Abstract: Contemporary risk stratification algorithms commonly use threshold-defined categories of clinically relevant risk factors. The Children's Oncology Group (COG) uses National Cancer Institute (NCI) risk group (RG), cytogenetics, and early response to therapy measured by minimal residual disease (MRD) using flow cytometry on day 8 peripheral blood (D8 PB) and day 29 bone marrow (D29 BM). However, it is unclear whether assigning different weights to individual risk factors, as well as using numerical values as continuous, rather than categorical, would more accurately predict relapse risk. Previous work (Loh, ASH 2020) described validation of a continuous prognostic index (PI) for risk of relapse published by UK investigators incorporating favorable and unfavorable genetics, white blood cell count (WBC), and D29 BM as continuous variables (O'Connor, JCO 2018; Enshaei, Blood 2020), and assessed the added value of D8 PB. We now extend this work by comparing patient outcomes with current COG risk classification to PI-derived risk classifications on the previously described population (Loh, ASH 2020). We first retrospectively classified patients (pts) (N=21,199 from prior COG trials AALL0331/0232 or AALL0932/1131 enrolled 2004-2019) in our analysis population using the COG risk stratification algorithm employed in the current generation of COG trials. Pts with Down syndrome or BCR/ABL1 were excluded. We classified our analysis population as SR-Favorable [SR-Fav, 24.5% (5-year relapse free survival (RFS) probability 0.97)], SR-Favorable/Average (not distinguishable because of missing D8 PB) [SR-Fav/Avg, 5.3% (.96)] , SR-Avg [20.5% (0.93)], SR-High [12.5% (0.83)] , HR-Fav [3.0% (0.96)], HR [29.6% (0.82)] , and Very HR [VHR, 1.1% (0.54)] according to NCI RG, CNS status, cytogenetics, D8 PB where relevant, D29 BM, and EOC MRD. Ninety-seven percent of pts had sufficient data to be retrospectively classified and thus 20,176 pts were considered for subsequent analyses. We next developed a multivariable model for RFS using log transformed MRD (τ(MRD)). Temporal external validation was first employed by developing models considering AALL0932/1131 data (n=12,453) and then validating them with AALL0331/0232 data (n=7,723). Of the full cohort of 20,176 pts, 24.4% could not be classified by COG PI, primarily due to missing D8 PB MRD which was not assessed routinely in earlier studies; thus the model was developed on 11,151 pts and validated on 4,103 pts. The COG PI (PI COG) was calculated using the equation [τ(d8 MRD) x -0.036 + τ(d29 MRD) x -0.119 + CYTO-GR x -0.914 + CYTO-HR x 0.752 + WBC log x 0.178]. The UK PI (PI UK) was also calculated using published coefficients [τ(d29 MRD) x -0.218 + CYTO-GR x -0.440 + CYTO-HR x 1.066 + WBC log x 0.138] for comparison to assess the practical significance of adding D8 PB. In contrast to the UK method, we identified risk groups by selecting PI cutoffs that maximized the discrimination of the predictive model as quantified by the concordance probability estimator (CPE) (Barrio, SORT 2017). This objective method of cutpoint determination allows for risk group definition without investigator agreement on exact prespecified risk group characteristics; this method also defined four risk groups (Low, Standard, Intermediate, and High). Cutpoints derived from the two different indices, applied to the pts who could be classified by PI COG (n=15,254), resulted in different proportions of pts in each of the risk groups with generally similar RFS estimates for each group. Using cutpoints estimated for PI COG (-2.073, -1.307, and -0.857) 36.0% (RFS = 0.97) were classified as low, 29.6% (0.93) standard, 17.1% (0.88) intermediate, and 17.4% (0.73) high risk of relapse. For PI UK ( -2.916, -2.534, and -1.15), among those who were classifiable by PI COG, 33.4% (0.97) were classified as low, 26.3% (0.93) standard, 30% (0.87) intermediate, and 10.4% (0.69) high. Finally, we compared the COG risk stratification to PI CPE-defined risk stratification in the cohort. As shown in the table, PI COG improves discrimination among individuals by identifying groups with different relapse risk than expected. The PI COG can thus identify patients for whom therapeutic intensification may not result in significantly better outcomes while improving the discrimination of HR pts to allow randomized interventions with achievable hazard ratios. Figure 1 Figure 1. Disclosures Loh: MediSix therapeutics: Membership on an entity's Board of Directors or advisory committees. Borowitz: Amgen, Blueprint Medicines: Honoraria. Zweidler-McKay: ImmunoGen: Current Employment. Mullighan: AbbVie: Research Funding; Amgen: Current equity holder in publicly-traded company; Illumina: Membership on an entity's Board of Directors or advisory committees; Pfizer: Research Funding. Hunger: Amgen: Current equity holder in publicly-traded company. Raetz: Pfizer: Research Funding; Celgene: Other: DSMB member.

Abstract: Background: Patients with Down syndrome (DS) have an approximately 10-fold increased risk of developing ALL, and the spectrum of genetic alterations differs from that of non-DS ALL. Rearrangement and/or overexpression of cytokine receptor-like factor 2 (CRLF2+) occurs in 50% of DS ALL, compared to only 5-10% CRLF2+ cases in non-DS children and adolescents. JAK2 or JAK1 mutations co-occur in about half of CRLF2+ cases in both DS and non-DS ALL. The prognostic significance of CRLF2+ ALL also appears to differ in the limited data reported to date, with less adverse impact in patients with DS compared to non-DS ALL. Here, we report the clinical characteristics and prognostic significance of B-ALL with CRLF2 overexpression and JAK alterations in children and adolescents/young adults (AYA) with DS who were treated on Children's Oncology Group (COG) clinical trials from 2003-2016. Methods: We analyzed clinical, laboratory, and outcome data for 317 patients with DS B-ALL treated on standard risk (SR) trials AALL0331 and AALL0932 and high risk (HR) trials AALL0232 and AALL1131, for whom CRLF2 status and rearrangement partners (IGH or P2RY8) were ascertained by flow cytometric assessment of surface expression; fluorescence in situ hybridization; and/or polymerase chain reaction (PCR) testing. JAK mutations were ascertained in a subset by PCR and sequencing. Minimal residual disease (MRD) was assessed by flow cytometry at the end of induction (EOI) and at end of consolidation (EOC) for a subset of EOI MRD+ patients. Results: We identified 168/317 (53.0%) CRLF2+ cases, and among those assessed for CRLF2 partner, 17/73 (23.3%) were IGH-CRLF2 and 56/73 (76.7%) were P2RY8-CRLF2. In the subset of 165 cases tested for JAK mutations (85 CRLF2- and 80 CRLF2+), 42/165 (25.4%) had JAK mutations, all of which co-occurred in CRLF2+ cases. CRLF2 positivity was significantly associated with younger age at diagnosis: 140/168 (83.3%) of CRLF2+ cases were under 10 years old, versus 106/149 (71.1%) of CRLF2- cases, p & lt;0.01. P2RY8-CRLF2 cases were significantly more likely than IGH-CRLF2 cases to be associated with age under 10 years at diagnosis (92.9% vs 29.4%, p & lt;0.0001), initial white blood count (WBC) & lt;50x103 (80.4% vs 52.9%, p & lt;0.024), National Cancer Institute (NCI) standard risk status (73.2% vs 23.5%, p & lt;0.0002), and day 29 MRD & lt;0.01% (67.9% vs 37.5%, p & lt;0.028). There were no significant associations between JAK mutation status and any clinical features assessed (sex, initial WBC, central nervous system or testicular involvement, NCI risk group, or EOI/EOC MRD). Among patients with neutral cytogenetics (defined as neither favorable [ETV6-RUNX1, double trisomies of chromosomes 4 and 10] nor unfavorable [BCR-ABL1, KMT2A-rearranged, hypodiploid, iAMP21] ), survival did not significantly differ between CRLF2+ and CRLF2- patients (Figure 1A,B), either for 5-year event-free survival (EFS) (79.1 +3.6% vs 77.6 +4.7%, p=0.856) or 5-year overall survival (OS) (89.5 ±2.8% vs 84.9 ±4.1%, p=0.674). There were also no significant differences in EFS or OS based on JAK mutation status or CRLF2 partner, although there were trends toward poorer outcomes in the CRLF2+/JAK+ and IGH-CRLF2 subgroups (Figure 1C). Finally, there was no significant difference in 5-year cumulative incidence of relapse (CIR) according to CRLF2 status (CRLF2+ 16.0 +3.0%, CRLF2- 10.6 +2.6%, p=0.179), although there were non-significant trends toward more relapses in CRLF2+ cases overall and in the NCI HR subgroup analysis. Discussion: Whereas CRLF2 and JAK alterations are associated with higher MRD, poorer survival, and increased CIR in patients with high-risk ALL without DS, these alterations do not demonstrate strong adverse prognostic impact in children and AYAs with DS-ALL treated on recent frontline COG trials, although larger sample sizes are needed to adequately assess for possible poorer prognoses associated with the CRLF2+/JAK+ and IGH-CRLF2 subgroups. Regardless, given the frequency of these targetable lesions and the increased risk of relapse and chemotherapy-associated toxicities in patients with DS-ALL, targeted therapies currently under investigation for these genetic lesions may be beneficial to replace some intensive blocks of therapy in DS-ALL with CRLF2 and/or JAK alterations, both to enhance anti-leukemic efficacy and decrease intensive chemotherapy-associated toxicities. Figure 1 Disclosures Tasian: Gilead Sciences: Research Funding; Incyte Corporation: Research Funding; Aleta Biotherapeutics: Membership on an entity's Board of Directors or advisory committees. Borowitz:Amgen: Honoraria. Mullighan:Illumina: Consultancy, Honoraria, Speakers Bureau; AbbVie, Inc.: Research Funding; Pfizer: Honoraria, Research Funding, Speakers Bureau. Raetz:Celgene: Other: DSMB member; Pfizer: Other: Institutional research funding. Loh:Pfizer: Other: Institutional Research Funding; Medisix Therapeutics: Membership on an entity's Board of Directors or advisory committees. Hunger:Novartis: Consultancy; Amgen: Current equity holder in publicly-traded company, Honoraria.

Abstract: Background: Philadelphia chromosome-like acute lymphoblastic leukemia (Ph-like ALL) occurs in 5-30% of children and adolescents/young adults (AYAs) with B-ALL, is driven by genetic alterations that induce constitutive cytokine receptor and kinase signaling, and is associated with poor clinical outcomes across the older pediatric-to-adult age spectrum (Tasian Blood 2017c, Reshmi Blood 2017, Roberts Blood 2018). Rearrangement and/or overexpression of cytokine receptor-like factor 2 (CRLF2+) occurs in 50% of Ph-like ALL cases with frequently co-occurring JAK2 or JAK1 point mutations or IL7R indel mutations. This study reports the clinical outcomes of children and AYAs with newly-diagnosed National Cancer Institute (NCI) standard-risk (SR) or high-risk (HR) CRLF2+ ALL without Down syndrome treated on four successive Children's Oncology Group (COG) phase 3 clinical trials from 2003 to 2018. Methods: We retrospectively assessed demographic characteristics, laboratory data, and clinical outcomes of 3757 patients with B-ALL treated on COG trials AALL0331 and AALL0932 (SR) and AALL0232 and AALL1131 (HR) whose diagnostic leukemia specimens were analysed by low-density microarray (LDA), fluorescence in situ hybridization, polymerase chain reaction (PCR), and/or anchored multiplex PCR testing (Harvey and Tasian Blood Advances 2020). Minimal residual disease (MRD) was assessed by flow cytometry at the end of induction (EOI) and at the end of consolidation for a subset of EOI MRD+ patients. Results: We identified 77/1541 (5.0%) SR and 244/2216 (11.0%) HR patients with CRLF2+ B-ALL in this cohort. Amongst those with diagnostic leukemia specimens analysed by LDA, 57/72 (79.2%) of SR CRLF2+ and 175/213 (82.2%) of HR CRLF2+ patients were positive for the Ph-like gene expression profile with an 8-gene score ≥0.5. P2RY8-CRLF2 fusions and IGH-CRLF2 translocations were detected in 64/77 (83.1%) and 10/77 (13.0%) of SR CRLF2+ patients and in 98/244 (40.2%) and 103/244 (42.2%) of HR CRLF2+ patients, respectively. CRLF2 rearrangements or F232C mutations were not found in the remaining 3 SR and 43 HR CRLF2+ patients, although other Ph-like alterations were discovered in some (n=3 IGH-EPOR fusions, 1 IL7R indel). Importantly, CRLF2+ vs non-CRLF2-overexpressing (CRLF2-) status was associated with older age (10.8 ±6.5 vs 7.8 ±5.8 years [mean ±SD], p & lt;0.0001), leukocytosis (diagnostic white blood cell count 77.5 ±98.5 vs 49.8 ±119.4 x 10e9/L [mean ±SD], p & lt;0.0001), and higher rates of EOI MRD positivity at a ≥0.01% threshold (47.9% vs 30.1%, p & lt;0.0001), which appeared largely driven by the Ph-like HR cohort as expected (57.9% MRD+ vs 42.1% MRD- in HR CRLF2+ and 44.6% MRD+ vs 55.4% MRD- in SR CRLF2+ patients, p & lt;0.003). Overall, CRLF2+ patients had inferior 5-year event-free survival (EFS; 63.3% ±3.1 vs 82.1% ±0.7, p & lt;0.0001) and overall survival (OS; 79.6% ±2.6 vs 90.5% ±0.6, p & lt;0.0001) compared to CRLF2- patients (Figure 1A-B) and a greater 5-year cumulative incidence of relapse (CIR; 30.4% ±2.7 vs 13.2% ±0.6, p & lt;0.001). While 5-year EFS and OS were particularly poor in Ph-like CRLF2+ HR patients (56.3% ±4.6 and 75.4% ± 3.9, respectively) and non-Ph-like CRLF2+ HR patients (EFS 63.7% ±10.2 and OS 74.4% ±8.9), outcomes for Ph-like CRLF2+ SR (EFS 87.2% ±4.5 and OS 94.5% ±3.1) and non-Ph-like CRLF2+ SR patients (EFS 86.2% ±9.3 and OS 100%) were quite good (p & lt;0.0001 for both EFS and OS; Figure 1C-D). Discussion: Patients with newly-diagnosed CRLF2+ B-ALL treated on frontline COG trials have higher rates of EOI MRD positivity, inferior survival, and increased CIR compared to their CRLF2- counterparts. EFS is especially poor in children and AYAs with NCI HR CRLF2+ ALL, particularly those with the Ph-like expression profile. Conversely, outcomes for children with NCI SR CRLF2+ ALL are reasonably favourable, irrespective of Ph-like status. Development of successful treatment strategies to decrease relapse and to improve survival remains a major therapeutic gap for NCI HR CRLF2+ ALL patients. Current clinical trials are studying the potential efficacy of kinase inhibitor addition to chemotherapy for children, adolescents, and adults with HR Ph-like ALL harboring CRLF2 rearrangements/other JAK pathway alterations or ABL class kinase fusions (NCT0240717, NCT02723994, NCT02883049, NCT03571321). Figure 1 Disclosures Tasian: Gilead Sciences: Research Funding; Incyte Corporation: Research Funding; Aleta Biotherapeutics: Membership on an entity's Board of Directors or advisory committees. Borowitz:Amgen: Honoraria. Mullighan:AbbVie, Inc.: Research Funding; Illumina: Consultancy, Honoraria, Speakers Bureau; Pfizer: Honoraria, Research Funding, Speakers Bureau. Hunger:Novartis: Consultancy; Amgen: Current equity holder in publicly-traded company, Honoraria. Raetz:Pfizer: Research Funding; Celgene/BMS: Other. Loh:Pfizer: Other: Institutional Research Funding; Medisix Therapeutics: Membership on an entity's Board of Directors or advisory committees.

Abstract: Current risk stratification for COG ALL patients (pts) relies on National Cancer Institute (NCI) risk group (RG) at diagnosis, somatic genetics, and early response to therapy as measured by specific thresholds of minimal residual disease (MRD) using flow cytometry on day 8 peripheral blood (D8 PB) and day 29 bone marrow (D29 BM). NCI RG is defined as age 1-10 years (yrs) and white blood cell count (WBC) & lt;50,000/uL (Standard Risk, SR); all other non-infant patients are high risk (HR). Using COG risk stratification, current therapies for SR and HR patients are based on 5-year projected event-free survival (EFS) of 92-97%, and 65-86%. Currently, two subsets, Ph-like and very high risk (VHR) ALL are identified with additional assays-genomic sequencing for Ph-like, and persistent BM MRD on D29 and at end of consolidation for VHR, and are eligible for different treatments. However, as UK investigators recently published (O'Connor, JCO 2018; Enshaei, Blood 2020), using multiple continuous variables as threshold-defined categorical data may diminish the power of accurately predicting relapse, and thus prescribe inappropriate post induction therapy. We tested the UK approach of transforming categorical variables into continuous data on 13,870 NCI SR and 7308 NCI HR B-ALL pts treated on two generations of COG trials: AALL0331 (SR; n=5094), AALL0932 (SR; n=8776), AALL0232 (HR; n=2883), and AALL1131 (HR; n=4425). Down syndrome and Ph+ pts were excluded from analysis. Clinical characteristics are listed in Table 1. ETV6-RUNX1 (25.24%) and double trisomies of chromosome 4, 10 (DT) (23.77%) comprised the favorable risk genetic RG (FRG) group (48.15% of risk classified) while KTM2A rearranged (1.71%), hypodiploidy (1.67%), and iAMP21 (2.56%) comprised the unfavorable risk genetic RG (URG) (6.26%). All others with genetic information were classified as intermediate risk genetic RG (IRG) (45.59% of risk classified). Among 4873 pts tested, 20.46% had Ph-like ALL. D8 PB and D29 BM MRD data were available for 76.42% and 96.69% pts, respectively. We first log transformed WBC, D8 and D29 MRD and displayed these by treatment protocol, NCI RG, and FRG/URG (separating out Ph-like independently). Age and WBC followed the normal expected distribution with the median age of SR pts 4.0 yrs (range 1-9) and HR 12 yrs (range 1-30). Transformed MRD was displayed as a variable t(MRD), corresponding to the negative log; max t(D29 MRD) was 13.82, corresponding to MRD & lt;1.0 x 10-5.The great majority of pts were MRD-positive at D8 (mean t(D8 MRD) 7.42); but there was broad distribution of values, with NCI SR and FRG pts having lower t(D8 MRD) (mean 7.52 and 8.08) than NCI HR and URG pts (mean 7.20 and 6.56) (p & lt; 0.001) . The great majority of pts were D29 MRD-negative (mean t(D29 MRD) 12.08), with NCI SR and FRG pts achieving lower D29 MRD (mean t(D29 MRD) 12.43 and 12.73) than NCI HR and URG pts (mean 11.40 and 10.95) (p & lt; 0.0001). Ph-like ALL pts had a mean t(D8 MRD) and t(D29 MRD) of 6.22 and 9.37. We next conducted a univariate analysis for risk factors for relapse, including sex, age, WBClog, CNS status, protocol-defined rapid early response status, FRG, URG, t(D8 MRD), and t(D29 MRD); all variables except CNS status were significant p & lt; 0.0001). Multivariable modeling showed that WBClog, FRG, URG, t(D8 MRD), t(D29 MRD) retained significance (p & lt; 0.0001). Finally, we applied the UK Prognostic Index (PIUKALL) equation [t(d29 MRD) x -0.218 + CYTO-GR x -0.440 + CYTO-HR x 1.066 + WBClog x 0.138] to the COG data using protocol, NCI RG, FRG, URG, IRG, or Ph-like RG in the model and validated the trends for relapse-free survival (RFS), which were similar in our groups with an overall median PIUKALL of -2.63 ( mean -2.32, SD -.90, min -3.54, max 1.79). We next added in t(D8 MRD) to define a PICOG and determined that D8 PB MRD added significantly to the model, mostly through discriminating between the hazard ratios of the FRG and the URG RGs. Importantly, the D8 PB MRD led to a qualitatively more distinctive group with a potentially lower predicted RFS in NCI SR pts, a group that has been more difficult to predict in the past, and yet comprises nearly half of all relapse events. Our analyses of 21,178 COG B-ALL pts confirm and extend the utility of integrating WBC and MRD as continuous rather than categorical values to refine risk stratification for patient treatment and trial design. Disclosures Loh: Pfizer: Other: Institutional Research Funding; Medisix Therapeutics: Membership on an entity's Board of Directors or advisory committees. Borowitz:Amgen: Honoraria. Zweidler-McKay:ImmunoGen, Inc.: Current Employment. Mattano:Melinta Therapeutics: Consultancy; Novartis: Consultancy; Pfizer: Consultancy. Hunger:Amgen: Current equity holder in publicly-traded company, Honoraria; Novartis: Consultancy. Raetz:Celgene/BMS: Other; Pfizer: Research Funding. Mullighan:Illumina: Consultancy, Honoraria, Speakers Bureau; Pfizer: Honoraria, Research Funding, Speakers Bureau; AbbVie, Inc.: Research Funding.

Abstract: To determine the prognostic significance of central nervous system (CNS) leukemic involvement in newly diagnosed T-cell acute lymphoblastic leukemia (T-ALL), outcomes on consecutive, phase 3 Children’s Oncology Group clinical trials were examined. AALL0434 and AALL1231 tested efficacy of novel agents within augmented-Berlin-Frankfurt-Münster (aBFM) therapy. In addition to testing study-specific chemotherapy through randomization, the AALL0434 regimen delivered cranial radiation therapy (CRT) to most participants (90.8%), whereas AALL1231 intensified chemotherapy to eliminate CRT in 88.2% of participants. In an analysis of 2164 patients with T-ALL (AALL0434, 1550; AALL1231, 614), 1564 had CNS-1 (72.3%), 441 CNS-2 (20.4%), and 159 CNS-3 (7.3%). The 4-year event-free-survival (EFS) was similar for CNS-1 (85.1% ± 1.0%) and CNS-2 (83.2% ± 2.0%), but lower for CNS-3 (71.8% ± 4.0%; P = .0004). Patients with CNS-1 and CNS-2 had similar 4-year overall survival (OS) (90.1% ± 0.8% and 90.5% ± 1.5%, respectively), with OS for CNS-3 being 82.7% ± 3.4% (P = .005). Despite therapeutic differences, outcomes for CNS-1 and CNS-2 were similar regardless of CRT, intensified corticosteroids, or novel agents. Except for significantly superior outcomes with nelarabine on AALL0434 (4-year disease-free survival, 93.1% ± 5.2%), EFS/OS was inferior with CNS-3 status, all of whom received CRT. Combined analyses of & gt;2000 patients with T-ALL identified that CNS-1 and CNS-2 status at diagnosis had similar outcomes. Unlike B-ALL, CNS-2 status in T-ALL does not impact outcome with aBFM therapy, without additional intrathecal therapy, with or without CRT. Although nelarabine improved outcomes for those with CNS-3 status, novel approaches are needed. These trials were registered at www.clinicaltrials.gov as #NCT00408005 (AALL0434) and #NCT02112916 (AALL1231).

Abstract: Trisomy 21, the genetic cause of Down syndrome (DS), is the most common congenital chromosomal anomaly. It is associated with a 20-fold increased risk of acute lymphoblastic leukemia (ALL) during childhood and results in distinctive leukemia biology. To comprehensively define the genomic landscape of DS-ALL, we performed whole genome sequencing and whole-transcriptome sequencing (RNA-Seq) on 295 cases. Our integrated genomic analyses identified 15 molecular subtypes of DS-ALL, with marked enrichment of CRLF2-r, IGH::IGF2BP1, and C/EBP altered (C/EBPalt) subtypes compared to 2257 non-DS-ALL cases. We observed abnormal activation of the CEBPD, CEBPA, and CEBPE genes in 10.5% of DS-ALL cases, via a variety of genomic mechanisms, including chromosomal rearrangements and noncoding mutations leading to enhancer hijacking. 42.3% of C/EBP-activated DS-ALL also have concomitant FLT3 point mutation or indel, relative to 4.1% in other subtypes (P=7.2×10-6). CEBPD overexpression enhanced the differentiation of mouse hematopoietic progenitor cells into pro-B cells in vitro, particularly in a DS genetic background. Notably, RAG-mediated somatic genomic abnormalities were common in DS-ALL, accounting for a median of 27.5% of structural alterations, compared to 7.7% in non-DS-ALL (P=2.1×10-12). Unsupervised hierarchical clustering analyses of CRLF2-rearranged DS-ALL identified substantial heterogeneity within this group, with the BCR::ABL1-like subset linked to an inferior event-free survival (hazard ratio=5.27, P=9.3×10-8), even after adjusting for known clinical risk factors (hazard ratio=4.32; P=0.0020). These results provide important insights into the biology of DS-ALL and point to opportunities for targeted therapy and treatment individualization.

Abstract: Introduction: Health disparities are major issue for racial, ethnic, and socioeconomically disadvantaged groups. Though outcomes in childhood acute lymphoblastic leukemia (ALL) have steadily improved, identifying persistent disparities is critical. Prior studies evaluating ALL outcomes by race or ethnicity have noted narrowing disparities or that residual disparities are secondary to differences in leukemia biology or socioeconomic status (SES). We aimed to identify persistent inequities by race/ethnicity and SES in childhood ALL in the largest cohort ever assembled for this purpose. Methods: We identified a cohort of newly-diagnosed patients with ALL, age 0-30.99 years who were enrolled on COG trials between 2004-2019. Race/ethnicity was categorized as non-Hispanic white vs. Hispanic vs. non-Hispanic Black vs. non-Hispanic Asian vs. Non-Hispanic other. SES was proxied by insurance status: United States (US) Medicaid (public health insurance for low-income individuals) vs. US other (predominantly private insurance) vs. non-US patients (mainly jurisdictions with universal health insurance). Event-free and overall survival (EFS, OS) were compared across race/ethnicity and SES. The relative contribution of disease prognosticators (age, sex, white blood cell count, lineage, central nervous system status, cytogenetics, end Induction minimal residual disease) was examined with Cox proportional hazard multivariable models of different combinations of the three constructs of interest (race/ethnicity, SES, disease prognosticators) and examining hazard ratio (HR) attenuation between models. Results: The study cohort included 24,979 children, adolescents, and young adults with ALL. Non-Hispanic White patients were 13,872 (65.6%) of the cohort, followed by 4,354 (20.6%) Hispanic patients and 1,517 (7.2%) non-Hispanic Black patients. Those insured with US Medicaid were 6,944 (27.8%). Five-year EFS (Table 1) was 87.4%±0.3% among non-Hispanic White patients vs. 82.8%±0.6% [HR 1.37, 95 th confidence interval (95CI) 1.26-1.49; p & lt;0.0001] among Hispanic patients and 81.9%±1.2% (HR 1.45, 95CI 1.28-1.56; p & lt;0.0001) among non-Hispanic Black patients. Outcomes for non-Hispanic Asian patients were similar to those of non-Hispanic White patients. US patients on Medicaid had inferior 5-year EFS as compared to other US patients (83.2%±0.5% vs. 86.3%±0.3%, HR 1.21, 95CI 1.12-1.30; p & lt;0.0001) while non-US patients had the best outcomes (5-year EFS 89.0%±0.7%, HR 0.78, 95CI 0.71-0.88; p & lt;0.0001). There was substantial imbalance in traditional disease prognosticators (e.g. T-cell lineage) across both race/ethnicity and SES, and of race/ethnicity by SES. For example, T-lineage ALL accounted for 17.6%, 9.4%, and 6.6% of Non-Hispanic Black, Non-Hispanic White, and Hispanic patients respectively (p & lt;0.0001). Table 2 shows the multivariable models and illustrates different patterns of HR adjustment among specific racial/ethnic and SES groups. Inferior EFS among Hispanic patients was substantially attenuated by the addition of disease prognosticators (HR decreased from 1.37 to 1.17) and further (but not fully) attenuated by the subsequent addition of SES (HR 1.11). In contrast, the increased risk among non-Hispanic Black children was minimally attenuated by both the addition of disease prognosticators and subsequent addition of SES (HR 1.45 to 1.38 to 1.32). Similarly, while the superior EFS of non-US insured patients was substantially attenuated by the addition of race/ethnicity and disease prognosticators (HR 0.79 to 0.94), increased risk among US Medicaid patients was minimally attenuated by the addition of race/ethnicity or disease prognosticators (HR 1.21 to 1.16). OS disparities followed similar patterns but were consistently worse than in EFS, particularly among patients grouped as non-Hispanic other. Conclusions: Substantial disparities in survival outcomes persist by race/ethnicity and SES in the modern era. Our findings suggest that reasons for these disparities vary between specific disadvantaged groups. Additional work is required to identify specific drivers of survival disparities that may be mitigated by targeted interventions. Figure 1 Figure 1. Disclosures Gupta: Jazz Pharmaceuticals: Consultancy, Membership on an entity's Board of Directors or advisory committees. Teachey: NeoImmune Tech: Research Funding; Sobi: Consultancy; BEAM Therapeutics: Consultancy, Research Funding; Janssen: Consultancy. Zweidler-McKay: ImmunoGen: Current Employment. Loh: MediSix therapeutics: Membership on an entity's Board of Directors or advisory committees.

Abstract: Background : The identification of mutations in IDH1 and IDH2 in ~20% of AML pts has ushered in the modern era of precision medicine in AML. The functional implications of the resulting neomorphic activity of these mutated enzymes, has resulted in FDA-approved targeted therapies. Similarly, the changes in methylation due to IDH mutations (IDHm) have shown high responses with HMA-based regimens. In the frontline setting, where traditional IC regimens are also used, no clear guidance exists which choice elicits the best outcomes for IDHm pts. Furthermore, emerging data on the importance of the biologic context on the response to different agents, including co-existing gene mutations and pt age, pose additional questions that need to be systematically addressed in order to determine the best-individualized approach. We set out to address this question, and provide data-driven treatment decision support for the ~20% of AML pts harboring IDHm. Methods : Using the AML pt collection from the Cancer and Leukemia Group B/Alliance for Clinical Trials in Oncology (Alliance, 1986-2013), and a new multicenter collaboration between four major US Cancer Centers (consecutive pts, 2015-2019), we have assembled the thus far largest cohort of 804 IDH1/2m adult AML pts, treated with standard 7+3 IC (n=578), IDH-directed inhibitors (IDHi, n=58) or HMA (without IDH2i or BCL2i, n=75). We investigated the role of different IDH1/2m, co-mutational patterns, and clinical features in predicting response to different frontline therapies. Results : IDH1/2m pts were predominantly older, with 64% aged ≥60 y. Nineteen percent of pts presented with extramedullary disease (EMD) at diagnosis. Pts with all IDHm mutation types commonly harbored DNMT3Am (IDH1-R132m, 38%; IDH2-R140m, 31%; IDH2-R172m, 48%), but differed with respect to other co-occurring mutations (Fig. 1). IDH1m pts most frequently had mutations in the NPM1 (43%), FLT3-ITD (19%), SRSF2 (15%), and NRAS (14%) genes. IDH2-R140m pts harbored mutations in NPM1 (37%), SRSF2 (33%), FLT3-ITD (19%) and RUNX1 (16%) most often, whereas IDH2-R172m pts frequently had BCORm (21%) and RUNX1m (20%), but rarely harbored FLT3-ITD (6%) or NPM1m (2%). Clinical outcomes had notable differences in complete remission (CR) rates, relapse rates (RR) and overall survival (OS), both with respect to IDHm-type, and also frontline therapy (Table 1). IDH1m pts treated with IC (n=239) had a CR rate of 69%. The CR rates were differentially impacted by clinical characteristics and co-occurring mutations, which were identified in multivariate analysis (MVA; positive prognosticator [PP] for CR: NPM1m; negative prognosticator [NP] : WT1m, FLT3-TKD, higher age, Table 2). IC-treated IDH1m pts had a RR of 60% (NP: ASXL1m), with a 3y-OS of 41% (NP: U2AF1m, WT1m, higher age, higher WBC). When treated with IDH1i (n=20), pts had a high CR rate of 70%, RR of 36%, and a 3y-OS of 44%. In contrast, pts treated with HMAs had a low CR rate of 37% (NP: higher BM blast %), and 3y-OS of 26%. IDH2-R140m pts treated with IC (n=231) had a CR rate of 68% (PP: NPM1m, FLT3-ITD NP: higher WBC), RR of 64% (NP: SRSF2m), with a 3y-OS of 37% (PP: NPM1m, WT1m; NP: PHF6m, higher age, higher WBC). The positive prognostic association of FLT3-ITD for CR achievement was surprising, but seemed to be independent of co-occurring NPM1m, with CR rates for pts with NPM1wt/ITD+: 70%, NPM1wt/ITD-: 57%, NPM1m/ITD+:83%, and NPM1m/ITD-:76%. When treated with IDH1i (n=27), pts had a CR rate of 48%, RR of 8%, with a 3y-OS of 29%. Again, pts treated with HMAs had a low CR rate of 28%, RR of 90% and 3y-OS of 21%. IDH2-R172m pts treated with IC (n=66) had a relatively low CR rate of 58% (NP: higher age, male sex, presence of EMD), RR of 53%, but a relatively high 3y-OS rate of 45% (median: 2.5y; NP: RUNX1m, higher WBC). The number of IDH2i- or HMA-treated pts with IDH2-R172m was too small for analyses. Conclusions: Given the relatively high response rates to IC of IDH1/2m pts, consideration of co-occurring mutations or clinical features (eg, WT1m or FLT3-TKD as NP for IDH1m, SRSF2m for IDH2-R140m or EMD for IDH2-R172m pts) may help guide frontline treatment decisions. Likewise, encouragingly high response and survival rates of pts treated with frontline IDHi should also factor into decision-making. As more information on high response and survival rates with HMA-based combination regimens comes forth, we will be adding these pts to our on-going analysis. *first: UB,PP,CT; #last:ASM,KS,AKE Figure 1 Figure 1. Disclosures Borate: Jazz Pharma: Research Funding; Genentech: Membership on an entity's Board of Directors or advisory committees, Other: Advisory Board; AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding; Pfizer: Membership on an entity's Board of Directors or advisory committees, Research Funding; Blueprint Medicine: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding; Daiichi-Sankyo: Membership on an entity's Board of Directors or advisory committees; Astellas: Membership on an entity's Board of Directors or advisory committees; incyte: Membership on an entity's Board of Directors or advisory committees, Research Funding; Rampal: Membership on an entity's Board of Directors or advisory committees; Galecto, Inc.: Consultancy; Promedior: Consultancy. Talati: AbbVie: Honoraria; Astellas: Speakers Bureau; Jazz: Speakers Bureau; Pfizer: Honoraria; BMS: Honoraria. Madanat: Onc Live: Honoraria; Blue Print Pharmaceutical: Honoraria; Stem line pharmaceutical: Honoraria; Geron Pharmaceutical: Consultancy. Blachly: KITE: Consultancy, Honoraria; INNATE: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria; AstraZeneca: Consultancy, Honoraria. Walker: Karyopharm Therapeutics: Current Employment, Current holder of individual stocks in a privately-held company, Current holder of stock options in a privately-held company. Marcucci: Agios: Other: Speaker and advisory scientific board meetings; Abbvie: Other: Speaker and advisory scientific board meetings; Novartis: Other: Speaker and advisory scientific board meetings. Blum: Leukemia and Lymphoma Society: Research Funding; Forma Therapeutics: Research Funding; Xencor: Research Funding; Nkarta: Research Funding; Celyad Oncology: Research Funding; AmerisourceBergen: Honoraria; Abbvie: Honoraria; Syndax: Honoraria. Larson: Novartis: Research Funding; Takeda: Research Funding; CVS/Caremark: Consultancy; Gilead: Research Funding; Astellas: Consultancy, Research Funding; Epizyme: Consultancy; Rafael Pharmaceuticals: Research Funding; Cellectis: Research Funding. Stone: GlaxoSmithKline: Consultancy; Syntrix/ACI: Membership on an entity's Board of Directors or advisory committees; Syndax: Membership on an entity's Board of Directors or advisory committees; Boston Pharmaceuticals: Consultancy; Bristol Myers Squibb: Consultancy; Aprea: Consultancy; BerGen Bio: Membership on an entity's Board of Directors or advisory committees; Arog: Consultancy, Research Funding; Astellas: Membership on an entity's Board of Directors or advisory committees; Foghorn Therapeutics: Consultancy; Gemoab: Membership on an entity's Board of Directors or advisory committees; Onconova: Consultancy; Innate: Consultancy; Janssen: Consultancy; Novartis: Consultancy, Research Funding; Jazz: Consultancy; Amgen: Membership on an entity's Board of Directors or advisory committees; Actinium: Membership on an entity's Board of Directors or advisory committees; AbbVie: Consultancy; Elevate Bio: Membership on an entity's Board of Directors or advisory committees; Syros: Membership on an entity's Board of Directors or advisory committees; Takeda: Consultancy; Agios: Consultancy, Research Funding; Celgene: Consultancy; Macrogenics: Consultancy. Byrd: Novartis, Trillium, Astellas, AstraZeneca, Pharmacyclics, Syndax: Consultancy, Honoraria; Newave: Membership on an entity's Board of Directors or advisory committees; Vincerx Pharmaceuticals: Current equity holder in publicly-traded company, Membership on an entity's Board of Directors or advisory committees. Mims: Xencor: Research Funding; Leukemia and Lymphoma Society's Beat AML clinical study: Consultancy, Research Funding; Aptevo: Research Funding; Daiichi Sankyo: Consultancy, Research Funding; Glycomemetics: Research Funding; Kartos Pharmaceuticals: Research Funding; Genentech: Consultancy; Abbvie: Consultancy; BMS: Consultancy; Kura Oncology: Consultancy; Syndax Pharmaceuticals: Consultancy; BMS: Consultancy; Jazz Pharmaceuticals: Consultancy; Aptevo: Research Funding. Sweet: Gilead: Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees; Astellas: Consultancy, Membership on an entity's Board of Directors or advisory committees; AROG: Membership on an entity's Board of Directors or advisory committees; Bristol Meyers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees. Eisfeld: Karyopharm (spouse): Current Employment.

Abstract: The early thymic precursor (ETP) immunophenotype was previously reported to confer poor outcome in T-cell acute lymphoblastic leukemia (T-ALL), requiring prospective confirmation using contemporary risk-adjusted therapy. Between 2009 and 2014, 1,256 newly-diagnosed children and young adults enrolled on COG AALL0434 were assessed for ETP status and minimal residual disease (MRD) using flow cytometry at a central reference laboratory. Subjects were categorized as ETP (n=145; 11.5%), Near-ETP (n=209; 16.7%) or Not-ETP (n=902, 71.8%). Despite higher rates of induction failure for ETP (6.2%) and Near-ETP (6.2%) than Not-ETP (1.2%) (P & lt;0.0001), all 3 groups showed excellent 5-year event-free survival (EFS) and overall survival (OS): ETP (80.4±3.9%; 86.8±3.4%), Near-ETP (81.1±3.3%; 89.6±2.6%) and Not-ETP (85.3±1.4%; 90.0±1.2%) (P=0.1679; P=0.3297). There was no difference in EFS or OS for subjects with day 29 MRD & lt;0.01% vs. 0.01%-0.1%. However, Day 29 MRD ≥0.1% was associated with inferior EFS and OS for patients with Near-ETP and Not-ETP, but not for those with ETP. Subjects with near-ETP and Not-ETP and a presenting WBC ≥200,000/microliter had inferior EFS and OS, but not for ETP. For subjects with Day 29 MRD ≥1%, end-consolidation MRD ≥0.01% was a striking predictor of inferior EFS (80.9±4.1% vs. 52.4±8.1%; P=0.0001). When considered as a single variable, subjects with all three T-ALL phenotypes had similar outcomes, and subjects with persistent post-induction disease had inferior outcomes regardless of their ETP phenotype. Although ETP status alone is not an independent predictor of outcome, future studies may provide additional insights into the mechanistic basis of resistant disease in stem-like T-ALL. Clinical trial is registered at AALL0434 (NCT00408005)