Mandrekar, Sumithra J.

7723 Background: It is critical that we understand the impact of patient, tumor, and treatment-related factors on patient prognosis for the proper design and analysis of Small Cell Lung Cancer (SCLC) trials. An analysis of 15 SCLC trials was performed to investigate and improve our understanding of several factors on OS. Methods: Data from 1623 patients (pts) were used. Age, gender, performance status (PS), tumor stage, body mass index (BMI), creatinine levels, hemoglobin levels, white blood cell counts (WBC), platelet counts, and bilirubin levels were tested for prognostic significance for OS both univariately and multivariately using a Cox Proportional Hazards Model. Models were stratified by protocol, and analyses carried out on the complete data available based on the selected covariates. Model discrimination (i.e., ability to discriminate patients with different survival times) was evaluated using the concordance index (COI). Results: Median follow-up was 63.1 months (range: 1.9 to 155.7). 58% and 42% of pts had extensive-stage or limited-stage SCLC, respectively. Patients with extensive-stage disease, PS>0, increased age, and male gender had significantly worse OS both univariately and multivariately. Patients with increased WBC had significantly worse OS univariately, however, WBC was not a significant predictor when adjusted for other factors. None of the other factors were prognostic for OS. Model discrimination improved by 6.3% when age, gender, PS, and stage were included in a model compared to a model with stage alone (COI improved from 0.63 to 0.67). Conclusions: Age, gender, PS and stage did better at predicting OS than stage alone. Further refinement of this model, including the addition of number of metastatic sites at baseline and treatment related factors, is currently underway. No significant financial relationships to disclose. [Table: see text]

7613 Background: Factors influencing the pattern of disease relapse after curative surgical resection in early stage NSCLC is unknown. We sought to evaluate the effect of tumor- and patient-related characteristics on the pattern of disease recurrence (local relapse and/or metastatic disease) and survival in relation to surgical resection for NSCLC. Methods: A consecutive retrospective series of 488 patients seen at Mayo Clinic Rochester who had complete resection of NSCLC between 1997 and 1998 was utilized. Cox proportional hazards model was used to evaluate the effect of age, gender, smoking status, TNM stage, number of lymph node (LN) involved, number of LN resected, and histopathologic diagnosis on RFS. Logistic regression was used to evaluate the effect on recurrence or death within the first 2 years after surgical resection. Results: Data on 342 patients with a median follow-up of 85 months (range: 0.1 to 162) are reported. 60% were male, and 81% had N0 stage at diagnosis. There were 26 (7.6%) never smokers. Median number of LN resected was 20 (interquartile range [IQR]: 14–29). Median age at surgery was 71 years (IQR: 64 to 76). A bi-modal pattern of local recurrence (N=62) after surgery for early stage NSCLC was observed, with 57% of patients having a local recurrence within 2 years and 21% of patients having a local recurrence from 5–7 years post-surgery. The median duration from surgery to first documented recurrence was 16 months (IQR: 8 to 39). While age, N stage, number of LN involved, and T stage were significant predictors of RFS univariately, only lesser LN resected (p=0.008), older age (p<0.0001) and higher T-stage (p=0.003) were significant adverse predictors of RFS in the multivariate analysis when adjusted for all factors. Higher T-Stage was associated with a significantly increased risk of recurrence or death within the first 2 years after surgical resection (p =0.004). Updated results using data from all 488 patients will be presented in the meeting. Conclusions: A trend towards a bimodal distribution of local recurrences after surgical resection of early stage NSCLC was observed. Increased number of LN resected, younger age and lower T stage were associated with better RFS. No significant financial relationships to disclose.

7547 Background: Sorafenib is a multikinase inhibitor with single-agent activity in previously treated NSCLC. In an effort to evaluate its single agent activity in previously untreated NSCLC, the NCCTG undertook a front-line “window of opportunity” study. Materials and Methods: Patients with stage IIIB (pleural effusion) or stage IV NSCLC received sorafenib dosed at 400 mg BID continuously, with a cycle defined as 4 weeks. Patients were evaluated weekly during the first 2 cycles with those who progressed rapidly going on to receive standard chemotherapy. Based on a two-stage Fleming design, if only at most 1 confirmed response was observed in the first 20 patients enrolled to stage I, the regimen would be considered ineffective. If 2 or more responses were observed, the study would proceed to stage 2 and accrue an additional 22 patients. If 5 or more confirmed responses were observed, the regimen would be recommended for further testing. Results: The study did not meet the stage I efficacy criteria (only 1 confirmed partial response in the first 20 patients) and was permanently closed after enrolling 25 evaluable patients [15 females, 10 males; 4 stage IIIB, 21 stage IV; median age 67 (45–85)]. 2 patients are still receiving treatment (14 and 15 months). No grade 3 or higher hematologic adverse events were observed. Thirteen (52%) patients had a grade 3 non-hematologic adverse event with fatigue (20%), diarrhea (8%), and dyspnea (8%) being the most common. There was one grade 4 pulmonary hemorrhage. A total of 3 (12%) PRs; and 7 (28%) SD were observed in the 25 patients 7 (28%) patients were progression- free at 24 weeks. Median survival and median time to progression were 8.8 and 2.9 months respectively. Conclusion: While the pre- specified efficacy endpoints were not met, the objective response rate of 12% and median survival of 8.8 months suggest that single agent sorafenib has activity similar to two-drug combinations. The feasibility and utility of the “window of opportunity” design in estimating the activity of novel compounds was demonstrated. Finally, the single-agent activity of sorafenib argues for combination studies with standard chemotherapy agents. No significant financial relationships to disclose.

6511 Background: In March 1998, the Common Toxicity Criteria (CTC) version 2.0 introduced the collection of attribution of adverse events (AE) to study drug. Collection of attribution adds time and cost to the clinical trial process, and reporting in the literature has varied. At ASCO 2006 results were presented from NCCTG trial 97–24–51 that showed ∼ 50% of events on the placebo arm were reported as attributed to study drug and 25% of the time the same event was not consistently attributed. We sought to validate these results in a second placebo controlled trial. Methods: Patients on the placebo arm of the phase III ACOSOG trial Z9001 (imatinib mesylate vs. placebo after resection of primary gastrointestinal stromal tumors) were evaluated since the reported AEs could not be due to study drug. Attribution was collected per CTCv3.0 as not related, unlikely, possibly, probably, or definitely related, and categorized as “unrelated” (not related or unlikely) and “related” (possible, probable, or definite). Patterns were evaluated using generalized estimating equations adjusting for multiple events per patient. Results: 202 patients and 2871 AEs were included. 52% of AEs were reported as “related”. Known imatinib AEs were more likely to be reported as “related”. The reported rate of AE relatedness varied by AE type. No patterns were observed by gender, age, PS, severity or visit of AE. When the same event was reported on the same patient on multiple visits, the attribution category changed at least once 33% of the time with 19% changing from “related” to “unrelated” or vice versa. Conclusion: 52% of events on the placebo arm of Z9001 were reported as attributed to study drug and 19% of the time the same event was not consistently attributed. These data provide further evidence that attribution is difficult to determine, unreliable, and of questionable value in interpreting randomized clinical trials. No significant financial relationships to disclose. [Table: see text]

Abstract Purpose Preclinical and clinical data have shown promise in using antiangiogenic agents to treat malignant pleural mesothelioma (MPM). We conducted this phase II study to evaluate the efficacy and toxicity of single-agent pazopanib in patients with MPM. Materials and Methods Patients with MPM who had received 0–1 prior chemotherapy regimens were eligible to receive pazopanib at a dose of 800 mg daily. The primary endpoint was progression-free survival rate at 6 months (PFS6), with a preplanned interim analysis for futility. Secondary endpoints included overall survival (OS), PFS, adverse events assessment and clinical benefit (complete response, partial response [PR], and stable disease [SD]). Results Thirty-four evaluable patients were enrolled, with a median age of 73 years (49–84). The trial was closed early because of lack of efficacy at the preplanned interim analysis. Only 8 patients (28.6%; 95% confidence interval [CI], 13.2–48.7%) in the first 28 evaluable were progression-free at 6 months. PFS6 was 32.4% (95% CI, 17.4–50.5). There were 2 PR (5.9%) and 16 SD (47.1%). The overall median PFS and OS were 4.2 months (95% CI, 2.0–6.0) and 11.5 months (95% CI: 5.3–18.2), respectively. The median PFS and OS for the previously untreated patients was 5.4 months (95% CI, 2.7–8.5) and 16.6 months (95% CI, 6.6–30.6), respectively; and 2.0 months (95% CI, 1.3–4.2) and 5.0 months (95% CI: 3.0–11.9), respectively, for the previously treated patients. Grade 3 or higher adverse events were observed in 23 patients (67.6%). Conclusion Single-agent pazopanib was poorly tolerated in patients with MPM. The primary endpoint of PFS6 was not achieved in the current study. ClinicalTrials.gov identification number. NCT00459862. Implications for Practice Single-agent pazopanib did not meet its endpoint in this phase II trial in malignant mesothelioma. Pazopanib is well tolerated in mesothelioma patients with a manageable toxicity profile. There is a need to better identify signals of angiogenesis that can be targeted in mesothelioma. Encouraging findings in frontline treatment warrant further investigations in combination with chemotherapy or immunotherapy.

Abstract Patients with acute myeloid leukemia (AML) harboring FLT3 internal tandem duplications (ITDs) have poor outcomes, in particular AML with a high (≥0.5) mutant/wild-type allelic ratio (AR). The 2017 European LeukemiaNet (ELN) recommendations defined 4 distinct FLT3-ITD genotypes based on the ITD AR and the NPM1 mutational status. In this retrospective exploratory study, we investigated the prognostic and predictive impact of the NPM1/FLT3-ITD genotypes categorized according to the 2017 ELN risk groups in patients randomized within the RATIFY trial, which evaluated the addition of midostaurin to standard chemotherapy. The 4 NPM1/FLT3-ITD genotypes differed significantly with regard to clinical and concurrent genetic features. Complete ELN risk categorization could be done in 318 of 549 trial patients with FLT3-ITD AML. Significant factors for response after 1 or 2 induction cycles were ELN risk group and white blood cell (WBC) counts; treatment with midostaurin had no influence. Overall survival (OS) differed significantly among ELN risk groups, with estimated 5-year OS probabilities of 0.63, 0.43, and 0.33 for favorable-, intermediate-, and adverse-risk groups, respectively (P &lt; .001). A multivariate Cox model for OS using allogeneic hematopoietic cell transplantation (HCT) in first complete remission as a time-dependent variable revealed treatment with midostaurin, allogeneic HCT, ELN favorable-risk group, and lower WBC counts as significant favorable factors. In this model, there was a consistent beneficial effect of midostaurin across ELN risk groups.

Background The phase 3 trial A041202 solidified the Bruton's Tyrosine Kinase (BTK) inhibitor ibrutinib as a standard of care for older patients with previously untreated CLL by showing superior progression-free survival (PFS) as compared with bendamustine plus rituximab. While ibrutinib is highly effective in previously untreated CLL, there do remain disadvantages to this therapy, specifically the low rate of complete response (CR) and therefore the need for continuous administration, which increases cost and toxicity. In older patients especially, toxicities with ibrutinib are common; 17% of patients had atrial fibrillation and 29% had grade 3 or higher hypertension on the A041202 study. Thus, strategies to decrease the exposure time to ibrutinib are of interest. Venetoclax is an inhibitor of BCL2 that has shown efficacy as a single agent and in combination with monoclonal antibodies, specifically the anti-CD20 monoclonal antibody obinutuzumab for patients with previously untreated CLL. One significant advantage to venetoclax is the ability to produce CRs and minimal residual disease negative (MRD-) responses. In this study, we compare ibrutinib plus obinutuzumab (IO) to ibrutinib plus venetoclax plus obinutuzumab (IVO) with a response-dependent discontinuation. While other studies have been designed with the goal of discontinuation of ibrutinib through combinations with venetoclax, no other study has been presented using a response-dependent discontinuation strategy. Study Design and Methods A041702 is a randomized phase 3 study led by the Alliance for Clinical Trials in Oncology that is currently enrolling through the NCI National Clinical Trials Network (NCTN). CLL patients age 70 years or older who are previously untreated and in need of therapy are eligible. Previous treatment of autoimmune complications with steroids or rituximab is allowed. Patients must have intermediate- or high-risk Rai stage, ECOG performance status 0-2, ANC ≥ 1000/mm3 unless due to marrow involvement, and platelets ≥ 30,000/mm3. CrCl must be ≥ 40 mL/min and AST/ALT ≤ 2.5x upper limit of normal. Patients with hepatitis B must have undetectable viral load, and patients must not have an intercurrent illness that is expected to limit survival to < 5 years. Warfarin and strong inhibitors or inducers of CYP3A4/5 are not permitted. Patients are initially preregistered to the study and submit a peripheral blood sample for central FISH analysis of del(17p). Patients who are registered are randomized 1:1 to Arm 1 (IO) or Arm 2 (IVO), and are stratified by Rai stage and presence of del(17p). IO consists of I daily starting cycle 1 day 1, and O dosed as standard starting cycle 1 day 1 and continuing to cycle 6 day 1. IVO consists of IO as in Arm 1, with V starting cycle 3 day 1 with standard 5-week ramp-up and continuing until cycle 14 day 28. At the end of 14 cycles, patients in both arms undergo response evaluation with central peripheral blood and bone marrow MRD testing. Patients on IO then continue I indefinitely. Patients on IVO who are in a bone marrow MRD- CR discontinue all therapy, and those who are not continue I indefinitely. The primary objective of the study is to compare PFS between IO and IVO using the strategy of response-dependent discontinuation. There is 90% power to detect a hazard ratio for PFS of 0.55 (corresponding to 5-year PFS rates of 70% and 82.187% for IO and IVO, respectively), at a one-sided significance level of 0.025 by a log-rank test. This design requires 128 events and 431 total evaluable patients assuming uniform accrual over the course of 3 years and minimum follow-up of 5 years. The study includes two interim analyses for superiority when 50% and 75% of the expected number of events have been observed and three interim analyses for futility when 25%, 50%, and 75% of the expected number of events have been observed. Conclusions A041702 is an ongoing phase 3 clinical trial using a novel response-dependent discontinuation method. Results of this study have the potential to change the standard of care for older patients with previously untreated CLL. The study is expected to accrue for 3 years beginning January 2019, and we welcome participation from sites throughout the NCTN. Support: U10CA180821, U10CA180882, UG1CA189823, U24CA196171; U10CA180820 (ECOG-ACRIN); https://acknowledgments.alliancefound.org; ClinicalTrials.gov Identifier: NCT03737981 Disclosures Woyach: Janssen: Consultancy, Research Funding; Pharmacyclics LLC, an AbbVie Company: Consultancy, Research Funding; AbbVie: Research Funding; Karyopharm: Research Funding; Loxo: Research Funding; Morphosys: Research Funding; Verastem: Research Funding. Lozanski:Beckman Coulter: Research Funding; Boehringer Ingelheim: Research Funding; Stemline Therapeutics Inc.: Research Funding; Genentec: Research Funding. Ding:Merck: Research Funding; DTRM Biopharma: Research Funding. Hill:Pharmacyclics: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; AstraZeneca: Consultancy, Honoraria; Celegene: Consultancy, Honoraria, Research Funding; Seattle Genetics: Consultancy, Honoraria; Takeda: Research Funding; Amgen: Research Funding; TG therapeutics: Research Funding; Abbvie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Genentech: Consultancy, Research Funding; Kite: Consultancy, Honoraria; Gilead: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees. Stone:Argenx, Celgene, Takeda Oncology: Other: Data and Safety Monitoring Board/Committee: ; Novartis, Agios, Arog: Research Funding; AbbVie, Actinium, Agios, Argenx, Arog, Astellas, AstraZeneca, Biolinerx, Celgene, Cornerstone Biopharma, Fujifilm, Jazz Pharmaceuticals, Amgen, Ono, Orsenix, Otsuka, Merck, Novartis, Pfizer, Sumitomo, Trovagene: Consultancy. Byrd:Janssen: Consultancy, Other: Travel Expenses, Research Funding, Speakers Bureau; BeiGene: Research Funding; Pharmacyclics LLC, an AbbVie Company: Other: Travel Expenses, Research Funding, Speakers Bureau; Gilead: Other: Travel Expenses, Research Funding, Speakers Bureau; Pharmacyclics LLC, an AbbVie Company: Other: Travel Expenses, Research Funding, Speakers Bureau; Genentech: Research Funding; Ohio State University: Patents & Royalties: OSU-2S; Janssen: Consultancy, Other: Travel Expenses, Research Funding, Speakers Bureau; Gilead: Other: Travel Expenses, Research Funding, Speakers Bureau; Novartis: Other: Travel Expenses, Speakers Bureau; Gilead: Other: Travel Expenses, Research Funding, Speakers Bureau; Pharmacyclics LLC, an AbbVie Company: Other: Travel Expenses, Research Funding, Speakers Bureau; TG Therapeutics: Other: Travel Expenses, Research Funding, Speakers Bureau; Novartis: Other: Travel Expenses, Speakers Bureau; Ohio State University: Patents & Royalties: OSU-2S; Acerta: Research Funding; Novartis: Other: Travel Expenses, Speakers Bureau; BeiGene: Research Funding; Ohio State University: Patents & Royalties: OSU-2S; TG Therapeutics: Other: Travel Expenses, Research Funding, Speakers Bureau; Acerta: Research Funding; Genentech: Research Funding; BeiGene: Research Funding; Genentech: Research Funding; Acerta: Research Funding; TG Therapeutics: Other: Travel Expenses, Research Funding, Speakers Bureau; Janssen: Consultancy, Other: Travel Expenses, Research Funding, Speakers Bureau.

With the launch of the National Cancer Institute’s Precision Medicine Initiative in 2015, there has been a shift to trial designs that tailor health care solutions to individual patients by using a screening platform and by moving away from the one-trial/one-biomarker-at-a-time approach. To make precision medicine a reality, it is critical to identify and validate potential biomarkers to help select patients who will truly benefit from a targeted therapy. In this article, we discuss five trial designs: enrichment, umbrella, basket, subgroup, and window of opportunity. For each trial design, we describe the design characteristics, use ongoing or completed trials as case studies, provide any recent advances to the trial design, and discuss advantages and disadvantages of each design.

Abstract Introduction: The most effective initial therapy for older adults with CLL has not yet been established due to the lack of comparison of chemoimmunotherapy (CIT) and targeted therapy with the Bruton's Tyrosine Kinase (BTK) inhibitor ibrutinib. CIT has been the gold standard since studies showing that addition of CD20 antibody to chemotherapy prolongs survival. Bendamustine plus rituximab (BR) is one standard, more aggressive CIT regimen for patients (pts) age 65 or older. While ibrutinib has been FDA approved for untreated CLL since 2016, it has only been compared to chlorambucil, which is relatively ineffective, and never before to aggressive CIT. Additionally, the benefit of the addition of rituximab to ibrutinib in this setting has not been prospectively studied in a phase 3 trial. As part of a randomized phase 3 trial, the Alliance sought to answer these important clinical questions. Pts and Methods: Alliance A041202 is a multicenter NCI National Clinical Trials Network phase 3 study comparing BR (Arm 1) with ibrutinib (Arm 2) and the combination of ibrutinib plus rituximab (Arm 3) to determine whether ibrutinib-containing regimens are superior to CIT in terms of PFS. Additionally, this study sought to determine if adding rituximab to ibrutinib would prolong PFS over ibrutinib alone. At time of progression, pts on Arm 1 could cross over to Arm 2. Eligible pts were those age ≥ 65 years with previously untreated, symptomatic CLL. Pts had a CrCl ≥ 40 mL/min, bilirubin ≤ 1.5 x ULN, and no significant life-limiting intercurrent illness or need for warfarin treatment. Pts were stratified based upon Rai stage, Zap-70 methylation performed centrally, and del(17)(p13.1) or del(11)(q22.3) by local interphase cytogenetics and were randomized 1:1:1 to each arm. With 166 pts per arm, the trial was powered to detect an improvement in 2-year PFS from 61% in Arm 1 to 75% in Arms 2 or 3 (HR=0.586) using two one-sided log-rank tests with type I error rate of 2.5% and 90% power. The Alliance Data and Safety Monitoring Board approved the data release after meeting the protocol-defined efficacy threshold at a planned interim analysis with a one-sided critical value of 0.001538. These data were locked July 2, 2018; updated results will be presented at the meeting. Results: Between 12/9/2013 and 5/16/2016, 547 pts were registered and randomized (Arms 1: 183, 2: 182, and 3: 182). Median age was 71 years and 67% of pts were men. High-risk Rai stage (stage III/IV) was seen in 54%, unmethylated Zap-70 in 53%, and del(17p) or del(11q) by local FISH in 28%. Local vs centralized FISH was performed for del(11q) and del(17p) with agreement between local and central results in 94% (Kappa=0.80) and 97% (Kappa=0.76) of pts, respectively. 525 (96%) pts were eligible and included in the primary PFS analysis (Arms 1: 176, 2: 178, and 3: 171). With median follow-up of 32 months (mo), median PFS was 41 mo in Arm 1 and has not been reached in Arms 2 or 3 (HR comparing Arm 2 to 1 is 0.40 with one-sided p&lt;0.0001; HR comparing Arm 3 to 1 is 0.41 with one-sided p&lt;0.0001; HR comparing Arm 3 to 2 is 1.01 with one-sided p=0.48). 2-year PFS estimates were 74%, 87% in 2, and 88% in Arms 1, 2, and 3 respectively. At this time, there are no significant differences in overall survival (OS) among arms (p=0.87), median OS has not been reached for any arm, and 2-year OS estimates were 95%, 90%, and 94% in Arms 1, 2, and 3, respectively. Adverse events (AEs) were compared among arms using Fisher's exact tests. Grade 3+ treatment-emergent AEs were seen in 428 of 537 evaluable pts with 61%, 41%, and 38% of pts experiencing Grade 3+ heme AEs (p&lt;0.0001) and 60%, 72%, and 71% of pts experiencing Grade 3+ non-heme AEs (p=0.03) in Arms 1, 2, and 3 respectively. Grade 5 AEs were seen in 5 (2.8%), 14 (7.8%), and 14 (7.7%) pts (p=0.07). Unexplained or unwitnessed death over the entire observation period was seen in 2 (1.1%), 7 (3.9%), and 4 (2.2%) pts (p=0.24) in Arms 1, 2, and 3 respectively. Conclusions: This international phase 3 trial demonstrates that ibrutinib produces superior PFS to standard CIT in older pts with CLL and justifies it as a standard of care treatment for pts age 65 and older. The addition of rituximab does not prolong PFS with ibrutinib. While ibrutinib represents a major therapeutic advance, toxicities and also cost justify future efforts to reduce the need for long-term continuous treatment. Support: K23CA178183, R01CA183444, U10CA180821, U10CA180882, U24CA196171, Clinicaltrials.gov identifier: NCT01886872 Figure. Figure. Disclosures Ding: Merck: Research Funding. Bartlett:Astra Zeneca: Research Funding; ImaginAB: Research Funding; Seattle Genetics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Pharmacyclics: Research Funding; Bristol-Meyers Squibb: Research Funding; Gilead: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Genentech: Research Funding; Pharmacyclics: Research Funding; Affimed: Research Funding; Janssen: Research Funding; Novartis: Research Funding; Merck & Co: Research Funding; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Pfizer: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Acerta: Membership on an entity's Board of Directors or advisory committees; Celgene: Research Funding; Immune Design: Research Funding; Forty Seven: Research Funding; Novartis: Research Funding; Millennium: Research Funding. Brander:BeiGene: Other: Institutional research funding for non investigator initiated clinical trial, Research Funding; TG Therapeutics: Consultancy, Honoraria, Other: Institutional research funding for non investigator initiated clinical trial, Research Funding; Genentech: Consultancy, Honoraria, Other: Institutional research funding for non investigator initiated clinical trial, Research Funding; Novartis: Consultancy, Other: DSMB; AbbVie: Consultancy, Honoraria, Other: Institutional research funding for non investigator initiated clinical trial, Research Funding; Pharmacyclics, an AbbVie Company: Consultancy, Honoraria, Research Funding; Teva: Consultancy, Honoraria; Acerta: Other: Institutional research funding for non investigator initiated clinical trial, Research Funding; DTRM: Other: Institutional research funding for non investigator initiated clinical trial, Research Funding. Barr:AbbVie, Gilead: Consultancy. Parikh:Gilead: Honoraria; Pharmacyclics: Honoraria, Research Funding; MorphoSys: Research Funding; Janssen: Research Funding; AstraZeneca: Honoraria, Research Funding; Abbvie: Honoraria, Research Funding. Coutre:Celgene: Research Funding; Janssen: Consultancy, Honoraria, Research Funding; Pharmacyclics LLC, an AbbVie Company: Honoraria, Research Funding; Gilead: Research Funding; Beigene: Consultancy; AbbVie: Consultancy, Research Funding. Lozanski:Novartis: Research Funding; BI: Research Funding; Genentech: Research Funding; Stem Line: Research Funding; Coulter: Research Funding; Beckman: Research Funding. Larson:Ariad/Takeda: Consultancy, Research Funding; BristolMyers Squibb: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding; Novartis: Consultancy, Research Funding. Erba:Amgen: Research Funding; Juno: Research Funding; Daiichi Sankyo: Consultancy, Research Funding; Daiichi Sankyo: Consultancy, Research Funding; MacroGenics: Consultancy; Juno: Research Funding; Janssen: Research Funding; Seattle Genetics: Consultancy, Research Funding; Janssen: Research Funding; Juno: Research Funding; Agios: Consultancy, Speakers Bureau; MacroGenics: Consultancy; Incyte: Consultancy, Speakers Bureau; Seattle Genetics: Consultancy, Research Funding; Takeda/Millenium: Research Funding; Novartis: Consultancy, Speakers Bureau; Takeda/Millenium: Research Funding; Incyte: Consultancy, Speakers Bureau; MacroGenics: Consultancy; Celgene: Consultancy, Speakers Bureau; Janssen: Research Funding; Novartis: Consultancy, Speakers Bureau; Celgene: Consultancy, Speakers Bureau; Astellas: Research Funding; Glycomimetics: Consultancy, Other: Chair, Data and Safety Monitoring Committee; MacroGenics: Consultancy; Daiichi Sankyo: Consultancy, Research Funding; Pfizer: Consultancy, Other: grant; Astellas: Research Funding; Juno: Research Funding; Janssen: Research Funding; Novartis: Consultancy, Speakers Bureau; Amgen: Research Funding; Agios: Consultancy, Speakers Bureau; Astellas: Research Funding; Agios: Consultancy, Speakers Bureau; Novartis: Consultancy, Speakers Bureau; Amgen: Research Funding; Pfizer: Consultancy, Other: grant; Pfizer: Consultancy, Other: grant; Astellas: Research Funding; Amgen: Research Funding; Agios: Consultancy, Speakers Bureau; Incyte: Consultancy, Speakers Bureau; Incyte: Consultancy, Speakers Bureau; Jazz: Consultancy, Speakers Bureau; Immunogen: Consultancy, Research Funding; Jazz: Consultancy, Speakers Bureau; Immunogen: Consultancy, Research Funding; Glycomimetics: Consultancy, Other: Chair, Data and Safety Monitoring Committee; Pfizer: Consultancy, Other: grant; Jazz: Consultancy, Speakers Bureau; Immunogen: Consultancy, Research Funding; Seattle Genetics: Consultancy, Research Funding; Jazz: Consultancy, Speakers Bureau; Seattle Genetics: Consultancy, Research Funding; Celgene: Consultancy, Speakers Bureau; Immunogen: Consultancy, Research Funding; Takeda/Millenium: Research Funding; Glycomimetics: Consultancy, Other: Chair, Data and Safety Monitoring Committee; Celgene: Consultancy, Speakers Bureau; Takeda/Millenium: Research Funding; Daiichi Sankyo: Consultancy, Research Funding; Glycomimetics: Consultancy, Other: Chair, Data and Safety Monitoring Committee. Owen:Janssen: Honoraria, Research Funding; Celgene: Research Funding; AstraZeneca: Honoraria, Research Funding; Pharmacyclics: Research Funding; F. Hoffmann-La Roche Ltd: Honoraria, Research Funding; AbbVie: Research Funding; Merck: Honoraria; Teva: Honoraria. Abramson:Bayer: Consultancy; Novartis: Consultancy; Merck: Consultancy; Karyopharm: Consultancy; Seattle Genetics: Consultancy; Verastem: Consultancy; Humanigen: Consultancy; Juno Therapeutics: Consultancy; Gilead: Consultancy; Celgene: Consultancy; Amgen: Consultancy.

Abstract Background: Overall survival (OS) remains the definitive primary efficacy endpoint to evaluate previously untreated acute myeloid leukemia (AML) therapies, but it requires prolonged follow-up. An earlier endpoint assessed post-treatment would expedite clinical trial conduct and accelerate patient access to effective new therapies. Our objective was to formally evaluate event-free survival (EFS) as a surrogate endpoint for OS in untreated AML. Methods: Individual patient data were analyzed from 2,475 patients (pts) from 4 multicenter, randomized controlled phase III trials of active treatment in previously untreated AML using anthracycline and cytarabine induction chemotherapy as the concurrent control (CALGB 10201, n=506, enrollment period 2003-2006, age 60-88 years (y); CALGB 10603, n=717, enrollment period 2008-2015, age 18-60 y, FLT3-mutated pts only; SWOG 0106, n=595, enrollment period 2004-2009, age 18-60 y; ECOG-ACRIN 1900, n=657, enrollment period 2002-2008, age 17-60 y). Individual patient-level surrogacy examines the association between the individual patients' EFS and OS time after adjusting for treatment effect, and was assessed using the copula bivariate survival model (Kendall's tau). Trial-level surrogacy measures how precisely the treatment effect on OS can be predicted on the basis of observed treatment effect on EFS, and was evaluated using both linear regression (R2WLS) weighted by trial size and Copula bivariate (R2Copula) models. Pre-specified criteria for surrogacy required either R2WLS or R2Copula ≥0.80, neither below 0.7, with either lower bound 95% Confidence Interval (CI) >0.60. Sensitivity analyses were conducted using different EFS definitions (Table 1). Results: With a median follow-up of 50.2 months for the 896 patients still alive, the median OS and EFS across all four trials were 20.9 months (95% CI: 19.0-22.7) and 5.6 months (95% CI: 4.5-6.4), respectively. Trial-level surrogacy for EFS was strong (R2WLS=0.79; R2Copula=0.89), indicating a high correlation of treatment effect between EFS and OS. At the individual patient-level, however, EFS showed weak association with OS (tau= 0.52), compared to the strength of trial-level surrogacy. The discrepancy between patient-level EFS and OS was greatest among patients who did not achieve a CR, followed by those who achieved a CR but relapsed (Figure 1). Sensitivity analysis on alternative EFS definitions showed that the trial-level surrogacy was similar, but individual patient-level surrogacy varied across different EFS definitions (Table 1). This is consistent with what we previously reported (ASH 2016): EFS estimates differed considerably based on the definition of induction failure (IF) in a single arm setting, but this had minimal impact on the estimation of the treatment effect using EFS in randomized trials. In addition, when considering only relapse and death as events (definition 4), both individual patient- and trial-level correlations were high. Conclusions: Correlation between EFS and OS was impacted by patients not achieving CR during induction. Despite the lack of patient-level correlation, a strong correlation between hazard ratios for treatment effects was observed between EFS and OS on the trial level. Hence, it remains debatable whether EFS represents a clinical benefit in itself for patient with untreated AML considering the strong correlation in treatment effects. Further validation is needed due to the small number of trials included and the heterogeneity across trials. Acknowledgment: We gratefully acknowledge the important contributions of the late Dr. Stephen H. Petersdorf, SWOG S0106 Study Chair. Support: U10CA180821, U10CA180882, U10CA180794, U10CA180820, U10CA180888; Clinicaltrials.gov Identifiers: NCT00085124 (10201), NCT00651261 (10603), NCT01253070 (11001), NCT00085709 (SWOG S0106), and NCT00049517 (ECOG-ACRIN E1900) Disclosures Uy: Curis: Consultancy; GlycoMimetics: Consultancy. Larson:Pfizer: Consultancy, Research Funding; BristolMyers Squibb: Consultancy, Research Funding; Novartis: Consultancy, Research Funding; Ariad/Takeda: Consultancy, Research Funding.