scholarly journals Genome-Wide Somatic Alterations in Multiple Myeloma Reveal a Superior Outcome Group

2020 ◽  
Vol 38 (27) ◽  
pp. 3107-3118 ◽  
Author(s):  
Mehmet Kemal Samur ◽  
Anil Aktas Samur ◽  
Mariateresa Fulciniti ◽  
Raphael Szalat ◽  
Tessa Han ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Overall Survival ◽  
High Risk ◽  
Chromosome 9 ◽  
Cell Transplant ◽  
Mutational Load ◽  
Newly Diagnosed ◽  
Therapeutic Algorithms ◽  
Genomic Markers ◽  
Somatic Alterations

PURPOSE Multiple myeloma (MM) is accompanied by heterogeneous somatic alterations. The overall goal of this study was to describe the genomic landscape of myeloma using deep whole-genome sequencing (WGS) and develop a model that identifies patients with long survival. METHODS We analyzed deep WGS data from 183 newly diagnosed patients with MM treated with lenalidomide, bortezomib, and dexamethasone (RVD) alone or RVD + autologous stem cell transplant (ASCT) in the IFM/DFCI 2009 study (ClinicalTrials.gov identifier: NCT01191060 ). We integrated genomic markers with clinical data. RESULTS We report significant variability in mutational load and processes within MM subgroups. The timeline of observed activation of mutational processes provides the basis for 2 distinct models of acquisition of mutational changes detected at the time of diagnosis of myeloma. Virtually all MM subgroups have activated DNA repair–associated signature as a prominent late mutational process, whereas APOBEC signature targeting C>G is activated in the intermediate phase of disease progression in high-risk MM. Importantly, we identify a genomically defined MM subgroup (17% of newly diagnosed patients) with low DNA damage (low genomic scar score with chromosome 9 gain) and a superior outcome (100% overall survival at 69 months), which was validated in a large independent cohort. This subgroup allowed us to distinguish patients with low- and high-risk hyperdiploid MM and identify patients with prolongation of progression-free survival. Genomic characteristics of this subgroup included lower mutational load with significant contribution from age-related mutations as well as frequent NRAS mutation. Surprisingly, their overall survival was independent of International Staging System and minimal residual disease status. CONCLUSION This is a comprehensive study identifying genomic markers of a good-risk group with prolonged survival. Identification of this patient subgroup will affect future therapeutic algorithms and research planning.

scholarly journals Gene Expression and Genomic Markers Identify a Subpopulation of Poor Prognosis t(4;14) Patients in Newly Diagnosed Multiple Myeloma

Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. 366-366
Author(s):  
Maria Ortiz ◽  
Fadi Towfic ◽  
Erin Flynt ◽  
Nicholas Stong ◽  
Sneh Lata ◽  
...  
Keyword(s):  
Gene Expression ◽  
Multiple Myeloma ◽  
High Risk ◽  
Poor Prognosis ◽  
Newly Diagnosed ◽  
Employment Equity ◽  
Gene Set ◽  
Combining Data ◽  
Genomic Markers ◽  
Equity Ownership

Cytogenetics is an important prognostic marker in multiple myeloma (MM). Patients with t(4;14) (~15% of newly diagnosed MM patients) are known to have short progression free survival (PFS) and overall survival (OS). This feature, measured by FISH, is used in combination with ISS=3 as a selection marker for patients with high risk (HR) of progression. Only a subset of patients grouped by t(4;14) and ISS=3 display genuinely poor survival, however, with ~25% dying within 24 months after diagnosis (similar to the Double Hit subgroup defined by Walker et al1). To elucidate this observation, we created the largest dataset of MM t(4;14) patients to date by combining data from the Myeloma Genome Project (MGP, n=73) and data from TOUL (n=100, patients analyzed in routine practice) to identify transcriptomic and/or genomic markers associated with HR t(4;14). Gene expression (GE), copy number aberration (CNA), single nucleotide variant (SNV) and translocations were derived from RNAseq and WGS/WES profiling of biopsies from patients aged less than 75 years who received transplant, and integrated with clinical information (including Age, PFS and OS). Demographics: MGP median age=61; 30% female; median PFS (mPFS)=26.2months (m) and median OS (mOS) not reached. TOUL median age=60; 35% female, mPFS=23.7m and mOS = 86.1m. Our previous work (Ortiz ASH 2018, Ortiz EHA 2018) identified a molecularly-defined HR MM patient subgroup (MDMS8, mPFS<20m, m0S<35m) defined by GE patterns related to cell cycle dysregulation. In that analysis, 24% of t(4;14) patients were identified as MDMS8 (mPFS<13m, mOS<30m), the rest (76%) were grouped in other lower risk molecular segments (mPFS<30m, mOS NR). A GE classifier for t(4;14) in MDMS8 vs the rest of t(4;14) patients was created on the MGP dataset and applied to identify similar patients in the TOUL data, obtaining a significant difference between MDMS8-like t(4;14) patients (20% prevalence, mPFS<15m, mOS<26m) in the TOUL dataset and non-HR t(4;14) (mPFS<26m, mOS<103m) in both PFS (p.value<1e-3) and OS (p.value<1e-5). Although there are some conventional t(4;14) gene expression surrogates, they do not identify the HR t(4:14) subgroup. Comparison of known t(4;14) gene expression markers MMSET and FGFR3 in HR t(4;14) (OS < 24ms & not_alive, N=34) versus non-HR t(4;14) patients (N=94) across both datasets combined did not yield significant differential expression of either gene (p.value>0.10). MMSET was over-expressed in all t(4;14) patients, while FGFR3 displayed a binomial distribution (two groups of patients with high (N=37, median value=10 log2CPM) and low (N=91, median value=2 log2CPM) FGFR3 expression) within t(4;14) patients (p.value<0.05) without association with outcome (p.value>0.10). GE analysis of HR t(4;14) vs non-HR t(4;14) patients aligned with MDMS8 biology, but identified new pathways also including DNA repair, MYC targets and Oxidative Phosphorylation being up-regulated in the HR t(4;14) group. A gene-set variation analysis based on the MSigDb C1 gene-set, wherein genes are grouped based on their genomic location, was performed to identify GE changes of potentially epigenomic origin. Results highlighted chr9q22, chr9q33, and chr13q13 as down-regulated in the HR t(4;14) group, while genes in 16q24 were significantly up-regulated. CNA analysis identified amplifications in chromosomes 3 and 19 and deletions in chr12p as significantly associated with the HR t(4;14) population (p.value < 0.05); while deletions in chr14q (preceding the translocated region) occurred more frequently in the non-HR t(4;14) group. Our results provide new insights into identification of these patients and underlying biology that could drive poor prognosis in t(4;14) patients. Molecular identification of HR t(4;14) patients would enable proper risk classification for this MM patient group and understanding differences in HR t(4;14) biology could provide the basis for identification of a specific therapeutic target for this HR subpopulation. An ongoing aim of this work is development of a clinically applicable classifier that accurately identifies this subpopulation of MM patients and the biological drivers of their high-risk disease. Disclosures Ortiz: Celgene Corporation: Employment, Equity Ownership. Towfic:Celgene Corporation: Employment, Equity Ownership. Flynt:Celgene Corporation: Employment, Equity Ownership. Stong:Celgene Corporation: Employment, Equity Ownership. Lata:Celgene Corporation: Employment, Equity Ownership. Sampath:Celgene Corporation: Employment, Equity Ownership. Rozelle:Celgene Corporation: Other: Contractor for Celgene. Trotter:Celgene Corporation: Employment, Equity Ownership. Thakurta:Celgene: Employment, Equity Ownership.

Analysis of 179 Patients with Newly Diagnosed Multiple Myeloma (MM) Treated with Novel Agents Followed by Autologous Stem Cell Transplantation (ASCT): a Retrospective Study

Blood ◽  
2010 ◽  
Vol 116 (21) ◽  
pp. 1343-1343
Author(s):  
Joyce Habib ◽  
Neil Dunavin ◽  
Gary Phillips ◽  
Patrick Elder ◽  
Meaghan Tranovich ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Overall Survival ◽  
High Risk ◽  
Research Funding ◽  
Progression Free Survival ◽  
Novel Agents ◽  
Genetic Profile ◽  
Newly Diagnosed ◽  
Free Survival

Abstract Abstract 1343 Background: Multiple myeloma (MM) is the second most common hematological malignancy in the United States with an estimated 20,580 new cases in 2009. Over the past decade, the introduction of novel agents (thalidomide, lenalidomide and bortezomib) have played a pivotal role in improving response rates, duration of response, overall survival (OS) and quality of life. In this study we describe a single center experience with novel agents used for induction followed by high dose chemotherapy (HDT) and first autologous stem cell transplant (ASCT) in patients with MM. Method: A retrospective review of the medical records of 179 newly diagnosed patients with MM seen between October 2006 and December 2009 at The Ohio State University was performed. All patients received novel therapy containing thalidomide, bortezomib or lenalidomide as part of an induction regimen followed by ASCT. All patients received melphalan 140mg/m2 or 200mg/m2 as preparative regimen. Kaplan-Meier estimates were used to plot progression free survival and overall survival. Results: Of the 181 patients seen, 2 were excluded because they did not receive a novel agent as part of induction treatment. Of the 179 patients analyzed, median age was 56.8 years (29-80) with 30% of patients older than 60 years. African American represented 19%. Fifty-nine percent were male, 80% had Durie-Salmon (DS) stage III while 25%, 28%, 18% represented International prognostic score (IPS) stage I, II, and III respectively with 27% unknown. Median comorbidity index score was 2 (2-7) and median Karnofsky performance score (KPS) was 90% (70-100). Thirty percent had high risk genetic profile, and 73% received one line of treatment before ASCT. The median time from diagnosis to ASCT was 8.33 months (4-58). The overall response rate (ORR) prior to transplant was 84% (9% complete (CR), 29% very good partial (VGPR), and 46% partial (PR)). The ORR post ASCT was 89% (CR 45%, VGPR 22%, PR 21%). Non relapse mortality was 1% and 3% at 100 days and 1 year respectively. At a median follow up of 31 months (7-90), 69 patients (38%) had relapsed. Median progression free survival (PFS) was 29 months with 1 and 3 years PFS of 79.3% and 61.5% respectively (Fig. 1). The OS was not reached. One and 3 years OS were 93% and 88% respectively (Fig. 1). Univariate analysis showed that time to transplant > 12 months was associated with poor outcome and decreased overall survival (HR 3.30, p = 0.008). High risk genetic profile was also found to be associated with decreased overall survival although this was not statistically significant (HR 2.31, p = 0.070). Multivariate analysis found that only time to transplant > 12 months was an independent predictor of decreased OS. Significant predictors for disease progression were high risk genetic profile and time to transplant > 12 months in patients receiving 2 or more treatments before ASCT. Conclusion: Induction with novel agents followed by HDT and ASCT improves CR rate, in our case from 9% to 45%. Median PFS (29 months) was comparable to other published data. OS was not been reached after a median follow up of 31 months. Predictors of progression include high risk genetic profile and time to transplant > 12 months. The only significant predictor for survival was time to transplant. Our study suggests that an early transplant may improve OS and PFS. An extended analysis will be presented at the meeting. Disclosures: Phillips: NCI/NIH: Research Funding; NCCM Grant: Research Funding; ARRA RC2 Grant: Research Funding. Byrd:Genzyme Corporation: Research Funding.

Extramedullary Multiple Myeloma Associated With Reduced Overall Survival: A Retrospective Single-Center Study

Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 5317-5317 ◽  
Author(s):  
Ido Barkay ◽  
Richard T. Maziarz ◽  
Andy I. Chen ◽  
William Dibb ◽  
Yiyi Chen ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Overall Survival ◽  
Multivariate Analysis ◽  
High Risk ◽  
Staging System ◽  
Novel Agents ◽  
Cell Transplant ◽  
Disease Characteristics ◽  
Staging Systems ◽  
Risk Patients

Abstract Introduction Multiple Myeloma (MM) is an incurable neoplasm, however recent advancements in therapies have led to median overall survival of 7-10 years in standard risk patients. High risk patients still succumb to the disease within 3 to 5 years. Traditionally used clinical prognostic markers such as the International Staging System (ISS), the Durie-Salmon (DS) staging system, and cytogenetics do not adequately predict response to novel agents or overall prognosis. We previously presented data identifying high risk sub-groups that succumb to shorter progression free survival (PFS) and overall survival (OS) after hematopoietic stem cell transplant (HSCT). Extramedullary disease (EMD) was a highly significant risk factor for poor survival. Methods A retrospective single institution cohort study was performed of 251 patients who underwent HSCT for MM between 1/1/2001 and 12/31/2011. Of these 251 patients, 18 were identified as having EMD, which was defined by the presence of ≥ 2 plasmacytomas in organs other than bone marrow or bone at any stage of disease. Data points collected included patient and disease characteristics, ISS and DS stage, cytogenetics and FISH, induction therapy, type and number of HSCT, treatment type and cycles, as well as maintenance therapy. Outcome measures included overall response rate (ORR), PFS and OS. Descriptive statistical analysis was conducted for all primary and secondary endpoints. Univariate and multivariate analysis were conducted using the Cox proportional hazards regression model. Results Patients with EMD represented 6.6% of our total population. Patient and disease characteristics are found in table 1. Seven of 18 patients had died by the time of data collection. With a median follow up time of 29 months, the median PFS and OS for the entire group (n= 251) compared to the EMD group (n= 18) were PFS: 22.3 months (95% CI 19.75 – 30.32) vs. 12.9 and OS: 57.3 months (95% CI: 46.52 - 77.77) vs. 17.2 (Figs 1 and 2). Results of univariate and multivariate analysis are in table 2. Conclusion Extramedullary multiple myeloma represents a small but highly aggressive subgroup of multiple myeloma. It prevails as a poor prognostic indicator despite the use of novel agents, yet it is not included in traditionally used staging systems. Further confirmatory studies are needed, and likely, new therapeutic approaches will be required for MM patients with EMD. Disclosures: Chen: Genzyme: supported database used for this study Other. Scott:Millenium Pharmaceuticals: Membership on an entity’s Board of Directors or advisory committees, Research Funding.

scholarly journals Defining Genomic Probability of Progression to Identify Low-Risk Smoldering Multiple Myeloma

Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 545-545
Author(s):  
Anil Aktas-Samur ◽  
Mariateresa Fulciniti ◽  
Sanika Derebail ◽  
Raphael Szalat ◽  
Giovanni Parmigiani ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
High Risk ◽  
High Sensitivity ◽  
Mutational Load ◽  
Newly Diagnosed ◽  
Genomic Features ◽  
Genomic Deletions ◽  
Smoldering Multiple Myeloma ◽  
Short Period

Abstract On an average, 1% of monoclonal gammopathy of undermined significance (MGUS) and 10% of smoldering Multiple Myeloma (SMM) progress to symptomatic MM every year within the first five years of diagnosis. The probability of progression significantly decreases for SMM patients after first 5 years. However, a distinct subset of SMM patients progress within 2 years and are re-classified as high-risk patients based on risk markers such as 20/2/20 or certain genomic features. Although recent studies have evaluated the high-risk genomic features for SMM but genomic background of SMM patients who do not progress to MM after long-term follow-up (>= 5 years) has not been described. Here, we evaluated transcriptomic and genomic changes enriched in non-progressor (NP) (no progression after 5 years of follow-up) precursor conditions (N=31) with those progressed within short period of time (N=71) and compared them with changes observed in newly diagnosed MM (N=192). Additionally, using transcriptome, epigenome and whole genome profiling we also studied additional unique samples from 18 patients at their precursor stage as well as when progressed to MM. Overall, we have observed significantly lower mutational load for NP SMM from progressor SMM (median SNV 4900 vs. 7881 p < 3e-04) with high sensitivity (0.83) and specificity (0.65) to separate NP from progressors. We have further developed a deep learning model by using more than 4500 genome wide features using ten-fold cross validation. This model indicated that not only the load but also the patterns of mutations (type, location, frequency) are different between two conditions. We also found that NP samples have significantly lower heterogeneity (p < 0.05). However, progressed samples showed similar mutational load and heterogeneity at precursor stage and MM. Among CNA differences, absence of gain or deletion of chr8 (not involving MYC region) were strong predictor of NP (OR=7.2 95% CI 2.2-24). Focal genomic loss was also significantly lower for NP (p=0.004) which was also reflected by low genome scar score (GSS) (p=0.07). Structural variant and copy number signature analysis also showed that NPs were showing significantly low exposure to non-clustered variable size genomic deletions. We observed similar frequency of primary translocations [t(11;14), t(4;14), and t(14;16)] in both progressor and NP samples as well as newly diagnosed MM. MYC translocation with any partner was not observed in NP samples, whereas 37% of progressor samples had a MYC translocations (OR=12.8). Adding all these differences including chr8 CNAs, MYC translocations, mutation burden, GSS, focal deletions, all driver mutations as well as primary translocations into recursive partitioning model to predict non-progressor SMM, we have identified a simple genomic model only involving chr8 CN changes and overall mutational burden to achieve a high sensitivity (0.82) and specificity (74%). Our transcriptomic analysis measured the distance between progressor and NP SMM as well as MM and found that NP SMM has greater difference with MM which is closer to progressor SMM. We quantified transcriptomic heterogeneity by using molecular degree of perturbation. This analysis showed that consistent with DNA changes, DNA repair pathway and MYC target genes are expressed similarly in NP SMM as in normal plasma cells compared to progressor SMM. Epigenomic analysis yielded 75 SEs regions differentially utilized between precursor and symptomatic MM stage using paired samples. The targeted genes included BMP6, PRDM1, STAT1, SERTAD2 and RAB21 and possibly regulating genes related to oncogenic KRAS activities. In conclusion, we define genomic characterization of non-progressor SMM and our results now provide the basis to develop molecular definition of SMM as well as risk driving features. Disclosures Munshi: Janssen: Consultancy; Pfizer: Consultancy; Legend: Consultancy; Novartis: Consultancy; Adaptive Biotechnology: Consultancy; Oncopep: Consultancy, Current equity holder in publicly-traded company, Other: scientific founder, Patents & Royalties; Takeda: Consultancy; Abbvie: Consultancy; Karyopharm: Consultancy; Amgen: Consultancy; Celgene: Consultancy; Bristol-Myers Squibb: Consultancy.

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.

scholarly journals Prognostic value of circulating plasma cells in newly diagnosed multiple myeloma

2020 ◽  
Author(s):  
Wenmin Han ◽  
Yuanyuan Jin ◽  
Min Xu ◽  
Sishu Zhao ◽  
Qinglin Shi ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Overall Survival ◽  
High Risk ◽  
Plasma Cells ◽  
Staging System ◽  
Blood Platelet ◽  
High Risk Group ◽  
Newly Diagnosed ◽  
Color Flow ◽  
Ultra High Risk

Abstract Purpose: Multiple myeloma (MM) is a clinically and biologically heterogeneous malignancy of plasma cell. The overall survival of MM patients varies from people to people ranged from several months to decades. It is always knotty how to predict MM prognosis. The presence of circulating plasma cells (CPCs) has been associated with a worse prognosis in patients with MM.Materials and Methods: This study retrospectively analyzed CPCs in 108 cases of newly diagnosed MM patients with 8-color flow cytometry to investigate its value for outcome prediction, and combined CPCs with R-ISS to stratify the risk of MM. Results: CPCs were detected in 58/108 patients (53.7%). The optimum cutoff predicting for overall survival was determined as 0.105% by using a ROC analysis. Compared with patients with CPCs < 0.105% (n = 66，61.1%), those with CPCs ≥0.105% (n = 42, 38.9%) showed lower blood platelet count (BPC) (P=0.038), but higher β2-microglobulin (β2-MG), lactate dehydrogenase (LDH), ferritin (FER) , and harboring P53 deletion, high-risk cytogenetic abnormality, (P = 0.011, 0.001, 0.002, <0.001, and 0.020, respectively). The higher R-ISS stage seems to harbor higher CPCs. CPCs≥0.105% are independently factor for adverse outcome (P<0.001). The combination of R-ISS staging system and CPCs level was used to stratify the risk of multiple myeloma，and R-ISS III stage with CPCs ≥0.105% was ranked as a real ultra-high-risk group. Conclusion: This study suggests that high CPCs is associated with an aggressive disease and that the current R-ISS system in conjunction with CPCs may facilitate the differentiation of NDMM patients. There may also is the potential significance in modifying the definitions of high-risk disease and the practice of adopting a risk-adapted initial treatment.

Outcomes of 252 Patients with High Risk Multiple Myeloma Treated with Hematopoietic Stem Cell Transplantation: Identification of Risk Factors Associated with Early Relapse, Shortened Progression Free and Overall Survival

Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 3957-3957
Author(s):  
Emma C. Scott ◽  
Stephen D. Smith ◽  
Andy I. Chen ◽  
Nicky Leeborg ◽  
Tarunpreet Bains ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Overall Survival ◽  
Stem Cell ◽  
High Risk ◽  
Hematopoietic Stem Cell ◽  
Chromosome 1 ◽  
Cell Transplant ◽  
Hematopoietic Stem ◽  
Factors Associated ◽  
Secondary Endpoints

Abstract Abstract 3957 Currently used clinical prognostic markers for patients with multiple myeloma (MM) such as the international staging system (ISS) and cytogenetics are inadequate predictors of response and survivorship after hematopoietic stem cell transplant (HSCT). Recently published large studies of HSCT as consolidation after primary therapy have demonstrated 3-year progression free survival (PFS) and overall survival (OS) rates of 45% and 78% respectively after tandem HSCT (BMT CTN 0102; Krishnan, Lancet Onc, 2011) and median time to progression of 46 and 27 after single autologous transplant, with and without lenalidomidemaintenance (CALGB 10104; McCarthy, NEJM, 2012). These studies (which include patients in the current cohort) have established expected PFS and OS benchmarks that allow identification of higher risk subsets. The aim of this study is to describe and further sub- stratify patients with high-risk myeloma (HRMM), with the goal to identify ‘higher’ risk groups that may benefit from alternative treatment strategies. Methods: A retrospective cohort study of HRMM patients who received an HSCT at OHSU between 01/01/2001 and 12/31/2011 was performed. We defined HRMM by the following: FISH and cytogenetic findings of del17p, t(4:14), t(14;16), t(14;20), chromosome (ch) 1 abnormalities, del 13q by cytogenetics; the presence of multiple extra-medullary plasmacytomas; plasmablastic morphology; higher ISS categories (II and III); Salmon- Durie(S-D) stages 2 and 3; recurrence or less than a partial remission (PR) to 2 consecutive lines of therapy prior to HSCT. Outcome measures included PFS and OS. Descriptive statistical analysis was conducted for all primary and secondary endpoints, patients' individual and clinical characteristics, and gene profiles. Kaplan-Meier method was used to estimate the OS and PFS function. Log-rank test was used to assess whether the survival function differs across the groups. Factors that are significantly associated with the primary and secondary endpoints were identified using univariateanalysis. Multivariate analysis is ongoing. Results: Patient and HSCT characteristics are found in table 1. With a median follow up of 40 months, relapse occurred in 127 patients, of which 77 (60%) occurred within 18 months post HSCT. Median PFS and OS are 22.3 (95% CI: 19.7 – 29.3) and 56.67 (95% CI: 40.1–69.9) months respectively. The 2-year PFS and OS rates were 47%, and 72% respectively. Univariate data analysis revealed the following factors that are highly associated with reduced PFS: del 17p (2- year PFS 26.2%; p= 0.09); ch 1 abnormalities (27.4%; p=0.0026); recurrence or < PR after 2 consecutive lines of chemotherapy prior to HSCT (27.5%; p= 0.07). For patients with chromosome 1 abnormalities, the presence of del 13q by cytogenetics further decreased the PFS (22%; p= 0.04;)(Figure 1). Factors associated with highly with a reduced OS are: ch 1 abnormalities (2-year OS 52.5%; p=0.0042); both chromosome 1 and del13q (46.2%; p=0.0016) and having multiple extra-medullary plasmacytomas (55.2%; p= 0.026 (Figure 2). Conclusion: Within the broad group of HRMM, certain groups have significantly inferior outcomes post HSCT, the worst being those with recurrence or < PR to 2 consecutive lines of chemotherapy prior to HSCT, those with any ch 1 abnormality and particularly those with additional del 13q by cytogenetics. Investigation of novel therapeutic and more aggressive strategies is warranted in these groups. Disclosures: Scott: Genzyme: Research Funding; Millenium: Speakers Bureau.

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