Prognostic impact of measurable residual disease in AML patients treated frontline with azacitidine and venetoclax: results from the French VENAURA registry

Prognostic impact of measurable residual disease in AML patients treated frontline with azacitidine and venetoclax: results from the French VENAURA registry | 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 Article Prognostic impact of measurable residual disease in AML patients treated frontline with azacitidine and venetoclax: results from the French VENAURA registry Maël Heiblig, Zofia Gross, Amine Belhabri, Urbain Tauveron-Jalenques, and 26 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7959681/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 11 You are reading this latest preprint version Abstract Measurable residual disease (MRD) is a key prognostic marker in acute myeloid leukemia (AML) but its significance in patients treated with azacitidine and venetoclax (AZA/VEN) outside clinical trials remains unclear. We retrospectively analyzed 220 newly diagnosed AML patients from the French VENAURA registry who achieved composite complete remission and underwent MRD evaluation by multiparametric flow cytometry (MFC, LAIP/LSC) and/or NPM1 RT-qPCR. Median age was 74 years. Cumulative MRD negativity was achieved in 62–67% of patients depending on the method. Attaining MRD negativity at any time was strongly associated with superior overall survival (OS: 31.3 months vs 15.7 months for LAIP, not reached vs 10.8 months for NPM1; all p<0.001) and lower cumulative incidence of relapse. Dual LAIP/LSC negativity conferred the best outcomes (4-year OS ~57%). Importantly, MRD response mitigated the adverse prognostic impact of ELN 2024 intermediate/poor risk, with MRD-negative patients achieving outcomes comparable to favorable-risk cases. MRD kinetics (early vs late responders) did not affect survival, while G-CSF use improved MRD conversion and OS. In real-world AZA/VEN–treated AML, achieving deep MRD negativity—by MFC or NPM1 RT-qPCR—emerges as the dominant prognostic determinant, overriding baseline risk and supporting its integration into response-adapted strategies. Health sciences/Diseases/Haematological diseases/Haematological cancer/Leukaemia/Acute myeloid leukaemia Biological sciences/Cancer/Haematological cancer/Leukaemia/Acute myeloid leukaemia Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction In patients treated intensively for acute myeloid leukemia (AML), measurable residual disease (MRD) has become a critical standardized endpoint which is highly predictive of relapse-free survival (RFS) and overall survival (OS) [1–4] . However, MRD predictive value at specific time points during intensive chemotherapy (IC) courses in AML has been mostly evaluated by quantitative polymerase chain reaction (RT-qPCR) for NPM1 mut , CBF -rearranged and PML::RARA AML [1,3,5] . Yet, only 30–35% of patients present molecular abnormalities that can be assessed by RT-qPCR, and even less in elderly patients. Multiparametric flow cytometry (MFC) MRD is applicable to a majority of patients after treatment-induced morphologic remission, even for those who do not harbor an appropriate molecular target for RT-qPCR. Tremendous efforts have been made to standardize MFC-MRD procedures and define specific thresholds according to DfN (Different from normal)/LAIP (leukemia associated immunophenotype) and more recently LSC (Leukemic Stem Cell) approaches [6] . In this context, LSC-MRD by MFC appeared to be highly predictive for survival and relapse risk in a large prospective cohort of patients treated with intensive chemotherapy (IC) [7] . While integrated into response assessment in pediatric AML, MFC-MRD in adult AML is not yet used as a preemptive factor for risk assessment, therapeutic intervention and/or hematopoietic stem cell transplantation allocation for patients treated with IC. For patients unfit for IC, low intensity therapy based on azacitidine are usually offered. A retrospective study reported that in patients age > 60 years and treated with hypomethylating agents, the cumulative incidence of relapse was shown lower among patients who had achieved a MRD-negative (MRD neg ) response, but no relationship between MRD and overall survival (OS) or relapse free survival (RFS) was demonstrated [8] . More recently, azacitidine and venetoclax (AZA/VEN) combination regimen have emerged as a new standard of care in frontline unfit AML patients [9] . In the VIALE-A prospective trial, patients treated with AZA/VEN were evaluated for MRD by MFC at the end of cycle 1, and every three cycles thereafter. Median OS was not reached in patients reaching MRD neg at any time with a predicted 12 months OS of 94% [10] . Similarly, Othman et al. reported on a large retrospective cohort of NPM1 mut patients treated with VEN based regimens that NPM1-MRD neg was associate with a favorable outcome [11] . Despite these advances, MRD negativity either by MFC or RT-qPCR (i.e. NPM1 mut ) determinants and their impact on survival outside clinical trial remains limited in AZA/VEN treated patients. Identifying patients with favorable outcome might be the corner stone for future de-escalation strategy. We aimed in this retrospective study to evaluate the predictive value of MRD negativity by MFC or NPM1 RT-qPCR and its kinetics on survival in AML patients treated upfront with AZA/VEN in real life settings. Methods 1. Study design VENAURA is an observational, multicenter registry collecting retrospective data on AZA/VEN-treated AML patients from 12 centers in the French Auvergne-Rhône-Alpes (AURA) region between January 2019 and February 2024 (IRB 00013204). Inclusion criteria were patients with AML according to the WHO 2022 classification (including low-blast AML/MDS) receiving AZA/VEN as frontline therapy, with at least one MRD assessment during the first six cycles. AZA/VEN response and MRD assessments were evaluated as described below. Composite complete remission (CRc) was defined as in the VIALE-A trial. Regarding MFC-MRD, its assessment was based on the LAIP approach according to the European LeukemiaNet (ELN) recommendations (bulk lysis and at least 500,000 recorded events to achieve a sensitivity threshold of at least 10⁻³ [0.1%]). MFC-MRD was performed on bone marrow samples using an 8-color panel and considered positive when detectable above the 0.1% threshold for LAIP and 0.01% for LSC assays [6,12] . A “backbone” of CD34/CD38/CD45/CD117 was used in both tubes, supplemented by CD7, CD56, CD13, CD33, HLA-DR, and CD19 for LAIP assessment, and by CD90 (Thy-1), Mix (CD97/CLL1/TIM3), CD45RA, and CD123 for LSC analysis [13] . LSC low was defined as an LSC population <1% at baseline, as previously reported [7] . NPM1 RT-qPCR MRD was performed as previously described [3] . MRD negativity (MRD neg ) was defined as ≤10⁻⁵ for NPM1 by RT-qPCR on peripheral blood (or bone marrow when available). For NPM1 mut patients evaluated by both flow cytometry and RT-qPCR, those negative by flow but positive by RT-qPCR were considered MRD pos . For patients evaluated only by MFC, an early MRD response was defined as negativity on the first MRD assessment (MRD1) confirmed at the second evaluation (MRD2). Late responders were defined by conversion from MRD1 positivity to MRD2 negativity between two time points. Poor MRD responders were defined as persistent MRD positivity at both MRD1 and MRD2, or loss of MRD1 negativity at MRD2. For Sankey diagrams, patients were censored at the time of the last received cycle, allogeneic hematopoietic stem cell transplantation, or toxic death. If patients were not re-evaluated at subsequent cycles, their MRD response for the next cycle was based on the last available MRD evaluation. 2. Statistical analysis For comparisons between patient characteristics, Mann–Whitney and Kruskal–Wallis tests were used for continuous quantitative variables, and the Chi-square test for categorical variables. Probabilities of OS were estimated using the Kaplan–Meier method. To study the cumulative incidence of relapse, a cumulative incidence model was applied. Univariate analyses were performed using the log-rank test for OS and Gray’s method for cumulative incidence outcomes. Multivariate regression was carried out using a Cox proportional hazards model, including all variables significant in univariate analyses. Statistical analyses were performed using GraphPad Prism software version 8.0.1 for Windows (GraphPad Software, San Diego, California, USA, www.graphpad.com) and R software version 4.1.1 (R Core Team, 2021. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org). Results 1. Patient characteristics Of the 438 frontline patients included in the registry, 220 achieved CRc and had at least one MRD assessment by MFC or RT-qPCR (NPM1) during follow-up (Supplemental Figure 1). Patients’ characteristics are summarized in Supplemental Table 1. Median age at diagnosis was 74.4 years (range: 31–88), and 15.4% of patients were aged over 80. A prior myeloid neoplasm was reported in 32.3% of cases, most frequently myelodysplastic syndromes (20%), followed by chronic myelomonocytic leukemia (8.6%) and myeloproliferative neoplasms (3.6%). Therapy-related AML (t-AML) was reported in 7.2% (16/220) of cases. Morphologically, 29.1% of patients had cytological myelodysplasia-related changes, and 25.4% had a monocytic bias (defined as FAB M4/5). Extramedullary disease was reported in 4.5% (10/220) of patients (five leukemia cutis, four central nervous system infiltrations, and one isolated myeloid sarcoma). Cytogenetic and molecular risk according to the 2024 ELN classification was available for 165/220 patients: 52.1% were favorable, 27.3% intermediate, and 20.6% adverse risk. After a median follow-up of 12.8 months, median OS of patients reaching CRc at any time during the first six cycles and evaluated for MRD was 17.8 months. 2. LAIP MRD response determinants and impact on survival Bone marrow LAIP-MRD assessment was performed at least once during the first six AZA/VEN cycles in 184/220 patients (83.6%), with a median time to first LAIP-MRD assessment (LAIP-MRD1) of one cycle (range: 1–6). At the end of cycle 1, 75.5% (139/184) were evaluated for LAIP-MRD, and 51.9% were LAIP-MRD1 neg . LAIP-MRD1 pos patients evaluated a second time during the first six cycles (n=66) converted to MRD2 neg in 45.4% (30/66) of cases by the end of cycle 6. Conversely, 16.6% of LAIP-MRD1 neg patients lost their MRD response during the first six cycles. The cumulative LAIP-MRD neg rate was 61.7% (Figure 1A). Overall, 27% of patients relapsed by the end of the first six cycles, mostly from the LAIP-MRD pos population (Figure 1B), while the LAIP-MRD neg rate remained stable. A prior history of MPN or MDS (HR=3.1, p=0.008), NPM1 mut (HR=0.1, p=0.009), granulocyte colony-stimulating factor (G-CSF) use at any time (HR=0.35, p=0.031), and complex karyotype (HR=2.32, p=0.025) were significantly associated with LAIP-MRD neg probability, while the ELN 2024 classification or single mutations (i.e., IDH mut , TP53 mut ) were not (Supplemental Table 2). Venetoclax dose or exposure duration during cycle 1 and subsequent cycles did not influence MRD response probability. Moreover, VEN dose reduction after cycle 1 did not affect relapse probability in either the LAIP-MRD1 neg or MRD1 pos populations. In patients who received G-CSF after CRc, the overall LAIP-MRD neg rate was 74.6% compared to 51.9% in those who did not (p=0.002). After logistic regression, only NPM1mut, prior history of MPN/MDS, and G-CSF use at any time were independently associated with LAIP-MRD neg probability (Table 1). When evaluated at the end of cycle 1, LAIP-MRD1 neg was associated with improved OS compared to LAIP-MRD1 pos (31.2 vs 17.8 months, p=0.044) (Figure 1C). However, LAIP-MRD1 was not predictive of relapse (Supplemental Figure 2A), and different LAIP-MRD thresholds at the end of cycle 1 were not predictive of relapse (Supplemental Figure 3A). Median OS for patients who achieved best LAIP-MRD neg at any time during the first six AZA/VEN cycles was 31.3 months, with an estimated 2-year OS of 58.9%. Conversely, median OS was significantly lower (15.7 months) in LAIP-MRDpos patients (HR=0.43, p<0.001) (Figure 1D). At 24 months, patients with best LAIP-MRD pos status had a higher CIR of 70.9% compared to 29.1% in those with best LAIP-MRD neg (Supplemental Figure 2B). Deeper LAIP-MRD responses at best MRD assessment were predictive of relapse. The 12-month CIR was 28.3%, 38%, 67.1%, and 70% for negative, 0.1–0.9%, 1–4.9%, and ≥5% LAIP-MRD, respectively (Supplemental Figure 3B). Regarding timing of MRD evaluation, among patients evaluated at two time points (LAIP-MRD1 and LAIP-MRD2) during the first six cycles, early LAIP-MRD responders had similar outcomes to late responders (p=0.32). In contrast, poor LAIP-MRD response was associated with lower OS (p<0.001) (Figure 1E). 3. LSC MRD response determinants and impact on survival Among the 175 patients assessed for LAIP-MRD by MFC, 61.1% (126/175) were also evaluated using the LSC approach at diagnosis. Median LSC levels at diagnosis were 4% (95% CI: 2–6%); 42% (53/126) and 58% (73/126) were LSC low and LSC high , respectively. Patients with LSC low populations at diagnosis were more frequently favorable according to ELN 2024 and enriched in NPM1mut (Supplemental Table 3). Of the 126 patients evaluated at baseline, 107 were subsequently followed for MRD. The cumulative LSC-MRD neg rate during the first six cycles was 67.4% (Figure 2A). Among patients evaluated at two time points during these cycles, conversion from LSC-MRD1 pos to LSC-MRD2 neg occurred in 13/27 (48.1%). By the end of cycle 6, 77.8% (21/27) of LSC-MRD pos patients who did not convert to LSC-MRD neg relapsed (Figure 2B). Conversely, relapse within the first six cycles occurred in only 7.1% (4/56) of patients who achieved LSC-MRD neg (Figure 2B). The cumulative LSC-MRD neg rate was significantly lower in patients with adverse ELN risk (40%) compared to favorable (73%) and intermediate (67%) groups (Figure 2C). Monocytic bias at diagnosis (OR=0.2, p=0.045), complex karyotype (OR=4.06, p=0.018), and adverse ELN 2024 classification were significantly associated with lower LSC-MRD neg probability (Supplemental Table 4). In the multivariate model, only prior MDS/MPN history was independently associated with LSC-MRD neg probability (Table 2), while G-CSF use and ELN classification were not. We then compared LAIP and LSC kinetics across cycles. Using a two-way ANOVA mixed-effects model assuming sphericity, MRD technique had a significant effect on MRD values (F(1,334)=6.84, p=0.0093), indicating that the predicted mean LAIP-MRD (M=3.46) was consistently higher than LSC-MRD (M=0.86; difference=2.60, 95% CI [0.64, 4.55]). However, the kinetic decay profiles of LAIP and LSC MRD were similar across groups (F(5,277)=0.58, p=0.71) (Figure 2D). When considering LSC levels at diagnosis, patients with LSC low had superior median OS compared to LSC high , but this did not reach statistical significance (NR vs 14.1 months, p=0.071) (Supplemental Figure 3). At the end of cycle 1, LSC-MRD1 neg status was associated with a favorable outcome compared to LSC-MRD1 pos (31.3 vs 8.2 months, p=0.044) (Figure 2E). Unlike LAIP-MRD, LSC-MRD1 was predictive of relapse (Supplemental Figure 2C). Median OS for patients who achieved LSC-MRD neg at any time during the first six AZA/VEN cycles was 31.3 months, with a 2-year OS of 56.4% (Figure 2F). As for LAIP-MRD, best LSC-MRD pos status was associated with poor outcomes, mainly due to a 24-month CIR of 83.3% compared to 45.1% in best LSC-MRD neg (Supplemental Figure 2D). Deeper LSC-MRD thresholds at cycle 1 or best MRD response were significantly associated with relapse, as any MRD pos level correlated with a higher relapse risk (Supplemental Figures 3C–D). When comparing timing of MRD evaluation, among patients assessed at two time points (LSC-MRD1 and LSC-MRD2), late MRD responders had outcomes similar to poor MRD responders (Figure 2G). Finally, as LSC and LAIP-MRD by MFC are complementary approaches to evaluate residual AML cells, both were combined to assess their joint impact on survival. Patients achieving dual LAIP-MRD neg /LSC-MRD neg exhibited very favorable outcomes, with median OS not reached and a 4-year estimated OS of 57%. Conversely, all other MRD response patterns were associated with significantly shorter survival (Figures 3A–B). Using Harrell’s C-index, dual LAIP-MRD neg /LSC-MRD neg (AUC=0.83) demonstrated superior prognostic discrimination compared to LAIP-MRD neg (AUC=0.7) or LSC-MRD neg (AUC=0.78) alone. 4. NPM1 MRD response rate and impact on survival A total of 56 patients with NPM1mut were evaluable by RT-qPCR. The NPM1 mutational burden showed a median mutated allelic fraction at diagnosis of 524% (range: 51–3452). By the end of cycle 1, only 7% of NPM1 mut patients were NPM1-MRD neg (Figure 4A). Overall, cumulative NPM1-MRD neg at any time was 62.5%, with a median time to MRD neg of six cycles (range: 1–6). Relapse rate within the first six cycles was low (10.7%) and occurred only in patients who did not achieve MRD neg by the end of cycle 6 (Figure 4B). No variables significantly influenced the probability of reaching NPM1-MRD neg . Achieving NPM1-MRD neg at any time during the first six AZA/VEN cycles was associated with median OS not reached and an estimated 4-year OS of 69.7%, whereas median OS in NPM1-MRD pos patients was significantly lower (10.8 months, p<0.001) (Figure 4C). We then compared NPM1 MRD kinetics to LAIP- and LSC-based approaches. Compared to LAIP-MRD, neither cycles (F(1.182,26.00)=1.22, p=0.29), MRD type (F(1,74)=1.74, p=0.19), nor their interaction (F(5,110)=1.20, p=0.32) had a significant effect on MRD kinetics, indicating statistically indistinguishable kinetic profiles between NPM1-MRD and LAIP-MRD. Similar results were observed with LSC-MRD (Figure 4D). While discrepancies between NPM1-MRD and LAIP-MRD were infrequent (Supplemental Figure 5), the depth of molecular response provided additional prognostic information. As NPM1 MRD negativity was typically achieved later and at different thresholds compared to MFC MRD, a ≥3-log reduction (3-logRED) in NPM1 transcript levels by the end of cycle 3 was strongly associated with a favorable prognosis compared to those not reaching this response (Figure 4E). Using Harrell’s C-index, >3-logRED NPM1 (AUC=0.85) demonstrated superior prognostic discrimination compared to MRD neg status within the first six AZA/VEN cycles (AUC=0.8). 5. Impact of MRD on survival according to ELN 2024 risk groups To further evaluate the overall impact of MRD response during the first six AZA/VEN cycles on outcome according to the ELN 2024 classification, we analyzed patients evaluated for both LAIP and NPM1-MRD. For NPM1 mut patients, MRD status (NEG vs POS) was based on RT-qPCR rather than LAIP/LSC-MRD. According to ELN 2024, median OS was 22.9, 13.8, and 10.9 months in favorable, intermediate, and adverse risk groups, respectively (Figure 5A). As there was no significant difference in outcome, intermediate and adverse groups were merged (INT/ADV) for further analysis. In the ELN favorable (FAV) group, median OS was not reached in MRD neg patients versus 16.7 months in MRD pos (p=0.002) (Figure 5B). Similarly, in the ELN INT/ADV group, median OS was 31.3 versus 9.3 months in MRD neg and MRD pos , respectively (p=0.008) (Figure 5B). MRD response abrogated the negative impact of ELN classification, as no significant differences were observed between FAV and INT/ADV MRD neg patients (HR=0.65, p=0.15), nor between FAV and INT/ADV MRD pos patients (HR=1.77, p=0.22) (Figure 5B). When using LSC (and NPM1 in evaluable patients), results were similar, with no significant difference between FAV and INT/ADV MRD neg patients (HR=0.54, p=0.09) (Supplemental Figure 6). Univariate analyses of variables influencing OS are summarized in Supplemental Table 5. After logistic regression, ANC at diagnosis (continuous, HR=1.04, p=0.001), diploid karyotype (yes vs no, HR=0.58, p=0.03), G-CSF use after cycle 1 (yes vs no, HR=0.6, p=0.03), and best MRD response (POS vs NEG, HR=2.44, p<0.001) were independently associated with OS, while HSCT and ELN 2024 classification were not (Table 3). Discussion In intensively treated AML, achieving deep MRD-negative complete remission is a well-established prognostic factor associated with prolonged OS and RFS compared with morphological remission alone. In older or unfit patients, azacitidine combined with venetoclax (AZA/VEN) not only improves complete remission rates but also increases the depth of response compared with azacitidine monotherapy [9] . In VIALE-A, 32% of patients in CRc under azacitidine alone achieved MRD negativity ( 60 years treated with hypomethylating agents alone found no significant correlation between MRD negativity and OS [8] . In contrast, AZA/VEN-treated patients achieving MRD-negative CRc showed longer remission durations and improved survival [10] . However, limited real-world data exist on the clinical impact of MRD and its kinetics in treatment-naive, lower-intensity, VEN-based therapy. Our study, one of the largest real-world series to date, confirms the strong association between MRD negativity (by MFC or NPM1 RT-qPCR) and survival outcomes, aligning with VIALE-A findings but with slightly lower OS, possibly reflecting broader real-life heterogeneity [10] . These observations suggest that MRD negativity retains its predictive value beyond controlled trial settings and supports its use as a clinically meaningful endpoint in routine practice. While the prognostic impact of LSC-MRD is well established in intensively treated AML (14–16), its relevance in lower-intensity regimens has been less explored. In the HOVON-SAKK135 trial, LSC persistence under azacitidine monotherapy correlated with adverse outcomes [14–16] . Consistent with these findings, we observed that LSC-MRD negativity after one cycle of AZA/VEN predicted superior OS (31.3 months), and failure to convert to MRD negativity within six cycles was almost invariably associated with relapse. These results align with recent data showing that LSC and LAIP integration refines prognostic stratification independently of ELN risk [7,17] . Together, they suggest that VEN-based regimens may effectively target not only the leukemic bulk but also stem-like compartments, translating into durable remissions. Interestingly, MRD timing of response (early vs. late responders) assessed by LAIP or LSC approaches were not different in terms of OS and RFS predictive value, indicating that the timing of MRD conversion may be less critical than ultimate MRD negativity, particularly given delayed hematologic recovery under AZA/VEN. Similar observation have been made in intensively treated patients [18] . Conversely, persistence of LSC positivity at cycle 1 identified patients at high risk of early relapse. Among NPM1 mut patients, a ≥ 3-log MRD reduction within the first three cycles was more predictive for long-term survival than a binary cutoff, consistent with Othman et al. and previous data on NPM1 MRD as a dynamic marker [11,19] . A key finding is that MRD negativity appeared to mitigate the adverse prognostic impact of intermediate and poor ELN 2024 risk groups [20] . Similar to VIALE-A and Maiti et al. , MRD-negative patients in these risk categories achieved survival outcomes approaching those of favorable-risk patient [9,21] . These results highlight MRD’s potential to refine ELN-based risk stratification in lower-intensity regimens. Neither venetoclax dose nor duration reduction impacted MRD negativity or survival, suggesting that treatment adaptations for cytopenias may not compromise depth of response. This is consistent with retrospective series comparing 7–14–21-day VEN schedules [22–24] . Conversely, post-cycle 1 G-CSF use independently increased MRD negativity probability and improved OS, corroborating post-hoc VIALE-A analyses [25] . These findings support proactive supportive care to preserve treatment intensity and optimize outcomes. Our study has limitations inherent to its retrospective design, including heterogeneity in MRD methodology and timing across centers. Nonetheless, the consistency of results with prospective data supports the robustness of MRD as a surrogate endpoint in real-world AZA/VEN settings. In this large real-world cohort of AML patients treated frontline with AZA/VEN, achieving MRD negativity—by multiparametric flow cytometry or NPM1 RT-qPCR—was strongly associated with improved survival and mitigated the adverse prognostic impact of ELN 2024 risk. Dual LAIP/LSC MRD assessment and dynamic NPM1 log reduction provided additional discriminative power, identifying patients with particularly durable outcomes. These findings establish MRD as a robust and actionable surrogate endpoint in lower-intensity AML therapy, supporting its integration into personalized treatment algorithms, including response-adapted de-escalation or early intensification strategies in future clinical trials. Declarations Competing interests : The authors declare no competing financial interests. Author contribution statement : MH treated patients, performed analysis and wrote paper, AP/DM realized flow cytometry analysis. 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Döhner H, Estey E, Grimwade D, Amadori S, Appelbaum FR, Büchner T, et al. Diagnosis and management of AML in adults: 2017 ELN recommendations from an international expert panel. Blood 2017;129(4):424‑47. Maiti A, DiNardo CD, Wang SA, Jorgensen J, Kadia TM, Daver NG, et al. Prognostic value of measurable residual disease after venetoclax and decitabine in acute myeloid leukemia. Blood Adv 2021;5(7):1876‑83. Karrar O, Abdelmagid M, Rana M, Iftikhar M, McCullough K, Al-Kali A, et al. Venetoclax duration (14 vs. 21 vs. 28 days) in combination with hypomethylating agent in newly diagnosed acute myeloid leukemia: Comparative analysis of response, toxicity, and survival. American Journal of Hematology 2024;99(2):E63‑6. Willekens C, Bazinet A, Chraibi S, Bataller A, Decroocq J, Arani N, et al. Reduced venetoclax exposure to 7 days vs standard exposure with hypomethylating agents in newly diagnosed AML patients. Blood Cancer J 2025;15(1):68. Aiba M, Shigematsu A, Suzuki T, Miyagishima T. Shorter duration of venetoclax administration to 14 days has same efficacy and better safety profile in treatment of acute myeloid leukemia. Ann Hematol 2023;102(3):541‑6. DiNardo CD, Pratz KW, Panayiotidis P, Wei X, Vorobyev V, Illés Á, et al. The impact of post-remission granulocyte colony-stimulating factor use in the phase 3 studies of venetoclax combination treatments in patients with newly diagnosed acute myeloid leukemia. Am J Hematol 2025;100(1):185‑8. Tables Tables 1 to 3 are available in the Supplementary Files section. Additional Declarations There is NO conflict of interest to disclose. Supplementary Files Table1.pptx Table 1: Multivariate analysis evaluating variables influencing LAIP-MRD neg probability Table2.pptx Table 2: Multivariate analysis evaluating variables influencing LSC-MRD neg probability Table3.pptx Table 3: Multivariate analysis for overall survival SupplementalFigure1.pdf Supplemental Figure 1 SupplementalFigure2.pdf Supplemental Figure 2 SupplementalFigure3.pdf Supplemental Figure 3 SupplementalFigure4.pdf Supplemental Figure 4 SupplementalFigure5.pdf Supplemental Figure 5 SupplementalFigure6.pdf Supplemental Figure 6 SupplementalTable1.pptx Supplemental Table 1 SupplementalTable2.pptx Supplemental Table 2 SupplementalTable3.pptx Supplemental Table 3 SupplementalTable4.pptx Supplemental Table 4 SupplementalTable5.pptx Supplemental Table 5 Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: revise 24 Nov, 2025 Review # 3 received at journal 21 Nov, 2025 Review # 2 received at journal 19 Nov, 2025 Review # 1 received at journal 10 Nov, 2025 Reviewer # 3 agreed at journal 31 Oct, 2025 Reviewer # 2 agreed at journal 31 Oct, 2025 Reviewer # 1 agreed at journal 30 Oct, 2025 Reviewers invited by journal 27 Oct, 2025 Editor assigned by journal 27 Oct, 2025 Submission checks completed at journal 27 Oct, 2025 First submitted to journal 25 Oct, 2025 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. 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16:48:30","extension":"html","order_by":28,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":112912,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7959681/v1/d1098c50e5c60d4439357438.html"},{"id":95524173,"identity":"36e11249-23c4-43aa-baf3-3e04941085ba","added_by":"auto","created_at":"2025-11-10 10:02:25","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":329273,"visible":true,"origin":"","legend":"\u003cp\u003eA. LAIP-MRD response rate by the end of cycle 1 and at best LAIP-MRD response; B. Sankey diagram of LAIP\u003cem\u003e-\u003c/em\u003eMRD status at each cycle; C. Overall survival according to LAIP\u003cem\u003e-\u003c/em\u003eMRD at the end of cycle 1 (MRD1); D. Overall survival according best LAIP\u003cem\u003e-\u003c/em\u003eMRD response; E. Overall survival according to LAIP\u003cem\u003e-\u003c/em\u003eMRD timing of responses defined as early (MRD1\u003csup\u003eneg\u003c/sup\u003e and MRD2\u003csup\u003e neg\u003c/sup\u003e), late (MRD1\u003csup\u003epos\u003c/sup\u003e and MRD2\u003csup\u003e neg\u003c/sup\u003e), and poor (MRD1\u003csup\u003epos/neg\u003c/sup\u003e and MRD2\u003csup\u003e pos\u003c/sup\u003e) MRD responses in patients evaluated at two different time points during 6 first cycles.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-7959681/v1/5be51726560c0df3a17cd425.png"},{"id":95321361,"identity":"3401692a-9982-4b8e-8438-add4ae52b7ff","added_by":"auto","created_at":"2025-11-06 16:48:29","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":186180,"visible":true,"origin":"","legend":"\u003cp\u003eA. LSC-MRD response rate by the end of cycle 1 and at best LSC-MRD response; B. Sankey diagram of LSC\u003cem\u003e-\u003c/em\u003eMRD status at each cycle; C. Best LSC-MRD response according ELN 2024 risk classification; D. LSC and LAIP MRD kinetics during 6 fist AZA/VEN cycles; E. Overall survival according LSC\u003cem\u003e-\u003c/em\u003eMRD at the end of cycle 1 (MRD1); F. Overall survival according best LSC\u003cem\u003e-\u003c/em\u003eMRD response; G. Overall survival according LSC\u003cem\u003e-\u003c/em\u003eMRD timing ofresponses defined as early (MRD1\u003csup\u003eneg\u003c/sup\u003e and MRD2\u003csup\u003e neg\u003c/sup\u003e), late (MRD1\u003csup\u003epos\u003c/sup\u003e and MRD2\u003csup\u003e neg\u003c/sup\u003e), and poor (MRD1\u003csup\u003epos/neg\u003c/sup\u003e and MRD2\u003csup\u003e pos\u003c/sup\u003e) MRD responses in patients evaluated at two different time points during 6 first cycles.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-7959681/v1/f732285531c6da83a2da9ca3.png"},{"id":95523546,"identity":"f7e99213-258f-4bc8-993c-ef5ebc2b9116","added_by":"auto","created_at":"2025-11-10 09:57:54","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":48024,"visible":true,"origin":"","legend":"\u003cp\u003eOverall survival and B. Cumulative incidence of relapse according to best dual LAIP/LSC MRD response at any time during 6 first AZA/VEN cycles\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-7959681/v1/62541f6b9b36aaca05c39df0.png"},{"id":95523493,"identity":"a73c72a9-56d7-4e83-91de-95ce506c103d","added_by":"auto","created_at":"2025-11-10 09:56:57","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":172586,"visible":true,"origin":"","legend":"\u003cp\u003eA. \u003cem\u003eNPM1\u003c/em\u003e-MRD response rate by the end of cycle 1 and at best MRD response in \u003cem\u003eNPM1\u003c/em\u003e\u003csup\u003e\u003cem\u003emut\u003c/em\u003e\u003c/sup\u003e patients; B. Sankey diagram of \u003cem\u003eNPM1\u003c/em\u003e RT-qPCR MRD status at each cycle in \u003cem\u003eNPM1\u003c/em\u003e\u003csup\u003e\u003cem\u003emut\u003c/em\u003e\u003c/sup\u003e patients; C. Overall survival of \u003cem\u003eNPM1\u003c/em\u003e\u003csup\u003e\u003cem\u003emut\u003c/em\u003e\u003c/sup\u003e patients according best \u003cem\u003eNPM1\u003c/em\u003e RT-qPCR MRD response; D. LSC, LAIP (by MFC) and \u003cem\u003eNPM1\u003c/em\u003e RT-qPCR MRD kinetics during 6 fist AZA/VEN cycles in \u003cem\u003eNPM1\u003c/em\u003e\u003csup\u003e\u003cem\u003emut\u003c/em\u003e\u003c/sup\u003e patients; E. Overall survival of \u003cem\u003eNPM1\u003c/em\u003e\u003csup\u003e\u003cem\u003emut\u003c/em\u003e\u003c/sup\u003e patients according to 3 log reduction status of \u003cem\u003eNPM1/ABL1 transcript ratio\u003c/em\u003e compared to baseline.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-7959681/v1/fd3f686d9b77b90181d0bc4d.png"},{"id":95524260,"identity":"5e1aa6df-6814-41fc-a0e0-e57540b1d091","added_by":"auto","created_at":"2025-11-10 10:02:33","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":38595,"visible":true,"origin":"","legend":"\u003cp\u003eA. Overall survival according to ELN 2024 risk classification; B. Overall survival according to ELN 2024 risk classification and best LAIP/\u003cem\u003eNPM1\u003c/em\u003e-MRD response during 6 fist cycles.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-7959681/v1/5d1e445e2384af0df1c8ab27.png"},{"id":95654439,"identity":"52c410d4-9289-4838-be2b-b0d05722576d","added_by":"auto","created_at":"2025-11-11 16:11:58","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1419929,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7959681/v1/153c07a7-871d-4d38-b1ce-8b3c62fae8fc.pdf"},{"id":95321360,"identity":"0fd77d96-89e4-42a5-94f3-8a864354531d","added_by":"auto","created_at":"2025-11-06 16:48:29","extension":"pptx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":39499,"visible":true,"origin":"","legend":"\u003cp\u003eTable 1: Multivariate analysis evaluating variables influencing LAIP-MRD\u003csup\u003eneg\u003c/sup\u003e probability\u003c/p\u003e","description":"","filename":"Table1.pptx","url":"https://assets-eu.researchsquare.com/files/rs-7959681/v1/ccfd6226e517ebd270326b84.pptx"},{"id":95321364,"identity":"8a8df782-905a-456c-b237-4a2c0967ec0b","added_by":"auto","created_at":"2025-11-06 16:48:29","extension":"pptx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":39747,"visible":true,"origin":"","legend":"\u003cp\u003eTable 2: Multivariate analysis evaluating variables influencing LSC-MRD\u003csup\u003eneg\u003c/sup\u003e probability\u003c/p\u003e","description":"","filename":"Table2.pptx","url":"https://assets-eu.researchsquare.com/files/rs-7959681/v1/cea848182e89c72740b9311d.pptx"},{"id":95524250,"identity":"e539900a-5991-4cd9-b622-78ba1657d124","added_by":"auto","created_at":"2025-11-10 10:02:33","extension":"pptx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":40660,"visible":true,"origin":"","legend":"\u003cp\u003eTable 3: Multivariate analysis for overall survival\u003c/p\u003e","description":"","filename":"Table3.pptx","url":"https://assets-eu.researchsquare.com/files/rs-7959681/v1/6f8b706676492ea069909fe4.pptx"},{"id":95524344,"identity":"1474a999-ffad-4488-a2c8-ef26f5145c94","added_by":"auto","created_at":"2025-11-10 10:02:38","extension":"pdf","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":102261,"visible":true,"origin":"","legend":"Supplemental Figure 1","description":"","filename":"SupplementalFigure1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7959681/v1/c7729187ffe8dcd5a4f40a57.pdf"},{"id":95523965,"identity":"773e1c49-a097-49da-b181-102a1a9e09e3","added_by":"auto","created_at":"2025-11-10 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09:59:44","extension":"pdf","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":132313,"visible":true,"origin":"","legend":"Supplemental Figure 6","description":"","filename":"SupplementalFigure6.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7959681/v1/9f1d9553a0a5ecad925c4e4f.pdf"},{"id":95523519,"identity":"617bd0c4-8f20-46a3-ad21-17711f9f7fc3","added_by":"auto","created_at":"2025-11-10 09:57:30","extension":"pptx","order_by":10,"title":"","display":"","copyAsset":false,"role":"supplement","size":41527,"visible":true,"origin":"","legend":"Supplemental Table 1","description":"","filename":"SupplementalTable1.pptx","url":"https://assets-eu.researchsquare.com/files/rs-7959681/v1/fe6db47ae03d5f8eb5be323f.pptx"},{"id":95321381,"identity":"6fc16bd5-9bd0-4626-a1ab-ff211644c6e3","added_by":"auto","created_at":"2025-11-06 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16:48:29","extension":"pptx","order_by":13,"title":"","display":"","copyAsset":false,"role":"supplement","size":52395,"visible":true,"origin":"","legend":"Supplemental Table 4","description":"","filename":"SupplementalTable4.pptx","url":"https://assets-eu.researchsquare.com/files/rs-7959681/v1/3ac41957d0e3014856405c90.pptx"},{"id":95321389,"identity":"5489c78a-16d4-4355-8a20-ff13b15384c1","added_by":"auto","created_at":"2025-11-06 16:48:29","extension":"pptx","order_by":14,"title":"","display":"","copyAsset":false,"role":"supplement","size":47487,"visible":true,"origin":"","legend":"Supplemental Table 5","description":"","filename":"SupplementalTable5.pptx","url":"https://assets-eu.researchsquare.com/files/rs-7959681/v1/82297095edf0796aaa165dd5.pptx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e conflict of interest to disclose.","formattedTitle":"Prognostic impact of measurable residual disease in AML patients treated frontline with azacitidine and venetoclax: results from the French VENAURA registry","fulltext":[{"header":"Introduction","content":"\u003cp\u003eIn patients treated intensively for acute myeloid leukemia (AML), measurable residual disease (MRD) has become a critical standardized endpoint which is highly predictive of relapse-free survival (RFS) and overall survival (OS)\u003csup\u003e[1–4]\u003c/sup\u003e. However, MRD predictive value at specific time points during intensive chemotherapy (IC) courses in AML has been mostly evaluated by quantitative polymerase chain reaction (RT-qPCR) for \u003cem\u003eNPM1\u003csup\u003emut\u003c/sup\u003e\u003c/em\u003e, \u003cem\u003eCBF\u003c/em\u003e-rearranged and \u003cem\u003ePML::RARA\u003c/em\u003e AML\u003csup\u003e[1,3,5]\u003c/sup\u003e. Yet, only 30–35% of patients present molecular abnormalities that can be assessed by RT-qPCR, and even less in elderly patients. Multiparametric flow cytometry (MFC) MRD is applicable to a majority of patients\u0026nbsp;after treatment-induced morphologic remission, even for those who do not harbor an appropriate molecular target for RT-qPCR. Tremendous efforts have been made to standardize MFC-MRD procedures and define specific thresholds according to DfN (Different from normal)/LAIP (leukemia associated immunophenotype) and more recently LSC (Leukemic Stem Cell) approaches\u003csup\u003e[6]\u003c/sup\u003e. In this context, LSC-MRD by MFC appeared to be highly predictive for survival \u0026nbsp; and relapse risk in a large prospective cohort of patients treated with intensive chemotherapy (IC)\u003csup\u003e[7]\u003c/sup\u003e. \u0026nbsp;While integrated into response assessment in pediatric AML, MFC-MRD in adult AML is not yet used as a preemptive factor for risk assessment, therapeutic intervention and/or hematopoietic stem cell transplantation allocation for patients treated with IC.\u003c/p\u003e\n\u003cp\u003eFor patients unfit for IC, low intensity therapy based on azacitidine are usually offered. A retrospective study reported that in patients age \u0026gt; 60 years and treated with hypomethylating agents, the cumulative incidence of relapse was shown lower among patients who had achieved a MRD-negative (MRD\u003csup\u003eneg\u003c/sup\u003e ) response, but no relationship between MRD and overall survival (OS) or relapse free survival (RFS) was demonstrated\u003csup\u003e[8]\u003c/sup\u003e. More recently, azacitidine and venetoclax (AZA/VEN) combination regimen\u0026nbsp;have\u0026nbsp;emerged as a new standard of care in frontline unfit AML patients\u003csup\u003e[9]\u003c/sup\u003e. In the VIALE-A prospective trial, patients treated with AZA/VEN were evaluated for MRD by MFC at the end of cycle 1, and every three cycles thereafter. Median\u0026nbsp;OS was not reached\u0026nbsp;in\u0026nbsp;patients\u0026nbsp;reaching\u0026nbsp;MRD\u003csup\u003eneg\u003c/sup\u003e at any time with a predicted 12 months OS of 94%\u003csup\u003e[10]\u003c/sup\u003e. Similarly, Othman et al. reported on a large retrospective cohort of \u003cem\u003eNPM1\u003c/em\u003e\u003csup\u003emut\u003c/sup\u003e patients treated with VEN based regimens that NPM1-MRD\u003csup\u003eneg\u003c/sup\u003e was associate with \u0026nbsp;a favorable outcome\u003csup\u003e[11]\u003c/sup\u003e. Despite these advances, MRD negativity either by MFC or RT-qPCR (i.e. \u003cem\u003eNPM1\u003c/em\u003e\u003csup\u003emut\u003c/sup\u003e) determinants and their impact on survival outside clinical trial remains limited in AZA/VEN treated patients. Identifying patients with favorable outcome might be the corner stone for future de-escalation strategy.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe aimed in this retrospective study to evaluate the predictive value of MRD negativity by MFC or \u003cem\u003eNPM1\u003c/em\u003e RT-qPCR and its kinetics on survival in AML patients treated upfront with AZA/VEN in real life settings.\u0026nbsp;\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e1. \u003cu\u003eStudy design\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eVENAURA is an observational, multicenter registry collecting retrospective data on AZA/VEN-treated AML patients from 12 centers in the French Auvergne-Rhône-Alpes (AURA) region between January 2019 and February 2024 (IRB 00013204).\u003c/p\u003e\n\u003cp\u003eInclusion criteria were patients with AML according to the WHO 2022 classification (including low-blast AML/MDS) receiving AZA/VEN as frontline therapy, with at least one MRD assessment during the first six cycles. AZA/VEN response and MRD assessments were evaluated as described below.\u003c/p\u003e\n\u003cp\u003eComposite complete remission (CRc) was defined as in the VIALE-A trial. Regarding MFC-MRD, its assessment was based on the LAIP approach according to the European LeukemiaNet (ELN) recommendations (bulk lysis and at least 500,000 recorded events to achieve a sensitivity threshold of at least 10⁻³ [0.1%]). MFC-MRD was performed on bone marrow samples using an 8-color panel and considered positive when detectable above the 0.1% threshold for LAIP and 0.01% for LSC assays\u003csup\u003e[6,12]\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eA “backbone” of CD34/CD38/CD45/CD117 was used in both tubes, supplemented by CD7, CD56, CD13, CD33, HLA-DR, and CD19 for LAIP assessment, and by CD90 (Thy-1), Mix (CD97/CLL1/TIM3), CD45RA, and CD123 for LSC analysis\u003csup\u003e[13]\u003c/sup\u003e. LSC\u003csup\u003elow\u003c/sup\u003e was defined as an LSC population \u0026lt;1% at baseline, as previously reported\u003csup\u003e[7]\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNPM1\u003c/em\u003e RT-qPCR MRD was performed as previously described\u003csup\u003e[3]\u003c/sup\u003e. MRD negativity (MRD\u003csup\u003eneg\u003c/sup\u003e) was defined as ≤10⁻⁵ for \u003cem\u003eNPM1\u003c/em\u003e by RT-qPCR on peripheral blood (or bone marrow when available). For \u003cem\u003eNPM1\u003c/em\u003e\u003csup\u003emut\u003c/sup\u003e patients evaluated by both flow cytometry and RT-qPCR, those negative by flow but positive by RT-qPCR were considered MRD\u003csup\u003epos\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eFor patients evaluated only by MFC, an early MRD response was defined as negativity on the first MRD assessment (MRD1) confirmed at the second evaluation (MRD2). Late responders were defined by conversion from MRD1 positivity to MRD2 negativity between two time points. Poor MRD responders were defined as persistent MRD positivity at both MRD1 and MRD2, or loss of MRD1 negativity at MRD2.\u003c/p\u003e\n\u003cp\u003eFor Sankey diagrams, patients were censored at the time of the last received cycle, allogeneic hematopoietic stem cell transplantation, or toxic death. If patients were not re-evaluated at subsequent cycles, their MRD response for the next cycle was based on the last available MRD evaluation.\u003c/p\u003e\n\u003cp\u003e2. \u003cu\u003eStatistical analysis\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eFor comparisons between patient characteristics, Mann–Whitney and Kruskal–Wallis tests were used for continuous quantitative variables, and the Chi-square test for categorical variables. Probabilities of OS were estimated using the Kaplan–Meier method.\u003c/p\u003e\n\u003cp\u003eTo study the cumulative incidence of relapse, a cumulative incidence model was applied. Univariate analyses were performed using the log-rank test for OS and Gray’s method for cumulative incidence outcomes. Multivariate regression was carried out using a Cox proportional hazards model, including all variables significant in univariate analyses.\u003c/p\u003e\n\u003cp\u003eStatistical analyses were performed using GraphPad Prism software version 8.0.1 for Windows (GraphPad Software, San Diego, California, USA, www.graphpad.com) and R software version 4.1.1 (R Core Team, 2021. \u003cem\u003eR: A language and environment for statistical computing.\u003c/em\u003e R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e1. \u003cu\u003ePatient characteristics\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eOf the 438 frontline patients included in the registry, 220 achieved CRc and had at least one MRD assessment by MFC or RT-qPCR (NPM1) during follow-up (Supplemental Figure 1). Patients’ characteristics are summarized in Supplemental Table 1. Median age at diagnosis was 74.4 years (range: 31–88), and 15.4% of patients were aged over 80.\u003c/p\u003e\n\u003cp\u003eA prior myeloid neoplasm was reported in 32.3% of cases, most frequently myelodysplastic syndromes (20%), followed by chronic myelomonocytic leukemia (8.6%) and myeloproliferative neoplasms (3.6%). Therapy-related AML (t-AML) was reported in 7.2% (16/220) of cases.\u003c/p\u003e\n\u003cp\u003eMorphologically, 29.1% of patients had cytological myelodysplasia-related changes, and 25.4% had a monocytic bias (defined as FAB M4/5). Extramedullary disease was reported in 4.5% (10/220) of patients (five leukemia cutis, four central nervous system infiltrations, and one isolated myeloid sarcoma).\u003c/p\u003e\n\u003cp\u003eCytogenetic and molecular risk according to the 2024 ELN classification was available for 165/220 patients: 52.1% were favorable, 27.3% intermediate, and 20.6% adverse risk.\u003c/p\u003e\n\u003cp\u003eAfter a median follow-up of 12.8 months, median OS of patients reaching CRc at any time during the first six cycles and evaluated for MRD was 17.8 months.\u003c/p\u003e\n\u003cp\u003e2. \u003cu\u003eLAIP MRD response determinants and impact on survival\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eBone marrow LAIP-MRD assessment was performed at least once during the first six AZA/VEN cycles in 184/220 patients (83.6%), with a median time to first LAIP-MRD assessment (LAIP-MRD1) of one cycle (range: 1–6). At the end of cycle 1, 75.5% (139/184) were evaluated for LAIP-MRD, and 51.9% were LAIP-MRD1\u003csup\u003eneg\u003c/sup\u003e. LAIP-MRD1\u003csup\u003epos\u003c/sup\u003e patients evaluated a second time during the first six cycles (n=66) converted to MRD2\u003csup\u003eneg\u003c/sup\u003e in 45.4% (30/66) of cases by the end of cycle 6. Conversely, 16.6% of LAIP-MRD1\u003csup\u003e\u0026nbsp;neg\u003c/sup\u003e patients lost their MRD response during the first six cycles. The cumulative LAIP-MRD\u003csup\u003e\u0026nbsp;neg\u003c/sup\u003e rate was 61.7% (Figure 1A).\u003c/p\u003e\n\u003cp\u003eOverall, 27% of patients relapsed by the end of the first six cycles, mostly from the LAIP-MRD\u003csup\u003epos\u0026nbsp;\u003c/sup\u003epopulation (Figure 1B), while the LAIP-MRD\u003csup\u003eneg\u003c/sup\u003e rate remained stable. A prior history of MPN or MDS (HR=3.1, p=0.008), NPM1\u003csup\u003emut\u0026nbsp;\u003c/sup\u003e(HR=0.1, p=0.009), granulocyte colony-stimulating factor (G-CSF) use at any time (HR=0.35, p=0.031), and complex karyotype (HR=2.32, p=0.025) were significantly associated with LAIP-MRD\u003csup\u003eneg\u003c/sup\u003e\u0026nbsp; probability, while the ELN 2024 classification or single mutations (i.e., \u003cem\u003eIDH\u003csup\u003emut\u003c/sup\u003e, TP53\u003csup\u003emut\u003c/sup\u003e\u003c/em\u003e) were not (Supplemental Table 2).\u003c/p\u003e\n\u003cp\u003eVenetoclax dose or exposure duration during cycle 1 and subsequent cycles did not influence MRD response probability. Moreover, VEN dose reduction after cycle 1 did not affect relapse probability in either the LAIP-MRD1\u003csup\u003eneg\u003c/sup\u003e or MRD1\u003csup\u003epos\u003c/sup\u003e populations. In patients who received G-CSF after CRc, the overall LAIP-MRD\u003csup\u003eneg\u0026nbsp;\u003c/sup\u003erate was 74.6% compared to 51.9% in those who did not (p=0.002). After logistic regression, only NPM1mut, prior history of MPN/MDS, and G-CSF use at any time were independently associated with LAIP-MRD\u003csup\u003eneg\u003c/sup\u003e probability (Table 1).\u003c/p\u003e\n\u003cp\u003eWhen evaluated at the end of cycle 1, LAIP-MRD1\u003csup\u003eneg\u003c/sup\u003e was associated with improved OS compared to LAIP-MRD1\u003csup\u003epos\u003c/sup\u003e (31.2 vs 17.8 months, p=0.044) (Figure 1C). However, LAIP-MRD1 was not predictive of relapse (Supplemental Figure 2A), and different LAIP-MRD thresholds at the end of cycle 1 were not predictive of relapse (Supplemental Figure 3A). Median OS for patients who achieved best LAIP-MRD\u003csup\u003eneg\u0026nbsp;\u003c/sup\u003eat any time during the first six AZA/VEN cycles was 31.3 months, with an estimated 2-year OS of 58.9%. Conversely, median OS was significantly lower (15.7 months) in LAIP-MRDpos patients (HR=0.43, p\u0026lt;0.001) (Figure 1D).\u003c/p\u003e\n\u003cp\u003eAt 24 months, patients with best LAIP-MRD\u003csup\u003epos\u003c/sup\u003e status had a higher CIR of 70.9% compared to 29.1% in those with best LAIP-MRD\u003csup\u003eneg\u003c/sup\u003e (Supplemental Figure 2B). Deeper LAIP-MRD responses at best MRD assessment were predictive of relapse. The 12-month CIR was 28.3%, 38%, 67.1%, and 70% for negative, 0.1–0.9%, 1–4.9%, and ≥5% LAIP-MRD, respectively (Supplemental Figure 3B).\u003c/p\u003e\n\u003cp\u003eRegarding timing of MRD evaluation, among patients evaluated at two time points (LAIP-MRD1 and LAIP-MRD2) during the first six cycles, early LAIP-MRD responders had similar outcomes to late responders (p=0.32). In contrast, poor LAIP-MRD response was associated with lower OS (p\u0026lt;0.001) (Figure 1E).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.\u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/strong\u003e\u003cu\u003eLSC MRD response determinants and impact on survival\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eAmong the 175 patients assessed for LAIP-MRD by MFC, 61.1% (126/175) were also evaluated using the LSC approach at diagnosis. Median LSC levels at diagnosis were 4% (95% CI: 2–6%); 42% (53/126) and 58% (73/126) were LSC\u003csup\u003elow\u003c/sup\u003e and LSC\u003csup\u003ehigh\u003c/sup\u003e, respectively. Patients with LSC\u003csup\u003elow\u003c/sup\u003e populations at diagnosis were more frequently favorable according to ELN 2024 and enriched in NPM1mut (Supplemental Table 3).\u003c/p\u003e\n\u003cp\u003eOf the 126 patients evaluated at baseline, 107 were subsequently followed for MRD. The cumulative LSC-MRD\u003csup\u003eneg\u003c/sup\u003e rate during the first six cycles was 67.4% (Figure 2A). Among patients evaluated at two time points during these cycles, conversion from LSC-MRD1\u003csup\u003epos\u0026nbsp;\u003c/sup\u003eto LSC-MRD2\u003csup\u003eneg\u003c/sup\u003e occurred in 13/27 (48.1%). By the end of cycle 6, 77.8% (21/27) of LSC-MRD\u003csup\u003epos\u003c/sup\u003e patients who did not convert to LSC-MRD\u003csup\u003eneg\u003c/sup\u003e relapsed (Figure 2B). Conversely, relapse within the first six cycles occurred in only 7.1% (4/56) of patients who achieved LSC-MRD\u003csup\u003eneg\u003c/sup\u003e (Figure 2B).\u003c/p\u003e\n\u003cp\u003eThe cumulative LSC-MRD\u003csup\u003eneg\u003c/sup\u003e rate was significantly lower in patients with adverse ELN risk (40%) compared to favorable (73%) and intermediate (67%) groups (Figure 2C). Monocytic bias at diagnosis (OR=0.2, p=0.045), complex karyotype (OR=4.06, p=0.018), and adverse ELN 2024 classification were significantly associated with lower LSC-MRD\u003csup\u003eneg\u003c/sup\u003e probability (Supplemental Table 4). In the multivariate model, only prior MDS/MPN history was independently associated with LSC-MRD\u003csup\u003eneg\u003c/sup\u003e probability (Table 2), while G-CSF use and ELN classification were not.\u003c/p\u003e\n\u003cp\u003eWe then compared LAIP and LSC kinetics across cycles. Using a two-way ANOVA mixed-effects model assuming sphericity, MRD technique had a significant effect on MRD values (F(1,334)=6.84, p=0.0093), indicating that the predicted mean LAIP-MRD (M=3.46) was consistently higher than LSC-MRD (M=0.86; difference=2.60, 95% CI [0.64, 4.55]). However, the kinetic decay profiles of LAIP and LSC MRD were similar across groups (F(5,277)=0.58, p=0.71) (Figure 2D).\u003c/p\u003e\n\u003cp\u003eWhen considering LSC levels at diagnosis, patients with LSC\u003csup\u003elow\u003c/sup\u003e had superior median OS compared to LSC\u003csup\u003ehigh\u003c/sup\u003e, but this did not reach statistical significance (NR vs 14.1 months, p=0.071) (Supplemental Figure 3). At the end of cycle 1, LSC-MRD1\u003csup\u003eneg\u003c/sup\u003e status was associated with a favorable outcome compared to LSC-MRD1\u003csup\u003epos\u003c/sup\u003e (31.3 vs 8.2 months, p=0.044) (Figure 2E). Unlike LAIP-MRD, LSC-MRD1 was predictive of relapse (Supplemental Figure 2C). Median OS for patients who achieved LSC-MRD\u003csup\u003eneg\u003c/sup\u003e at any time during the first six AZA/VEN cycles was 31.3 months, with a 2-year OS of 56.4% (Figure 2F). As for LAIP-MRD, best LSC-MRD\u003csup\u003epos\u003c/sup\u003e status was associated with poor outcomes, mainly due to a 24-month CIR of 83.3% compared to 45.1% in best LSC-MRD\u003csup\u003eneg\u003c/sup\u003e (Supplemental Figure 2D). Deeper LSC-MRD thresholds at cycle 1 or best MRD response were significantly associated with relapse, as any MRD\u003csup\u003epos\u003c/sup\u003e level correlated with a higher relapse risk (Supplemental Figures 3C–D). When comparing timing of MRD evaluation, among patients assessed at two time points (LSC-MRD1 and LSC-MRD2), late MRD responders had outcomes similar to poor MRD responders (Figure 2G).\u003c/p\u003e\n\u003cp\u003eFinally, as LSC and LAIP-MRD by MFC are complementary approaches to evaluate residual AML cells, both were combined to assess their joint impact on survival. Patients achieving dual LAIP-MRD\u003csup\u003eneg\u003c/sup\u003e/LSC-MRD\u003csup\u003eneg\u003c/sup\u003e exhibited very favorable outcomes, with median OS not reached and a 4-year estimated OS of 57%. Conversely, all other MRD response patterns were associated with significantly shorter survival (Figures 3A–B). Using Harrell’s C-index, dual LAIP-MRD\u003csup\u003eneg\u003c/sup\u003e/LSC-MRD\u003csup\u003eneg\u003c/sup\u003e (AUC=0.83) demonstrated superior prognostic discrimination compared to LAIP-MRD\u003csup\u003eneg\u003c/sup\u003e (AUC=0.7) or LSC-MRD\u003csup\u003eneg\u003c/sup\u003e (AUC=0.78) alone.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.\u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/strong\u003e\u003cu\u003eNPM1 MRD response rate and impact on survival\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eA total of 56 patients with NPM1mut were evaluable by RT-qPCR. The NPM1 mutational burden showed a median mutated allelic fraction at diagnosis of 524% (range: 51–3452). By the end of cycle 1, only 7% of NPM1\u003csup\u003emut\u003c/sup\u003e patients were NPM1-MRD\u003csup\u003eneg\u0026nbsp;\u003c/sup\u003e(Figure 4A). Overall, cumulative NPM1-MRD\u003csup\u003eneg\u003c/sup\u003e at any time was 62.5%, with a median time to MRD\u003csup\u003eneg\u003c/sup\u003e of six cycles (range: 1–6). Relapse rate within the first six cycles was low (10.7%) and occurred only in patients who did not achieve MRD\u003csup\u003eneg\u003c/sup\u003e by the end of cycle 6 (Figure 4B). No variables significantly influenced the probability of reaching NPM1-MRD\u003csup\u003eneg\u003c/sup\u003e. Achieving NPM1-MRD\u003csup\u003eneg\u003c/sup\u003e at any time during the first six AZA/VEN cycles was associated with median OS not reached and an estimated 4-year OS of 69.7%, whereas median OS in NPM1-MRD\u003csup\u003epos\u003c/sup\u003e patients was significantly lower (10.8 months, p\u0026lt;0.001) (Figure 4C).\u003c/p\u003e\n\u003cp\u003eWe then compared NPM1 MRD kinetics to LAIP- and LSC-based approaches. Compared to LAIP-MRD, neither cycles (F(1.182,26.00)=1.22, p=0.29), MRD type (F(1,74)=1.74, p=0.19), nor their interaction (F(5,110)=1.20, p=0.32) had a significant effect on MRD kinetics, indicating statistically indistinguishable kinetic profiles between NPM1-MRD and LAIP-MRD. Similar results were observed with LSC-MRD (Figure 4D).\u003c/p\u003e\n\u003cp\u003eWhile discrepancies between NPM1-MRD and LAIP-MRD were infrequent (Supplemental Figure 5), the depth of molecular response provided additional prognostic information. As NPM1 MRD negativity was typically achieved later and at different thresholds compared to MFC MRD, a ≥3-log reduction (3-logRED) in NPM1 transcript levels by the end of cycle 3 was strongly associated with a favorable prognosis compared to those not reaching this response (Figure 4E). Using Harrell’s C-index, \u0026gt;3-logRED NPM1 (AUC=0.85) demonstrated superior prognostic discrimination compared to MRD\u003csup\u003eneg\u003c/sup\u003e status within the first six AZA/VEN cycles (AUC=0.8).\u003c/p\u003e\n\u003cp\u003e5. \u003cu\u003eImpact of MRD on survival according to ELN 2024 risk groups\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eTo further evaluate the overall impact of MRD response during the first six AZA/VEN cycles on outcome according to the ELN 2024 classification, we analyzed patients evaluated for both LAIP and NPM1-MRD. For NPM1\u003csup\u003emut\u003c/sup\u003e patients, MRD status (NEG vs POS) was based on RT-qPCR rather than LAIP/LSC-MRD.\u003c/p\u003e\n\u003cp\u003eAccording to ELN 2024, median OS was 22.9, 13.8, and 10.9 months in favorable, intermediate, and adverse risk groups, respectively (Figure 5A). As there was no significant difference in outcome, intermediate and adverse groups were merged (INT/ADV) for further analysis.\u003c/p\u003e\n\u003cp\u003eIn the ELN favorable (FAV) group, median OS was not reached in MRD\u003csup\u003eneg\u003c/sup\u003e patients versus 16.7 months in MRD\u003csup\u003epos\u003c/sup\u003e (p=0.002) (Figure 5B). Similarly, in the ELN INT/ADV group, median OS was 31.3 versus 9.3 months in MRD\u003csup\u003eneg\u003c/sup\u003e and MRD\u003csup\u003epos\u003c/sup\u003e, respectively (p=0.008) (Figure 5B). MRD response abrogated the negative impact of ELN classification, as no significant differences were observed between FAV and INT/ADV MRD\u003csup\u003eneg\u003c/sup\u003e patients (HR=0.65, p=0.15), nor between FAV and INT/ADV MRD\u003csup\u003epos\u003c/sup\u003e patients (HR=1.77, p=0.22) (Figure 5B). When using LSC (and NPM1 in evaluable patients), results were similar, with no significant difference between FAV and INT/ADV MRD\u003csup\u003eneg\u003c/sup\u003e patients (HR=0.54, p=0.09) (Supplemental Figure 6).\u003c/p\u003e\n\u003cp\u003eUnivariate analyses of variables influencing OS are summarized in Supplemental Table 5. After logistic regression, ANC at diagnosis (continuous, HR=1.04, p=0.001), diploid karyotype (yes vs no, HR=0.58, p=0.03), G-CSF use after cycle 1 (yes vs no, HR=0.6, p=0.03), and best MRD response (POS vs NEG, HR=2.44, p\u0026lt;0.001) were independently associated with OS, while HSCT and ELN 2024 classification were not (Table 3).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn intensively treated AML, achieving deep MRD-negative complete remission is a well-established prognostic factor associated with prolonged OS and RFS compared with morphological remission alone. In older or unfit patients, azacitidine combined with venetoclax (AZA/VEN) not only improves complete remission rates but also increases the depth of response compared with azacitidine monotherapy\u003csup\u003e[9]\u003c/sup\u003e. In VIALE-A, 32% of patients in CRc under azacitidine alone achieved MRD negativity (\u0026lt; 10⁻³ by DfN/LAIP flow cytometry), but MRD status had limited evaluability due to small sample size. Similarly, a retrospective analysis of patients \u0026gt; 60 years treated with hypomethylating agents alone found no significant correlation between MRD negativity and OS\u003csup\u003e[8]\u003c/sup\u003e. In contrast, AZA/VEN-treated patients achieving MRD-negative CRc showed longer remission durations and improved survival\u003csup\u003e[10]\u003c/sup\u003e. However, limited real-world data exist on the clinical impact of MRD and its kinetics in treatment-naive, lower-intensity, VEN-based therapy.\u003c/p\u003e\n\u003cp\u003eOur study, one of the largest real-world series to date, confirms the strong association between MRD negativity (by MFC or NPM1 RT-qPCR) and survival outcomes, aligning with VIALE-A findings but with slightly lower OS, possibly reflecting broader real-life heterogeneity\u003csup\u003e[10]\u003c/sup\u003e. These observations suggest that MRD negativity retains its predictive value beyond controlled trial settings and supports its use as a clinically meaningful endpoint in routine practice.\u003c/p\u003e\n\u003cp\u003eWhile the prognostic impact of LSC-MRD is well established in intensively treated AML (14–16), its relevance in lower-intensity regimens has been less explored. In the HOVON-SAKK135 trial, LSC persistence under azacitidine monotherapy correlated with adverse outcomes\u003csup\u003e[14–16]\u003c/sup\u003e. Consistent with these findings, we observed that LSC-MRD negativity after one cycle of AZA/VEN predicted superior OS (31.3 months), and failure to convert to MRD negativity within six cycles was almost invariably associated with relapse. These results align with recent data showing that LSC and LAIP integration refines prognostic stratification independently of ELN risk\u003csup\u003e[7,17]\u003c/sup\u003e. Together, they suggest that VEN-based regimens may effectively target not only the leukemic bulk but also stem-like compartments, translating into durable remissions.\u003c/p\u003e\n\u003cp\u003eInterestingly, MRD timing of response (early vs. late responders) assessed by LAIP or LSC approaches were not different in terms of OS and RFS predictive value, indicating that the timing of MRD conversion may be less critical than ultimate MRD negativity, particularly given delayed hematologic recovery under AZA/VEN. Similar observation have been made in intensively treated patients\u003csup\u003e[18]\u003c/sup\u003e. Conversely, persistence of LSC positivity at cycle 1 identified patients at high risk of early relapse. Among NPM1\u003csup\u003emut\u003c/sup\u003e patients, a ≥ 3-log MRD reduction within the first three cycles was more predictive for long-term survival than a binary cutoff, consistent with Othman et al. \u0026nbsp;and previous data on NPM1 MRD as a dynamic marker\u003csup\u003e[11,19]\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eA key finding is that MRD negativity appeared to mitigate the adverse prognostic impact of intermediate and poor ELN 2024 risk groups\u003csup\u003e[20]\u003c/sup\u003e. Similar to VIALE-A \u0026nbsp;and Maiti et al. , MRD-negative patients in these risk categories achieved survival outcomes approaching those of favorable-risk patient\u003csup\u003e[9,21]\u003c/sup\u003e. These results highlight MRD’s potential to refine ELN-based risk stratification in lower-intensity regimens.\u003c/p\u003e\n\u003cp\u003eNeither venetoclax dose nor duration reduction impacted MRD negativity or survival, suggesting that treatment adaptations for cytopenias may not compromise depth of response. This is consistent with retrospective series comparing 7–14–21-day VEN schedules\u003csup\u003e[22–24]\u003c/sup\u003e. Conversely, post-cycle 1 G-CSF use independently increased MRD negativity probability and improved OS, corroborating post-hoc VIALE-A analyses\u003csup\u003e[25]\u003c/sup\u003e. These findings support proactive supportive care to preserve treatment intensity and optimize outcomes.\u003c/p\u003e\n\u003cp\u003eOur study has limitations inherent to its retrospective design, including heterogeneity in MRD methodology and timing across centers. Nonetheless, the consistency of results with prospective data supports the robustness of MRD as a surrogate endpoint in real-world AZA/VEN settings.\u003c/p\u003e\n\u003cp\u003eIn this large real-world cohort of AML patients treated frontline with AZA/VEN, achieving MRD negativity—by multiparametric flow cytometry or NPM1 RT-qPCR—was strongly associated with improved survival and mitigated the adverse prognostic impact of ELN 2024 risk. Dual LAIP/LSC MRD assessment and dynamic NPM1 log reduction provided additional discriminative power, identifying patients with particularly durable outcomes. These findings establish MRD as a robust and actionable surrogate endpoint in lower-intensity AML therapy, supporting its integration into personalized treatment algorithms, including response-adapted de-escalation or early intensification strategies in future clinical trials.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e\u003cu\u003eCompeting interests\u003c/u\u003e\u003c/strong\u003e:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing financial interests.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contribution statement\u003c/strong\u003e: MH treated patients, performed analysis and wrote paper, AP/DM realized flow cytometry analysis. ZG, AB, UTJ, ET, GAR, MC, AC, NBFHCS, CR, SL, GMP, MM\u003csup\u003e2\u003c/sup\u003e, JC, MM\u003csup\u003e6\u003c/sup\u003e, NM, SC, UT, AD and GLM treated patients. LC, ST, EB, SC, PF, BL and SH performed RT-qPCR and NGS analysis.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eJourdan E, Boissel N, Chevret S, Delabesse E, Renneville A, Cornillet P, et al.\u0026nbsp;Prospective evaluation of gene mutations and minimal residual disease in patients with core binding factor acute myeloid leukemia. Blood 2013;121(12):2213‑23.\u0026nbsp;\u003c/li\u003e\n\u003cli\u003eTerwijn M, van Putten WLJ, Kelder A, van der Velden VHJ, Brooimans RA, Pabst T, et al.\u0026nbsp;High prognostic impact of flow cytometric minimal residual disease detection in acute myeloid leukemia: data from the HOVON/SAKK AML 42A study. J Clin Oncol 2013;31(31):3889‑97.\u003c/li\u003e\n\u003cli\u003eBalsat M, Renneville A, Thomas X, de\u0026nbsp;Botton S, Caillot D, Marceau A, et al. 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Minimal/measurable residual disease in AML: a consensus document from the European LeukemiaNet MRD Working Party. Blood 2018;131(12):1275‑91.\u003c/li\u003e\n\u003cli\u003ePlesa A, Mathis S, Dumezy F, Lhoumeau AC, Saada V, Arnoux I, et al. Flow MRD Monitoring Combining Laip/Dfn and CD34+CD38- LSCs Is a Strong Predictor of Outcome in Adult AML Independently of the ELN-2022 Risk: First Results from the Multicentric Acute Leukemia French Intergroup MRD Flow Network. Blood 2024;144(Supplement 1):226.\u003c/li\u003e\n\u003cli\u003eBoddu P, Jorgensen J, Kantarjian H, Borthakur G, Kadia T, Daver N, et al. Achievement of a negative minimal residual disease state after hypomethylating agent therapy in older patients with AML reduces the risk of relapse. Leukemia 2018;32(1):241‑4.\u003c/li\u003e\n\u003cli\u003eDiNardo CD, Jonas BA, Pullarkat V, Thirman MJ, Garcia JS, Wei AH, et al. Azacitidine and Venetoclax in Previously Untreated Acute Myeloid Leukemia. N Engl J Med 2020;383(7):617‑29.\u003c/li\u003e\n\u003cli\u003e Pratz KW, Jonas BA, Pullarkat V, Recher C, Schuh AC, Thirman MJ, et al. Measurable Residual Disease Response and Prognosis in Treatment-Na\u0026iuml;ve Acute Myeloid Leukemia With Venetoclax and Azacitidine. J Clin Oncol 2022;40(8):855‑65.\u003c/li\u003e\n\u003cli\u003e Othman J, Tiong IS, O\u0026rsquo;Nions J, Dennis M, Mokretar K, Ivey A, et al. Molecular MRD is strongly prognostic in patients with NPM1-mutated AML receiving venetoclax-based nonintensive therapy. Blood 2024;143(4):336‑41.\u003c/li\u003e\n\u003cli\u003e Heuser M, Freeman SD, Ossenkoppele GJ, Buccisano F, Hourigan CS, Ngai LL, et al. 2021 Update on MRD in acute myeloid leukemia: a consensus document from the European LeukemiaNet MRD Working Party. Blood 2021;138(26):2753‑67.\u003c/li\u003e\n\u003cli\u003e Plesa A, Dumontet C, Mattei E, Tagoug I, Hayette S, Sujobert P, et al. High frequency of CD34+CD38-/low immature leukemia cells is correlated with unfavorable prognosis in acute myeloid leukemia. World J Stem Cells 2017;9(12):227‑34.\u003c/li\u003e\n\u003cli\u003e Reuvekamp T, Ngai LL, den\u0026nbsp;Hartog D, Carbaat-Ham J, Fayed MMHE, Scholten WJ, et al. CD34+CD38- leukemia stem cells predict clinical outcomes in acute myeloid leukemia patients treated non-intensively with hypomethylating agents. Leukemia 2025;39(4):972‑5.\u003c/li\u003e\n\u003cli\u003e Mawalankar G, Achrekar AR, G Y, Satam B, Ghogale S, Deshpande N, et al. Leukemic Stem Cell Measurable Residual Disease (LSC MRD) Status Is a Better Predictor of Relapse Than Multiparametric Flowcytometric Analysis in Acute Myeloid Leukemia Patients. Blood 2024;144(Supplement 1):2953.\u003c/li\u003e\n\u003cli\u003e Li SQ, Xu LP, Wang Y, Zhang XH, Chen H, Chen YH, et al. An LSC-based MRD assay to complement the traditional MFC method for prediction of AML relapse: a prospective study. Blood 2022;140(5):516‑20.\u0026nbsp;\u003c/li\u003e\n\u003cli\u003e Zeijlemaker W, Grob T, Meijer R, Hanekamp D, Kelder A, Carbaat-Ham JC, et al.\u0026nbsp;CD34+CD38- leukemic stem cell frequency to predict outcome in acute myeloid leukemia. Leukemia 2019;33(5):1102‑12.\u003c/li\u003e\n\u003cli\u003e Jen WY, Sasaki K, Ravandi F, Kadia TM, Wang SA, Wang W, et al. Impact of measurable residual disease clearance kinetics in patients with AML undergoing intensive chemotherapy. Blood Adv 2025;9(4):783‑92.\u003c/li\u003e\n\u003cli\u003e Ivey A, Hills RK, Simpson MA, Jovanovic JV, Gilkes A, Grech A, et al. Assessment of Minimal Residual Disease in Standard-Risk AML. New England Journal of Medicine 2016;374(5):422‑33.\u003c/li\u003e\n\u003cli\u003e D\u0026ouml;hner H, Estey E, Grimwade D, Amadori S, Appelbaum FR, B\u0026uuml;chner T, et al.\u0026nbsp;Diagnosis and management of AML in adults: 2017 ELN recommendations from an international expert panel. Blood 2017;129(4):424‑47.\u003c/li\u003e\n\u003cli\u003e Maiti A, DiNardo CD, Wang SA, Jorgensen J, Kadia TM, Daver NG, et al. Prognostic value of measurable residual disease after venetoclax and decitabine in acute myeloid leukemia. Blood Adv 2021;5(7):1876‑83.\u003c/li\u003e\n\u003cli\u003e Karrar O, Abdelmagid M, Rana M, Iftikhar M, McCullough K, Al-Kali A, et al. Venetoclax duration (14 vs. 21 vs. 28 days) in combination with hypomethylating agent in newly diagnosed acute myeloid leukemia: Comparative analysis of response, toxicity, and survival. American Journal of Hematology 2024;99(2):E63‑6.\u003c/li\u003e\n\u003cli\u003e Willekens C, Bazinet A, Chraibi S, Bataller A, Decroocq J, Arani N, et al. Reduced venetoclax exposure to 7 days vs standard exposure with hypomethylating agents in newly diagnosed AML patients. Blood Cancer J 2025;15(1):68.\u003c/li\u003e\n\u003cli\u003e Aiba M, Shigematsu A, Suzuki T, Miyagishima T. Shorter duration of venetoclax administration to 14 days has same efficacy and better safety profile in treatment of acute myeloid leukemia. Ann Hematol 2023;102(3):541‑6.\u003c/li\u003e\n\u003cli\u003e DiNardo CD, Pratz KW, Panayiotidis P, Wei X, Vorobyev V, Ill\u0026eacute;s \u0026Aacute;, et al. The impact of post-remission granulocyte colony-stimulating factor use in the phase 3 studies of venetoclax combination treatments in patients with newly diagnosed acute myeloid leukemia. Am J Hematol 2025;100(1):185‑8.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1 to 3 are available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"leukemia","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"leu","sideBox":"Learn more about [Leukemia](http://www.nature.com/leu/)","snPcode":"41375","submissionUrl":"https://mts-leu.nature.com/cgi-bin/main.plex","title":"Leukemia","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7959681/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7959681/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Measurable residual disease (MRD) is a key prognostic marker in acute myeloid leukemia (AML) but its significance in patients treated with azacitidine and venetoclax (AZA/VEN) outside clinical trials remains unclear. We retrospectively analyzed 220 newly diagnosed AML patients from the French VENAURA registry who achieved composite complete remission and underwent MRD evaluation by multiparametric flow cytometry (MFC, LAIP/LSC) and/or NPM1 RT-qPCR. Median age was 74 years. Cumulative MRD negativity was achieved in 62–67% of patients depending on the method. Attaining MRD negativity at any time was strongly associated with superior overall survival (OS: 31.3 months vs 15.7 months for LAIP, not reached vs 10.8 months for NPM1; all p\u003c0.001) and lower cumulative incidence of relapse. Dual LAIP/LSC negativity conferred the best outcomes (4-year OS ~57%). Importantly, MRD response mitigated the adverse prognostic impact of ELN 2024 intermediate/poor risk, with MRD-negative patients achieving outcomes comparable to favorable-risk cases. MRD kinetics (early vs late responders) did not affect survival, while G-CSF use improved MRD conversion and OS. In real-world AZA/VEN–treated AML, achieving deep MRD negativity—by MFC or NPM1 RT-qPCR—emerges as the dominant prognostic determinant, overriding baseline risk and supporting its integration into response-adapted strategies.","manuscriptTitle":"Prognostic impact of measurable residual disease in AML patients treated frontline with azacitidine and venetoclax: results from the French VENAURA registry","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-06 16:48:24","doi":"10.21203/rs.3.rs-7959681/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"revise","date":"2025-11-24T12:30:36+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"This content is not available.","date":"2025-11-21T22:31:54+00:00","index":3,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2025-11-19T21:20:06+00:00","index":2,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2025-11-10T13:17:21+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2025-11-01T00:20:57+00:00","index":3,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2025-10-31T07:05:10+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2025-10-30T08:43:10+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewersInvited","content":"","date":"2025-10-27T13:56:21+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-27T13:51:04+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-27T13:50:12+00:00","index":"","fulltext":""},{"type":"submitted","content":"Leukemia","date":"2025-10-25T20:39:02+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"leukemia","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"leu","sideBox":"Learn more about [Leukemia](http://www.nature.com/leu/)","snPcode":"41375","submissionUrl":"https://mts-leu.nature.com/cgi-bin/main.plex","title":"Leukemia","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"b2cdf981-6b99-402e-8da3-b8ea6a1dce2c","owner":[],"postedDate":"November 6th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":56960573,"name":"Health sciences/Diseases/Haematological diseases/Haematological cancer/Leukaemia/Acute myeloid leukaemia"},{"id":56960574,"name":"Biological sciences/Cancer/Haematological cancer/Leukaemia/Acute myeloid leukaemia"}],"tags":[],"updatedAt":"2026-04-23T08:41:29+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-06 16:48:24","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7959681","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7959681","identity":"rs-7959681","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}