A New Prognostic Index for Waldenström Macroglobulinemia Based on a Multicenter Retrospective Study of the Japanese Society of Myeloma

Abstract Background: We recently reported that the International Prognostic Scoring System for Waldenström macroglobulinemia (ISSWM), which is widely used to predict the prognosis of WM patients, might not be applicable to Japanese patients, and evidence of pleural effusion might be a novel adverse prognostic factor for symptomatic WM in the rituximab era. Further studies with a large number of patients are deemed to be conducted. Methods: We retrospectively analyzed the clinical data of 498 patients with WM diagnosed between January 2001 and December 2015 from 44 institutes involved with the Japanese Society of Myeloma. The overall survival (OS) was analyzed using Kaplan-Meier methods and compared using log-rank test. Several clinical characteristics at the diagnosis were assessed by Cox regression for univariate and multivariate analyses of the OS. Results: We included 420 cases diagnosed with symptomatic (n=314) and asymptomatic WM (n=106) in accordance with the classification of the Second International Workshop on WM. The median age at the diagnosis was 69 (range, 32-91) years, with 75.5% male, and 16.0% had an Eastern Cooperative Oncology Group performance status (ECOG PS) of 2-4. Oral alkylating agents, purine analogs, cyclophosphamide, doxorubicin, vincristine and prednisolone (CHOP) or CHOP-like regimens ± rituximab, rituximab monotherapy, or dexamethasone, rituximab and cyclophosphamide (DRC) were mainly administered as initial treatment. Rituximab-containing therapy was administered in 76.8% of all patients. The median follow-up was 45 months. The 5-year OS rate for all patients was 77.9%, while the rates for those with symptomatic and asymptomatic WM were 72.9% and 92.2%, respectively. Significant differences in the survival were seen between risk groups of ISSWM in symptomatic WM patients (5-year OS: high, 55.4%; intermediate, 81.2%; low, 90.2%; p<0.0001) (Figure 1). A univariate analysis showed that age >65 years, platelet count ≤10×104/µL, serum β2-microglobulin (β2-MG) >3 mg/L, ECOG PS 2-4, abnormal karyotype, pleural involvement, WBC <4000/µL, amyloidosis, fluid retention, pleural effusion, ascites, serum albumin ≤3.5 g/dL, serum creatinine >1.5 mg/dL, CRP >2.0 mg/dL and sIL-2R >4000 U/mL were significant adverse prognostic factors for the OS. A multivariate analysis revealed that a platelet count ≤10×104/µL (hazard ratio [HR] 5.942; 95% confidence interval [CI] 2.265-14.761), serum β2-MG >3 mg/L (HR 2.748; 95% CI 1.091-7.655), ECOG PS 2-4 (HR 2.899; 95% CI 1.219-6.290), and pleural involvement (HR 11.066; 95% CI 3.672-29.829) were adverse independent risk factors for symptomatic WM. We constructed a prognostic model by combining these prognostic variables as follows: patients with good risk (n=219), no adverse factors or only serum β2-MG >3 mg/L or ECOG PS 2-4; patients with poor risk (n=81), ≥1 adverse factors with a platelet count ≤10×104/µL, pleural involvement, or both serum β2-MG >3 mg/L and ECOG PS 2-4. The 5-year OS rates were 82.3% for good risk and 44.4% for poor risk, and this prognostic model significantly stratified symptomatic WM patients separately by the survival (p<0.0001) (Figure 2). The survival of patients with both poor risk in our model and high risk in ISSWM were extremely poor (5-year OS: poor and high [n=57], 24.7%; poor and intermediate [n=14], 80.0%; poor and low [n=2], not available; p=0.0031). In contrast, no significant differences were observed for the survival for the ISSWM risk groups in patients with good risk in our model (5-year OS: good and high [n=69], 76.0%; good and intermediate [n=83], 81.6%; good and low [n=42], 89.5%; p=0.2045). Conclusion: Although ISSWM may be useful for survival risk stratification in Japanese patients, we found that intermediate- and high-risk patients seemed to have a better prognosis than those in Western studies in the rituximab era (Dimopoulos MA, et al. Haematologica. 2008; 93: 1420-22). Thrombocytopenia and pleural involvement were found to be strong adverse prognostic factors in symptomatic WM, and our new prognostic index including them was easy to use in daily clinical practice and superior to ISSWM for detecting high-risk patients. Further studies are warranted to validate our prognostic index, especially in the era of novel agents. Disclosures Yamamoto: Bristol-Myers Squibb: Honoraria. Hagiwara:Celgene: Membership on an entity's Board of Directors or advisory committees; Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees. Sunami:Celgene: Honoraria, Research Funding; Sanofi: Research Funding; Janssen: Research Funding; Daiichi-Sankyo: Research Funding; Ono: Honoraria, Research Funding; Bristol-Myers Squibb K.K.: Honoraria, Research Funding; AbbVie: Research Funding; Takeda: Research Funding; MSD: Research Funding; GlaxoSmithKline: Research Funding; Novartis: Research Funding. Kurokawa:Teijin Pharma: Research Funding; Eizai: Research Funding; Kyowa Hakko Kirin: Honoraria, Research Funding; Chugai Pharmaceutical: Research Funding; Sumitomo Dainippon Pharma: Research Funding; Pfizer: Research Funding; Takeda Pharmaceutical: Research Funding; MSD: Honoraria, Research Funding; Ono Pharmaceutical: Honoraria, Research Funding; Nippon Sinyaku: Honoraria, Research Funding; Astellas Pharma: Research Funding; Otsuka Pharmaceutical: Research Funding. Takamatsu:Janssen: Honoraria; Celgene: Honoraria, Research Funding; Bristol-Myers Squibb: Research Funding; Ono: Research Funding. Ito:Bristol-Myers Squibb, Celgene: Honoraria. Tamura:Bristol-Myers Squibb: Honoraria; Celgene: Honoraria, Research Funding; Ono Pharmaceutical: Honoraria; Takeda Pharmaceutical: Honoraria.

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Possibility of a Risk-Adapted Treatment Strategy for Untreated Aggressive Adult T-Cell Leukemia-Lymphoma (ATL) Based on the ATL Prognostic Index: A Supplementary Analysis of the JCOG9801 Study

Blood ◽

10.1182/blood-2018-99-112734 ◽

2018 ◽

Vol 132 (Supplement 1) ◽

pp. 1645-1645

Author(s):

Kosuke Toyoda ◽

Kunihiro Tsukasaki ◽

Ryunosuke Machida ◽

Tomohiro Kadota ◽

Takuya Fukushima ◽

...

Keyword(s):

High Risk ◽

Research Funding ◽

Risk Group ◽

Prognostic Index ◽

Risk Groups ◽

Low Risk ◽

Intermediate Risk ◽

Adult T Cell Leukemia ◽

Ann Arbor ◽

Ecog Ps

Abstract Introduction The JCOG9801 study, a randomized phase III trial of the Japan Clinical Oncology Group (JCOG), compared CHOP every two weeks (CHOP-14) with VCAP-AMP-VECP (mLSG15) for patients with untreated aggressive adult T-cell leukemia-lymphoma (ATL) [J Clin Oncol 2007;25:5458-64]. Based on a higher complete response (CR) rate and marginally better overall survival (OS), we concluded that mLSG15 could be a sufficiently effective regimen at the expense of higher toxicity profiles. However, there was an insufficient mLSG15 effect among patients with an Eastern Cooperative Oncology Group performance status (ECOG PS) of 0 or those aged ≥56 years, suggesting that mLSG15 is not always a definitive treatment for all patients with aggressive ATL. Thus, identifying patients who should receive mLSG15 is essential. We aimed to conduct a supplementary analysis of patients enrolled in the JCOG9801 study using the ATL prognostic index (ATL-PI) that has been recently advocated for acute- and lymphoma-types of ATL [J Clin Oncol 2012;30:1635-40]. Methods We adopted the "age-adjusted" ATL-PI that was established for ATL patients aged ≤70 years as patients aged between 15 and 69 years were eligible in the JCOG9801 study. Having eliminated "age", this index comprised 4 factors, namely Ann Arbor stage (III or IV), ECOG PS (>1), serum albumin (<3.5 g/dL), and soluble interleukin-2 receptor (sIL-2R; >20,000 U/mL). We excluded patients lacking any factors of the age-adjusted ATL-PI and those with unfavorable chronic type based on the age-adjusted ATL-PI model from patients enrolled in JCOG9801. Subsequently, we categorized the remaining patients into three groups, namely low, intermediate, and high risk, and compared mLSG15 and CHOP-14 in terms of OS, treatment CR rate, and toxicity in each risk group. Results Of 118 enrolled JCOG9801 patients, we included 105 patients in this supplementary analysis based on the above criteria, of which 51 and 54 were treated with mLSG15 and CHOP-14, respectively. According to the age-adjusted ATL-PI, these patients were classified as follows: low (n=44, 41.9%), intermediate (n=54, 51.4%), and high (n=7, 6.7%) risks. Regarding patient characteristics, between the two treatment arms, there were no remarkable differences in age, sex, ECOG PS, ATL subtypes, Ann Arbor stage, presence of B symptoms, presence of bulky mass (≥5 cm), and serum albumin, serum calcium, and sIL-2R levels. The mLSG15 arm included 21 (41.2%), 25 (49.0%), and 5 (9.8%) patients in the low-, intermediate-, and high-risk groups, respectively, whereas the CHOP-14 arm included 23 (42.6%), 29 (53.7%), and 2 (3.7%) patients, respectively. We excluded the high-risk group from our analysis due to the small number of patients. mLSG15 did not show any superior trend for OS compared to CHOP-14 in the low-risk group (hazard ratio [HR]: 0.957; 95% confidence interval [CI]: 0.491-1.868) (Figure A). In contrast, in the intermediate-risk group, better prognosis for OS was observed with mLSG15 (HR: 1.538; 95% CI: 0.841-2.811) than with CHOP-14 (Figure B). Similarly, the CR rate, including the unconfirmed CR rate, did not differ between both arms of the low-risk group (mLSG15 vs. CHOP-14, 47.6% vs. 43.5%), while in the intermediate-risk group, mLSG15 showed a higher CR rate than CHOP-14 (44.0% vs. 13.8%). Regarding toxicity profiles, grade 4 thrombocytopenia was more frequently observed in the mLSG15 arm of both risk groups than in the CHOP-14 arm (66.7% vs. 4.5% in the low-risk group; 68.0% vs. 24.1% in the intermediate-risk group only). There was a higher incidence of grade 4 neutropenia in the mLSG15 arm than in the CHOP-14 arm (100.0% vs. 75.9%) only in the intermediate-risk group. All three treatment-related deaths were documented in the mLSG15 arm of the intermediate-risk group. Conclusions Given the very poor prognosis of ATL, our findings suggest that despite higher toxicities, mLSG15 is more suitable for the intermediate-risk group of age-adjusted ATL-PI, whereas its benefits appear modest in the low-risk group. This supplementary analysis is exploratory; therefore, a further prospective study of aggressive ATL is necessary to confirm these results. Disclosures Tsukasaki: Daiich-Sankyo: Consultancy; Ono Pharma: Consultancy; HUYA: Consultancy, Research Funding; Chugai Pharma: Honoraria, Research Funding; Eisai: Research Funding; Celgene: Honoraria; Mundy Pharma: Honoraria; Kyowa-hakko/Kirin: Honoraria; Seattle Genetics: Research Funding. Fukushima:NEC corporation: Research Funding. Maruyama:Bristol-Myers Squibb: Honoraria; Solasia Pharma: Research Funding; Pfizer: Research Funding; Nippon Boehringer Ingelheim: Research Funding; Novartis: Research Funding; Otsuka: Research Funding; Astellas Pharma: Research Funding; Abbvie: Research Funding; Mundipharma International: Honoraria, Research Funding; Takeda: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; Eisai: Honoraria, Research Funding; Biomedis International: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; Kyowa Hakko Kirin: Honoraria, Research Funding; Fujifilm: Honoraria, Research Funding; Ono Pharmaceutical: Honoraria, Research Funding; MSD: Honoraria, Research Funding; Chugai Pharma: Honoraria, Research Funding; Dai-ichi-Sankyo: Honoraria; Dai-Nippon-Sumitomo: Honoraria; Asahi Kasei Pharma: Honoraria; AstraZeneca: Research Funding; Amgen Astellas BioPharma: Research Funding; Zenyaku Kogyo: Honoraria, Research Funding; GlaxoSmithKline: Research Funding. Nagai:SymBio Pharmaceuticals Limited: Research Funding; Otsuka Pharmaceutical Co., Ltd.: Research Funding; Kyowa Hakko Kirin Co., Ltd.: Honoraria, Research Funding; Janssen Pharmaceutical K.K.: Honoraria, Research Funding; Chugai Pharmaceutical Co., Ltd.: Honoraria, Research Funding; Solasia Pharma K.K.: Research Funding; Bristol-Myers Squibb: Honoraria, Research Funding; Bayer Yakuhin Ltd.: Research Funding; Abbvie G. K.: Research Funding; Celgene Corporation: Honoraria, Research Funding; Takeda Pharmaceutical Co., Ltd.: Honoraria, Research Funding; AstraZeneca plc.: Research Funding; Roche Ltd.: Honoraria; Esai Co., Ltd.: Honoraria, Research Funding; HUYA Bioscience International: Research Funding; Ono Pharmaceutical Co., Ltd.: Honoraria, Research Funding; Sanofi K. K.: Honoraria; Zenyaku Kogyo Co., Ltd.: Honoraria, Research Funding; Mundipharma K.K.: Honoraria, Research Funding; Gilead Sciences Inc.: Honoraria, Research Funding.

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The Absolute Monocyte and Lymphocyte Counts at Diagnosis Predict Survival and Identify High-Risk Patients In Diffuse Large-B-Cell Lymphoma

Blood ◽

10.1182/blood.v116.21.3088.3088 ◽

2010 ◽

Vol 116 (21) ◽

pp. 3088-3088

Author(s):

Ryan A. Wilcox ◽

Kay Ristow ◽

Thomas M. Habermann ◽

David James Inwards ◽

Ivana Micallef ◽

...

Keyword(s):

Overall Survival ◽

High Risk ◽

Confidence Interval ◽

Prognostic Index ◽

B Cell Lymphoma ◽

Hazard Ratio ◽

Poor Risk ◽

Large B Cell Lymphoma ◽

Risk Patients ◽

Good Risk

Abstract Abstract 3088 Background: Despite the use of modern immunochemotherapy (R-CHOP) regimens, almost 50% of patients with diffuse large-B-cell lymphoma (DLBCL) will relapse. Current prognostic models, most notably the International Prognostic Index, are comprised of patient and tumor characteristics and are unable to identify patients with less than a 50% chance of long-term survival. However, recent observations demonstrate that factors related to host adaptive immunity and the tumor microenvironment are powerful prognostic variables in non-Hodgkin lymphoma Methods: We retrospectively examined the absolute neutrophil count (ANC), monocyte count (AMC) and lymphocyte count (ALC), obtained from an automated complete blood count with differential, as prognostic variables in a cohort of 255 consecutive DLBCL patients that were uniformly treated with R-CHOP between 2000 and 2007 at a single institution. The primary study objective was to assess if ANC, AMC, and ALC at diagnosis were predictors of overall survival (OS) in DLBCL. Results: At diagnosis, the median ANC was 4720/uL (range 1190–17690), the median AMC was 610/uL (range 30–4040), and the median ALC was 1220/uL (range 140–5410). The median follow-up for these patients was 48 months. In the univariate analysis, each of these variables predicted OS as continuous variables. As dichotomized variables, an elevated ANC (≥5500/μL; hazard ratio 1.75, 95% confidence interval 1.14–2.60, p=0.01) and AMC (≥610/μL; hazard ratio 3.36, 95% confidence interval 2.10–5.59, p<0.0001) were each associated with inferior OS. In contrast, the presence of lymphopenia, defined as an ALC ≤1000/uL, was associated with inferior OS (hazard ratio 2.21, 95% confidence interval 1.43–3.39, p=0.0004). When components of the IPI were included on multivariate analysis only the AMC and ALC were independently significant prognostic factors for OS, with hazard ratios of 3.37 (95% confidence interval 2.05–5.74, p<0.0001) and 2.19 (95% confidence interval 1.38–3.44, p=0.0009), respectively. The dichotomized AMC and ALC generated the AMC/ALC prognostic index (PI) and stratified patients into 3 risk groups: very good (AMC <610/uL and ALC >1000/uL), good (AMC ≥610/uL or ALC ≤1000/uL), and poor-risk (AMC ≥610/uL and ALC ≤1000/uL) populations. For both the very good (n=79) and good-risk (n=134) groups median OS has not been reached with estimated 5-year overall survival of 88% and 69%, respectively. Median OS for poor-risk (n=42) patients was 1.7 years (95% confidence interval 1.1–2.7 years) with an estimated 5-year overall survival of 28% (p<0.0001). By comparison, the R-IPI was unable to identify a group of patients with a median survival less than 8 years. The estimated 5-year OS was 93%, 71% and 53% for very good, good and poor-risk patients, respectively. We sought to determine whether the AMC/ALC PI may provide additional prognostic information when combined with the R-IPI. To test this possibility, the 171 very good/good risk and 84 poor risk patients identified by the R-IPI were subsequently risk stratified using the AMC/ALC PI. Among R-IPI very good/good risk patients a subset of poor risk patients (n=21) with a median OS of 2.2 years (95% confidence interval 1.1–6.6 years) and 35% 5-year OS could be identified with the AMC/ALC PI. In contrast, 5-year OS ranged from 75%-88% among very good and good risk patients. Similarly, stratification of R-IPI poor risk patients by the AMC/ALC PI identified subsets of very good (n=19) and good risk (n=44) patients with median OS that had not been reached and 86% and 55% 5-year OS, respectively. High risk (n=21) patients had a median OS of 1.4 years (95% confidence interval 0.9–2.2 years) and an estimated 5-year OS of less than 25%. Conclusions: Measurement of AMC and ALC at diagnosis is widely applicable, cost effective, predicts OS, and identifies high-risk patients with DLBCL. Disclosures: No relevant conflicts of interest to declare.

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55例血管免疫母细胞性T细胞淋巴瘤的临床特征和预后模型

Blood ◽

10.1182/blood-2020-141699 ◽

2020 ◽

Vol 136 (Supplement 1) ◽

pp. 37-38

Author(s):

Xiaohong Tan ◽

Jie Sun ◽

Sha He ◽

Chao Rong ◽

Hong Cen

Keyword(s):

High Risk ◽

Prognostic Model ◽

Risk Group ◽

Prognostic Index ◽

Risk Groups ◽

High Risk Group ◽

Low Risk ◽

Intermediate Risk ◽

Ecog Ps ◽

Medical University

Angioimmunoblastic T-cell lymphoma (AITL) is a distinct subtype of peripheral T-cell lymphoma with unique clinical and pathological features. This study aim to analyze the characteristics of AITL and to design a prognostic model specifically for AITL, providing risk stratification in affected patients. We retrospectively analyzed 55 newly diagnosed AITL patients at the Affiliated Tumor Hospital of Guangxi Medical University from January 2007 to June 2016 and was permitted by the Ethics Committee of the Affiliated Tumor Hospital of Guangxi Medical University. Among these patients, the median age at diagnosis was 61 (27-85) and 54.55% (30/55) of the patients were older than 60 years. 43 patients were male, accounting for 78.18% of the whole. Among these, 92.73% (51/55) of the diagnoses were estimated at advanced stage. A total of 20 (36.36%) patients were scored >1 by the ECOG performance status. Systemic B symptoms were described in 16 (29.09%) patients. In nearly half of the patients (27/55; 49.09%) had extranodal involved sites. The most common extranodal site involved was BM (11/55; 20.00%). 38.18% (21/55) and 27.27% (15/55) patients had fever with body temperature ≥37.4℃ and pneumonia, respectively. 40% (22/55) patients had cavity effusion or edema. Laboratory investigations showed the presence of anemia (hemoglobin <120 g/L) in 60% (33/55), thrombocytopenia (platelet counts <150×109/L) in 29.09% (16/55), and elevated serum LDH level in 85.45% (47/55) of patients. Serum C-reactive protein and β2-microglobulin levels were found to be elevated in 60.98% (25/41) and 75.00% (36/48)of the patients, respectively. All patients had complete information for stratification into 4 risk subgroups by IPI score, in which scores of 0-1 point were low risk (9/55;16.36%), two points were low-intermediate risk (17/55; 30.92%), three points were high-intermediate risk (20/55; 36.36%), and four to five points were high risk (9/55; 16.36%). 55 patients were stratified by PIT score with 7.27% (4/55) of patients classified as low risk, 32.73% (18/55) as low-intermediate risk, 34.55% (19/55) as high-intermediate risk, and 25.45% (14/55) as high risk depending on the numbers of adverse prognostic factors.The estimated two-year and five-year overall survival (OS) rate for all patients were 50.50% and 21.70%. Univariate analysis suggested that ECOG PS (p= 0.000), Systemic B symptoms (p= 0.006), fever with body temperature ≥ 37.4℃ (p= 0.000), pneumonia (p= 0.001), cavity effusion or edema (p= 0.000), anemia (p= 0.013), and serum LDH (p= 0.007) might be prognostic factors (p< 0.05) for OS. Multivariate analysis found prognostic factors for OS were ECOG PS (p= 0.026), pneumonia (p= 0.045), and cavity effusion or edema(p= 0.003). We categorized three risk groups: low-risk group, no adverse factor; intermediate-risk group, one factor; and high-risk group, two or three factors. Five-year OS was 41.8% for low-risk group, 15.2% for intermediate-risk group, and 0.0% for high-risk group (p< 0.000). Patients with AITL had a poor outcome. This novel prognostic model balanced the distribution of patients into different risk groups with better predictive discrimination as compared to the International Prognostic Index and Prognostic Index for PTCL. Disclosures No relevant conflicts of interest to declare.

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Somatic Mutations Improve Risk Classification By Cytogenetic Abnormalities in Patients with Myelodysplastic Syndrome after Hematopoietic Stem Cell Transplantation

Blood ◽

10.1182/blood-2019-125937 ◽

2019 ◽

Vol 134 (Supplement_1) ◽

pp. 512-512

Author(s):

Fevzi F. Yalniz ◽

Rima M. Saliba ◽

Orhan K. Yucel ◽

Guillermo Garcia-Manero ◽

Jeremy Ramdial ◽

...

Keyword(s):

High Risk ◽

Disease Progression ◽

Board Of Directors ◽

Research Funding ◽

Risk Groups ◽

Advisory Committees ◽

Hematopoietic Stem ◽

Ras Pathway ◽

Cart Analysis ◽

Poor Risk

Background: Hematopoietic stem cell transplantation (HSCT) offers potentially curative therapy for patients with myelodysplastic syndrome (MDS) but disease progression after HSCT remains a major reason for failure after transplant. Identification of risk factors for progression of MDS after HSCT would allow to identify target population for early initiation of preventive treatments to improve outcomes. Methods: Patients with a diagnosis of MDS who received first HSCT between 2013 and 2018 with available pre-transplant genetic profile obtained from next generation sequencing of genes were included for the retrospective analysis. Cytogenetic findings were categorized by the revised International Prognostic Scoring System (R-IPSS). Primary outcome of interest was risk of disease progression. Classification and regression tree (CART) analysis was performed to evaluate independent predictors on multivariate analysis using standard methods. Results: Of 378 MDS patients transplanted within the study period, 225 were eligible to be included in this analyses. As shown in the table 1, the study cohort was high risk; cytogenetic risk groups were very-poor and poor in 50 (23%) and 32 (15%) patients, respectively. At least one pathogenic mutation was identified in 215 (91%) of patients prior to transplant. Most frequently mutated genes included, TP53 (24%, 54/225), RAS pathway genes (NRAS, KRAS, FLT3, PTPN11 and KIT) (20%, 44/225), TET2 (16%, 37/172), ASXL1 (12%, 27/172) and DNMT3A (11%, 25/200). In our cohort, patients with very-poor cytogenetics had a high frequency of TP53 mutations (73%), and TP53 mutations occurred almost exclusively in patients with very-poor cytogenetics (76% v 7%; P < .001). That makes those two groups almost inseparable from each other. The median follow-up in 121 (54%) survivors was 24 months (range, 1.8 to 74 months). Of the 225 patients, 65 (29%) had disease progression after HSCT, with a median of 154 days to progression (range, 28 to 1196). By univariate analyses, presence of TP53 (HR, 3.2; CI, 1.9-5.4; P<.001), DNMT3A (HR, 2.6; CI, 1.5-4.7; P=.001), RAS pathway mutations (HR, 2.01; CI, 1.2-3.4; P=.01), therapy related MDS (HR, 2.05; CI, 1.2-3.5; P=.008), very poor risk cytogenetics (HR, 3.4; CI, 1.9-6.3; P<.002), and use of post-transplant cyclophosphamide (PTCy) (HR, 0.5; CI, 0.3-0.96; P=.003) were significant predictors of progression rate. As previously mentioned, we used CART analysis to evaluate independent predictors of progression. The results demonstrated that given the significant overlap with TP53 and very poor cytogenetics, when both variables were forced into the model, only very poor cytogenetics remained significant for progression. Based on CART analysis, 4 mutually exclusive risk groups for progression were identified (Figure 1): high risk (very poor risk cytogenetics or DNMT3Amut), intermediate risk (good, intermediate or poor risk cytogenetics/RAS-pathmut/DNMT3Awt), low risk (poor risk cytogenetics/RAS-pathwt /DNMT3Awt) and a very low risk group (very good, good or intermediate risk cytogenetics/RAS-pathwt /DNMT3Awt). The correlation between R-IPSS based cytogenetic risk and our identified risk groups is shown in table 2. This illustrates how the addition of molecular data upstaged 25% of the patients to a higher risk category as well as downstaged 23% of the patients to a lower risk category for disease progression when compared to the original R-IPSS classification. The cumulative incidence of disease progression at 2 years was 6% (reference), 26% (P=.005), 42% (P<.001) and 56% (P<.001) in very-low, low, intermediate and high risk groups, respectively (Figure 2). Within the risk groups identified, progression incidence was comparable by conditioning intensity and the use of PTCy. The actuarial 2-year progression-free survival for the defined 4 risk groups was, 69% (reference), 48% (HR, 2; P=.04), 38% (HR, 2.2; P=.009), 22% (HR, 3.2; P<.001) and 14% (HR, 4.8; P<.001), in very-low, low, intermediate and high-risk groups, respectively. Non-relapse mortality was similar across the identified risk groups. Conclusion: The proposed model, by incorporating DNMT3A and RAS pathway molecular mutation status to cytogenetic risk per R-IPSS, improves upon the classification of risk groups and enables the physician to better risk stratify and predict likelihood of progression after transplantation. Disclosures Garcia-Manero: Amphivena: Consultancy, Research Funding; Helsinn: Research Funding; Novartis: Research Funding; AbbVie: Research Funding; Celgene: Consultancy, Research Funding; Astex: Consultancy, Research Funding; Onconova: Research Funding; H3 Biomedicine: Research Funding; Merck: Research Funding. Popat:Bayer: Research Funding; Incyte: Research Funding; Jazz: Consultancy. Ciurea:Kiadis Pharma: Membership on an entity's Board of Directors or advisory committees, Other: stock holder; Spectrum: Membership on an entity's Board of Directors or advisory committees; Miltenyi: Research Funding; MolMed: Membership on an entity's Board of Directors or advisory committees. Kebriaei:Jazz: Consultancy; Pfizer: Honoraria; Kite: Honoraria; Amgen: Research Funding. Bashir:Imbrium: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees; Spectrum: Membership on an entity's Board of Directors or advisory committees; Kite: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; StemLine: Research Funding; Acrotech: Research Funding; Celgene: Research Funding. Champlin:Actinium: Consultancy; Johnson and Johnson: Consultancy; Sanofi-Genzyme: Research Funding. Oran:Astex pharmaceuticals: Research Funding; AROG pharmaceuticals: Research Funding.

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Inclusion of Patient's Self-Reported Fatigue into a Standard Laboratory Risk Classification Enhances Survival Prediction in Patients with Advanced Myelodysplastic Syndromes

Blood ◽

10.1182/blood.v128.22.1242.1242 ◽

2016 ◽

Vol 128 (22) ◽

pp. 1242-1242

Author(s):

Fabio Efficace ◽

Pasquale Niscola ◽

Francesco Cottone ◽

Gianluca Gaidano ◽

Amelie Anota ◽

...

Keyword(s):

High Risk ◽

Research Funding ◽

Prognostic Index ◽

Risk Groups ◽

Sensitivity Analyses ◽

Favorable Prognosis ◽

High Fatigue ◽

Eortc Qlq C30 ◽

Eortc Qlq

Abstract BACKGROUND: Patients with higher risk myelodysplastic syndromes (MDS) according to the International Prognostic Scoring System (IPSS) have poor life expectancy making accurate prediction of overall survival (OS) a critical issue for optimal and personalized patients' management. PURPOSE: The primary objective of this study was to develop a patient-based prognostic index for higher risk-disease, that would include self-reported fatigue into the widely used IPSS classification. A secondary objective was to examine whether this patient-based index would provide more accurate OS prediction than the standard IPSS classification. PATIENTS AND METHODS: Analysis is based on 280 newly diagnosed patients with MDS classified with an intermediate-2 or high-risk score (i.e., higher-risk) according to the IPSS. Patients were recruited in an international prospective cohort observational study involving 37 centers. OS was defined as the date of diagnosis of IPSS intermediate-2 or high risk MDS up to death for any cause. Patients were censored at the date of last follow up if not dead at the time of analysis. Before treatment start, all patients completed the EORTC QLQ-C30 questionnaire and the fatigue scale was a priori selected for possible inclusion into the IPSS. Among all observed values of the fatigue score (range: 0-100) we looked for a threshold defining four risk groups, formed by patients reporting either low or high fatigue respectively in intermediate-2 and high risk IPSS groups. The final prognostic index was developed based on univariate and multivariate Cox models. Differences among Kaplan-Meier OS estimation of new risk categories were assessed by log-rank test. Sensitivity analyses were performed, 1) assessing differences in patients' baseline characteristics among risk groups, by Kruskal-Wallis and Fisher's exact tests 2) accounting for several potential confounding factors (baseline and time-dependent) in a multivariate extended Cox model, including treatment received after baseline assessment and further evolution into acute myeloid leukemia, 3) performing a bootstrap resampling procedure to internally validate the final prognostic index. Discrimination and calibration of the new index were evaluated. For all analyses, α=0.05. RESULTS: With a median follow- up of 15 months (IQR 8-27) we observed 113 deaths. The median OS of the overall population was 17 months (95% CI, 15-19). The majority of patients (N=165, 59%) received treatment with hypomethylating agents. The final cut-off value selected for the EORTC QLQ-C30 fatigue scale was 45 points discriminating between patients with low (<45 points) or high fatigue (≥45 points). A new risk score classification was then developed, namely, the Fatigue(FA)-IPSS(h), enabling to distinguish three risk group categories (i.e., risk-1, risk-2 and risk-3) in contrast to the two categories of the IPSS (intemediate-2 and high-risk). Patients with the most favorable prognosis according to the FA-IPSS(h) (i.e., risk-1) had a median OS of 23 months (95% CI, 19-29), those with risk-2 had a median survival of 16 months (95% CI, 12-17) and those with the least favorable prognosis (risk-3) had median OS of 10 months (95% CI, 4-13). In contrast, median OS was 20 months (95% CI, 17-24 months) and 13 months (95% CI, 9-16 months) for patients with an IPSS intermediate-2 and high risk scores, respectively. Survival rates at 6 months, one and two years were markedly different amongst the three groups of the FA-IPSS(h). For example, one-year OS for patients with the most favorable prognosis (risk-1) was 80.2% (95% CI, 73.4-87.8) and only 37.5% (95% CI, 23.8-59.1) for those with the poorest prognosis (risk-3). Sensitivity analyses supported our findings. The FA-IPSS(h) index showed very good predictive performance (bootstrap-corrected c-index=0.911). CONCLUSION: The FA-IPSS(h) is a new prognostic index that integrates patient's self-reported fatigue into the well established IPSS index. Its use might enhance physicians' ability to more accurately predict OS in higher-risk MDS. Also, implementation of this index into standard practice might have important implications to elicit a more active patient participation during initial consultations. Disclosures Efficace: Seattle Genetics: Consultancy; Bristol Myers Squibb: Consultancy; TEVA: Consultancy, Research Funding; Lundbeck: Research Funding. Gaidano:Gilead: Consultancy, Honoraria, Speakers Bureau; Janssen: Consultancy, Honoraria, Speakers Bureau; Novartis: Consultancy, Honoraria, Speakers Bureau; Karyopharm: Consultancy, Honoraria; Roche: Consultancy, Honoraria, Speakers Bureau; Morphosys: Consultancy, Honoraria. Bonnetain:Roche: Consultancy, Honoraria, Research Funding; Novartis: Consultancy, Honoraria, Research Funding; Celgène: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Ipsen: Consultancy, Honoraria; Integragen: Consultancy, Honoraria; Nestle: Consultancy, Honoraria; BMS: Consultancy, Honoraria; Chugai: Consultancy, Honoraria; Merck Serono: Consultancy, Honoraria; Bayer: Consultancy, Honoraria. Fianchi:Novartis: Honoraria; Celgene: Honoraria; Janssen: Honoraria. Breccia:Novartis: Consultancy, Honoraria; Celgene: Honoraria; Bristol Myers Squibb: Honoraria; Ariad: Honoraria; Pfizer: Honoraria. Platzbecker:Celgene Corporation: Honoraria, Research Funding; Janssen-Cilag: Honoraria, Research Funding; Novartis: Honoraria, Research Funding; Amgen: Honoraria, Research Funding; TEVA Pharmaceutical Industries: Honoraria, Research Funding.

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Germline Genetic Variation of ASXL1 and BIM Predicts Response to Imatinib and Identifies a Subset of High Sokal Risk Patients with the Greatest Risk of Treatment Failure and Disease Progression

Blood ◽

10.1182/blood.v126.23.475.475 ◽

2015 ◽

Vol 126 (23) ◽

pp. 475-475 ◽

Cited By ~ 2

Author(s):

Justine E Marum ◽

Leanne Purins ◽

David T Yeung ◽

Wendy Tara Parker ◽

David J Price ◽

...

Keyword(s):

Genetic Variation ◽

High Risk ◽

Board Of Directors ◽

Research Funding ◽

Risk Groups ◽

Front Line ◽

Advisory Committees ◽

Poor Risk ◽

Significant Difference ◽

Selection Of

Abstract Background: Scoring systems at CML diagnosis, such as Sokal risk, provide important response prediction for imatinib (IM) treated patients (pts). Specific treatment policies have been suggested for high risk pts to optimize otherwise inferior outcomes. However, responses among pts with high risk are heterogeneous and new biomarkers are required to facilitate rational selection of optimal therapy. Biological factors, such as germline genetic variation, may play a role in therapy response dynamics. We aimed to identify predictive biomarkers of response to IM at CML diagnosis to aid selection of front line therapy for optimal treatment outcomes. Methods: Targeted amplicon sequencing using a custom Ion AmpliSeq panel and the Ion Proton was performed for 35 genes: 10 BCL2 family genes involved in TKI initiated apoptosis (including BIM, BAD and BCL2); 5 drug metabolism genes; and 20 genes implicated in hematologic malignancies (including ASXL1 and TET2). Genotypes were determined for 200 candidate single nucleotide variants (SNPs) for 528 front line IM and 83 front line NIL treated pts. For the IM pts, baseline variables were assessed for association with outcome: Sokal risk, age, gender, assigned IM dose (400, 600 or 800 mg); and genotype. Results: SNPs significantly associated with outcome in univariate analyses were assessed in multivariate models with the other baseline variables. The Sokal risk, ASXL1 rs4911231 and BIM rs686952 SNPs were independent predictors of 12 mo MMR, 48 mo MR4, MR4.5 and failure free survival (FFS, loss of any response, death, progression to AP/BC). For the ASXL1 SNP, the homozygous T genotype (155/508 evaluable pts, 30%), and for the BIM SNP, the A allele (249/507 evaluable pts, 49%) were associated with superior outcomes. We explored the additive effect of combining the genotypes of the ASXL1 and BIM SNPs on outcome. Three risk groups were readily identified (defined in Fig): Good (16% of evaluable pts), Average (46%) and Poor (37%). There were significant differences in the cumulative incidence of 3 mo EMR, 12 mo MMR, and 48 mo MR4, MR4.5 and FFS, as stratified by these SNP risk groups in IM treated pts (Table and Fig A). No significant association was found for progression to AP/BC or survival for any baseline variable. To examine the predictive power of SNP genotype within the high Sokal risk group, high risk pts were stratified by SNP genotype group. Significant differences were observed for EMR, MMR, MR4, MR4.5 and FFS (Table and Figure B), demonstrating the ability of the SNP genotype within high Sokal risk pts to predict response. Moreover, high Sokal risk pts harboring a poor risk SNP genotype had a significantly higher risk of progression to AP/BC vs high Sokal risk pts with an average/good risk genotype, 12% vs 2% (P =.03). The impact of SNP genotype risk on achieving 12 mo MMR was examined in the 83 pts treated with frontline NIL (median 24 mo follow up). In contrast to the significant difference observed for IM pts, there was no significant difference for NIL pts: 75% vs 73% vs 64% for good, average and poor risk, respectively, P =.34, suggesting the poor risk conferred by genotype may be abrogated by more potent TKI. Conclusion: Our data suggest inherent genetic variation contributes to the heterogeneity of response to IM. An intronic SNP in BIM, a key initiator of TKI induced apoptosis, and a synonymous SNP in ASXL1 exon 12, a region commonly mutated in hematologic cancers, were strong biomarkers of IM response. The mechanism by which these SNPs affect response awaits further clinical and experimental evaluation. Among pts with high Sokal risk, the genotype of these 2 SNPs delineated response and identified a good risk subgroup where more potent TKI may not be required for optimal outcomes. Assessment of genetic variation at diagnosis may contribute to a prognostic score that will allow for optimization of therapy. Disclosures Yeung: Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: travel grant international meeting, Research Funding. Hughes:Bristol-Myers Squibb: Honoraria, Research Funding; ARIAD: Honoraria, Research Funding; Novartis: Honoraria, Research Funding. Branford:BMS: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Ariad: Research Funding; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Qiagen: Membership on an entity's Board of Directors or advisory committees.

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Serum Albumin and Peripheral Blood Lymphocyte/Monocyte Ratio at Diagnosis May Provide Additional Prognostic Information in R-IPI Good Risk Diffuse Large-B-Cell Lymphoma Patients Treated with R-CHOP

Blood ◽

10.1182/blood.v126.23.2658.2658 ◽

2015 ◽

Vol 126 (23) ◽

pp. 2658-2658 ◽

Cited By ~ 1

Author(s):

Branimir Spassov ◽

Donka Vassileva ◽

Georgi Michaylov ◽

Gueorgui Balatzenko ◽

Margarita Guenova

Keyword(s):

Risk Group ◽

Univariate Analysis ◽

Prognostic Significance ◽

Prognostic Index ◽

B Cell Lymphoma ◽

Risk Groups ◽

Prognostic Information ◽

Poor Risk ◽

Risk Patients ◽

Good Risk

Abstract Background and Aim: Diffuse large B-cell lymphoma (DLBCL) is the most common type of non-Hodgkin lymphoma. Currently, the standard of care in DLBCL patients (pts) is rituximab-CHOP immunochemotherapy (R-CHOP) and the prognostic stratification is performed by the Revised International Prognostic Index (R-IPI), identifying 3 distinct prognostic groups with a very good, good and poor outcome. A lot of new prognostic markers have been introduced into the clinical practice to perform better pts' stratification. Particular prognostic relevance has been attributed to serum albumin (SA), β2-microglobulin (B2M), peripheral blood lymphocyte/ monocyte ratio (LMR), neutrophil/lymphocyte ratio (NLR) etc. However the data of these prognostic factors across the different R-IPI prognostic groups are limited. Therefore, we decided to access whether SA, B2M, LMR and NLR were predictors of overallsurvival (OS) across the different R-IPI groups of R-CHOP treated DLBCL pts. Patients and Methods: We retrospectively reviewed the clinical outcome of 281 R-CHOP treated DLBCL pts with median age 58 years and 51.8 % male. According to the R-IPI score, the pts in very good, good and poor risk were 24.2%, 54.8% and 21%, respectively. Laboratory levels of albumin, absolute lymphocyte, monocyte and neutrophil count were recorded, and LMR and NLR - calculated. Serum B2M levels were measured by radioimmunoassay. A receiver operating characteristic (ROC) curve analysis was used to illustrate in our data set the best cut off values of SA, B2M, LMR and NLR to predict OS by Kaplan-Meier method. Univariate analysis to evaluate differences between variables was performed by the log rank. A multivariate analysis was performed by Cox proportional-hazards models. Results: The estimated 5-year OS was 87.1%, 74% and 31% for R-IPI very good, good and poor-risk patients, respectively. The median values of SA, B2M, LMR and NLR were 40.7 g/L, 2.9 mg/L, 2.95 and 2.86, respectively. Our data showed that on univariate analysis inferior OS was associated with decreased SA (≤39.4 g/L; 95% confidence interval (CI) 0.70-0.82, p=<0.001), elevated B2M (>2.6 mg/L; 95% CI 0.68-0.80, p=<0.001), reduced LMR (≤2.16; 95% CI 0.71-0.81, p=<0.001) and increased NLR (>2.61; 95% CI 0.66-0.77, p=<0.001), presented as dichotomized variables. On multivariate analysis the independent prognostic significance was confirmed only for SA and LMR, with hazard ratios of 0.23 (95% CI 0.11-0.49, p<0.001) and 0.41 (95% CI 0.21-0.81, p=0.011), respectively. Based on the dichotomized SA and LMR values a SA/LMR prognostic index (PI) was created stratifying patients into 3 risk groups: very good (SA >39.4 g/L and LMR >2.16; n=75), good (SA ≤39.4 g/L or LMR ≤2.16; n=52) and poor-risk (SA ≤39.4 g/L and LMR ≤2.16; n=41) populations. The estimated 5-year OS was 88.7% for very good, 51.7% for good, and 8.8% for poor SA/LMR PI group (p<0.001). Median OS for poor-risk patients was 1.1 years (95% CI 1.03-1.72 years) and not reached for both the very good and good-risk groups. We sought to determine whether the SA/LMR PI may provide additional prognostic information within the R-IPI risk groups. Due to low number of deaths - 4.4% (3/68), no statistics could be calculated in very good R-IPI risk group. Within the R-IPI good risk patients SA/LMR PI allowed us to discriminate 3 subgroups, characterized by significant differences in 3-year and median OS (Figure 1): a SA/LMR PI poor risk subgroup (n=18) with 10.4% 3-years OS and 1.13 years (95% CI 0.82-1.44 years) median OS; a SA/LMR PI good risk subgroup (n=32) with 59.5% 3-years OS and median not reached; and a SA/LMR PI very good risk subgroup (n=50) with not reached median OS and 91.3% 3-years OS comparable to the OS in R-IPI very good patients (p=0.229). Only SA retained its independent prognostic significance in R-IPI poor risk group. Conclusion: SA and LMR are independent prognostic markers to predict survival in DLBCL pts. Adding these variables to prognostic models such as the R-IPI score might improve their predictive ability, providing particularly relevant information within the R-IPI good risk group. A subgroup of R-IPI good risk pts with a very good SA/LMR PI was identified, comparable to the R-IPI very good risk category in terms of OS. Figure 1. Overall survival of R-CHOP treated R-IPI good risk DLBCL patients according to SA and LMR at diagnosis Figure 1. Overall survival of R-CHOP treated R-IPI good risk DLBCL patients according to SA and LMR at diagnosis Disclosures No relevant conflicts of interest to declare.

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Real-world (RW) treatment (tx) patterns and outcomes of 3,455 previously untreated mantle cell lymphoma (MCL) patients (pts) in U.S. routine clinical practice.

Journal of Clinical Oncology ◽

10.1200/jco.2021.39.15_suppl.7504 ◽

2021 ◽

Vol 39 (15_suppl) ◽

pp. 7504-7504

Author(s):

Peter Martin ◽

Michael Wang ◽

Anita Kumar ◽

Keqin Qi ◽

Katherine Daly ◽

...

Keyword(s):

High Risk ◽

International Prognostic Index ◽

Prognostic Index ◽

Community Setting ◽

Cell Transplant ◽

Bulky Disease ◽

Non Hodgkin Lymphoma ◽

Community Oncology ◽

Mantle Cell ◽

Ecog Ps

7504 Background: MCL is a non-Hodgkin lymphoma with heterogeneous biology and outcomes. We characterized RW tx patterns and outcomes of MCL pts to identify factors associated with outcomes in the US. Methods: This retrospective study included adult MCL pts diagnosed Jan 2011-Nov 2020 in the nationwide Flatiron Health EHR-derived deidentified database. Pt characteristics, tx patterns, time to next tx (rwTTNT, defined as start of first-line [1L] tx to subsequent tx or death) and rwOS were evaluated. Results: 3455 pts were included, 85.3% from a community oncology setting. In 2946 (85.2%) pts with documented 1L MCL tx, median age was 69.5 y (range 27.7-85.3); 9.5% had blastoid/pleomorphic MCL. 262 (39.6%) and 235 (35.6%) of 661 pts with available MCL international prognostic index (MIPI) had intermediate and high risk, respectively. 150/1253 pts (12.0%) with available ECOG PS had PS ≥ 2. Chemoimmunotherapy was the most common 1L tx, including BR in 1223 (41.5%), R-CHOP in 512 (17.4%) and cytarabine (ara-C)-containing tx in 414 (14.1%). 667 pts received R maintenance (MR). In 1036 pts < 65 y, 243 pts received 1L stem cell transplant (SCT), mainly autologous. In 1L-treated pts, with median follow-up of survivors of 45.3 mos (range 0.03-117.2), median rwTTNT was 24 mos; 36-mo rwOS was 67%. The Table shows tx received and outcomes by age and SCT status. MVA analyses showed age ≥ 65 y, ECOG PS ≥ 2, LDH/ULN ≥ 1, WBC ≥ 10 × 109/L, bulky disease (≥ 5 cm) and blastoid/pleomorphic morphology were associated with shorter rwTTNT and rwOS; MR was independently associated with longer rwTTNT and rwOS. In pts < 65 y who were alive and did not initiate subsequent tx within 6 mos of 1L tx (“SCT-eligible”), 36-mo rwTTNT and rwOS were similar between pts treated with vs without SCT: 65% vs 59% and 86% vs 85%, respectively. Conclusions: In this large RW cohort of primarily community-based US practices, median 1L rwTTNT for MCL pts was ̃ 2 y. BR was the most commonly used 1L tx. SCT was uncommon even in pts < 65 y, suggesting RW considerations may influence SCT eligibility and availability. Also, SCT was not clearly associated with rwOS. As with other reports, older age and high-risk disease features were predictive of worse outcome in RW, while MR appeared to be associated with better outcomes. Outcomes across the board appear worse than prospective trials, suggesting a need to focus on developing tx that can be delivered effectively in the community setting.[Table: see text]

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Proposal of a Novel Latin American International Prognostic Index (LATAM-IPI) for Diffuse Large B-Cell Lymphoma (DLBCL) By the Grupo Para El Estudio De Linfoproliferativos En Latino-America (GELL)

Blood ◽

10.1182/blood-2020-142836 ◽

2020 ◽

Vol 136 (Supplement 1) ◽

pp. 25-27

Author(s):

Luis Villela Villela ◽

Ana Ramirez-Ibarguen ◽

Brady E Beltran ◽

Camila Peña ◽

Denisse A. Castro ◽

...

Keyword(s):

High Risk ◽

Board Of Directors ◽

Research Funding ◽

Scoring Systems ◽

Risk Groups ◽

Training Set ◽

Extranodal Involvement ◽

Advisory Committees ◽

Internal Validation ◽

Biological Variables

Introduction. There are different scoring systems to differentiate risk groups in patients with DLBCL treated with chemoimmunotherapy. Those systems have used the same 5 variables (age, performance status, LDH, stage, extranodal involvement) for 27 years. However, LATAM data have not been included in the development of previous scoring systems. It is important to mention that novel biological variables, such as albumin, beta-2-microglobulin (B2M) and platelet/lymphocyte ratio (PLR), have been reported and could improve discrimination (Villela et al. Blood 2019; 134Suppl_1: 1613). Therefore, we carried out a large, multinational study to develop and validate a LATAM-IPI score. Methods. This is a retrospective cohort of 1030 patients with a diagnosis of DLBCL treated with standard chemoimmunotherapy with curative intent between 2010 and 2018. Data were obtained from 8 LATAM countries: Argentina, Colombia, Chile, Guatemala, Mexico, Paraguay, Peru, and Venezuela. The five classic IPI variables (age, ECOG, extranodal involvement, LDH, stage) were analyzed and albumin and PLR were added (Villela et al. Blood 2019; 134Suppl_1: 1613). B2M was not included because it was not requested regularly in all countries. Development of LATAM-IPI: The training set consisted of 85% of the sample, randomly selected, and the remaining 15% was reserved for internal validation. Using the training set, the univariate and multivariate association between clinical prognostic factors and OS was analyzed fitting Cox proportional-hazard models. Outcomes. Clinical characteristics of the training (n=878) and internal validation (n=151) cohorts are shown in Table 1. There were no statistical differences in baseline characteristics between the cohorts. The median follow-up for the whole cohort was 36 months (IQR: 11-57). When exploring the classic IPI variables on the training set, all variables were associated with high risk of mortality [age 65-74, Hazard Ratio (HR) 1.24, 95% CI 0.96 to 1.58, p=0.08; age ≥75, HR 1.71, 95% CI 1.28 to 2.28, p=0.0003), ECOG (≥ 2, HR=2, 95% CI 1.61 to 2.53; p<0.0001), EN (≥2, HR=1.53, 95% CI 1.18 to 1.97; p=0.0012), stage (III/IV, HR=2.1, 95% CI 1.64 to 2.69; p<0.0001) and LDH (ratio 1.1-2.9, HR=1.55, 95% CI 1.22 to 1.97; p=0.0003; ratio ≥3, HR= 2.68, 95% CI 1.93 to 3.7, p<0.0001). Similarly, the biological variables Albumin (≤3.5 mg/dL, HR 2.37, 95% CI 1.9 to 2.95, p<0.0001) and PLR (≥273, HR= 1.52, 95% CI 1.23 to 1.87; p=0.0001) were associated with high risk of death. Next, these variables were evaluated by multivariate analysis. The independent variables were albumin (<3.5 mg/dL, HR 1.84, 95% CI 1.45 to 2.3, p<0.0001, 1 point), LDH (ratio 1.1 to 2.9, HR 1.30, 95% CI 1.02 to 1.67, p=0.03, 1 point; ratio ≥3, HR=1.84, 95% CI 1.31 to 2.5, p=0.0004, 2 points), advanced stage (HR 1.65, 95% CI 1.27 to 2.13, p=0.0001, 1 point), age (≥75, HR= 1.51, 95% CI 1.15 to 1.98, p=0.003, 1 point), and ECOG (≥2, HR 1.40, 95% CI 1.10 to 1.77, p=0.005). Now, for the development of LATAM-IPI, the groups were distributed as follows: 0 points, low; 1-3 points, intermediate; 4-6 points, high risk. There were no differences in the distribution of the risk groups between training and validation sets (Table 2). In the learning cohort, the 5-year OS rates for low, intermediate and high risk were 81%, 63% and 33%, respectively (p<0.0001). In the validation cohort, the 5-year OS rates for low, intermediate and high risk were 81%, 63% and 44%, respectively (p=0.02) (Figure 1). Conclusions: Using multinational learning and validation cohorts including over 1,000 DLBCL patients treated with standard chemoimmunotherapy in LATAM, we developed a novel LATAM-IPI score using age ≥75 years, ECOG ≥2, advanced stage, LDH ratio (1.1-29 and ≥3) and albumin <3.5 mg/dl. Next steps are to disseminate our results with other involved researchers in LATAM to prospectively assess and reproduce our results. We expect this score will help to further define the prognosis of DLBCL patients in LATAM. Disclosures Villela: amgen: Speakers Bureau; Roche: Other: advisory board, Speakers Bureau. Idrobo:Janssen: Honoraria, Speakers Bureau; Amgen: Honoraria, Speakers Bureau; Abbvie: Honoraria, Speakers Bureau; Tecnofarma: Honoraria, Speakers Bureau; Takeda: Honoraria, Speakers Bureau. Gomez-Almaguer:Amgen: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Novartis: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; AbbVie: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Celgene/BMS: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; AstraZeneca: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Pfizer: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Roche: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Castillo:Janssen: Consultancy, Research Funding; TG Therapeutics: Research Funding; Kymera: Consultancy; Abbvie: Research Funding; Beigene: Consultancy, Research Funding; Pharmacyclics: Consultancy, Research Funding.

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Integrated Transcriptomic Analysis of Necrosis-related Gene in Diffuse Gliomas

Journal of Neurological Surgery Part A Central European Neurosurgery ◽

10.1055/s-0039-1683448 ◽

2019 ◽

Vol 80 (04) ◽

pp. 240-249

Author(s):

Jiajia Wang ◽

Jie Ma

Keyword(s):

Gene Expression ◽

High Risk ◽

Differentially Expressed Genes ◽

Expression Profiles ◽

Prognostic Index ◽

Gene Expression Profiles ◽

Risk Groups ◽

Low Risk ◽

Differentially Expressed ◽

Low Grade

Glioblastoma multiforme (GBM), an aggressive brain tumor, is characterized histologically by the presence of a necrotic center surrounded by so-called pseudopalisading cells. Pseudopalisading necrosis has long been used as a prognostic feature. However, the underlying molecular mechanism regulating the progression of GBMs remains unclear. We hypothesized that the gene expression profiles of individual cancers, specifically necrosis-related genes, would provide objective information that would allow for the creation of a prognostic index. Gene expression profiles of necrotic and nonnecrotic areas were obtained from the Ivy Glioblastoma Atlas Project (IVY GAP) database to explore the differentially expressed genes.A robust signature of seven genes was identified as a predictor for glioblastoma and low-grade glioma (GBM/LGG) in patients from The Cancer Genome Atlas (TCGA) cohort. This set of genes was able to stratify GBM/LGG and GBM patients into high-risk and low-risk groups in the training set as well as the validation set. The TCGA, Repository for Molecular Brain Neoplasia Data (Rembrandt), and GSE16011 databases were then used to validate the expression level of these seven genes in GBMs and LGGs. Finally, the differentially expressed genes (DEGs) in the high-risk and low-risk groups were subjected to gene ontology enrichment, Kyoto Encyclopedia of Genes and Genomes pathway, and gene set enrichment analyses, and they revealed that these DEGs were associated with immune and inflammatory responses. In conclusion, our study identified a novel seven-gene signature that may guide the prognostic prediction and development of therapeutic applications.

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