Gimotty, Phyllis A.

Abstract Background: Despite advances, the majority of patients (pts) with acute myeloid leukemia (AML) will die of their disease. Current genetics-based risk classification schemes inadequately predict outcome. We sought to determine if a novel methylation-based biomarker could enhance risk stratification in AML. Methods: Using a novel methylation assay (xMELP) validated for the clinical laboratory, we performed DNA methylation assessment at 17 previously identified prognostic loci to calculate a summary methylation statistic (M-score, Wertheim et al. Clin Chem 2015) for 166 pts with de novo AML treated at the University of Pennsylvania (UPENN). Targeted next-generation sequencing (NGS) of 33 hematologic malignancy-associated genes was performed for a 136 pt subset. The association of M-score with other prognostic variables and outcome [complete remission (CR) and overall survival (OS)] was evaluated. Median follow-up was 68.1 mos (range 1.4-150.2) among 38 survivors and 10.5 mos (range 0.1-95.2) among those (n=128) deceased. The optimal M-score for identifying groups with differing OS in the total UPENN cohort defined a binary classifier. The classifier was validated in UPENN subgroups and in a separate ECOG ACRIN E1900 trial cohort. Results: The mean and median M-score for the UPENN cohort was 92.3 (95% confidence interval [CI], 87.4-97.2) and 91.4 (range, 30.8-97.3), respectively; the M-score was not significantly associated with age, gender, specimen type, blast percent, NPM1, or FLT3-ITD. Patients with favorable cytogenetics had a lower mean M-score than those with non-favorable cytogenetics; there was no difference between intermediate and unfavorable cytogenetic groups. Univariate analyses demonstrated that a 10-unit increase in M-score was associated with a 10% increase in the hazard of death (HR 1.1; P<.0001) and a 20% increase in the odds of failing to achieve CR (OR 1.2, P<.0001). In multivariable Cox analysis, higher M-score (HR 1.1, P=.011) and older age (P=.001) were significantly associated with increased hazard of death, while NPM1+/FLT3-ITD-status (P=.031) was associated with decreased hazard of death. In a multivariable logistic analysis, higher M-score (HR, 1.1, P=.034) and older age (P=.007) were associated with increased odds of failing to achieve CR, while favorable cytogenetics (P=.030) was associated with achievement of CR. Based on the maximization of the log-rank statistic, the optimal M-score cutpoint was 86, which defined a binary risk classifier (hazard of death for high vs low M-score: unadjusted HR 2.5, P<.0001; adjusted HR 1.9, P=.003). Median OS was 26.6 vs. 10.6 mos for low and high M-score groups (Figure). The CR rates for low and high M-score groups were 84% and 61%, respectively. The performance of the M-score classifier was confirmed in pts ≤ 60 yrs with intermediate cytogenetics (log-rank P=.001, OS in high vs low M-score groups: 36.4 vs 14.0 mos) and among pts who achieved CR with initial therapy (log-rank P<.00001, OS 43.9 vs 17.2 mos). The M-score classifier identified groups with different outcome regardless of allogeneic transplant. The M-score classifier was validated in the E1900 cohort (n=383). The mean and median M-scores were similar to the UPENN cohort and M-score was significantly associated with OS on multivariable analysis (P<0.0001). The M-score classifier identified E1900 subgroups with different OS (log-rank P<.00001; OS 29.5 vs 12.6 mos), a finding confirmed in the intermediate cytogenetics group, in those aged <50 and ≥50 yrs, and among pts assigned to both standard and high dose daunorubicin. Notably, high dose daunorubicin benefited patients with high M-scores (P=.001), but not those with low M-scores (P=.328). We also evaluated the prognostic value of the M-score in the context of an extended molecular profile. Random forest analysis of the UPENN cohort showed that M-score and age are the most robust predictors of OS, while a subset of recurrent mutations (FLT3-ITD, NPM1, IDH2, TET2, TP53, NRAS, CEBPA) also contribute to prognosis, but to a lesser degree. Conclusion: The M-score and associated classifier represent promising tools for clinical decision-making in AML and deserve further investigation. The prognostic value of the M-score may be superior to mutational analysis. Optimal methods for integration of M-score, clinical and genetic information are being defined. Figure 1. Figure 1. Disclosures Loren: Merck: Research Funding. Levine:Foundation Medicine: Consultancy; CTI BioPharma: Membership on an entity's Board of Directors or advisory committees; Loxo Oncology: Membership on an entity's Board of Directors or advisory committees.

Abstract Acute lymphoblastic leukemia (ALL) has a high relapse rate in adults. While the biology of the patient may be responsible for the marked difference in survival seen in comparison to children, variable adherence to complex chemotherapy regimens may also play a role. However, there is very little understanding about the risk factors for delays in therapy and the impact of delays on survival. To study delays in newly diagnosed adult ALL patients, we conducted an observational study using data from ECOG 2993/ MRC_UKALLXII (Rowe, Blood 2005). We analyzed Ph- patients who started intensification after documented complete remission (CR). A long delay (LD) was defined as > 98 days from start of induction to start of intensification (IS), which was >2 weeks delay beyond the 84 days recommended per protocol. A Very Long Delay (VLD) was defined as a >4 weeks delay. Of 2109 patients enrolled, 1247 patients met inclusion criteria for analysis. Of note, 435 Ph- patients who achieved CR after induction but did not proceed to intensification were excluded. In univariate analysis, female sex (p<0.001), Black race (p=0.01), and older age (p<0.001) were associated with increased odds of LD. During induction presence of infection (p=0.01), dose reductions (p=0.001), duration of neutropenia (p=0.007), thrombocytopenia (p<0.001), and hospitalization duration (p<0.001) were associated with LD. In multivariate regression, age, female sex, dose reduction, Black race, and hospitalization duration were significantly associated with LD and VLD (Table I). At 2 years after diagnosis, 801/1247 (64.2%) patients were alive. Of the surviving patients, 181 (22.5%) had VLD, and 620 (77.4%), had delay <4 weeks, p=0.073. Of the alloHCT patients, 333 were alive: 57/333 (17%) had VLD, and 276/333 (83%) had been delayed <4 weeks (p=0.036). As of July 2014, 687/1247 (55%) patients have died, with a median time to death from start of intensification of 13.3 months (range 0.8-231). Survival analysis was stratified by post-remission therapy, with living patients censored at date last seen. Patients who received myeloablative allogeneic HCT (allo HCT) had poorer overall survival from start of intensification (OS-IS) and event free survival (EFS-IS) after LD or VLD. While OS-IS and EFS-IS were significantly worse for alloHCT patients after VLD (p=0.02 and p=0.03) respectively, survival was not worse for non-transplant patients after VLD (p=0.24 and p=0.10) (Figure I). In a multivariate Cox regression, adjusting for other high-risk disease features (age, cell lineage, and white cell count at diagnosis), patients who underwent allo HCT had significantly worse OS-IS (HR 1.4, p=0.02) and EFS-IS (HR 1.4, p=0.02) after experiencing VLD compared to alloHCT patients who experienced <4 weeks delay. When evaluating OS and EFS from diagnosis, VLD was still associated with poorer OS (HR 1.34, p=0.04) and EFS (HR 1.34, p=0.03). There was no difference in OS or EFS in patients who received non-transplant post-remission therapy based on delay. In a comprehensive analysis of the largest adult ALL study ever reported, we identified significant risk factors predictive of LD and VLD (>2 and >4 weeks beyond mandatory rest period). Our findings highlighted that patients were delayed because of chemotherapy toxicity and also identified healthcare disparities. VLD was associated with poorer OS and EFS in patients undergoing alloHCT, but not in patients undergoing non-transplant post remission therapy. Further studies are planned to prospectively identify patient barriers to on-schedule treatment with a goal of earlier intervention. The ability to better predict and intervene on risk factors for delay can improve adherence to protocol and optimize long-term survival. Table I: Multivariate Regression for LD and VLD Risk Factors Variable Odds Ratio 95% Confidence Interval p-value Days in the hospital Phase I Induction 1.01 1.00-1.02 0.04 Duration of Thrombocytopenia, Phase I 1.02 1.01-1.03 0.001 Age by Decade 1.2 1.08-1.31 <0.001 Reduced Dose in Induction 1.54 1.08-2.22 0.019 Sex, Female 1.56 1.22-2.0 <0.001 Race, Black 3.4 1.41-7.96 0.006 Figure 1 Figure 1. p=0.023 Disclosures No relevant conflicts of interest to declare.

Adults with acute lymphoblastic leukemia (ALL) have a poorer prognosis than children due to a high risk of relapse. One explanation may be variable adherence to dose‐intense chemotherapy. However, little is known about risk factors for delays in therapy and their impact on survival. We conducted an analysis of ECOG 2993/UKALLXII trial to study delays in postremission chemotherapy in adults with newly diagnosed ALL. Logistic regression was used to identify risk factors for a very long delay (VLD, >4 weeks) in start of intensification therapy. Cox regression was used to evaluate the impact of delays on overall survival (OS) and event‐free survival (EFS). We evaluated 1076 Philadelphia chromosome negative (Ph−) patients who completed induction chemotherapy, achieved complete remission, and started intensification. Factors independently associated with VLD included duration of hospitalization (odds ratio [OR] = 1.2, P < 0.001) during Phase I; thrombocytopenia during Phase I (OR = 1.16, P = 0.004) or Phase II (OR 1.13, P = 0.001); chemotherapy dose reductions during Induction Phase I (OR = 1.72, P < 0.014); female sex (OR = 1.53, P = 0.010); Black (OR = 3.24, P = 0.003) and Asian (OR = 2.26, P = 0.021) race; and increasing age (OR = 1.31, P < 0.001). In multivariate Cox regression, patients who underwent allogeneic stem cell transplant (alloHCT) had significantly worse OS (HR 1.4, P = 0.03) and EFS (HR 1.4, P = 0.02) after experiencing a VLD compared to alloHCT patients who experienced ≤4 weeks delay. Specific populations (female, older, Black, and Asian patients) were more likely to experience delays in chemotherapy, as were those with significant toxicity during induction. VLDs in therapy negatively affected outcomes in patients undergoing allografting. Am. J. Hematol. 91:1107–1112, 2016. © 2016 Wiley Periodicals, Inc.

BACKGROUND. Variable response to chemotherapy in acute myeloid leukemia (AML) represents a major treatment challenge. Clinical and genetic features incompletely predict outcome. The value of clinical epigenetic assays for risk classification has not been extensively explored. We assess the prognostic implications of a clinical assay for multilocus DNA methylation on adult patients with de novo AML. METHODS. We performed multilocus DNA methylation assessment using xMELP on samples and calculated a methylation statistic (M-score) for 166 patients from UPENN with de novo AML who received induction chemotherapy. The association of M-score with complete remission (CR) and overall survival (OS) was evaluated. The optimal M-score cut-point for identifying groups with differing survival was used to define a binary M-score classifier. This classifier was validated in an independent cohort of 383 patients from the Eastern Cooperative Oncology Group Trial 1900 (E1900; NCT00049517). RESULTS. A higher mean M-score was associated with death and failure to achieve CR. Multivariable analysis confirmed that a higher M-score was associated with death ( P = 0.011) and failure to achieve CR ( P = 0.034). Median survival was 26.6 months versus 10.6 months for low and high M-score groups. The ability of the M-score to perform as a classifier was confirmed in patients ≤ 60 years with intermediate cytogenetics and patients who achieved CR, as well as in the E1900 validation cohort. CONCLUSION. The M-score represents a valid binary prognostic classifier for patients with de novo AML. The xMELP assay and associated M-score can be used for prognosis and should be further investigated for clinical decision making in AML patients.

The American Joint Committee on Cancer (AJCC) has increasingly recognized the need for more personalized probabilistic predictions than those delivered by ordinal staging systems, particularly through the use of accurate risk models or calculators. However, judging the quality and acceptability of a risk model is complex. The AJCC Precision Medicine Core conducted a 2‐day meeting to discuss characteristics necessary for a quality risk model in cancer patients. More specifically, the committee established inclusion and exclusion criteria necessary for a risk model to potentially be endorsed by the AJCC. This committee reviewed and discussed relevant literature before creating a checklist unique to this need of AJCC risk model endorsement. The committee identified 13 inclusion and 3 exclusion criteria for AJCC risk model endorsement in cancer. The emphasis centered on performance metrics, implementation clarity, and clinical relevance. The facilitation of personalized probabilistic predictions for cancer patients holds tremendous promise, and these criteria will hopefully greatly accelerate this process. Moreover, these criteria might be useful for a general audience when trying to judge the potential applicability of a published risk model in any clinical domain. CA Cancer J Clin 2016;66:370–374. © 2016 American Cancer Society.