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Abstract History of prior cancer is a widespread exclusion criterion in cancer trials. Up to 80% of NCI-sponsored and 80% of industry-sponsored lung cancer trials exclude patients with a prior cancer. We suspect this exclusion is commonly applied in other cancer trials, although no definitive data exist. Prior cancer is especially common among older patients and those with certain cancer types. Among patients >65 years, 15.1% overall have prior cancer. In Multiple Myeloma, the most common plasma cell disorder (PCD), prevalence of prior cancer is as high as 17.4%. Examining the prior cancer exclusion criterion is important because the number of US cancer survivors is large and rapidly growing. Arbitrarily excluding cancer survivors from trials is not evidence-based and exclusion presumably arises from assumptions that higher mortality of patients with prior cancer could hinder study conduct and bias trial outcomes. However, few data exist to support this assumption of higher mortality. In fact, we demonstrated that lung cancer patients with a prior cancer have similar or lower mortality risk, compared to those without prior cancer. In this abstract, we reviewed prior cancer related eligibility criteria in three of the most common PCD (Multiple Myeloma, Amyloidosis and Waldenström Macroglobulinemia) clinical trials sponsored or endorsed by 5 major Co-Operative groups in North America (Table 1). We use descriptive statistics (n, %) and Fisher's exact tests to describe characteristics of trials with and without exclusion criteria. Of 33 trials, 26 (79%) excluded patients with prior cancer as follows - active cancer (12%), within 2-3 years of PCD diagnosis (9%), or within 5 years of PCD diagnosis (55%). Many trials had exceptions to prior cancer exclusion. Specifically, 67% of trials allowed non-melanoma skin cancer, 58% allowed in-situ cervical cancer, 12% allowed early stage prostate cancer. Table 2 shows the association between clinical trial characteristics and prior cancer exclusion. There was no association between prior cancer exclusion and phase of study, transplant studies, or survival end point. Exclusion criteria varied across year of activation (p=0.01); for example, 75% of studies activated 1990-1999 excluded prior cancer, compared to 100% of studies activated after 2010. Type of PCD was marginally associated with exclusion criteria (p=0.08); 74% of Multiple Myeloma trials excluded patients with prior cancer compared to 100% of the Amyloidosis and Waldenström Macroglobulinemia trials. Conclusion: A substantial proportion of potential participants may be excluded from PCD clinical trials because of a history of prior cancer. This practice impacts accrual, generalizability, and fair access to cutting-edge treatments and the highest level of clinical care. As treatment outcomes for other cancers continue to improve, it is likely that the prevalence of multiple primary cancers will increase. This exclusion criterion is applied widely across studies, including more than two-thirds of those with non-survival endpoints. Our study is the first to examine the prevalence and potential impact of prior cancer exclusion in PCD clinical trials. Using population-based cancer registry data, we plan to undertake further research to understand the appropriateness and ramifications of this standard exclusion policy in PCD cancer trials. Disclosures Collins: Agios: Research Funding; Bristol Myers Squibb: Research Funding; Celgene Corporation: Research Funding; Arog Pharmaceuticals: Research Funding. Devine:Kiadis Pharma: Consultancy. Usmani:Amgen, BMS, Celgene, Janssen, Merck, Pharmacyclics,Sanofi, Seattle Genetics, Takeda: Research Funding; Abbvie, Amgen, Celgene, Genmab, Merck, MundiPharma, Janssen, Seattle Genetics: Consultancy. Anderson:Amgen: Speakers Bureau; Takeda: Speakers Bureau; Celgene: Speakers Bureau. Kumar:Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees; Roche: Research Funding; AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: Membership on an entity's Board of Directors or advisory committees, Research Funding; Oncopeptides: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; KITE: 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, Research Funding; KITE: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding.

Abstract Background : TET2, located on chromosome 4q24, is frequently mutated in the majority of patients with chronic myelomonocytic leukemia (CMML). TET2 has 11 exons, and variations, especially in exon 3 have been described as a part of age related clonal hematopoiesis (Jaiswal NEJM 2015). In CMML, somatic TET2 mutations in the absence of ASXL1 mutations (ASXL1wt/TET2mt) were previously shown to impart a favorable outcome on survival (Patnaik BCJ 2015). In the current larger CMML patient cohort, we describe the number and type of TET2 mutations and examine their phenotypic and prognostic effects. Methods : 261 patients with CMML were included in the study. All patients had bone marrow (BM) biopsies and cytogenetics performed at diagnosis. Targeted capture assays were carried out on BM DNA specimens obtained at diagnosis for the following genes; TET2, DNMT3A, IDH1, IDH2, ASXL1, EZH2, SUZ12, SRSF2, SF3B1, ZRSR2, U2AF1, PTPN11, Tp53, SH2B3, RUNX1, CBL, NRAS, KRAS, JAK2, CSF3R, FLT3, KIT, CALR, MPL, NPM1, CEBPA, IKZF, and SETBP1. TET2 (NM_001127208.2) coverage extended from exons 3-11, with frame shift, non-sense, and missense variations considered pathogenic. Previously annotated single nucleotide polymorphisms (http//www.hapmap.org) were considered non-pathogenic. Results: Among the 261 study patients, 65% were males and median age was 70 years (range, 28-91). 154 (59%), 64 (25%) and 43 (16%) patients were classified as CMML-0, 1 and 2, respectively. At a median follow-up of 23 months, 174 (67%) deaths and 37 (14%) leukemic transformations were documented. Mutational frequencies ≥4% were encountered in; ASXL1 45%, TET2 42%, SRSF2 40%, NRAS 14%, SETBP1 13%, CBL 10%, JAK2 7%, RUNX1 6%, DNMT3A 6%, U2AF1 6%, SF3B1 5%, ZRSR2 4%, Tp53 4% and IDH2 4%. i) TET2 mutations type, number and phenotypic correlates: TET2 mutations were seen in 109 (42%) patients; these included frameshift 33 (30%), nonsense 29 (27%) and missense 11 (10%) variants whereas 36 (33%) had more than one type of mutation. Overall, 57 (52%) patients had more than 1 TET2 mutations: 52 (48%) patients had 1, 46 (42%) 2 and 11 (10%) ≥3 TET2 mutations. Among all 109 TET2 mutated patients, 65% were male, and median age was 71 years with no significant difference in age and gender distribution between mutated and un-mutated cases, or type of TET2 mutations; however, older patients were more likely to carry multiple TET2 mutations (p=0.01). Compared to their un-mutated counterparts, TET2 mutated cases were less likely to have a low hemoglobin (p<0.001), circulating immature myeloid cells (IMC) (p=0.001), peripheral blood (PB) (p=0.009) and BM blasts (p=0.009), and have high-risk stratification per Mayo Molecular Model (p<0.001); these differences were not affected by the type or number of TET2 mutations. TET2 mutated cases were more likely to have a higher frequency of SRSF2 (p=0.004) and lower frequency of ASXL1 (p=0.03), Tp53 (p=0.04) and IDH1/2 mutations (p<0.001); these associations were also not affected by the type or number of TET2 mutations. ii) Impact on survival: Median survival for the entire cohort (n=261) was 24 months. In univariate analysis, survival was superior in TET2 mutated (median 33 months) versus wild-type (median 21 months) patients [p=0.03; HR 1.3 95% CI 1.12-1.86] (figure 1A). This survival difference remained significant after adjustment for age (p=0.04), leukocyte count (p=0.017), absolute monocyte count (p=0.02), absolute lymphocyte count (p=0.02), platelet count (p=0.015), circulating IMC (p=0.03), DNMT3A (p=0.02) and ASXL1 (p=0.045) mutations; however, significance was lost after adjustment for abnormal karyotype (p=0.32) and the Mayo Molecular Model (p=0.0003). These observations were not affected by the type or number of TET2 mutations. Finally, our previous observation regarding the survival advantage of ASXL1wt/TET2mt versus other genotypes was most apparent for patients with multiple TET2 mutations (p=0.02) (figure 1B). Conclusions: TET2 mutations are common in CMML and constitute approximately equal proportions of frameshift and non-sense mutations, while missense mutations are less frequent. Majority of TET2 mutated CMML cases harbor more than one mutant variant. Regardless, the relevance of type and number of TET2 mutations in CMML was limited to an association between older age and number of mutations and the latter with possibly improved survival in the absence of clonal ASXL1 mutations. Disclosures No relevant conflicts of interest to declare.

Background and Aims Among patients with cirrhosis awaiting liver transplantation, prediction of wait‐list (WL) mortality is adjudicated by the Model for End Stage Liver Disease–Sodium (MELD‐Na) score. Replacing serum creatinine (SCr) with estimated glomerular filtration rate (eGFR) in the MELD‐Na score may improve prediction of WL mortality, especially for women and highest disease severity. Approach and Results We developed (2014) and validated (2015) a model incorporating eGFR using national data (n = 17,095) to predict WL mortality. Glomerular filtration rate (GFR) was estimated using the GFR assessment in liver disease (GRAIL) developed among patients with cirrhosis. Multivariate Cox proportional hazard analysis models were used to compare the predicted 90‐day WL mortality between MELD‐GRAIL‐Na (re‐estimated bilirubin, international normalized ratio [INR], sodium, and GRAIL) versus MELD‐Na. Within 3 months, 27.8% were transplanted, 4.3% died on the WL, and 4.7% were delisted for other reasons. GFR as estimated by GRAIL (hazard ratio [HR] 0.382, 95% confidence interval [CI] 0.344‐0.424) and the re‐estimated model MELD‐GRAIL‐Na (HR 1.212, 95% CI 1.199‐1.224) were significant predictors of mortality or being delisted on the WL within 3 months. MELD‐GRAIL‐Na was a better predictor of observed mortality at highest deciles of disease severity (≥ 27‐40). For a score of 32 or higher (observed mortality 0.68), predicted mortality was 0.67 (MELD‐GRAIL‐Na) and 0.51 (MELD‐Na). For women, a score of 32 or higher (observed mortality 0.67), the predicted mortality was 0.69 (MELD‐GRAIL‐Na) and 0.55 (MELD‐Na). In 2015, use of MELD‐GRAIL‐Na as compared with MELD‐Na resulted in reclassification of 16.7% (n = 672) of patients on the WL. Conclusion Incorporation of eGFR likely captures true GFR better than SCr, especially among women. Incorporation of MELD‐GRAIL‐Na instead of MELD‐Na may affect outcomes for 12%‐17% awaiting transplant and affect organ allocation.

Background and Aims A high proportion of patients develop chronic kidney disease (CKD) after liver transplantation (LT). We aimed to develop clinical/protein models to predict future glomerular filtration rate (GFR) deterioration in this population. Approach and Results In independent multicenter discovery (CTOT14) and single‐center validation (BUMC) cohorts, we analyzed kidney injury proteins in serum/plasma samples at month 3 after LT in recipients with preserved GFR who demonstrated subsequent GFR deterioration versus preservation by year 1 and year 5 in the BUMC cohort. In CTOT14, we also examined correlations between serial protein levels and GFR over the first year. A month 3 predictive model was constructed from clinical and protein level variables using the CTOT14 cohort (n = 60). Levels of β‐2 microglobulin and CD40 antigen and presence of hepatitis C virus (HCV) infection predicted early (year 1) GFR deterioration (area under the curve [AUC], 0.814). We observed excellent validation of this model (AUC, 0.801) in the BUMC cohort (n = 50) who had both early and late (year 5) GFR deterioration. At an optimal threshold, the model had the following performance characteristics in CTOT14 and BUMC, respectively: accuracy (0.75, 0.8), sensitivity (0.71, 0.67), specificity (0.78, 0.88), positive predictive value (0.74, 0.75), and negative predictive value (0.76, 0.82). In the serial CTOT14 analysis, several proteins, including β‐2 microglobulin and CD40, correlated with GFR changes over the first year. Conclusions We have validated a clinical/protein model (PRESERVE) that early after LT can predict future renal deterioration versus preservation with high accuracy. This model may help select recipients at higher risk for subsequent CKD for early, proactive renal sparing strategies.

PURPOSE Older women with breast cancer remain under-represented in clinical trials. The Cancer and Leukemia Group B 49907 trial focused on women age 65 years and older. We previously reported the primary analysis after a median follow-up of 2.4 years. Standard adjuvant chemotherapy showed significant improvements in recurrence-free survival (RFS) and overall survival compared with capecitabine. We now update results at a median follow-up of 11.4 years. PATIENTS AND METHODS Patients age 65 years or older with early breast cancer were randomly assigned to either standard adjuvant chemotherapy (physician’s choice of either cyclophosphamide, methotrexate, and fluorouracil or cyclophosphamide and doxorubicin) or capecitabine. An adaptive Bayesian design was used to determine sample size and test noninferiority of capecitabine. The primary end point was RFS. RESULTS The design stopped accrual with 633 patients at its first sample size assessment. RFS remains significantly longer for patients treated with standard chemotherapy. At 10 years, in patients treated with standard chemotherapy versus capecitabine, the RFS rates were 56% and 50%, respectively (hazard ratio [HR], 0.80; P = .03); breast cancer–specific survival rates were 88% and 82%, respectively (HR, 0.62; P = .03); and overall survival rates were 62% and 56%, respectively (HR, 0.84; P = .16). With longer follow-up, standard chemotherapy remains superior to capecitabine among hormone receptor–negative patients (HR, 0.66; P = .02), but not among hormone receptor–positive patients (HR, 0.89; P = .43). Overall, 43.9% of patients have died (13.1% from breast cancer, 16.4% from causes other than breast cancer, and 14.1% from unknown causes). Second nonbreast cancers occurred in 14.1% of patients. CONCLUSION With longer follow-up, RFS remains superior for standard adjuvant chemotherapy versus capecitabine, especially in patients with hormone receptor–negative disease. Competing risks in this older population dilute overall survival benefits.

Abstract Background Glioblastoma (GBM) is the most common primary malignant adult brain tumor. Temozolomide (TMZ) is the standard of care and is most effective in GBMs that lack the DNA repair protein O6-methylguanine-DNA methyltransferase (MGMT). Moreover, even initially responsive tumors develop a secondary resistance to TMZ and become untreatable. Since aberrant epidermal growth factor receptor (EGFR) signaling is widespread in GBM, EGFR inhibition has been tried in multiple clinical trials without success. We recently reported that inhibiting EGFR leads to increased secretion of tumor necrosis factor (TNF) and activation of a survival pathway in GBM. Here, we compare the efficacy of TMZ versus EGFR plus TNF inhibition in an orthotopic mouse model of GBM. Methods We use an orthotopic model to examine the efficacy of TMZ versus EGFR plus TNF inhibition in multiple subsets of GBMs, including MGMT methylated and unmethylated primary GBMs, recurrent GBMs, and GBMs rendered experimentally resistant to TMZ. Results The efficacy of the 2 treatments was similar in MGMT methylated GBMs. However, in MGMT unmethylated GBMs, a combination of EGFR plus TNF inhibition was more effective. We demonstrate that the 2 treatment approaches target distinct and non-overlapping pathways. Thus, importantly, EGFR plus TNF inhibition remains effective in TMZ-resistant recurrent GBMs and in GBMs rendered experimentally resistant to TMZ. Conclusion EGFR inhibition combined with a blunting of the accompanying TNF-driven adaptive response could be a viable therapeutic approach in MGMT unmethylated and recurrent EGFR-expressing GBMs.

TPS4596 Background: First-line treatment of mRCC has rapidly changed to include IPI-NIVO or CABO, with clinical benefit of each based on the Checkmate 214 and CABOSUN trials. Combination immunotherapy with VEGF therapies have shown benefit in the JAVELIN 101 and KEYNOTE 426 trials over sunitinib. It is yet unclear which patients (pts) benefit most from combination immunotherapy-VEGF inhibitors, and the optimal sequence of drugs. Methods: In an adaptive, randomized, multicenter, phase 3 trial (Alliance A031704, PDIGREE), pts will start treatment with induction IPI 1mg/kg and NIVO 3mg/kg intravenously (IV) once every 3 weeks. Key inclusion criteria include clear cell mRCC, IMDC intermediate or poor risk, Karnofsky performance status >70, and no prior treatments for mRCC. Based on 3-month radiographic assessment (after completing IPI-NIVO combination), pts with complete responses (CR) will undergo maintenance NIVO 480mg IV every 4 weeks, pts with progression of disease (PD) will switch to CABO 60mg oral daily, and pts with non-CR/non-PD will be randomized to NIVO 480mg IV every 4 weeks versus NIVO 480mg IV every 4 weeks with CABO 40mg oral daily. Randomization will be stratified by IMDC risk criteria and presence of bone metastases. The primary endpoint of the study is overall survival (OS). We hypothesize that 3-year OS rate will improve to 70% for NIVO-CABO compared to 60% for NIVO alone; to achieve 85% power with a two-sided alpha of 0.05 and exponential distribution, 696 patients will be randomized. Accounting for 30% patients with either CR or PD, and 5% dropout from toxicity, up to 1046 pts will be enrolled. Key secondary endpoints include PFS, 12-month CR rate, ORR based on RECIST 1.1 and irRECIST criteria, and toxicity profiles. Quality of life will be assessed based on the FKSI-19, PROMIS-fatigue, and EQ5D-5L questionnaires. Biomarkers associated with CR and association of IL-6 with treatment benefit will be assessed. Other tissue-based and plasma-based biomarkers are planned. Enrollment will begin this year. Support from UG1CA189823, U24CA196171; https://acknowledgments.alliancefound.org . Clinical trial information: NCT03793166.