Ethnic Disparities in Hodgkin's Lymphoma (HL): A Large-Scale Population Based Analysis of Hispanics with HL in Texas

BACKGROUND: It is estimated that 8480 persons in USA will be diagnosed with Hodgkin Lymphoma (HL) in 2020 accounting to approximately 0.5% of all new cancer diagnoses. The advent of new treatment options has improved the outcomes of this disease and 5-year relative survival rate is 87.4% currently. However, studies have shown that outcomes of HL have been worse in Hispanics (Annals of Oncology, PMID: 22241896) especially in late stage disease and HI experience up to a 35% higher risk of HL specific mortality than whites (AACR,PMID: 26826029). There is an unmet need in the field and dossiers on underrepresented ethnic minorities need to be carefully considered, compared to existing data. Our study aims to compare survival outcomes in Hispanics (HI) vs Non-Hispanics (NH) with HL and to our knowledge this is the largest cohort of patients from an area that represents a large proportion of HI population in the USA. METHODS: This is a retrospective study that examines HL patients obtained from Texas Cancer Registry (TCR) database between 2006-2016 and identified by the International Classification of Diseases for Oncology Third Edition (ICD-O-3) code list. All patient data was provided to us de-identified. Standard demographic variables collected include gender, race, ethnicity, dates at diagnosis and death, primary payer at diagnosis, subtype of lymphoma, stage, treatment modality, poverty index among others. Categorical outcomes were summarized with frequencies and percentages while age (years), the only continuously distributed outcome was summarized with the mean and standard deviation. The significance of variation in the distribution of categorical outcomes with ethnicity (HI vs NH) was assessed with Fisher's Exact tests or Pearson's Chi-square tests as appropriate; age was assessed with T-tests or Wilcoxon tests as appropriate. Survival time (years) was measured from date of primary diagnosis to death. Patients not coded as dead were considered censored on survival time at the date last seen. Survival distributions were described with Kaplan-Meier curves and significance of variation in median survival with ethnicity was assessed with log rank testing. At risk tables were computed based on the Kaplan-Meier estimate of the survival curve. All statistical testing was two-sided with a significance level of 5%. Corrections for multiple testing were not applied. The R language [R Core Team (2013). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria] was used throughout. RESULTS: We identified 6353 patients with HL, of which 1843 were HI (29%), 4510 NH (71%). Median age of diagnosis in HI was 41.3 vs 42.3 in NH (p = 0.084). Males were more frequently affected, 56.5% in HI vs 54.8 in NH (p = 0.213). Most frequent poverty index bracket for HI was between 20-100% vs 10-19.9% for NH (p < 0.001). Most frequent payment model amongst both groups was private insurance with 28.1% in HI vs 45.1% in NH (p < 0.001). Metro/non-border most frequent locality amongst both groups (p value n/a) with Harris county accounting to 15.7% of HL in HI vs 16.5% of HL in NH. Bexar county accounted for 12.5% of HL in HI vs 5.2% of HL in NH. Most common stage at diagnosis in both groups was III/IV with 43% in HI vs 33.7% in NH (p < 0.001). In both groups most frequent chemotherapy included multiple agents, 57.1% in HI vs 48.8% in NH (p < 0.001). Majority in both groups neither got any radiation, 77% in HI vs 76.5% in NH (p = 0.208) nor hematologic transplant, 92% in HI vs 88.6% in NH (p = 0.01). We found the median overall survival time in HI was 10.5 years vs 10.8 years in NH; the overall survival probability for HI vs NH at 2 years was 0.8 [CI 0.771-0.811] vs 0.85 [CI 0.83-0.853], at 5 years was 0.72 [CI 0.694-0.743] vs 0.77 [CI 0.753-0.782] and at 10 years was 0.60 [CI 0.544-0.646] vs 0.65 [CI 0.615-0.679]. CONCLUSION: Our study demonstrates that amongst the population of Texas, HI patients with HL have a statistically significant worse overall survival probability (p value < 0.0001) when compared to NH patients with HL. It is of paramount importance that outcomes for all racial and ethnic groups continue to improve but very little is known about the basis for these differences. This warrants a deeper investigation into the biological and non-biological determinants for these differences. Figure Disclosures Diaz Duque: ADCT Therapeutics: Research Funding; Molecular Templates: Research Funding; AstraZeneca: Research Funding; Hutchinson Pharmaceuticals: Research Funding; Seattle Genetics: Speakers Bureau; Verastem: Speakers Bureau; AbbVie: Speakers Bureau.

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Understanding Oncological Disparities in Mycosis Fungoides within Hispanic Enriched Communities

Blood ◽

10.1182/blood-2021-151891 ◽

2021 ◽

Vol 138 (Supplement 1) ◽

pp. 5016-5016

Author(s):

Rodolfo Garza-Morales ◽

Carolina Velez-Mejia ◽

Qianqian Liu ◽

Joel E Michalek ◽

Adolfo Enrique Diaz Duque

Keyword(s):

Survival Time ◽

Mycosis Fungoides ◽

Survival Probability ◽

Research Funding ◽

Private Insurance ◽

Statistical Testing ◽

Insurance Status ◽

Poverty Index ◽

Significant Difference ◽

Age Of Diagnosis

Abstract Introduction Cutaneous T cell lymphomas (CTCLs) are a heterogeneous group of extra-nodal non-Hodgkin's lymphomas that are characterized by a cutaneous infiltration of malignant monoclonal T lymphocytes (F1000Res. PMID 27540476). Among them, Mycosis Fungoides (MF) is the most predominant subtype, accounting for 50-65% of cases (An Bras Dermatol. PMID 30066762). Although most patients with MF are Non-Hispanic (NH), from the 1970s to 2010s there has been an increase in the percentage of HI patients (4% to 11%, respectively) (J Eur Acad Dermatol Venereol. PMID 32141115). Racial disparities in MF have been studied, but they are still poorly understood in Hispanic (HI) populations and further studies are needed to evaluate the role of ethnicity in MF outcomes. In this study, we focused on two communities, Texas (TX) and Florida (FL), which have a strong HI representation. According to the U.S 2020 Census, 39% of the population of TX and 26% of the population of FL are HI. Therefore, the purpose of this study is to compare demographics, treatment patterns, and survival outcomes of HI and NH patients diagnosed with MF, and to contrast HI cohorts between TX and FL. Methods This is a retrospective analysis of patients diagnosed and recorded in the Texas Cancer Registry and the Florida Cancer Data System from years (y) 2006-2017. Inclusion criteria was histopathologic proven MF. Patients were divided into HI and NH for comparison. Standard demographic, socioeconomic, clinical, and survival variables were reviewed. All statistical testing was determined using Fisher's Exact test, Pearson's Chi-square test, T-test or Wilcoxon test, as appropriate. Survival time was measured using the day of diagnosis to last date of follow up or death. Survival distribution were calculated based on Kaplan-Meier curves. All statistical testing was two-sided with a significance level of 5%. Results We identified a total 2566 (1373 TX, 1193 FL) patients with MF. 319 (12%) were HI and 2247 (88%) were NH. The median age of diagnosis in our TX population was 50 y in HI and 59 y in NH (p < 0.001). In FL, the median age of diagnosis was 57 y in HI and 65 y in NH (p <0.001). There was a statistically significant difference in poverty index between HI and NH in both TX and FL. The majority of HI (42%) in TX were in the 20-100% bracket while the majority of NH (28%) in TX were in the 10-19.9% bracket (p<0.001). In contrast, the majority of HI (36%) in FL were in the 10-19.9% bracket while the majority of NH (34%) in FL were also in the 10-19.9% bracket (p<0.001). In patient where insurance status was known, there was a statistically significant difference in insurance status with the most frequent insurance being private insurance for HI in TX (28%) and NH in TX (24%) (p<0.001). In FL, HI (39%) had private insurance whereas NH (30%) had government-sponsored insurance (p<0.001). The most common stage at diagnosis in both cohorts in TX and FL was Stage I with 56% HI in TX vs 56% NH in TX (p=0.526) and 54% HI in FL vs 44% NH in FL (p=0.052). In both cohorts, majority of HI (71%) in TX, and NH (72%) in TX (p=0.38), HI (73%) in FL and NH (81%) (p=0.156) did not undergo chemotherapy. In TX, median survival (MS) was 10.8 y for HI, and 9.7y for NH; whereas in FL, MS was not reached for HI, and for NH was 8.3y. The survival probability at 2 y was 0.921, 0.904, 0.875, 0.836 for HI in TX, NH in TX, HI in FL, and NH in FL, respectively. The survival probability at 5 y was 0.819, 0.775, 0.728, 0.665 for HI in TX, NH in TX, HI in FL, and NH in FL, respectively. The survival probability at 10 y was 0.714, 0.440, 0.512, 0.451 for HI in TX, NH in TX, HI in FL, and NH in FL, respectively. There was no statistically significant difference in overall survival (OS) probability between HI and NH in TX (p = 0.079) and FL (p = 0.28). Conclusions In this study, we evaluated ethnic disparities in MF, we chose to study TX and FL, two states that have a strong HI representation. In both populations, we found a statistically significant difference between HI and NH in poverty index and insurance status. Although there were no statistically significant differences in median survival time or survival probability at 2, 5, and 10 y among the HI and NH cohorts within each state, we observed that NH and HI in FL had a lower survival probability at 2, 5, and 10 y when compared to NH and HI in TX. Moreover, NH in TX had a much lower OS probability when compared to HI. These disparities may be a direct reflection of the significantly higher rates of poverty among HI in FL compared to HI in TX. Figure 1 Figure 1. Disclosures Diaz Duque: Incyte: Consultancy; Morphosys: Speakers Bureau; Astra Zeneca: Research Funding; Hutchinson Pharmaceuticals: Research Funding; Epizyme: Consultancy; ADCT: Consultancy.

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Demographic Differences in the Treatment and Mortality of Lymphoplasmacytic Lymphoma in Texas: Does Ethnicity Play Any Role?

Blood ◽

10.1182/blood-2020-138604 ◽

2020 ◽

Vol 136 (Supplement 1) ◽

pp. 17-20

Author(s):

Michael E Auster ◽

Snegha Ananth ◽

Lakene Raissa Djoufack Djoumessi ◽

Qianqian Liu ◽

Joel E Michalek ◽

...

Keyword(s):

Survival Time ◽

Median Survival ◽

Survival Probability ◽

Research Funding ◽

Statistical Testing ◽

P Value ◽

Hispanic Paradox ◽

Lymphoplasmacytic Lymphoma ◽

Poverty Index ◽

Significant Difference

BACKGROUND: Social determinants and demographics exert an overwhelming influence on the health of the individual and overall population health (J Am Geriatr Soc. PMID: 28369694).The Hispanic paradox has been well characterized, demonstrating that although Hispanic patients (HisP) have higher disability, depressive, metabolic, and inflammatory risk when compared to non-Hispanic (nHisP), they continue to live long lives (J Health Soc Behav. PMID: 31771347). The characterization of these differences in hematology has not been well documented. This study seeks to characterize Lymphoplasmacytic lymphoma (LPL). LPL is a rare lymphoma of B-cell origin demonstrating an incidence of 1000 to 1500 new cases per year in the United States (Hematol Oncol Clin North Am, PMID: 31229160). Epidemiological research is not well documented in this lymphoma subtype, especially regarding the HisP. Given that Texas has the second highest state with HisP in the country (US Census Bureau), we studied the demographics of this disease and specifically researched the demographics, treatment patterns and survival between HisP and nHisP in Texas. METHODS: This is a retrospective study of a cohort of patients diagnosed with lymphoma (Hodgkin and Non-Hodgkin) from the Texas Cancer Registry (TCR) database. Patient's included were those >18 years of age during 2006-2016 and this study focused on the LPL subset. Standard demographic variables collected include gender, race, ethnicity, birthplace, occupation, dates at diagnosis and death, primary payer at diagnosis, subtype of lymphoma, stage, type of treatment, poverty index, and vitality status among others. The significance of variation in the distribution of categorical outcomes with ethnicity (HisP, nHisP) was assessed with Fisher's Exact tests or Pearson's Chi-square tests as appropriate; age was assessed with T-tests or Wilcoxon tests as appropriate. Survival time was measured in years from date of primary diagnosis to date of death. Survival distributions were described with Kaplan-Meier curves and significance of variation in median survival with ethnicity was assessed with log rank testing. All statistical testing was two-sided with a significance level of 5%. RESULTS AND DISCUSSION: Out of 490 patients diagnosed with LPL, 64 were HisP and 426 nHisP. Of this population, the HisP had a higher percentage of patients at the higher end of the poverty index (42.4% to 20% with p value <0.001) and higher rates of being uninsured or on Medicare (51.6 to 43.4% with p value <0.001). There were no statistically significant differences in the staging at the time of diagnosis between the two groups, mostly III/IV (HisP 65.6% to nHisP 62% P value 0.387). Treatment modalities differed slightly in that the nHisP populations were more likely to receive beam radiation than the HisP (3.4% to 0, P value 0.005) but overall chemotherapy differences were not statistically significant. The median survival time in years for HisP and nHisP was 6.8 and 7.6 respectively, and the overall survival probability was not significantly different with a P value of 0.59. The survival probabilities at 2, 5 and 10 years between HisP and nHisP were respectively, 0.657 with Confidence interval (CI)[0.545,0.792], 0.573 CI [0.455,0.722], 0.448 CI [0.32,0.627], compared to 0.766 CI [0.723,0.811], 0.620 CI [0.566,0.68], 0.129 CI [0.042,0.389]. CONCLUSION: In this study we show that in Texas, for those diagnosed with LPL, there is a statistically significant difference in the rates of poverty and insurance when comparing Hisp to nHisP. While this is true, there is no clear statistically significant difference in overall treatment or survival probability, which is consistent with the Hispanic paradox. Due to the rarity of this disease, the population size is limited which may skew the data. More research is needed in order to further characterize the differences between these two populations and determine what can be done to narrow these differences. Disclosures Diaz Duque: ADCT Therapeutics: Research Funding; Molecular Templates: Research Funding; AstraZeneca: Research Funding; Hutchinson Pharmaceuticals: Research Funding; Seattle Genetics: Speakers Bureau; Verastem: Speakers Bureau; AbbVie: Speakers Bureau.

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Is There a Disparity in Oncological Outcomes for Hispanics? Analysis of Burkitt Lymphoma

Blood ◽

10.1182/blood-2020-136485 ◽

2020 ◽

Vol 136 (Supplement 1) ◽

pp. 45-46

Author(s):

Carolina Velez-Mejia ◽

Daniela Hernandez ◽

Joel E Michalek ◽

Qianqian Liu ◽

Adolfo Enrique Diaz Duque

Keyword(s):

Overall Survival ◽

Survival Analysis ◽

Survival Probability ◽

Burkitt Lymphoma ◽

Research Funding ◽

Statistical Testing ◽

Statistical Computing ◽

P Value ◽

Oncological Outcomes ◽

The Us

Background Burkitt lymphoma (BL) is a rare but highly aggressive B cell neoplasm, with treatment success rates exceeding 80% in the United States (US) (Blood, PMC:3682339). Although there are different presentations of BL, the treatment and prognosis are quite similar among them (Blood, PMID:15265787). Trends in outcomes of BL have been previously reported, however, sub-analysis for minorities like Hispanics (HI), have not been widely studied. Understanding ethnic disparities in outcomes and patterns of care are crucial given the growth of HI in the US (APMIS, PMID:23607450). There is an unmet need in this field; therefore, this population-based study aims to help understand the impact of ethnicity in clinical outcomes for BL. Material and Methods A retrospective analysis of patients diagnosed with BL recorded in the Texas Cancer Registry was carried out. Inclusion criteria was histopathologic proven BL using the International Classification of Diseases for Oncology Third Edition (ICD-O-3) code list. Patients were divided in HI and non-Hispanics (NH) for comparison. Key demographic, socioeconomic, clinical, and survival outcome variables were reviewed. All statistical testing was determined using Fisher's Exact test, Pearson's Chi-square test, T-test or Wilcoxon test, as appropriate. Survival analysis was calculated in years from date of primary diagnosis to date of death or last date of follow up. Survival distributions were described with Kaplan-Meier curves and significance of variation in median survival with ethnicity was assessed with log rank testing. All statistical testing was two-sided with a significance level of 5%. The R language [R Core Team (2013). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria] was used throughout. Results From 2006-2016, 896 patients (HI: n=275, NH: n=621) were diagnosed with BL. The median age at diagnosis for HI was 41 years vs 44 for NH [p-value 0.05]. Male sex predominated for HI and NH. Origin for HI was mainly Spain, Mexico and Central/South America. Both HI and NH were mainly identified as white; other races included black, asian and Native American [p-value <0.001]. For HI, the bracket of poverty indicator that prevailed was 20-100%; while majority of NH were in 10-19.99% [p-value <0.001]. There was a statistical significance regarding the primary payer at diagnosis [p-value <0.001]. HI had a similar distribution among private insurance (PI), Medicaid, Medicare and not insured/self-pay; while NH had primarily PI. The greatest proportion of HI and NH where located in the metropolitan, non-border area. The majority of HI and NH were diagnosed at stage III-IV [p-value 0.459]. Treatment at diagnosis showed a similar pattern for HI and NH, choosing mainly chemotherapy. For both groups, most of the patients did not undergo transplant or radiation (Figure1A). The median survival time for HI was 4.2 years and for NH was 7.0 years. Survival probability at 2, 5 and 10 years for HI was 0.53 (CI=0.467,0.599), 0.50 (CI=0.484,0.573) and 0.33 (CI=0.213,0.515), respectively. For NH it was 0.60 (CI=0.568,0.65), 0.53 (CI=0.385,0.506) and 0.44 (0.385,0.506), respectively (Figure1B). The overall survival probability at 10 years did not show a statistically significant difference for HI vs NH [p-value 0.12] (Figure1C). Conclusions Survival analysis at 10 years shows similar outcomes for HI vs NH; however, significant differences were observed in demographics and sociocultural variables. HI were diagnosed at a younger age, predominantly of Spanish origin and white race. More HI were uninsured compared to NH, as well as their poverty index was statistically higher. The fact that no variation was reported in overall survival may be explained by the use of standardized treatment. From our analysis, racial or economical variations do not seem to affect oncological outcomes in BL for HI in the US. Disclosures Diaz Duque: ADCT Therapeutics: Research Funding; Molecular Templates: Research Funding; AstraZeneca: Research Funding; Hutchinson Pharmaceuticals: Research Funding; Seattle Genetics: Speakers Bureau; Verastem: Speakers Bureau; AbbVie: Speakers Bureau.

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A First Large Statewide Population Based Study Evaluating Racial Differences in Treatment and Survival between Hispanics and Non-Hispanics with Diffuse Large B Cell Lymphoma (DLBCL)

Blood ◽

10.1182/blood-2020-142151 ◽

2020 ◽

Vol 136 (Supplement 1) ◽

pp. 9-9

Author(s):

Daniela Hernandez ◽

Carolina Velez-Mejia ◽

Joel E Michalek ◽

Qianqian Liu ◽

Adolfo Enrique Diaz Duque

Keyword(s):

Survival Time ◽

Racial Differences ◽

Survival Probability ◽

Research Funding ◽

B Cell Lymphoma ◽

Population Based ◽

P Value ◽

Poverty Index ◽

Large B Cell Lymphoma ◽

Kaplan Meier

BACKGROUND: Diffuse Large B Cell Lymphoma (DLBCL) is the most common and most aggressive subtype of Non-Hodgkin Lymphoma. (Blood PMID: 9166827) Despite significant advances, treatment survival remains heterogenous due to biologic differences and perhaps ethnic and racial disparities. Multiple epidemiological studies have evaluated racial differences, mainly comparing African Americans (AA) with Non-Hispanic (NH), showing AA patients have a 10-20% higher risk of death. (BMC PMID: 21073707, Leuk PMID: 22800091, Cancer PMID: 24048801) A recent study showed how socioeconomic factors also influence patient survival and this can be linked to racial differences as well. (Blood PMID: 24705494). Small sample studies have characterized DLBCL in Hispanics (HI) but no definite conclusions have been drawn. (ASH Blood 2018 132:4867, JCO 10.1200, Blood (2019) 134 (Supplement_1): 2916). The need of larger studies to characterize survival differences establishes the basis of our population-based analysis in Texas comparing DLBCL in HI vs NH. METHODS: This is a retrospective study of a cohort of patients diagnosed with lymphoma from the Texas Cancer Registry (TCR) database. Patients with DLBCL diagnosed from 2006 to 2016 were identified by the International Classification of Diseases for Oncology Third Edition (ICD-O-3) code list. Standard demographic variables collected include gender, race, ethnicity, birthplace, occupation, dates at diagnosis and death, primary payer at diagnosis, subtype of lymphoma, stage, type of treatment, poverty index, and vitality status among others. Categorical outcomes were summarized with frequencies and percentages and age (years) was the only continuously distributed outcome with the mean and standard deviation. The significance of variation in the distribution of categorical outcomes with ethnicity (HI, NH) was assessed with Fisher's Exact tests or Pearson's Chi-square tests as appropriate; age was assessed with T-tests or Wilcoxon tests as appropriate. Survival time was measured in years from date of primary diagnosis to date of death. Patients not coded as dead were considered censored on survival time at the date last seen. Survival distributions were described with Kaplan-Meier curves and significance of variation in median survival with ethnicity was assessed with log rank testing. At risk tables were computed based on the Kaplan-Meier estimate of the survival curve. All statistical testing was two-sided with a significance level of 5%. RESULTS: A total of 15,083 patients met inclusion criteria, with 3583 HI and 11500 NH diagnosed with DLBCL from 2006 to 2016. Demographic data was analyzed and compared between both groups, (Fig 1A). The median age of diagnosis was 61.7 on HI population and 65 on the NH. Among the HI population most of the patients were of Mexican origin (25%). HI have a higher percentage (24%) of non-insured or Medicaid than NH (8%) with a significant p value of <0.001 and a statistically significant higher poverty index within HI with 54% living on a 20-100% poverty land. Staging was similar between both groups. Most of the patients, 46% of HI and 45% of NH, have a stage III-IV grade DLBCL. The NH population received more treatment with chemotherapy 4% compared to 2% of the HI group, but this difference was not statistically significant. Both groups received similar treatments with bone marrow transplant, or radiation. The median survival time was similar between HI and NH, 4.4 and 4.3 years respectively. Survival probability at 2, 5 and 10 years for HI was 0.59 (CI 0.576,0.611), 0.48 (CI 0.467, 0.506) and 0.301 (CI 0.265,0.34) respectively. For NH the survival probability was similar, 0.602 (CI 0.592,0.611), 0.473 (CI 0.463,0484) and 0.242 (CI 0.223,0.262) respectively (Fig 1B). The overall survival probability at 10 years did not show a statistically significant difference for HI vs NH (p-value 0.46) (Fig 1C). CONCLUSION. Despite demographic disparities between HI and NH, and statistically significant differences with more HI patients uninsured and a higher index of poverty land; there was no significant distinction in overall survival in patients with DLBCL. The findings suggest no impact of ethnicity to that regard. Disclosures Diaz Duque: ADCT Therapeutics: Research Funding; Molecular Templates: Research Funding; AstraZeneca: Research Funding; Hutchinson Pharmaceuticals: Research Funding; Seattle Genetics: Speakers Bureau; Verastem: Speakers Bureau; AbbVie: Speakers Bureau.

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Ethnicity Matters When Comparing Overall Survival for Patients Diagnosed with Follicular Lymphoma

Blood ◽

10.1182/blood-2021-147902 ◽

2021 ◽

Vol 138 (Supplement 1) ◽

pp. 1356-1356

Author(s):

Carolina Velez-Mejia ◽

Rodolfo Garza Morales ◽

Qianqian Liu ◽

Joel E Michalek ◽

Adolfo Enrique Diaz Duque

Keyword(s):

Overall Survival ◽

Follicular Lymphoma ◽

Survival Probability ◽

Research Funding ◽

Median Overall Survival ◽

Population Based ◽

Statistical Testing ◽

Wilcoxon Test ◽

P Value ◽

Population Based Study

Abstract Background Follicular lymphoma (FLy) is one of the most common subtypes of Non-Hodgkin Lymphomas (NHL) (Cancer EpidemiolPMC4323749). In prior studies, better progression-free survival has been noted in Hispanics (HI), however, further characterization of this ethnic minority needs to be addressed (Ann Lymphoma PMC5877479). This result is consistent with previous research explaining the development of NHL as an heterogeneous process where unique outcomes for races have been noted (Cancer PMID: 22434428). This is the first combined statewide population-based study of Texas (TX) and Florida (FL) evaluating ethnic differences for HI vs Non-Hispanics (NH) comparingdemographics, socioeconomic, clinical and survival patterns of patients diagnosed with FLy. The value of using these states relies on the fact that the percentage of HI in TX and FL are 39.7% and 26.4%, respectively (US Census 2020). Material and Methods This is a retrospective analysis of patients diagnosed with FLy recorded in the Texas Cancer Registry and the Florida Cancer Data System from 2006-2017. Inclusion criteria was histopathologic proven FLy. Patients were divided into HI and NH for comparison. Standard demographic, socioeconomic, clinical, and survival variables were reviewed. All statistical testing was determined using Fisher's Exact test, Pearson's Chi-square test, T-test or Wilcoxon test, as appropriate. Survival time was measured using the day of diagnosis to last date of follow up or death. Survival distribution were calculated based on Kaplan-Meier curves. Results From 2006-2017, 20,497 patients (HI n=3,176, NH n=17,321) were diagnosed with FLy (Table 1, Table 3). In TX, the median age at diagnosis for HI was 60 years (y) vs 64 y for NH [p-value <0.001]. In FL, it was 62 y and 67 y, respectively [p-value <0.001]. In both states, female sex predominated for HI and NH. In TX, the bracket of poverty index that prevailed for HI was 20-100% while for NH was 10-19.9% [p-value <0.001]. In FL, the largest number of HI and NH were in the 10-19.9% bracket [p-value <0.001]. In TX, both HI and NH were more likely be with government-sponsor insurance, however, up to 15% of HI did not have insurance vs 4% in NH [p-value <0.001]. This was also the case in FL, however their number of uninsurance corresponded to 6% and 2% respectively. In TX, the largest number of HI and NH patients were diagnosed at stage III-IV with 49% and 42% respectively [p-value <0.001]. In FL, for these stages it corresponded to 43% and 37% for HI and NH [p-value <0.001]. In TX, treatment at diagnosis showed a similar pattern for HI and NH, choosing mainly no treatment followed by multiple chemotherapy agents [p-value <0.001]. In FL, this trend was also seen. In both states and for HI and NH, most of the patients did not undergo transplant or radiation. In TX, the median overall survival for HI was 9.2 y vs 8.6 y for NH; the survival probability at 2, 5 and 10 y for HI corresponded to 0.835, 0.701 and 0.453, while for NH it was 0.850, 0.703 and 0.354, respectively; and the overall survival probability at 10 y had no statistically significant difference [p-value 0.44] (Table 2, Graph 1). In FL, the median overall survival for HI was not reached vs NH at 10.1 y; the survival probability for HI at 2, 5 and 10 y was 0.871, 0.777 and 0.601, while for NH it was 0.845, 0.709 and 0.506, respectively; and the overall survival probability at 10 y was statistically significant [p-value <0.0001] (Table 4, Graph 2). Conclusions This large two statewide population-based study identified statistical differences in oncological outcomes comparing HI and NH in patients diagnosed with FLy. HI diagnosed with FLy have higher survival at 10 y, and this difference was statistically significant in FL. Moreover, statistical significance was noted in demographic, sociodemographic and disease characteristics. Additional research should be carried out to identify the variables that drive this difference since advance stage, lack of insurance or treatment at diagnosis do not seem to be influencing it. There may be a combination of lifestyle factors (alcohol, cigarette, diet, other), occupational hazards, autoimmune diseases or protective mechanisms, infectious diseases exposures and unique epigenetic interactions that may explain why HI live longer when diagnosed with FLy. Figure 1 Figure 1. Disclosures Diaz Duque: Incyte: Consultancy; Morphosys: Speakers Bureau; Astra Zeneca: Research Funding; Hutchinson Pharmaceuticals: Research Funding; Epizyme: Consultancy; ADCT: Consultancy.

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The Role of Ethnicity in Hepatosplenic T-Cell Lymphoma: A Retrospective Survival Analysis in Texas

Blood ◽

10.1182/blood-2020-142502 ◽

2020 ◽

Vol 136 (Supplement 1) ◽

pp. 19-19

Author(s):

Leyla Bojanini Molina ◽

Joel E Michalek ◽

Qianqian Liu ◽

Adolfo Enrique Diaz Duque

Keyword(s):

Overall Survival ◽

Survival Analysis ◽

Survival Probability ◽

Research Funding ◽

Clinical Characteristics ◽

Median Overall Survival ◽

Cell Lymphoma ◽

Statistical Computing ◽

P Value ◽

Hepatosplenic T Cell Lymphoma

Background Hepatosplenic T-Cell lymphoma (HSTCL) is an aggressive type of lymphoma with extremely low incidence. It has a high fatality rate with a 5-year overall survival (OS) of <10% (Am J Surg Pathol, PMID: 26872013). Although there is no therapy that has proven to produce sustained remission, recent studies suggest improvement in outcomes with allogeneic stem cell transplant (allo-SCT) (Leukemia, PMID: 25234166). Clinical characteristics and therapeutic outcomes have been previously reported; however, documentation of outcomes in minorities such as Hispanics (HI) are lacking. Given the growth of the HI population in the US it is imperative to understand the difference in outcomes and patterns of care (CA Cancer J Clin, PMID: 30285281). The present study aims to fill this gap in the literature; therefore, the present population-based study evaluates the impact of ethnicity in clinical outcomes for HSTCL. Material and Methods We retrospectively searched for cases of HSTCL recorded in the Texas Cancer Registry. Inclusion criteria included and established pathologic diagnosis of HSTCL using the International Classification of Diseases for Oncology Third Edition (ICD-O-3) code list. Patients were divided between HI and non-Hispanics (NH). Demographic, socioeconomic, clinical and survival outcomes were recorded. Statistical analysis included Fisher's Exact test, Pearson's Chi-square test, T-test or Wilcoxon test. Survival analysis was calculation in years from date of primary diagnosis to date of death or last date of follow up. Survival distributions were described with Kaplan-Meier curves, and long rank testing was used to assess significance of variation in median survival with ethnicity. All statistical testing was two-sided with a significance level of 5%. The R language [R Core Team (2013). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria] was used throughout. Results From 2006-2016, a total of 25 patients were diagnosed with HSTCL; 23 (92%) were NH and 2 (7%) were HI [<0.0001]. The median age at diagnosis was 46 for HI and 48 for NH. It was predominantly seen in males for both HI and NH. The patients mostly self-identified as white (HI: n=2, Nh: n=16), and there were 7 (30%) NH patients that self-identified as black. For HI, one patient was in the bracket of poverty indicator of 10-19.9% and the other one was in the 20-100%; for the NH patients the bracket that prevailed was 10-19.9% [p-value 0.56]. Both HI patients had private insurance (PI); insurance status on NH patients included 7 (33.3%) with PI, 5 (23.8%) with Medicare, and 7 (33.3%) was unknown [p-value 0.64]. The majority of HI and NH patients were located in the metropolitan, non-border area. Stage at diagnosis for NH was mostly III-IV; one HI had a stage III-IV HSTCL and the other was unstaged [p-value 1.0]. From a therapeutic standpoint, the majority of HI and NH patients received chemotherapy, with 13 patients (HI: n=2, NH: n=11) receiving multiple agents as first-line therapy [p-value 0.84]. From the two groups, only 3 (13%) NH patients underwent allo-SCT [p-value 0.014]. The majority of HI and NH did not undergo radiation (Figure 1A). The median overall survival was 0.5 years in HI and 0.6 in NH. The survival probability at 2 years for HI and NH was 0.5 (CI=0.16, 1) and 0.29 (CI=0.15, 0.56) respectively; at 5 years for HI was 0.5 (CI 0.16, 1) and for NH was 0.23 (CI=0.10, 0.51) (Figure 1B). The overall survival probability at 10 years was not statistically different for HI vs NH [p-value 0.53] (Figure 1C). Conclusions Survival analysis shows that HSTCL is usually fatal with a median overall survival of less than a year, and no difference in survival probability at 10 years for both HI and NH. The majority of patients in our study were non-Hispanic white males. A significant finding was that NH patients had access to allo-SCT as opposed to the HI patients. No statistically significant difference in survival was noted depending on the insurance or poverty levels. No other demographics or sociocultural variables seemed to have an impact in outcomes. The main limitation of our study is our sample size that limits generalizability and power of our statistical analysis. Further studies using multiple cancer registries are warranted to assess the clinical characteristics and survival outcomes in HI with HSTCL. Disclosures Diaz Duque: ADCT Therapeutics: Research Funding; Molecular Templates: Research Funding; AstraZeneca: Research Funding; Hutchinson Pharmaceuticals: Research Funding; Seattle Genetics: Speakers Bureau; Verastem: Speakers Bureau; AbbVie: Speakers Bureau.

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Population-Based Analysis of Hispanic Vs Non-Hispanic Patients Diagnosed with Hodgkin Lymphoma in Texas and Florida

Blood ◽

10.1182/blood-2021-152695 ◽

2021 ◽

Vol 138 (Supplement 1) ◽

pp. 4531-4531

Author(s):

Abhishek Pandya ◽

Munaf Al-Kadhimi ◽

Qianqian Liu ◽

Joel E Michalek ◽

Adolfo Enrique Diaz Duque

Keyword(s):

Survival Time ◽

Hodgkin Lymphoma ◽

Median Survival ◽

Survival Probability ◽

Research Funding ◽

Poverty Index ◽

Survival Probabilities ◽

Kaplan Meier ◽

Significant Difference ◽

Race Ethnicity

Abstract Introduction: Classical Hodgkin lymphoma (cHL) accounts for about 90% of cases of HL. (Medicine PMID 26107683) Within cHL, there are 4 main histologic subtypes; the incidence of cHL varies based on age, race/ethnicity, geography, socioeconomic factors, Epstein Barr virus status, and the prevalence of HIV/AIDS. (Adv HematologyPMID 21197477) Considerable disparities exist in the incidence and survival rates between Hispanic (H) and non-Hispanic (NH) populations with cHL. (Ann Oncol PMID 22241896) Between 2013-2017, the incidence rate of cHL in Florida (FL) was 457 per 100,00, and in Texas (TX), it was 408 per 100,000. (North American Association of Central Cancer Registries, 2020) Our study aims to determine demographics, treatment outcomes, and survival outcomes of H and NH patients diagnosed with cHL in TX and FL. Methods: This is a retrospective study of a cohort of patients diagnosed with lymphoma (Hodgkin and Non-Hodgkin) from the Texas Cancer Registry (TCR) and the Florida Cancer Data System (FCDS) between 2006-2017. The third edition of the International Classification of Diseases for Oncology (ICD-O-3) was used to identify patient with cHL. Variables include gender, race, ethnicity, birthplace, occupation, dates at diagnosis and death, primary payer at diagnosis, subtype of lymphoma, stage, type of treatment, poverty index, and vitality status. The significance of variation in the distribution of categorical outcomes with ethnicity (H, NH) was assessed with Fisher's Exact tests or Pearson's Chi-square tests as appropriate; age was assessed with T-tests or Wilcoxon tests as appropriate. Survival time was measured in years from date of primary diagnosis to the date of death. Survival distributions were described with Kaplan-Meier curves and significance of variation in median survival with ethnicity was assessed with log rank testing. At risk tables were computed based on the Kaplan-Meier estimate of the survival curve. All statistical testing was two-sided with a significance level of 5%. Corrections for multiple testing were not applied. Results: There were 6152 (1266 H, 4886 NH) patients in FL and 6241(1736 H, 4505 NH) patients in TX identified with cHL. In FL, the median age at diagnosis was 44.8 years (y) for H vs 48.3y for NH (p < 0.001) while in TX, there was no statistically significant difference (45.8y H, 44.9y NH, p = 0.102). In FL, there was no statistically significant difference among females (44% H, 46% NH, p = 0.136) and males (56% H, 53% NH, p = 0.136) while there was one in TX among females (43% H, 45% NH, p = 0.048) and males (58% H, 55% NH, p = 0.048). In FL, the majority of H (40.5%) and NH (36.6%) were in the 10-19.9% poverty index (p<0.001). In TX, the majority of H (51.2%) were in the 20-100% poverty index while the majority of NH (32.2%) were in the 10-19.9% index (p<0.001). In FL, 10.7% H and 6.4% NH were without insurance at time of diagnosis (p<0.001) while in TX, 23.8% H and 11.7% NH were in that position (p<0.001). The most common stage of diagnosis was stage III/IV with 37.8% H vs 34.2% NH in FL (p<0.001) and 44.1% H vs 34.6% NH in TX (p<0001). In FL, median survival time was 10.6y H vs 11.4y NH, while in TX, it was 10.3y H vs 10.4y NH. In FL, the survival probabilities at years 2, 5, and 10 were 0.858, 0.774, and 0.550 for H vs 0.808, 0.696, and 0.545 for NH, respectively. In TX, the survival probabilities at years 2, 5, and 10 were 0.758, 0.674, and 0.522 for H vs 0.828, 0.743, and 0.579 for NH, respectively. The survival probability at years 2, 5, and 10 were higher for H compared to NH in FL (p = 0.0018), however the survival probability at years 2, 5, and 10 were lower for H compared to NH in TX (p < 0.0001). Conclusion: Our study of patients diagnosed with cHL demonstrated several statistically significant differences among H and NH patients in both states. Importantly, H patients in TX had a statistically significant lower survival probability at 2, 5, and 10y compared to NH patients. A reason for this could be the more significant number of uninsured H as compared to NH patients. Conversely, H patients in FL had a statistically significant higher survival probability at 2 and 5y compared to NH patients, partly explained by the lower median age of diagnosis of H patients compared to NH patients. There is a need for further analysis that could help explain the disparities among the different ethnicities. Figure 1 Figure 1. Disclosures Diaz Duque: Astra Zeneca: Research Funding; Epizyme: Consultancy; Morphosys: Speakers Bureau; Incyte: Consultancy; ADCT: Consultancy; Hutchinson Pharmaceuticals: Research Funding.

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Disparities in Mantle Cell Lymphoma Outcomes in Hispanics: A Population Based Analysis in Texas and Florida

Blood ◽

10.1182/blood-2021-145937 ◽

2021 ◽

Vol 138 (Supplement 1) ◽

pp. 4081-4081

Author(s):

Brian Warnecke ◽

Daniel Rosas ◽

Alexandra Wehbe ◽

Qianqian Liu ◽

Joel E Michalek ◽

...

Keyword(s):

Survival Time ◽

Median Survival ◽

Survival Probability ◽

Median Survival Time ◽

Research Funding ◽

Cell Lymphoma ◽

Poverty Index ◽

Significant Difference ◽

Mantle Cell ◽

Age Of Diagnosis

Abstract Introduction: Mantle cell lymphoma (MCL) is a rare, aggressive type of B-cell non-Hodgkin lymphoma (NHL) that accounts for approximately 7% of adult NHL's in the United States. (JCO PMID: 9704731)Although recent advancements in treatment have improved survival, prognosis remains poor. (Blood PMID: 30154113) There have been several recent studies demonstrating ethnic disparities in MCL, however, there is a paucity of survival outcome data in Hispanic (H) patients with MCL. (CLMLPMID: 31029647) The purpose of this study was to compare the demographics, treatment patterns, and survival outcomes of H and Non-Hispanic (NH) patients diagnosed with MCL, and to contrast Hispanic cohorts between Texas (TX) and Florida (FL). Methods: This is a retrospective cohort study of patients diagnosed with lymphoma (Hodgkin and Non-Hodgkin) from the Texas Cancer Registry (TCR) and the Florida Cancer Data System (FCDS) from 2006-2017. This particular analysis focuses on patients with diagnosis of MCL. Key variables included gender, race, ethnicity, birthplace, dates of diagnosis and death, primary payer at diagnosis, poverty index, stage at diagnosis, and type of treatment. The significance of variation in distribution of categorical outcomes with ethnicity [H, NH] was assessed with Fisher's Exact tests or Pearson's Chi-square as appropriate; age was assessed with T-test or Wilcoxon. Survival time was measured in years from date of primary diagnosis to date of death. Survival distributions were described with Kaplan-Meier curves and significance of variation in median survival with ethnicity was assessed with log rank testing. All statistical testing was two-sided with a significance level of 0.05. Results: We identified a total 4619 (2078 TX, 2541 FL) patients with MCL. 669 (15%) were H and 3950 (85%) were NH. In TX, the median age of diagnosis was 65.6 years (y) in H and 68.3 y in NH (p < 0.001). In FL, the median age of diagnosis was 67.56 in H and 70.06 in NH (p < 0.001). There was a statistically significant difference in poverty index between the cohorts in both TX and FL. The majority of H (50%) in TX were in the 20-100% bracket while the majority of NH (36%) in TX were in the 10-19.9% bracket (p < 0.001). The majority of H (39%) in FL were in the 10-19.9% bracket, and the majority of NH (35%) were also in the 10-19.9% bracket (p < 0.001). Interestingly, there were only 30% of H in FL in the 20-100% bracket. There was a statistically significant difference in insurance status with the most frequent insurance being government-sponsored insurance for H in TX (48%), NH in TX (58%), H in FL (48%), and NH in FL (62%). Patients were without insurance at time of diagnosis in 14% of H in TX and 9% of H in FL, in contrast to 4% of NH in TX and 2% NH in FL. The most common stage at diagnosis in both cohorts in TX and FL was Stage III/IV with 68% H in TX vs 65% NH in TX (p = 0.746) and 69% H in FL vs 67% NH in FL (p = 0.316). The most frequent chemotherapy regimen included multiple agents for all cohorts, 43% H in TX vs 37% NH in TX (p = 0.063), and 48% H in FL vs 42% NH in FL (p = 0.695). Median survival time was 3.4 y H in TX, 3.5 y NH in TX, 4.1 y H in FL, and 4.3 y NH in FL. The survival probability at 2 years was 0.636, 0.640, 0.707, 0.675 for H in TX, NH in TX, H in FL, and NH in FL, respectively. The survival probability at 5 years was 0.371, 0.379, 0.445, 0.459 for H in TX, NH in TX, H in FL, and NH in FL, respectively. The survival probability at 10 years was 0.147, 0.118, 0.276, 0.245 for H in TX, NH in TX, H in FL, and NH in FL, respectively. There was no statistically significant difference in survival probability at 2, 5, or 10 years between H and NH in TX (p = 0.68) and FL (p = 0.72). Conclusions: Our study of patients diagnosed with MCL demonstrated statistically significant differences between H and NH patients in median age of diagnosis, poverty index, and insurance status at diagnosis. These disparities were observed in patients between the cancer registries in both states. Although there were no statistically significant differences in median survival time or survival probability at 2, 5, and 10 years among the H cohorts within each state, we observed intriguing data when the two states were compared. Strikingly, H in TX had much lower survival probability at 2, 5, and 10 years compared to H in FL. In addition, H in TX were noted to have a shorter median survival time compared to H in FL. These disparities may be a direct reflection of the significantly higher rates of poverty and lack of insurance among H in TX compared to H in FL. Figure 1 Figure 1. Disclosures Diaz Duque: ADCT Therapeutics: Research Funding; Astra Zeneca: Research Funding; Hutchinson Pharmaceuticals: Research Funding; Epizyme: Research Funding.

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Survival and Outcomes for T-Cell Lymphomas in a Ubiquitous Hispanic Community: A Texas Cancer Registry Retrospective Study

Blood ◽

10.1182/blood-2020-136223 ◽

2020 ◽

Vol 136 (Supplement 1) ◽

pp. 17-18

Author(s):

Gerardo Manuel Rosas ◽

Sushanth Kakarla ◽

Brian Warnecke ◽

Sarah Allison Smith ◽

Joel E Michalek ◽

...

Keyword(s):

United States ◽

Overall Survival ◽

Retrospective Study ◽

T Cell ◽

Cancer Registry ◽

Research Funding ◽

The United States ◽

Poverty Index ◽

T Cell Lymphomas ◽

Kaplan Meier

BACKGROUND Non-Hodgkin Lymphomas (NHL) represent one of the most common cancers in the United States, accounting for about 4% of all cancers and it is estimated over 77,000 people (including children and adults) will be diagnosed with NHL in the United States in 2020. Depending on the data, it is estimated T-cell lymphomas make up anywhere from 7 to 15% of all NHLs. Given their relative rarity compared to other sub-types of lymphomas (and malignancies at large), there is a scarce literature regarding their outcomes in ethnic minority groups. Retrospective reviews of cancer registries and SEER databases have demonstrated conflicting evidence regarding outcomes in Hispanics (HI) with some studies suggesting worse overall survival (OS) in this group (Clin Lymphoma Myeloma Leuk. PMID: 26198444), while others suggest comparable outcomes in the setting of healthcare homogeneity (Leuk Lymphoma. PMID: 25012944). MATERIALS/METHODS This is a retrospective study of a cohort of patients diagnosed with T-cell NHL from the Texas Cancer Registry (2006-2016). Patients were identified by the International Classification of Diseases for Oncology Third Edition (ICD-O-3) code list. Data was provided to us completely de-identified. Key variables collected included gender, ethnicity, dates at diagnosis and death, payer, stage, treatment, and poverty index. Categorical outcomes were summarized with frequencies and percentages and age, the only continuously distributed outcome, with the mean and standard deviation. The significance of variation in distribution of categorical outcomes with ethnicity [HI, non-Hispanic (NH)] was assessed with Fisher's Exact tests or Pearson's Chi-square as appropriate; age was assessed with T-test or Wilcoxon. Survival time was measured in years from date of primary diagnosis to date of death. Survival distributions were described with Kaplan-Meier curves and significance of variation in median survival with ethnicity was assessed with log rank testing. At risk tables were computed based on the Kaplan-Meier estimate of the survival curve. All statistical testing was two-sided with a significance level of 5%. Corrections for multiple testing were not applied. The R language was used throughout. RESULTS We identified 2074 patients with T-cell NHL (n= 902 Peripheral T Cell, NOS; 295 Angioimmunoblastic T Cell; 577 Anaplastic Large T Cell; 120 NK/T-cell; and 180 Adult T-cell Leukemia/Lymphoma). 553 were HI (26%), 1521 NH (74%). Median age of diagnosis in HI was 50.1 vs 57.4 in NH (p = <0.001). Males were more frequently affected, 63.8% in HI vs 58.9% in NH (p = 0.048). Most frequent poverty index was 20-100% for HI vs 10-19.9% for NH (p < 0.001). Most frequent payor for both groups were Medicare with 24.3% in HI vs 35.3% in NH (p < 0.001). Most common stage at diagnosis in both groups was III/IV with 50.3% in HI vs 49.7% in NH (p = 0.031). Most frequent chemotherapy included multiple agents for both, 55.7% in HI vs 44.2% in NH (p < 0.001). Majority in both groups had neither hematologic transplant 90.2% in HI vs 85.3% in NH (p = 0.073) nor radiation, 84.4% in HI vs 82.9% in NH (p = 0.076). Median overall survival (OS) in HI was 1.7 years vs 1.9 in NH; survival probability for HI vs NH at 2 years was 0.46 vs 0.49, at 5 years 0.37 vs 0.35, and at 10 years 0.24 vs 0.23 with no statistically significant difference in OS probability (p=0.89). CONCLUSION Our study demonstrates that amongst the population of Texas, HI with T-cell NHL have similar outcomes when compared to their NH counterparts. Breakdown of our cohort demonstrated similar healthcare utilization, as well as diagnostic and treatment modalities amongst both groups. Within the context of healthcare equality, we ascertained similar outcomes amongst groups, which is in agreement with previous reports claiming homogeneity of medical care helps overcome ethnic disparities. Figure Disclosures Diaz Duque: ADCT Therapeutics: Research Funding; Molecular Templates: Research Funding; AstraZeneca: Research Funding; Hutchinson Pharmaceuticals: Research Funding; Seattle Genetics: Speakers Bureau; Verastem: Speakers Bureau; AbbVie: Speakers Bureau.

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Comparison of Troponin T and N-Terminal-Pro-Brain Natriuretic Peptides In Two Models of Treatment Related Mortality In AL Amyloidosis Patients Following Autologous Stem Cell Transplantation

Blood ◽

10.1182/blood.v116.21.3572.3572 ◽

2010 ◽

Vol 116 (21) ◽

pp. 3572-3572

Author(s):

Nelson Leung ◽

Shaji Kumar ◽

Angela Dispenzieri ◽

Martha Lacy ◽

Francis Buadi ◽

...

Keyword(s):

Risk Factors ◽

Overall Survival ◽

Multivariate Analysis ◽

Uric Acid ◽

Risk Factor ◽

Risk Ratio ◽

Research Funding ◽

P Value ◽

Additional Risk ◽

Kaplan Meier

Abstract Abstract 3572 High dose melphalan and autologous stem cell transplantation (ASCT) is an effective treatment for light chain amyloidosis (AL) but high treatment related mortality (TRM) limits its use. Both cardiac troponin T (cTnT) and N-terminal-pro-brain natriuretic peptide (NT-pro-BNP) are sensitive predictors of high risk patients. Aim of this study is to compare two models of TRM, one using cTnT and the other BNP. Patients who underwent ASCT between 7/1996 and 7/2009 at the Mayo Clinic were analyzed retrospectively. Variables were chosen for ease of measurement and reproducibility thus echocardiographic parameters were excluded. Each additional risk factor must contribute to a significant increase in TRM. Also, since NT-pro-BNP and cTnT are already highly associated with mortality, the other risk factors must be independent predictors. Univariate analysis revealed serum albumin, B-2-microglobulin, cTnT, NT-pro-BNP, and uric acid were associated with TRM while age, sex, alkaline phosphatase, serum creatinine, CRP, proteinuria were not (Table 1). Multivariate analysis showed albumin and uric acid were independent risk factors to cTnT and NT-pro-BNP (Table 2). Of the 412 patients, 347 (8.9% TRM) could be evaluated by the cTnT, albumin and uric acid (TAU) model and 282 (9.2%) TRM could be evaluated by the NT-pro-BNP, albumin, uric acid (BAU) model. Both models showed increasing TRM with additional risk factors beyond 1 risk factor (Table 3 and 4). Albumin and uric acid were found to be significant contributors in both models. Patients with elevated cTnT alone had a 0% TRM vs 23.4% if they had 1 additional risk factor, p = 0.03. Similarly, TRM was 3.7% in patients with elevated NT-pro-BNP alone but 18.0% if they had 1 other risk factor, p = 0.05. NT-pro-BNP and cTnT could not be used in the same model because cTnT becomes non-significant. Both models were superior to visceral organ involvement which had TRM of 5.3% with 1, 9.2% with 2 and 16.7% with 3 organ involvement. Both models were also predictive of overall survival (Figure 1 and Figure 1b). Our results show that these models show that albumin and uric acid with either cTnT or NT-pro-BNP can accurately predict TRM in AL patients undergoing ASCT. Multivariate analysis shows that the NT-pro-BNP containing model may be superior since cTnT loses it significance when added to the model. Our results suggest these models could be very helpful in identifying high risk patients not suitable for ASCT. Figure 1a Overall survival evaluated by Kaplan-Meier method on 347 patients using the TAU model. Mortality increased significantly with the number of risk factors, p < 0.001. Solid line represents patients with 0 risk factors, dotted line represents patients with 1 risk factor, dashed line represents those with 2 risk factors and dotted dashed line represent those with 3 risk factors. Figure 1a. Overall survival evaluated by Kaplan-Meier method on 347 patients using the TAU model. Mortality increased significantly with the number of risk factors, p < 0.001. Solid line represents patients with 0 risk factors, dotted line represents patients with 1 risk factor, dashed line represents those with 2 risk factors and dotted dashed line represent those with 3 risk factors. Figure 1b Overall survival evaluated by Kaplan-Meier method on 282 patients using the BAU model. Overall survival was significantly longer in patients with less risk factors, p < 0.001. Solid line represents patients with 0 risk factors, dotted line represents patients with 1 risk factor, dashed line represents those with 2 risk factors and dotted dashed line represent those with 3 risk factors. Figure 1b. Overall survival evaluated by Kaplan-Meier method on 282 patients using the BAU model. Overall survival was significantly longer in patients with less risk factors, p < 0.001. Solid line represents patients with 0 risk factors, dotted line represents patients with 1 risk factor, dashed line represents those with 2 risk factors and dotted dashed line represent those with 3 risk factors. Table 1. Patient characteristics Control TRM p-value N 318 29 Age 58 (25–73) 55 (35–75) 0.54 Sex (male) 58.2% 72.4% 0.13 Albumin (g/dl) 2.7 (0.8–4.4) 2.2 (0.8–3.7) 0.02 Alkaline phosphatase (U/L) 89 (28–1014) 86 (31–1394) 0.22 b2m (mg/ml) 2.6 (1.0–35.1) 3.2 (1.3–15.2) 0.007 NT-pro-BNP (pg/ml) 564 (12–35000) 1661 (21–35001) 0.03 CRP (mg/L) 0.3 (0.01–16.6) 0.3 (0.05–3.2) 0.34 cTnT (ng/ml) 0.01 (0–1.0) 0.03 (0.01–0.22) <0.001 Scr (mg/dl) 1.1 (0.4–12) 1.2 (0.8–2.3) 0.09 Proteinuria (g/d) 3.4 (0.01–35.4) 5.1 (0.1–20.5) 0.10 Uric acid (mg/dl) 6.2 (1–14.8) 7.5 (3.7–13.2) 0.02 Organ Involvement 1 94.7% 5.3% 0.04 2 90.7% 9.3% 3 83.3% 16.7% Table 2. Multivariate analysis using proportional hazard model cutoffs >Risk Ratio >p-value Model TAU cTnT 0.04 ng/ml 2.78 0.01 Albumin 3.3 g/dl 3.11 0.03 Uric acid 8.5 mg/dl 2.69 0.02 Model BAU NT-pro-BNP 1270 pg/ml 3.77 0.003 Albumin 3.3 g/dl 3.53 0.04 Uric acid 8.5 mg/dl 3.11 0.03 Table 3. Model of cTnT, albumin and uric acid TAU Risk Factors n TRM p-value Risk Ratio 0 69 2.9% 1 205 5.9% 0.33 2 61 16.4% 0.009 2.98 3 12 41.7% 0.05 8.52 Table 4. Model of NT-pro-BNP, albumin and uric acid BAU Risk Factors >n >TRM >p-value >Risk Ratio 0 28 0% 1 161 5.6% 0.20 2 82 14.6% 0.02 2.7 3 11 45.5% 0.01 10.8 Disclosures: Kumar: Celgene: Consultancy, Research Funding; Millennium: Research Funding; Merck: Consultancy, Research Funding; Novartis: Research Funding; Genzyme: Consultancy, Research Funding; Cephalon: Research Funding. Dispenzieri:Celgene: Honoraria, Research Funding; Binding Site: Honoraria. Lacy:Celgene: Research Funding.

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