ALBERT

Description: BACKGROUND Evidence suggests that co-morbidities at diagnosis can influence treatment decisions and outcomes in lymphoma patients. Considering the bimodal presentation of Hodgkin Lymphoma (HL) and that the majority of Non-Hodgkin lymphoma (NHL) patients are over 65 years of age, it can be especially challenging to manage them as older patients have a higher number of co-morbidities. Studies have shown that comorbidity is associated with an inferior outcome and a lower likelihood of receiving treatment with curative intent. It must also be noted that older adults with significant co-morbidities are often excluded from clinical trials due to co-morbidities and that Hispanics (HI) have been historically underrepresented. There is a need to take a closer look at this precise patient population. The main objective of our study was to determine the common co-morbidities and their impact on outcome in a prevalently Hispanic population with both HL and NHL at the only NCI designated Cancer Center of South Texas. To our knowledge this is the largest cohort of HL patients from a single academic institution that serves primarily Hispanics. METHODS We located and retrospectively analyzed a total of 616 patients with diagnosis of Lymphoma (HL and NHL) by International Classification of Diseases (ICD) codes and identified 477 patients who met criteria for inclusion; the patients all received care at UT Health San Antonio, between 2008-2018. Key variables for each patient included age, gender, race/ ethnicity, comorbidities, and vitality status in 2018. Continuously distributed outcomes were summarized with the mean and standard deviation and categorical outcomes were summarized with frequencies and percentages. The significance of variation in the mean with disease category was assessed with one way ANOVA and the significance of associations between categorical outcomes was assessed with Pearson's Chi Square or Fisher's Exact test as appropriate. Multivariate logistic regression was used to model binary outcomes in terms of covariates and indicators of disease. All statistical testing was two-sided with a significance level of 5%. R1 was used throughout. The study was approved by the local Institutional Review Board. The findings will be available to patients, funders and medical community through traditional publishing and social media. RESULTS We identified 477 patients with HL and NHL, 262 were Hispanic (HI) [55%], 205 non-Hispanic (NH) [43%], 10 not specified [2%]; there were 232 females (49%) and 245 males (51%). Co-morbidities that were identified and analyzed were: Diabetes Mellitus (DM), Hypertension (HTN), Chronic Kidney Disease (CKD), Coronary Artery Disease (CAD) and Congestive Heart Failure (CHF). The most common co-morbidity across all lymphoma subtypes was HTN. More than or equal to 50% of patients with Burkitt's, CTCL, Hodgkin's, Plasmablastic lymphoma, T cell lymphoma had no co-morbidities. In order to determine outcome, we took into consideration vitality status at the end of 2018. When comparing HI vs NH and adjusting for individual co-morbidities (HTN, DM, CAD, CHF, CKD) there is a trend towards a higher risk of poor outcome in NH patients when compared to HI (OR 1.17, CI 0.51-2.69, p-value= 0.7176). When we looked at patients who had both CAD and CHF and adjusted for other co-morbidities the trend remained with a higher risk for poor outcome in NH (OR 1.29, CI 0.57-2.91, p-value=0.53456). Looking at patients with a combination of CAD, CHF, CKD and DM (adjusting for other individual co-morbidities) there was also a trend towards poor outcome in NH (OR 1.26, CI 0.57-2.78, p-value= 0.569316). Overall, patients with CKD had an increased risk of poor outcome (OR 15.13, CI 1.5-153.13, p-value=0.0214) as well as patients with four co-morbidities including CAD, CHF, CKD and DM2 (OR 4.89, CI 1.68-14.23, p-value=0.003597). The absence of co-morbidities shows a trend towards a better outcome (OR 0.77, CI 0.19-3.17, p-value=0.721). CONCLUSION Within the limitations of sample size, our study demonstrates that in the prevalently Hispanic population of our institution, the presence of both CKD on its own as well as CKD with multiple co-morbidities (CKD, CAD, CHF, DM2) increases the risk of poor outcome. There is a trend towards a higher risk of poor outcome in the NH population with co-morbidities when compared to HI but further studies are needed. Disclosures No relevant conflicts of interest to declare.

Description: BACKGROUND With a greater proportion of the general population continuing to age from advancements in scientific knowledge, more patients newly diagnosed with malignant lymphoid tumors are elderly (age 〉 70). Geriatric oncology continues to face challenges in the management of these conditions because of co-morbid conditions, and therapy tolerance limitations associated with aging. Research has shown that geriatric patients get less chemotherapy than non-geriatric counterparts. The main objective of this study was to analyze outcomes of elderly patients (age〉65) diagnosed with Hodgkin and Non Hodgkin lymphoma and the relation to several variables including HIV status, financial status and ethnicity. METHODS We identified and included elderly patients (age 〉65) diagnosed with any subtype lymphoma by using ICD-9 and ICD-10 codes. The patients identified received care exclusively with Mays Cancer Center at UT Health San Antonio between 1998-2017. Variables for each patient measured included age, gender, diagnosis, stage, 〉 2 comorbidities, vitality status, HIV status, insurance status, treatment received, and treatment response. Dates of treatment and type of treatment was confirmed by documentation or chemotherapy orders, and diagnosis was confirmed by original pathology report. The statistical significance of associations with treatment response was assessed with Pearson's Chi-Square, Fisher's Exact test, and a logistic regression model with a generalized logit link with a 3-level response (CR, PR, F) where CR was designated as the referent. For each effect, the Odds Ratio (OR) and its 95% confidence interval (95% CI) are reported. All statistical testing was two-sided with a significance level of 5%. SAS Version 9.4 for Windows (SAS Institute, Cary NC) was used throughout. RESULTS Our patient population (n=346) was shown to have a median of 56, female patients (n=174, 50.3%), males patients (n=172, 49.7%), Hispanics (n=180, 52%), uninsured (n=107, 30.9%), and HIV (n=22, 6%). Diagnoses studied included aggressive lymphomas (Burkitt's, 1ry CNS, Hodgkin's, NHL, PTLD; n=252) and indolent lymphomas (Marginal Zone, Follicular; n=94). The odds of treatment failure (F) and of Partial Response (PR) in patients 〉65 was significantly increased relative to the odds in those ≤65 (F OR=1.04, 95% CI 1.01 to 1.07, p=0.02, PR OR=1.03, 95% CI 1 to 1.05, p=0.032). In an examination of variation in the relation between treatment response and treatment (chemo, chemo/immunotherapy, immune therapy alone, others) with age, we found no overall association between treatment response and treatment after adjustment for age (p=0.92) and no association between treatment response and treatment among those ≤65 or 〉65 (p=0.54 and p=0.97) respectively. CONCLUSION Hematologic malignancies are potentially curable or may have long lasting remission with current available treatment options; however, age with concurrent declining functional status can preclude many therapies. In our patient population, age did not preclude aggressive treatment with intent for cure. Disclosures No relevant conflicts of interest to declare.

Description: BACKGROUND Currently, the options for treatment of hematologic malignancies continues to expand with resulting positive outcomes in overall survival, but there is still concern that not all populations have the opportunity for cancer treatment due to lack of health insurance. We have taken a cohort of patients with health-insurance related disparities in a majority-minority population whose immigration status often precludes them from standard insurance but can still utilize a payment plan (PP) associated with hospital care. The main objective of our study was to see how insurance status in a majority-minority population affected treatment response. METHODS Doing a retrospective analysis of a cohort of 364 patients with hematologic malignancies at a single center institution, the patients identified received care exclusively with Mays Cancer Center at UT Health San Antonio, between 1998-2017. Variables for each patient measured included age, gender, date of diagnosis, treatment received, date of first treatment, initial response to treatment, stage, 〉 2 comorbidities, vitality status, HIV status, and insurance status. The patient's insurance status was either identified as funded (to include Medicare, Medicaid, and private insurance), unfunded (self pay) or unfunded-payment plan (PP) associated with the hospital. Statistical significance was assessed with Pearson's Chi-Square, Fisher's Exact test, and a logistic regression model with a generalized logit link with a 3-level response (CR, PR, F) where CR was designated as the referent. For each effect, the Odds Ratio (OR) and its 95% confidence interval (95% CI) are reported. All statistical testing was two-sided with a significance level of 5%. SAS Version 9.4 for Windows (SAS Institute, Cary NC) was used throughout. RESULTS Our patient population (n=346) was shown to have a median of 56, female patients (n=174, 50.3%), males patients (n=172, 49.7%), Hispanics (n=180, 52%), uninsured (n=107, 30.9%), and HIV (n=22, 6%). Diagnoses studied included aggressive lymphomas (Burkitt's, 1ry CNS, Hodgkin's, NHL, PTLD; n=252) and indolent lymphomas (Marginal Zone, Follicular; n=94). The odds of treatment failure (F) and of Partial Response (PR) in Hispanic patients was not significantly different from the odds in non-Hispanic patients (F OR=1.43, 95% CI 0.62 to 3.3, p=0.40, PR OR=1.36, 95% CI 0.73 to 2.54, p=0.33). Despite having a slightly larger insured patient population (68.9%), insurance status did not affect outcome for our patients. Less than 30% of patients used Carelink or had no insurance in this cohort [Carelink CR 58 (24.7%) PR 17 (24.3%) F 10 (24.4%), No insurance CR 15 (6.4%) PR 5 (7.1%) F 2 (4.9%)]. Twenty percent of Hispanic patients (36/180) and 29.5% (49/166) of non-Hispanic patients reported using Carelink. After combining Carelink with no insurance, the odds of treatment failure (F) and of Partial Response (PR) in patients with insurance was not significantly different from the odds in those without insurance (F OR=1.12, 95% CI 0.44 to 2.84, p=0.81, PR OR=0.95, 95% CI 0.49 to 1.85, p=0.89). In an examination of variation in the relation between treatment response and insurance status with ethnicity, we found no overall association between treatment response and insurance after adjustment for ethnicity (p=0.97) and no association between treatment response and insurance status among Hispanic or non-Hispanic patients (p=0.75 and p=0.69 respectively). CONCLUSION This study directly challenges the idea that Hispanic populations are faced with being the least likely to have health insurance of any racial or ethnic group; among those 18-64 years of age, 37% of Hispanics are uninsured compared to 13% of non-Hispanic whites. In an uninsured minority-majority Hispanic patient population with PP firmly established in the community that allows for ready access to healthcare, insurance status and race did not adversely affect outcome. Disclosures No relevant conflicts of interest to declare.

Description: Introduction: Historically, a lack of health insurance has been reported to correlate with decreased access to medical care, a delay in cancer treatment and poorer outcomes overall. Furthermore, access to preventive services for cancer screening also decrease with lack of medical insurance (1, 2). Also, studies report that an increase in Medicaid expansion help reduce racial disparities previously seen between African American and Caucasian patients (3). The aim of this study was to present and analyze vitality data based on insurance coverage among Hispanic (HI) and non-Hispanic (NH) population at the only NCI designated cancer center of South Texas primarily serving Hispanics. Methods: This is a retrospective observational study of a cohort of patients seen with diagnosis of lymphoma by International Classification of Diseases (ICD) codes from 2008 to 2018 at UT Health San Antonio. Diffuse Large B Cell Lymphoma (DLBCL) cases were not included. Variables included age of diagnosis, lymphoma subtype, stage at diagnosis, comorbidities, treatment received, lines of therapy, B symptoms present, death, and cause of death and current vitality status. Continuously distributed outcomes were summarized with the mean and standard deviation and categorical outcomes were summarized with frequencies and percentages. The significance of variation in the mean with disease category was assessed with one-way ANOVA and the significance of associations between categorical outcomes was assessed with Pearson's Chi Square or Fisher's Exact test as appropriate. Multivariate logistic regression was used to model binary outcomes in terms of covariates and indicators of disease. All statistical testing was two-sided with a significance level of 5%. R1 was used throughout. Primary end point was to characterize insurance status. Secondary end points - overall 3 and 5-year survival based on insurance and demographics. Results: A total of 477 patients with lymphoma were identified. Hodgkin lymphoma (HL)( n = 116, 24%), non-Hodgkin lymphoma (NHL) (n = 308, 65%), T cell lymphoma (TCL) ( n = 53, 11%). Subtypes for all indolent lymphomas ( n = 217), of which included; Follicular lymphoma (FL) ( n = 123), Marginal Zone lymphoma (MZL) ( n = 53), Nodular Lymphocyte Predominant Hodgkin Lymphoma (NLPHL) (n = 8), Small lymphocytic lymphoma (SLL) ( n = 28). Overall mean age of diagnosis for all lymphoma subtypes was 51, male patients (n = 244, 51%), female patients (n = 232, 49%), HI (n = 263, 56%) vs NH (n = 204, 44%), Mean BMI at diagnosis was 29 across all lymphoma groups. Most patients identified had Medicare (MC) (n = 115, 24%), or commercial insurance (CI) ( n = 222, 47%), others were approved for indigent care coverage (ICC) (n = 85, 18%), for Medicaid (MI) (n = 17, 4%), or unfunded (UF)( n = 35, 7%). Of those diagnosed with HL (n = 116); 60% (70) had MC or CI, 40% (46) had ICC, MI or were UF. Of those with Indolent Lymphomas (n = 217), 77% (166) had MC or CI and 23% (49) had ICC, MI or UF; and among patients with T cell lymphomas (n = 53), 63% (22) had MC or CI and 37% (13) ICC, MI or UF respectively. Overall number of HI patients alive at 3 years with MC or CI was 98 and 5 recorded deaths. Those with ICC or MI/UF were 52 and 11 respectively. Comparison of vitality data at 3 years follow up among both groups did not show a difference with a fisher p value of 0.056. Overall number of NH alive at 3 years with MC or CI was 90 and 11 recorded deaths. Those with ICC or MI/UF were 21 and 3 respectively. Comparison of vitality data at 3 years follow up among both groups did not show a difference with a fisher p value of 0.173. Overall number of HI alive at 5 years with MC or CI was 78 and 7 recorded deaths. Those with ICC or MI/UF were 36 and 11 respectively. Comparison of vitality data at 5 years follow up among both groups did not show a difference with a fisher p value of 0.064. Overall number of NH alive at 5 years with MC or CI was 70 and 14 recorded deaths and those with ICC or MI/UF were 16 and 4 respectively. Comparison of vitality data at 5 years follow up among both groups did not show a difference with a fisher p value of 0.169. Conclusion: Across all HI and NH, at the 3 and 5 year follow up mark, there was no significant vitality difference shown in our patient population between those with CI and or MC vs those with MI, ICC or UF. This study demonstrated that across all lymphoma subtypes, patients with access to healthcare had similar outcomes in vitality irrespective of demographics or insurance. Disclosures No relevant conflicts of interest to declare.

Description: Background: P53 activation is a major pathway by which normal tissues respond to DNA damaging agents such as chemo and radiotherapy. We have shown that the use of very low dose arsenic (LDA) for 3 days before chemotherapy in animal models temporarily and reversibly suppresses p53 activation for about 5 days. LDA-mediated protection requires functional p53 and thus is selective to normal tissues, as essentially every cancer cell has dysfunctional p53. Arsenic Trioxide (ATO) is currently used to treat acute promyelocytic leukemia at a much higher dose (50-fold higher than the dose we used for suppression of p53). The primary objectives of this trial were to: 1) define the lowest safe dose of ATO that blocks p53 activity in vitro as measured in patients(pts)' peripheral lymphocytes and 2) assess the potential of LDA to decrease hematological toxicity in pts receiving chemotherapy. Methods: Pts with malignancies other than leukemia who were to receive at least 4 cycles of myelosuppressive chemotherapy given at least 2 weeks apart were eligible. Pts had to have no baseline p53 activation in peripheral lymphocytes but p53 had to be responsive as measured by an in vitro assay. For objective 1, dose escalation was performed at the starting dose of ATO 0.005mg/kg/day for 3 days. For objective 2, ATO 0.005mg/kg /day x 3 was given prior to chemotherapy cycles 2, 4 and 6 only. WBC, HgB, platelet and ANC counts were obtained on chemotherapy days 1 (prior to chemotherapy), 8, 15 and 22. The p53 activation level in peripheral lymphocytes (prior to chemotherapy) was measured on day 1 of each chemotherapy cycle by ELISA essay. For the current analysis for objective 2, we compared only cycles 1 and 2 at days 1, 8, and 15 among the pts who received 3 week cycle chemotherapy regimens. Their p53 activation level on day 1 of cycle 2 was compared to that on day 1 of cycle 1. Pts whose p53 level was lower in cycle 2 were defined as group A (i.e. suppressed). Those whose p53 level was higher in cycle 2 were defined as group B. Groups A and B were compared in log units with regard to four tests (WBC, HgB, platelet, and ANC) with a repeated measures linear model of the test result in terms of group (A,B), test, cycle (1,2), day (1, 8, 15), and interaction terms, assuming an autoregressive order 1 autocorrelation matrix. All statistical testing was two-sided with a significance level of 5%; corrections for multiple comparisons were not applied. Results: Thirty-three evaluable pts were accrued. Chemotherapy was: TC (docetaxel, cyclophosphamide)-8, AC (doxorubicin, cyclophosphamide)-7, eight other regimens-18 pts. Twenty-four pts were treated with 3 week regimens and have p53 data available. For Objective 1, ATO at a dose of 0.005mg/kg/day for 3 days blocked p53 activity in vitro as measured in pts' peripheral lymphocytes and was not associated with any toxicity. Eight pts belonged to group A and 14 group B. Two pts who showed no change in p53 on day 1 between cycles 1 and 2 were excluded. For Objective 2, we found that the relationship between group and mean test result varied significantly with test (p

Description: Background Monoclonal gammopathy of undetermined significance (MGUS) is an asymptomatic condition arising from clonal plasma cells and has the risk of transformation to multiple myeloma (MM). Dysregulated expression of microRNAs (miRs) has been well demonstrated in MM, but miRs are not as well characterized in MGUS. We previously found an increased risk for MGUS in Vietnam veterans exposed to Agent Orange and its contaminant 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD). Here we report the effect of age on serum levels of 13 miRs in MGUS cases and controls from that study cohort. Methods The study base population comprised 958 US veterans who participated in the 2002 follow-up of the Air Force Health Study (AFHS). A total of 49 MGUS cases were identified by using their serum stored at the AFHS 2002 follow-up (Landgren O et al. JAMA Oncology, 2015). The current study included 47 MGUS cases and 85 controls. The controls were selected from the veterans who did not have MGUS, did not have a history of tumors, and whose TCDD level was below the third quartile value among the study base. Quantitative real-time PCR (qPCR) was used to determine the serum levels of 13 miRs (let-7a, let-7i, miR-16, miR-20a, miR-21, miR-34a, miR-106b, miR-146a, miR-181a, miR-192, miR-205, miR-335 and miR-361) that were previously shown to be dysregulated in MM or other cancers . The cycle threshold (Ct) values obtained from qPCR were normalized by using spiked-in cel-miR-39 as a control. Univariate rank regression was used to examine the relationships between relative expression of each miR and age, and each miR and MGUS status (MGUS vs control); each miR-MGUS relation was also examined with adjustment for age. All miR values were analyzed in log2 units. Continuously distributed age was summarized by the median and interquartile range (IQR): age variation with MGUS status was assessed with Kruskal-Wallis test. All statistical testing was two-sided with a significance level of p

Description: BACKGROUND It is estimated that 8110 persons will be diagnosed with Hodgkin Lymphoma (HL) in the US during 2019, but the advent of new treatment options has increased the cure rate to at least 80%. It has been reported that the rates of HL are lower in the adolescent and young adult (AYA) Hispanic population but significantly higher in the Hispanic population older than 65. The relative survival estimates are stated to be similar between AYA Hispanics (HI) and non-Hispanics (NH) but for ages 65-84, HI have a significantly higher mortality rate. Pediatric studies have suggested that ethnicity plays a role in outcomes in patients with HL but there is limited data in the adult population. There is an unmet need in the field, where dossiers on underrepresented ethnic minorities need to be carefully considered and compared to existing data. Therefore, our study aims to compare survival outcomes in Hispanics vs Non-Hispanics with HL, who were treated at the only NCI designated cancer center of South Texas. To our knowledge this is the largest cohort of HL patients from a single academic institution that serves primarily Hispanics. METHODS We located and retrospectively analyzed a total of 616 patients with diagnosis of Lymphoma (HL and NHL) by International Classification of Diseases (ICD) codes and identified 116 cases of HL; all the patients received care at UT Health San Antonio, between 2008-2018. Key variables for each patient included age, gender, race/ethnicity, comorbidities, insurance status, stage, BM and extranodal involvement, treatment received, outcome at 3 and 5 years and vitality status in 2018. Continuously distributed outcomes were summarized with the mean and standard deviation and categorical outcomes were summarized with frequencies and percentages. The significance of variation in the mean with disease category was assessed with one way ANOVA and the significance of associations between categorical outcomes was assessed with Pearson's Chi Square or Fisher's Exact test as appropriate. Multivariate logistic regression was used to model binary outcomes in terms of covariates and indicators of disease. All statistical testing was two-sided with a significance level of 5%. R1 was used throughout. The study was approved by the local Institutional Review Board. The findings will be available to patients, funders and medical community through traditional publishing and social media. RESULTS We identified 116 patients with HL, of which 73 were HI (63%), 43 NH (36%) and 1 not specified (1%). In regard to race, 92% identified as Caucasian, 4% as African American, 3% other and 1% Asian. The median age at diagnosis was 37.4, (SD 15.13). There were 49 females (42%) and 67 males (58%). The most common funding source was commercial insurance N=54 (47%), followed by a hospital payment plan N=30 (26%), Medicare N=16 (14%), unfunded N=13 (11%) and Medicaid N=3 (2%). Most prevalent co-morbidities were HTN N=28 (24%) and diabetes mellitus N= 23(20%); 50% of patients had no co-morbidities (N=63).At diagnosis ECOG of 0-1 was seen in 108 patients (93%); 8 were Stage I (7%), 39 stage II (33%), 32 stage III (28%), and 37 stage IV (32%). EBV was positive in 26 patients (22%). There were 15 patients that were HIV positive (13%), 54% with CD4 count