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

Blood ◽  
2014 ◽  
Vol 124 (21) ◽  
pp. 2106-2106 ◽  
Author(s):  
Jatin J. Shah ◽  
Rafat Abonour ◽  
Brian G M Durie ◽  
Jayesh Mehta ◽  
Mohit Narang ◽  
...  
Keyword(s):  
Risk Factors ◽  
Overall Survival ◽  
African American ◽  
High Risk ◽  
Board Of Directors ◽  
Interim Analysis ◽  
Research Funding ◽  
Advisory Committees ◽  
Kaplan Meier ◽  
High Risk Disease

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

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

Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 1222-1222
Author(s):  
Kee Yon, Lionel See ◽  
Kok Chong Bernard Yap ◽  
Dong-Wook Kim ◽  
Hein Than ◽  
Yeow-Tee Goh
Keyword(s):  
Risk Factors ◽  
High Risk ◽  
Board Of Directors ◽  
Research Funding ◽  
Chronic Phase ◽  
Progression Free Survival ◽  
P Value ◽  
Survival Curves ◽  
Advisory Committees ◽  
Kaplan Meier

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

scholarly journals Prognostic Implications of Multiple Cytogenetic High-Risk Abnormalities in Patients with Newly Diagnosed Multiple Myeloma

Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 5615-5615
Author(s):  
Moritz Binder ◽  
S. Vincent Rajkumar ◽  
Rhett P. Ketterling ◽  
Angela Dispenzieri ◽  
Martha Q. Lacy ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Overall Survival ◽  
High Risk ◽  
Board Of Directors ◽  
Research Funding ◽  
Cumulative Effect ◽  
Newly Diagnosed ◽  
Advisory Committees ◽  
Kaplan Meier ◽  
Prognostic Implications

Abstract Background: Cytogenetic evaluation using fluorescence in situ hybridization (FISH) at the time of diagnosis is essential for initial risk stratification in multiple myeloma. The presence of specific cytogenetic abnormalities is known to confer a poor prognosis, less is known about the cumulative effect of multiple cytogenetic high-risk abnormalities. We aimed to evaluate the prognostic implications of the presence of multiple cytogenetic high-risk abnormalities at the time of diagnosis. Methods: We studied 226 patients who were diagnosed with multiple myeloma between July 2004 and July 2014 at Mayo Clinic Rochester, underwent FISH evaluation within six months of diagnosis, and presented with cytogenetic high-risk abnormalities. High-risk cytogenetics were defined as t(4;14), t(14;16), t(14;20), del(17p), or gain(1q). Bone marrow aspirates were evaluated for deletions, monosomies, trisomies, and tetrasomies using chromosome- or centromere-specific FISH probes. IGH rearrangements were evaluated using an IGH break-apart probe and evaluating up to five potential partners (FGFR3, CCND1, CCND3, MAF, and MAFB). Kaplan-Meier overall survival estimates were calculated and the log-rank test was used to compare overall survival in patients with single and multiple cytogenetic high-risk abnormalities. A multivariable-adjusted Cox regression model was used to assess the effect of multiple cytogenetic high-risk abnormalities on overall survival adjusting for age, sex, and Revised International Staging System (R-ISS) stage. P-values below 0.05 were considered statistically significant. Results: The median age at diagnosis was 65 years (32 - 90), 129 (57%) of the patients were male. The median overall survival was 3.5 years (3.1 - 4.9) for the entire cohort (n = 226), 4.0 years (3.3 - 5.1) for those with one cytogenetic high-risk abnormality (n = 182, 80%), and 2.6 years (1.7 - 3.1) for those with two cytogenetic high-risk abnormalities (n = 44, 20%). There were no patients with more than two cytogenetic high-risk abnormalities. Ninety-eight patients (45%) had a high-risk translocation, 77 (35%) had del(17p), 39 (18%) had a high-risk translocation plus del(17p), and 5 (2%) had gain(1q) plus either a high-risk translocation or del(17p). Figure 1 shows the Kaplan-Meier overall survival estimates stratified by the number of cytogenetic high-risk abnormalities (n = 226). The presence of two cytogenetic high-risk abnormalities (compared to one) was of prognostic significance after adjusting for age, sex, and R-ISS stage (HR 2.01, 95% CI 1.27 - 3.19, p = 0.003, n = 205). Conclusions: Approximately one in five patients with newly diagnosed high-risk multiple myeloma presented with two high-risk abnormalities at the time of diagnosis. These patients experienced inferior overall survival suggesting a cumulative effect of multiple cytogenetic high-risk abnormalities. The relatively low number of observed gain(1q) was likely related to the fact that not all patients were evaluated for that abnormality. Therefore the presented hazard ratio represents a conservative effect estimate and may underestimate the true effect. Figure 1 Figure 1. Disclosures Dispenzieri: GSK: Membership on an entity's Board of Directors or advisory committees; Jannsen: Research Funding; Alnylam: Research Funding; Celgene: Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; Prothena: Membership on an entity's Board of Directors or advisory committees; pfizer: Research Funding. Kapoor:Takeda: Research Funding; Celgene: Research Funding; Amgen: Research Funding. Kumar:Janssen: Consultancy, Research Funding; BMS: Consultancy; AbbVie: Research Funding; Millennium: Consultancy, Research Funding; Onyx: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Sanofi: Consultancy, Research Funding; Skyline: Honoraria, Membership on an entity's Board of Directors or advisory committees; Array BioPharma: Consultancy, Research Funding; Noxxon Pharma: Consultancy, Research Funding; Kesios: Consultancy; Glycomimetics: Consultancy.

Integrative Network Analysis of Newly Diagnosed Multiple Myeloma Identifies a Novel RNA-Seq Based High Riskgene Signature

Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 3285-3285
Author(s):  
Alessandro Lagana ◽  
Deepak Perumal ◽  
David Melnekoff ◽  
Ben Readhead ◽  
Brian Kidd ◽  
...  
Keyword(s):  
Overall Survival ◽  
High Risk ◽  
Board Of Directors ◽  
Research Funding ◽  
Newly Diagnosed ◽  
Advisory Committees ◽  
Free Survival ◽  
Kaplan Meier ◽  
Risk Patients ◽  
Equity Ownership

Abstract High-risk Multiple Myeloma (MM) is characterized by unresponsiveness to multiple therapies, rapid disease progression and short overall survival, and may be significantly different from relapsed MM, where aggressiveness is usually a result of drug-resistance associated to clonal selection. Several gene expression-based signatures have been proposed in the past years, however the identification of high-risk patients at diagnosis still represents a challenge. Next generation high-throughput sequencing technologies have enabled a deeper insight into cancer genomes and transcriptomes at an unprecedented level of detail. MMRF CoMMpass is a longitudinal, prospective observational study, started in 2011, that aims to collect and analyze sequencing and clinical data from >1,000 MM patients at initial diagnosis and at relapse. CoMMpass is a real world observational study and, as such, reflects the therapeutic heterogeneity seen across patient populations and provides a unique opportunity to correlate molecular profiles, genomic alterations and clinical characteristics of MM with treatment outcome. Here we present a network approach to identify high-risk myeloma patients developed using next generation sequencing data from 450 patients in the IA7 release of CoMMpass. We generated MMNet, an integrated network model of newly diagnosed myeloma based on RNA-seq, Whole-Exome (WXS) and Whole-Genome (WGS) data correlated with clinical outcomes. MMNet consisted of 37 modules of coexpressed genes, that were further characterized by functional enrichment analysis and correlation with clinical traits and genomic alterations, i.e. somatic mutations and copy number alterations inferred from WGS and WXS data. A total of 89 progression/death events have been reported for the cohort within the second year since the beginning of the study. Cox regression analysis identified a module of co-expressed genes whose over-expression was significantly correlated with early relapse (<2yr) (HR 1.75, 95%CI = 1.169-2.614, p=0.005). The module was also associated to stage III R-ISS, high clonality (>4 clones) and high mutational burden, as well as higher percentage of plasma cells in both bone marrow and peripheral blood, which are traits associated with high-risk disease. Module expression was also up regulated in patients with mutations in TP53 and MAX, 13q deletion and 1q amplification. We further narrowed down the signature to 286 genes (the MMNet-286 signature) strongly correlated with time to Event Free Survival (EFS) (r = -0.81, p = 0). This gene-set was significantly enriched for several pathways including Cell Cycle, DNA repair and Homologous Recombination (q < 0.01). Cox regression analysis showed that the two clusters induced by MMNet-286 discriminated between lower and higher risk patients with respect to EFS (HR = 2.22, 95% CI = 1.505-3.295, p = 4.007e-5) (Fig. 1). The prognostic value of MMNet-286 was confirmed on two independent datasets: Broyl-2010 (HR = 1.76, 95% CI = 1.182-2.642, p = 0.005) and Shaughnessy-2006 (HR = 2.65, 95% CI = 1.746-4.031, p = 2.03e-6) (Fig. 2 and 3). The Broyl-2010 dataset consisted of 275 samples from newly diagnosed myeloma patients included in the HOVON65/GMMG-HD4 trial (GSE19784). The Shaughnessy-2006 dataset consisted of 559 samples from newly diagnosed patients pre-TT2 and -TT3 treatments (GSE2658). Comparison of MMNet-286 with previous high risk signatures and disease classes revealed an overlap of five genes with the UAMS-70 signature, twelve genes with the EMC-92 signature and fifteen genes with the set of up-regulated genes in the UAMS PR class, for which the coexpression module was enriched. In Conclusion, our results demonstrate the advantages of employing integrated network models to identify prognostic features based on next generation sequencing data from large cohort of patients. Applications of the MMNet-286 signature include the generation of a prognostic assay (i.e. NanoString) for the identification of high-risk patients. Future work will aim at validation of the signature in larger cohorts from CoMMpass and other studies. Figure 1 Kaplan-Meier curves of event free survival in the MMRF cohort stratified by the MMNet-286 signature. Figure 1. Kaplan-Meier curves of event free survival in the MMRF cohort stratified by the MMNet-286 signature. Figure 2 Kaplan-Meier curves of overall survival in the Broyl cohort stratified by the MMNet-286 signature. Figure 2. Kaplan-Meier curves of overall survival in the Broyl cohort stratified by the MMNet-286 signature. Figure 3 Kaplan-Meier curves of overall survival in the Shaughnessy cohort stratified by the MMNet-286 signature. Figure 3. Kaplan-Meier curves of overall survival in the Shaughnessy cohort stratified by the MMNet-286 signature. Disclosures Chari: Novartis: Consultancy, Research Funding; Array Biopharma: Consultancy, Research Funding; Pharmacyclics: Research Funding; Amgen Inc.: Honoraria, Research Funding; Celgene: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Takeda: Consultancy, Research Funding. Cho:Genentech Roche: Membership on an entity's Board of Directors or advisory committees, Research Funding; Bristol-Myers Squibb: Membership on an entity's Board of Directors or advisory committees, Research Funding; Agenus, Inc.: Research Funding; Ludwig Institute for Cancer Research: Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy, Research Funding. Barlogie:Signal Genetics: Patents & Royalties. Dudley:GlaxoSmithKline: Consultancy; Janssen Pharmaceuticals, Inc.: Consultancy; Ayasdi, Inc.: Equity Ownership; Ecoeos, Inc.: Equity Ownership; NuMedii, Inc.: Equity Ownership; Ontomics, Inc.: Equity Ownership; AstraZeneca: Speakers Bureau; NuMedii, Inc.: Patents & Royalties; Personalis: Patents & Royalties.

scholarly journals Overall Survival and Subgroup Analysis from a Randomized Phase III Study of Intravenous Rigosertib Versus Best Supportive Care (BSC) in Patients (pts) with Higher-Risk Myelodysplastic Syndrome (HR-MDS) after Failure of Hypomethylating Agents (HMAs)

Blood ◽  
2014 ◽  
Vol 124 (21) ◽  
pp. 163-163 ◽  
Author(s):  
Guillermo Garcia-Manero ◽  
Pierre Fenaux ◽  
Aref Al-Kali ◽  
Maria R. Baer ◽  
Mikkael A. Sekeres ◽  
...  
Keyword(s):  
Overall Survival ◽  
High Risk ◽  
Board Of Directors ◽  
Primary Endpoint ◽  
Research Funding ◽  
Phase Iii ◽  
Controlled Study ◽  
Advisory Committees ◽  
Phase Iii Study ◽  
Very High

Abstract Background: No approved treatment options are available to HR-MDS pts after HMA therapy. Study 04-21 (“ONTIME” trial) was a Phase III, randomized, controlled study of the efficacy and safety of rigosertib, a novel small molecule inhibitor of PI3-kinase and PLK pathways, in a heterogeneous population of MDS pts who had relapsed after, failed to respond to, or progressed during administration of HMAs. The study was conducted at 87 sites in the United States and 5 European countries. Methods:From Dec 2010 to Aug 2013, 299 HR-MDS pts [<30% bone marrow blasts (BMBL)] who had progressed on (37% of total enrollment), failed to respond to (25%), or relapsed after (38%) HMA treatment were stratified on BMBL count and randomized 2:1 to receive rigosertib (199 pts) or BSC (100 pts). Rigosertib was administered at 1800 mg/24 hr for 72-hr as a continuous intravenous (CIV) ambulatory infusion, every 2 weeks for the first 16 weeks, and then every 4 weeks. The primary endpoint was overall survival (OS), analyzed on an intention-to-treat (ITT) basis using the Kaplan-Meier method stratified on BMBL (5% to 19% vs. 20% to 30%). The trial had a 95% power to detect a 13-wk increase in median OS from 17 wks on BSC, with a 2-sided alpha = 0.05. The following results are based on 242 deaths: 161 in the rigosertib arm and 81 in the BSC arm. Results : Overall, the 2 arms were balanced in terms of baseline characteristics, with the majority of pts being male (66%), and White (82%). Age ranged from 50-90 yrs in the rigosertib arm and 55-86 years in the BSC arm (median, 74 yrs). The majority of pts (85%) had an Eastern Cooperative Oncology Group (ECOG) score of 0 or 1. The median duration of the last HMA therapy was 8.8 months (mo) in the rigosertib arm and 10.3 mo in the BSC arm; 127 (64%) of rigosertib pts and 57% of BSC pts were classified as “primary HMA failure” (ie, they failed to respond to or progressed during HMA therapy, as defined by Prebet et al, J Clin Oncol, 2011). A 2.3-mo improvement in median OS was found in the overall (ITT) population (8.2 mo rigosertib vs. 5.9 mo BSC) (Figure 1). The ITT survival for rigosertib was similar to that noted in Phase I/II studies (35 weeks). The stratified log-rank p-value was 0.33. The stratified hazard ratio was 0.87, which was quite different from the ratio of medians (5.9/8.2 = 0.72), due to the fact that the 2 survival curves converged at 15 mo. Notably, among the 184 patients with primary HMA failure, the median OS was 8.6 mo in the rigosertib arm (N = 127) vs. 5.3 mo in the BSC arm (N = 57), HR= 0.69, p= 0.040 (Figure 2). Multivariate Cox regression, adjusting for pretreatment prognostic factors, showed little change in the treatment effect. The following subgroups were correlated with better OS: pts with failure of/progression on HMA treatment, pts with duration of HMA treatment ≤ 9 mo, pts < 75 years of age, and pts with very high risk per IPSS-R (Figure 3). Rigosertib was well tolerated, with a median dose intensity of 92%. There were no significant compliance or operations issues related to ambulatory continuous infusion. Protocol-defined dose reductions were reported in 5% of pts, with 24% experiencing dose delays of >7 days, mostly due to unrelated adverse events (AEs). No obvious differences between rigosertib and BSC were found in the incidence of AEs (rigosertib, 99%; BSC, 85%) or of ≥ Grade 3 AEs (rigosertib, 79%; BSC, 68%). In the rigosertib arm, AEs reported by ≥ 20% of pts, irrespective of severity or causality, were nausea (35%), diarrhea (33%), constipation (31%), fatigue (30%), fever (27%), anemia (22%), and peripheral edema (21%). Rigosertib had low myelotoxicity, consistent with previous clinical experience. Conclusions:Although the primary endpoint in this Phase III study of rigosertib vs BSC in pts with HR-MDS did not reach statistical significance in the ITT population, encouraging rigosertib treatment-related improvement in OS was noted in several subgroups of MDS pts, including those with “primary HMA failure and in patients in the IPSS-R Very High Risk category. CIV therapy with rigosertib had a favorable safety profile in this orphan population of elderly pts with MDS. Figure 1 Figure 1. Figure 2 Figure 2. Figure 3 Figure 3. Disclosures Fenaux: Celgene: Research Funding; Janssen: Research Funding; Novartis: Research Funding. Sekeres:Celgene Corp.: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees; Boehringer Ingelheim: Membership on an entity's Board of Directors or advisory committees. Roboz:Novartis: Consultancy; Agios: Consultancy; Celgene: Consultancy; Glaxo SmithKline: Consultancy; Astra Zeneca: Consultancy; Sunesis: Consultancy; Teva Oncology: Consultancy; Astex: Consultancy. Wilhelm:Onconova Therapeutics, Inc: Employment, Equity Ownership. Wilhelm:Onconova Therapeutics, Inc: Employment. Azarnia:Onconova Therapeutics, Inc: Employment. Maniar:Onconova Therapeutics, Inc: Employment.

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 Identifying Ultra-High Risk Smoldering Multiple Myeloma

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 3192-3192 ◽  
Author(s):  
Theresia Akhlaghi ◽  
Even H Rustad ◽  
Venkata D Yellapantula ◽  
Neha Korde ◽  
Sham Mailankody ◽  
...  
Keyword(s):  
Risk Factors ◽  
High Risk ◽  
Board Of Directors ◽  
Research Funding ◽  
Advisory Committees ◽  
Ultra High Risk ◽  
Risk Of Progression ◽  
Equity Ownership ◽  
M Spike ◽  
Risk Biomarkers

Abstract Introduction Smoldering multiple myeloma (SMM) is an asymptomatic precursor stage to active multiple myeloma (MM), comprised by a heterogenous group of patients with varying rates of progression. While the overall yearly progression rate is 10% the first 5 years, some patients progress at a considerably higher rate. A study from the Mayo Clinic showed that in a subset of 21 patients defined by ≥60% monoclonal bone marrow plasma cells (BMPC), 95% progressed within 2 years. It was subsequently concluded by the International Myeloma Working Group (IMWG) that patients with biomarkers predictive of a 2-year progression rate at 80%, and a median time to progression at 12 months were at ultra-high risk of progression and should be considered to have MM requiring treatment despite being asymptomatic. In 2014, ultra-high risk biomarkers were incorporated in the definition of MM, including BMPC ≥60%, free light chain (FLC) ratio ≥100 and ≥2 focal lesions on magnetic resonance imaging (MRI). While the updated myeloma definition changed the diagnosis of some patients with ultra-high risk SMM to MM, there remain patients classified as SMM progressing at a very high rate. In the present study, we aimed at further identifying ultra-high risk biomarkers predictive of a high rate of progression to active MM. Methods Patients with SMM presenting to Memorial Sloan Kettering Cancer Center between the years 2000 and 2017 were identified and included in the study. Diagnosis of SMM and progression to MM requiring therapy was defined according to the IMWG criteria at the time of diagnosis. Baseline patient and disease characteristics were collected at date of diagnosis with SMM, including pathology reports, laboratory results and imaging data. Time to progression (TTP) was assessed using the Kaplan-Meier method with log-rank test for comparisons. Optimal cut-off values for continuous variables were assessed with receiver operating characteristics (ROC) curve. Patients who had not progressed by the end of study or were lost to follow up were censored at the date of last visit. Univariate Cox regression was used to estimate risk factors for TTP with hazard ratios (HR) and 95% confidence intervals (CI). Significant univariate risk factors were selected for multivariate Cox regression. Results A total of 444 patients were included in the study. Median follow-up time was 78 months. During the study period, 215 (48%) patients progressed to active MM, with a median TTP of 72 months. Cut-off points for BMPC, M-spike, and FLC ratio were determined with ROC curves to be 20%, 2 g/dL, and 18, respectively, for predicting high risk of progression. The following factors were associated with significantly increased risk of progression to active MM: BMPC >20%, M-spike >2g/dL, FLC ratio >18, immunoparesis with depression of 1 and 2 uninvolved immunoglobulins respectively, elevated lactate dehydrogenase, elevated beta-2-microglobulin, and low albumin (Table 1). In the multivariate model, BMPC >20% (HR 2.5, 95% CI 1.6-3.9), M-spike >2g/dL (HR 3.2, CI 1.9-5.5), FLC ratio >18 (HR 1.8, CI 1.1-3.0), albumin <3.5 g/dL (HR 3.9, CI 1.5-10.0), and immunoparesis with 2 uninvolved immunoglobulins (HR 2.3, CI 1.2-4.3), predicted a decreased TTP (Table 1). A total of 12 patients had 4 or 5 of the risk factors from the multivariate model, 8 of these did not meet the 2014 IMWG criteria for MM. These patients had a significantly shorter TTP than patients with less than 4 risk factors (median TTP 11 vs 74 months, p<0.0001, Figure 1). At 16 months, 82% of these patients had progressed, and within 2 years, 91% of the patients progressed. Only one patient remained progression free after 2 years, progressing at 31 months. Of patients with less than 4 risk factors, 19% progressed within the first 2 years. Conclusion In addition to baseline BMPC >20%, M-spike >2g/dL, FLC-ratio >18, we found that albumin <3.5g/dL and immunoparesis of both uninvolved immunoglobulins at the time of diagnosis with SMM were highly predictive of a decreased TTP to MM requiring therapy. These biomarkers are readily available and routinely assessed in clinic. Patients with 4 or 5 of these risk factors represent a new ultra-high risk group that progress to active disease within 2 years, further expanding on the definition of ultra-high risk SMM. In accordance with the rationale on ultra-high risk biomarkers as criteria established by the IMWG in 2014, such patients should be considered to have MM requiring therapy. Disclosures Korde: Amgen: Research Funding. Mailankody:Janssen: Research Funding; Takeda: Research Funding; Juno: Research Funding; Physician Education Resource: Honoraria. Lesokhin:Squibb: Consultancy, Honoraria; Serametrix, inc.: Patents & Royalties: Royalties; Takeda: Consultancy, Honoraria; Genentech: Research Funding; Bristol-Myers Squibb: Consultancy, Honoraria, Research Funding; Janssen: Research Funding. Hassoun:Oncopeptides AB: Research Funding. Smith:Celgene: Consultancy, Patents & Royalties: CAR T cell therapies for MM, Research Funding. Shah:Amgen: Research Funding; Janssen: Research Funding. Mezzi:Amgen: Employment, Equity Ownership. Khurana:Amgen: Employment, Equity Ownership. Braunlin:Amgen: Employment. Werther:Amgen: Employment, Equity Ownership. Landgren:Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Karyopharm: Consultancy; Merck: Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy, Research Funding; Pfizer: Consultancy; Celgene: Consultancy, Research Funding.

scholarly journals Treatment Outcomes of Real Life Elderly Multiple Myeloma Patients:Â Analysis from Registry of Monoclonal Gammopathies (RMG)

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 2019-2019
Author(s):  
Jakub Radocha ◽  
Roman Hajek ◽  
Lucie Brozova ◽  
Ludek Pour ◽  
Ivan Spicka ◽  
...  
Keyword(s):  
Risk Factors ◽  
Multiple Myeloma ◽  
Overall Survival ◽  
Treatment Outcomes ◽  
Board Of Directors ◽  
Research Funding ◽  
Statistical Significance ◽  
Real Life ◽  
Advisory Committees ◽  
Monoclonal Gammopathies

Abstract Introduction: Multiple myeloma patients over the age of 65 represent the majority of myeloma population. The main goal was to evaluate treatment outcomes in terms of overall survival for elderly patients based on initial choice of anti-myeloma drugs, and to find potential factors affecting survival. Patients and Methods: This is a retrospective registry based analysis from the Registry of monoclonal gammopathies of the Czech Myeloma Group. Patients with multiple myeloma diagnosed between 2007-2016 over the age of 65 with symptomatic myeloma were included in the analysis. Basic demographic data and disease characteristics were obtained. The Kaplan-Meier estimates were completed by the Greenwood confidence interval. The log-rank test was used to estimate the statistical significance of the difference between the curves. The Cox proportional hazards model was performed to explore the univariate significance of risk factors. Results: Data from 1410 MM patients were obtained. Gender [HR 1.316 (1.124-1.541), p=0.001], age [above 75 vs. 66-75, HR 1.437 (1.221-1.692), p< 0.001], creatinine levels [at cutoff 152 µmol/L, HR 1.613 (1.365-1.905), p< 0.001] and ECOG performance status [0-1 vs. 2-4, 1.869 (1.594-2.191), p< 0.001] were found to significantly affect overall survival. Moreover these risk factors have cumulative effect on overall survival of the patients. Overall survival of patients regardless to above mentioned risk factors treated with upfront bortezomib (N = 880) was median OS 40.4 months (CI: 36.1-44.7), patients treated with upfront thalidomide (N = 370) had median OS 48.1 months (CI: 41.0-55.2), for lenalidomide (N = 64) median overall survival was 53.2 months (CI: 44.6-61.8) and for combination of bortezomib and thalidomide (N = 46) 32.2 months (CI: 26.6-37.8). When any of these risk factors was present the OS in each group shortened. In the group of patients with no risk factors (N = 255) the median OS for bortezomib (N = 126) was not reached, for thalidomide (N = 96) the median OS was 66.3 months (CI: 43.1-89.6), for lenalidomide (N = 17) 71.1 months (CI: 44.8-97.4) and for combination of bortezomib and thalidomide (N=8) was not reached. In the group of patients with 1 risk factor (N = 514) the median OS for bortezomib (N = 303) was 46.1 months (CI: 36.2-56.1), for thalidomide (N = 141) 56.2 months (CI: 47.5-64.9), for lenalidomide (N = 29) 49.0 months (CI: 9.7-88.2) and for combination of bortezomib and thalidomide (N=20) was not reached. In the group of patients with 2 risk factors (N = 420) the median OS for bortezomib (N = 288) was 34.0 months (CI: 24.7-43.4), for thalidomide (N = 87) 31.9 months (CI: 22.8-40.9), for lenalidomide (N = 14) 33.2 months (CI: 0.0-67.6) and for combination of bortezomib and thalidomide (N=20) 29.4 months (CI: 7.6-51.1). In the group of patients with 3-4 risk factors (N = 221) the median OS for bortezomib (N = 163) was 19.2 months (CI: 14.9-23.5), for thalidomide (N = 46) 18.9 months (CI: 13.0-24.7), for lenalidomide (N = 4) 6.1 months (CI: 0.0-63.0) and for combination of bortezomib and thalidomide (N=3) 14.3 months (CI:-). Conclusion: The overall survival of patients above the age of 65 shows promising results with the use of novel agents. The treatment outcomes seem to be generally affected by overall condition, age and gender of the patient rather than treatment modality used upfront. Figure. Figure. Disclosures Hajek: Amgen: Consultancy, Honoraria, Research Funding; Bristol Myers Squibb: Consultancy, Honoraria; Takeda: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Novartis: Research Funding. Maisnar:Amgen: 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; Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees.

scholarly journals Bortezomib, Lenalidomide and Dexamethasone (VRD) Followed By Autologous Stem Cell Transplant for Newly Diagnosed Multiple Myeloma; The Mayo Clinic Experience

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 2147-2147
Author(s):  
M Hasib Sidiqi ◽  
Mohammed A Aljama ◽  
Angela Dispenzieri ◽  
Eli Muchtar ◽  
Francis K. Buadi ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Overall Survival ◽  
High Risk ◽  
Maintenance Therapy ◽  
Board Of Directors ◽  
Mayo Clinic ◽  
Research Funding ◽  
Advisory Committees ◽  
Post Transplant ◽  
Standard Risk

Abstract We retrospectively reviewed all patients receiving bortezomib, lenalidomide and dexamethasone induction followed by autologous stem cell transplantation (ASCT) within 12 months of diagnosis for multiple myeloma at the Mayo Clinic. 243 patients treated between January 2010 and April of 2017 were included in the study. Median age was 61 (interquartile range, 55-67) with 62% of patients being male. High risk cytogenetic abnormalities (HRA) were present in 34% of patients. 166 (68%) patients received some form of maintenance/other therapy post transplant (no maintenance (NM, n=77), lenalidomide maintenance (LM, n=108), bortezomib maintenance (BM, n=39) and other therapy (OT, n=19)). Overall response rate was 99% with complete response (CR) rate of 42% and 62% at day 100 and time of best response post transplant respectively. The four cohorts categorized by post transplant therapy were well matched for age, gender and ISS stage. HRA were more common amongst patients receiving bortezomib maintenance or other therapy post transplant (NM 18% vs LM 22% vs BM 68% vs OT 79%, p<0.0001). Two year and five year overall survival rates were 90% and 67% respectively with an estimated median overall survival (OS) and progression free survival (PFS) of 96 months and 28 months respectively for the whole cohort. OS was not significantly different when stratified by post-transplant therapy (Median OS 96 months for NM vs not reached for LM vs 62 months for BM vs not reached for OT, p=0.61), however post-transplant therapy was predictive of PFS (median PFS 23 months for NM vs 34 months for LM vs 28 months for BM vs 76 months for OT, p=0.01). High risk cytogenetics was associated with a worse OS but not PFS when compared to patients with standard risk (median OS: not reached for standard risk vs 60 months for HRA, p=0.0006; median PFS: 27 months for standard risk vs 22 months for HRA, p=0.70). In patients that did not receive maintenance therapy presence of HRA was a strong predictor of OS and PFS (median OS: not reached for standard risk vs 36 months for HRA, p<0.0001; median PFS: 24 months for standard risk vs 7 months for HRA, p<0.0001). Patients receiving maintenance therapy appeared to have a similar PFS and OS irrespective of cytogenetics (median OS: not reached for standard risk vs 62 months for HRA, p=0.14; median PFS: 35 months for standard risk vs 34 months for HRA, p=0.79).On multivariable analysis ISS stage III and achieving CR/stringent CR predicted PFS whilst the only independent predictors of OS were presence of HRA and achieving CR/stringent CR. The combination of bortezomib, lenalidomide and dexamethasone followed by ASCT is a highly effective regimen producing deep and durable responses in many patients. Maintenance therapy in this cohort may overcome the poor prognostic impact of high risk cytogenetic abnormalities. Table Table. Disclosures Dispenzieri: Celgene, Takeda, Prothena, Jannsen, Pfizer, Alnylam, GSK: Research Funding. Lacy:Celgene: Research Funding. Dingli:Alexion Pharmaceuticals, Inc.: Other: Participates in the International PNH Registry (for Mayo Clinic, Rochester) for Alexion Pharmaceuticals, Inc.; Millennium Takeda: Research Funding; Millennium Takeda: Research Funding; Alexion Pharmaceuticals, Inc.: Other: Participates in the International PNH Registry (for Mayo Clinic, Rochester) for Alexion Pharmaceuticals, Inc.. Kapoor:Celgene: Research Funding; Takeda: Research Funding. Kumar:KITE: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding. Gertz:Abbvie: Consultancy; Apellis: Consultancy; annexon: Consultancy; Medscape: Consultancy; celgene: Consultancy; Prothena: Honoraria; spectrum: Consultancy, Honoraria; Amgen: Consultancy; janssen: Consultancy; Ionis: Honoraria; Teva: Consultancy; Alnylam: Honoraria; Research to Practice: Consultancy; Physicians Education Resource: Consultancy.

scholarly journals The Combination of Frailty and ISS Scores Identifies a Simple Prognostic Index for Overall Survival in Elderly Patients Treated with Novel Agents-Based Induction Therapy

Blood ◽  
2014 ◽  
Vol 124 (21) ◽  
pp. 4740-4740
Author(s):  
Alessandra Larocca ◽  
Sara Bringhen ◽  
Roman Hajek ◽  
Maria Teresa Petrucci ◽  
Massimo Offidani ◽  
...  
Keyword(s):  
Overall Survival ◽  
High Risk ◽  
Board Of Directors ◽  
Research Funding ◽  
Dose Intensity ◽  
Staging System ◽  
Advisory Committees ◽  
Frail Patients ◽  
International Staging System ◽  
Frailty Score

Abstract Background: Several biological parameters define patients with multiple myeloma (MM) at high-risk of progression or death. The well-known International Staging System (ISS), as well as age per se, are insufficient to explain differences of overall survival (OS) in patients over 65 years, who are 2/3 of newly diagnosed (ND) MM patients. We have recently showed that a frailty score combining age, functional status (Activity of Daily Living and Instrumental Activity of Daily living scores) and comorbidities (Charlson index) defines 3 categories of patients - fit, intermediate-fitness, frail - with significantly differences in OS and progression-free survival (Larocca A, et al. Blood 2013 122:687). Here we assess the causes of the different mortality in intermediate-fitness and frail groups compared to fit ones and present a final prognostic score based on the combination of ISS and frailty scores. Methods: NDMM patients over 65 years enrolled in 3 clinical trials, receiving either lenalidomide, bortezomib or carfilzomib were included in the analysis. Details on treatment regimens and results of these studies have previously been reported (Palumbo A, et al. Blood 2013 122:536; Larocca A, et al. Blood 2013 122:539, Bringhen S et al. Blood 2014 Jul 3;124(1):63-9). The cumulative incidences of discontinuation and toxicities were calculated using the Fine & Gray model. The frailty score was combined with ISS with the CHi-squared Automatic Interaction Detector method used as an iterative decision tree. Results: 869 patients (median age 74 years) were included in the analysis; 260 (30%) were frail, 269 (31%) intermediated-fitness and 340 (39%) fit. The 3-year OS was 57% in frail, 76% in intermediated-fitness and 84% in fit patients. Overall, 143 patients (16%) died, 70 (27%) frail, 39 (14%) intermediate-fitness and 34 (10%) fit. The causes of death were: disease progression [35 (13%) in frail, 22 (8%) in intermediate-fitness and 18 (5%) in fit patients] and toxicity [21 (8%), 10 (4%) and 11 (3%), respectively]. The higher risk of death for progression was related with the lower dose-intensity due to the higher rate of drug discontinuation and/or dose reduction. The average dose intensity was lower in frail (74%, p=0.0006) and intermediate-fitness patients (80%, p=0.07) compared with fit patients (85%). The cumulative incidence of drug discontinuation for any cause, excluding progression and death, was higher in frail (25%; HR 2.21, p<0.001) and intermediate-fitness (22%; HR: 1.41, p=0.052) patients compared with fit ones (17%). The most frequent reasons for toxicity-related death were cardiac events [11 (4%) in frail patients, 2 (1%) in intermediate-fitness, 3 (1%) in fit] and infections [8 (3%), 2 (1%) and 2 (1%), respectively]. When we combined the frailty score with the ISS, 6 groups of patients and 4 risk categories were identified: fit patients with ISS I at low risk (15%; 3-year OS: 94%), fit patients with ISS stage II or III and intermediate-fitness patients with ISS I, II or III at intermediate risk (55%; 3-year OS: 75-77%.), frail patients with ISS stage I or II at high risk (19%; 3-year OS: 61%) and frail patients with ISS stage III at very-high risk (11%, 3-year OS: 55%) (Figure 1). Conclusion: The inferior survival observed among intermediate-fitness and in frail patients as compared to fit ones, is related to a higher rate of toxic deaths and disease progression, due to a lower dose intensity. The combination of the frailty score, evaluating the patient's status, and the standard ISS, taking into account the biological characteristics of the disease, can predict survival and enhances the single predictive values of the scores, thus representing a valuable tool for treatment-decision in the clinical practice. Figure 1. Overall survival of patients classified into 6 categories according to the recursive partitioning analysis by combining the frailty score and the International Staging System. Figure 1. Overall survival of patients classified into 6 categories according to the recursive partitioning analysis by combining the frailty score and the International Staging System. Disclosures Larocca: Janssen Cilag: Honoraria; Celgene: Honoraria. Off Label Use: Use off-label of lenalidomide (immunomodulatory drug), carfilzomib (proteasome inhibitor), subcutaneous bortezomib (proteasome inhibitor) in terms of schedule used and combination.. Bringhen:Onyx: Consultancy; Merck Sharp & Dohme: Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria; Janssen and Cilag: Honoraria; Celgene: Honoraria. Hajek:Janssen: Honoraria; Celgene: Consultancy, Honoraria; Merck: Consultancy, Honoraria. Offidani:Celgene: Honoraria; Janssen: Honoraria. Maracci:Mundipharma: Honoraria. Gay:Sanofi: Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees. Marasca:Janssen: Honoraria; Celgene: Honoraria. Giuliani:Celgene: Research Funding. Musto:Janssen: Honoraria; Celgene: Honoraria. Boccadoro:Sanofi: Consultancy, Membership on an entity's Board of Directors or advisory committees; Onyx: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen-Cilag: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees. Sonneveld:Millenium: Honoraria, Research Funding; Onyx: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; Celgene: Honoraria, Research Funding. Palumbo:Celgene: Consultancy, Honoraria; Janssen-Cilag: Consultancy, Honoraria; Millennium Pharmaceuticals, Inc.: Consultancy, Honoraria; Onyx Pharmaceuticals: Consultancy, Honoraria; Array BioPharma: Honoraria; Amgen: Consultancy, Honoraria; Sanofi: Honoraria; Genmab A/S: Consultancy, Honoraria; Bristol-Myers Squibb: Consultancy, Honoraria.

scholarly journals Estimated Glomerular Filtration Rate Is an Independent Predictor of Outcome in High-Risk Myelodysplastic Syndrome (MDS) and Low Blast Count Acute Myeloid Leukaemia (AML) Patients Treated with Azacytidine (AZA). a Retrospective Study from the MDS Registry of the Hellenic MDS Study Group

Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. 5423-5423
Author(s):  
Sotirios Papageorgiou ◽  
Vasileios Papadopoulos ◽  
Papoutselis Menelaos ◽  
Anthi Bouhla ◽  
Argiris Symeonidis ◽  
...  
Keyword(s):  
High Risk ◽  
Board Of Directors ◽  
Research Funding ◽  
Cox Regression ◽  
Performance Status ◽  
Univariate Analysis ◽  
Advisory Committees ◽  
Landmark Analysis ◽  
Kaplan Meier ◽  
Blast Count

Introduction. Myelodysplastic Syndrome (MDS) is a disease of the elderly. Apart from IPSS, IPSS-R and WPSS, several indexes incorporating patient comorbidities (such as the MDS CI index- Della Porta et al Haematologica 2011, the HCT-CI index - Sorror et al Blood 2005) and performance status (the GFM index- Itzykson et al Blood 2011) have been used to predict outcome in MDS patients treated with azacytidine (AZA). We sought to investigate the effect of comorbidities on the outcome after AZA in a large group of patients from the MDS registry of the Hellenic MDS Study Group. Methods. The present study has been conducted as a retrospective observational cohort one. It included high-risk MDS and low blast count AML patients treated with AZA from 26 centers in Greece from 2007 to 2018. T-test and ANOVA were used to compare scale variables between two or more groups respectively. Univariate analysis of nominal and scale survival data was performed using Kaplan-Meier survival curves and Cox regression respectively. All variables achieving p<0.05 at univariate analysis were considered eligible for multivariate analysis; the latter was based on Cox regression method. Results. We analyzed 536 consecutive patients. Patient characteristics are depicted in Table 1. The median follow-up period was 27.5±4.8 months. 371 patients received at least four cycles of AZA and 165 patients received less than 4 cycles of AZA. Patients who received ≥4 cycles of AZA did not differ from those who received <4 cycles regarding gender, age, estimated Glomerular Filtration Rate (eGFR), cardiovascular, renal, and tumor comorbidities. Significantly higher IPSS-R and GFM scores at baseline were found in the group of patients receiving < 4 cycles of AZA compared to patients who received ≥ 4 cycles of AZA (p=0.042 and 0.05 respectively), while transfusion dependence at baseline occurred more often in patients who received ≥ 4 cycles of AZA (p=0.039). To assess the prognostic significance of risk factors on leukemia free survival (LFS) and overall survival (OS), univariate and multivariate analysis for the whole population was performed, as well as a landmark analysis for patients who were treated with at least 4 cycles of AZA. ECOG performance status and the presence of peripheral blasts were independent prognostic factors for LFS and OS for the whole cohort analysis while response to AZA and the presence of peripheral blasts were independent prognosticators for LFS and OS in the landmark analysis. In addition, prior low dose cytarabine was an independent adverse prognostic factor for LFS in the landmark analysis. As regards comorbidities, neither of MDS-CI, HCT-CI and GFM systems independently predicted LFS or OS in either analysis, but eGFR with a cut-off of 45 ml/min was a strong and independent prognosticator for LFS and OS in both the standard and the landmark analysis. Kaplan-Meier survival curves regarding LFS and OS at AZA initiation and landmark analysis after 4th cycle of AZA in relation with eGFR are shown in Figure 1. Conclusion. This is the first study to demonstrate the importance of eGFR at baseline as a prognostic marker for LFS and OS in high-risk MDS and low-blast AML patients treated with AZA. The role of comorbidities and PS needs to be further evaluated in this patient group. Disclosures Symeonidis: Roche: Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Research Funding; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Gilead: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; MSD: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding; Pfizer: Research Funding; Tekeda: Membership on an entity's Board of Directors or advisory committees, Research Funding. Vassilakopoulos:Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; WinMedica: Honoraria, Membership on an entity's Board of Directors or advisory committees; Abbvie: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene / GenesisPharma: Honoraria, Membership on an entity's Board of Directors or advisory committees; Roche: 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. Panayiotidis:Bayer: Other: Support of clinical trial. Pappa:Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Research Funding; Gilead: Honoraria, Research Funding; Novartis: Honoraria, Research Funding, Speakers Bureau; Roche: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene / GenesisPharma: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Abbvie: Research Funding; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Kotsianidis:Celgene: Research Funding.

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