Early peripheral clearance of leukemia-associated immunophenotypes in AML: centralized analysis of a randomized trial

Although genetics is a relevant risk factor in acute myeloid leukemia (AML), it can be minimally informative and/or not readily available for the early identification of patients at risk for treatment failure. In a randomized trial comparing standard vs high-dose induction (ClinicalTrials.gov 64NCT00495287), we studied early peripheral blast cell clearance (PBC) as a rapid predictive assay of chemotherapy response to determine whether it correlates with the achievement of complete remission (CR), as well as postremission outcome, according to induction intensity. Individual leukemia-associated immunophenotypes (LAIPs) identified pretherapy by flow cytometry were validated and quantified centrally after 3 days of treatment, expressing PBC on a logarithmic scale as the ratio of absolute LAIP1 cells on day 1 and day 4. Of 178 patients, 151 (84.8%) were evaluable. Patients in CR exhibited significantly higher median PBC (2.3 log) compared with chemoresistant patients (1.0 log; P<.0001). PBC<1.0 predicted the worst outcome (CR, 28%). With 1.5 log established as the most accurate cutoff predicting CR, 87.5% of patients with PBC .1.5 (PBChigh, n = 96) and 43.6% of patients with PBC 641.5 (PBClow, n = 55) achieved CR after single-course induction (P<.0001). CR and PBChigh rates were increased in patients randomized to the high-dose induction arm (P 5 .04) and correlated strongly with genetic/cytogenetic risk. In multivariate analysis, PBC retained significant predictive power for CR, relapse risk, and survival. Thus, PBC analysis can provide a very early prediction of outcome, correlates with treatment intensity and disease subset, and may support studies of customized AML therapy

COVID-19 in adult acute myeloid leukemia patients: a long-term follow-up study from the European Hematology Association survey (EPICOVIDEHA)

Patients with acute myeloid leukemia (AML) are at high risk of dying from coronavirus disease 2019 (COVID-19). The optimal management of AML patients with COVID-19 has not been established. Our multicenter study included 388 adult AML patients diagnosed with COVID-19 between February 2020 and October 2021. The vast majority were receiving or had received AML treatment in the preceding 3 months. COVID-19 was severe in 41.2% and critical in 21.1% of cases. The chemotherapeutic schedule was modified in 174 patients (44.8%), delayed in 68 and permanently discontinued in 106. After a median follow-up of 325 days, 180 patients (46.4%) had died; death was attributed to COVID-19 (43.3%), AML (26.1%) or to a combination of both (26.7%), whereas in 3.9% of cases the reason was unknown. Active disease, older age, and treatment discontinuation were associated with death, whereas AML treatment delay was protective. Seventy-nine patients had a simultaneous AML and COVID-19 diagnosis, with better survival when AML treatment could be delayed (80%; P<0.001). Overall survival in patients with a diagnosis of COVID-19 between January 2020 and August 2020 was significantly lower than that in patients diagnosed between September 2020 and February 2021 and between March 2021 and September 2021 (39.8% vs. 60% vs. 61.9%, respectively; P=0.006). COVID-19 in AML patients was associated with a high mortality rate and modifications of therapeutic algorithms. The best approach to improve survival was to delay AML treatment, whenever possible

Combining the HCT-CI, G8, and AML-Score for Fitness Evaluation of Elderly Patients with Acute Myeloid Leukemia: A Single Center Analysis

Background: Accurate assessment of elderly acute myeloid leukemia (AML) patients is essential before intensive induction chemotherapy and subsequent allogeneic hematopoietic stem cell transplantation. In this context, we investigated the capacity of three scores for frailty prediction. Methods: At diagnosis, 197 patients were clinically evaluated for appropriate treatment intensity. In parallel and independently, the G8-score, the Hematopoietic Stem Cell Index (HCT-CI) and the AML-score for CR were determined for each patient and analyzed with respect to overall survival (OS). Results: The G8-score and the HCT-CI were able to significantly separate “fit” from “unfit” patients, p = 0.008. In univariate Cox models, the predictive role for OS was confirmed: for the G8-score (HR: 2.35, 95% CI 1.53–3.60, p p = 0.009) and the AML-score (HR: 5.59, 95% CI 2.04–15.31, p = 0.001), the latter was subsequently used to verify the cohort. In the multivariate Cox model, the results were confirmed for the G8- (HR: 2.03, p p = 0.001). Of interest, when combining the scores, their prediction capacity was significantly enhanced, p < 0.001. Conclusions: The G8-, the HCTCI and the AML-score represent valid tools in the frailty assessment of elderly AML patients at diagnosis

Combining the HCT-CI, G8, and AML-Score for Fitness Evaluation of Elderly Patients with Acute Myeloid Leukemia: A Single Center Analysis

Background: Accurate assessment of elderly acute myeloid leukemia (AML) patients is essential before intensive induction chemotherapy and subsequent allogeneic hematopoietic stem cell transplantation. In this context, we investigated the capacity of three scores for frailty prediction. Methods: At diagnosis, 197 patients were clinically evaluated for appropriate treatment intensity. In parallel and independently, the G8-score, the Hematopoietic Stem Cell Index (HCT-CI) and the AML-score for CR were determined for each patient and analyzed with respect to overall survival (OS). Results: The G8-score and the HCT-CI were able to significantly separate &ldquo;fit&rdquo; from &ldquo;unfit&rdquo; patients, &lt;0.001 and p = 0.008. In univariate Cox models, the predictive role for OS was confirmed: for the G8-score (HR: 2.35, 95% CI 1.53&ndash;3.60, p &lt; 0.001), the HCT-CI (HR: 1.91, 95% CI 1.17&ndash;3.11, p = 0.009) and the AML-score (HR: 5.59, 95% CI 2.04&ndash;15.31, p = 0.001), the latter was subsequently used to verify the cohort. In the multivariate Cox model, the results were confirmed for the G8- (HR: 2.03, p &lt; 0.001) and AML-score (HR: 3.27, p = 0.001). Of interest, when combining the scores, their prediction capacity was significantly enhanced, p &lt; 0.001. Conclusions: The G8-, the HCTCI and the AML-score represent valid tools in the frailty assessment of elderly AML patients at diagnosis