Stahl, Maximilian

e19007 Background: While clinical outcomes of patients (pts) with TP53 mutated (m) acute myeloid leukemia (AML) are dismal, subsets of pts with eligibility to curative intent therapies can do better. As racial disparities are known to impact outcome in hematological malignancies, we sought to explore disparities in TP53m AML. Methods: We conducted a multicenter study of 304 TP53m AML pts, divided into 2 groups, White (n= 240) and Black/Hispanic (n=64), to compare difference in disease characteristics and clinical outcome. We grouped Black and Hispanic together as the number of pts were small in each group and our aim was to evaluate outcome in under-represented races/ethnicities. Results: Baseline characteristics are summarized in Table. The median age of the pts was comparable between White and Black/Hispanic (p= 0.97). A significantly higher proportion of Black/Hispanic pts (23%) had diabetes mellitus when compared with White (14%) pts (p= 0.02). A higher proportion of Black/Hispanic pts had therapy-related AML (33% vs. 20%, p= 0.03), complex cytogenetics (98% vs. 87%, p= 0.003) and co-mutations (70% vs. 57%, p= 0.02). The proportion of pts who received hypomethylating agent + venetoclax (29% vs 20%, p= 0.20) or CPX-351 (22% vs 20%, p= 0.13) were comparable between White and Black/Hispanic, respectively. A higher proportion of Black/Hispanic pts received supportive care (17% vs. 4%, p= 0.002). White pts had higher rates of complete remission with or without count recovery (25% vs. 19%, p= 0.07). Only 6% of Black/Hispanic pts received allogeneic stem cell transplantation (alloHCT) compared to 16% for White pts (p= 0.01). The median event free survival was 2 months (mo) (95% CI;1.52-2.41) and 2.5 mo (95% CI:1.62-3.31) in White and Black/Hispanic pts, respectively (p= 0.71). The median overall OS was shorter for Black/Hispanic (6.37 mo [95% CI:2.88-9.85]) than for White (6.90 mo [95% CI:5.55-8.24] [p= 0.009]). Conclusions: Our study demonstrates poorer OS in Black/Hispanic pts with TP53m AML. Potential drivers of this disparity include lower alloHCT rates, higher rates of pts receiving supportive care, and higher-risk disease in Black/Hispanic pts.[Table: see text]

Abstract Background: TP53 mutations occur in 10-20% of patients with AML, constitute high-risk disease as per ELN criteria, and confer poorer prognosis. Venetoclax combination therapies and CPX-351 were recently approved for AML treatment and lead to improved outcomes in subsets of high-risk AML, however the most effective approach for treatment of TP53-mutated (m) AML remains unclear. In this study we explored the clinical outcome of TP53m AML patients treated over the last 8 years as novel therapies have been introduced to our therapeutic armamentarium. Methods: We conducted a multicenter observational study in collaboration with 4 U.S. academic centers and analyzed clinical characteristics and outcome of 174 TP53m AML patients diagnosed between March 2013 and February 2021. Mutation analysis was performed on bone marrow specimens using 42, 49, 199, or 400 gene targeted next generation sequencing (NGS) panels. Patients with an initial diagnosis of AML were divided into 4 groups (GP) based on the progressive use of novel therapies in clinical trials and their approvals as AML induction therapy during different time periods: 2013-2017 (GP1, n= 37), 2018-2019 (GP2, n= 53), 2019-2020 (GP3, n= 48) and 2020-2021 (GP4, n= 36) to analyze difference in outcome. Results: Baseline characteristics were not significantly different across different GP, as shown in Table 1. Median age of patients was 68 (range [R], 18-83), 65 (R, 29-88), 69 (R, 37-90) and 70 (R, 51-97) years in GP1-4, respectively (p=0.40). The percentage of patients with de novo AML/secondary AML/therapy-related AML in GP1-4 was 40/40/20, 36/29/24, 37.5/37.5/25 and 28/52/20, respectively (p=0.82). The proportion of patients with complex cytogenetics (CG) was 92%, 89%, 96% and 94% in GP1-4, respectively (p=0.54). The median TP53m variant allele frequency (VAF) was 48% (range [R], 5-94), 42% (R, 5-91), 45% (R, 10-94) and 60% (R, 8-82) in GP1-4, respectively (p=0.38). Four (11%), 13 (24.5%), 10 (21%) and 9 (25%) patients had multiple TP53 mutations in GP1-4, respectively (p=0.33). The proportion of patients who received 3+7 (30%, 16%, 6% & 8%; p=0.01), HMA only (11%, 18%, 2% & 8%; p=0.06), venetoclax-based (2.5%, 12%, 48%, & 61%; p <0.01) and CPX-351 induction (16%, 40%, 28% & 5%; p<0.001) were varied in GP1-4, respectively. The rate of CR/CRi was 22%, 26%, 28% and 18% in GP1-4, respectively (p=0.63). Treatment related mortality during induction was observed in 3%, 7%, 10% and 17% of patients in GP1-4, respectively (p=0.18). Overall, 28 (16%) patients received allogeneic hematopoietic stem cell transplantation (alloHCT) after induction/consolidation: 22%, 15%, 17% and 11% in GP1-4, respectively (p=0.67). In subset analysis, there was no difference in the rate of CR/CRi with venetoclax-based regimens vs. others (39% vs 61%, p=0.18) or with CPX-351 vs. others (25% vs 75%, p=0.84). The median progression-free survival was 7.7, 7.0, 5.1 and 6.6 months in GP1-4, respectively (p=0.60, Fig 1A). The median overall survival (OS) was 9.4, 6.1, 4.0 and 8.0 months in GP1-4, respectively (p=0.29, Fig 1B). In univariate analysis for OS, achievement of CR/CRi (p<0.001) and alloHCT in CR1 (p<0.001) associated with favorable outcome, whereas complex CG (p=0.01) and primary refractory disease (p<0.001) associated with poor outcome. Multiple TP53 mutations (p=0.73), concurrent ASXL1m (p=0.86), extra-medullary disease (p=0.92), ≥ 3 non-TP53m mutations (p=0.72), TP53m VAF ≥ 40% vs. < 40% (p=0.25), induction with CPX-351 vs. others (p=0.59) or venetoclax-based regimen vs. others (p=0.14) did not show significance for favorable or poor OS in univariate analysis. In multivariable analysis, alloHCT in CR1 (hazard ratio [HR]=0.28, 95% CI: 0.15-0.53; p=0.001) retained an association with favorable OS and complex CG (HR 4.23, 95%CI: 1.79-10.0; p=0.001) retained an association with dismal OS. Conclusion: We present the largest experience with TP53m AML patients analyzed by NGS. Although outcomes were almost universally dismal, alloHCT appears to improve the long-term survival in a subset of these patients. Effective therapies are warranted to successfully bridge patients to alloHCT and to prolong survival for transplant ineligible patients. Figure 1 Figure 1. Disclosures Badar: Pfizer Hematology-Oncology: Membership on an entity's Board of Directors or advisory committees. Litzow: Omeros: Other: Advisory Board; Pluristem: Research Funding; Actinium: Research Funding; Amgen: Research Funding; Jazz: Other: Advisory Board; AbbVie: Research Funding; Astellas: Research Funding; Biosight: Other: Data monitoring committee. Shallis: Curis: Divested equity in a private or publicly-traded company in the past 24 months. Goldberg: Celularity: Research Funding; Astellas: Consultancy, Membership on an entity's Board of Directors or advisory committees; Aprea: Research Funding; Arog: Research Funding; DAVA Oncology: Honoraria; Genentech: Consultancy, Membership on an entity's Board of Directors or advisory committees; Pfizer: Research Funding; Prelude Therapeutics: Research Funding; Aptose: Consultancy, Research Funding; AbbVie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Atallah: BMS: Honoraria, Speakers Bureau; Takeda: Consultancy, Research Funding; Amgen: Consultancy; Abbvie: Consultancy, Speakers Bureau; Novartis: Consultancy, Honoraria, Research Funding; Pfizer: Consultancy, Research Funding. Foran: revolution medicine: Honoraria; gamida: Honoraria; bms: Honoraria; pfizer: Honoraria; novartis: Honoraria; takeda: Research Funding; kura: Research Funding; h3bioscience: Research Funding; OncLive: Honoraria; servier: Honoraria; aptose: Research Funding; actinium: Research Funding; abbvie: Research Funding; trillium: Research Funding; sanofi aventis: Honoraria; certara: Honoraria; syros: Honoraria; taiho: Honoraria; boehringer ingelheim: Research Funding; aprea: Research Funding; sellas: Research Funding; stemline: Research Funding.

Abstract Background. Gene mutation profiling is increasingly employed for diagnosis, risk stratification, and clinical management in patients with MDS. However, current World Health Organization MDS classification is still based on histologic findings (with the exception of SF3B1 for MDS-RS), and guidelines generally suggest that clinical decisions be guided by clinico-pathologic risk stratification tools such as Revised International Prognostic Scoring System (IPSS-R). We sought to study beliefs and patterns of practice with respect to gene mutation profiling among health care providers who manage patients with MDS. Methods. A link to a 23-question web-based survey was emailed to members of the Eastern Cooperative Oncology Group (ECOG)-ACRIN Cancer Research Group, Alliance for Clinical Trials in Oncology (Alliance), and the Southwest Oncology Group (SWOG), and the Cancer Trials Support Unit (CTSU) on 5/1/2018 with 6 subsequent weekly reminders. The Qualtrics survey platform was used to record anonymous responses. We used descriptive statistics to analyze the data. No incentive was provided for responses. Results. Of 371 received responses, 262 were received from providers who did not manage MDS patients or lacked analyzable data and therefore were excluded. Of 109 eligible responses, 108 responders were from institutions representing 31 US states (one respondent was from South America). Median age of respondents was 48 years (range, 33-75); 43 (39%) were women. A third of responders (32%) worked at a university hospital, while 25%, 17%, and 5% worked at a community hospital, private practice, or other settings, respectively. While 37% of participants worked at institutions with guidelines for clinical care of MDS patients, 28% reported that their institutional guidelines recommended MDS-specific gene mutation profiling. Such testing was performed at institutions of 13% participants; institutions of 26% of responders tested a general AML panel that included MDS-specific genes. The total number of respondents whose institutions sent out either an MDS-specific gene panel or a general AML gene panel with MDS-specific genes was similar, 25% and 12%, respectively (Fig. 1). Of those who routinely perform molecular testing, 94% do so at diagnosis, 56% at relapse, 33% during preparation for stem cell transplant, 31% after the failure of hypomethylating agents (HMA), 24% during screening for a clinical trial, and 15% at initial treatment (Fig. 2). MDS gene mutation profiling was felt to be most helpful in diagnosis (rarely 11%; sometimes 49%; often 30%; always 9%), risk stratification (sometimes 31%; often 51%; always 15%), and prognosis (sometimes 31%; often 51%; always 14%); its role was more limited in response assessment (never 12%; rarely 25%; sometimes 44%; often 14%) and to predict responses to HMAs (never 5%; rarely 28%; sometimes 52%, often 14%) (Fig. 3). Various types of evidence were used to stratify MDS risk and prognosis: genetic mutations were used by nearly everyone (95%); 70% relied on morphologic findings, while gene expression/transcriptome profiling was used by 40%. Eighty-four percent of responders reported relying on conventional prognostic models like IPSS-R to identify high-risk patients for whom they would consider intensive treatment options. For this purpose, 62% would also rely on mutation profiling, and 32% would also consider higher frequency of gene mutations. While mutations in the p53 pathway were felt to be helpful in terms of risk stratification and treatment decisions by 70% of responders, 43%, 39%, 31%, 26% 23%, 20%, and 3% considered mutations in spliceosome, DNA methylation, transcription factors, histone modification, signaling, RAS pathway, and cohesin genes, respectively, to be useful as well. Approximately 31% of responders were not certain as to which mutations would affect risk stratification and management choices and said they needed to review literature. The respondents also cited multiple limitations to wider clinical use of MDS gene mutation profiling (Fig. 4). Conclusions. Our survey demonstrates widespread use of gene mutation profiling in the management of patients with MDS, but also reveals substantial variability in beliefs, practices, testing logistics, and interpretation of molecular profiling. Our findings emphasize the need for high-quality data to develop consensus evidence-based guidelines for gene profiling of MDS patients. Disclosures Sekeres: Opsona: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Opsona: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees. Bejar:AbbVie/Genentech: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; Foundation Medicine: Consultancy; Astex/Otsuka: Consultancy, Honoraria; Modus Outcomes: Consultancy; Takeda: Research Funding; Genoptix: Consultancy. Gore:Celgene: Consultancy, Research Funding. Zeidan:Ariad: Consultancy, Speakers Bureau; Gilead: Consultancy; Incyte: Employment; Celgene: Consultancy; Abbvie: Consultancy; Agios: Consultancy; Novartis: Consultancy; Pfizer: Consultancy.

Abstract Introduction: Patients with RR-AML, particularly older adults, have dismal outcomes and limited therapy options. Given low response rates and high toxicity with salvage intensive chemotherapy, and frequent ineligibility for allogeneic stem cell transplantation (alloSCT), many patients are treated with HMAs. Robust data regarding use of HMAs in AML predominates in the frontline setting, while their use in RR-AML has limited supportive data. Here wesought to analyze theoutcomes and their predictors in patients with RR-AML treated with HMAs. Methods:We collected data, spanning a period from 2006 to 2016, from 7 centers in the United States and 4 centers in Europe regarding patients treated with HMAs for RR-AML. Responses were defined by International Working Group criteria. Kaplan-Meier methods estimated overall survival (OS) from initiation of HMAs to death or end of follow-up. Multivariable logistic regression models estimated odds for response, and multivariable Cox Proportional Hazard (CPH) models estimated hazards ratios (HR) for OS. Covariates considered included HMA received, age at diagnosis (in years), AML classification at diagnosis (AML with myelodysplasia-related changes [AML-MRC], therapy-related [t]-AML), disease status (relapsed vs. refractory), number of therapy lines prior to HMA (1 vs. 2 vs. >=3), duration of first complete remission (CR1), white blood cell count, peripheral blood blast percentage, bone marrow (BM) cellularity (<=20% vs. > 20%), BM blast percentage (<=20% vs. >20%), cytogenetic risk group, and the presence of complex or chromosome 7 abnormalities. Results: Of 514 patients, 217 patients (42.2%) had refractory and 297 (58%) had relapsed AML. By end of study, 415 patients (88.5%) had died. Median follow-up for living patients was 11.6 months.Median age at diagnosis was 64 years (range [R], 16-92). AML-MRC was diagnosed in 29.0% while 8.2% had t-AML. Median number of prior therapies was 2 (R, 1-7), with 48.3% receiving 1 prior line, 30.2% receiving 2 prior lines, and 21.5% receiving >=3 prior lines. Prior alloSCT was performed in 21.2%. Only 1.9% had good risk (core binding factor) karyotype, while 56.2% had intermediate risk karyotype, and 41.9% had poor risk karyotype. Azacitidine was used in 45.8% and decitabine in 54.2%; median number of azacitidine cycles was 4 (Interquartile range [IQR], 2-6) compared to 2 for decitabine (IQR, 1-4, p <0.001). Best response to HMAs was CR in 11.7% (95%CI, 9%-14%), CRi in 6.4% (95%CI, 4.3%-8.8%), hematologic improvement (HI) in 8% (95%CI, 5.7%-10.5%), stable disease (SD) in 9.8% (95%CI, 7.2%-12.5%), while 64.1% (95%CI, 57.7%-66.2%) had progressive disease (PD). Median OS from HMA initiation for all patients was 6.9 months (IQR, 3.0-13.3). There was a significant difference in OS based on best response achieved [Figure 1]. Unadjusted OS showed an insignificant trend for worsening with increasing number of prior lines of therapy [Figure 2A]. In unadjusted analyses, there was no difference in OS based on HMA received in all patients [Figure 2B] or the subset who received only 1 prior line of therapy (median OS: Azacitidine vs. decitabine 8.4 vs 7.3 months, p=0.88). Following HMA therapy, the median number of subsequent therapies was 0 (R, 0-6), and only 12.8% underwent alloSCT. In multivariate CPH models, HMA used was not significantly associated with OS (HR=0.80, 95%CI, 0.42-1.51, p=0.49), while increasing age, and presence of complex cytogenetics and chromosome 7 abnormalities were significantly associated with risk of death [Table 1]. In multivariable logistic regression models, HMA used was not associated with achieving CR+CRi (Odds ratio=0.56, p=0.32). Conclusions: In this largest reported cohort of patients with RR-AML treated with HMAs, we found that HMAs are often used as alast line of therapy, with a minority of patients receiving subsequent treatment. Nonetheless, the minority of patients who achieve CR (11.7%) with HMA therapy had a median OS of 25.6 months. Therefore, use of HMAs for management of RR-AML is a reasonable intervention in the absence of clinical trial options. There appears to be no difference in OS or probability of achieving CR+CRi based on HMA used. Ongoing analyses in this dataset include further evaluations of predictors, including genetic mutations, and the development of prediction tools for clinical outcomes with HMA therapy. Figure 1. Figure 1. Disclosures Podoltsev: Ariad: Consultancy, Honoraria; Incyte: Consultancy, Honoraria. Ritchie:Novartis: Honoraria; Incyte: Speakers Bureau; Arian: Speakers Bureau; Pfizer: Honoraria; Celgene: Speakers Bureau. Sekeres:Millenium/Takeda: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees. Komrokji:Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Consultancy, Speakers Bureau. Al-Kali:Onconova Therapeutics, Inc.: Research Funding; Celgene: Research Funding. Santini:Celgene: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria; Novartis: Consultancy, Honoraria; Onconova: Consultancy; Amgen: Consultancy; Astex: Consultancy. Roboz:Cellectis: Research Funding; Agios, Amgen, Amphivena, Astex, AstraZeneca, Boehringer Ingelheim, Celator, Celgene, Genoptix, Janssen, Juno, MEI Pharma, MedImmune, Novartis, Onconova, Pfizer, Roche/Genentech, Sunesis, Teva: Consultancy. Fenaux:Celgene, Janssen,Novartis, Astex, Teva: Honoraria, Research Funding. Prebet:celgene: Consultancy, Honoraria; Novartis: Consultancy, Honoraria. Gore:celgene: Consultancy, Honoraria. Zeidan:Ariad: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria; Incyte: Consultancy, Honoraria; Celgene: Consultancy, Honoraria.