT and no transplant groups). Table 1, selected only for the no HCT group, demonstrates the mortality rates by age and gender. Figure 1 indicates that AML patients who have survived relapse-free for at least 3 years continue to have higher mortality rates compared to the normative population for up to 14 years. This finding is not altered even if the very small number of patients who die from late relapse (&gt;3 years from diagnosis) are removed from the analysis (data not shown) Conclusions Patients with AML who remain in CR at 3 years, do not have a normal life expectancy, even if they do not undergo HCT. The shorter life expectancy observed following an HCT may, at least in part, be related to the prior intensive therapy or other predisposing factors (e.g. CHIP) of the leukemia, rather than the transplant procedure itself. Figure 1 Figure 1. Disclosures Luger: Syros: Honoraria; Agios: Honoraria; Daiichi Sankyo: Honoraria; Jazz Pharmaceuticals: Honoraria; Brystol Myers Squibb: Honoraria; Acceleron: Honoraria; Astellas: Honoraria; Pfizer: Honoraria; Onconova: Research Funding; Celgene: Research Funding; Biosight: Research Funding; Hoffman LaRoche: Research Funding; Kura: Research Funding. Lazarus: Bristol Myer Squibb: Membership on an entity's Board of Directors or advisory committees. Douer: Amgen: Consultancy, Speakers Bureau; Servier: Consultancy, Speakers Bureau; Adaptive: Current holder of individual stocks in a privately-held company, Current holder of stock options in a privately-held company, Speakers Bureau; Jazz: Consultancy. Tallman: Syros: Membership on an entity's Board of Directors or advisory committees; Kura: Membership on an entity's Board of Directors or advisory committees; Innate Pharma: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees; Biosight: Membership on an entity's Board of Directors or advisory committees; Roche: Membership on an entity's Board of Directors or advisory committees; Jazz Pharma: Membership on an entity's Board of Directors or advisory committees; Oncolyze: Membership on an entity's Board of Directors or advisory committees; KAHR: Membership on an entity's Board of Directors or advisory committees; Orsenix: Membership on an entity's Board of Directors or advisory committees; Daiichi-Sankyo: Membership on an entity's Board of Directors or advisory committees; Abbvie: Membership on an entity's Board of Directors or advisory committees; Amgen: Research Funding; Rafael Pharmaceuticals: Research Funding; Glycomimetics: Research Funding; Biosight: Research Funding; Orsenix: Research Funding; Abbvie: Research Funding; NYU Grand Rounds: Honoraria; Mayo Clinic: Honoraria; UC DAVIS: Honoraria; Northwell Grand Rounds: Honoraria; NYU Grand Rounds: Honoraria; Danbury Hospital Tumor Board: Honoraria; Acute Leukemia Forum: Honoraria; Miami Leukemia Symposium: Honoraria; New Orleans Cancer Symposium: Honoraria; ASH: Honoraria; NCCN: Honoraria. Litzow: Pluristem: Research Funding; Biosight: Other: Data monitoring committee; AbbVie: Research Funding; Actinium: Research Funding; Astellas: Research Funding; Omeros: Other: Advisory Board; Jazz: Other: Advisory Board; Amgen: Research Funding.