Venetoclax combined with intensive chemotherapy proved to be safe with promising activity in fit patients with no-low-risk newly diagnosed acute myeloid leukemia (AML), as demonstrated also by an intermediate analysis of the GIMEMA AML1718 trial (NCT03455504). The latter trial, still ongoing, is based on the administration of venetoclax-FLAI to intermediate/high-risk ELN2017 AML and produced a complete remission (CR) rate of 84%, a minimal residual disease (MRD)-negativity rate of 74% and a 12-month Overall Survival (OS) and disease-free survival (DFS) of 75.7% (95%CI: 64.1%, 89.5%) and 80.7% (95%CI: 67.9%, 95.9%), respectively. In order to evaluate the actual advantage of the addition of venetoclax to chemotherapy, the GIMEMA AML1718 was matched to AML1310, which entailed a "3+7"-like induction and a risk-adapted, MRD-directed post-remission transplant allocation (NCT01452646, Venditti et al - Blood 2019). To generate a reliable comparison, AML1718 and AML1310 were matched by using a propensity score and then compared in terms of CR achievement, MRD-negativity and survival outcomes. Patient-level data from GIMEMA AML1718 (n=57) and AML1310 (N=445) with ELN2017 risk classification available were used to conduct a propensity score matching analysis, widely used for reducing the effects of confounding when estimating the effects of treatment on outcomes. Conditional on the propensity score, the distribution of measured variables is expected to be the same in treated (i.e. AML1718) and control (i.e. AML1310) subjects. In the present propensity score model, we included the following variables: age at diagnosis, gender, ELN2017 risk classification and transplant. Different methods for matching were attempted, including 1:1 nearest neighbor, full-matching, optimal matching (1:2, 1:3 and 1:4) and 1:2 genetic matching. The methods employed for assessing balancing were: i) Standardized Mean Difference - Love plot, ii) Empirical cumulative density function, iii) Variance ratio, iv) Empirical QQ-plot. Weights were calculated with probit or logit regression models according to the propensity score method used. Weights obtained from full-matching were used to adjust outcomes (CR, MRD negativity and survival outcomes). No patients were dropped in the full-matching process. A standardized bias score less than 0.25 was used as a criterion for adequate balancing. We used balance tables and Love plots to assess for covariate balance before and after matching. Survival curves were compared by Log-rank test and Restricted Mean Survival Time (RMST) at 12 months. AML1718 and AML1310 cohorts differed in terms of age (median: 54 vs 49 years, p=0.003) and risk category (p< .0001) - since the low risk was not represented in AML1718 trial - and female sex (35% vs 48%, p=0.069), though to a lesser extent. Contrariwise, the percentage of transplanted patients was comparable before matching (49% vs 49%, p=0.96). Being more recent, AML1718 median follow-up was shorter than AML1310 (10.5 vs 75.8 months). Full-matching, 1:2 optimal matching and 1:2 genetic matching produced the best balancing. Table 1 shows the results of the analysis for the unmatched and matched data. After balancing, according to all matching methods, the CR rate observed in the AML1718 was significantly higher than AML1310, as well as MRD-negativity rate. Comparing survival outcomes at 12 months, emerged that, upon matching, OS and DFS estimates of the AML1718 were higher than those of AML1310, though a slight statistical significance was reached only with the optimal matching on DFS (p=0.042). This result was confirmed by a statistically significant difference between the two RMST at 12 months (p=0.036). Despite this, a longer AML1718 follow-up is needed to provide a robust comparison between the two protocols. Our propensity-score analysis showed that combining venetoclax with chemotherapy in newly diagnosed AML patients resulted in improved outcomes in terms of CR rate and MRD-negativity: these achievements are crucial to allow transition to allogenic transplantation in first remission. With regards to survival outcomes, a solid conclusion will be drawn when a longer AML1718 follow-up is available. These preliminary results highlight the incremental benefit of venetoclax added to intensive induction chemotherapy and paves the way to novel combination regimens based on venetoclax.

The Addition of Venetoclax to Induction Chemotherapy in No Low-Risk AML Patients: A Propensity Score-Matched Analysis of the Gimema AML1718 and AML1310 Trials / Piciocchi, Alfonso; Messina, Monica; Cipriani, Marta; Paoloni, Francesca; Simonetti, Giorgia; Palmieri, Raffaele; Marconi, Giovanni; Buccisano, Francesco; Fazi, Paola; Vignetti, Marco; Martinelli, Giovanni; Venditti, Adriano. - In: BLOOD. - ISSN 0006-4971. - 140:Supplement 1(2022), pp. 137-138. (Intervento presentato al convegno 64th ASH Annual Meeting and Exposition tenutosi a New Orleans; Louisiana) [10.1182/blood-2022-158890].

The Addition of Venetoclax to Induction Chemotherapy in No Low-Risk AML Patients: A Propensity Score-Matched Analysis of the Gimema AML1718 and AML1310 Trials

Piciocchi, Alfonso;Messina, Monica;Cipriani, Marta;Paoloni, Francesca;Simonetti, Giorgia;Marconi, Giovanni;Fazi, Paola;Vignetti, Marco;
2022

Abstract

Venetoclax combined with intensive chemotherapy proved to be safe with promising activity in fit patients with no-low-risk newly diagnosed acute myeloid leukemia (AML), as demonstrated also by an intermediate analysis of the GIMEMA AML1718 trial (NCT03455504). The latter trial, still ongoing, is based on the administration of venetoclax-FLAI to intermediate/high-risk ELN2017 AML and produced a complete remission (CR) rate of 84%, a minimal residual disease (MRD)-negativity rate of 74% and a 12-month Overall Survival (OS) and disease-free survival (DFS) of 75.7% (95%CI: 64.1%, 89.5%) and 80.7% (95%CI: 67.9%, 95.9%), respectively. In order to evaluate the actual advantage of the addition of venetoclax to chemotherapy, the GIMEMA AML1718 was matched to AML1310, which entailed a "3+7"-like induction and a risk-adapted, MRD-directed post-remission transplant allocation (NCT01452646, Venditti et al - Blood 2019). To generate a reliable comparison, AML1718 and AML1310 were matched by using a propensity score and then compared in terms of CR achievement, MRD-negativity and survival outcomes. Patient-level data from GIMEMA AML1718 (n=57) and AML1310 (N=445) with ELN2017 risk classification available were used to conduct a propensity score matching analysis, widely used for reducing the effects of confounding when estimating the effects of treatment on outcomes. Conditional on the propensity score, the distribution of measured variables is expected to be the same in treated (i.e. AML1718) and control (i.e. AML1310) subjects. In the present propensity score model, we included the following variables: age at diagnosis, gender, ELN2017 risk classification and transplant. Different methods for matching were attempted, including 1:1 nearest neighbor, full-matching, optimal matching (1:2, 1:3 and 1:4) and 1:2 genetic matching. The methods employed for assessing balancing were: i) Standardized Mean Difference - Love plot, ii) Empirical cumulative density function, iii) Variance ratio, iv) Empirical QQ-plot. Weights were calculated with probit or logit regression models according to the propensity score method used. Weights obtained from full-matching were used to adjust outcomes (CR, MRD negativity and survival outcomes). No patients were dropped in the full-matching process. A standardized bias score less than 0.25 was used as a criterion for adequate balancing. We used balance tables and Love plots to assess for covariate balance before and after matching. Survival curves were compared by Log-rank test and Restricted Mean Survival Time (RMST) at 12 months. AML1718 and AML1310 cohorts differed in terms of age (median: 54 vs 49 years, p=0.003) and risk category (p< .0001) - since the low risk was not represented in AML1718 trial - and female sex (35% vs 48%, p=0.069), though to a lesser extent. Contrariwise, the percentage of transplanted patients was comparable before matching (49% vs 49%, p=0.96). Being more recent, AML1718 median follow-up was shorter than AML1310 (10.5 vs 75.8 months). Full-matching, 1:2 optimal matching and 1:2 genetic matching produced the best balancing. Table 1 shows the results of the analysis for the unmatched and matched data. After balancing, according to all matching methods, the CR rate observed in the AML1718 was significantly higher than AML1310, as well as MRD-negativity rate. Comparing survival outcomes at 12 months, emerged that, upon matching, OS and DFS estimates of the AML1718 were higher than those of AML1310, though a slight statistical significance was reached only with the optimal matching on DFS (p=0.042). This result was confirmed by a statistically significant difference between the two RMST at 12 months (p=0.036). Despite this, a longer AML1718 follow-up is needed to provide a robust comparison between the two protocols. Our propensity-score analysis showed that combining venetoclax with chemotherapy in newly diagnosed AML patients resulted in improved outcomes in terms of CR rate and MRD-negativity: these achievements are crucial to allow transition to allogenic transplantation in first remission. With regards to survival outcomes, a solid conclusion will be drawn when a longer AML1718 follow-up is available. These preliminary results highlight the incremental benefit of venetoclax added to intensive induction chemotherapy and paves the way to novel combination regimens based on venetoclax.
2022
64th ASH Annual Meeting and Exposition
AML; propensity-score; venetoclax
04 Pubblicazione in atti di convegno::04c Atto di convegno in rivista
The Addition of Venetoclax to Induction Chemotherapy in No Low-Risk AML Patients: A Propensity Score-Matched Analysis of the Gimema AML1718 and AML1310 Trials / Piciocchi, Alfonso; Messina, Monica; Cipriani, Marta; Paoloni, Francesca; Simonetti, Giorgia; Palmieri, Raffaele; Marconi, Giovanni; Buccisano, Francesco; Fazi, Paola; Vignetti, Marco; Martinelli, Giovanni; Venditti, Adriano. - In: BLOOD. - ISSN 0006-4971. - 140:Supplement 1(2022), pp. 137-138. (Intervento presentato al convegno 64th ASH Annual Meeting and Exposition tenutosi a New Orleans; Louisiana) [10.1182/blood-2022-158890].
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