scholarly journals Prognostic and Biologic Significance of Long Non-Coding RNA (lncRNA) Profiling in Cytogenetically Abnormal Acute Myeloid Leukemia (CA-AML)

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 2767-2767
Author(s):  
Dimitrios Papaioannou ◽  
Deedra Nicolet ◽  
Xiaoqing Rong-Mullins ◽  
Krzysztof Mrózek ◽  
Jessica Kohlschmidt ◽  
...  
Keyword(s):  
High Risk ◽  
Board Of Directors ◽  
Research Funding ◽  
Risk Group ◽  
High Risk Group ◽  
Low Risk ◽  
Group Status ◽  
Advisory Committees ◽  
Expression Levels ◽  
Pathway Analyses

Abstract Introduction: Aberrant expression levels of lncRNAs have been shown to independently associate with outcome of younger and older patients (pts) with cytogenetically normal AML. However, the prognostic and biologic significance of lncRNA expression in CA-AML pts have not been extensively studied. Methods: We performed whole transcriptome profiling (RNA-seq) in 469 pts with de novo CA-AML. Cytogenetic analyses were performed in institutional laboratories and the results were reviewed centrally. All pts were treated on frontline Cancer and Leukemia Group B (CALGB)/Alliance protocols. Results: To evaluate the prognostic significance of lncRNA expression in CA-AML, we analyzed RNA-seq data of 469 pts by applying a machine learning algorithm-based approach. As CA-AML pts constitute a heterogeneous group, we first determined which other clinical and molecular parameters were prognostic [i.e., associated with event-free survival (EFS)] in our dataset. Among the parameters tested, the European LeukemiaNet (ELN) Risk Group status and age group [i.e., younger than 60 years (y) or aged 60 y and older] significantly associated with clinical outcome of CA-AML pts. Next, we individually identified each lncRNA that associated with EFS while adjusting for ELN Risk Group and age group. We conducted random forest analyses to select the prognostic lncRNAs, whose combined expression levels could generate an effective outcome predictor for CA-AML pts. For each step of the random forest analyses, a bootstrap technique was applied; a simple random sample of pts was drawn which served as the training set and the out-of-sample pts were used as the independent validation set. We identified 55 prognostic lncRNAs and used their expression levels to separate our CA-AML cohort into a lncRNA low-risk (n=161) and a lncRNA high-risk (n=308) group. With regard to clinical characteristics, pts in the lncRNA low-risk group were younger (P<.001) and had lower platelet counts (P<.001) and higher white blood cell counts (P=.01) than pts in the lncRNA high-risk group. Concerning cytogenetic abnormalities, pts in the low-risk group more often had core-binding factor translocations or inversions (P<.001) and less often complex karyotypes (P<.001) than pts in the high-risk group. Pts in the lncRNA low-risk group had higher complete remission (CR) rates than pts in the high-risk group (91% vs 48%, P<.001). LncRNA low-risk group status also associated with longer disease-free survival (DFS; 5-y rates 49% vs 12%, P<.001), overall survival (OS; 5-y rates: 58% vs 14%, P<.001) and EFS (5-y rates: 45% vs 6%, P<.001). With regard to the accuracy of outcome prediction, the lncRNA risk classification had a C-index of 0.73, which compares favorably with other prognostic classifiers of AML pts. In multivariable analyses, lncRNA low-risk status was an independent marker for higher CR rates, as well as for longer DFS, OS and EFS (P<.001 in all comparisons), after adjusting for other covariates. Finally, we examined the prognostic value of the lncRNA risk classification within the Favorable and Intermediate ELN Groups of our dataset, for which lncRNA risk groups had adequate pt numbers. Among pts in ELN Favorable Group, lncRNA low-risk pts (n=128) had higher CR rates (P=.003) and longer DFS (P<.001), OS (P<.001) and EFS (P<.001) than lncRNA high-risk pts (n=32). Similarly, in the ELN Intermediate Group (n=85), lncRNA low-risk group status (n=28) associated with higher CR rates (P=.01), longer OS (P=.01) and EFS (P=.005) and a trend for longer DFS (P=.08). To gain biological insights, we examined the molecular pathways regulated by the 55 prognostic lncRNAs. To minimize the confounding effects of differences in the concurrent cytogenetic abnormalities, we restricted these analyses to the ELN Favorable Group. We identified approximately 900 transcripts that were differentially expressed between lncRNA low- and high-risk pts. DAVID pathway analyses showed enrichment of genes involved in the processes of phosphorylation, acetylation and RNA-binding. Ingenuity pathway analyses of up-stream regulators identified aberrant activity of homeobox genes such as MEIS1, HOXA9 and HOXA10 in the lncRNA low-risk group and other transcription factors such as MYC, FOSB and JUN in the high-risk group. Conclusion: We conclude that lncRNA profiling provides meaningful prognostic and biologic information in CA-AML pts. Disclosures Kolitz: Magellan Health: Consultancy, Honoraria. Powell:Rafael Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees. Stone:Cornerstone: Consultancy; Astellas: Consultancy; Orsenix: Consultancy; Merck: Consultancy; Celgene: Consultancy, Other: Data and Safety Monitoring Board, Steering Committee; Novartis: Consultancy, Research Funding; Arog: Consultancy, Research Funding; Fujifilm: Consultancy; Ono: Consultancy; Jazz: Consultancy; Sumitomo: Consultancy; Pfizer: Consultancy; Otsuka: Consultancy; Argenx: Other: Data and Safety Monitoring Board; Amgen: Consultancy; AbbVie: Consultancy; Agios: Consultancy, Research Funding. Uy:Curis: Consultancy; GlycoMimetics: Consultancy. Wang:Amgen: Consultancy; Amgen: Consultancy; Pfizer: Consultancy, Membership on an entity's Board of Directors or advisory committees; Novartis: Speakers Bureau; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees; Novartis: Speakers Bureau; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees; Jazz: Speakers Bureau; Pfizer: Consultancy, Membership on an entity's Board of Directors or advisory committees; Jazz: Speakers Bureau. Stock:Jazz Pharmaceuticals: Consultancy.

Combining Information Regarding Chromosomal Aberrations t(4;14), Del(17p13) and the Copy Number of 1q21 with the International Staging System Classification Allows Stratification of Myeloma Patients Undergoing Autologous Stem Cell Transplantation: Results From the HOVON-65/GMMG HD4 Trial

Blood ◽  
2011 ◽  
Vol 118 (21) ◽  
pp. 332-332
Author(s):  
Kai Neben ◽  
Henk M. Lokhorst ◽  
Anna Jauch ◽  
Uta Bertsch ◽  
Thomas Hielscher ◽  
...  
Keyword(s):  
High Risk ◽  
Board Of Directors ◽  
Research Funding ◽  
Prognostic Value ◽  
Risk Group ◽  
Staging System ◽  
Risk Groups ◽  
Low Risk ◽  
Advisory Committees ◽  
International Staging System

Abstract Abstract 332 PURPOSE : In Multiple Myeloma (MM), the combination of serum beta-2-microglobulin level with serum albumin concentration has been proposed as an outcome predictor in the International Staging System (ISS). More recently, subgroups of MM defined by genetic and cytogenetic abnormalities have been associated with unique biologic, clinical, and prognostic features. PATIENTS AND METHODS: We analyzed the prognostic value of 12 chromosomal abnormalities by fluorescent in situ hybridization (FISH) in a series of 354 MM patients treated within the HOVON-65/GMMG-HD4 trial. Patients with newly diagnosed MM were randomized to receive either three cycles of VAD (arm A; vincristine, adriamycin, dexamethasone) or PAD (arm B; bortezomib, adriamycin, dexamethasone). All patients underwent autologous stem cell transplantation (ASCT) followed by maintenance therapy with thalidomide 50 mg daily (arm A) or bortezomib 1.3 mg/m2 once every 2 weeks (arm B), respectively. In addition, a second cohort of patients was analyzed as a control group (n=462), undergoing ASCT at the University of Heidelberg between September 1994 and December 2010. RESULTS: For the entire group of patients treated within the HOVON-65/GMMG-HD4 trial, we identified 233 patients with 2 copies (67.7%), 95 patients with 3 copies (27.6%) and 16 patients (4.7%) with more than three copies of the chromosomal region 1q21. In addition to del(17p13) and t(4;14), we added +1q21 (>3 copies) to the group of high-risk aberrations, since the outcome of these patients was almost as poor as it was observed for patients with del(17p13). Subsequently, we analyzed whether combining the ISS score with information on the presence of high-risk aberrations could improve the prognostic value with regard to patients' outcome. A combination of the presence or absence of del(17p13), t(4;14), or +1q21 (>3 copies) with the ISS score allowed patients to be stratified into three distinct groups: low-risk [absence of del(17p13)/t(4;14)/+1q21 (>3 copies) and ISS I], high-risk [presence of del(17p13)/t(4;14)/+1q21 (>3 copies) and ISS II/III], and intermediate-risk (all remaining patients). Most of the patients belonged to the low- (33%) and intermediate-risk (49%) groups, whereas 18% were allocated to the high-risk group. The median PFS times for the low-, intermediate-, and high-risk groups were 41.9 months, 31.1 months (HR=1.7; p=0.0018) and 18.7 months (HR=3.6; p<0.0001), respectively. The 3yr-overall survival (OS) decreased from 94% in the low-risk group to 80% (HR=4.6; p=0.0001) and 43% (HR=12.8; p<0.0001) in the intermediate- and high-risk groups, respectively. These results were confirmed in the independent cohort of patients: From date of first ASCT, the median PFS times for the low-, intermediate-, and high-risk groups were 43.3 months, 23.0 months (HR=1.5; p=0.015) and 13.8 months (HR=2.4; p=0.0003), respectively. The 4yr-OS decreased from 84% in the low-risk group to 71% (HR=2.1; p=0.0043) and 49% (HR=3.84; p<0.0001) in the intermediate- and high-risk groups, respectively. CONCLUSION: In our series, the ISS/FISH-based score/algorithm predicted PFS and OS much better than the ISS alone. Our results with molecular cytogenetic techniques may already have implications for the risk-adapted clinical management of patients with MM particularly in younger patients. Disclosures: van de Velde: Ortho Biotech Oncology Research & Development: Employment. Sonneveld:Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen-Cilag: Membership on an entity's Board of Directors or advisory committees, Research Funding; Onyx: Membership on an entity's Board of Directors or advisory committees, Research Funding; Millennium: Membership on an entity's Board of Directors or advisory committees.

scholarly journals Impact of Cytogenetics on Outcomes of Transplant-Ineligible Patients with Newly Diagnosed Multiple Myeloma Treated with Continuous Lenalidomide Plus Low-Dose Dexamethasone in the First (MM-020) Trial

Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 730-730 ◽  
Author(s):  
Herve Avet-Loiseau ◽  
Cyrille Hulin ◽  
Lofti Benboubker ◽  
Meletios A. Dimopoulos ◽  
Andrew Belch ◽  
...  
Keyword(s):  
High Risk ◽  
Board Of Directors ◽  
Research Funding ◽  
Risk Group ◽  
Risk Groups ◽  
High Risk Group ◽  
Continuous Treatment ◽  
Duration Of Treatment ◽  
Advisory Committees ◽  
Reduced Risk

Abstract Introduction: Cytogenetic abnormalities in patients (pts) with multiple myeloma (MM) are of prognostic importance and can be associated with poor outcomes (Bergsagel, Blood, 2011). The FIRST trial is a pivotal phase 3 study with the largest data set in transplant-ineligible pts with newly diagnosed MM (NDMM). This subanalysis evaluates the impact of cytogenetics on outcomes in transplant-ineligible pts with NDMM continuously treated with lenalidomide plus low-dose dexamethasone until disease progression (Rd continuous). Methods: Transplant-ineligible pts with NDMM were randomized to 1 of 3 treatment arms: Rd continuous, Rd18 (Rd for 18 cycles [72 weeks]), or melphalan-prednisone-thalidomide (MPT; for 12 cycles [72 weeks]). Cytogenetics were assessed using fluorescence in situ hybridization. Pts were categorized into cytogenetic risk groups according to International Myeloma Working Group criteria. High-risk cytogenetics included del(17p), t(4;14), and t(14;16); all other pts were categorized as non-high risk. The primary endpoint was progression-free survival (PFS; primary comparators were Rd continuous vs MPT), and key secondary endpoints were overall survival (OS), overall response rate (ORR), and safety. Results: A total of 762 of 1623 pts from the intent-to-treat population had validated cytogenetic profiles, with 142 pts in the high-risk group and 620 pts in the non-high-risk group. Baseline characteristics were well balanced across cytogenetic risk groups (Table 1). The median follow-up for OS was 40.2 months for the 762 pts in this analysis (data cutoff, March 03, 2014). In the non-high-risk group, median duration of treatment was 19.4 months with Rd continuous and 16.6 months with both Rd18 and MPT. In the high-risk group, median duration of treatment was 10.0 months with Rd continuous, 8.2 months with Rd18, and 12.0 months with MPT. Rd continuous treatment resulted in a 24% reduced risk of death or progression compared with MPT and an even greater 32% reduced risk in pts without high-risk cytogenetics (Table 2). In non-high-risk pts, median PFS was 31.1 months with Rd continuous compared with 21.2 and 24.9 months with Rd18 and MPT, respectively (Figure). However, in high-risk pts, the observed numerical median PFS favoring Rd18 is mainly due to small pt numbers influenced by long runners (n = 5), and the greatly overlapping 95% CIs from all 3 arms show the difference is likely to be minimal. Rd continuous treatment resulted in a 28% reduced risk of death vs MPT overall and a 34% reduced risk in pts without high-risk cytogenetics. OS was similar across treatment arms for high-risk pts. ORRs in all cytogenetic risk groups favored Rd continuous vs MPT. In pts with high-risk cytogenetics, higher-quality responses were also observed with Rd continuous vs MPT treatment. Similar results were seen with Rd continuous compared with Rd18, although OS and ORR benefits overall and in pts without high-risk cytogenetics were not as pronounced. In all 3 treatment arms, adverse events were consistent across cytogenetic risk groups. Conclusions: Rd continuous treatment resulted in PFS and OS benefits vs MPT in pts with validated cytogenetic profiles. This was largely due to PFS and OS improvements in pts without high-risk cytogenetics. In the high-risk group, the longest PFS was observed with Rd18 treatment and OS was similar across treatment arms. Despite being on the continuous vs fixed duration treatment arm, high-risk pts on Rd continuous received a shorter duration of treatment than those on MPT, which may explain why PFS favored MPT vs Rd continuous. Higher response rates were observed with Rd continuous vs MPT, regardless of cytogenetic risk, and greater quality responses were observed in pts with high-risk cytogenetics. The safety profile of Rd continuous was manageable and consistent between cytogenetic risk groups. Results support Rd continuous as a standard treatment option for pts with NDMM who are ineligible for transplant, especially those without high-risk cytogenetics. Additional PFS and OS benefits may be achieved in pts with high-risk cytogenetics when Rd continuous is used as a backbone for combination therapy with a novel agent. Promising activity in pts with high-risk cytogenetic abnormalities has been demonstrated using this approach (Lonial et al, N Engl J Med, 2015; Stewart et al, N Engl J Med, 2015). Disclosures Hulin: Celgene Corporation: Honoraria; Janssen: Honoraria; Amgen: Honoraria; Bristol Myers Squibb: Honoraria. Dimopoulos:Celgene: Honoraria; Onyx: Honoraria; Novartis: Honoraria; Janssen-Cilag: Honoraria; Amgen: Honoraria; Janssen: Honoraria; Genesis: Honoraria. Reece:Lundbeck: Honoraria; Amgen: Honoraria; Merck: Research Funding; Bristol-Myers Squibb: Research Funding; Janssen-Cilag: Consultancy, Honoraria, Research Funding; Onyx: Consultancy; Celgene: Consultancy, Honoraria, Research Funding; Novartis: Honoraria, Research Funding; Millennium Takeda: Research Funding; Otsuka: Research Funding. Catalano:Roche: Consultancy, Honoraria; Gilead: Consultancy, Honoraria; Celgene Corporation: Consultancy, Honoraria. Pinto:Takeda: Honoraria, Research Funding; Celgene Corporation: Honoraria; Spectrum: Honoraria. Ludwig:Takeda: Research Funding; Celgene Corporation: Honoraria, Speakers Bureau; Onyx: Honoraria, Speakers Bureau; Bristol Myers Squibb: Honoraria, Speakers Bureau; Janssen Cilag: Honoraria, Speakers Bureau. Bahlis:Celgene Corporation: Honoraria, Research Funding. Cavo:Janssen-Cilag, Celgene, Amgen, BMS: Honoraria. Moreau:Takeda: Other: Adboard; Janssen: Other: Adboard; Novartis: Other: Adboard; Amgen: Other: Adboard; Celgene: Honoraria, Other: Adboard. Qiu:Johnson & Johnson: Speakers Bureau; Celgene Corporation: Speakers Bureau; Roche: Speakers Bureau. Schots:Celgene Corporation: Research Funding. Marek:Celgene Corporation: Employment, Equity Ownership. Chen:Celgene Corporation: Employment, Equity Ownership. Yiu:Celgene Corporation: Employment, Equity Ownership. Ervin-Haynes:Celgene Corporation: Employment. Facon:Janssen: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Millenium: Membership on an entity's Board of Directors or advisory committees; Onyx: Membership on an entity's Board of Directors or advisory committees; BMS: Membership on an entity's Board of Directors or advisory committees; Celgene: 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; Amgen: Membership on an entity's Board of Directors or advisory committees; Pierre Fabre: Membership on an entity's Board of Directors or advisory committees.

Application of a Validated Predictive Model for Venous Thromboembolism in Cancer to Patients with Multiple Myeloma

Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 534-534
Author(s):  
Natasha Catherine Edwin ◽  
Jesse Keller ◽  
Suhong Luo ◽  
Kenneth R Carson ◽  
Brian F. Gage ◽  
...  
Keyword(s):  
High Risk ◽  
Research Funding ◽  
Risk Group ◽  
High Risk Group ◽  
Low Risk ◽  
Intermediate Risk ◽  
Discriminative Ability ◽  
Blood Institute ◽  
C Statistic

Abstract Background Patients with multiple myeloma (MM) have a 9-fold increased risk of developing venous thromboembolism (VTE). Current guidelines recommend pharmacologic thromboprophylaxis in patients with MM receiving an immunomodulatory agent in the presence of additional VTE risk factors (NCCN 2015, ASCO 2014, ACCP 2012). However, putative risk factors vary across guidelines and no validated VTE risk tool exists for MM. Khorana et al. developed a VTE risk score in patients with solid organ malignancies and lymphoma (Blood, 2008). We sought to apply the Khorana et al. score in a population with MM. Methods We identified patients diagnosed with MM within the Veterans Health Administration (VHA) between September 1, 1999 and December 31, 2009 using the International Classification of Diseases (ICD)-03 code 9732/3. We followed the cohort through October 2014. To eliminate patients with monoclonal gammopathy of undetermined significance and smoldering myeloma, we excluded patients who did not receive MM-directed therapy within 6 months of diagnosis. We also excluded patients who did not have data for hemoglobin (HGB), platelet (PLT) count, white blood count (WBC), height and weight, as these are all variables included in the Khorana et al. risk model. Height and weight were assessed within one month of diagnosis and used to calculate body mass index (BMI). We measured HGB, PLT count, and WBC count prior to treatment initiation: within two months of MM diagnosis. A previously validated algorithm, using a combination of ICD-9 code for VTE plus pharmacologic treatment for VTE or IVC filter placement, identified patients with incident VTE after MM diagnosis (Thromb Res, 2015). The study was approved by the Saint Louis VHA Medical Center and Washington University School of Medicine institutional review boards. We calculated VTE risk using the Khorana et al. score: We assigned 1 point each for: PLT ≥ 350,000/μl, HGB < 10 g/dl, WBC > 11,000/μl, and BMI ≥ 35 kg/m2. Patients with 0 points were at low-risk, 1-2 points were considered intermediate-risk and ≥3 points were termed high-risk for VTE. We assessed the relationship between risk-group and development of VTE using logistic regression at 3- and 6-months. We tested model discrimination using the area under the receiver operating characteristic curve (concordance statistic, c) with a c-statistic range of 0.5 (no discriminative ability) to 1.0 (perfect discriminative ability). Results We identified 1,520 patients with MM: 16 were high-risk, 802 intermediate-risk, and 702 low-risk for VTE using the scoring system in the Khorana et al. score. At 3-months of follow-up, a total of 76 patients developed VTE: 27 in the low-risk group, 48 in the intermediate-risk group, and 1 in the high-risk group. At 6-months of follow-up there were 103 incident VTEs: 41 in the low-risk group, 61 in the intermediate-risk group, and 1 in the high-risk group. There was no significant difference between risk of VTE in the high- or intermediate-risk groups versus the low-risk group (Table 1). The c-statistic was 0.56 at 3-months and 0.53 at 6-months (Figure 1). Conclusion Previously, the Khorana score was developed and validated to predict VTE in patients with solid tumors. It was not a strong predictor of VTE risk in MM. There is a need for development of a risk prediction model in patients with MM. Figure 1. Figure 1. Disclosures Carson: American Cancer Society: Research Funding. Gage:National Heart, Lung and Blood Institute: Research Funding. Kuderer:Janssen Scientific Affairs, LLC: Consultancy, Honoraria. Sanfilippo:National Heart, Lung and Blood Institute: Research Funding.

scholarly journals Mutation Landscape and Prognostic Correlates of ASXL1 Variants in Primary and Secondary Myelofibrosis

Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 2578-2578
Author(s):  
Giacomo Coltro ◽  
Paola Guglielmelli ◽  
Giada Rotunno ◽  
Carmela Mannarelli ◽  
Chiara Maccari ◽  
...  
Keyword(s):  
High Risk ◽  
Board Of Directors ◽  
Risk Group ◽  
Risk Groups ◽  
High Risk Group ◽  
Prognostic Impact ◽  
Driver Genes ◽  
Advisory Committees ◽  
Risk Of Death ◽  
Significant Difference

Abstract Introduction: Myelofibrosis (MF), whether primary (PMF) or secondary (SMF) to polycythemia vera or essential thrombocytemia, is characterized by a complex and partially undeciphered molecular architecture. Besides mutations in driver genes (JAK2, CALR, MPL), somatic mutations in selected myeloid-associated genes have been shown to impact prognosis of MF patients (pts). Among these, ASXL1 mutations (ASXL1MTs) are associated with poor outcomes in myeloid malignancies including PMF, where they are included in the category of "high molecular risk" (HMR) mutations along with EZH2MTs, IDH1/2MTs, and SRSF2MTs (Vannucchi AM, Leukemia 2013). However, a recent study (Luque Paz D, Blood Adv 2021) questioned the value of ASXL1MTs in MF. The current study aimed at further characterizing the prognostic role of ASXL1MTs in MF. Methods: After IRB approval, pts with WHO-defined MF were included in the study. Mutational analysis by targeted NGS was performed as previously described (Guglielmelli P, JCO 2017). All deposited variants were manually curated to assess pathogenicity. In this study, we also used the molecular model proposed by Luque Paz et al. that identifies 4 genetic groups: TP53MT; High-risk (≥1 mutation in EZH2, CBL, U2AF1, SRSF2, IDH1/2); ASXL1MT-only; and "Others". Results: A total of 525 pts were included in the study, including 331 (63%) PMF and 194 (37%) SMF. Median age at diagnosis was 89 (18-90) years, 314 (60%) were male. The median follow-up time was 80 (98% CI, 68-90) months. Overall, 324 (62%) pts were JAK2MT, 126 (24%) CALRMT, 24 (5%) MPLMT, 40 (8%) triple negative (TN), and 11 (2%) double mutated. Among non-driver genes, ASXL1MTs were found in 158 (30%) pts, EZH2MTs in 45 (9%), SRSF2MTs in 37 (7%), NRASMTs in 30 (6%) U2AF1MTs in 27 (5%), TP53MTs and CBLMTs in 25 (5%) each, IDH1/2 MTs in 18 (3%), and KRAS MTs in 15 (3%). Pts in the HMR category were 125 (38%) in PMF and 63 (32%) in SMF. According to the above model, distribution of pts was as follows: TP53MT n=25 (5%), High-risk n=137 (26%), ASXL1MT-only n=64 (12%), and Others n=299 (57%). Pts in the TP53MT and ASXL1MT-only groups were more likely to be diagnosed with SMF compared to pts in the High-risk and Others groups (44% and 48% vs 28% and 38%, respectively). In addition, the High-risk group was enriched in TN pts (16%), while CALRMTs were more common in the ASXL1MT-only and Others compared to the TP53MT and High-risk groups (25% and 27% vs 12% and 18%, respectively). In univariate analysis, the TP53MT and High-risk groups were associated with the worst overall survival (OS), with median values of 38 (14-110) and 55 (45-85) months (P=.0039), respectively (Fig 1A). Albeit remarkably better, the OS of pts in the ASXL1MT-only group was inferior compared to pts in the Others group (median 124 [91-156] vs 193 [142-NR] months; P=.0118) (Fig 1A). We then analyzed separately PMF and SMF cohorts. In the former, the TP53MT and High-risk groups remained associated with the worst OS (median 58 [20-126] vs 55 [36-85] months), although with no significant difference, likely due to the low frequency (4%) of TP53MTs mutations in PMF (Fig 1B). Concurrently, the negative prognostic impact of the ASXL1MT-only group was confirmed in comparison to the Others group (median 103 [78-NR] vs 320 [178-NR] months; P=.0170). In pts with SMF, while the TP53MT group (6%) had by far the worst OS (median 13 [6-NR] months), the OS of the ASXL1MT-only group (median 141 [56-171] months) was comparable to that of the Others group (median 131 [106-NR] months; P=.5188) and not different from the High-risk group (median 58 [45-174] months; P=.3606) (Fig 1C). In a further analysis including only pts in the High-risk group, ASXL1MTs were found in 62% and 63% of patients with PMF and SMF, respectively. In survival analysis, the presence of ASXL1MTs was associated with an increased risk of death only in PMF (median OS 47 [31-73] vs 102 [34-317] months; P=.0240), unlike in SMF (median OS 90 [47-174] vs 25 [16-338] months; P=.3296) (Fig 1D-E). Conclusion: In the current study, we critically re-addressed the prognostic impact of ASXL1MTs by applying a genetic model recently developed by Luque Paz et al. to our cohort of molecularly annotated, WHO-defined MF pts. Overall, our results confirm that ASXL1MTs -even in the absence of other co-occurring high-risk mutations- harbor a negative prognostic impact mainly in PMF. These findings also reinforce the idea that PMF and SMF represent two different biological entities. Figure 1 Figure 1. Disclosures Vannucchi: Incyte: Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees; BMS: Honoraria, Membership on an entity's Board of Directors or advisory committees; AbbVie: Membership on an entity's Board of Directors or advisory committees.

scholarly journals A Novel Prognostic Model That Is Superior to FLIPI-1 and FLIPI-2 and Integrates Clinical and Treatment Factors to Predict Progression-Free Survival and Early Treatment Failure in Patients with Follicular Lymphoma in the GALLIUM Trial

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 2872-2872 ◽  
Author(s):  
Farheen Mir ◽  
Andrew Grigg ◽  
Michael Herold ◽  
Wolfgang Hiddemann ◽  
Robert Marcus ◽  
...  
Keyword(s):  
High Risk ◽  
Board Of Directors ◽  
Research Funding ◽  
Prognostic Model ◽  
Low Risk ◽  
Prognostic Variables ◽  
Advisory Committees ◽  
High Risk Disease ◽  
Risk Patients ◽  
Equity Ownership

Abstract Introduction: Progression of disease within 24 months of initial therapy (POD24) is associated with poor survival in patients with follicular lymphoma (FL). Existing prognostic models, such as FLIPI-1 and FLIPI-2, show poor sensitivity for POD24, and are derived from cohorts lacking bendamustine-treated patients. More accurate predictive models based on current standard therapies are needed to identify patients with high-risk disease. The Phase III GALLIUM trial (NCT01332968) compared the safety and efficacy of standard chemotherapy regimens plus rituximab (R) or obinutuzumab (G) in patients with previously untreated FL. Using GALLIUM data, we developed a novel risk stratification model to predict both PFS and POD24 in FL patients after first-line immunochemotherapy. Methods: Enrolled patients were aged ≥18 years with previously untreated FL (grades 1-3a), Stage III/IV disease (or Stage II with bulk), and ECOG PS ≤2, and required treatment by GELF criteria. Patients were randomized to receive either G- or R-based immunochemotherapy, followed by maintenance with the same antibody in responders. The chemotherapy arm (CHOP, CVP, or bendamustine) was selected by each study center. POD24 was defined as progressive disease or death due to disease within 24 months of randomization (noPOD24 = no progression or lymphoma-related death in that period). The most strongly prognostic variables, based on PFS hazard ratios, were estimated using penalized multivariate Cox regression methodology via an Elastic Net model. Selected variables were given equal weights, and a clinical score was formed by summating the number of risk factors for each patient. Low- and high-risk categories were determined using a cut-off that provided the best balance between true- and false-positives for PFS. PFS correlation and sensitivity to predict POD24 were assessed. The data used are from an updated GALLIUM efficacy analysis (data cut-off: April 2018; median follow-up: 57 months). Results: 1202 FL patients were enrolled. Based on data availability and biological plausibility (i.e. could reasonably be linked with high-risk disease), 25 potential clinical and treatment-related prognostic variables were entered into the Elastic Net model (Table). A model containing 11 factors was retained by the methodology and chosen as the best model (Table). Patients were categorized as 'low risk' if they scored between 0 and 3 (n=521/1000 patients with complete data) and as 'high risk' if they scored between 4 and 11 (n=479/1000 patients). At 2 years, the PFS rate was 84.5% in the whole FL population. Using our model, 2-year PFS for high-risk patients was 77% compared with 79.9% for FLIPI-1 and FLIPI-2. In low-risk patients, 2-year PFS was 92% compared with 87.9% for FLIPI-1 and 87.6% for FLIPI-2 (low-intermediate-risk patients). Our model increased the inter-group difference in 2-year PFS rate from 8% (FLIPI-1) and 7.7% (FLIPI-2) to 15%. At 3 years, the inter-group difference increased from 6.9% (FLIPI-1) and 9% (FLIPI-2) to 17% (Figure). Sensitivity for a high-risk score to predict POD24 was 73% using our model compared with 55% for FLIPI-1 and 52% for FLIPI-2 (based on 127 POD24 and 873 noPOD24 patients with complete data). Excluding patients who received CVP, which is now rarely used, resulted in an inter-group difference in PFS of 15% at 2 years and 16.8% at 3 years. A sensitivity analysis showed that inclusion of the 9 clinical factors only (i.e. removal of CVP and R treatment as variables) formed a more basic scoring system (low-risk patients, 1-3; high-risk patients, 4-9); the inter-group difference in PFS was 16.5% at 2 years and 17.6% at 3 years. However, sensitivity for POD24 decreased to 56%. Conclusion: Our clinical prognostic model was more accurate at discriminating patients likely to have poor PFS than either FLIPI-1 or FLIPI-2, and its prognostic value was sustained over time. Our model also identified the FL population at risk of POD24 with greater sensitivity. Variables such as age and bone marrow involvement were not retained by our model, and thus may not have a major impact in the current era of therapy. Factors such as sum of the products of lesion diameters were included, as this captures tumor burden more accurately than presence of bulk disease. Future studies will aim to improve the accuracy of the model by considering gene expression-based prognostic markers and DNA sequencing to form a combined clinico-genomic model. Disclosures Mir: F. Hoffmann-La Roche: Employment. Hiddemann:F. Hoffman-La Roche: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Bayer: Consultancy, Research Funding. Marcus:F. Hoffman-La Roche: Other: Travel support and lecture fees; Roche: Consultancy, Other: Travel support and lecture fees ; Gilead: Consultancy. Seymour:Genentech Inc: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Honoraria, Research Funding; Celgene: Consultancy; AbbVie: Consultancy, Honoraria, Research Funding; F. Hoffmann-La Roche Ltd: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees. Bolen:Roche: Other: Ownership interests PLC*. Knapp:Roche: Employment. Launonen:Launonen: Other: Ownership interests none PLC; Travel, accommodation, expenses; Novartis: Consultancy, Equity Ownership, Other: Ownership interests none PLC; Travel. accommodation, expenses; Roche: Employment, Other: Travel, accommodation, expenses. Mattiello:Roche: Employment. Nielsen:F. Hoffmann-La Roche Ltd: Employment, Other: Ownership interests PLC. Oestergaard:Roche: Employment, Other: Ownership interests PLC. Wenger:F. Hoffmann-La Roche Ltd: Employment, Equity Ownership, Other: Ownership interests PLC. Casulo:Gilead: Honoraria; Celgene: Research Funding.

scholarly journals Progression Risk-Based Classification of Asymptomatic Waldenström Macroglobulinemia

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 150-150
Author(s):  
Mark Bustoros ◽  
Romanos Sklavenitis-Pistofidis ◽  
Chia-jen Liu ◽  
Efstathios Kastritis ◽  
Geoffrey Fell ◽  
...  
Keyword(s):  
Bone Marrow ◽  
High Risk ◽  
Board Of Directors ◽  
Research Funding ◽  
Proportional Hazards ◽  
Risk Group ◽  
Advisory Committees ◽  
Waldenström Macroglobulinemia ◽  
Waldenstrom Macroglobulinemia ◽  
Risk Of Progression

Abstract Background. Waldenström macroglobulinemia (WM) is a low-grade non-Hodgkin's lymphoplasmacytic lymphoma associated with overproduction of monoclonal IgM protein. It is preceded by an asymptomatic stage, called Smoldering Waldenström Macroglobulinemia (SWM), associated with a high risk of progression to overt disease. Current understanding of progression risk in SWM is based on a few small studies, and it is still unclear how to distinguish the asymptomatic patients who will progress from those who will not. Patients and Methods. We obtained clinical data of all WM patients who had been diagnosed and followed up at Dana-Farber Cancer Institute from 1982 to the end of 2014. Only patients with asymptomatic disease at the time of diagnosis were included in this study to identify risk factors for disease progression. Patients who received chemotherapy for a second cancer, before or after asymptomatic WM diagnosis (n =24), were excluded as chemotherapy might have affected the natural course of disease. Patients who progressed to or were diagnosed later with other types of B-cell lymphoproliferative disorders or Amyloidosis (n =71) and patients with myeloproliferative disorders or thalassemia (n = 4) were all excluded from our cohort. Furthermore, we excluded patients with no morphologic evidence of lymphoplasmacytic infiltration in the bone marrow biopsy (n =37), those without a bone marrow biopsy done at time of diagnosis (n =21), and those who were treated for peripheral neuropathy alone (n =13). Progression was defined based on the Consensus Panel recommendations of the Second International Workshop on WM. Survival analysis was performed using the Kaplan-Meier method and differences between the curves were tested by log-rank test. Effects of potential risk factors on progression rates was examined using Cox proportional-hazards models, with hazard ratios (HRs) and associated 95% confidence intervals (CIs). Results. A total of 439 patients were included in the study. During the 35-year study period and a median follow up of 7.8 years, 317 patients (72.2%) progressed to symptomatic WM. The median time to progression was 3.9 (95% CI 3.2-4.6) years. In the multivariate analysis, IgM ≥ 4,500 mg/dL (adjusted HR 4.65; 95% CI 2.52-8.58; p < 0.001), BM lymphoplasmacytic infiltration ≥ 70% (adjusted HR 2.56; 95% CI 1.69-3.87; p < 0.001), β2-microglobulin ≥ 4.0 mg/dL (adjusted HR 2.31; 95% CI 1.19-4.49; p = 0.014), and albumin < 3.5 g/dL (adjusted HR 2.78; 95% CI 1.52-5.09; p = 0.001) were all identified as independent predictors of disease progression, suggesting those thresholds could be clinically useful for determining high-risk patients. On the other hand, given the continuous nature of these variables, we built a proportional hazards model based on four variables (Bone marrow infiltration percentage, serum IgM, albumin, β2-microglobulin). The model divided the cohort into 3 distinct risk groups: a high-risk group with a median time to progression (TTP) of 1.9 years (95% CI 1.64-2.13), an intermediate-risk group with median TTP of 4.6 years (95% CI 4.31-5.15), and a low-risk group with a median TTP of 8.1 years (95% CI 7.33-8.13)(See Figure). To enhance its clinical applicability, we made the model available as user interface through a webpage and mobile application, where clinicians can enter an individual SWM patient's lab values and get information regarding their risk group and estimated individual risk of progression to symptomatic WM. Conclusion. We have assembled the largest cohort of SWM patients to date, which allowed us to identify four independent predictors of progression to overt disease: BM infiltration ≥ 70%, IgM ≥ 4,500 mg/dL, b2m ≥ 4.0 mg/dL and albumin < 3.5 g/dL. Using those variables in a proportional hazards model, we developed a robust, flexible classification system based on risk of progression to symptomatic WM. This system stratifies SWM patients into low-, intermediate- and high-risk groups and thus has the potential to inform patient monitoring and care. Most importantly, it can help identify high-risk patients who might benefit from early intervention in this rare malignancy. Figure 1. Figure 1. Disclosures Bustoros: Dava Oncology: Honoraria. Kastritis:Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Prothena: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees. Soiffer:Jazz Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees. Treon:Johnson & Johnson: Consultancy; Janssen: Consultancy, Other: Travel, Accommodations, Expenses; BMS: Research Funding; Pharmacyclics: Consultancy, Other: Travel, Accommodations, Expenses, Research Funding. Castillo:Genentech: Consultancy; Millennium: Research Funding; Abbvie: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Beigene: Consultancy, Research Funding; Pharmacyclics: Consultancy, Research Funding. Dimopoulos:Amgen: Honoraria; Janssen: Honoraria; Takeda: Honoraria; Celgene: Honoraria; Bristol-Myers Squibb: Honoraria. Ghobrial:BMS: Consultancy; Janssen: Consultancy; Takeda: Consultancy; Celgene: Consultancy.

scholarly journals A Randomized Placebo-Controlled Phase 2 Study of Metformin for the Prevention of Progression of Monoclonal Gammopathy of Undetermined Significance and Low Risk Smoldering Multiple Myeloma

Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 1659-1659
Author(s):  
Catherine R. Marinac ◽  
Robert A. Redd ◽  
Julia Prescott ◽  
Alexandra Savell ◽  
Courtney Igne ◽  
...  
Keyword(s):  
High Risk ◽  
Board Of Directors ◽  
Monoclonal Gammopathy ◽  
Research Funding ◽  
Controlled Trial ◽  
Low Risk ◽  
M Protein ◽  
Advisory Committees ◽  
Randomized Controlled ◽  
Bone Marrow Plasma

Abstract Background: Multiple Myeloma (MM) is thought to evolve from the precursor conditions monoclonal gammopathy of undetermined significance (MGUS) and smoldering MM (SMM), which are common premalignant disorders that progress to overt MM in a subset of individuals for reasons that are poorly understood. Despite increasing interest in preventing disease progression in this patient population, the standard of care still consists of close surveillance until progression to MM; however, once MM develops it cannot be cured. Therefore, the identification of prevention and interception strategies for patients with MGUS and SMM is of considerable importance. A promising pharmacologic intervention to reduce the risk of progression of MGUS/SMM to MM is metformin, a drug commonly used to treat type 2 diabetes but that is also considered safe for use in non-diabetic populations. In vivo and in vitro studies have revealed that metformin has direct antitumor effects across a variety of cancers including MM, and recent epidemiological data suggests it may reduce the risk of MM in diabetic patients with MGUS. Here, we describe the first randomized controlled trial testing the efficacy of metformin in reducing clinical signs of disease progression in patients with MGUS and SMM (NCT04850846). Study Design and Methods: This is a phase II single center, randomized controlled trial of metformin vs. placebo in patients with high-risk MGUS and low-risk SMM. The primary objective of the study is to determine whether metformin can reduce or stabilize serum monoclonal (M-)protein concentrations from baseline to 6-months. Exploratory objectives include mass spectrometry quantification of M-protein, examination of molecular evolution of tumor cells in response to metformin, as well as changes in other clinical laboratory parameters in response to metformin. To be eligible, patients must have high-risk MGUS or low-risk SMM. High-risk MGUS is defined as bone marrow plasma cell concentration &lt;10% with one or more of the following higher-risk features: serum M-protein level ≥1.5 g/dL to &lt;3 g/dL or abnormal free light-chain (FLC) ratio (&lt;0.26 or&gt;1.65); a forthcoming amendment will include non-IgG subtype as an additional high-risk feature. Low-risk SMM is defined as bone marrow plasma cells ≥10%with the absence of any features of high-risk SMM. Metformin and its corresponding placebo are the pharmacological treatments. The metformin dose is 1500 milligrams/day, provided in 500 milligram pills. To minimize gastrointestinal symptoms, metformin is started at a low dose of 500 milligram (1 pill) per day and participants gradually increase the dosage over the course of the first month of treatment until the full 1500 milligram (3 pill) per day regimen is achieved. The study treatment period is 6 months, with primary outcomes assessed at the end of the 6-month treatment period. Conclusions and Future Directions: While the cornerstone of clinical management in MGUS and SMM is to delay therapy until progression to symptomatic MM, patients and oncologists continually seek new ways to prevent end organ damage and incurable malignancy. This trial is positioned to provide preliminary but robust mechanistic data to support the development of novel prevention strategies for MGUS and SMM patients. Disclosures Marinac: GRAIL Inc: Research Funding; JBF Legal: Consultancy. Sperling: Adaptive: Consultancy. Parnes: Sigilon: Membership on an entity's Board of Directors or advisory committees; Genentech: Membership on an entity's Board of Directors or advisory committees; UniQure: Membership on an entity's Board of Directors or advisory committees; Sunovion: Consultancy; I-mAb: Consultancy; Aspa: Consultancy; Genentech/Hoffman LaRoche: Research Funding; Shire/Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding. Richardson: Protocol Intelligence: Consultancy; Regeneron: Consultancy; Sanofi: Consultancy; Secura Bio: Consultancy; AbbVie: Consultancy; Janssen: Consultancy; GlaxoSmithKline: Consultancy; AstraZeneca: Consultancy; Karyopharm: Consultancy, Research Funding; Takeda: Consultancy, Research Funding; Celgene/BMS: Consultancy, Research Funding; Oncopeptides: Consultancy, Research Funding; Jazz Pharmaceuticals: Consultancy, Research Funding. Ghobrial: AbbVie, Adaptive, Aptitude Health, BMS, Cellectar, Curio Science, Genetch, Janssen, Janssen Central American and Caribbean, Karyopharm, Medscape, Oncopeptides, Sanofi, Takeda, The Binding Site, GNS, GSK: Consultancy. Nadeem: Karyopharm: Membership on an entity's Board of Directors or advisory committees; Adaptive Biotechnologies: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees; BMS: Membership on an entity's Board of Directors or advisory committees; GSK: Membership on an entity's Board of Directors or advisory committees. OffLabel Disclosure: metformin, which is an anti-diabetic medication

scholarly journals Progressive Hyperleukocytosis during Initial Therapy Is a Predictive Marker for Differentiation Syndrome and Early Mortality in Adult Patients with Acute Promyelocytic Leukemia

Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 4009-4009
Author(s):  
Jae-Ho Yoon ◽  
Heeje Kim ◽  
Sung-Soo Park ◽  
Young-Woo Jeon ◽  
Sung-Eun Lee ◽  
...  
Keyword(s):  
Board Of Directors ◽  
Research Funding ◽  
Low Dose ◽  
Risk Group ◽  
Early Death ◽  
Initial Therapy ◽  
High Risk Group ◽  
Advisory Committees ◽  
Leukocyte Counts ◽  
Low Dose Cytarabine

Abstract Background: Acute promyelocytic leukemia (APL) is classified into a favorable-risk group and long-term overall survival (OS) is estimated at around 80%. Relapse rate of APL is lower than another acute myeloid leukemia (AML) subtypes, but we confront higher incidence of early deaths caused by fatal complications including bleeding events and differentiation syndromes (DS) during initial therapy. Recently, although arsenic trioxide (ATO) is introduced with a better survival outcome, the results were from data of low to intermediate-risk group. Thus, patients in high-risk group still show poor survival outcome with high probability of early complications and deaths. We calculated the incidence of DS and early deaths, and tried to find out affecting factors for those early events. Methods: In this single center retrospective study, 259 APL patients (median 42 years old (16-72), follow-up was 65.4 months (11.1 - 170.5) from 2002 to 2014 were analyzed. APL was diagnosed by RT-PCR method for detection of PML-RARa and all patients were available with cytogenetic results. All except 5 patients with normal karyotype was identified with t(15;17)(q22;q21) and 77 showed combination of additional karyotypes. All patients were supported with sufficient transfusion and received ATRA. Our treatment protocol was based on the modified AIDA protocol using ATRA and idarubicin monotherapy (Sanz et al. Blood. 1999; 94: 3015-21) but some patients with comorbidity were treated with ATO, low-dose cytarabine, and ATRA alone for remission induction. For hyperleukocytosis, we conducted leukapheresis when leukocyte counts exceeded 50 (x109/L) and some were treated with hydroxyurea, cytarabine and prophylactic dexamethasone. High-risk group was determined according to the Sanz criteria which presented leukocyte count > 10 (x109/L) at diagnosis. For leukocyte count, we checked diagnostic level (WBCdx) and the maximal level (WBCmax) during initial therapy and identified a group which showed a meaningful increment of WBCmax compared to WBCdx. Results: ATRA was applied in 258 patients and 217 (84.1%) were treated with idarubicin, 13 (5.0%) were with ATO, 3 (1.2%) were with low-dose cytarabine. Eight-week cumulative incidence of early death and DS was 13.5% and 17.8%, and hematological CR was identified in 222 (86.0%) patients. Five-year OS and EFS was 76.8% and 69.8%, and CIR rate was 15.7%. Six patients showed clonal evolution to therapy-related AML and 3 patients died in CR. FLT3-TKD and FLT3-ITD mutation was identified in 12 (7.3%) and 34 (20.7%) patients, and PML-RARa BCR3 and BCR1 subtype was identified in 70 (36.8%) and 120 (63.2%) patients, respectively. For leukocyte counts, except for WBCdx higher than 43 (x109/L), which showed significantly higher rate of early death and DS, patient groups with WBCdx <10 (x109/L) vs. 10 to 43 (x109/L) showed no differences regarding early death or DS. We identified that the significance of WBCdx has been changed with increment during initial therapy which revealed WBCmax was more influential. Among the patients with WBCdx <43 (x109/L), WBCmax increased higher than 43 (x109/L) was related with higher incidence of early death (35.5%) and DS (30.6%), while more DS (40%) was identified in patients with higher increment ratio from WBDdx <10 (x109/L). Multivariate analysis revealed WBCmax > 43 (x109/L) and low antithrombin III were significant for DS, while old age, WBCmax, and high D-dimer were associated with early death. In our data, dexamethasone prophylaxis did not show a preventive effect for DS or early death, while leukapheresis in patients with WBCmax >43 (x109/L) showed marginally decreased early death rate `resulting superior OS without significant bleeding complications. Conclusion: Our data revealed WBCmax with higher increment ratio was a significant predictive factor for early death and DS compared to WBCdx even in the low Sanz-risk group. The role of dexamethasone, transfusion support including antithrombin III, leukapheresis or cytoreduction should be evaluated in the specific patient subset for reducing early events in APL. Disclosures Kim: ILYANG: Consultancy, Honoraria, Research Funding; Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Novartis: Consultancy, Honoraria, Research Funding, Speakers Bureau; BMS: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau. Lee:Alexion Pharmaceuticals, Inc.: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau.

scholarly journals Evaluation of the International Prognostic Index for Chronic Lymphocytic Leukemia (CLL-IPI) and Validation of a Proposed Novel Risk Model (BALL Score) in Real-World Relapsed/Refractory (R/R) CLL Patients Receiving Idelalisib and Rituximab

Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. 5485-5485
Author(s):  
Massimo Gentile ◽  
Gianluigi Reda ◽  
Francesca Romana Mauro ◽  
Paolo Sportoletti ◽  
Luca Laurenti ◽  
...  
Keyword(s):  
High Risk ◽  
Risk Stratification ◽  
Board Of Directors ◽  
Research Funding ◽  
Advisory Board ◽  
Low Risk ◽  
Intermediate Risk ◽  
Advisory Committees ◽  
Scientific Advisory Board ◽  
Scientific Advisory

The CLL-IPI score, which combines genetic, biochemical, and clinical parameters, represents a simple worldwide model able to refine risk stratification for CLL patients. This score, developed in the era of chemo-immunotherapy, has not been gauged extensively in R/R-CLL patients treated with novel targeted agents, such as BCR and BCL2 inhibitors. Soumerai et al (Lancet Hematol 2019) assembled a novel risk model for OS in the setting of R/R-CLL receiving targeted therapies in clinical trials. This model, consisting of four accessible markers (β2M, LDH, Hb, and time from initiation of last therapy; BALL score), is able to cluster 3 groups of CLL patients with significantly different OS. This multicenter, observational retrospective study aimed to validate the proposed Soumerai (BALL) and/or CLL-IPI scores for R/R-CLL real-world patients treated with idelalisib and rituximab (IDELA-R). The primary objectives were to determine whether: i) the CLL-IPI retains its prognostic power also in R/R patients treated with IDELA-R; ii) the BALL score is of prognostic value for IDELA-treated R/R-CLL patients, and iii) the BALL score is predictive of PFS. This study, sponsored by Gilead (ISR#IN-IT-312-5339), included CLL patients collected from 12 Italian centers, who received IDELA-R (idelalisib 150 mg b.i.d. and a total of 8 rituximab infusions intravenously) outside clinical trials as salvage therapy with available data for the calculation of the CLL-IPI and BALL scores at the time of treatment start. OS was estimated for all subgroups of both scores. Additionally, risk-specific PFS was assessed. Kaplan-Meier curve, log-rank test, and Cox regression analyses were performed. The prognostic accuracy of the predictive model was assessed by Harrell's C-index. Overall, 120 CLL patients were included in this analysis. The majority of patients were Binet stage B and C (94.2%). The median age was 75 years and 83 cases (69.2%) were male. The median number of previous therapies was 3 (range 1-9) Baseline patient features are listed in Table 1. After a median follow-up of 1.6 years (1 month to 5.8 years), 33 patients had died and 39 experienced an event (death or progression). CLL-IPI scoring (115/120 evaluable cases) indicated that 6 patients (5.2%) were classified as low-risk, 24 (20.9%) as intermediate-risk, 58 (50.4%) as high-risk, and 27 (23.5%) as very high-risk. Stratification of patients according to the CLL-IPI score did not allow prediction of significant differences in OS. Thus, low-risk patients had a 2-year OS probability of 75% (HR=1), with an intermediate-risk of 68% (HR=2.9, 95%CI 0.37-23.3, P=0.3), high-risk of 83% (HR=1.58, 95%CI 0.2-12.5, P=0.66), and very high-risk of 63% (HR=5.9, 95%CI 0.78-45.2, P=0.86). Next, we tested a modified CLL-IPI by assigning a more balanced score to the original CLL-IPI variables (Soumerai et al, Leukemia Lymphoma 2019), partially overlapping previous results. Specifically, modified CLL-IPI high-risk group showed a significantly different OS as compared with intermediate- and low-risk groups. However, differently from the original report no difference was observed between low- and intermediate-risk). According to the BALL score (120/120 evaluable cases), 33 patients (27.5%) were classified as low-risk, 68 (56.7%) as intermediate-risk, and 19 (15.8%) as high-risk. Stratification of patients according to the BALL score predicted significant differences in terms of OS. Thus, low-risk patients had a 2-year OS probability of 92% (HR=1), intermediate-risk of 76% (HR=5.47, 95%CI 1.3-23.7, P=0.023), and high-risk of 54% (HR=15.1, 95%CI 3.4-67, P<0.0001) (Figure 1). Harrell's C-statistic was 0.68 (P<0.001) for predicting OS. To note, BALL score failed to significantly stratify patients in terms of PFS. As for Soumerai et al (Leukemia Lymphoma 2019), the original CLL-IPI score did not retain discriminative power in term of OS in R/R-CLL patients receiving IDELA-R. The modified CLL-IPI failed to stratify low- and intermediate-risk groups, likely due to the number of cases analysed in the current cohort and the heterogeneous IDELA-containing regimens included in the Soumerai study (Soumerai et al, Leukemia Lymphoma 2019). The CLL-IPI was designed for CLL patients treated with first-line chemo-immunotherapy. Herein, we confirm the prognostic power of the BALL score in this real-world series for OS, while losing the predictive impact of patient outcomes in terms of PFS. Disclosures Mauro: Gilead: Consultancy, Research Funding; Jannsen: Consultancy, Research Funding; Shire: Consultancy, Research Funding; Abbvie: Consultancy, Research Funding; Roche: Consultancy, Research Funding. Coscia:Abbvie: Membership on an entity's Board of Directors or advisory committees; Gilead: Membership on an entity's Board of Directors or advisory committees; Karyopharm Therapeutics: Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding. Varettoni:ABBVIE: Other: travel expenses; Roche: Consultancy; Janssen: Consultancy; Gilead: Other: travel expenses. Rossi:Gilead: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Abbvie: Honoraria, Other: Scientific advisory board; Janseen: Honoraria, Other: Scientific advisory board; Roche: Honoraria, Other: Scientific advisory board; Astra Zeneca: Honoraria, Other: Scientific advisory board. Gaidano:AbbVie: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Sunesys: Consultancy, Honoraria; Astra-Zeneca: Consultancy, Honoraria; Janssen: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau.

Comparison Of Conventional, FISH and GEP Prognostic Factors In Multiple Myeloma: Introducing a Novel Risk Stratification

Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 3092-3092 ◽  
Author(s):  
Rowan Kuiper ◽  
Martin van Vliet ◽  
Annemiek Broyl ◽  
Yvonne de Knegt ◽  
Bronno van der Holt ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Prognostic Factors ◽  
High Risk ◽  
Board Of Directors ◽  
Research Funding ◽  
Low Risk ◽  
Partial Likelihood ◽  
Data Sets ◽  
Advisory Committees ◽  
Risk Patients

Abstract Introduction Multiple Myeloma (MM) is a heterogeneous disease with highly variable survival. Gene expression profiling (GEP) classifiers, such as the EMC-92, can consistently distinguish high risk patients from standard risk patients. Other prognostic factors for MM include the international staging system (ISS) and FISH. Here we present a comparison of prognostic factors and introduce a novel stratification based on EMC-92 and ISS. Methods Scores were calculated for the GEP classifiers EMC-92, UAMS-70, UAMS-17, UAMS-80 and MRC-IX-6 for the following five studies: HOVON-65/GMMG-HD4 (n=328; GSE19784), MRC-IX (n=247; GSE15695), UAMS-TT2 (n=345; GSE2658), UAMS-TT3 (n=238; E-TABM-1138 and GSE2658) and APEX (n=264; GSE9782; for details, see Kuiper R, et al. Leukemia (2012) 26: 2406–2413). FISH data were available for the HOVON-65/GMMG-HD4 trial and the MRC-IX trial. ISS values were available for all datasets except UAMS-TT2. Univariate associations between markers and overall survival (OS) were investigated in a Cox regression analysis, using Bonferroni multiple testing correction. For pair wise analysis of markers, the significance in the increase of partial likelihood was calculated. In order to find the strongest combination (defined as the highest partial likelihood) of GEP-ISS, we compared these pair-wise on the same data. Training sets of classifiers were excluded for those analyses in which that specific classifier was tested. All survival models have been stratified for study. The calculations were done in R using the package survival. Results Prognostic value of FISH, GEP and serum markers was determined in relation to overall survival (Figure 1). GEP classifiers generally performed much better than FISH markers. Of 6 FISH markers with known adverse risk, del(17p), t(4;14), t(14;20) and del(13q) demonstrated a significant association only in one of two data sets with available FISH (HOVON-65/GMMG-HD4). GEP classifiers, on the other hand, are much more robust. Classifiers EMC-92, UAMS-70 and UAMS-80 significantly identify a high-risk population in all evaluated data sets, whereas the UAMS-17 and the MRC-IX-6 classifiers predict high-risk patients in three of four datasets. As expected, ISS staging demonstrated stable and significant hazard ratios in most studies (three out of four). Indeed, when evaluating a merged data set, both ISS and all evaluated GEP classifiers are strong prognostic factors independent of each other. Markers with additive value to each other include all combinations of GEP classifiers as well as the combination of GEP classifiers together with ISS. Tested in independent sets, the EMC-92 classifier combined with ISS is the best combination, as compared to other classifier-ISS combinations tested on the same independent data sets. The strongest risk stratification in 3 groups was achieved by splitting the EMC-92 standard risk patients into low risk, based on ISS stage I, and intermediate risk, based on ISS stage II and III. This stratification retains the original EMC-92 high-risk group, and is robust in all cohorts. The proportions of patients defined as low, intermediate and high risk for this combined EMC-92-ISS classifier are 31% / 47% / 22 % (HOVON-65/GMMG-HD4), 19% / 61% / 20 % (MRC-IX), 46% / 39% / 15 % (UAMS-TT3) and 32% / 55% / 13 % (APEX). Variability in low risk proportion is caused by the variable incidence of ISS stage I. Conclusions We conclude that GEP is the strongest predictor for survival in multiple myeloma and far more robust than FISH. Adding ISS to EMC-92 results in the strongest combination of any of the GEP classifier-ISS combinations. Stratification in low risk, intermediate and high risk may result in improved treatment and ultimately in longer survival of MM patients. This research was supported by the Center for Translational Molecular Medicine (BioCHIP project) Disclosures: van Vliet: Skyline Diagnostics: Employment. Mulligan:Millennium Pharmaceuticals: Employment. Morgan:Celgene: Consultancy, Honoraria, Membership on an entity’s Board of Directors or advisory committees; Millenium: Consultancy, Honoraria, Membership on an entity’s Board of Directors or advisory committees; Novartis: Consultancy, Honoraria, Membership on an entity’s Board of Directors or advisory committees; Merck: Consultancy, Honoraria, Membership on an entity’s Board of Directors or advisory committees; Johnson and Johnson: Consultancy, Honoraria, Membership on an entity’s Board of Directors or advisory committees. Goldschmidt:Celgene: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria, Research Funding; Novartis: Consultancy, Honoraria, Research Funding. Lokhorst:Genmab A/S: Consultancy, Research Funding; Celgene: Honoraria; Johnson-Cilag: Honoraria; Mudipharma: Honoraria. van Beers:Skyline Diagnostics: Employment. Sonneveld:Janssen-Cilag: Honoraria; Celgene: Honoraria; Onyx: Honoraria; Janssen-Cilag: Research Funding; Millenium: Research Funding; Onyx: Research Funding; Celgene: Research Funding.

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