Real-World Effectiveness of First-Line Azacitidine or Decitabine with or without Venetoclax in AML Patients Unfit for Intensive Therapy

Real-World Effectiveness of First-Line Azacitidine or Decitabine with or without Venetoclax in AML Patients Unfit for Intensive Therapy | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Real-World Effectiveness of First-Line Azacitidine or Decitabine with or without Venetoclax in AML Patients Unfit for Intensive Therapy Fabian Acker, Jörg Chromik, Emily Tiedjen, Sebastian Wolf, Jonas B. Vischedyk, and 10 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3945651/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Standard frontline treatment in patients with acute myeloid leukemia (AML) unfit for intensive therapy is the combination of a hypomethylating agent (HMA) with venetoclax (VEN). However, retrospective data confirming the benefits of this regimen outside of clinical trials are sparse and have shown conflicting results. Thus, we performed a multicenter retrospective analysis of outcomes with HMA-VEN compared to HMA alone in patients with newly diagnosed AML unfit for intensive treatment. A total of 213 patients were identified from 3 German tertiary care centers. Of those, 125 were treated with HMA-VEN and 88 with HMA alone. Median overall survival (OS) in the HMA-VEN cohort was 7.9 months (95% confidence interval [CI], 5.1–14.7) compared to 4.9 months (3.1–7.1) with HMA alone. After 1 year, 42% (95% CI, 33–54) and 19% (12–30) of patients were alive, respectively. The hazard ratio (HR) for death was 0.64 (95% CI, 0.46–0.88; p = 0.006). After adjusting for age, NCCN cytogenetic risk, NPM1, RUNX1, and TP53 status, ECOG performance status, baseline leukocytes, and type of HMA, treatment with HMA-VEN remained significantly associated with a prolonged survival (HR, 0.48; 95% CI, 0.29–0.77). Accordingly, time to next treatment (TTNT) was longer with HMA-VEN with a HR of 0.63 (95% CI, 0.47–0.85). Patients who achieved recovery of peripheral blood counts had a favorable prognosis (HR for death, 0.52; 95% CI, 0.33–0.84). These data align with findings from the pivotal VIALE-A trial and support the use of HMA-VEN in patients unfit for intensive therapy. AML Azacitidine Decitabine Hypomethylating Agent Venetoclax Real-World Data Figures Figure 1 Figure 2 Figure 3 Introduction Intensive chemotherapy and allogeneic stem cell transplantation are the most effective treatment strategies for patients with acute myeloid leukemia (AML) 1,2 . However, with a median age of 71 years at disease onset 3 , a relevant proportion of patients with AML is not eligible for intensive treatment due to comorbidities or reduced general condition. The current standard of care in the elderly or frail patient population is the combination of a hypomethylating agent (HMA), either azacitidine (AZA) or decitabine (DEC), with the oral BCL2 inhibitor venetoclax (VEN) based on the results of the VIALE-A study 2,4 . In this randomized phase III trial, patients with newly diagnosed AML who were considered unfit for intensive treatment received either AZA-VEN or AZA plus placebo. The median overall survival (OS) was 14.7 months (95% confidence interval [CI], 11.9–18.7) in the experimental arm compared to 9.6 months (7.4–12.7) in the control arm with a hazard ratio (HR) for death of 0.66 (95% CI, 0.52–0.85) favoring AZA-VEN combination treatment. In a pooled analysis of VIALE-A and a phase Ib study of AZA-VEN, the superior outcomes with the combination treatment were consistently found across all European Leukemia Network (ELN) 2017 risk groups with HRs for death of 0.45 (95% CI, 0.24–0.83), 0.62 (0.35–1.08), and 0.59 (0.44–0.79) in favorable, intermediate, and adverse risk disease, respectively 5 . However, there are only limited real-world analyses on the effectiveness of HMA-VEN compared with HMA monotherapy 6–9 . Interestingly, most of these retrospective studies failed to confirm an OS benefit in the real-world scenario, albeit sample sizes were generally small. Given these conflicting data, we performed this complimentary study in a larger patient cohort to provide further external validation of the VIALE-A results 10 . Methods Study design We conducted a multicenter retrospective cohort study in patients with newly diagnosed AML who were considered unfit for intensive therapy to evaluate the real-world effectiveness of HMA-VEN in comparison to the historical standard of HMA monotherapy. This study was approved by the ethics committee at University Hospital Frankfurt (UCT-51-2022) and the institutional review boards of the participating centers (University Hospitals Homburg and Marburg). Data were collected retrospectively from electronic health records, pseudonymized and merged for central analysis. The reporting adheres to Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines 11 . Patient selection Patients with diagnosis of AML according to the 2016 WHO classification 12 were considered eligible if they received a first-line therapy with azacitidine or decitabine either alone (HMA cohort) or combined with venetoclax using any dosing schedule (HMA-VEN cohort) in one of the participating centers. Prior cytoreductive therapy with leukapheresis, low-dose cytarabine, hydroxyurea or anthracycline monotherapy did not preclude inclusion. Venetoclax received marketing authorization by the European Medicines Agency (EMA) in the given indication in April 2021. However, negotiations with health insurances in Germany for reimbursement were not completed until December 2021. Thus, there were several patients who started treatment with HMA monotherapy before December 2021 and subsequently received venetoclax during the course of therapy after the respective health insurance agreed to cost coverage on a per-case basis. These patients were excluded from the analysis if they received more than 3 cycles of HMA monotherapy in order to avoid potential survivorship bias favoring the HMA-VEN cohort. Statistical analysis Baseline characteristics were summarized using descriptive statistics. Efficacy endpoints included OS and time to next treatment (TTNT) which were evaluated using Kaplan-Meier estimates. OS was defined as time from treatment start to death by any cause. In patients receiving allogeneic hematopoietic stem cell transplantation (HSCT), OS was censored at the date of HSCT, unless specified otherwise. Time to next treatment (TTNT) was defined as the time from treatment start to the first day of the first subsequent systemic treatment, regardless of remission status, or death. Unstratified log-rank tests were used for comparisons between the treatment cohorts. Hazard ratios (HR) and their corresponding 95% CI were derived from univariable, unstratified Cox proportional hazards (PH) models. Follow-up is reported as median and range of Kaplan-Meier estimated potential follow-up 13 . Response data were collected according to ELN 2022 criteria 2 . Confidence intervals were calculated using the Clopper-Pearson method. All centers stated that response assessments involving bone marrow aspirations were not routinely performed during most of the analyzed time period, given the palliative treatment setting. In order to reduce the risk of sampling bias, we decided to restrict all analyses of treatment response to patients with at least one evaluable response assessment during the first three months of treatment. Patients not fulfilling this criterion were considered unevaluable for response. Thus, response data in this study should be interpreted qualitatively and with caution. Accordingly, we decided to not report progression-free survival or duration of response in this study. To evaluate potential influencers of survival, univariable Cox PH models were fitted with each of a set of clinical and molecular baseline characteristics, selected by expert opinion and literature review. These variables included sex (male vs. female), age (above vs. below median), ECOG performance status (PS), disease origin (primary vs. secondary AML), National Comprehensive Cancer Network (NCCN) cytogenetic risk group version 2.2016 (dichotomized into poor vs. non-poor, Suppl. Table 1), mutational status of NPM1, RUNX1, TP53, ASXL1 and IDH1/IDH2 (either one or both), FLT3 ITD (present vs. absent) as well as baseline leukocytes (≥ 50/nl vs. <50/nl) and bone marrow blasts (≥ 50% vs. <50%). Finally, a multivariable Cox regression was performed using treatment and the factors previously identified as potential confounders (defined as P value ≤ 0.3 in the univariable analyses). No imputation on missing data was performed. Patients with missing values were excluded entirely from the respective analysis. Statistical tests were two-sided with significance level set at α = 0.05. All analyses were done using R version 4.2.3. Results Patients A total of 213 patients matching the eligibility criteria were identified between 2013 and 2022. Thereof, 125 patients were treated with HMA-VEN and 88 with HMA monotherapy. Six patients had been excluded due to switch from HMA to HMA-VEN after having received more than 3 cycles of monotherapy, as described in the Methods section. Patients in the HMA group were diagnosed earlier (interquartile range [IQR], January 2016 – November 2018) than patients who received HMA-VEN (December 2020 – April 2022). Only 3 patients (3.4%) still started HMA monotherapy after VEN received marketing authorization in April 2021. Baseline characteristics were generally well balanced between groups (Table 1 ). Median age in the HMA-VEN and HMA cohorts were 76 (range, 37–91) and 74 years (54–94), respectively. There were no significant differences in the assignment to NCCN 2.2016 or ELN 2017 risk groups between cohorts. However, patients in the HMA-VEN cohort were in slightly better general condition with 56% having an ECOG PS ≤ 1 compared to 41% in the monotherapy group. Additionally, more patients in the combination group had de novo instead of secondary AML (64% vs. 47%). Table 1 – Baseline Characteristics Characteristic HMA-VEN (N = 125) HMA (N = 88) Sex – No. (%) Female 46 (37) 37 (42) Male 79 (63) 51 (58) Age – yr Median (Range) 76 (37–91) 74 (54–94) ECOG PS – No. (%) 0–1 70 (56) 36 (41) 2–3 44 (35) 48 (55) 4 2 ( 2 ) 0 (0) Missing 9 ( 7 ) 4 ( 5 ) Etiology – No. (%) De novo 80 (64) 41 (47) After MDS 24 (19) 28 (32) After MPN 6 ( 5 ) 8 ( 9 ) After MDS/MPN 5 ( 4 ) 2 ( 2 ) Therapy-related 10 ( 8 ) 9 ( 10 ) Missing 0 (0) 0 (0) ELN 2017 Risk – No. (%) Favorable 14 ( 11 ) 11 ( 12 ) Intermediate 34 (27) 27 (31) Adverse 75 (60) 48 (55) Missing 2 ( 2 ) 2 ( 2 ) NCCN Cytogenetic Risk – No. (%) Favorable 2 ( 2 ) 2 ( 2 ) Intermediate 87 (70) 54 (61) Poor 33 (26) 29 (33) Missing 3 ( 2 ) 3 ( 3 ) NPM1 Mutation – No. (%) Yes 22 (18) 10 ( 11 ) No 94 (75) 71 (81) Missing 9 ( 7 ) 7 ( 8 ) CEBPA Mutation* – No. (%) Yes 1 ( 1 ) 1 ( 1 ) No 111 (89) 77 (88) Missing 13 ( 10 ) 10 ( 11 ) RUNX1 Mutation – No. (%) Yes 26 (21) 4 ( 5 ) No 91 (73) 61 (69) Missing 8 ( 6 ) 23 (26) FLT3 TKD – No. (%) Yes 6 ( 5 ) 0 (0) No 72 (58) 41 (47) Missing 47 (38) 47 (53) FLT3 ITD – No. (%) Yes 19 ( 15 ) 4 ( 5 ) No 67 (54) 41 (47) Missing 39 (31) 43 (49) TP53 Mutation – No. (%) Yes 22 (18) 15 ( 17 ) No 97 (78) 58 (66) Missing 6 ( 5 ) 15 ( 17 ) ASXL1 Mutation – No. (%) Yes 28 (22) 11 ( 12 ) No 92 (74) 53 (60) Missing 5 ( 4 ) 24 (27) IDH1 Mutation – No. (%) Yes 13 ( 10 ) 4 ( 5 ) No 68 (54) 32 (36) Missing 44 (35) 52 (59) IDH2 Mutation – No. (%) Yes 8 ( 6 ) 6 ( 7 ) No 73 (58) 32 (36) Missing 44 (35) 50 (57) Bone marrow Blasts – % Median (Range) 47 (11–95) 34 (20–90) Missing – No. (%) 6 ( 5 ) 10 ( 11 ) Peripheral Blasts – % Median (Range) 19.0 (0.0–91.0) 6.5 (0.0–81.0) White Blood Count (/nl) Median (Range) 7.0 (0.6–437.0) 4.1 (0.4–239.0) Prior Treatments – No. (%) / Missing (%) HMA 5 ( 4 ) / 8 ( 6 ) 5 ( 6 ) / 1 ( 1 ) Hydroxyurea 4 ( 3 ) / 4 ( 3 ) 2 ( 2 ) / 0 (0) HSCT§ 2 ( 2 ) / 0 (0) 2 ( 2 ) / 0 (0) Baseline refers to the status prior to initiation of the respective treatments. (*) CEBPA mutations include both in-frame bZIP mutations and any biallelic mutations, due to changes in classification. (§) HSCT for prior MDS or MPN. HMA denotes hypomethylating agent, VEN venetoclax, ECOG PS Eastern Cooperative Oncology Group Performance Status, MDS myelodysplastic syndrome, MPN myeloproliferative neoplasm, ELN European Leukemia Network, NCCN National Comprehensive Cancer Network, NPM1 nucleophosmin 1, CEBPA CCAAT/enhancer-binding protein-α, RUNX1 Runt-related transcription factor 1, FLT3 fms like tyrosine kinase 3, TKD tyrosine kinase domain, ITD internal tandem duplications, TP53 tumor protein p53, ASXL1 putative polycomb group protein ASXL1, IDH1/2 isocitrate dehydrogenase 1/2, and HSCT hematopoietic stem cell transplantation. In the HMA-VEN cohort, 122 (98%) and 3 (2%) patients received AZA and DEC, respectively, compared to 58 (66%) and 30 (34%) in the HMA cohort. Survival outcomes With a median time of follow-up of 12.8 months in the HMA-VEN cohort (range, 0.4–61.7) and 26.6 months in the HMA cohort (0.2–67.2), OS was significantly longer in patients receiving HMA-VEN (Fig. 1 A). Median OS in the HMA-VEN and HMA cohorts was 7.9 months (range, 5.1–14.7) and 4.9 months (3.1–7.1), respectively, with 42% (95% CI, 33–54) and 19% (12–30) of patients being alive after 1 year of treatment. The HR for death was 0.64 (95% CI, 0.46–0.88; p = 0.006). Favorable OS in the HMA-VEN cohort compared to the HMA cohort was consistently found across most subgroups defined by baseline patient or tumor characteristics, including age, NPM1 and TP53 status, and NCCN and ELN 2017 risk groups (Suppl. Figure 1). Median OS in the HMA-VEN and HMA cohorts was 20.2 (95% CI, 20.2-not calculable [NC]) and 7.6 months (1.4-NC), respectively, in patients with ELN 2017 favorable risk disease compared to 9.5 (6.2-NC) and 4.9 months (2.8–11.0) with intermediate and 7.0 (4.2–12.0) and 4.6 months (2.6–7.1) with adverse risk AML (Suppl. Figure 2). Surprisingly, in patients with ASXL1-mutant AML, OS was numerically shorter with HMA-VEN compared to HMA monotherapy (Suppl. Figure 3A). Multiple regression including an interaction analysis suggests a differential impact of ASXL1 status depending on the treatment received (P value for interaction, 0.04; Suppl. Figure 3B). However, numbers are too low to draw conclusions. TTNT was significantly longer in the HMA-VEN cohort, with a median of 5.3 months (95% CI, 4.2–7.4) compared to 3.4 months (2.5–4.9) in the HMA cohort (Fig. 1 B). HR for treatment switch or death was 0.63 (95% CI, 0.47–0.85; p = 0.002) favoring the combination cohort. Treatment response Of the 125 patients in the HMA-VEN cohort and 88 patients in the HMA cohort, 49 (39%) and 29 (33%) patients, respectively, were evaluable for response. More patients in the combination group achieved composite complete remission (cCR) as best response, which was defined as either CR or CR with incomplete (CRi) or partial (CRh) hematological recovery (Table 2 ). In the HMA-VEN group, 28 of 49 (57%; 95% CI, 42–71) evaluable patients had cCR compared to 4 of 29 (14%, 4–32) in the HMA group. In contrast, 9 of 49 (31%, 9–32) and 13 of 29 (45%, 26–64) evaluable patients had no response, respectively. Table 2 – Best Response Best response according to European Leukemia Network 2022 criteria stratified by treatment. Patients without response assessment during the first three months of treatment were considered non-evaluable. (*) percentages in the response categories are calculated as the number of patients in the respective category divided by the number of evaluable patients in the treatment cohort. HMA denotes hypomethylating agent, VEN venetoclax, CR complete remission, CRi complete remission with incomplete recovery, CRh complete remission with partial recovery, MLFS morphologic leukemia-free state, and PR partial remission. Response HMA-VEN (N = 125) HMA (N = 88) Non-Evaluable – No. (%) 76 (61) 59 (67) Evaluable* – No. (%) 49 (39) 29 (33) cCR 28 (57) 4 ( 14 ) CR 17 (35) 3 ( 10 ) CRi 10 (20) 1 ( 3 ) CRh 1 ( 2 ) 0 () MLFS 8 ( 16 ) 4 ( 14 ) PR 4 ( 8 ) 8 (28) No Response 9 (18) 13 (45) Supplementary Data In patients treated with HMA-VEN, achievement of cCR was associated with favorable OS with a HR for death of 0.25 (95% CI, 0.10–0.59; Fig. 2 A). Median OS in HMA-VEN patients with cCR was 24.3 months (95% CI, 11.7-NC) compared to 5.0 (3.5-NC) in patients without cCR. Since a large proportion of patients in a palliative treatment setting do not undergo response assessments outside of clinical trials, we evaluated whether the recovery of peripheral blood counts was also prognostic for OS. In the HMA-VEN cohort, 58 of 125 patients (46%) achieved blood count recovery, defined as neutrophils ≥ 1/nl and platelets ≥ 100/nl, and 67 (54%) did not. Patients with recovery exhibited a longer OS with a HR for death of 0.52 (95% CI 0.33–0.84; Fig. 2 B). Median OS was 16.4 months (95% CI, 8.1–22.5) and 3.8 months (3.2–9.5), respectively. Subsequent treatments In the HMA-VEN and HMA cohorts, 27 of 125 (22%) and 31 of 88 (35%) of patients received at least one subsequent treatment for AML with the majority being low intensity regimens (Suppl. Table 2). Only 3 patients (3%) in the HMA cohort received venetoclax as part of any subsequent therapy. Intensive treatment was given in 1 (1%) and 10 (11%) patients in the HMA-VEN and HMA cohorts, respectively. HSCT was performed in 14 (11%) and 8 (9%) patients. Without censoring for HSCT, OS continued to favor the HMA-VEN cohort with a HR for death of 0.71 (95% CI, 0.52–0.98; Suppl. Figure 4A). Post-transplantation survival is shown in Suppl. Figure 4B. Multiple regression In the univariable regression models, treatment group, NCCN poor cytogenetic risk (HR 1.99; 95% CI, 1.40–2.83), ECOG PS ≥ 2 (2.67; 1.89–3.77) and presence of a TP53 mutation (1.94; 1.27–2.97) were associated with shorter OS (Fig. 3 ). Based on the criteria defined above, treatment, age, NCCN risk group, ECOG PS, leukocytes as well as NPM1, RUNX1, and TP53 status were included into the multiple regression model. In addition, we decided to also include the choice of HMA because of large imbalances between the cohorts. In the multivariable analysis, treatment with HMA-VEN remained significantly associated with a prolonged OS with a HR for death of 0.48 (95% CI, 0.29–0.77; p = 0.003; Fig. 3 ). While patients with higher age or assignment to the NCCN poor risk group showed a tendency towards shorter OS, only TP53 mutations (HR, 1.82; 95% CI, 1.01–3.30) and ECOG PS ≥ 2 (2.78; 1.77–4.37) were significantly coupled with poorer survival in the multivariable regression model. The use of DEC was associated with numerically improved OS compared to AZA. A second analysis using the ELN 2017 risk stratification instead of the NCCN 2.2016 classification of cytogenetic risk, showed similar results. The HR for death was 0.51 (95% CI, 0.34–0.78) for treatment with HMA-VEN compared to HMA alone. Moreover, favorable and intermediate ELN 2017 risk were associated with improved OS compared to adverse risk with HRs of 0.46 (95% CI, 0.24–0.85) and 0.59 (0.39–0.88), respectively (Suppl. Figure 5). Discussion To our knowledge, this is the so far largest retrospective study comparing the outcomes of HMA-VEN combination and HMA monotherapy in patients with AML who are unfit for intensive chemotherapy. We demonstrated an OS benefit for the combination treatment in a real-world setting which remained significant after adjusting for prognostic baseline variables. Nevertheless, survival times were generally shorter in comparison to the VIALE-A trial 4 . Since the captured baseline characteristics appear similar to those reported in the trial, the reasons for this discrepancy remain unclear but may in part be attributable to comorbidities or the survivorship bias associated with the screening phase in the context of a clinical study. Despite the limitations in interpreting response data in our study, response rates appeared higher in patients treated with HMA-VEN compared to HMA. In our study, baseline characteristics were generally balanced between cohorts. However, 34% patients in the monotherapy cohort received DEC compared to only 2% with HMA-VEN. While VEN is approved in combination with both AZA and DEC by FDA and EMA, this is most likely because AZA was the HMA used in the VIALE-A trial 4 . Consequently, we included the choice of HMA as variable in the multiple regression model and found no significant impact on OS between AZA and DEC. Given the low number of patients receiving DEC-VEN in our study, an interaction analysis was not performed. Kwag et al. 8 recently showed that outcomes with DEC-VEN vs. DEC monotherapy are comparable with those seen with AZA-VEN vs. AZA: in 148 patients receiving either DEC-VEN or DEC, OS was superior in the combination group with a HR of 0.60 (95% CI, 0.40–0.91) after propensity score matching. Notably, 26% and 5% of patients in the DEC-VEN and DEC arms, respectively, continued to HSCT. While it is unclear, whether this reflects different treatment intentions or simply the superior response rates using DEC-VEN, OS remained significantly improved when censoring for HSCT with a HR of 0.62 (0.40–0.97) 8 . In our study, patients with ASXL1-mutant AML had shorter OS with HMA-VEN compared to HMA alone. Given that preclinical and clinical data in AML and MDS suggest improved response rates with the addition of VEN in ASXL1-mutant disease 14–17 , our results appear implausible. Confirmation from independent cohorts will be required for robust hypotheses generation as findings from subgroup analyses may be subject to alpha error inflation. Our study has several other limitations. First, we were not able to adjust for comorbidities which represent important confounders, especially in the context of elderly and frail patients. Second, as high response rates have been reported for HMA-VEN, physicians may be increasingly inclined to treat borderline frail patients with HMA-VEN with HSCT consolidation in mind. This may have introduced unmeasurable imbalances. However, HSCT rates were comparable between cohorts. Third, our study compared patients from different time periods. Different supportive measures may have influenced survival. Four, we did not provide information on comorbidities, toxicity and quality of life, because these parameters could not be reliably derived from electronic health records. In conclusion, our data support the findings of VIALE-A that the addition of VEN to HMA improves OS in patients unfit for intensive treatment, despite most retrospective studies so far have failed to demonstrate a survival benefit for HMA-VEN vs. HMA 6–9 . Declarations No funding was received for conducting this study. Contribution: F.A. and J.C. conceptualized and designed the study; F.A., J.S., and J.B. acquired clinical data; F.A. performed statistical analyses and wrote the initial draft of the manuscript; F.A., J.C., E.T., S.W., J.V., P.M., J.E., K.K., M.S., B.S., T.O., H.S., A.N., J.S., and J.B. contributed to data interpretation, critically reviewed the manuscript, and approved the final version. Conflict-of-interest disclosure: F.A. received support for attending meetings and speaker’s honoraria from AstraZeneca, and consultant fees from IQVIA. P.M. received research grants from the Else Kröner Fresenius Stiftung. A.N. received institutional grants by the Carreras Leukemia foundation (AH05-01). T.O. received research funding from Gilead and Merck KGaA (both not related to this work). T.O. is consultant for Roche, Merck KGaA, Janssen, Genmab, Abbvie, Kronos Bio, Beigene (all not related to this work). T.O. received honoraria from Roche, Merck KGaA, Janssen, Genmab, Abbvie, Kronos Bio, Beigene. The remaining authors declare no competing financial interests. Correspondence: Dr. Fabian Acker; University Hospital Frankfurt, Department of Hematology and Oncology, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany; e‑mail: [email protected] . Upon reasonable request addressed to the corresponding author, data shown in this work, including individual patient data after de-identification, will be shared to investigators who provide a methodologically sound proposal. References Kantarjian H, Kadia T, DiNardo C et al (2021) Acute myeloid leukemia: current progress and future directions. Blood Cancer J 11(2):1–25. 10.1038/s41408-021-00425-3 Döhner H, Wei AH, Appelbaum FR et al (2022) Diagnosis and management of AML in adults: 2022 recommendations from an international expert panel on behalf of the ELN. 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Am J Hematol 97(6):E214–E216. 10.1002/ajh.26539 Aldoss I, Yang D, Pillai R et al (2019) Association of leukemia genetics with response to venetoclax and hypomethylating agents in relapsed/refractory acute myeloid leukemia. Am J Hematol 94(10):E253–E255. 10.1002/ajh.25567 Garcia JS, Wolach O, Vachhani P et al (2021) Comparative Effectiveness of Venetoclax Combinations Vs Other Therapies Among Patients with Newly Diagnosed Acute Myeloid Leukemia: Results from the AML Real World Evidence (ARC) Initiative. Blood 138(Supplement 1):2328. 10.1182/blood-2021-151285 Rahmani NE, Ramachandra N, Sahu S et al (2021) ASXL1 mutations are associated with distinct epigenomic alterations that lead to sensitivity to venetoclax and azacytidine. Blood Cancer J 11(9):1–8. 10.1038/s41408-021-00541-0 Additional Declarations Competing interest reported. F.A. received support for attending meetings and speaker’s honoraria from AstraZeneca, and consultant fees from IQVIA. P.M. received research grants from the Else Kröner Fresenius Stiftung. A.N. received institutional grants by the Carreras Leukemia foundation (AH05-01). T.O. received research funding from Gilead and Merck KGaA (both not related to this work). T.O. is consultant for Roche, Merck KGaA, Janssen, Genmab, Abbvie, Kronos Bio, Beigene (all not related to this work). T.O. received honoraria from Roche, Merck KGaA, Janssen, Genmab, Abbvie, Kronos Bio, Beigene. The remaining authors declare no competing financial interests. Supplementary Files supplementaldata.pdf Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3945651","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":273877883,"identity":"9b11d03c-e3ef-422e-b8fa-7b42f86170d0","order_by":0,"name":"Fabian Acker","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABFElEQVRIie2PMUvEMBTHXxF6S+ytlyX9Ci8UTvw2LUJvdBMFwYZC+xVOPPwMTp0cchy0S90DESwcODnopnAcxoodjl51dMgP3pCX/N7/BcBi+Ze4ps5NSVMhsLbz2t7IIaXulOCr48wBcFhxsm7mH5RxXkbri9uCeZJMmwbwdHyTRenh/Qa8KulVJnW84g+FDqgkRxgCHs8fy2VKnhFovSdGjTIqCh3dmZRJtN0gqFm+JhIBVdhr+GqUf4iFvmoVk4K+mom0VZ6aXgWVWzoi0SH+KKji5bei+vfidXxCk1Lz65V71ipcxZFYyIDQun8xVpX8LbnUvlelBX03ClMxT14kY1615/sdBztn8st7i8VisQzwCVSgY2SbKbZXAAAAAElFTkSuQmCC","orcid":"","institution":"Goethe University Frankfurt, University Hospital, Department of Medicine II, Hematology and Oncology","correspondingAuthor":true,"prefix":"","firstName":"Fabian","middleName":"","lastName":"Acker","suffix":""},{"id":273877884,"identity":"47068bed-2a46-4a28-bf3f-39b36bdc2ec3","order_by":1,"name":"Jörg Chromik","email":"","orcid":"","institution":"Goethe University Frankfurt, University Hospital, Department of Medicine II, Hematology and Oncology","correspondingAuthor":false,"prefix":"","firstName":"Jörg","middleName":"","lastName":"Chromik","suffix":""},{"id":273877885,"identity":"d033bd10-4b05-40f4-ba3b-36702b464ca7","order_by":2,"name":"Emily Tiedjen","email":"","orcid":"","institution":"Philipps University Marburg, and University Hospital Giessen and Marburg, Carreras Leukemia Center, Hematology, Oncology, Immunology","correspondingAuthor":false,"prefix":"","firstName":"Emily","middleName":"","lastName":"Tiedjen","suffix":""},{"id":273877886,"identity":"3724209a-434f-4c0c-b3dd-2c1d4912284c","order_by":3,"name":"Sebastian Wolf","email":"","orcid":"","institution":"Goethe University Frankfurt, University Hospital, Department of Medicine II, Hematology and Oncology","correspondingAuthor":false,"prefix":"","firstName":"Sebastian","middleName":"","lastName":"Wolf","suffix":""},{"id":273877887,"identity":"98f82227-c338-4b86-96c4-79194a01112f","order_by":4,"name":"Jonas B. Vischedyk","email":"","orcid":"","institution":"Goethe University Frankfurt, University Hospital, Department of Medicine II, Hematology and Oncology","correspondingAuthor":false,"prefix":"","firstName":"Jonas","middleName":"B.","lastName":"Vischedyk","suffix":""},{"id":273877888,"identity":"ddbbf86e-f03f-471c-b617-8678fa813d25","order_by":5,"name":"Philipp Makowka","email":"","orcid":"","institution":"Goethe University Frankfurt, University Hospital, Department of Medicine II, Hematology and Oncology","correspondingAuthor":false,"prefix":"","firstName":"Philipp","middleName":"","lastName":"Makowka","suffix":""},{"id":273877889,"identity":"679015f1-3899-4b36-a2f5-0977f9f34a1b","order_by":6,"name":"Julius C. Enßle","email":"","orcid":"","institution":"Goethe University Frankfurt, University Hospital, Department of Medicine II, Hematology and Oncology","correspondingAuthor":false,"prefix":"","firstName":"Julius","middleName":"C.","lastName":"Enßle","suffix":""},{"id":273877890,"identity":"927a9b80-0731-41bb-87a2-32a9660aa48d","order_by":7,"name":"Khouloud Kouidri","email":"","orcid":"","institution":"Goethe University Frankfurt, University Hospital, Department of Medicine II, Hematology and Oncology","correspondingAuthor":false,"prefix":"","firstName":"Khouloud","middleName":"","lastName":"Kouidri","suffix":""},{"id":273877891,"identity":"e686ad11-2d9f-40d1-b6df-60812298980c","order_by":8,"name":"Martin Sebastian","email":"","orcid":"","institution":"Goethe University Frankfurt, University Hospital, Department of Medicine II, Hematology and Oncology","correspondingAuthor":false,"prefix":"","firstName":"Martin","middleName":"","lastName":"Sebastian","suffix":""},{"id":273877892,"identity":"2e1b4898-e567-4de4-809a-736a1504b55b","order_by":9,"name":"Björn Steffen","email":"","orcid":"","institution":"Goethe University Frankfurt, University Hospital, Department of Medicine II, Hematology and Oncology","correspondingAuthor":false,"prefix":"","firstName":"Björn","middleName":"","lastName":"Steffen","suffix":""},{"id":273877893,"identity":"41e2a6d1-d935-4a5c-ba90-e4e89c6240e5","order_by":10,"name":"Thomas Oellerich","email":"","orcid":"","institution":"Goethe University Frankfurt, University Hospital, Department of Medicine II, Hematology and Oncology","correspondingAuthor":false,"prefix":"","firstName":"Thomas","middleName":"","lastName":"Oellerich","suffix":""},{"id":273877894,"identity":"9a7cc573-a5fb-4961-a5af-a66f2d6a9892","order_by":11,"name":"Hubert Serve","email":"","orcid":"","institution":"Goethe University Frankfurt, University Hospital, Department of Medicine II, Hematology and Oncology","correspondingAuthor":false,"prefix":"","firstName":"Hubert","middleName":"","lastName":"Serve","suffix":""},{"id":273877895,"identity":"3eeb5831-6ca8-4142-a275-ee30b4edd8b7","order_by":12,"name":"Andreas Neubauer","email":"","orcid":"","institution":"Philipps University Marburg, and University Hospital Giessen and Marburg, Carreras Leukemia Center, Hematology, Oncology, Immunology","correspondingAuthor":false,"prefix":"","firstName":"Andreas","middleName":"","lastName":"Neubauer","suffix":""},{"id":273877896,"identity":"a038e773-6853-4d3a-b5a8-01a996db625d","order_by":13,"name":"Jonas A. Schäfer","email":"","orcid":"","institution":"Philipps University Marburg, and University Hospital Giessen and Marburg, Carreras Leukemia Center, Hematology, Oncology, Immunology","correspondingAuthor":false,"prefix":"","firstName":"Jonas","middleName":"A.","lastName":"Schäfer","suffix":""},{"id":273877897,"identity":"5fb6ee31-aaa4-47f6-a81b-248d25dfe231","order_by":14,"name":"Jörg T. Bittenbring","email":"","orcid":"","institution":"Department of Internal Medicine 1, Oncology, Hematology, Clinical Immunology and Rheumatology, Saarland University Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Jörg","middleName":"T.","lastName":"Bittenbring","suffix":""}],"badges":[],"createdAt":"2024-02-10 10:44:40","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3945651/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3945651/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":51510047,"identity":"ce971679-8aa3-4889-bf82-6d495314a108","added_by":"auto","created_at":"2024-02-22 20:57:33","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":225342,"visible":true,"origin":"","legend":"\u003cp\u003eOverall Survival and Time to Next Treatment\u003c/p\u003e\n\u003cp\u003eKaplan-Meier plots of overall survival (A) and time to next treatment (B) stratified by the treatment received. CI denotes confidence interval, HMA hypomethylating agent, and VEN venetoclax.\u003c/p\u003e","description":"","filename":"figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-3945651/v1/97f9b179dbf10a59a33ac51e.png"},{"id":51510049,"identity":"11112f79-c80e-4058-84d3-cd171aa06293","added_by":"auto","created_at":"2024-02-22 20:57:33","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":207521,"visible":true,"origin":"","legend":"\u003cp\u003eOverall Survival in the HMA-VEN Cohort by Remission Status and Blood Count Recovery\u003c/p\u003e\n\u003cp\u003eKaplan-Meier plot of overall survival in patients treated with a hypomethylating agent and venetoclax, stratified by either remission status (A) or recovery of blood counts, defined at neutrophil count ≥1/nl and platelet count ≥100/nl (B). Remission refers to composite complete remission (cCR), defined as either complete remission (CR), CR with incomplete (CRi) or partial (CRh) hematological recovery. Patients unevaluable for response were excluded from plot A (see text). CI denotes confidence interval.\u003c/p\u003e","description":"","filename":"figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-3945651/v1/c1acd83eccef5a123e52b0e5.png"},{"id":51510931,"identity":"afc9b394-e59d-40d9-9418-2ef9e9ca1a3e","added_by":"auto","created_at":"2024-02-22 21:05:33","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":402975,"visible":true,"origin":"","legend":"\u003cp\u003eUnivariable and Multivariable Regression of Overall Survival\u003c/p\u003e\n\u003cp\u003eForest plots illustrating hazard ratios for overall survival based on clinical and molecular baseline characteristics. Hazard ratios and corresponding confidence intervals were derived from univariable (left) and a multivariable (right) Cox proportional hazards models. HR denotes hazard ratio, CI confidence interval, Ref reference, HMA hypomethylating agent, VEN venetoclax, AML acute myeloid leukemia, NCCN National Comprehensive Cancer Network, ECOG PS Eastern Cooperative Oncology Group Performance Status, NPM1 nucleophosmin 1, RUNX1 Runt-related transcription factor 1, FLT3 fms like tyrosine kinase 3, ITD internal tandem duplications, TP53 tumor protein p53, ASXL1 putative polycomb group protein ASXL1, IDH1/2 isocitrate dehydrogenase 1/2, mut mutated, and wt wild-type.\u003c/p\u003e","description":"","filename":"figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-3945651/v1/1f602234a7242687a9e01e62.png"},{"id":55603991,"identity":"dfcde8b1-d652-4fe5-a2d4-05886dfd39f4","added_by":"auto","created_at":"2024-04-30 12:30:21","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1221716,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3945651/v1/a0b7b0ca-487f-422b-b4a0-fcce5aa1fb56.pdf"},{"id":51510050,"identity":"0b722e75-fa7d-4757-b102-ab6d1af8b9d5","added_by":"auto","created_at":"2024-02-22 20:57:33","extension":"pdf","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":1279657,"visible":true,"origin":"","legend":"","description":"","filename":"supplementaldata.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3945651/v1/ede45ac74f3c8f04402aa1ac.pdf"}],"financialInterests":"Competing interest reported. F.A. received support for attending meetings and speaker’s honoraria from AstraZeneca, and consultant fees from IQVIA. P.M. received research grants from the Else Kröner Fresenius Stiftung. A.N. received institutional grants by the Carreras Leukemia foundation (AH05-01). T.O. received research funding from Gilead and Merck KGaA (both not related to this work). T.O. is consultant for Roche, Merck KGaA, Janssen, Genmab, Abbvie, Kronos Bio, Beigene (all not related to this work). T.O. received honoraria from Roche, Merck KGaA, Janssen, Genmab, Abbvie, Kronos Bio, Beigene. The remaining authors declare no competing financial interests.","formattedTitle":"Real-World Effectiveness of First-Line Azacitidine or Decitabine with or without Venetoclax in AML Patients Unfit for Intensive Therapy","fulltext":[{"header":"Introduction","content":"\u003cp\u003eIntensive chemotherapy and allogeneic stem cell transplantation are the most effective treatment strategies for patients with acute myeloid leukemia (AML)\u003csup\u003e1,2\u003c/sup\u003e. However, with a median age of 71 years at disease onset\u003csup\u003e3\u003c/sup\u003e, a relevant proportion of patients with AML is not eligible for intensive treatment due to comorbidities or reduced general condition.\u003c/p\u003e \u003cp\u003eThe current standard of care in the elderly or frail patient population is the combination of a hypomethylating agent (HMA), either azacitidine (AZA) or decitabine (DEC), with the oral BCL2 inhibitor venetoclax (VEN) based on the results of the VIALE-A study\u003csup\u003e2,4\u003c/sup\u003e. In this randomized phase III trial, patients with newly diagnosed AML who were considered unfit for intensive treatment received either AZA-VEN or AZA plus placebo. The median overall survival (OS) was 14.7 months (95% confidence interval [CI], 11.9\u0026ndash;18.7) in the experimental arm compared to 9.6 months (7.4\u0026ndash;12.7) in the control arm with a hazard ratio (HR) for death of 0.66 (95% CI, 0.52\u0026ndash;0.85) favoring AZA-VEN combination treatment. In a pooled analysis of VIALE-A and a phase Ib study of AZA-VEN, the superior outcomes with the combination treatment were consistently found across all European Leukemia Network (ELN) 2017 risk groups with HRs for death of 0.45 (95% CI, 0.24\u0026ndash;0.83), 0.62 (0.35\u0026ndash;1.08), and 0.59 (0.44\u0026ndash;0.79) in favorable, intermediate, and adverse risk disease, respectively\u003csup\u003e5\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eHowever, there are only limited real-world analyses on the effectiveness of HMA-VEN compared with HMA monotherapy\u003csup\u003e6\u0026ndash;9\u003c/sup\u003e. Interestingly, most of these retrospective studies failed to confirm an OS benefit in the real-world scenario, albeit sample sizes were generally small. Given these conflicting data, we performed this complimentary study in a larger patient cohort to provide further external validation of the VIALE-A results\u003csup\u003e10\u003c/sup\u003e.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design\u003c/h2\u003e \u003cp\u003eWe conducted a multicenter retrospective cohort study in patients with newly diagnosed AML who were considered unfit for intensive therapy to evaluate the real-world effectiveness of HMA-VEN in comparison to the historical standard of HMA monotherapy.\u003c/p\u003e \u003cp\u003e This study was approved by the ethics committee at University Hospital Frankfurt (UCT-51-2022) and the institutional review boards of the participating centers (University Hospitals Homburg and Marburg). Data were collected retrospectively from electronic health records, pseudonymized and merged for central analysis. The reporting adheres to Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines\u003csup\u003e11\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003ePatient selection\u003c/h2\u003e \u003cp\u003ePatients with diagnosis of AML according to the 2016 WHO classification\u003csup\u003e12\u003c/sup\u003e were considered eligible if they received a first-line therapy with azacitidine or decitabine either alone (HMA cohort) or combined with venetoclax using any dosing schedule (HMA-VEN cohort) in one of the participating centers. Prior cytoreductive therapy with leukapheresis, low-dose cytarabine, hydroxyurea or anthracycline monotherapy did not preclude inclusion.\u003c/p\u003e \u003cp\u003eVenetoclax received marketing authorization by the European Medicines Agency (EMA) in the given indication in April 2021. However, negotiations with health insurances in Germany for reimbursement were not completed until December 2021. Thus, there were several patients who started treatment with HMA monotherapy before December 2021 and subsequently received venetoclax during the course of therapy after the respective health insurance agreed to cost coverage on a per-case basis. These patients were excluded from the analysis if they received more than 3 cycles of HMA monotherapy in order to avoid potential survivorship bias favoring the HMA-VEN cohort.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eBaseline characteristics were summarized using descriptive statistics. Efficacy endpoints included OS and time to next treatment (TTNT) which were evaluated using Kaplan-Meier estimates. OS was defined as time from treatment start to death by any cause. In patients receiving allogeneic hematopoietic stem cell transplantation (HSCT), OS was censored at the date of HSCT, unless specified otherwise. Time to next treatment (TTNT) was defined as the time from treatment start to the first day of the first subsequent systemic treatment, regardless of remission status, or death. Unstratified log-rank tests were used for comparisons between the treatment cohorts. Hazard ratios (HR) and their corresponding 95% CI were derived from univariable, unstratified Cox proportional hazards (PH) models. Follow-up is reported as median and range of Kaplan-Meier estimated potential follow-up\u003csup\u003e13\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eResponse data were collected according to ELN 2022 criteria\u003csup\u003e2\u003c/sup\u003e. Confidence intervals were calculated using the Clopper-Pearson method. All centers stated that response assessments involving bone marrow aspirations were not routinely performed during most of the analyzed time period, given the palliative treatment setting. In order to reduce the risk of sampling bias, we decided to restrict all analyses of treatment response to patients with at least one evaluable response assessment during the first three months of treatment. Patients not fulfilling this criterion were considered unevaluable for response. Thus, response data in this study should be interpreted qualitatively and with caution. Accordingly, we decided to not report progression-free survival or duration of response in this study.\u003c/p\u003e \u003cp\u003eTo evaluate potential influencers of survival, univariable Cox PH models were fitted with each of a set of clinical and molecular baseline characteristics, selected by expert opinion and literature review. These variables included sex (male vs. female), age (above vs. below median), ECOG performance status (PS), disease origin (primary vs. secondary AML), National Comprehensive Cancer Network (NCCN) cytogenetic risk group version 2.2016 (dichotomized into poor vs. non-poor, Suppl. Table\u0026nbsp;1), mutational status of NPM1, RUNX1, TP53, ASXL1 and IDH1/IDH2 (either one or both), FLT3 ITD (present vs. absent) as well as baseline leukocytes (\u0026ge;\u0026thinsp;50/nl vs. \u0026lt;50/nl) and bone marrow blasts (\u0026ge;\u0026thinsp;50% vs. \u0026lt;50%). Finally, a multivariable Cox regression was performed using treatment and the factors previously identified as potential confounders (defined as P value\u0026thinsp;\u0026le;\u0026thinsp;0.3 in the univariable analyses).\u003c/p\u003e \u003cp\u003eNo imputation on missing data was performed. Patients with missing values were excluded entirely from the respective analysis. Statistical tests were two-sided with significance level set at α\u0026thinsp;=\u0026thinsp;0.05. All analyses were done using R version 4.2.3.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003ePatients\u003c/h2\u003e \u003cp\u003eA total of 213 patients matching the eligibility criteria were identified between 2013 and 2022. Thereof, 125 patients were treated with HMA-VEN and 88 with HMA monotherapy. Six patients had been excluded due to switch from HMA to HMA-VEN after having received more than 3 cycles of monotherapy, as described in the \u003cspan refid=\"Sec2\" class=\"InternalRef\"\u003eMethods\u003c/span\u003e section.\u003c/p\u003e \u003cp\u003ePatients in the HMA group were diagnosed earlier (interquartile range [IQR], January 2016 \u0026ndash; November 2018) than patients who received HMA-VEN (December 2020 \u0026ndash; April 2022). Only 3 patients (3.4%) still started HMA monotherapy after VEN received marketing authorization in April 2021.\u003c/p\u003e \u003cp\u003eBaseline characteristics were generally well balanced between groups (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Median age in the HMA-VEN and HMA cohorts were 76 (range, 37\u0026ndash;91) and 74 years (54\u0026ndash;94), respectively. There were no significant differences in the assignment to NCCN 2.2016 or ELN 2017 risk groups between cohorts. However, patients in the HMA-VEN cohort were in slightly better general condition with 56% having an ECOG PS\u0026thinsp;\u0026le;\u0026thinsp;1 compared to 41% in the monotherapy group. Additionally, more patients in the combination group had \u003cem\u003ede novo\u003c/em\u003e instead of secondary AML (64% vs. 47%).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u0026ndash; Baseline Characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHMA-VEN\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;125)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHMA\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;88)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex \u0026ndash; No. (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e46 (37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37 (42)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e79 (63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51 (58)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge \u0026ndash; yr\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian (Range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e76 (37\u0026ndash;91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e74 (54\u0026ndash;94)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eECOG PS \u0026ndash; No. (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u0026ndash;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70 (56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36 (41)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u0026ndash;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44 (35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48 (55)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMissing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEtiology \u0026ndash; No. (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDe novo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e80 (64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41 (47)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAfter MDS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24 (19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28 (32)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAfter MPN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAfter MDS/MPN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTherapy-related\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMissing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eELN 2017 Risk \u0026ndash; No. (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFavorable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34 (27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27 (31)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdverse\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75 (60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48 (55)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMissing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNCCN Cytogenetic Risk \u0026ndash; No. (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFavorable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e87 (70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54 (61)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33 (26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29 (33)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMissing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNPM1 Mutation \u0026ndash; No. (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22 (18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e94 (75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e71 (81)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMissing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCEBPA Mutation* \u0026ndash; No. (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e111 (89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e77 (88)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMissing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13 (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRUNX1 Mutation \u0026ndash; No. (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26 (21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e91 (73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61 (69)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMissing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 (26)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFLT3 TKD \u0026ndash; No. (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e72 (58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41 (47)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMissing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e47 (38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47 (53)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFLT3 ITD \u0026ndash; No. (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19 (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e67 (54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41 (47)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMissing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39 (31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43 (49)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTP53 Mutation \u0026ndash; No. (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22 (18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e97 (78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58 (66)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMissing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eASXL1 Mutation \u0026ndash; No. (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28 (22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e92 (74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53 (60)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMissing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24 (27)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIDH1 Mutation \u0026ndash; No. (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13 (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e68 (54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32 (36)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMissing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44 (35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52 (59)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIDH2 Mutation \u0026ndash; No. (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e73 (58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32 (36)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMissing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44 (35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50 (57)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBone marrow Blasts \u0026ndash; %\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian (Range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e47 (11\u0026ndash;95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34 (20\u0026ndash;90)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMissing \u0026ndash; No. (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePeripheral Blasts \u0026ndash; %\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian (Range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19.0 (0.0\u0026ndash;91.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.5 (0.0\u0026ndash;81.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWhite Blood Count (/nl)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian (Range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.0 (0.6\u0026ndash;437.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.1 (0.4\u0026ndash;239.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePrior Treatments \u0026ndash; No. (%) / Missing (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHMA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) / 8 (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e) / 1 (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHydroxyurea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) / 4 (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) / 0 (0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHSCT\u0026sect;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) / 0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) / 0 (0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eBaseline refers to the status prior to initiation of the respective treatments. (*) CEBPA mutations include both in-frame bZIP mutations and any biallelic mutations, due to changes in classification. (\u0026sect;) HSCT for prior MDS or MPN. HMA denotes hypomethylating agent, VEN venetoclax, ECOG PS Eastern Cooperative Oncology Group Performance Status, MDS myelodysplastic syndrome, MPN myeloproliferative neoplasm, ELN European Leukemia Network, NCCN National Comprehensive Cancer Network, NPM1 nucleophosmin 1, CEBPA CCAAT/enhancer-binding protein-α, RUNX1 Runt-related transcription factor 1, FLT3 fms like tyrosine kinase 3, TKD tyrosine kinase domain, ITD internal tandem duplications, TP53 tumor protein p53, ASXL1 putative polycomb group protein ASXL1, IDH1/2 isocitrate dehydrogenase 1/2, and HSCT hematopoietic stem cell transplantation.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn the HMA-VEN cohort, 122 (98%) and 3 (2%) patients received AZA and DEC, respectively, compared to 58 (66%) and 30 (34%) in the HMA cohort.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eSurvival outcomes\u003c/h2\u003e \u003cp\u003eWith a median time of follow-up of 12.8 months in the HMA-VEN cohort (range, 0.4\u0026ndash;61.7) and 26.6 months in the HMA cohort (0.2\u0026ndash;67.2), OS was significantly longer in patients receiving HMA-VEN (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). Median OS in the HMA-VEN and HMA cohorts was 7.9 months (range, 5.1\u0026ndash;14.7) and 4.9 months (3.1\u0026ndash;7.1), respectively, with 42% (95% CI, 33\u0026ndash;54) and 19% (12\u0026ndash;30) of patients being alive after 1 year of treatment. The HR for death was 0.64 (95% CI, 0.46\u0026ndash;0.88; p\u0026thinsp;=\u0026thinsp;0.006).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFavorable OS in the HMA-VEN cohort compared to the HMA cohort was consistently found across most subgroups defined by baseline patient or tumor characteristics, including age, NPM1 and TP53 status, and NCCN and ELN 2017 risk groups (Suppl. Figure\u0026nbsp;1). Median OS in the HMA-VEN and HMA cohorts was 20.2 (95% CI, 20.2-not calculable [NC]) and 7.6 months (1.4-NC), respectively, in patients with ELN 2017 favorable risk disease compared to 9.5 (6.2-NC) and 4.9 months (2.8\u0026ndash;11.0) with intermediate and 7.0 (4.2\u0026ndash;12.0) and 4.6 months (2.6\u0026ndash;7.1) with adverse risk AML (Suppl. Figure\u0026nbsp;2).\u003c/p\u003e \u003cp\u003eSurprisingly, in patients with ASXL1-mutant AML, OS was numerically shorter with HMA-VEN compared to HMA monotherapy (Suppl. Figure\u0026nbsp;3A). Multiple regression including an interaction analysis suggests a differential impact of ASXL1 status depending on the treatment received (P value for interaction, 0.04; Suppl. Figure\u0026nbsp;3B). However, numbers are too low to draw conclusions.\u003c/p\u003e \u003cp\u003eTTNT was significantly longer in the HMA-VEN cohort, with a median of 5.3 months (95% CI, 4.2\u0026ndash;7.4) compared to 3.4 months (2.5\u0026ndash;4.9) in the HMA cohort (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). HR for treatment switch or death was 0.63 (95% CI, 0.47\u0026ndash;0.85; p\u0026thinsp;=\u0026thinsp;0.002) favoring the combination cohort.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eTreatment response\u003c/h2\u003e \u003cp\u003eOf the 125 patients in the HMA-VEN cohort and 88 patients in the HMA cohort, 49 (39%) and 29 (33%) patients, respectively, were evaluable for response. More patients in the combination group achieved composite complete remission (cCR) as best response, which was defined as either CR or CR with incomplete (CRi) or partial (CRh) hematological recovery (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In the HMA-VEN group, 28 of 49 (57%; 95% CI, 42\u0026ndash;71) evaluable patients had cCR compared to 4 of 29 (14%, 4\u0026ndash;32) in the HMA group. In contrast, 9 of 49 (31%, 9\u0026ndash;32) and 13 of 29 (45%, 26\u0026ndash;64) evaluable patients had no response, respectively.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003e\u0026ndash; Best Response\u003c/b\u003e Best response according to European Leukemia Network 2022 criteria stratified by treatment. Patients without response assessment during the first three months of treatment were considered non-evaluable. (*) percentages in the response categories are calculated as the number of patients in the respective category divided by the number of evaluable patients in the treatment cohort. HMA denotes hypomethylating agent, VEN venetoclax, CR complete remission, CRi complete remission with incomplete recovery, CRh complete remission with partial recovery, MLFS morphologic leukemia-free state, and PR partial remission.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResponse\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHMA-VEN\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;125)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHMA\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;88)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-Evaluable \u0026ndash; No. (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e76 (61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59 (67)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEvaluable* \u0026ndash; No. (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e49 (39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29 (33)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ecCR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28 (57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17 (35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCRi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCRh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 ()\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMLFS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (28)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo Response\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (45)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003e\u003cb\u003eSupplementary Data\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn patients treated with HMA-VEN, achievement of cCR was associated with favorable OS with a HR for death of 0.25 (95% CI, 0.10\u0026ndash;0.59; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). Median OS in HMA-VEN patients with cCR was 24.3 months (95% CI, 11.7-NC) compared to 5.0 (3.5-NC) in patients without cCR.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eSince a large proportion of patients in a palliative treatment setting do not undergo response assessments outside of clinical trials, we evaluated whether the recovery of peripheral blood counts was also prognostic for OS. In the HMA-VEN cohort, 58 of 125 patients (46%) achieved blood count recovery, defined as neutrophils\u0026thinsp;\u0026ge;\u0026thinsp;1/nl and platelets\u0026thinsp;\u0026ge;\u0026thinsp;100/nl, and 67 (54%) did not. Patients with recovery exhibited a longer OS with a HR for death of 0.52 (95% CI 0.33\u0026ndash;0.84; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). Median OS was 16.4 months (95% CI, 8.1\u0026ndash;22.5) and 3.8 months (3.2\u0026ndash;9.5), respectively.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eSubsequent treatments\u003c/h2\u003e \u003cp\u003eIn the HMA-VEN and HMA cohorts, 27 of 125 (22%) and 31 of 88 (35%) of patients received at least one subsequent treatment for AML with the majority being low intensity regimens (Suppl. Table\u0026nbsp;2). Only 3 patients (3%) in the HMA cohort received venetoclax as part of any subsequent therapy. Intensive treatment was given in 1 (1%) and 10 (11%) patients in the HMA-VEN and HMA cohorts, respectively. HSCT was performed in 14 (11%) and 8 (9%) patients. Without censoring for HSCT, OS continued to favor the HMA-VEN cohort with a HR for death of 0.71 (95% CI, 0.52\u0026ndash;0.98; Suppl. Figure\u0026nbsp;4A). Post-transplantation survival is shown in Suppl. Figure\u0026nbsp;4B.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eMultiple regression\u003c/h2\u003e \u003cp\u003eIn the univariable regression models, treatment group, NCCN poor cytogenetic risk (HR 1.99; 95% CI, 1.40\u0026ndash;2.83), ECOG PS\u0026thinsp;\u0026ge;\u0026thinsp;2 (2.67; 1.89\u0026ndash;3.77) and presence of a TP53 mutation (1.94; 1.27\u0026ndash;2.97) were associated with shorter OS (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eBased on the criteria defined above, treatment, age, NCCN risk group, ECOG PS, leukocytes as well as NPM1, RUNX1, and TP53 status were included into the multiple regression model. In addition, we decided to also include the choice of HMA because of large imbalances between the cohorts. In the multivariable analysis, treatment with HMA-VEN remained significantly associated with a prolonged OS with a HR for death of 0.48 (95% CI, 0.29\u0026ndash;0.77; p\u0026thinsp;=\u0026thinsp;0.003; Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). While patients with higher age or assignment to the NCCN poor risk group showed a tendency towards shorter OS, only TP53 mutations (HR, 1.82; 95% CI, 1.01\u0026ndash;3.30) and ECOG PS\u0026thinsp;\u0026ge;\u0026thinsp;2 (2.78; 1.77\u0026ndash;4.37) were significantly coupled with poorer survival in the multivariable regression model. The use of DEC was associated with numerically improved OS compared to AZA.\u003c/p\u003e \u003cp\u003eA second analysis using the ELN 2017 risk stratification instead of the NCCN 2.2016 classification of cytogenetic risk, showed similar results. The HR for death was 0.51 (95% CI, 0.34\u0026ndash;0.78) for treatment with HMA-VEN compared to HMA alone. Moreover, favorable and intermediate ELN 2017 risk were associated with improved OS compared to adverse risk with HRs of 0.46 (95% CI, 0.24\u0026ndash;0.85) and 0.59 (0.39\u0026ndash;0.88), respectively (Suppl. Figure\u0026nbsp;5).\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eTo our knowledge, this is the so far largest retrospective study comparing the outcomes of HMA-VEN combination and HMA monotherapy in patients with AML who are unfit for intensive chemotherapy. We demonstrated an OS benefit for the combination treatment in a real-world setting which remained significant after adjusting for prognostic baseline variables. Nevertheless, survival times were generally shorter in comparison to the VIALE-A trial\u003csup\u003e4\u003c/sup\u003e. Since the captured baseline characteristics appear similar to those reported in the trial, the reasons for this discrepancy remain unclear but may in part be attributable to comorbidities or the survivorship bias associated with the screening phase in the context of a clinical study. Despite the limitations in interpreting response data in our study, response rates appeared higher in patients treated with HMA-VEN compared to HMA.\u003c/p\u003e \u003cp\u003eIn our study, baseline characteristics were generally balanced between cohorts. However, 34% patients in the monotherapy cohort received DEC compared to only 2% with HMA-VEN. While VEN is approved in combination with both AZA and DEC by FDA and EMA, this is most likely because AZA was the HMA used in the VIALE-A trial\u003csup\u003e4\u003c/sup\u003e. Consequently, we included the choice of HMA as variable in the multiple regression model and found no significant impact on OS between AZA and DEC. Given the low number of patients receiving DEC-VEN in our study, an interaction analysis was not performed. Kwag et al.\u003csup\u003e8\u003c/sup\u003e recently showed that outcomes with DEC-VEN vs. DEC monotherapy are comparable with those seen with AZA-VEN vs. AZA: in 148 patients receiving either DEC-VEN or DEC, OS was superior in the combination group with a HR of 0.60 (95% CI, 0.40\u0026ndash;0.91) after propensity score matching. Notably, 26% and 5% of patients in the DEC-VEN and DEC arms, respectively, continued to HSCT. While it is unclear, whether this reflects different treatment intentions or simply the superior response rates using DEC-VEN, OS remained significantly improved when censoring for HSCT with a HR of 0.62 (0.40\u0026ndash;0.97)\u003csup\u003e8\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn our study, patients with ASXL1-mutant AML had shorter OS with HMA-VEN compared to HMA alone. Given that preclinical and clinical data in AML and MDS suggest improved response rates with the addition of VEN in ASXL1-mutant disease\u003csup\u003e14\u0026ndash;17\u003c/sup\u003e, our results appear implausible. Confirmation from independent cohorts will be required for robust hypotheses generation as findings from subgroup analyses may be subject to alpha error inflation.\u003c/p\u003e \u003cp\u003eOur study has several other limitations. First, we were not able to adjust for comorbidities which represent important confounders, especially in the context of elderly and frail patients. Second, as high response rates have been reported for HMA-VEN, physicians may be increasingly inclined to treat borderline frail patients with HMA-VEN with HSCT consolidation in mind. This may have introduced unmeasurable imbalances. However, HSCT rates were comparable between cohorts. Third, our study compared patients from different time periods. Different supportive measures may have influenced survival. Four, we did not provide information on comorbidities, toxicity and quality of life, because these parameters could not be reliably derived from electronic health records.\u003c/p\u003e \u003cp\u003eIn conclusion, our data support the findings of VIALE-A that the addition of VEN to HMA improves OS in patients unfit for intensive treatment, despite most retrospective studies so far have failed to demonstrate a survival benefit for HMA-VEN vs. HMA\u003csup\u003e6\u0026ndash;9\u003c/sup\u003e.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eNo funding was received for conducting this study.\u003c/p\u003e\n\u003cp\u003eContribution: F.A. and J.C. conceptualized and designed the study; F.A., J.S., and J.B. acquired clinical data; F.A. performed statistical analyses and wrote the initial draft of the manuscript; F.A., J.C., E.T., S.W., J.V., P.M., J.E., K.K., M.S., B.S., T.O., H.S., A.N., J.S., and J.B. contributed to data interpretation, critically reviewed the manuscript, and approved the final version.\u003c/p\u003e\n\u003cp\u003eConflict-of-interest disclosure: F.A. received support for attending meetings and speaker\u0026rsquo;s honoraria from AstraZeneca, and consultant fees from IQVIA. P.M. received research grants from the Else Kr\u0026ouml;ner Fresenius Stiftung. A.N. received institutional grants by the Carreras Leukemia foundation (AH05-01). T.O. received research funding from Gilead and Merck KGaA (both not related to this work). T.O. is consultant for Roche, Merck KGaA, Janssen, Genmab, Abbvie, Kronos Bio, Beigene (all not related to this work). T.O. received honoraria from Roche, Merck KGaA, Janssen, Genmab, Abbvie, Kronos Bio, Beigene. The remaining authors declare no competing financial interests.\u003c/p\u003e\n\u003cp\u003eCorrespondence: Dr. Fabian Acker; University Hospital Frankfurt, Department of Hematology and Oncology, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany; e‑mail: [email protected].\u003c/p\u003e\n\u003cp\u003eUpon reasonable request addressed to the corresponding author, data shown in this work, including individual patient data after de-identification, will be shared to investigators who provide a methodologically sound proposal.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eKantarjian H, Kadia T, DiNardo C et al (2021) Acute myeloid leukemia: current progress and future directions. 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Blood Cancer J 11(9):1\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41408-021-00541-0\u003c/span\u003e\u003cspan address=\"10.1038/s41408-021-00541-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"AML, Azacitidine, Decitabine, Hypomethylating Agent, Venetoclax, Real-World Data","lastPublishedDoi":"10.21203/rs.3.rs-3945651/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3945651/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eStandard frontline treatment in patients with acute myeloid leukemia (AML) unfit for intensive therapy is the combination of a hypomethylating agent (HMA) with venetoclax (VEN). However, retrospective data confirming the benefits of this regimen outside of clinical trials are sparse and have shown conflicting results. Thus, we performed a multicenter retrospective analysis of outcomes with HMA-VEN compared to HMA alone in patients with newly diagnosed AML unfit for intensive treatment. A total of 213 patients were identified from 3 German tertiary care centers. Of those, 125 were treated with HMA-VEN and 88 with HMA alone. Median overall survival (OS) in the HMA-VEN cohort was 7.9 months (95% confidence interval [CI], 5.1\u0026ndash;14.7) compared to 4.9 months (3.1\u0026ndash;7.1) with HMA alone. After 1 year, 42% (95% CI, 33\u0026ndash;54) and 19% (12\u0026ndash;30) of patients were alive, respectively. The hazard ratio (HR) for death was 0.64 (95% CI, 0.46\u0026ndash;0.88; p\u0026thinsp;=\u0026thinsp;0.006). After adjusting for age, NCCN cytogenetic risk, NPM1, RUNX1, and TP53 status, ECOG performance status, baseline leukocytes, and type of HMA, treatment with HMA-VEN remained significantly associated with a prolonged survival (HR, 0.48; 95% CI, 0.29\u0026ndash;0.77). Accordingly, time to next treatment (TTNT) was longer with HMA-VEN with a HR of 0.63 (95% CI, 0.47\u0026ndash;0.85). Patients who achieved recovery of peripheral blood counts had a favorable prognosis (HR for death, 0.52; 95% CI, 0.33\u0026ndash;0.84). These data align with findings from the pivotal VIALE-A trial and support the use of HMA-VEN in patients unfit for intensive therapy.\u003c/p\u003e","manuscriptTitle":"Real-World Effectiveness of First-Line Azacitidine or Decitabine with or without Venetoclax in AML Patients Unfit for Intensive Therapy","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-02-22 20:57:28","doi":"10.21203/rs.3.rs-3945651/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e5ee0361-5b37-445e-986d-d2144353c0b9","owner":[],"postedDate":"February 22nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-04-30T12:29:56+00:00","versionOfRecord":[],"versionCreatedAt":"2024-02-22 20:57:28","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3945651","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3945651","identity":"rs-3945651","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}