Shi, Qian

3564 Background: Lethal-7 (let-7) microRNA has been shown to inhibit colon cancer cell proliferation by inducing KRAS downregulation after binding to specific sites in the 3’- UTR. Recent studies identified a KRAS 3’-UTR polymorphism in the let-7 complimentary site (LCS6) that has been shown to weaken let-7 binding and alter KRAS expression. Carriers of the LCS6 G-allele showed worse survival in metastatic colorectal cancer from prior studies of limited sample size. In the current study, we evaluated the LCS6 variant in 2,834 Stage III colon cancer patients and its association with disease-free survival (DFS), KRAS mutation status, and other clinicopathological features. Methods: In the NCCTG phase III trial (N0147), the LCS6 variant was assayed in germline DNA extracted from whole blood using RT-PCR. Extracted tumor DNA was analyzed for KRAS exon 2 mutations. Chi-squared and two-sample t test were used to compare baseline factors and KRAS mutation status between patients defined by LCS6 variant status. Log-rank tests and multivariate Cox models assessed the unadjusted and adjusted associations between LCS6 status and DFS, respectively. Results: We identified 432 (15.2%) patients heterozygous or homozygous for the LCS6 G-allele and 2402 (84.8%) patients homozygous for the LCS6 T-allele. G-allele carriers were significantly more frequent in Caucasians than other races (Chi-Squared Test, p<0.0001). No associations were found between the LCS6 genotype and T stage, positive lymph node number, tumor differentiation, or primary tumor location (all p>0.2). Moreover, the LCS6 genotype was not associated with DFS (hazard ratio = 0.93, p=0.49) even after combining LCS6 genotype with KRAS mutation status. Conclusions: We report the largest association study investigating the LCS6 polymorphism and colon cancer outcome. There is no significant evidence that the germline LCS6 genotype was associated with DFS in stage III colon cancer patients. Additional studies are needed to determine if LCS6 genotype differs between tumor and germline DNA which may further clarify its prognostic value.

PURPOSE The Fast Healthcare Interoperability Resources (FHIR) is emerging as a next-generation standards framework developed by HL7 for exchanging electronic health care data. The modeling capability of FHIR in standardizing cancer data has been gaining increasing attention by the cancer research informatics community. However, few studies have been conducted to examine the capability of FHIR in electronic data capture (EDC) applications for effective cancer clinical trials. The objective of this study was to design, develop, and evaluate an FHIR-based method that enables the automation of the case report forms (CRFs) population for cancer clinical trials using real-world electronic health records (EHRs). MATERIALS AND METHODS We developed an FHIR-based computational pipeline of EDC with a case study for modeling colorectal cancer trials. We first leveraged an existing FHIR-based cancer profile to represent EHR data of patients with colorectal cancer, and then we used the FHIR Questionnaire and QuestionnaireResponse resources to represent the CRFs and their data population. To test the accuracy of and overall quality of the computational pipeline, we used synoptic reports of 287 Mayo Clinic patients with colorectal cancer from 2013 to 2019 with standard measures of precision, recall, and F1 score. RESULTS Using the computational pipeline, a total of 1,037 synoptic reports were successfully converted as the instances of the FHIR-based cancer profile. The average accuracy for converting all data elements (excluding tumor perforation) of the cancer profile was 0.99, using 200 randomly selected records. The average F1 score for populating nine questions of the CRFs in a real-world colorectal cancer trial was 0.95, using 100 randomly selected records. CONCLUSION We demonstrated that it is feasible to populate CRFs with EHR data in an automated manner with satisfactory performance. The outcome of the study provides helpful insight into future directions in implementing FHIR-based EDC applications for modern cancer clinical trials.

PURPOSE The microsatellite instability (MSI) or deficient mismatch repair (dMMR) phenotype is usually regarded as a single biologic entity, given the absence of comparative analyses regarding prognosis and response to chemotherapy between sporadic and familial dMMR cancers. PATIENTS AND METHODS Patients with stage III colon cancers were randomly assigned to FOLFOX (leucovorin, fluorouracil, and oxaliplatin) with or without cetuximab in 2 large adjuvant phase III trials (N = 5,577). Among patients with MSI and KRAS exon 2 wild-type (WT) tumors, the prognostic and predictive impacts of sporadic versus familial dMMR cancers and BRAF V600E mutational status were determined. Multivariable Cox proportional hazards models were used to assess disease-free survival (DFS) by treatment arm, adjusting for age, sex, tumor grade, Eastern Cooperative Oncology Group performance status, pT/pN stage, and primary tumor location. RESULTS Among patients with MSI status with complete data for dMMR mechanism analysis (n = 354), 255 (72%) had sporadic ( BRAF mutation and/or MLH1 methylation) and 99 (28%) had familial tumors ( BRAF WT and unmethylated MLH1 or loss of MSH2/MSH6/PMS2 protein expression). A large proportion of dMMR sporadic tumors were mutated for BRAF (n = 200). In patients treated with FOLFOX, DFS did not differ statistically by dMMR mechanism, whereas in patients treated with FOLFOX plus cetuximab, those with sporadic tumors had worse DFS than those with familial cancers (multivariable hazard ratio, 2.69; 95% CI, 1.02 to 7.08; P = .04). Considering the predictive utility, the interaction between treatment and dMMR mechanism was significant ( P = .03). Furthermore, a nonsignificant trend toward a deleterious effect of adding cetuximab to FOLFOX was observed in patients with BRAF-mutant but not BRAF WT tumors. CONCLUSION The addition of cetuximab to adjuvant FOLFOX was associated with shorter DFS in patients with sporadic dMMR colon cancer. Additional studies are needed to validate these results in metastatic disease.

Background: Disease progression (PD) after frontline IC therapy for DLBCL is a clinically significant event and only 20-40% of patients achieve durable remissions with salvage chemotherapy. Patients who experience early PD or have disease refractory to IC have especially poor outcomes. Chimeric antigen receptor T-cell therapy has emerged as a novel effective therapy for selected cases of relapsed or refractory (r/r) DLBCL, although its availability is limited by cost and logistic challenges. Simple, clinically applicable prognostic tools would be useful for selecting patients for consideration for novel therapies vs those who are more likely to be successfully managed by conventional therapies, but few have been developed for r/r DLBCL. Methods: Model building was performed in patients with PD after IC from 13 frontline, multicenter, randomized DLBCL clinical trials from the SEAL Consortium. All patients received rituximab and an anthracycline-based combination IC and were followed systematically; however therapy received, clinical, and laboratory data at progression were not available. OS was defined as time from first progression until death from any cause. Associations between variables and OS were evaluated using Cox models; splines were used to model functional forms. Validation was performed in the University of Iowa/Mayo Clinic SPORE Molecular Epidemiology Resource (MER) and Danish LYFO cohorts. Model performance was assessed using time-dependent concordance indices (c-stat), Brier scores, and calibration with metrics evaluated at two years from progression. Results: Model Development (SEAL): 1125 of 5112 patients had PD after IC. Median time to PD (TTP) was 11.8 months (IQR 6.6-23.5); median age at PD was 68 years (IQR 60-73). At a median follow-up of 21 months from PD (IQR 7-43), 732 patients (65%) had died and 24 month overall survival after PD (OS24) was 35% (95% CI: 32-38). TTP was strongly associated with post PD OS (spline p-value&lt;0.0001) with OS24 ranging from 18% in patients with TTP &lt;6 months compared to 69% in patients with TTP &gt; 36 months (Figure A). Additionally, age at PD (spline p-value&lt;0.0001) was associated with post PD OS. A model consisting of age at PD including patients 40-80 years and TTP ranging 0-60 months was created (n=1011, Figure B) due to sparse data outside these intervals. C-stat was 0.67, and the model was well calibrated (predicted OS24 = 34% vs. actual OS24 = 34%). External Validation (MER): The model was validated in 290 patients with DLBCL who initiated 2nd line therapy after PD to IC. Median age at PD was younger than the SEAL cohort at 62 years (IQR 57-70). Patients with biopsy proven indolent histology at relapse were excluded. Median TTP was 8.2 months (IQR 5.1-17.0). At a median follow-up of 87 months from PD, 201 patients (69%) had died. OS24 was 47% (95% CI: 41-53). The model showed similar concordance (c-stat=0.65), but underestimated OS24 (predicted =33% vs. 47% actual, Figure C). External Validation (LYFO): The model was validated in 599 patients with DLBCL and PD after frontline IC. Median age at PD was 67 years (IQR 60-73). Median TTP was 10.1 months (IQR 6.0-19.4). At a median follow-up of 82 months from PD, 435 patients (73%) had died. OS24 was 38% (95% CI: 34-42). The model showed similar concordance (c-stat=0.67) when applied to the LYFO cohort, but again underestimated OS24 (predicted =32% vs. 38% actual, Figure D). Case vignettes: A 74 year old patient who progressed 9 months after diagnosis would have a predicted OS24 of 20%. A 58 year old patient who progressed 32 months after diagnosis would have a predicted OS24 of 65% Conclusions: TTP to following IC is strongly associated with post-progression survival in DLBCL. We developed a model from the largest frontline clinical trial dataset in DLBCL and validated a simple to apply clinical prognostic tool in the r/r setting. The model allows better understanding of expected outcomes in r/r DLBCL and can aid design and interpretation of trial results in this setting. The model underestimated the actual survival probability when applied to non-trial validation cohorts. Recalibration of the model for transplant eligible patients and development of smartphone based point-of-care application of the model is ongoing. Figure Disclosures Maurer: Celgene: Research Funding; Nanostring: Research Funding; Morphosys: Membership on an entity's Board of Directors or advisory committees. Schmitz:Riemser: Consultancy, Honoraria; Celgene: Equity Ownership; Gilead: Honoraria; Novartis: Honoraria. Farooq:Kite Pharma: Research Funding; Celgene: Honoraria. Flowers:Optimum Rx: Consultancy; Burroughs Wellcome Fund: Research Funding; BeiGene: Consultancy, Research Funding; Karyopharm: Consultancy; AstraZeneca: Consultancy; Gilead: Consultancy, Research Funding; Eastern Cooperative Oncology Group: Research Funding; Genentech, Inc./F. Hoffmann-La Roche Ltd: Consultancy, Research Funding; Bayer: Consultancy; TG Therapeutics: Research Funding; Acerta: Research Funding; Celgene: Consultancy, Research Funding; National Cancer Institute: Research Funding; Denovo Biopharma: Consultancy; Pharmacyclics/Janssen: Consultancy, Research Funding; Spectrum: Consultancy; Millenium/Takeda: Research Funding; AbbVie: Consultancy, Research Funding; V Foundation: Research Funding. Frederiksen:Alexion: Research Funding; Gilead: Research Funding; Abbvie: Research Funding; Janssen Pharmaceuticals: Research Funding; Novartis: Research Funding. Cunningham:Eli Lilly: Research Funding; 4SC: Research Funding; Bayer: Research Funding; MedImmune: Research Funding; Celgene: Research Funding; AstraZeneca: Research Funding; Merrimack: Research Funding; Sanofi: Research Funding; Amgen: Research Funding; Janssen: Research Funding; Merck: Research Funding; Clovis: Research Funding. Jørgensen:Gilead: Membership on an entity's Board of Directors or advisory committees; Roche: Membership on an entity's Board of Directors or advisory committees. Poeschel:Amgen: Other: Travel, accommodations, expenses; Abbvie: Other: Travel, accomodations, expenses; Hexal: Speakers Bureau; Roche: Other: Travel, accomodations, expenses. Nowakowski:F. Hoffmann-La Roche Ltd: Research Funding; Curis: Research Funding; Selvita: Membership on an entity's Board of Directors or advisory committees; NanoString: Research Funding; MorphoSys: Consultancy, Research Funding; Genentech, Inc.: Research Funding; Bayer: Consultancy, Research Funding; Celgene: Consultancy, Research Funding. Seymour:Takeda: Consultancy; Celgene: Consultancy, Research Funding, Speakers Bureau; AbbVie: Consultancy, Honoraria, Research Funding, Speakers Bureau; Acerta: Consultancy; Janssen: Consultancy, Research Funding; Roche: Consultancy, Research Funding, Speakers Bureau. Merli:Takeda: Honoraria, Other: Travel Expenses; Gilead: Honoraria; Mundipharma: Honoraria; Roche: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel expenses, Research Funding; Sandoz: Membership on an entity's Board of Directors or advisory committees; Teva: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees, Other: Travel Expenses; Janssen: Honoraria. Haioun:novartis: Honoraria; celgene: Honoraria; roche: Consultancy; celgene: Consultancy; gilead: Consultancy; takeda: Consultancy; janssen cilag: Consultancy; amgen: Honoraria; servier: Honoraria. Tilly:roche: Membership on an entity's Board of Directors or advisory committees; servier: Honoraria; merck: Honoraria; Gilead: Honoraria; Janssen: Honoraria; BMS: Honoraria; Karyopharm: Consultancy; Astra-Zeneca: Consultancy; Celgene: Consultancy, Research Funding; Roche: Consultancy. Salles:Amgen: Honoraria, Other: Educational events; BMS: Honoraria; Merck: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis, Servier, AbbVie, Karyopharm, Kite, MorphoSys: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Educational events; Autolus: Consultancy, Membership on an entity's Board of Directors or advisory committees; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Educational events; Epizyme: Consultancy, Honoraria; Roche, Janssen, Gilead, Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Educational events. El-Galaly:Roche: Employment, Other: Travel support; Takeda: Other: Travel support.

TPS594 Background: Effective treatment options are very limited for patients with advanced refractory biliary tract cancer (BTC). Fluoropyrimidine-based chemotherapy regimen such as 5-fluorouracil and irinotecan are frequently utilized for these patients after first-line therapy despite lack of FDA approval. Trifluridine/tipiracil (FTD/TPI) is a novel oral nucleoside with antitumor activity in both fluoropyrimidine sensitive and resistant tumors due to its unique mechanisms of action. Given early toxicity and efficacy data from our previous study on single-agent trifluridine/tipiracil (FTD/TPI) in advanced BTC, the clinical evaluation of its combination with irinotecan represents a rational approach for the treatment of advanced refractory BTC. Methods: This is a single-arm phase II trial with a two-stage design to assess the efficacy of trifluridine/tipiracil (FTD/TPI) and irinotecan in advanced refractory BTC. Key eligibility criteria include histologically confirmed advanced, unresectable BTC who have progressed on at least one line of systemic therapy and have measurable disease per RECIST v1.1. Target accrual is 25. Treatment includes trifluridine/tipiracil (FTD/TPI) 25 mg/m2 on days 1-5 and irinotecan 180 mg/m2 on day 1 in 14-day cycles. Patients will be evaluated for response every 4 cycles and in the absence of disease progression, therapy may be given up to 2 years. The primary end point is the progression-free survival rate at 16 weeks. Secondary endpoints include overall response rate, disease control rate, progression-free survival, overall survival, and incidence of adverse events. Correlative biomarker studies include evaluations of circulating tumor DNA and circulating tumor cells at baseline, after 4 cycles and at progression; and development of patient-derived tumor organoids from pre-treatment biopsies for parallel treatments. This study was approved and funded in part by the National Comprehensive Cancer Network (NCCN) Oncology Research Program from general research support provided by Taiho Oncology, Inc. Clinical trial information: NCT 04072445.

89 Background: Monitoring of adverse events (AE) is crucial in clinical trials. Maximum grade per patient (pt) is commonly used but better metrics are needed to aid describing and comparing AE profiles. Methods: We developed and evaluated 2 longitudinal AE summary metrics. 1) Onset time of max grade refers to whether a pt has max grade within pre-specified timeframes for an AE, e.g. onset can be defined as “early” (max grade before the 6th cy) or “late” (≥ 6th cy). 2) Adverse effect load (AEL) is a longitudinal score of worst grade possible excluding death over the entire treatment for an AE. Higher AEL means worst overall experience of AE. We applied these metrics to real trial data. Pts were from 6 mCRC trials included in ARCAD database and received Irinotecan-based (n = 1,119) or Oxaliplatin-based (n = 1,230) treatments that did not include biologicals. AEs were diarrhea, nausea/vomiting, neutropenia/leukopenia, and neuropathy. We used linear model to AEL and logistic model to the other metrics, adjusting for age, sex, and number of metastases. Results: For nausea/vomiting, pts in Oxali-based chemo showed a higher AEL compared to patients in Iri-based (mean (M) [standard deviation (SD)] = 0.04 [0.06] vs. 0.02 [0.04]; p < 0.001) even though less pts had gr ≥ 3 (10.4% vs. 16.2%, resp.; p < 0.001), suggesting a lower-grade but persistent nausea/vomiting for Oxali-based. Among pts with diarrhea max gr 2, pts in Iri-based had higher AEL than with Oxali-based (M [SD] = 0.11 [0.11] vs. 0.08 [0.09]; p = 0.008), indicating more persistent diarrhea for Iri-based trts even among pts with same max grade. For neutropenia/leukopenia, pts in Oxali-based trts experienced higher AEL (M [SD] = 0.09 [0.13] vs. 0.05 [0.11], p < 0.001), and more pts in Oxali-based trts had gr ≥ 3 (70.1% vs. 64.4%; p = 0.002), suggesting that pts in Oxali-based trts experienced worst overall and max grade neutropenia/leukopenia compared to pts in Iri-based. Conclusions: To improve toxicity assessment in clinical trials, AEL and onset time of max grade are new measures that describe the evolution of adverse events over time. Further validation is warranted.

6 Background: Rates and survival outcomes for second-line therapy for mCRC for OA vs. YA are poorly understood. Methods: Pts with available subsequent treatment data after progression from 10 1st line trials were included. Associations between key clinical/disease characteristics, time to initial progression (TTiP) and rate of receipt of second-line therapy were evaluated. Time to progression (TTP) and overall survival (OS) were compared between OA and YA who were enrolled on second-line trials by Cox regression, adjusting for age, sex, ECOG PS, number of metastatic sites, presence of metastasis in lung/liver/peritoneum. Results: OA comprised 16.4% of first-line trials. OA and ECOG PS >0 were less likely to receive second-line therapy than YA. Odds of receiving second-line therapy decreased by 11% for each additional decade of life in multivariate analysis (p=0.0117). OA enrolled in second-line trials experience similar mTTP and mOS as YA (5.1 vs. 5.2mos; 11.6 vs 12.4mos, respectively). Conclusions: OA are less likely to receive 2nd line therapy for mCRC. We did not observe a statistical difference in survival outcomes for OA vs. YA following second-line therapy. Further study is needed to examine unmeasured factors, including comorbidity and functional status given observed inferior outcomes among adults with ECOG PS >0, and consideration given to inclusion of geriatric assessment to select OA likely to benefit from 2nd line therapy for mCRC. [Table: see text]

188 Background: Unplanned subgroup analyses from several studies have suggested primary tumor sidedness (PTS) as a potential prognostic and predictive parameter in metastatic colorectal cancer (mCRC). We aimed to investigate the prognostic and predictive impact of PTS on outcomes. Methods: PTS data of 7,828 mCRC patients (pts) from 10 first-line randomized trials in the ARCAD database were pooled. PTS was defined as right-sided (RS) or left-sided (LS) if tumor arose from the cecum to the hepatic flexure or from the splenic flexure to the rectum, respectively; transverse colon cancers were not included. Overall survival (OS) and progression-free survival (PFS) were assessed using Kaplan-Meier and Cox models adjusting for age, sex, performance status (PS), prior radiation/chemo, and stratified by treatment arm. Predictive value was tested by interaction term between PTS and treatment (anti-EGFR plus chemotherapy vs. chemotherapy alone). Results: Compared to RS pts (2407, 31%), LS pts (5421, 69%) had better OS (median: 21.6 v 16.8 mos; HRadj: 0.73, 95% CI 0.69-0.78, P < .001) and PFS (median 8.4 v 7.2 mos; HRadj: 0.81, 95% CI 0.76-0.86, P < .001). Results were consistent among subgroups defined by age, sex, PS, metastatic sites and chemo backbone (irinotecan- and oxaliplatin-based). Interaction between PTS and KRAS mutation was significant (Pinteraction< .001): LS is associated with better prognosis only among KRAS wild-type (wt) (HRadj: OS 0.62, 95% CI, 0.55-0.70; PFS 0.71, 95% CI 0.63-0.80), but not among KRAS mutated pts. Among KRAS wt pts, survival benefit from anti-EGFR was observed for LS, but not for RS (table). Conclusions: The prognostic value of PTS is restricted to the KRAS wt population. PTS is predictive of anti-EGFR efficacy, with a significant improvement of survival for LS mCRC pts. These results suggest treatment stratification in mCRC studies by both PTS and KRAS status. [Table: see text]

Introduction: Most patients with newly diagnosed FL treated with rituximab (R) alone or R + chemotherapy will experience prolonged progression-free survival and overall survival (OS), but it remains unclear what factors have the greatest influence on FL-associated and other causes of death in this patient population. We utilized individual patient data from 13 first-line randomized clinical trials from the FLASH database to perform a comprehensive multistate survival analysis to examine and quantify the relationships between clinical characteristics, treatment response, and early, intermediate, and late FL outcomes. Methods: The multistate survival analysis model defined states for "Alive after beginning Induction Treatment (TX)", "Alive after beginning Maintenance TX", "Death due to FL", and "Death from Other Causes" (Figure 1). We used the Aalen-Johansen estimator, a generalization of the Kaplan-Meier estimator, to calculate the likelihood of being in each model state and estimate the course of FL over time. Making no assumptions on the probability distributions and capable of coping with censored observations, the Aalen-Johansen estimator is a convenient and reliable nonparametric estimator for clinical data. Results: Among 7,465 FL patients with median age 56 (range 18-90) years, 49.2% were female; 28.7% Stage I-III, 71.3% Stage IV, and FLIPI was 0-1 (20.0%), 2 (36.8%), ≥ 3 (43.2%). Following initiation of induction treatment, 2-, 5- and 10-year death rates were 1.7%, 3.8%, and 5.8% due to FL, and 0.7%, 2.1%, and 4.8% from other causes (Figure 2). Death rates at 2, 5, and 10 years due to FL and other causes for subgroups based on clinical characteristics and treatment response are shown in Table 1. Notably, patients > 70 years and patients with FLIPI ≥ 3 had worse outcomes and patients achieving CR at 18, 24, and 30 months experienced improved outcomes. Conclusion: This is the largest study using data from randomized trials to quantify the impact of clinical factors on early, intermediate and late mortality by cause of death. We demonstrated that age > 70 years and FLIPI ≥ 3 were linked to increased FL-associated death and response to TX distinguished patients with favorable and poor outcomes. Future analyses should quantify the impact of predictors on the rate/time of FL outcomes in multivariable models. Disclosures Salles: Roche, Janssen, Gilead, Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Educational events; Amgen: Honoraria, Other: Educational events; BMS: Honoraria; Merck: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis, Servier, AbbVie, Karyopharm, Kite, MorphoSys: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Educational events; Epizyme: Consultancy, Honoraria; Autolus: Consultancy, Membership on an entity's Board of Directors or advisory committees; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Educational events. Hoster:Janssen: Research Funding; Roche Pharma AG: Other: Travel Support. Hiddemann:Bayer: Research Funding; Gilead: Consultancy, Honoraria; Vector Therapeutics: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Research Funding; Roche: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria. Herold:Roche: Honoraria, Research Funding; Janssen: Consultancy, Honoraria; Gilead: Honoraria; Celgene: Honoraria. Morschhauser:Servier: Consultancy; Gilead: Consultancy; Janssen: Honoraria; Roche/Genentech: Consultancy; BMS: Honoraria; Celgene: Honoraria. Rummel:Roche Pharma AG: Honoraria, Research Funding; Celgene: Honoraria; Janssen: Honoraria; Sandoz: Honoraria. Kimby:AbbVie,: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Roche: Membership on an entity's Board of Directors or advisory committees; Jansen: Membership on an entity's Board of Directors or advisory committees; Gilead: Other: educational lectures. Vitolo:Abbvie: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Kite: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Celgene: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Gilead: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Juno Therapeutics: Membership on an entity's Board of Directors or advisory committees; F. Hoffmann-La Roche: Speakers Bureau; Novartis: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Gyan:Pfizer: Honoraria. Ladetto:Celgene: Honoraria; Roche: Honoraria; Janssen: Honoraria; Abbvie: Honoraria; Acerta: Honoraria; Sandoz: Honoraria. Nielsen:F. Hoffmann-La Roche Ltd: Employment, Equity Ownership. Flowers:AstraZeneca: Consultancy; BeiGene: Consultancy, Research Funding; Eastern Cooperative Oncology Group: Research Funding; Burroughs Wellcome Fund: Research Funding; AbbVie: Consultancy, Research Funding; Optimum Rx: Consultancy; V Foundation: Research Funding; Pharmacyclics/Janssen: Consultancy, Research Funding; Bayer: Consultancy; Gilead: Consultancy, Research Funding; TG Therapeutics: Research Funding; Denovo Biopharma: Consultancy; Acerta: Research Funding; National Cancer Institute: Research Funding; Millenium/Takeda: Research Funding; Genentech, Inc./F. Hoffmann-La Roche Ltd: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Spectrum: Consultancy;

Abstract Background: Patients (pts) with DLBCL who receive first-line anthracycline based immunochemotherapy and remain in remission at 2 years have excellent outcomes with overall survival (OS) in one study that was comparable to the age and sex matched general population in cohorts from the US and France (Maurer et al, JCO 2014). To evaluate whether these findings are robust and generalizable, we assessed OS stratified by progression-free survival at 24 months (PFS24) using individual patient data from pts with DLBCL enrolled in 14 multi-center, international randomized clinical trials as part of the SEAL consortium. Methods: Central data alignment was performed by the SEAL statistics and data center. All enrolled patients treated with rituximab-containing anthracycline-based immunochemotherapy as part of initial induction therapy were included in this analysis using an intent-to-treat approach. PFS was defined as time from initiation of first-line therapy to progression or death. PFS24 was defined as being alive and progression-free 24 months (731 days) after initiation of therapy. Overall survival from PFS24 was defined as time from achieving PFS24 until death due to any cause. OS was compared to each patient's age-, sex-, and country- matched general population using expected survival and standardized mortality ratios (SMR). Country-level population rate tables were obtained from www.mortality.org where available. A per-study average rate table was used when country information was unavailable. OS beyond 9 years from treatment initiation was only available the time of analysis from two trials (13% of cohort) and thus follow-up from PFS24 was restricted to the first 7 years after PFS24 for this analysis. Results: Fourteen studies with 7975 patients were included in the SEAL database. 5853 (73%) received rituximab as part of induction therapy and used in this analysis. Median age was 62 years (range 18-92) with 56% >60 years, 54% were male, 57% had elevated LDH, 63% had stage III/IV disease, 13% had ECOG PS 2-4, and IPI was 0-1 in 36%, 2 in 25%, 3 in 23%, and 4-5 in 16%. At a median follow-up of 4.4 years, 1337 (23%) had disease progression, 1489 patients (25%) had died, and 5101 patients were evaluable for PFS24. 1423 (28%) of evaluable patients failed to achieve PFS24. These patients had poor outcomes after progression with median OS of 7.2 months (95% CI 6.8-8.1), 5-year OS of 19%, and SMR of 32.1 (95% CI: 30.0-34.4). Outcome was excellent (median unreached) in the 3678 patients who were progression-free at 24 months, with subsequent OS after achieving PFS24 approaching the age and sex matched general population (Figure). The observed vs. expected OS at 3, 5, and 7 years after achieving PFS24 was 93.1% vs. 94.4%, 87.6% vs. 89.5%, and 80.0% vs. 83.7%, respectively, the SMR was 1.22 (95% CI: 1.09-1.37). In subset analyses examining pts achieving PFS24, adverse prognostic characteristics at baseline (elevated LDH, advanced stage, ECOG PS 2-4, high IPI) were associated with greater decrement in OS from the general population based expected survival (Table). Conclusions: PFS24 from the start of initial therapy stratifies DLBCL pts into populations with distinct outcomes. DLBCL pts treated with rituximab containing anthracycline-based immunotherapy on large randomized clinical trials who are alive without progression at 24 months from start of initial therapy have excellent outcomes with survival that is marginally lower but clinically indistinguishable from the age-, sex-, and country-matched background population for at least 7 years after achieving PFS24. Further follow-up time will be needed to assess any long-term impact of late relapse and survivorship issues in this population. Table Table. Figure Figure. Disclosures Shi: Mayo Clinic: Employment. Cunningham:Amgen: Research Funding; Astra-Zeneca: Research Funding; Bayer: Research Funding; Celgene: Research Funding; Merrimack: Research Funding; Medimmune: Research Funding. Seymour:AbbVie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel support, Research Funding, Speakers Bureau; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel support, Speakers Bureau; Genentech: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Gilead: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Roche: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees. Jaeger:Roche: Honoraria, Research Funding; Celgene: Honoraria, Research Funding. Haioun:Sandoz: Honoraria, Membership on an entity's Board of Directors or advisory committees; Gilead: Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; Roche: Honoraria, Membership on an entity's Board of Directors or advisory committees. Ghesquieres:Mundipharma: Consultancy; Roche France: Research Funding; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees. Merli:Roche: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees; Teva Pharmaceuticals Industries: Membership on an entity's Board of Directors or advisory committees. Herbrecht:Servier: Membership on an entity's Board of Directors or advisory committees; Gilead: Membership on an entity's Board of Directors or advisory committees; Cell Therapeutics, Inc: Membership on an entity's Board of Directors or advisory committees. Flament:Celgene: Employment, Equity Ownership. Fu:Celgene: Employment, Equity Ownership. Flowers:Gilead: Consultancy, Research Funding; Roche: Consultancy, Research Funding; Acerta: Research Funding; ECOG: Research Funding; Mayo Clinic: Research Funding; Pharmacyclics, LLC, an AbbVie Company: Research Funding; Millenium/Takeda: Research Funding; Infinity: Research Funding; TG Therapeutics: Research Funding; Genentech: Consultancy, Research Funding; NIH: Research Funding; AbbVie: Research Funding. Ou:Mayo Clinic: Employment. Sargent:Celgene: Research Funding. Coiffier:MorphoSys: Consultancy; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees; Gilead: Consultancy, Membership on an entity's Board of Directors or advisory committees; Roche: Consultancy; Celltrion: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene: 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.