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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 Introduction Type 1 von Willebrand disease (VWD 1) accounts for ~75% of VWD. The National Heart, Lung, and Blood (NHLBI) VWD guidelines recommend VWF:Ag and VWF:RCo cut-off levels of <30 (IU/dL or %) for definite laboratory diagnosis of VWD 1. However, guidelines indicate that patients with "low VWF" (VWF:Ag and VWF:RCo in the 30-50 IU/dl range) could be candidates for agents to increase VWF levels if they are at risk for bleeding. Here we examine the diagnostic practices for VWD at Mayo Clinic Rochester by determining the proportion of patient currently classified as VWD 1 that meet NHLBI criteria for "low VWF". In addition, we assess changes in the laboratory phenotype of the aging population of patients with "low VWF" and VWD 1. Methods Patients with a diagnosis of VWD 1 at our institution were identified through our institutional hemophilia treatment center database (1986 to 2017). All available VWF:Ag and VWF activity (ristocetin cofactor assay [VWF:RCo] and latex immuno-activity assay [VWF:Ab]) levels performed at our institution and available in our electronic medical record (EMR) were recorded. Exclusion criteria included confounding variables known to effect VWF levels (eg,. hormonal therapy, pregnancy, desmopressin, or VWF/VIII concentrate administration) at the time of first laboratory assessment (VWF:Ag and VWF activity (by either VWF:Ab or VWF: RCo) at our institution. Bleeding score, retrospectively assessed using the MCMDM-1 VWD bleeding assessment tool (BAT), at the time of first clinical evaluation was recorded if enough information was available in the EMR. All VWF testing was recorded for comparative analysis between the first and the most recent measurements within the study period. Patients were not included in age-related analysis if the most recent laboratory values were obtained in the presence of the confounding variables noted above. Statistical analysis was performed using JMPfor paired t-tests and STATA for multilevel mixed-effects regression analysis. Results 78 patients (50 F) met study criteria. Median age at initial presentation at our institution was 27.5 (0-75) years. Medians (ranges) for VWF:Ag (n=78), VWF:Ab (n=41), and VWF:RCo (n=75) were 39 (5-60)%, 37 (19-53)%, and 36 (11-62)%, respectively (reference ranges 55-200% for VWF and factor VIII values). Coagulation factor VIII activity (FVIII:C) was 63 (10-122)% (n=78). Of 37 patient with available blood type results, 23 (62%) were blood group O. 56% of patients (n=44) met NHLBI criteria for classification as "low VWF" (Figure 1, Panel A). There was no difference in bleeding score between patients with VWD 1 (median bleeding score: 4 (0-14), n=22) compared to those with "low VWF" (median bleeding score: 4 (0-14), n=37). 54 patients had repeat laboratory testing at 4.5 (0-29) years after initial testing. VWF antigen and activity levels were compared in those who had repeat testing done >1 year (n=36) after initial lab testing at our institution. Median age of patients at time of most recent measurement was 42.5 (5-87) years compared to 35.5 (0-75) years at first measurement. VWF:Ag was significantly higher in the most recent measurement compared to the first measurement (p< 0.05, Figure 1, Panel B ). There was no statistically significant difference between VWF activity levels in the first versus the most recent measurement. There was a non-significant trend towards increasing VWF:Ag with increasing age; however when stratified into "low VWF" and VWD 1 disease groups, there was a significant relationship between VWF Ag and age in the "low VWF" group with mixed effects regression model (coefficient: 0.207, p:0.043). Conclusion Approximately 55% of patients with a clinical diagnosis for VWD 1 meet criteria for "low VWF." In our cohort, there was no difference in bleeding (BAT) scores between the two groups; however our analysis is limited by its retrospective nature. We also demonstrate a statistically significant increase in VWF:Ag with aging; however, with regression analysis, this change was only noted in those in the "low VWF" group. Larger prospective studies controlling for confounding factors are needed to further demonstrate the effect of age on VWF antigen and activity levels. Disclosures No relevant conflicts of interest to declare.

Abstract Background We have previously reported and validated that the E-IPI, provided better discrimination of overall survival (OS) than the IPI for DLBCL patients > 60 years of age treated with R-CHOP (Advani et al., BJH 2010 and 12-ICML 2013 Abstract 222). Recent reports suggest that males > 60 years treated with R-CHOP have worse outcomes likely related to differences in rituximab clearance (Muller et al., Blood 2012). In this study, we explored if the addition of male sex to the E-IPI further improved risk stratification. Methods DLBCL patients > 60 years treated with R-CHOP on the E4494, RICOVER-60 and GELA 98-5 trials were included. A multivariate analysis was performed to assess whether male sex is an independent prognostic factor for OS in addition to the five E-IPI risk factors, E-IPI score, and E-IPI risk group. Male sex (S) was added as an additional risk factor to the E-IPI (S-EIPI, 0-6) and patients regrouped according to the number of risk factors: low (L)=0-1, low intermediate (LI)=2, high intermediate (HI)=3 and high (H)=4-6 based on the observed OS using Kaplan-Meier curves. C-statistic was used to compare the discrimination ability. The 5 year OS was estimated using the Kaplan-Meier method. Results 1079 patients (E4494, n=267; RICOVER-60, n=610; GELA 98-5, n=202) with a median follow-up of 8.9 years were included. In multivariate analyses, male sex was a significant independent predictor for OS adjusting for all five E-IPI factors, (HR 1.5, p < 0.0001), E-IPI score (HR 1.42, p < 0.001), and E-IPI risk group (HR 1.42, p < 0.001) (Table 1). C-statistic was 0.66 for S-EIPI and 0.64 for EIPI. Incorporation of sex into the E-IPI shifted 35% patients to higher risk groups, including 110 patients into the highest risk group (Table 2). The estimated 5 year OS for the S-EIPI L, LI, HI, and H risk groups was 87%, 70%, 58%, and 40%, respectively (Table 3). Compared to E-IPI, the 95% C.I. did not overlap among S-EIPI risk groups. Conclusion For DLBCL patients >60 years treated with R-CHOP, our results suggest the addition of male sex to the E-IPI may improve categorization of patients into well-defined clinically relevant risk groups. Patients with low risk S-EIPI have an excellent outcome (5 year OS 87%). Patients with high risk S-EIPI have a 5 year OS of only 40% and therapies beyond standard R-CHOP need to be explored. Disclosures: Horning: Genentech: Employment; Roche: Equity Ownership.

Abstract Background Platelet dense granule (DG) deficiencies, including Hermansky-Pudlak syndrome, are relatively common and frequently under-diagnosed hereditary platelet hypofunctional disorders. Among various laboratory tests, platelet whole mount (WM) transmission electron microscopy (TEM) is considered the gold standard method for diagnosing DG deficiencies. Nevertheless, platelet DG TEM testing is still largely a research tool and has not been thoroughly validated and standardized as a clinical test. Furthermore, reference ranges (RR) of DG count/platelet (DGC) have not been adequately established. Aim Our goals were to validate and standardize platelet WM TEM testing and establish reference ranges for platelet DGC. Methods Based on previously established methods (Blood, 33:598-606), we first optimized and standardized various pre-analytical, analytical and post-analytical procedures including sample matrix, sample stability, platelet-rich plasma (PRP) preparation, platelet mounting procedure and DG counting criteria. Then whole blood samples in ACD-B tubes were collected from a total of 128 healthy donors (64 males and 64 females). Platelet DGC, percentage of platelets without any DG (empty platelets), platelet count (PC), mean platelet volume (MPV) and immature platelet fraction (IPF) were measured. In addition, platelet aggregometry analyses were performed on citrated PRP samples from the same donors. Standard statistical analyses were employed in this study. Results DGC and platelet ultra-structure were stable when whole blood samples were stored at room temperature (RT) for up to 4 days. Reproducible DGC and adequate preservation of platelet ultrastructure depended on an optimized mounting method. The DG counting criteria were developed based on previous publications and guidance from Dr. James G. White. Using the same WM TEM images and DG counting criteria, agreements among different technologists (n=5) improved from 60% to 95%. Finally, DGC reference range study using 128 healthy donor samples (age range 18, 72 years) and scoring 100-200 platelets from each donor showed that the DGC distribution of each donor sample was left-skewed with a median of 15% of empty platelets (range: 3, 40). The median DGC was 2.6 with a range of 1.0—5.1. Reference ranges established at the lower 95th percentile for DGC empty platelets is ≤ 31% (95% CI 28, 34) and for the mid-95th percentiles of DGCs between 1.5 and 4.0. DGCs were weakly associated with MPV and IPF (ρ between 0.22 and 0.28); and inversely associated with the percentage of empty platelets (ρ between -0.26 and -0.25). DGC showed no significant association with PC, platelet maximum aggregation or primary slope of aggregation, nor age or gender. Conclusion We validated platelet WM TEM procedures and for the first time established an adult reference range for platelet DGC. The results of association analyses implied that immature platelets may have slightly more DGs. Disclosures: No relevant conflicts of interest to declare.

Abstract Introduction The role of body mass index (BMI) impacting clinical outcome among lymphoma patients is controversial. Two recent studies suggest that increased BMI is associated with significantly improved survival. In this study the association between BMI at study entry and failure-free survival (FFS) and overall survival (OS) was evaluated in three phase III Eastern Cooperative Oncology Group-led trials, among patients with DLBCL (E4494), follicular lymphoma (FL) (E1496) and Hodgkin's lymphoma (HL) (E2496). Patients and Methods 537 patients with DLBCL, 730 patients with HD and 282 patients with FL were included in the analysis. BMI was calculated as weight (kilograms) divided by the square of height (meters), using data at study entry. BMI was analyzed both as continuous and categorical variables (underweight <18.5 kg/m2, normal weight: 18.5 to < 25 kg/ m2, overweight: 25 to < 30 kg/ m2, and obese :≥ 30 kg/ m2).The underweight group was excluded due to low (< 2%) prevalence. Baseline patient and clinical characteristics, treatment received and clinical outcomes were compared across BMI categories. PFS was defined as the time from study entry to relapse, progression, or death. OS was measured from study entry to death of any cause. The log-rank test and Cox regression models was used to check the association. The association between BMI and FFS/OS was also independently assessed among patients treated with rituximab. A sensitivity analysis was performed excluding patients with significant weight loss at baseline. Results Among patients with DLBCL, HL and FL, the median age was 70, 33 and 56; 29%, 29% and 37% were obese and 38%, 27% and 37% were overweight, respectively. Age was significantly different among BMI groups in all three studies. Higher BMI groups tended to have better prognosis at study entry among DLBCL and HL patients. BMI was not associated with clinical outcome, with p-values of 0.89, 0.30 and 0.40 for FFS, and p-values of 0.64, 0.67 and 0.09 for OS, for patients with DLBCL, HL and FL, respectively (Figure 1). In multivariate analysis adjusting for other clinical factors, BMI remains an insignificant predictor for all three histologies (Table 1). When limiting to patients treated with rituximab, the association remains non-significant for both FL patients (p=0.92 for PFS, p=0.36 for OS) and DLBCL patients (Figure 2). A subset analysis of males with DLBCL treated on R-CHOP, which matched the study cohort used in a recent report (Carson et al, 2012), revealed no differences in FFS (p=0.48) or OS (p=0.58) (Figure 2). Sensitivity analysis excluding patients with weight loss at study entry resulted in similar findings. Conclusion BMI was not significantly associated with clinical outcomes among patients with DLBCL, HL or FL, in three prospective phase III clinical trials. The findings contradict some previous reports of similar investigations. Further work is required to understand the observed discrepancies. Disclosures: Horning: Genentech: Employment.