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

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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Homozygous Deletion of p16, p14 and p15 Is a Poor Prognostic Factor in Adult B-Lineage Acute Lymphoblastic Leukemia, Not in Childhood B-ALL: A Comparison through Deletion and Hypermethylation Study

Blood ◽

10.1182/blood.v112.11.4477.4477 ◽

2008 ◽

Vol 112 (11) ◽

pp. 4477-4477

Author(s):

Miyoung Kim ◽

Seon-Hee Yim ◽

Hai Rim Shin ◽

Nam Sun Cho ◽

Seong_Ho Kang ◽

...

Keyword(s):

Overall Survival ◽

Multivariate Analysis ◽

Promoter Methylation ◽

Lymphoblastic Leukemia ◽

Disease Free Survival ◽

Homozygous Deletion ◽

P Value ◽

Free Survival ◽

Kaplan Meier ◽

P15 Gene

Abstract Backgrounds: The biologic characteristics of childhood acute lymphoblastic leukemia (ALL) is different from those of adult ALL. Tumor suppressor genes, p16, p14, and p15 gene are inactivated either by promoter methylation, deletion or mutation, however, in leukemia, promoter methylation and deletion are the main mechanisms of inactivation. Aims: To compare the alteration status of p16, p14, and p15 gene in childhood and adult ALL, we analyzed the incidences and the prognostic significances of deletion and hypermethylation of p16, p14, and p15 in childhood and adult B-ALL. The association between alterations of those genes and known cytogenetic prognostic factors (BCR-ABL, TEL-AML, MLL rearrangement, and numerical changes) were also assessed. Methods: A total of 91 newly diagnosed B-ALL patients (61 children, 30 adults) were studied. Interphase fluorescent in situ hybridization study (p16, BCR-ABL, TEL-AML, MLL) and methylation specific PCR were performed using bone marrow mononuclear cells. Numerical changes were assessed by FISH and chromosome analysis. Chi-square test, Fisher’s exact test, Kaplan and Meier method and Cox proportional hazards regression were applied for statistical analysis. Results: The frequencies of homozygous deletion of p16, p14, and p15 were 11.5% in children and 30.0% in adult, showing higher incidence in adults (p=0.029). In overall survival study, homozygous deletion was associated with the worse prognosis in adults (Fig 1, p=0.019), but not in childhood. The incidences of promoter methylation of p16, p14, and p15 were as follows: 34.4%, 14.8%, and 34.4% in children; 26.7%, 10.0%, and 40.0% 26.7% in adults, respectively, with no statistical difference between two groups. No significant association was observed between deletion and hypermethylation. Childhood ALL showed inactivation of p16 (39.3%), p14 (24.6%), and p15 (42.6%), while adult ALL showed inactivation of p16 (46.7%), p14 (33.3%), and p15 (56.7%), with the same order of frequencies, but with higher tendency of methylation in adult ALL. In p14 unmethylated adults, the homozygous deletion had adverse effect on overall survival (OS) (p=0.036). There were no significant association between chromosomal aberrations and promoter methylation in childhood and adult ALL. The children with sole MLL rearrangement showed poorer disease free survival (DFS) than those with sole homozygous deletion with low statistical significance (p=0.059). Homozygous deletion was translated into poor prognosis in OS in adults without MLL rearrangement (p=0.011). Adult with normal karyotype showed shorter OS when accompanied by homozygous deletion, although p value was 0.051. Conclusions: We performed a comprehensive analysis of deletion and hypermethylation of p16, p14, and p15 genes in both childhood and adult B-ALL. Homozygous deletion was more frequent in adults, showing association with shorter OS in adults, but not in children. This difference of distribution and prognostic value between childhood and adult ALL could be one of the explanations for the disparity of clinical outcome. Our results suggest that homozygous deletion is an independent prognostic factor in adult ALL. Table 1. Deletion and methylation profiles of p16, p14, and p15, and their prognostic siginificances P16, P14, and P15 Deletion P16 Methylation P14 Methylation P15 Methylation *P: p value by multivariate analysis †OS: Overall survival ‡DPS: Disease free survival Childhood Frequency 11.5% 34.4% 14.8% 34.4% *P (†OS) 0.853 0.979 0.651 0.591 P (‡DPS) 0.716 0.956 0.809 0.977 Adults Frequency 30.0% 26.7% 10.0% 40.0% P (OS) 0.019 0.151 0 892 0.330 P (DPS) 0.218 0.382 0.079 0.760 Figure 1. Kaplan-Meier curve for childhood and adult B-ALL patients.  P value was obtained by multivariate analysis using Cox hazard regression model. (A) Childhood B-ALL (B) B. Adult B-ALL Figure 1. Kaplan-Meier curve for childhood and adult B-ALL patients.  P value was obtained by multivariate analysis using Cox hazard regression model. (A) Childhood B-ALL (B) B. Adult B-ALL

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Risk Factors Associated with Survival Outcome in Patients with Chronic Myeloid Leukaemia in Accelerated Phase Treated with Tyrosine Kinase Inhibitors

Blood ◽

10.1182/blood.v128.22.1222.1222 ◽

2016 ◽

Vol 128 (22) ◽

pp. 1222-1222

Author(s):

Kee Yon, Lionel See ◽

Kok Chong Bernard Yap ◽

Dong-Wook Kim ◽

Hein Than ◽

Yeow-Tee Goh

Keyword(s):

Risk Factors ◽

High Risk ◽

Board Of Directors ◽

Research Funding ◽

Chronic Phase ◽

Progression Free Survival ◽

P Value ◽

Survival Curves ◽

Advisory Committees ◽

Kaplan Meier

Abstract Chronic Myeloid Leukaemia (CML) is a triphasic disease which typically presents in chronic phase with risk of progression to more aggressive phases in a certain proportion of patients. Accelerated Phase (AP), as described in the pre-Tyrosine Kinase Inhibitor (TKI) era by Kantarjian et al in 1988, is an intermediate stage with a poor median overall survival (OS) of ≤18 months without haematopoietic stem cell transplantation (HSCT). Since TKI therapy has revolutionized CML treatment, a significantly improved OS has been seen in most CML patients, including those in AP. Not all CML-AP patients require HSCT upfront nowadays and many are able to achieve major molecular remission (MMR) and favourable OS on TKI therapy. However, updated classifications of CML-AP by the World Health Organization (WHO) and European LeukemiaNet (ELN) do not reflect these significant advances in the TKI era. There is a need to re-evaluate the CML-AP classification that will have an impact on treatment decisions for CML-AP patients. In this study, we explored the association between various haematological parameters at diagnosis and the probabilities of OS and progression-free survival (PFS) of CML-AP patients on TKI therapy. Overall Survival (OS) and Progression-Free Survival (PFS) trends of 75 newly diagnosed CML-AP patients treated with frontline TKIs between 2000 to 2013 from Singapore General Hospital and Seoul St. Mary's Hospital in South Korea were retrospectively analysed with regards to demographic and haematological parameters, such as cell counts from serum and bone marrow at diagnosis, using cox proportional hazards analysis. Survival was also compared using log-rank test with Bonferroni corrections between CML-AP patients and 227 CML Chronic Phase (CML-CP) high-risk Sokal and 34 Blast Crisis (CML-BC) patients on TKI-based therapy. OS was defined as duration from diagnosis of CML-AP to death from any reason. PFS was defined as duration from disease diagnosis to the first occurrence of progression or death due to CML. As a whole, CML-AP patients treated with frontline TKI had survival that paralleled CML-CP high-risk Sokal patients (p-value = 0.694 for OS, p-value = 0.258 for PFS). Most of the death and progression occurred less than 3 years of starting TKI therapy (69.2% for OS, 84.6% for PFS). Multivariable analysis in CML-AP patients showed that male gender, bone marrow (BM) blasts ≥10% and clonal chromosomal abnormalities (CCAs) at diagnosis were associated with poor OS (Hazard Ratio (HR) 18.53, p-value = 0.013; HR 1.16, p-value = 0.010; HR 5.05, p-value = 0.044, respectively) and poor PFS (HR 12.96, p-value = 0.021; HR 1.17, p-value = 0.007; HR 8.84.05, p-value = 0.008, respectively). CML-AP patients with all 3 of these risk factors experienced the worst OS compared to those with 1 or zero risk factors (p-value <0.001). Patients with all 3 risk factors also had the poorest PFS compared to those with 2, 1 and zero risk factors (p-value = 0.022, <0.001, <0.001 respectively; figure 1). CML-AP Patients with 2 risk factors or less, had OS and PFS probabilities comparable to CML-CP patients with high-risk Sokal score (p-value = 0.082 for OS, p-value= 0.813 for PFS, figure 2 and 3 respectively). However, CML-AP patients with all 3 risk factors showed inferior OS and PFS probabilities similar to CML-BC patients (p-value = 0.799 for OS, p-value = 0.624 for PFS; figure 2 and 3 respectively). Our findings suggested that CML-AP was a heterogeneous group with varying survival probabilities on TKI therapy. Male gender, BM blasts ≥10% and CCAs at diagnosis were risk factors shown to be predictive of survival probabilities, and identified a high-risk sub-group among CML-AP patients with inferior OS and PFS rates similar to CML-BC patients. Aggressive chemotherapeutic strategies including HSCT should be warranted in these patients. However, TKI therapy alone with close molecular surveillance may be a reasonable option for optimally responding low-risk CML-AP patients who are not eligible for HSCT. Figure 1. Kaplan-Meier survival curves for PFS according to stratification of the number of risk factors present in CML-AP patients. Figure 1. Kaplan-Meier survival curves for PFS according to stratification of the number of risk factors present in CML-AP patients. Figure 2. Kaplan-Meier survival curves for OS according to phases of CML with AP patients separated by number of risk factors present. Figure 2. Kaplan-Meier survival curves for OS according to phases of CML with AP patients separated by number of risk factors present. Figure 3. Kaplan-Meier survival curves for PFS according to phases of CML with AP patients separated by number of risk factors present. Figure 3. Kaplan-Meier survival curves for PFS according to phases of CML with AP patients separated by number of risk factors present. Disclosures Kim: BMS: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Novartis: Consultancy, Honoraria, Research Funding, Speakers Bureau; ILYANG: Consultancy, Honoraria, Research Funding; Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau. Goh:BMS: Honoraria; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche: Honoraria; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Honoraria; Takeda: Honoraria; Alexion: Honoraria, Membership on an entity's Board of Directors or advisory committees.

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The Impact of Graft Nephrectomy on Subsequent Transplants: Multivariate Analysis of Risk Factors for Second Graft Loss and for Multiple Transplantations–A Single-Center Retrospective Study

ISRN Transplantation ◽

10.5402/2013/362571 ◽

2013 ◽

Vol 2013 ◽

pp. 1-9 ◽

Cited By ~ 1

Author(s):

Emmanouil Giorgakis ◽

Asim Syed ◽

Hector Gonzalez

Keyword(s):

Risk Factors ◽

Multivariate Analysis ◽

Risk Factor ◽

Retrospective Study ◽

Independent Risk Factor ◽

Graft Loss ◽

Kaplan Meier ◽

Independent Risk Factors ◽

Allograft Loss ◽

The Impact

Introduction. The management of a failed primary allograft remains unclear and the evidence of the effect of transplantectomy to future transplants conflicting. Aim of this study is to review the impact of failed primary graft nephrectomy on future transplants. Materials/Methods. Retrospective study of 101 patients retransplanted in a single institution. Median follow-up was 68 months. Patients were divided into two groups; G1 (n=49) was the nephrectomy group; G2 (n=52) was the graft in situ group. The patients’ and second graft survival were analysed with the Kaplan-Meier method. The patients’ and transplant characteristics were analyzed with student’s t-test. The retransplant risk factors and the risk factors for multiple transplants were obtained via a logistic regression model. Results. The odds of second graft loss post-transplantectomy were high (OR = 5.24). Demographics, HLA mismatch and first graft rejection rates were similar among the two groups and did not affect the outcome. Transplantectomy accelerated the loss of a future failing graft. Multivariate analysis showed transplantectomy as independent risk factor for second allograft loss. Transplantectomy and younger age are significant independent risk factors for future multiple transplants. Conclusion. Transplantectomy of the failed primary graft is an independent risk factor for retransplant loss and for multiple renal transplants.

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Connect MM®—the Multiple Myeloma (MM) Disease Registry: Interim Analysis of Overall Survival and Outcomes in Patients with High-Risk Disease

Blood ◽

10.1182/blood.v124.21.2106.2106 ◽

2014 ◽

Vol 124 (21) ◽

pp. 2106-2106 ◽

Cited By ~ 1

Author(s):

Jatin J. Shah ◽

Rafat Abonour ◽

Brian G M Durie ◽

Jayesh Mehta ◽

Mohit Narang ◽

...

Keyword(s):

Risk Factors ◽

Overall Survival ◽

African American ◽

High Risk ◽

Board Of Directors ◽

Interim Analysis ◽

Research Funding ◽

Advisory Committees ◽

Kaplan Meier ◽

High Risk Disease

Abstract Background: MM treatment (Tx) advances have greatly improved clinical outcomes for patients (pts). A recent study demonstrated improved survival in MM through the past decade attributable to the impact of initial therapy with lenalidomide, bortezomib, and thalidomide. The greatest impact was observed in older pts (Kumar, et al. Leukemia, 2014). Connect MM, the first and largest prospective, observational, US-based, multicenter registry was designed to characterize pts, Tx patterns, and outcomes in newly diagnosed MM (NDMM). Methods: This ongoing registry was initiated in September 2009. Eligible pts with NDMM (diagnosis must have occurred within 2 mos of study entry) were enrolled at 234 US sites. Data were collected at baseline and each subsequent quarter using an electronic case report form. The initial enrollment includes all pts who had provided informed consent as of November 1, 2012 (N = 1493). The data cutoff for this analysis was Dec 10, 2013. A total of 1444 pts were treated and were included in overall survival (OS) analyses. Survival was examined for all treated pts adjusting for pt and Tx characteristics including age, autologous stem cell transplant (ASCT) status, gender, race, disease risk factors (International Myeloma Working Group [IMWG] high risk vs. non-high risk), and therapy received (triplet vs. non-triplet) among others. Triplet therapy was defined as any combination of 3 or more drugs during the first Tx regimen. OS was estimated using Kaplan-Meier methods and comparisons across groups were assessed used the log-rank test. Results: At the time of data cutoff, 1493 pts were enrolled with 1444 having received Tx. Of the treated pts 253 pts (18%) had IMWG high-risk disease and 108 pts (7%) had del(17p) at baseline. Median age was 67 y (range, 24-94 y), 57.2% were male, and 81.9% were white. Median follow-up was 29 mos (0-49.4 mos). The median OS for all treated pts was 44.4 mos. When assessed by age group, OS was significantly different (log-rank P < .0001) with a median of 47.6 mos for pts aged < 65 y (n = 632), 45.0 mos for those aged 65 to < 75 y (n = 443), and 33.7 mos for those aged ≥ 75 y (n = 369). OS was significantly longer for pts with ASCT vs. no ASCT (P < .0001), but not different by gender (P = .962) or race (Caucasian vs. African American vs. other; P = .250). Three-year OS probabilities by subgroup are listed in Table 1. When considering risk factors, IMWG risk was borderline significant (high vs. non-high; P = .106), and presence of del(17p) by cytogenetics and FISH was associated with significantly shortened OS (P = .005; Figure 1A). Interestingly, use of triplet therapy vs. non-triplet therapy was associated with significantly prolonged OS regardless of IMWG risk (non-high: P < .0001; high: P = .003; Figure 1B). However, no improvement was noted for triplet vs. non-triplet therapy in pts with del(17p). By multivariate analysis, the significant (P < .05) factors impacting OS were age (in 10-yr increments), International Staging System (ISS) disease stage, ECOG performance status, history of diabetes, anemia, renal function, and platelet count. Conclusions: This interim analysis based on initially treated pts demonstrated that age, ISS stage, and co-morbidities impact OS irrespective of IMWG cytogenetic risk. Triplet Tx was associated with significantly longer OS in pts regardless of IMWG risk status. This is the largest prospective pt cohort with high-risk disease including del(17p). Pts with high-risk disease did not have significantly lower OS vs. pts without high-risk features. Pts with del(17p) (p53 deletion) continue to have shorter OS approaching 3 y and increased survival with use of triplet therapy. Table 1. Kaplan-Meier Estimated 3-Y OS Probability Patients 3-y OS Probability (%) (95% CI) All (N = 1444) 62.6 (59.5-65.8) < 65 y (n = 632) 69.8 (65.2-74.3) 65 to < 75 y (n = 443) 65.0 (59.4-70.6) ≥ 75 y (n = 369) 47.2 (40.7-53.8) Gender Male (n = 831) 62.1 (57.9-66.3) Female (n = 613) 63.4 (58.7-68.2) Race Caucasian (n = 1191) 61.8 (58.3-65.3) African American (n = 183) 64.4 (55.4-73.5) Other (n = 27) 77.6 (57.3-98.0) ASCT Yes (n = 494) 77.1 (72.5-81.7) No (n = 950) 54.2 (50.0-58.3) Triplet therapy Yes (n = 778) 69.3 (65.3-73.3) No (n = 666) 54.8 (49.9-59.6) IMWG risk High (n = 253) 59.0 (51.6-66.4) Standard (n = 566) 66.3 (61.4-71.2) Low (n = 86) 75.7 (63.6-87.8) del(17p) Present (n = 108) 52.7 (41.8-63.6) Absent (n = 1336) 63.4 (60.1-66.7) Figure 1 Figure 1. Disclosures Shah: Celgene Corp: Consultancy, Research Funding. Abonour:Celgene Corp: Honoraria, Speakers Bureau. Durie:Celgene Corp: Export Board Committee Other, Membership on an entity's Board of Directors or advisory committees; IRC Onyx: Membership on an entity's Board of Directors or advisory committees; DMC Millennium: Membership on an entity's Board of Directors or advisory committees; IRC J&J: Membership on an entity's Board of Directors or advisory committees. Mehta:Celgene Corp: Consultancy, Speakers Bureau. Narang:Celgene Corp: Membership on an entity's Board of Directors or advisory committees. Terebelo:Celgene Corp: Membership on an entity's Board of Directors or advisory committees. Gasparetto:Celgene: Consultancy, Honoraria; Millenium: Honoraria. Thomas:Celgene Corp: Membership on an entity's Board of Directors or advisory committees. Toomey:Celgene Corp: Membership on an entity's Board of Directors or advisory committees. Hardin:Celgene Corp: Research Funding. Srinivasan:Celgene Corp: Employment, Equity Ownership. Ricafort:Celgene Corp: Employment. Nagarwala:Celgene Corp: Employment. Rifkin:Celgene Corp: Consultancy; Millenium: Consultancy; Onyx: Consultancy; Takeda: Consultancy; Amgen: Consultancy.

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

Blood ◽

10.1182/blood-2020-137230 ◽

2020 ◽

Vol 136 (Supplement 1) ◽

pp. 29-30

Author(s):

Sushanth Kakarla ◽

Gerardo Manuel Rosas ◽

Sarah Allison Smith ◽

Brian Warnecke ◽

Joel E Michalek ◽

...

Keyword(s):

Overall Survival ◽

Survival Time ◽

Survival Probability ◽

Research Funding ◽

Private Insurance ◽

Statistical Testing ◽

Statistical Computing ◽

P Value ◽

Poverty Index ◽

Kaplan Meier

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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Similar 1 Year Survival of Patients Receiving Plerixafor (Mozobil*®) Plus G-CSF Versus Placebo Plus G-CSF Mobilized Autologous Grafts: Results From Two Phase 3 Randomized Trials in Patients with NHL or MM Undergoing Autologous Transplantation After Front-Line or Rescue Mobilization.

Blood ◽

10.1182/blood.v114.22.2319.2319 ◽

2009 ◽

Vol 114 (22) ◽

pp. 2319-2319

Author(s):

Ivana N Micallef ◽

Patrick Stiff ◽

Edward Stadtmauer ◽

Brian J. Bolwell ◽

Sachin Marulkar ◽

...

Keyword(s):

Overall Survival ◽

Board Of Directors ◽

Research Funding ◽

P Value ◽

Phase 3 ◽

Two Phase ◽

Advisory Committees ◽

Kaplan Meier ◽

Cd34 Cells ◽

Equity Ownership

Abstract Abstract 2319 Poster Board II-296 Background: Data from two phase 3 clinical trials indicate that plerixafor plus G-CSF is safe and more effective than G-CSF alone in mobilizing CD34+ hematopoietic stem cells (HSC) for autologous HSC transplantation (auto-HSCT) in patients with non-Hodgkin's lymphoma (NHL) or multiple myeloma (MM). Herein we report 1-year overall survival in patients with NHL or MM who have undergone auto-HSCT with cells mobilized with plerixafor plus G-CSF compared to placebo plus G-CSF. Furthermore, we also report 1-year overall survival in patients with NHL who failed mobilization on either arm and entered a rescue protocol. Methods: Data were obtained from two prospective, randomized, double-blind, placebo-controlled, phase 3 clinical trials that compared the safety and efficacy of plerixafor (0.24 mg/kg/day SQ) plus G-CSF (10 mg/kg/day) with placebo plus G-CSF for mobilization of HSC for autologous HSCT in patients with NHL or MM. In the NHL study, patients in either study arm who failed mobilization (&0.8 ×106 CD34+ cells/kg in 2 days or &2 × 106 CD34+ cells/kg in 4 days) were eligible to enter the rescue protocol and received plerixafor + G-CSF mobilization. Overall survival in patients was estimated by the Kaplan-Meier method. Results: In the NHL study, 135/150 (90.0%) patients in the plerixafor group compared with 82/148 (55.4%) patients in the placebo group, underwent transplantation (p&0.001) with a median (range) of 5.41 (1.95-17.6) and 3.85 (1.98-8.74) × 106 CD34+ cells/kg, respectively (p&0.001). A total of 62 patients (10 from the plerixafor arm and 52 from the placebo arm) failed mobilization and proceeded to rescue mobilization with plerixafor + G-CSF. Of these, 52 patients (84%) proceeded to transplantation with a median (range) of 3.8 (1.1-10.5) x 106 CD34+ cells/kg. Kaplan-Meier estimates of 1-year overall survival for patients in the plerixafor and placebo groups in the primary ITT population (rescue patients were censored as of consent date for rescue) were 76.0% and 64.7%, respectively. Kaplan-Meier estimate of 1-year overall survival in the rescue group was 83.7%. The Log rank p-value comparing all 3 survival estimates (plerixafor, placebo and rescue) was 0.765 (Figure 1A). In the MM study, 142/148 (95.9%) patients in the plerixafor group and 136/154 (88.3%) patients in the placebo group underwent transplantation (p=0.014) with a median (range) of 5.40 (1.20-16.74) and 3.96 (1.76-16.88) × 106 CD34+ cells/kg, respectively (p&0.001). In this trial, Kaplan-Meier estimates of 1-year overall survival in the plerixafor and placebo groups were 93.6% and 95.8%, respectively (Log-rank p-value=0.771; Figure 1B). Conclusions: These data suggest that overall survival at 1 year is similar between patients with MM or NHL mobilized with plerixafor plus G-CSF compared to placebo plus G-CSF. Furthermore, in the NHL study, patient survival in the rescue protocol was similar to that seen in the phase III trial. Collection of follow-up data on overall survival is ongoing. Disclosures: Micallef: Genzyme Corporation: Membership on an entity's Board of Directors or advisory committees, Research Funding. Stiff:Genzyme Corporation: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Stadtmauer:Genzyme Corporation: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Bolwell:Genzyme Corporation: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Marulkar:Genzyme Corporation: Employment, Equity Ownership. Hsu:Genzyme Corporation: Employment, Equity Ownership. DiPersio:Genzyme: Honoraria.

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Prevalence and prognostic impact of left ventricular systolic dysfunction after acute myocardial infarction

European Heart Journal ◽

10.1093/ehjci/ehaa946.1796 ◽

2020 ◽

Vol 41 (Supplement_2) ◽

Author(s):

T.J Jernberg ◽

E.O Omerovic ◽

E.H Hamilton ◽

K.L Lindmark ◽

L.D Desta ◽

...

Keyword(s):

Diabetes Mellitus ◽

Risk Factors ◽

Myocardial Infarction ◽

Atrial Fibrillation ◽

Risk Factor ◽

Reperfusion Therapy ◽

Left Ventricular ◽

Funding Source ◽

Additional Risk Factor ◽

Additional Risk

Abstract Background Left ventricular dysfunction after an acute myocardial infarction (MI) is associated with poor outcome. The PARADISE-MI trial is examining whether an angiotensin receptor-neprilysin inhibitor reduces the risk of cardiovascular death or worsening heart failure (HF) in this population. The aim of this study was to examine the prevalence and prognosis of different subsets of post-MI patients in a real-world setting. Additionally, the prognostic importance of some common risk factors used as risk enrichment criteria in the PARADISE-MI trial were specifically examined. Methods In a nationwide myocardial infarction registry (SWEDEHEART), including 87 177 patients with type 1 MI between 2011–2018, 3 subsets of patients were identified in the overall MI cohort (where patients with previous HF were excluded); population 1 (n=27 568 (32%)) with signs of acute HF or an ejection fraction (EF) <50%, population 2 (n=13 038 (15%)) with signs of acute HF or an EF <40%, and population 3 (PARADISE-MI like) (n=11 175 (13%)) with signs of acute HF or an EF <40% and at least one risk factor (Age ≥70, eGFR <60, diabetes mellitus, prior MI, atrial fibrillation, EF <30%, Killip III-IV and STEMI without reperfusion therapy). Results When all MIs, population 1 (HF or EF <50%), 2 (HF or EF <40%) and 3 (HF or EF <40% + additional risk factor (PARADISE-MI like)) were compared, the median (IQR) age increased from 70 (61–79) to 77 (70–84). Also, the proportion of diabetes (22% to 33%), STEMI (38% to 50%), atrial fibrillation (10% to 24%) and Killip-class >2 (1% to 7%) increased. After 3 years of follow-up, the cumulative probability of death or readmission because of heart failure in the overall MI population and in population 1 to 3 was 17.4%, 26.9%, 37.6% and 41.8%, respectively. In population 2, all risk factors were independently associated with death or readmission because of HF (Age ≥70 (HR (95% CI): 1.80 (1.66–1.95)), eGFR <60 (1.62 (1.52–1.74)), diabetes mellitus (1.35 (1.26–1.44)), prior MI (1.16 (1.07–1.25)), atrial fibrillation (1.35 (1.26–1.45)), EF <30% (1.69 (1.58–1.81)), Killip III-IV (1.34 (1.19–1.51)) and STEMI without reperfusion therapy (1.34 (1.21–1.48))) in a multivariable Cox regression analysis. The risk increased with increasing number of risk factors (Figure 1). Conclusion Depending on definition, post MI HF is present in 13–32% of all MI patients and is associated with a high risk of subsequent death or readmission because of HF. The risk increases significantly with every additional risk factor. There is a need to optimize management and improve outcomes for this high risk population. Figure 1 Funding Acknowledgement Type of funding source: Private company. Main funding source(s): Novartis

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Abstract P146: Uric Acid is an Independent Risk Factor for Developing Hypertension From Prehypertension: A 5-year Japanese Cohort Study

Hypertension ◽

10.1161/hyp.70.suppl_1.p146 ◽

2017 ◽

Vol 70 (suppl_1) ◽

Author(s):

Masanari Kuwabara ◽

Shigeko Hara ◽

Koichiro Niwa ◽

Minoru Ohno ◽

Ichiro Hisatome

Keyword(s):

Diabetes Mellitus ◽

Risk Factors ◽

Blood Pressure ◽

Body Mass Index ◽

Uric Acid ◽

Risk Factor ◽

Cohort Study ◽

Serum Uric Acid ◽

Independent Risk Factor ◽

Drinking Habits

Objectives: Prehypertension frequently progresses to hypertension and is associated with cardiovascular diseases, stroke, excess morbidity and mortality. However, the identical risk factors for developing hypertension from prehypertension are not clarified. This study is conducted to clarify the risks. Methods: We conducted a retrospective 5-year cohort study using the data from 3,584 prehypertensive Japanese adults (52.1±11.0 years, 2,081 men) in 2004 and reevaluated it 5 years later. We calculated the cumulative incidences of hypertension over 5 years, then, we detected the risk factors and calculated odds ratios (ORs) for developing hypertension by crude analysis and after adjustments for age, sex, body mass index, smoking and drinking habits, baseline systolic and diastolic blood pressure, pulse rate, diabetes mellitus, dyslipidemia, chronic kidney disease, and serum uric acid. We also evaluated whether serum uric acid (hyperuricemia) provided an independent risk for developing hypertension. Results: The cumulative incidence of hypertension from prehypertension over 5 years was 25.3%, but there were no significant differences between women and men (24.4% vs 26.0%, p=0.28). The cumulative incidence of hypertension in subjects with hyperuricemia (n=726) was significantly higher than those without hyperuricemia (n=2,858) (30.7% vs 24.0%, p<0.001). After multivariable adjustments, the risk factors for developing hypertension from prehypertension were age (OR per 1 year increased: 1.023; 95% CI, 1.015-1.032), women (OR versus men: 1.595; 95% CI, 1.269-2.005), higher body mass index (OR per 1 kg/m 2 increased: 1.051; 95% CI 1.021-1.081), higher baseline systolic blood pressure (OR per 1 mmHg increased: 1.072; 95% CI, 1.055-1.089) and diastolic blood pressure (OR per 1 mmHg increased: 1.085; 95% CI, 1.065-1.106), and higher serum uric acid (OR pre 1 mg/dL increased: 1.149; 95% CI, 1.066-1.238), but not smoking and drinking habits, diabetes mellitus, dyslipidemia, and chronic kidney diseases. Conclusions: Increased serum uric acid is an independent risk factor for developing hypertension from prehypertension. Intervention studies are needed to clarify whether the treatments for hyperuricemia in prehypertensive subjects are useful.

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Uric acid levels are critical for non-alcoholic fatty liver disease

10.21203/rs.2.23270/v1 ◽

2020 ◽

Author(s):

Guanqun Chao ◽

Yue Zhu ◽

Lizheng Fang

Keyword(s):

Risk Factors ◽

Uric Acid ◽

Risk Factor ◽

Fatty Liver ◽

Serum Uric Acid ◽

Uric Acid Level ◽

Acid Level ◽

Serum Uric Acid Level ◽

Density Lipoprotein ◽

Diagnostic Threshold

Abstract Background: To clarify the risk factors associated with NAFLD and further clarify the correlation between uric acid level and NAFLD by analyzing the correlation between NAFLD and different metabolic factors.Methods: Datas were obtained from subjects who underwent health examination in the Health promotion centre of Sir Run Run Shaw hospital of Zhejiang University from January 2016 to December 2017.The diagnosis of NAFLD was according to the clinical diagnosis of the Guidelines.Statistical analyses were performed using R software.Results: 79492 subjects were analyzed. 56680(71.3%) participants did not have NAFLD, 22812(28.7%) participants had NAFLD. Male, age, BMI, high blood pressure, central obesity, high glycosylated hemoglobin, high serum uric acid, high triglyceride, high total cholesterol, high low density lipoprotein cholesterol (LDL-C), abnormal liver function were risk factors of NAFLD, however, low high-density lipoprotein cholesterol (HDL-C) level was another risk factor of NAFLD.OR value suggested serum uric acid was a robust risk factor for NAFLD in all subgroups.In male group, AUC was 0.656 (95%CI: 0.651-0.661), the optimal diagnostic threshold was 395.5 mol/L, the sensitivity was 61.9%, the specificity was 61.1%, and the yoden index was 0.23. In female group, AUC was 0.716 (95%CI: 0.708-0.724), the optimal diagnostic threshold was 294.5 mol/L, sensitivity was 67.7%, specificity was 64.5%, and the Jordan index was 0.32.Conclusions: Our study suggested that there was a close correlation between serum uric acid level and NAFLD.Uric acid levels was a key risk factor for NAFLD.The diagnosis of fatty liver in patients can be preliminarily determined by detecting uric acid level.Contributions to the literature：1. The purpose of this study was to clarify the risk factors associated with NAFLD and further clarify the correlation between uric acid level and NAFLD by analyzing the correlation between NAFLD and different metabolic factors in the physical examination population.2. There was a close correlation between serum uric acid level and NAFLD.Uric acid levels was a key risk factor for NAFLD.3. The diagnosis of fatty liver in patients can be preliminarily determined by detecting uric acid level.

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Risk factors for hypertensive crisis in children with acute glomerulonephritis

Paediatrica Indonesiana ◽

10.14238/pi56.2.2016.101-6 ◽

2016 ◽

Vol 56 (2) ◽

pp. 101

Author(s):

Sherly Yuniarchan ◽

Risky Vitria Prasetyo ◽

Ninik Asmaningsih Soemyarso ◽

Mohammad Sjaifullah Noer

Keyword(s):

Risk Factors ◽

Logistic Regression ◽

Risk Factor ◽

Pediatric Population ◽

Hypertensive Crisis ◽

Significant Risk ◽

Significant Risk Factor ◽

P Value ◽

Acute Glomerulonephritis ◽

Female Ratio

Background Hypertensive crisis occurs in 1-4% of the hypertensive pediatric population, mostly due to acute glomerulonephritis (AGN). Some factors have been suggested to affect blood pressure (BP) in children, such as age, sex, race/ethnicity, obesity, and socioeconomic status, but little is known for risk factors for hypertensive crisis in AGN.Objective To analyze the risk factors for hypertensive crisis in children with AGN.Methods Retrospectively, we studied possible risk factors for hypertensive crisis in children with AGN at Dr. Soetomo Hospital from 2007 to 2011. Hypertensive crisis was defined as systolic BP ≥180 mmHg or diastolic BP ≥120 mmHg (for children ≥ 6 years of age); and systolic and/or diastolic BP >50% above the 95th percentile (for children aged <6 years). We evaluated the demographic and clinical characteristics as potential risk factors. Statistical analysis was done with Chi-square, Fisher’s exact, and logistic regression tests. Variables with P <0.25 in the univariable analysis were further analyzed by the multivariable logistic regression model. A P value of < 0.05 was considered statistically significant.Results There were 101 children included (mean age 9.7 (SD 2.17) years), with a male-to-female ratio of 2.7:1. Hypertensive crisis occurred in 42 (41.6%) children, of whom 8 had hypertensive urgency and 34 had hypertensive emergency. Proteinuria was seen in 53 children with AGN (52.5%) and was the significant risk factor for hypertensive crisis in our subjects (OR=2.75; 95%CI 1.16 to 6.52; P=0.021). Gender, clinical profiles, ethnicity, nutritional status, blood urea nitrogen (BUN), and glomerular filtration rate (GFR) were not significant risk factors for hypertensive crisis.Conclusion Proteinuria is the significant risk factor for hypertensive crisis in children with AGN.

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