Mini-consolidations or intermediate-dose cytarabine (IDAC) for the post-remission therapy of AML patients over 60. A retrospective study from the DATAML and SAL registries.

Mini-consolidations or intermediate-dose cytarabine (IDAC) for the post-remission therapy of AML patients over 60. A retrospective study from the DATAML and SAL registries. | 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 Mini-consolidations or intermediate-dose cytarabine (IDAC) for the post-remission therapy of AML patients over 60. A retrospective study from the DATAML and SAL registries. Christian Récher, Pierre-Yves Dumas, Emilie Bérard, Suzanne Tavitian, and 21 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4453206/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 According to current recommendations, older AML patients in first complete remission (CR) after induction chemotherapy should receive consolidation with intermediate-dose cytarabine (IDAC). However, no study has demonstrated the superiority of IDAC over other regimen. In this retrospective study, we compared the efficacy of mini-consolidations (idarubicin 8 mg/m² day 1, cytarabine 50 mg/m²/12 hours, day 1–5) and IDAC. Inclusion criteria were newly diagnosed AML, age > 60 years, first CR after induction and at least 1 cycle of consolidation. Of the 796 included patients, 322 patients received mini-consolidations and 474 patients received IDAC. Mini-consolidation patients were older, more often had de novo AML and unfavorable risk. The rate of allogeneic transplantation was higher in the IDAC group. The median number of cycles was higher in the mini-consolidation group (4 vs 2; P < 0.0001). Median relapse-free survival was 18 months with mini-consolidations and 12 months with IDAC ( P = 0.0064). In multivariate analysis, the risk of relapse or death was significantly higher in the IDAC group ( P = 0.004). Median OS was 36 vs. 31 months with mini-consolidations or IDAC, respectively ( P = 0.46). In multivariate analysis, the consolidation regimen had no significant influence on OS ( P = 0.43). In older AML patients, post-remission therapy with mini-consolidations represents an alternative to IDAC. Health sciences/Diseases/Haematological diseases/Haematological cancer/Leukaemia/Acute myeloid leukaemia Health sciences/Health care/Therapeutics/Drug therapy/Chemotherapy Acute myeloid leukemia intensive chemotherapy consolidation post-remission therapy cytarabine supportive care older patients. Figures Figure 1 Introduction In older patients with newly diagnosed acute myeloid leukemia (AML) who are suitable for intensive treatment, induction chemotherapy remains the established therapeutic option associated with long-term survival. 1 , 2 However, for the 60–70% of those older patients who achieve complete remission (CR), the optimal post-remission consolidation therapy has not been clearly defined by prospective clinical trials, and remains a matter of debate. 3 , 4 In the seminal study of the Cancer and Leukaemia Group B (CALGB) that established high-dose of cytarabine (HDAC) as a standard for post-remission therapy in patients younger than 60 years of age, there was no difference in relapse-free (RFS) and overall survival (OS) in patients > 60 years randomized to receive four courses of cytarabine at 100 mg/m 2 /day, 400 mg/m 2 /day (continuous infusion over 5 days), or 3 g/m 2 (over a 3 h infusion each 12 h on days 1, 3, and 5). 5 The CALGB group also compared standard dose cytarabine (SDAC) at 100 mg/m² every 12 hours for 5 days with an intensified schedule of cytarabine 500 mg/m² every 12 hours associated with mitoxantrone for 3 days in older patients without any difference in RFS and OS. 6 The Acute Leukemia French Association (ALFA) 9803 clinical trial comparing a single “3 + 7” consolidation course with an outpatient schedule consisting of six cycles of single-dose anthracycline combined with subcutaneous cytarabine at 60 mg/m² every 12 hours for 5 days in AML patients over 65 years showed an OS advantage in favor of the repeated courses of mini-consolidations. 7 Both trials also demonstrated lower toxicity with reduced-intensity regimens. In line with these studies, the 2017 ELN guidelines indicated that there was no established value of intensive consolidation therapy in older patients with intermediate or adverse-risk genetics. 8 The 2022 ELN recommendations, however, propose that patients ineligible for allogeneic hematopoietic stem cell transplantation (allo-HSCT) should receive consolidation therapy with intermediate-dose cytarabine (IDAC, 500–1000 mg/m²/12h, d1-3, for 3–4 cycles), mainly because this schedule has become popular in practice, as it could mimic the cytarabine dose effect observed in younger patients without too much toxicity. The DATAML centers traditionally use the consolidation schema of the French Innovative Leukemia Organization (FILO) study group including up to six out-patient mini-consolidation cycles for most patients although some patients may occasionally receive IDAC. 9 , 10 In a recent retrospective study, we compared both strategies in patients of the DATAML registry and showed no difference in RFS and OS. 11 The aim of this study was to compare the efficacy and tolerability of the mini-consolidations used in the French DATAML registry and IDAC used routinely by the German Study Alliance Leukemia (SAL) group in a larger series of AML patients > 60 years in first complete remission after intensive induction chemotherapy. The primary objective was to compare OS in patients treated with mini-consolidations or IDAC. Secondary objectives were to compare RFS and cumulative incidence of relapse (CIR). Subjects and Methods Patients The inclusion criteria for this retrospective study were newly diagnosed AML between 01/01/2010 and 12/31/2019, age > 60 years, first CR after one or two “3 + 7" induction cycles, consolidation treatment with at least 1 cycle of mini-consolidation or IDAC. Patients with acute promyelocytic leukemia or AML with t(9;22)/ BCR::ABL1 , patients treated with CPX-351 or patients who had received both types of consolidation (mini-consolidation and IDAC) were not included. A minimal data set extracted from DATAML and SAL registries included the variables age, sex, ECOG (eastern cooperative oncology group) performance status at diagnosis, history of cytotoxic treatment, date of diagnosis, AML status (de novo or secondary), white blood cell count, 2017 ELN risk classification, mutational status, nature of first-line therapy, allo-HSCT in first complete remission or after relapse, date of day 1 of first consolidation cycle, number of post-remission cycles, date of relapse and/or death. This study was performed in accordance with the Declaration of Helsinki. All registries were approved by institutional review boards or national authorities, and informed consent was obtained from all patients. Treatments and endpoints Mini-consolidation treatment included cytarabine 50 mg/m²/12h on days 1–5 by subcutaneous injection and idarubicin 8 mg/m² on day 1 performed on an outpatient basis (up to 6 cycles every 30 to 45 days). IDAC was cytarabine 1-1.5g/m²/12h on days 1–3 or 1, 3, 5 (up to 3 cycles). Allo-HSCT was proposed in eligible patients with intermediate or adverse risk AML according to local practices. CIR, RFS and OS were defined according to the European Leukemia Net (ELN) criteria. 1 Statistical analysis Patients characteristics were described using numbers and frequencies for qualitative data, and median, interquartile range (IQR), and range (minimum − maximum) for quantitative data. Categorical variables were compared between IDAC and mini-consolidations arms using the chi2 test (or Fisher’s exact test when necessary). Student’s t test was used to compare the distributions of continuous data (Mann–Whitney’s test was used when the distribution departed significantly from normality or when homoscedasticity was rejected). For OS and RFS, differences in survival functions between the IDAC and mini-consolidations arms were described using survival at 1, 3 and 5 years together with median with IQR and were tested using the log-rank test. For relapse (CIR), cumulative incidence functions were drawn (as non-relapse mortality was used as a competing event) and compared using Gray’s test. Adjusted hazard ratios (HR) and 95% confidence intervals (95%CI) were assessed using a standard Cox model for OS and RFS, and a proportional sub-distribution hazard model (an extension of the Cox model) for competing risks for CIR. 12 Multivariate analyses included IDAC versus mini-consolidations arms together with potential confounding factors [age, gender, performance status, WBC, 2017 ELN risk, secondary vs. de novo AML, NPM1 and FLT3 -ITD mutations, study period and allo-HSCT in first complete remission] associated with the endpoints (to the threshold of p < 0.20). Stepwise regression analysis was then used to assess variables that were significantly and independently associated with the endpoints (p < 0.05). The proportional hazard assumption was tested for each covariate of the Cox model using log-log plot curves and was always supported. When the linear hypothesis was not supported, continuous potential confounding factors were transformed into ordered data. Interactions between all potential confounding factors and IDAC versus mini-consolidations were tested. None were significant, indicating that the effect of treatment (IDAC versus mini-consolidations) was not significantly different according to all confounding factors analyzed, especially according to age, 2017 ELN risk, NPM1 mutation or allo-HSCT in first CR. Allo-HSCT in first CR was evaluated as a time-dependent qualitative covariate. To better appreciate the impact of IDAC versus mini-consolidations, we used the propensity score method to more extensively take into account potential baseline differences between IDAC versus mini-consolidations arms. A multivariate logistic regression model was generated to estimate for each patient a propensity score to receive IDAC versus mini-consolidations. Covariates were all variables expected to be associated with IDAC versus mini-consolidations in clinical practice (age, gender, performance status, WBC, 2017 ELN risk, secondary vs. de novo AML, NPM1 and FLT3 -ITD mutations, study period, history of cytotoxic treatment, targeted therapy added to induction and inclusion in a clinical trial). The performance of the model was estimated with the chi2-Hosmer-Lemeshow statistic and the C-statistic. Based on propensity score, subjects with IDAC were matched with patients with mini-consolidations. In the subgroup of propensity score matched patients, endpoints were compared between IDAC and mini-consolidations arms, after adjustment for allo-HSCT (as time-dependent variable). All reported p-values were two-sided and the significance threshold was 60 years who had obtained a first CR after intensive induction chemotherapy between January 1, 2010 and December 31, 2019. Post remission therapy was mini-consolidations in 322 patients (40.5%) from the DATAML registry and IDAC in 474 patients (59.5%) from the SAL registry. Their characteristics are presented in Table 1 . Compared to patients treated with IDAC, patients treated with mini-consolidation were slightly older (47.5% >70 years vs. 40.1%; P = 0.037), more often had de novo AML (81.4% vs. 75.3%; P = 0.044) and adverse risk according to 2017 ELN classification (22% vs. 12%; P < 0.001). There were no differences in terms of sex, performance status at diagnosis, white blood cell (WBC) count, FLT3 -ITD or NPM1 mutations. Induction therapy consisted mainly of idarubicin-cytarabine-lomustine (76.4%) in the mini-consolidation group and daunorubicin-cytarabine (96%) in the IDAC group. Midostaurin was added to induction chemotherapy in 14 patients (4.3%) of the mini-consolidation group and 3 patients (0.6%) of the IDAC group ( P < 0.001). There were 94 patients (29.2%) of the mini-consolidation group and 59 patients (12.4%) of the IDAC group ( P < 0.001) included in a clinical trial at induction. The median number of consolidation cycles was 4 (IQR, 2–6) with mini-consolidations and 2 (IQR, 1–3) with IDAC ( P < 0.0001). The rate of allo-HSCT was higher in the IDAC group both in first CR (18% vs. 12%, P = 0.019) and after relapse (31% vs. 10%, P < 0.0001). Table 1 Characteristics of patients according to post remission therapy. Mini-consolidations IDAC p value Total 322 (40.5%) 474 (59.5%) 796 (100.0%) Sex - n (%) Male Female 178 (55.3) 144 (44.7) 256 (54.0) 218 (46.0) 0.723 434 (54.5) 362 (45.5) Study period - n (%) 2010–2014 2015–2019 139 (43.2) 183 (56.8) 260 (54.9) 214 (45.1) 0.001 399 (50.1) 397 (49.9) Age (years) Median Min;Max 69.4 61.1; 82.8 69.0 61.0; 86.0 0.015 69.00 61.0; 86.0 Age (years) - n (%) ≤ 70 > 70 169 (52.5) 153 (47.5) 284 (59.9) 190 (40.1) 0.037 453 (56.9) 343 (43.1) AML status - n (%) De novo Secondary 262 (81.4) 60 (18.6) 354 (75.3) 116 (24.7) 0.044 616 (77.8) 176 (22.2) History of cytotoxic treatment - n (%) None Chemotherapy Radiotherapy Chemotherapy + radiotherapy Others 283 (87.9) 6 (1.9) 18 (5.6) 7 (2.2) 8 (2.5) 435 (91.8) 22 (4.6) 11 (2.3) 6 (1.3) 0 (0.0) < 0.0001 718 (90.2) 28 (3.5) 29 (3.6) 13 (1.6) 8 (1.0) Performance status - n (%) 0–1 2-3-4 262 (83.2) 53 (16.8) 381 (82.1) 83 (17.9) 0.701 643 (82.5) 136 (17.5) WBC (Giga/L) n /missing Median IQR Min;Max 321/1 5.2 2.1; 28.1 0.4;359.4 472/2 7.4 2.0;41.8 0.2;305.0 0.466 793/3 6.2 2.1;35.3 0.2;359.4 WBC (Giga/L) - n (%) < 30 ≥ 30 243 (75.7) 78 (24.3) 332 (70.3) 140 (29.7) 0.096 575 (72.5) 218 (27.5) 2017 ELN risk - n (%) Favorable Intermediate Adverse 98 (39.2) 96 (38.4) 56 (22.4) 152 (34.8) 231 (52.9) 54 (12.4) < 0.001 250 (36.4) 327 (47.6) 110 (16.0) FLT3 -ITD - n (%) No Yes 223 (80.5) 54 (19.5) 334 (80.7) 80 (19.3) 0.955 557 (80.6) 134 (19.4) NPM1 mutation - n (%) No Yes 161 (58.1) 116 (41.9) 262 (59.8) 176 (40.2) 0.653 423 (59.2) 292 (40.8) Induction chemotherapy - n (%) Daunorubicin-cytarabine Idarubicin-cytarabine Idarubicin-cytarabine-lomustine Daunorubicin-cytarabine-GO Other 6 (1.9) 65 (20.2) 246 (76.4) 0 (0.0) 5 (1.6) 455 (96.0) 1 (0.2) 0 (0.0) 2 (0.4) 16 (3.4) < 0.0001 461 (57.9) 66 (8.3) 246 (30.9) 2 (0.3) 21 (2.6) Clinical trial - n (%) No Yes 228 (70.8) 94 (29.2) 415 (87.6) 59 (12.4) < 0.0001 643 (80.8) 153 (19.2) IQR, Inter-Quartile Range; Min, Minimum; Max, Maximum; WBC, white blood cell count; ELN, European LeukemiaNet; GO, gemtuzumab ozogamycin. Overall survival The median follow-up was 61 months (inter quartile range, IQR, 40–81) for the whole population, 63 (IQR, 50–74) in the mini-consolidation group and 58 months (IQR, 28–87) in the IDAC group. Median OS was 36 (IQR, 14–109) and 31 months (IQR, 14–99) in the mini-consolidation and IDAC groups, respectively ( P = 0.46) (Fig. 1 A). OS at 1, 3 and 5 years was 80% (95% confidence interval [CI]: 75–84) vs. 81% (95%CI: 77–84), 51 (95%CI: 45–56) vs. 46% (95%CI: 41–51) and 35% (95%CI: 29–40) vs 34% (95%CI: 29–39) in the mini-consolidation and IDAC groups, respectively. Univariate and multivariate analysis are shown in Table 2 . In the multivariate analysis, consolidation type was not significantly and independently associated with OS ( P = 0.425). Adjustment for the number of consolidation cycles (< 2 vs. ≥2) did not modify the impact of consolidation type ( P = 0.575) Table 2 Univariate and multivariate analyses for overall survival Univariate Multivariate Number Events HR 95% CI P -value HR 95% CI P -value Treatment Mini-consolidations IDAC 322 474 203 269 1 1.07 0.89;1.29 0.464 1 1.08 0.89;1.31 0.425 Study period 2010–2014 2015–2019 399 397 272 200 1 0.82 0.69;0.99 0.041 Sex Male Female 434 362 261 211 1 1.00 0.83;1.19 0.969 Age (years) ≤ 70 > 70 453 343 251 221 1 1.31 1.09;1.57 0.004 1 1.35 1.12;1.62 0.002 AML status De novo Secondary 616 176 353 115 1 1.17 0.95;1.45 0.142 Performance status at diagnosis 0–1 2-3-4 643 136 374 88 1 1.37 1.09;1.73 0.008 1 1.35 1.06;1.71 0.014 WBC (G/L) < 30 ≥ 30 575 218 328 141 1 1.27 1.04;1.55 0.017 1 1.22 1.00;1.50 0.050 2017 ELN risk Favorable Intermediate Adverse 250 327 110 127 207 72 1 1.33 1.74 1.07;1.66 1.30;2.33 0.011 < 0.001 1 1.39 1.79 1.11;1.74 1.34;2.40 0.004 < 0.001 FLT3 -ITD No Yes 557 134 328 83 1 1.14 0.90;1.45 0.283 NPM1 mutation No Yes 423 292 262 157 1 0.81 0.66;0.99 0.036 Allo-HSCT No Yes 676 120 410 62 1 0.82 0.62;1.07 0.139 HR, hazard ratio; CI, confidence interval; WBC, white blood cell count; ELN, European LeukemiaNet; Allo-HSCT, allogeneic hematopoietic stem cell transplantation. Cumulative incidence of relapse and relapse free survival In the mini-consolidation group, 209 patients relapsed and the CIR was 39%, 56% and 62% at 1, 2 and 3 years, respectively. In the IDAC group, 302 patients relapsed and the CIR was 44%, 61% and 67% at 1, 2 and 3 years, respectively (Fig. 1 B). Univariate and multivariate analyses for CIR are shown in Supplementary Table 1. In multivariate analysis, the relapse risk was significantly and independently higher in patients treated with IDAC (HR 1.30, 95%CI: 1.1–1.6; P = 0.006). Adjustment for the number of consolidation cycles did not modify the impact of IDAC on the relapse risk (HR 1.28, 95%CI: 1.1–1.5; P = 0.012). Median RFS was 18 (IQR, 7–75) and 12 months (IQR, 7–33) in the mini-consolidation and IDAC groups, respectively ( P = 0.006) (Fig. 1 C). RFS at 1, 3 and 5 years was 60% (95%CI: 54–65) vs. 50% (95%CI: 45–54), 33% (95%CI: 28–38) vs. 24% (95%CI: 20–28) and 27% (95%CI: 22–32) vs 19% (95%CI: 15–23) in the mini-consolidation and IDAC groups, respectively. Univariate and multivariate analysis are shown in Table 3 . In multivariate analysis, the risk of relapse or death was significantly and independently higher in patients treated with IDAC (HR 1.29, 95%CI: 1.1–1.5; P = 0.004). Adjustment for the number of consolidation cycles did not modify the impact of IDAC on RFS (HR 1.26, 95%CI: 1.1–1.5; P = 0.011) Table 3 Univariate and multivariate analyses for relapse-free survival Univariate Multivariate Number Events HR 95% CI P -value HR 95% CI P -value Treatment Mini-consolidations IDAC 322 474 233 349 1 1.26 1.07;1.49 0.007 1 1.29 1.09;1.54 0.004 Study period 2010–2014 2015–2019 399 397 314 265 1 0.87 0.74;1.02 0.089 Sex Male Female 434 362 319 263 1 0.98 0.83;1.15 0.803 Age (years) ≤ 70 > 70 453 343 317 265 1 1.21 1.03;1.42 0.024 AML status De novo Secondary 616 176 445 133 1 1.15 0.94;1.39 0.170 Performance status at diagnosis 0–1 2-3-4 643 136 467 102 1 1.22 0.99;1.52 0.066 WBC (G/L) < 30 ≥ 30 575 218 411 168 1 1.18 0.99;1.41 0.072 1 1.24 1.03;1.50 0.026 2017 ELN risk Favorable Intermediate Adverse 250 327 110 171 247 84 1 1.16 1.40 0.95;1.41 1.08;1.82 0.145 0.012 * 1.31 1.02;1.68 0.032 FLT3 -ITD No Yes 557 134 413 99 1 1.09 0.88;1.36 0.435 NPM1 mutation No Yes 423 292 325 200 1 0.82 0.68;0.97 0.024 1 0.75 0.62;0.91 0.004 Allo-HSCT No Yes 676 120 510 72 1 0.68 0.53;0.87 0.003 1 0.59 0.46;0.76 < 0.001 HR, hazard ratio; CI, confidence interval; WBC, white blood cell count; ELN, European LeukemiaNet; Allo-HSCT, allogeneic hematopoietic stem cell transplantation. * adverse vs. favorable/intermediate (= 1). Propensity score matching To better appreciate the impact of mini-consolidations vs. IDAC on OS, CIR, and RFS we used the propensity score method to take into account potential baseline differences between patients treated with mini-consolidations in the DATAML registry and those treated with IDAC in the SAL registry. A multivariate logistic regression model was generated to estimate for each patient a propensity score to receive mini-consolidations or IDAC. Covariates were all variables expected to be associated with mini-consolidations vs. IDAC (age, gender, performance status, WBC, 2017 ELN risk, secondary vs. de novo AML, NPM1 and FLT3 -ITD mutations, study period, history of cytotoxic treatment, targeted therapy added to induction and inclusion in a clinical trial). The performance of the model was appreciated with the χ 2 -Hosmer-Lemeshow statistic (p-value = 0.456) and the c-statistic (0.73, 95%CI: 0.69–0.76). Mean propensity score was 0.503 (± 0.209) in the mini-consolidation group (n = 322) and 0.341 (± 0.162) in the IDAC group (n = 470). According to the propensity score, 214 subjects treated with mini-consolidations were matched with 214 subjects with IDAC (206 with a precision of 0.0001, 6 with a precision of 0.001, 64 with a precision of 0.01 and 152 with a precision of 0.1). Mean propensity score was the same in both groups (0.407 ± 0.161) in the matched sample. OS, CIR, and RFS were compared between mini-consolidation and IDAC treatment in the subgroup of propensity score matched patients after adjustment for allo-HSCT (as time-dependent variable). The results remained unchanged compared with the findings of the multivariate analyses in the whole patient population (Supplementary Table 2). Discussion This study comparing two therapeutic strategies for post-remission therapy showed that mini-consolidations including a single anthracycline-dose and standard dose of cytarabine represent an alternative to the recommended IDAC regimen in AML patients older than 60 years who are in first CR after induction chemotherapy. Of note, no significant interaction between treatment (mini-consolidations vs. IDAC) and classical confounding factors was found, indicating that the effect of consolidation regimen was not different in subgroups and in particular according to age, 2017 ELN risk, NPM1 mutation or allo-HSCT (analyzed as a time-dependent variable). Although overall survival was similar with both strategies, the post remission therapy with mini-consolidations was associated with a lower incidence of relapses and a better relapse free survival. The explanations for this difference are unclear. Despite adjustment for the number of cycles, it is possible that the higher number of treatment cycles in the mini-consolidation group contributed to this result by increasing the duration of exposure to genotoxic treatment. A similar finding was observed in the randomized trial of the ALFA group comparing 6 cycles of mini-consolidations and a single intensive chemotherapy cycle in patients older than 65 years. 7 Alternatively, the synergistic combination of standard dose cytarabine and idarubicin could have induce a stronger anti-leukemic activity on residual disease. In younger AML patients, multidrug regimens combining anthracyclines and IDAC or HDAC have shown similar or even greater efficacy than IDAC/HDAC, notably in high-risk patients, but with increased toxicity. 13 – 15 Lastly, differences in induction chemotherapy may also have played a role. Lomustine used in patients of the DATAML registry has been associated with better outcome in older AML patients while comparisons between idarubicin and daunorubicin yielded heterogeneous results. 9 , 16 , 17 , 18 However, effective salvage options and equally distributed genetically determined disease biology in both treatment groups led to similar overall survival in the long term. Demonstrating a similar outcome of mini consolidations over IDAC in terms of OS may have important implications. Indeed, two recent studies by the DATAML registry in France showed that mini-consolidations were associated with a considerable reduction in infection rates, pancytopenia duration, transfusion requirements and hospitalization stays compared to IDAC. Patients receiving mini-consolidations spent on average 20 days less in hospital over the whole period of post-remission treatment. 11 Importantly, an economic analysis performed from the French National Health Insurance perspective and focused on costs associated with inpatient stays, showed that the mini-consolidation strategy could save up to 30,000 euros per patient compared to IDAC in the French health care system. 19 Comparing the two approaches, we can conclude that patients can be treated on an outpatient basis, are longer on treatment and increase their cumulative anthracyclin dose with mini-consolidation. On the other hand, total treatment time with IDAC is shorter, associated with more pronounced cytopenia, and usually requiring inpatient treatment. The limitations of this study include its retrospective and non-randomized nature. There was heterogeneity in induction chemotherapy regimen and we also recognize that the number of six mini-consolidation cycles has not been established by clinical trials but rather by clinical practice, and therefore the optimal number of mini-consolidation cycles is yet to be defined. Moreover, maintenance therapy with oral azacitidine was not approved during the study period and we can only speculate that this treatment might have limited the risk of relapse after IDAC in our study. 20 Nevertheless, the multivariate analysis based on a large cohort of patients (n = 796) and the propensity score enables us to draw reliable conclusions on the absence of difference between the two strategies in terms of OS. Consolidation treatment of older AML patients remains an evolving field with the advent of new drugs and the widespread use of allo-HSCT and maintenance. It should deepen the response to induction therapy without triggering major toxicity. The OS results of our study show the curative potential of current state-of-the-art chemotherapy and at the same time demonstrate the need for further improvement. In this respect, it may be worth exploring whether either or both consolidation approaches may be suited for the addition of new drugs such as venetoclax or quizartinib without excessive hematological toxicity and/or the replacement of anthracyclines to further increase the curative potential and proportion of long-term survivors diagnosed with AML. Declarations Acknowledgments We would like to thank the data management unit of Toulouse University Hospital as well as the central study office and all member sites of the Study Alliance Leukemia (SAL) study group. Authors’ contributions CR, PYD, EB, ST, TL, JG, CA, AB, ED, JBR, JPV, FV, IL, EK, ACdG, AS, SZ, UP, CMT, CB, MB, HS, SB, AP, CRö, collected data, treated patients or performed biological analyses. EB performed statistical analysis and wrote the paper. CR collected data, treated patients, supervised analysis and wrote the paper. All authors reviewed, provided comments and approved the manuscript. Competing Interests Christian Récher declares a consulting or advisory role with Abbvie, Amgen, Astellas, BMS, Boehringer, Jazz Pharmaceuticals, J&J as well as Servier, received research funding from Abbvie, Amgen, Astellas, BMS, Iqvia and Jazz Pharmaceuticals, and support for attending meetings and/or travel from Abbvie, Novartis and Servier. Pierre-Yves Dumas declares a consulting or advisory role for Daiichi-Sankyo, Astellas, Novartis, Abbvie, Servier, BMS, Jazz Pharmaceutical, Janssen, received research funding (to institution) from Daiichi-Sankyo, Astellas, Novartis, Servier, BMS, Roche, Iqvia and support for attending meetings and/or travel from Abbvie, Gilead and Lilly. François Vergez declares research grants from Pierre Fabre and Roche; advisor for Astellas and Amgen. Uwe Platzbecker declares Honoraria and Research support from BMS, Abbvie, Curis, Jazz and Ryvu. Isabelle Luquet declares an advisory role for Jazz Pharmaceuticals. Carsten Müller-Tidow declares institutional research funding from Pfizer and BiolineRx. LR declares institutional research funding from AbbVie and honoraria from BeiGene, Jazz, Neovii. Claudia Baldus declares advisory honoraria from Astellas, Bristol-Meyer-Squibb, Jazz, Janssen, Pfizer, Servier, Amgen, Astra Zeneca. Martin Bornhäuser declares honoraria from Jazz Pharmaceuticals Advisory Board: ActiTrexx; employment by University Hospital TU Dresden, King's College London. Sarah Bertoli declares a consulting or advisory role with Abbvie, Astellas, BMS-Celgene, Jazz Pharmaceuticals as well as Servier and received travel grants from Abbvie and Pfizer. Arnaud Pigneux declares a consulting or advisory role with Astellas, BMS, Servier, Abbvie, Gilead, Jazz Pharmaceuticals, Novartis, Pfizer, received research funding from Astellas, BMS, Roche, Servier and support for attending meetings and/or travel from Servier, Abbvie. Christoph Röllig declares institutional research funding by AbbVie, Novartis, and Pfizer and advisory honoraria from AbbVie, Astellas, Bristol-Meyer-Squibb, Jazz, Janssen, Novartis, Otsuka, Pfizer, Servier. All other authors declare no competing interests. Data Availability Statement The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request. References Döhner H, Wei AH, Appelbaum FR, Craddock C, DiNardo CD, Dombret H, et al. Diagnosis and management of AML in adults: 2022 recommendations from an international expert panel on behalf of the ELN. Blood 2022; 140(12): 1345–1377. 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Postremission therapy in older patients with de novo acute myeloid leukemia: a randomized trial comparing mitoxantrone and intermediate-dose cytarabine with standard-dose cytarabine. Blood 2001; 98(3): 548–553. Gardin C, Turlure P, Fagot T, Thomas X, Terre C, Contentin N, et al. Postremission treatment of elderly patients with acute myeloid leukemia in first complete remission after intensive induction chemotherapy: results of the multicenter randomized Acute Leukemia French Association (ALFA) 9803 trial. Blood 2007; 109(12): 5129–5135. 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): 424–447. Pigneux A, Béné MC, Salmi LR, Dumas PY, Delaunay J, Bonmati C, et al. Improved Survival by Adding Lomustine to Conventional Chemotherapy for Elderly Patients With AML Without Unfavorable Cytogenetics: Results of the LAM-SA 2007 FILO Trial. J Clin Oncol 2018; 36(32): 3203–3210. Pigneux A, Béné MC, Guardiola P, Recher C, Hamel JF, Sauvezie M, et al. Addition of Androgens Improves Survival in Elderly Patients With Acute Myeloid Leukemia: A GOELAMS Study. J Clin Oncol 2017; 35(4): 387–393. Galtier J, Alric C, Bérard E, Leguay T, Tavitian S, Bidet A, et al. Intermediate-dose cytarabine or standard-dose cytarabine plus single-dose anthracycline as post-remission therapy in older patients with acute myeloid leukemia: impact on health care resource consumption and outcomes. Blood Cancer J 2021; 11(11): 180. Fine JP, Gray RJ. A Proportional Hazards Model for the Subdistribution of a Competing Risk. Journal of the American Statistical Association 1999; 94(446): 496–509. Miyawaki S, Ohtake S, Fujisawa S, Kiyoi H, Shinagawa K, Usui N, et al. A randomized comparison of 4 courses of standard-dose multiagent chemotherapy versus 3 courses of high-dose cytarabine alone in postremission therapy for acute myeloid leukemia in adults: the JALSG AML201 Study. Blood 2011; 117(8): 2366–2372. Burnett AK, Russell NH, Hills RK, Hunter AE, Kjeldsen L, Yin J, et al. Optimization of Chemotherapy for Younger Patients With Acute Myeloid Leukemia: Results of the Medical Research Council AML15 Trial. Journal of Clinical Oncology 2013; 31(27): 3360–3368. Schaich M, Parmentier S, Kramer M, Illmer T, Stölzel F, Röllig C, et al. High-dose cytarabine consolidation with or without additional amsacrine and mitoxantrone in acute myeloid leukemia: results of the prospective randomized AML2003 trial. J Clin Oncol 2013; 31(17): 2094–2102. Gardin C, Chevret S, Pautas C, Turlure P, Raffoux E, Thomas X, et al. Superior long-term outcome with idarubicin compared with high-dose daunorubicin in patients with acute myeloid leukemia age 50 years and older. J Clin Oncol 2013; 31(3): 321–327. Teuffel O, Leibundgut K, Lehrnbecher T, Alonzo TA, Beyene J, Sung L. Anthracyclines during induction therapy in acute myeloid leukaemia: a systematic review and meta-analysis. Br J Haematol 2013; 161(2): 192–203. Li X, Xu S, Tan Y, Chen J. The effects of idarubicin versus other anthracyclines for induction therapy of patients with newly diagnosed leukaemia. Cochrane Database Syst Rev 2015; (6): Cd010432. Mounie M, Dumas PY, Liva-Yonnet S, Fabre D, Leguay T, Galtier J, et al. Cost comparison of post-remission strategies in younger and older AML patients in France. Blood Cancer J 2023; 13(1): 100. Wei AH, Döhner H, Pocock C, Montesinos P, Afanasyev B, Dombret H, et al. Oral Azacitidine Maintenance Therapy for Acute Myeloid Leukemia in First Remission. N Engl J Med 2020; 383(26): 2526–2537. Additional Declarations Yes there is potential conflict of interest. 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Röllig","email":"","orcid":"https://orcid.org/0000-0002-3791-0548","institution":"University Hospital, Technical University Dresden","correspondingAuthor":false,"prefix":"","firstName":"Christoph","middleName":"","lastName":"Röllig","suffix":""}],"badges":[],"createdAt":"2024-05-21 08:16:25","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4453206/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4453206/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":58077498,"identity":"f2ab6e76-8a49-4cba-bf2f-517c6e09adfd","added_by":"auto","created_at":"2024-06-10 22:34:06","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":20175,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eKaplan Meier curves for overall survival (A), cumulative incidence of relapse (B) and relapse free survival (C).\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"OnlineFigure1.png","url":"https://assets-eu.researchsquare.com/files/rs-4453206/v1/049a4c6a4eff63e53da8b1e8.png"},{"id":58732598,"identity":"b6d8c19d-1cc3-4042-811d-5333459ed8cd","added_by":"auto","created_at":"2024-06-20 11:39:15","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1079788,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4453206/v1/06c04f1a-5dad-4d4e-964e-8892f8709155.pdf"},{"id":58077719,"identity":"61729ae2-1697-40c2-8172-0cafd0dec853","added_by":"auto","created_at":"2024-06-10 22:42:06","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":325455,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"Supplementaryinformation.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4453206/v1/8a22cf74ea81930cb985baf9.pdf"}],"financialInterests":"\u003cb\u003eYes\u003c/b\u003e there is potential conflict of interest.","formattedTitle":"Mini-consolidations or intermediate-dose cytarabine (IDAC) for the post-remission therapy of AML patients over 60. A retrospective study from the DATAML and SAL registries.","fulltext":[{"header":"Introduction","content":"\u003cp\u003eIn older patients with newly diagnosed acute myeloid leukemia (AML) who are suitable for intensive treatment, induction chemotherapy remains the established therapeutic option associated with long-term survival.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e However, for the 60\u0026ndash;70% of those older patients who achieve complete remission (CR), the optimal post-remission consolidation therapy has not been clearly defined by prospective clinical trials, and remains a matter of debate.\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e In the seminal study of the Cancer and Leukaemia Group B (CALGB) that established high-dose of cytarabine (HDAC) as a standard for post-remission therapy in patients younger than 60 years of age, there was no difference in relapse-free (RFS) and overall survival (OS) in patients\u0026thinsp;\u0026gt;\u0026thinsp;60 years randomized to receive four courses of cytarabine at 100 mg/m\u003csup\u003e2\u003c/sup\u003e/day, 400 mg/m\u003csup\u003e2\u003c/sup\u003e/day (continuous infusion over 5 days), or 3 g/m\u003csup\u003e2\u003c/sup\u003e (over a 3 h infusion each 12 h on days 1, 3, and 5).\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e The CALGB group also compared standard dose cytarabine (SDAC) at 100 mg/m\u0026sup2; every 12 hours for 5 days with an intensified schedule of cytarabine 500 mg/m\u0026sup2; every 12 hours associated with mitoxantrone for 3 days in older patients without any difference in RFS and OS.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e The Acute Leukemia French Association (ALFA) 9803 clinical trial comparing a single \u0026ldquo;3\u0026thinsp;+\u0026thinsp;7\u0026rdquo; consolidation course with an outpatient schedule consisting of six cycles of single-dose anthracycline combined with subcutaneous cytarabine at 60 mg/m\u0026sup2; every 12 hours for 5 days in AML patients over 65 years showed an OS advantage in favor of the repeated courses of mini-consolidations.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e Both trials also demonstrated lower toxicity with reduced-intensity regimens. In line with these studies, the 2017 ELN guidelines indicated that there was no established value of intensive consolidation therapy in older patients with intermediate or adverse-risk genetics.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e The 2022 ELN recommendations, however, propose that patients ineligible for allogeneic hematopoietic stem cell transplantation (allo-HSCT) should receive consolidation therapy with intermediate-dose cytarabine (IDAC, 500\u0026ndash;1000 mg/m\u0026sup2;/12h, d1-3, for 3\u0026ndash;4 cycles), mainly because this schedule has become popular in practice, as it could mimic the cytarabine dose effect observed in younger patients without too much toxicity.\u003c/p\u003e \u003cp\u003eThe DATAML centers traditionally use the consolidation schema of the French Innovative Leukemia Organization (FILO) study group including up to six out-patient mini-consolidation cycles for most patients although some patients may occasionally receive IDAC.\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e In a recent retrospective study, we compared both strategies in patients of the DATAML registry and showed no difference in RFS and OS.\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThe aim of this study was to compare the efficacy and tolerability of the mini-consolidations used in the French DATAML registry and IDAC used routinely by the German Study Alliance Leukemia (SAL) group in a larger series of AML patients\u0026thinsp;\u0026gt;\u0026thinsp;60 years in first complete remission after intensive induction chemotherapy. The primary objective was to compare OS in patients treated with mini-consolidations or IDAC. Secondary objectives were to compare RFS and cumulative incidence of relapse (CIR).\u003c/p\u003e"},{"header":"Subjects and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePatients\u003c/h2\u003e \u003cp\u003eThe inclusion criteria for this retrospective study were newly diagnosed AML between 01/01/2010 and 12/31/2019, age\u0026thinsp;\u0026gt;\u0026thinsp;60 years, first CR after one or two \u0026ldquo;3\u0026thinsp;+\u0026thinsp;7\" induction cycles, consolidation treatment with at least 1 cycle of mini-consolidation or IDAC. Patients with acute promyelocytic leukemia or AML with t(9;22)/\u003cem\u003eBCR::ABL1\u003c/em\u003e, patients treated with CPX-351 or patients who had received both types of consolidation (mini-consolidation and IDAC) were not included. A minimal data set extracted from DATAML and SAL registries included the variables age, sex, ECOG (eastern cooperative oncology group) performance status at diagnosis, history of cytotoxic treatment, date of diagnosis, AML status (de novo or secondary), white blood cell count, 2017 ELN risk classification, mutational status, nature of first-line therapy, allo-HSCT in first complete remission or after relapse, date of day 1 of first consolidation cycle, number of post-remission cycles, date of relapse and/or death. This study was performed in accordance with the Declaration of Helsinki. All registries were approved by institutional review boards or national authorities, and informed consent was obtained from all patients.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eTreatments and endpoints\u003c/h2\u003e \u003cp\u003eMini-consolidation treatment included cytarabine 50 mg/m\u0026sup2;/12h on days 1\u0026ndash;5 by subcutaneous injection and idarubicin 8 mg/m\u0026sup2; on day 1 performed on an outpatient basis (up to 6 cycles every 30 to 45 days). IDAC was cytarabine 1-1.5g/m\u0026sup2;/12h on days 1\u0026ndash;3 or 1, 3, 5 (up to 3 cycles). Allo-HSCT was proposed in eligible patients with intermediate or adverse risk AML according to local practices. CIR, RFS and OS were defined according to the European Leukemia Net (ELN) criteria.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003ePatients characteristics were described using numbers and frequencies for qualitative data, and median, interquartile range (IQR), and range (minimum\u0026thinsp;\u0026minus;\u0026thinsp;maximum) for quantitative data. Categorical variables were compared between IDAC and mini-consolidations arms using the chi2 test (or Fisher\u0026rsquo;s exact test when necessary). Student\u0026rsquo;s t test was used to compare the distributions of continuous data (Mann\u0026ndash;Whitney\u0026rsquo;s test was used when the distribution departed significantly from normality or when homoscedasticity was rejected). For OS and RFS, differences in survival functions between the IDAC and mini-consolidations arms were described using survival at 1, 3 and 5 years together with median with IQR and were tested using the log-rank test. For relapse (CIR), cumulative incidence functions were drawn (as non-relapse mortality was used as a competing event) and compared using Gray\u0026rsquo;s test. Adjusted hazard ratios (HR) and 95% confidence intervals (95%CI) were assessed using a standard Cox model for OS and RFS, and a proportional sub-distribution hazard model (an extension of the Cox model) for competing risks for CIR.\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e Multivariate analyses included IDAC versus mini-consolidations arms together with potential confounding factors [age, gender, performance status, WBC, 2017 ELN risk, secondary vs. de novo AML, \u003cem\u003eNPM1\u003c/em\u003e and \u003cem\u003eFLT3\u003c/em\u003e-ITD mutations, study period and allo-HSCT in first complete remission] associated with the endpoints (to the threshold of p\u0026thinsp;\u0026lt;\u0026thinsp;0.20). Stepwise regression analysis was then used to assess variables that were significantly and independently associated with the endpoints (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The proportional hazard assumption was tested for each covariate of the Cox model using log-log plot curves and was always supported. When the linear hypothesis was not supported, continuous potential confounding factors were transformed into ordered data. Interactions between all potential confounding factors and IDAC versus mini-consolidations were tested. None were significant, indicating that the effect of treatment (IDAC versus mini-consolidations) was not significantly different according to all confounding factors analyzed, especially according to age, 2017 ELN risk, \u003cem\u003eNPM1\u003c/em\u003e mutation or allo-HSCT in first CR. Allo-HSCT in first CR was evaluated as a time-dependent qualitative covariate. To better appreciate the impact of IDAC versus mini-consolidations, we used the propensity score method to more extensively take into account potential baseline differences between IDAC versus mini-consolidations arms. A multivariate logistic regression model was generated to estimate for each patient a propensity score to receive IDAC versus mini-consolidations. Covariates were all variables expected to be associated with IDAC versus mini-consolidations in clinical practice (age, gender, performance status, WBC, 2017 ELN risk, secondary vs. de novo AML, \u003cem\u003eNPM1\u003c/em\u003e and \u003cem\u003eFLT3\u003c/em\u003e-ITD mutations, study period, history of cytotoxic treatment, targeted therapy added to induction and inclusion in a clinical trial). The performance of the model was estimated with the chi2-Hosmer-Lemeshow statistic and the C-statistic. Based on propensity score, subjects with IDAC were matched with patients with mini-consolidations. In the subgroup of propensity score matched patients, endpoints were compared between IDAC and mini-consolidations arms, after adjustment for allo-HSCT (as time-dependent variable). All reported p-values were two-sided and the significance threshold was \u0026lt;\u0026thinsp;0.05. Statistical analyses were performed using STATA\u0026reg; version 18.0 (STATA Corp., College Station, TX).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStudy population\u003c/h2\u003e \u003cp\u003eThis retrospective study included 796 patients\u0026thinsp;\u0026gt;\u0026thinsp;60 years who had obtained a first CR after intensive induction chemotherapy between January 1, 2010 and December 31, 2019. Post remission therapy was mini-consolidations in 322 patients (40.5%) from the DATAML registry and IDAC in 474 patients (59.5%) from the SAL registry. Their characteristics are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Compared to patients treated with IDAC, patients treated with mini-consolidation were slightly older (47.5% \u0026gt;70 years vs. 40.1%; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.037), more often had de novo AML (81.4% vs. 75.3%; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.044) and adverse risk according to 2017 ELN classification (22% vs. 12%; \u003cem\u003eP\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.001). There were no differences in terms of sex, performance status at diagnosis, white blood cell (WBC) count, \u003cem\u003eFLT3\u003c/em\u003e-ITD or \u003cem\u003eNPM1\u003c/em\u003e mutations. Induction therapy consisted mainly of idarubicin-cytarabine-lomustine (76.4%) in the mini-consolidation group and daunorubicin-cytarabine (96%) in the IDAC group. Midostaurin was added to induction chemotherapy in 14 patients (4.3%) of the mini-consolidation group and 3 patients (0.6%) of the IDAC group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). There were 94 patients (29.2%) of the mini-consolidation group and 59 patients (12.4%) of the IDAC group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) included in a clinical trial at induction. The median number of consolidation cycles was 4 (IQR, 2\u0026ndash;6) with mini-consolidations and 2 (IQR, 1\u0026ndash;3) with IDAC (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). The rate of allo-HSCT was higher in the IDAC group both in first CR (18% vs. 12%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.019) and after relapse (31% vs. 10%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001).\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\u003cb\u003eCharacteristics of patients according to post remission therapy.\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMini-consolidations\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIDAC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e322 (40.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e474 (59.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e796 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex - n (%)\u003c/b\u003e\u003c/p\u003e \u003cp\u003eMale\u003c/p\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e178 (55.3)\u003c/p\u003e \u003cp\u003e144 (44.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e256 (54.0)\u003c/p\u003e \u003cp\u003e218 (46.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.723\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e434 (54.5)\u003c/p\u003e \u003cp\u003e362 (45.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eStudy period - n (%)\u003c/b\u003e\u003c/p\u003e \u003cp\u003e2010\u0026ndash;2014\u003c/p\u003e \u003cp\u003e2015\u0026ndash;2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e139 (43.2)\u003c/p\u003e \u003cp\u003e183 (56.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e260 (54.9)\u003c/p\u003e \u003cp\u003e214 (45.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e399 (50.1)\u003c/p\u003e \u003cp\u003e397 (49.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge (years)\u003c/b\u003e\u003c/p\u003e \u003cp\u003eMedian\u003c/p\u003e \u003cp\u003eMin;Max\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69.4\u003c/p\u003e \u003cp\u003e61.1; 82.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e69.0\u003c/p\u003e \u003cp\u003e61.0; 86.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e69.00\u003c/p\u003e \u003cp\u003e61.0; 86.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge (years) - n (%)\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u0026le;\u0026thinsp;70\u003c/p\u003e \u003cp\u003e\u0026gt;\u0026thinsp;70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e169 (52.5)\u003c/p\u003e \u003cp\u003e153 (47.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e284 (59.9)\u003c/p\u003e \u003cp\u003e190 (40.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.037\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e453 (56.9)\u003c/p\u003e \u003cp\u003e343 (43.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAML status - n (%)\u003c/b\u003e\u003c/p\u003e \u003cp\u003eDe novo\u003c/p\u003e \u003cp\u003eSecondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e262 (81.4)\u003c/p\u003e \u003cp\u003e60 (18.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e354 (75.3)\u003c/p\u003e \u003cp\u003e116 (24.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.044\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e616 (77.8)\u003c/p\u003e \u003cp\u003e176 (22.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHistory of cytotoxic treatment - n (%)\u003c/b\u003e\u003c/p\u003e \u003cp\u003eNone\u003c/p\u003e \u003cp\u003eChemotherapy\u003c/p\u003e \u003cp\u003eRadiotherapy\u003c/p\u003e \u003cp\u003eChemotherapy\u0026thinsp;+\u0026thinsp;radiotherapy\u003c/p\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e283 (87.9)\u003c/p\u003e \u003cp\u003e6 (1.9)\u003c/p\u003e \u003cp\u003e18 (5.6)\u003c/p\u003e \u003cp\u003e7 (2.2)\u003c/p\u003e \u003cp\u003e8 (2.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e435 (91.8)\u003c/p\u003e \u003cp\u003e22 (4.6)\u003c/p\u003e \u003cp\u003e11 (2.3)\u003c/p\u003e \u003cp\u003e6 (1.3)\u003c/p\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e718 (90.2)\u003c/p\u003e \u003cp\u003e28 (3.5)\u003c/p\u003e \u003cp\u003e29 (3.6)\u003c/p\u003e \u003cp\u003e13 (1.6)\u003c/p\u003e \u003cp\u003e8 (1.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePerformance status - n (%)\u003c/b\u003e\u003c/p\u003e \u003cp\u003e0\u0026ndash;1\u003c/p\u003e \u003cp\u003e2-3-4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e262 (83.2)\u003c/p\u003e \u003cp\u003e53 (16.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e381 (82.1)\u003c/p\u003e \u003cp\u003e83 (17.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.701\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e643 (82.5)\u003c/p\u003e \u003cp\u003e136 (17.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWBC (Giga/L)\u003c/b\u003e\u003c/p\u003e \u003cp\u003en /missing\u003c/p\u003e \u003cp\u003eMedian\u003c/p\u003e \u003cp\u003eIQR\u003c/p\u003e \u003cp\u003eMin;Max\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e321/1\u003c/p\u003e \u003cp\u003e5.2\u003c/p\u003e \u003cp\u003e2.1; 28.1\u003c/p\u003e \u003cp\u003e0.4;359.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e472/2\u003c/p\u003e \u003cp\u003e7.4\u003c/p\u003e \u003cp\u003e2.0;41.8\u003c/p\u003e \u003cp\u003e0.2;305.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.466\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e793/3\u003c/p\u003e \u003cp\u003e6.2\u003c/p\u003e \u003cp\u003e2.1;35.3\u003c/p\u003e \u003cp\u003e0.2;359.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWBC (Giga/L) - n (%)\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u0026lt;\u0026thinsp;30\u003c/p\u003e \u003cp\u003e\u0026ge;\u0026thinsp;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e243 (75.7)\u003c/p\u003e \u003cp\u003e78 (24.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e332 (70.3)\u003c/p\u003e \u003cp\u003e140 (29.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.096\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e575 (72.5)\u003c/p\u003e \u003cp\u003e218 (27.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2017 ELN risk - n (%)\u003c/b\u003e\u003c/p\u003e \u003cp\u003eFavorable\u003c/p\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003cp\u003eAdverse\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e98 (39.2)\u003c/p\u003e \u003cp\u003e96 (38.4)\u003c/p\u003e \u003cp\u003e56 (22.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e152 (34.8)\u003c/p\u003e \u003cp\u003e231 (52.9)\u003c/p\u003e \u003cp\u003e54 (12.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e250 (36.4)\u003c/p\u003e \u003cp\u003e327 (47.6)\u003c/p\u003e \u003cp\u003e110 (16.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFLT3\u003c/b\u003e\u003cb\u003e-ITD - n (%)\u003c/b\u003e\u003c/p\u003e \u003cp\u003eNo\u003c/p\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e223 (80.5)\u003c/p\u003e \u003cp\u003e54 (19.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e334 (80.7)\u003c/p\u003e \u003cp\u003e80 (19.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.955\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e557 (80.6)\u003c/p\u003e \u003cp\u003e134 (19.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNPM1\u003c/b\u003e \u003cb\u003emutation - n (%)\u003c/b\u003e\u003c/p\u003e \u003cp\u003eNo\u003c/p\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e161 (58.1)\u003c/p\u003e \u003cp\u003e116 (41.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e262 (59.8)\u003c/p\u003e \u003cp\u003e176 (40.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.653\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e423 (59.2)\u003c/p\u003e \u003cp\u003e292 (40.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInduction chemotherapy - n (%)\u003c/b\u003e\u003c/p\u003e \u003cp\u003eDaunorubicin-cytarabine\u003c/p\u003e \u003cp\u003eIdarubicin-cytarabine\u003c/p\u003e \u003cp\u003eIdarubicin-cytarabine-lomustine\u003c/p\u003e \u003cp\u003eDaunorubicin-cytarabine-GO\u003c/p\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (1.9)\u003c/p\u003e \u003cp\u003e65 (20.2)\u003c/p\u003e \u003cp\u003e246 (76.4)\u003c/p\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003cp\u003e5 (1.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e455 (96.0)\u003c/p\u003e \u003cp\u003e1 (0.2)\u003c/p\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003cp\u003e2 (0.4)\u003c/p\u003e \u003cp\u003e16 (3.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e461 (57.9)\u003c/p\u003e \u003cp\u003e66 (8.3)\u003c/p\u003e \u003cp\u003e246 (30.9)\u003c/p\u003e \u003cp\u003e2 (0.3)\u003c/p\u003e \u003cp\u003e21 (2.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eClinical trial - n (%)\u003c/b\u003e\u003c/p\u003e \u003cp\u003eNo\u003c/p\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e228 (70.8)\u003c/p\u003e \u003cp\u003e94 (29.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e415 (87.6)\u003c/p\u003e \u003cp\u003e59 (12.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e643 (80.8)\u003c/p\u003e \u003cp\u003e153 (19.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eIQR, Inter-Quartile Range; Min, Minimum; Max, Maximum; WBC, white blood cell count; ELN, European LeukemiaNet; GO, gemtuzumab ozogamycin.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eOverall survival\u003c/h2\u003e \u003cp\u003eThe median follow-up was 61 months (inter quartile range, IQR, 40\u0026ndash;81) for the whole population, 63 (IQR, 50\u0026ndash;74) in the mini-consolidation group and 58 months (IQR, 28\u0026ndash;87) in the IDAC group. Median OS was 36 (IQR, 14\u0026ndash;109) and 31 months (IQR, 14\u0026ndash;99) in the mini-consolidation and IDAC groups, respectively (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.46) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). OS at 1, 3 and 5 years was 80% (95% confidence interval [CI]: 75\u0026ndash;84) vs. 81% (95%CI: 77\u0026ndash;84), 51 (95%CI: 45\u0026ndash;56) vs. 46% (95%CI: 41\u0026ndash;51) and 35% (95%CI: 29\u0026ndash;40) vs 34% (95%CI: 29\u0026ndash;39) in the mini-consolidation and IDAC groups, respectively. Univariate and multivariate analysis are shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. In the multivariate analysis, consolidation type was not significantly and independently associated with OS (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.425). Adjustment for the number of consolidation cycles (\u0026lt;\u0026thinsp;2 \u003cem\u003evs.\u003c/em\u003e \u0026ge;2) did not modify the impact of consolidation type (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.575)\u003c/p\u003e \u003cp\u003e \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\u003eUnivariate and multivariate analyses for overall survival\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003eUnivariate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c9\" namest=\"c7\"\u003e \u003cp\u003eMultivariate\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEvents\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTreatment\u003c/p\u003e \u003cp\u003eMini-consolidations\u003c/p\u003e \u003cp\u003eIDAC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e322\u003c/p\u003e \u003cp\u003e474\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e203\u003c/p\u003e \u003cp\u003e269\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e1.07\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.89;1.29\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.464\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e1.08\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.89;1.31\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.425\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\u003eStudy period\u003c/b\u003e\u003c/p\u003e \u003cp\u003e2010\u0026ndash;2014\u003c/p\u003e \u003cp\u003e2015\u0026ndash;2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e399\u003c/p\u003e \u003cp\u003e397\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e272\u003c/p\u003e \u003cp\u003e200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e0.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.69;0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.041\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e \u003cp\u003eMale\u003c/p\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e434\u003c/p\u003e \u003cp\u003e362\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e261\u003c/p\u003e \u003cp\u003e211\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.83;1.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.969\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge (years)\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u0026le;\u0026thinsp;70\u003c/p\u003e \u003cp\u003e\u0026gt;\u0026thinsp;70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e453\u003c/p\u003e \u003cp\u003e343\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e251\u003c/p\u003e \u003cp\u003e221\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e1.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.09;1.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e1.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.12;1.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAML status\u003c/b\u003e\u003c/p\u003e \u003cp\u003eDe novo\u003c/p\u003e \u003cp\u003eSecondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e616\u003c/p\u003e \u003cp\u003e176\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e353\u003c/p\u003e \u003cp\u003e115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e1.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.95;1.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePerformance status at diagnosis\u003c/b\u003e\u003c/p\u003e \u003cp\u003e0\u0026ndash;1\u003c/p\u003e \u003cp\u003e2-3-4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e643\u003c/p\u003e \u003cp\u003e136\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e374\u003c/p\u003e \u003cp\u003e88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e1.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.09;1.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e1.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.06;1.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWBC (G/L)\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u0026lt;\u0026thinsp;30\u003c/p\u003e \u003cp\u003e\u0026ge;\u0026thinsp;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e575\u003c/p\u003e \u003cp\u003e218\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e328\u003c/p\u003e \u003cp\u003e141\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e1.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.04;1.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e1.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.00;1.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.050\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2017 ELN risk\u003c/b\u003e\u003c/p\u003e \u003cp\u003eFavorable\u003c/p\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003cp\u003eAdverse\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e250\u003c/p\u003e \u003cp\u003e327\u003c/p\u003e \u003cp\u003e110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e127\u003c/p\u003e \u003cp\u003e207\u003c/p\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e1.33\u003c/p\u003e \u003cp\u003e1.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.07;1.66\u003c/p\u003e \u003cp\u003e1.30;2.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e1.39\u003c/p\u003e \u003cp\u003e1.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.11;1.74\u003c/p\u003e \u003cp\u003e1.34;2.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFLT3\u003c/b\u003e\u003cb\u003e-ITD\u003c/b\u003e\u003c/p\u003e \u003cp\u003eNo\u003c/p\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e557\u003c/p\u003e \u003cp\u003e134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e328\u003c/p\u003e \u003cp\u003e83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e1.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.90;1.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.283\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNPM1\u003c/b\u003e \u003cb\u003emutation\u003c/b\u003e\u003c/p\u003e \u003cp\u003eNo\u003c/p\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e423\u003c/p\u003e \u003cp\u003e292\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e262\u003c/p\u003e \u003cp\u003e157\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.66;0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAllo-HSCT\u003c/b\u003e\u003c/p\u003e \u003cp\u003eNo\u003c/p\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e676\u003c/p\u003e \u003cp\u003e120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e410\u003c/p\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e0.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.62;1.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.139\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003eHR, hazard ratio; CI, confidence interval; WBC, white blood cell count; ELN, European LeukemiaNet; Allo-HSCT, allogeneic hematopoietic stem cell transplantation.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eCumulative incidence of relapse and relapse free survival\u003c/h2\u003e \u003cp\u003eIn the mini-consolidation group, 209 patients relapsed and the CIR was 39%, 56% and 62% at 1, 2 and 3 years, respectively. In the IDAC group, 302 patients relapsed and the CIR was 44%, 61% and 67% at 1, 2 and 3 years, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). Univariate and multivariate analyses for CIR are shown in Supplementary Table\u0026nbsp;1. In multivariate analysis, the relapse risk was significantly and independently higher in patients treated with IDAC (HR 1.30, 95%CI: 1.1\u0026ndash;1.6; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.006). Adjustment for the number of consolidation cycles did not modify the impact of IDAC on the relapse risk (HR 1.28, 95%CI: 1.1\u0026ndash;1.5; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.012).\u003c/p\u003e \u003cp\u003eMedian RFS was 18 (IQR, 7\u0026ndash;75) and 12 months (IQR, 7\u0026ndash;33) in the mini-consolidation and IDAC groups, respectively (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.006) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC). RFS at 1, 3 and 5 years was 60% (95%CI: 54\u0026ndash;65) vs. 50% (95%CI: 45\u0026ndash;54), 33% (95%CI: 28\u0026ndash;38) vs. 24% (95%CI: 20\u0026ndash;28) and 27% (95%CI: 22\u0026ndash;32) vs 19% (95%CI: 15\u0026ndash;23) in the mini-consolidation and IDAC groups, respectively. Univariate and multivariate analysis are shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. In multivariate analysis, the risk of relapse or death was significantly and independently higher in patients treated with IDAC (HR 1.29, 95%CI: 1.1\u0026ndash;1.5; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.004). Adjustment for the number of consolidation cycles did not modify the impact of IDAC on RFS (HR 1.26, 95%CI: 1.1\u0026ndash;1.5; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.011)\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUnivariate and multivariate analyses for relapse-free survival\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003eUnivariate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c9\" namest=\"c7\"\u003e \u003cp\u003eMultivariate\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEvents\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTreatment\u003c/p\u003e \u003cp\u003eMini-consolidations\u003c/p\u003e \u003cp\u003eIDAC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e322\u003c/p\u003e \u003cp\u003e474\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e233\u003c/p\u003e \u003cp\u003e349\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e1.26\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.07;1.49\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e1.29\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.09;1.54\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.004\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\u003eStudy period\u003c/b\u003e\u003c/p\u003e \u003cp\u003e2010\u0026ndash;2014\u003c/p\u003e \u003cp\u003e2015\u0026ndash;2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e399\u003c/p\u003e \u003cp\u003e397\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e314\u003c/p\u003e \u003cp\u003e265\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.74;1.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.089\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e \u003cp\u003eMale\u003c/p\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e434\u003c/p\u003e \u003cp\u003e362\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e319\u003c/p\u003e \u003cp\u003e263\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.83;1.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.803\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge (years)\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u0026le;\u0026thinsp;70\u003c/p\u003e \u003cp\u003e\u0026gt;\u0026thinsp;70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e453\u003c/p\u003e \u003cp\u003e343\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e317\u003c/p\u003e \u003cp\u003e265\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e1.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.03;1.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAML status\u003c/b\u003e\u003c/p\u003e \u003cp\u003eDe novo\u003c/p\u003e \u003cp\u003eSecondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e616\u003c/p\u003e \u003cp\u003e176\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e445\u003c/p\u003e \u003cp\u003e133\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e1.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.94;1.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.170\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePerformance status at diagnosis\u003c/b\u003e\u003c/p\u003e \u003cp\u003e0\u0026ndash;1\u003c/p\u003e \u003cp\u003e2-3-4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e643\u003c/p\u003e \u003cp\u003e136\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e467\u003c/p\u003e \u003cp\u003e102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e1.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.99;1.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.066\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWBC (G/L)\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u0026lt;\u0026thinsp;30\u003c/p\u003e \u003cp\u003e\u0026ge;\u0026thinsp;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e575\u003c/p\u003e \u003cp\u003e218\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e411\u003c/p\u003e \u003cp\u003e168\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e1.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.99;1.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.072\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e1.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.03;1.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.026\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2017 ELN risk\u003c/b\u003e\u003c/p\u003e \u003cp\u003eFavorable\u003c/p\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003cp\u003eAdverse\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e250\u003c/p\u003e \u003cp\u003e327\u003c/p\u003e \u003cp\u003e110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e171\u003c/p\u003e \u003cp\u003e247\u003c/p\u003e \u003cp\u003e84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e1.16\u003c/p\u003e \u003cp\u003e1.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.95;1.41\u003c/p\u003e \u003cp\u003e1.08;1.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.145\u003c/p\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e*\u003c/p\u003e \u003cp\u003e1.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.02;1.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.032\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFLT3\u003c/b\u003e\u003cb\u003e-ITD\u003c/b\u003e\u003c/p\u003e \u003cp\u003eNo\u003c/p\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e557\u003c/p\u003e \u003cp\u003e134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e413\u003c/p\u003e \u003cp\u003e99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e1.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.88;1.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.435\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNPM1\u003c/b\u003e \u003cb\u003emutation\u003c/b\u003e\u003c/p\u003e \u003cp\u003eNo\u003c/p\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e423\u003c/p\u003e \u003cp\u003e292\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e325\u003c/p\u003e \u003cp\u003e200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e0.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.68;0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.62;0.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAllo-HSCT\u003c/b\u003e\u003c/p\u003e \u003cp\u003eNo\u003c/p\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e676\u003c/p\u003e \u003cp\u003e120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e510\u003c/p\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e0.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.53;0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.46;0.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003eHR, hazard ratio; CI, confidence interval; WBC, white blood cell count; ELN, European LeukemiaNet; Allo-HSCT, allogeneic hematopoietic stem cell transplantation.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e* adverse \u003cem\u003evs.\u003c/em\u003e favorable/intermediate (=\u0026thinsp;1).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003ePropensity score matching\u003c/h2\u003e \u003cp\u003eTo better appreciate the impact of mini-consolidations vs. IDAC on OS, CIR, and RFS we used the propensity score method to take into account potential baseline differences between patients treated with mini-consolidations in the DATAML registry and those treated with IDAC in the SAL registry. A multivariate logistic regression model was generated to estimate for each patient a propensity score to receive mini-consolidations or IDAC. Covariates were all variables expected to be associated with mini-consolidations vs. IDAC (age, gender, performance status, WBC, 2017 ELN risk, secondary vs. de novo AML, \u003cem\u003eNPM1\u003c/em\u003e and \u003cem\u003eFLT3\u003c/em\u003e-ITD mutations, study period, history of cytotoxic treatment, targeted therapy added to induction and inclusion in a clinical trial). The performance of the model was appreciated with the χ\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e-Hosmer-Lemeshow statistic (p-value\u0026thinsp;=\u0026thinsp;0.456) and the c-statistic (0.73, 95%CI: 0.69\u0026ndash;0.76). Mean propensity score was 0.503 (\u0026plusmn;\u0026thinsp;0.209) in the mini-consolidation group (n\u0026thinsp;=\u0026thinsp;322) and 0.341 (\u0026plusmn;\u0026thinsp;0.162) in the IDAC group (n\u0026thinsp;=\u0026thinsp;470). According to the propensity score, 214 subjects treated with mini-consolidations were matched with 214 subjects with IDAC (206 with a precision of 0.0001, 6 with a precision of 0.001, 64 with a precision of 0.01 and 152 with a precision of 0.1). Mean propensity score was the same in both groups (0.407\u0026thinsp;\u0026plusmn;\u0026thinsp;0.161) in the matched sample. OS, CIR, and RFS were compared between mini-consolidation and IDAC treatment in the subgroup of propensity score matched patients after adjustment for allo-HSCT (as time-dependent variable). The results remained unchanged compared with the findings of the multivariate analyses in the whole patient population (Supplementary Table\u0026nbsp;2).\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study comparing two therapeutic strategies for post-remission therapy showed that mini-consolidations including a single anthracycline-dose and standard dose of cytarabine represent an alternative to the recommended IDAC regimen in AML patients older than 60 years who are in first CR after induction chemotherapy. Of note, no significant interaction between treatment (mini-consolidations vs. IDAC) and classical confounding factors was found, indicating that the effect of consolidation regimen was not different in subgroups and in particular according to age, 2017 ELN risk, \u003cem\u003eNPM1\u003c/em\u003e mutation or allo-HSCT (analyzed as a time-dependent variable).\u003c/p\u003e \u003cp\u003eAlthough overall survival was similar with both strategies, the post remission therapy with mini-consolidations was associated with a lower incidence of relapses and a better relapse free survival. The explanations for this difference are unclear. Despite adjustment for the number of cycles, it is possible that the higher number of treatment cycles in the mini-consolidation group contributed to this result by increasing the duration of exposure to genotoxic treatment. A similar finding was observed in the randomized trial of the ALFA group comparing 6 cycles of mini-consolidations and a single intensive chemotherapy cycle in patients older than 65 years.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e Alternatively, the synergistic combination of standard dose cytarabine and idarubicin could have induce a stronger anti-leukemic activity on residual disease. In younger AML patients, multidrug regimens combining anthracyclines and IDAC or HDAC have shown similar or even greater efficacy than IDAC/HDAC, notably in high-risk patients, but with increased toxicity.\u003csup\u003e\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e Lastly, differences in induction chemotherapy may also have played a role. Lomustine used in patients of the DATAML registry has been associated with better outcome in older AML patients while comparisons between idarubicin and daunorubicin yielded heterogeneous results.\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e However, effective salvage options and equally distributed genetically determined disease biology in both treatment groups led to similar overall survival in the long term.\u003c/p\u003e \u003cp\u003eDemonstrating a similar outcome of mini consolidations over IDAC in terms of OS may have important implications. Indeed, two recent studies by the DATAML registry in France showed that mini-consolidations were associated with a considerable reduction in infection rates, pancytopenia duration, transfusion requirements and hospitalization stays compared to IDAC. Patients receiving mini-consolidations spent on average 20 days less in hospital over the whole period of post-remission treatment.\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e Importantly, an economic analysis performed from the French National Health Insurance perspective and focused on costs associated with inpatient stays, showed that the mini-consolidation strategy could save up to 30,000 euros per patient compared to IDAC in the French health care system.\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e Comparing the two approaches, we can conclude that patients can be treated on an outpatient basis, are longer on treatment and increase their cumulative anthracyclin dose with mini-consolidation. On the other hand, total treatment time with IDAC is shorter, associated with more pronounced cytopenia, and usually requiring inpatient treatment.\u003c/p\u003e \u003cp\u003eThe limitations of this study include its retrospective and non-randomized nature. There was heterogeneity in induction chemotherapy regimen and we also recognize that the number of six mini-consolidation cycles has not been established by clinical trials but rather by clinical practice, and therefore the optimal number of mini-consolidation cycles is yet to be defined. Moreover, maintenance therapy with oral azacitidine was not approved during the study period and we can only speculate that this treatment might have limited the risk of relapse after IDAC in our study.\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e Nevertheless, the multivariate analysis based on a large cohort of patients (n\u0026thinsp;=\u0026thinsp;796) and the propensity score enables us to draw reliable conclusions on the absence of difference between the two strategies in terms of OS.\u003c/p\u003e \u003cp\u003eConsolidation treatment of older AML patients remains an evolving field with the advent of new drugs and the widespread use of allo-HSCT and maintenance. It should deepen the response to induction therapy without triggering major toxicity. The OS results of our study show the curative potential of current state-of-the-art chemotherapy and at the same time demonstrate the need for further improvement. In this respect, it may be worth exploring whether either or both consolidation approaches may be suited for the addition of new drugs such as venetoclax or quizartinib without excessive hematological toxicity and/or the replacement of anthracyclines to further increase the curative potential and proportion of long-term survivors diagnosed with AML.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to thank the data management unit of Toulouse University Hospital as well as the central study office and all member sites of the Study Alliance Leukemia (SAL) study group.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCR, PYD, EB, ST, TL,\u003csup\u003e\u0026nbsp;\u003c/sup\u003eJG, CA, AB, ED, JBR,\u003csup\u003e\u0026nbsp;\u003c/sup\u003eJPV,\u003csup\u003e\u0026nbsp;\u003c/sup\u003eFV,\u003csup\u003e\u0026nbsp;\u003c/sup\u003eIL, EK, ACdG, AS, SZ,\u003csup\u003e\u0026nbsp;\u003c/sup\u003eUP, CMT, CB, MB, HS, SB, AP, CR\u0026ouml;, collected data, treated patients or performed biological analyses. EB performed statistical analysis and wrote the paper. CR collected data, treated patients, supervised analysis and wrote the paper.\u0026nbsp;All authors reviewed, provided comments and approved the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eChristian R\u0026eacute;cher declares a consulting or advisory role with Abbvie, Amgen, Astellas, BMS, Boehringer, Jazz Pharmaceuticals, J\u0026amp;J as well as Servier, received research funding from Abbvie, Amgen, Astellas, BMS, Iqvia and Jazz Pharmaceuticals, and support for attending meetings and/or travel from Abbvie, Novartis and Servier.\u003c/p\u003e\n\u003cp\u003ePierre-Yves Dumas declares a consulting or advisory role for Daiichi-Sankyo, Astellas, Novartis, Abbvie, Servier, BMS, Jazz Pharmaceutical, Janssen, received research funding (to institution) from Daiichi-Sankyo, Astellas, Novartis, Servier, BMS, Roche, Iqvia and support for attending meetings and/or travel from Abbvie, Gilead and Lilly.\u003c/p\u003e\n\u003cp\u003eFran\u0026ccedil;ois Vergez declares research grants from Pierre Fabre and Roche; advisor for Astellas and Amgen.\u003c/p\u003e\n\u003cp\u003eUwe Platzbecker declares Honoraria and Research support from BMS, Abbvie, Curis, Jazz and Ryvu.\u003c/p\u003e\n\u003cp\u003eIsabelle Luquet declares an advisory role for Jazz Pharmaceuticals.\u003c/p\u003e\n\u003cp\u003eCarsten M\u0026uuml;ller-Tidow declares institutional research funding from Pfizer and BiolineRx. LR declares institutional research funding from AbbVie and honoraria from BeiGene, Jazz, Neovii.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eClaudia Baldus declares advisory honoraria from Astellas, Bristol-Meyer-Squibb, Jazz, Janssen, Pfizer, Servier, Amgen, Astra Zeneca.\u003c/p\u003e\n\u003cp\u003eMartin Bornh\u0026auml;user declares honoraria from Jazz Pharmaceuticals Advisory Board: ActiTrexx; employment by University Hospital TU Dresden, King\u0026apos;s College London.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSarah Bertoli declares a consulting or advisory role with Abbvie, Astellas, BMS-Celgene, Jazz Pharmaceuticals as well as Servier and received travel grants from Abbvie and Pfizer.\u003c/p\u003e\n\u003cp\u003eArnaud Pigneux declares a consulting or advisory role with Astellas, BMS, Servier, Abbvie, Gilead, Jazz Pharmaceuticals, Novartis, Pfizer, received research funding from Astellas, BMS, Roche, Servier and support for attending meetings and/or travel from Servier, Abbvie.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eChristoph R\u0026ouml;llig declares institutional research funding by AbbVie, Novartis, and Pfizer and advisory honoraria from AbbVie, Astellas, Bristol-Meyer-Squibb, Jazz, Janssen, Novartis, Otsuka, Pfizer, Servier.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll other authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eD\u0026ouml;hner H, Wei AH, Appelbaum FR, Craddock C, DiNardo CD, Dombret H, \u003cem\u003eet al.\u003c/em\u003e Diagnosis and management of AML in adults: 2022 recommendations from an international expert panel on behalf of the ELN. 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Blood 2017; 129(4): 424\u0026ndash;447.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePigneux A, B\u0026eacute;n\u0026eacute; MC, Salmi LR, Dumas PY, Delaunay J, Bonmati C, \u003cem\u003eet al.\u003c/em\u003e Improved Survival by Adding Lomustine to Conventional Chemotherapy for Elderly Patients With AML Without Unfavorable Cytogenetics: Results of the LAM-SA 2007 FILO Trial. J Clin Oncol 2018; 36(32): 3203\u0026ndash;3210.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePigneux A, B\u0026eacute;n\u0026eacute; MC, Guardiola P, Recher C, Hamel JF, Sauvezie M, \u003cem\u003eet al.\u003c/em\u003e Addition of Androgens Improves Survival in Elderly Patients With Acute Myeloid Leukemia: A GOELAMS Study. J Clin Oncol 2017; 35(4): 387\u0026ndash;393.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGaltier J, Alric C, B\u0026eacute;rard E, Leguay T, Tavitian S, Bidet A, \u003cem\u003eet al.\u003c/em\u003e Intermediate-dose cytarabine or standard-dose cytarabine plus single-dose anthracycline as post-remission therapy in older patients with acute myeloid leukemia: impact on health care resource consumption and outcomes. Blood Cancer J 2021; 11(11): 180.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFine JP, Gray RJ. A Proportional Hazards Model for the Subdistribution of a Competing Risk. Journal of the American Statistical Association 1999; 94(446): 496\u0026ndash;509.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMiyawaki S, Ohtake S, Fujisawa S, Kiyoi H, Shinagawa K, Usui N, \u003cem\u003eet al.\u003c/em\u003e A randomized comparison of 4 courses of standard-dose multiagent chemotherapy versus 3 courses of high-dose cytarabine alone in postremission therapy for acute myeloid leukemia in adults: the JALSG AML201 Study. Blood 2011; 117(8): 2366\u0026ndash;2372.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBurnett AK, Russell NH, Hills RK, Hunter AE, Kjeldsen L, Yin J, \u003cem\u003eet al.\u003c/em\u003e Optimization of Chemotherapy for Younger Patients With Acute Myeloid Leukemia: Results of the Medical Research Council AML15 Trial. Journal of Clinical Oncology 2013; 31(27): 3360\u0026ndash;3368.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchaich M, Parmentier S, Kramer M, Illmer T, St\u0026ouml;lzel F, R\u0026ouml;llig C, \u003cem\u003eet al.\u003c/em\u003e High-dose cytarabine consolidation with or without additional amsacrine and mitoxantrone in acute myeloid leukemia: results of the prospective randomized AML2003 trial. J Clin Oncol 2013; 31(17): 2094\u0026ndash;2102.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGardin C, Chevret S, Pautas C, Turlure P, Raffoux E, Thomas X, \u003cem\u003eet al.\u003c/em\u003e Superior long-term outcome with idarubicin compared with high-dose daunorubicin in patients with acute myeloid leukemia age 50 years and older. J Clin Oncol 2013; 31(3): 321\u0026ndash;327.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTeuffel O, Leibundgut K, Lehrnbecher T, Alonzo TA, Beyene J, Sung L. Anthracyclines during induction therapy in acute myeloid leukaemia: a systematic review and meta-analysis. Br J Haematol 2013; 161(2): 192\u0026ndash;203.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi X, Xu S, Tan Y, Chen J. The effects of idarubicin versus other anthracyclines for induction therapy of patients with newly diagnosed leukaemia. \u003cem\u003eCochrane Database Syst Rev\u003c/em\u003e 2015; (6): Cd010432.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMounie M, Dumas PY, Liva-Yonnet S, Fabre D, Leguay T, Galtier J, \u003cem\u003eet al.\u003c/em\u003e Cost comparison of post-remission strategies in younger and older AML patients in France. Blood Cancer J 2023; 13(1): 100.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWei AH, D\u0026ouml;hner H, Pocock C, Montesinos P, Afanasyev B, Dombret H, \u003cem\u003eet al.\u003c/em\u003e Oral Azacitidine Maintenance Therapy for Acute Myeloid Leukemia in First Remission. N Engl J Med 2020; 383(26): 2526\u0026ndash;2537.\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":"Acute myeloid leukemia, intensive chemotherapy, consolidation, post-remission therapy, cytarabine, supportive care, older patients.","lastPublishedDoi":"10.21203/rs.3.rs-4453206/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4453206/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAccording to current recommendations, older AML patients in first complete remission (CR) after induction chemotherapy should receive consolidation with intermediate-dose cytarabine (IDAC). However, no study has demonstrated the superiority of IDAC over other regimen. In this retrospective study, we compared the efficacy of mini-consolidations (idarubicin 8 mg/m\u0026sup2; day 1, cytarabine 50 mg/m\u0026sup2;/12 hours, day 1\u0026ndash;5) and IDAC. Inclusion criteria were newly diagnosed AML, age\u0026thinsp;\u0026gt;\u0026thinsp;60 years, first CR after induction and at least 1 cycle of consolidation. Of the 796 included patients, 322 patients received mini-consolidations and 474 patients received IDAC. Mini-consolidation patients were older, more often had de novo AML and unfavorable risk. The rate of allogeneic transplantation was higher in the IDAC group. The median number of cycles was higher in the mini-consolidation group (4 vs 2; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). Median relapse-free survival was 18 months with mini-consolidations and 12 months with IDAC (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0064). In multivariate analysis, the risk of relapse or death was significantly higher in the IDAC group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.004). Median OS was 36 vs. 31 months with mini-consolidations or IDAC, respectively (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.46). In multivariate analysis, the consolidation regimen had no significant influence on OS (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.43). In older AML patients, post-remission therapy with mini-consolidations represents an alternative to IDAC.\u003c/p\u003e","manuscriptTitle":"Mini-consolidations or intermediate-dose cytarabine (IDAC) for the post-remission therapy of AML patients over 60. A retrospective study from the DATAML and SAL registries.","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-10 22:34:01","doi":"10.21203/rs.3.rs-4453206/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":"3a330164-ff4f-4027-990f-57d6a14c1c5c","owner":[],"postedDate":"June 10th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":32378343,"name":"Health sciences/Diseases/Haematological diseases/Haematological cancer/Leukaemia/Acute myeloid leukaemia"},{"id":32378344,"name":"Health sciences/Health care/Therapeutics/Drug therapy/Chemotherapy"}],"tags":[],"updatedAt":"2024-06-20T11:31:08+00:00","versionOfRecord":[],"versionCreatedAt":"2024-06-10 22:34:01","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4453206","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4453206","identity":"rs-4453206","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}