Abstract: Abstract 1829 Poster Board I-855 Introduction In addition to current clinical and cytogenetic risk factors, several highly predictive gene expression based risk stratifications have been proposed in multiple myeloma. At the same time, putative drugable targets have been identified which are only expressed in a subpopulation of myeloma patients (e.g. AURKA). Whereas assessment of both works well within a clinical trial or an experimental setting, they can currently not readily be applied to clinical routine. Methods As reference a group of 300 Affymetrix U133 Plus 2.0 DNA microarrays from patients with multiple myeloma is preprocessed using GC-RMA. Quality control of the DNA microarrays is implemented according to the MACQ-Project. Gene expression based prediction of sex, immunoglobulin- and light chain type is used as sample identity-test within a multicenter-setting. Gene expression based risk stratification (IFM-score, 70-gene high risk score, gene expression based proliferation index) and molecular classifications are assessed as published, as are individual target genes e.g. AURKA. To classify a patient within a prospective clinical routine setting, the documentation by value strategy (Kostka & Spang, 2008) was adapted for GC-RMA preprocessing and is used for documenting the quantitative preprocessing information of the reference group. The gene expression based report is developed in the open source language R, containing a GUI based on Gtk2, and the final report is created as a PDF-file. Results We present here our publicly available (http://code.google.com/p/gep-r) open source software-framework (GEP-R) that allows creating a gene expression based report from Affymetrix raw-data. The risk stratification of an individual patient is assessed and based on saved preprocessing information of a reference cohort by treating the individual patient's expression data as being part of this group, assuring comparable risk stratification. Results can be interpreted and commented within the report and a PDF based document be created. The generation of the report can be performed within short time on a standard computer. Conclusion Gene expression reporting allows validated assessment of risk and of individual therapeutic targets in myeloma patients within a clinical routine setting. Disclosures No relevant conflicts of interest to declare.

Abstract: BACKGROUND. At the time of diagnosis, myeloma cells are characterized by a low proliferation rate that increases in relapse. Presence of proliferation correlates with adverse prognosis. At the same time, myeloma cells harbor a high median number of chromosomal aberrations, often associated with genetic instability. Cellular proliferation and genetic instability in turn have been associated with Aurora-kinase expression in several cancer entities, including multiple myeloma. PATIENTS AND METHODS. Expression of Aurora-A, -B and -C was assessed using Affymetrix DNA-microarrays in 784 samples including two independent sets of 233 and 345 CD138-purified myeloma cells from previously untreated patients. Chromosomal aberrations were assessed by comprehensive iFISH using a set of probes for the chromosomal regions 1q21, 6q21, 8p21, 9q34, 11q23, 11q13, 13q14.3, 14q32, 15q22, 17p13, 19q13, 22q11, as well as the translocations t(4;14)(p16.3;q32.3) and t(11;14) (q13;q32.3). Proliferation of primary myeloma cells (n=67) was determined by propidium iodine staining. The effect of the clinical Aurora-kinase inhibitor VX680 on proliferation of 20 human myeloma cell lines and survival of 5 primary myeloma cell-samples was tested. RESULTS. We found Aurora-A and -B to be expressed at varying frequencies in primary myeloma cells of different patient-cohorts, including 23% for Aurora A in our first cohort of patients treated with high dose therapy (see figure shown below). Aurora-C expression was found in testis-samples only. Myeloma cell-samples with detectable Aurora-A expression show a significantly higher proliferation rate, whereas the number of chromosomal aberrations (aneuploidy) is not higher compared to myeloma-cells with absent Aurora-A expression. The same holds true for subclonal aberrations (i.e. genetic instability). The Aurora-kinase inhibitor VX680 induces apoptosis in all myeloma cell lines and primary myeloma cell-samples tested. Presence of Aurora-A expression delineates significantly inferior event-free and overall survival in two independent cohorts of patients undergoing high-dose chemotherapy and autologous stem cell transplantation. This observation is independent of conventional prognostic factors, i.e. serum-ß2-microglobulin or ISS-stage. CONCLUSION. Aurora-kinase inhibitors (including VX680 tested here) are very active on myeloma cell lines as well as primary myeloma cells and represent a promising weapon in the therapeutic arsenal against multiple myeloma. Gene expression profiling allows the assessment of Aurora-kinase expression and thus in turn a tailoring of treatment to patients expressing Aurora-A associated with adverse prognosis. Figure Figure

Abstract: Genetic instability and cellular proliferation have been associated with aurora kinase expression in several cancer entities, including multiple myeloma. Therefore, the expression of aurora-A, -B, and -C was determined by Affymetrix DNA microarrays in 784 samples including 2 independent sets of 233 and 345 CD138-purified myeloma cells from previously untreated patients. Chromosomal aberrations were assessed by comprehensive interphase fluorescence in situ hybridization and proliferation of primary myeloma cells by propidium iodine staining. We found aurora-A and -B to be expressed at varying frequencies in primary myeloma cells of different patient cohorts, but aurora-C in testis cell samples only. Myeloma cell samples with detectable versus absent aurora-A expression show a significantly higher proliferation rate, but neither a higher absolute number of chromosomal aberrations (aneuploidy), nor of subclonal aberrations (chromosomal instability). The clinical aurora kinase inhibitor VX680 induced apoptosis in 20 of 20 myeloma cell lines and 5 of 5 primary myeloma cell samples. Presence of aurora-A expression delineates significantly inferior event-free and overall survival in 2 independent cohorts of patients undergoing high-dose chemotherapy, independent from conventional prognostic factors. Using gene expression profiling, aurora kinase inhibitors as a promising therapeutic option in myeloma can be tailoredly given to patients expressing aurora-A, who in turn have an adverse prognosis.

Abstract: BACKGROUND. The proliferation-rate of primary myeloma cells is a strong adverse prognostic factor in various trials, but not routinely assessed, partially due to effort in obtaining it. AIM. As gene-expression profiling is increasingly considered a standard diagnostics in myeloma, we investigated the possibility to develop a prognostically relevant gene-expression based proliferation index (GPI). PATIENTS AND METHODS. Gene expression was determined by Affymetrix DNA-microarrays in 784 samples including two independent sets of 233 and 345 CD138-purified myeloma cells from previously untreated patients. The GPI was derived by selecting genes associated with proliferation (in terms of gene ontology) differentially expressed in proliferating malignant (human myeloma cell lines) and benign (plasmablastic) cells compared to non-proliferating, non-malignant cells (normal plasma cells and memory B-cells). The GPI comprises the sum of the expression values of 50 genes (ASPM, AURKA, AURKB, BIRC5, BRCA1, BUB1, BUB1B, CCNA2, CCNB1, CCNB2, CDC2, CDC20, CDC25C, CDC6, CDCA8, CDKN3, CEP55, CHEK1, CKS1B, CKS2, DLG7, ESPL1, GINS1, GTSE1, KIAA1794, KIF11, KIF15, KIF20A, KIF2C, KNTC2, MAD2L1, MCM10, MCM6, MKI67, NCAPD3, NCAPG, NCAPG2, NEK2, NPM1, PAK3, PCNA, PGAM1, PLK4, PTTG1, RACGAP1, SMC2, SPAG5. STIL, TPX2, ZWINT). Proliferation of primary myeloma cells was assessed by propidium iodinestaining (n=67). Chromosomal aberrations were assessed by comprehensive iFISH using a set of probes for the chromosomal regions 1q21, 6q21, 8p21, 9q34, 11q23, 11q13, 13q14.3, 14q32, 15q22, 17p13, 19q13, 22q11, as well as the translocations t(4;14)(p16.3;q32.3) and t(11;14)(q13;q32.3). RESULTS. In the two groups, 39 and 32 percent of primary myeloma cells show a GPI above the median plus three standard deviations of normal bone marrow plasma cells, respectively. The GPI is significantly higher in advanced- compared to early-stage myeloma (P=.001) and in patients harboring a gain of 1q21 (n=95, P & lt;0.001). It correlates significantly with proliferation as determined by propidium iodine in primary myeloma cells (rs=.52, P & lt;.001, n=67). The GPI as continuous variable is significantly predictive for event-free survival (EFS, n=120, P & lt;.001, n=345, P & lt;.001, respectively) and overall survival (OAS, n=345, P & lt;.001) in patients treated with high-dose chemotherapy, independent of serum-β2-microglobulin (B2M) or ISS-stage. A GPI above the median (GPIhigh) delineated significantly inferior EFS (n=168, 41.6 vs. 26 months, P=.04, HR 1.57, CI [1.02,2.42]; n=345, 68.6 vs. 45.2 months, HR 1.55, CI [1.16,2.09] , P=.003) and OAS (n=345, P & lt;.001) in two independent cohorts of patients undergoing high-dose chemotherapy. By using B2M above 3.5 mg/l and GPI as staging variables, four groups with difference in median EFS (n=345, B2M & lt;3.5mg/l, GPIhigh/low 76.1 months; B2M & lt; 3.5mg/l, GPIhigh 62.4 months, B2M ≥3.5mg/l, GPIlow 41.8 months, B2M ≥3.5mg/l, GPI 36.1 months, P & lt;.001) and OAS can be delineated. CONCLUSION. The GPI represents a validated tool for the assessment of proliferation in multiple myeloma patients, allows a risk stratification in terms of proliferation either alone or in combination with B2M or ISS, respectively, and has the potential to be used within a risk adapted targeting of anti-proliferative treatment.

Abstract: Multiple Myeloma (MM) is a malignant lymphoproliferative B-cell disease characterized by the accumulation of monoclonal plasma cells in the bone marrow. Acquired genomic aberrations have been shown to significantly impact response to chemotherapy and survival in MM. The aim of our study was to assess the clinical relevance of genomic abnormalities in 306 MM patients treated with high-dose chemotherapy (HDCT) and peripheral stem cell transplantation (PBSCT) in our center. We analyzed 171 males and 135 females with a median age of 60 years (range 25 – 73 years). According to the international staging system (ISS), MM patients were classified as stage I (46.6%), stage II (36.1%) and stage III (17.4%) at the onset of chemotherapy. All patients underwent frontline HDCT with 200 melphalan mg/m2 and PBSCT according or in analogy to the GMMG-HD3- or GMMG-HD4-trials. Interphase-FISH-analysis was performed on CD138-purified plasma cells using probes for chromosomes 1q21, 6q21, 8p21, 9q34, 11q23, 13q14.3, 15q22, 17p13, 19q13, and 22q11, as well as IgH-translocations t(4;14)(p16.3;q32.3) and t(11;14)(q13;q32.3). For the entire group, the median overall survival (OS) and progression-free survival (PFS) after HDCT was 6.4 and 2.2 years, respectively. Table 1. Chromosomal abnormalities with significant results (a-level=0.05) on PFS or OS (univariate analysis, unadjusted p-values) Aberration yes vs. no Frequency % 3-year PFS % P value 3-year OS % P value del(8p21) 19 26 vs. 37 0.01 58 vs. 78 0.02 del(13q14.3) 46 23 vs. 53 & lt;0.001 65 vs. 83 0.03 del(17p13) 10 22 vs. 40 0.02 44 vs. 82 & lt;0.001 t(4;14) 14 10 vs. 42 & lt;0.001 54 vs. 81 0.04 +1q21 35 20 vs. 46 & lt;0.001 67 vs. 85 0.002 +19q13 54 49 vs. 22 0.03 76 vs. 73 0.92 In a first step, we analyzed the prognostic impact of each individual chromosomal aberration on PFS and OS (Table 1). After adjustment for the ISS-score, del(8p21), del(13q14.3), del(17p13), t(4;14) as well as gains of 1q21 and 19q13 preserved significant impact on PFS, while del(17p13), t(4;14) and gain of 1q21 were of statistical significance for OS, indicating that these chromosomal aberrations give prognostic information in addition to the ISS-score. Subsequently, we performed a multivariate analysis including all the chromosomal aberrations analyzed. While del(17p13) and gain of 1q21 showed significant results on OS, del(13q14.3), del(22q11) and gain of 15q22 were significant for PFS. In conclusion, our results show that the heterogeneity seen in the clinical course of MM patients after HDCT can be correlated with distinct chromosomal aberrations. This analysis may have implications for the risk-adopted management of patients with MM.

Abstract: Background: Peripheral neuropathy (PN) is an important, dose-limiting toxicity of bortezomib (BTZ). Subanalysis of the phase 3 VISTA trial of intravenous (IV) BTZ in newly diagnosed MM patients identified baseline neuropathy as only clinical risk factor for Bortezomib-induced peripheral neuropathy (BiPN). Since subcutaneous (SC) application reduces rates of BiPN, BTZ is mainly applied subcutaneously in current clinical trials and general practice. Data on clinical risk factors for BiPN in the era of SC BTZ are limited. We analyzed risk factors for PN in patients treated with SC or IV BTZ in the prospective randomized MM5 phase III trial of the German Myeloma Multicenter Group (GMMG). Methods: Primary end-points of the MM5 trial were response to VCD (BTZ 1.3 mg/m2, days 1, 4, 8, 11; Cyclophosphamide 900 mg/m2 IV; day 1, Dexamethasone 40 mg/d, orally, days 1-2, 4-5, 8-9, 11-12) compared to PAd (BTZ 1.3 mg/m2, days 1, 4, 8, 11; Doxorubicin 9 mg/m2 IV, days 1-4; Dexamethasone 20 mg/d, orally, days 1-4, 9-12, 17-20) induction therapy with respect to remission and progression-free survival (PFS). Induction therapy was followed by stem cell mobilization and harvest, high-dose therapy and Lenalidomide-based consolidation/maintenance therapy. From 07/2010 until 11/2013, 604 patients were randomly assigned to receive 3 cycles of PAd or VCD. Based on the results by Moreau et al, administration of BTZ was changed from IV to SC in 02/2012 after 314 patients were enrolled. We performed univariate and multivariate testing to analyze the association of different factors with the occurrence of PN ≥ grade 2 according to NCI CTCAE version 4.0 after completion of induction therapy. Factors included: Treatment arm (PAd vs. VCD), route of administration (IV vs. SC), existing baseline PN as well as baseline ISS, creatinine ≥2.0 mg/dl , body mass index (BMI), hemoglobin and calcium levels. Fisher's exact test was used for univariate analyses. A multivariate logistic regression model was adapted to analyze the influence of all factors on the occurrence of PN. In this model the impact of a single factor on PN is measured by an odds ratio (OR) based on a characteristic effect (change of one unit for categorical factors and change of interquartile range for continuous factors). Results: Of the analyzed patients, who received at least one dose of trial medication (PAd: n=150 IV/140 SC; VCD: n=154 IV/140 SC), 61 patients (10.2%) developed PN ≥ grade 2. Rates of PN were higher in patients treated with PAd (n=40; 13.5%) compared to VCD (n=21; 7.0%). Neither the presence of higher ISS stage at baseline, nor the route of administration had an impact on development of PN after 3 cycles of induction therapy in univariate analyses. However, PN was more frequent in IV-treated patients during the third cycle of induction therapy (IV: 7.6%; SC: 1.8%, p = 0.001). Median baseline BMI was significantly higher in patients who developed PN (26.9 kg/m2; 19.5-43.7 kg/m2) compared to patients without PN (25.7 kg/m2; 16.7-44-6 kg/m2, p=0.04). Also baseline hemoglobin levels were higher in patients with PN (12.0 g/dl; 6.8-15.9 g/dl) compared to patients without PN (10.8 g/dl; 5.8-16.3 g/dl, p=0.004). While baseline calcium levels were significantly lower in patients with PN (2.3 mmol/l; 1.6-3.5 mmol/l) compared to patients without PN (2.4 mmol/l; 1.6-5.4 mmol/l, p=0.04), baseline creatinine were not different in both groups. Multivariate logistic regression adjusting for the above mentioned factors confirmed the effect of VCD treatment compared to PAd on the development of PN (OR 0.49, 95% confidence interval (CI) [0.28, 0.89], p=0.02) and the importance of pre-existing PN (OR 3.12, 95% CI [1.26, 7.76] , p=0.01). Also baseline calcium (OR 0.71, 95% CI [0.51, 0.99], p=0.04) and hemoglobin levels (OR 1.53, 95% CI [1.01, 2.33] , p=0.05) proved to have an impact on the development of PN in the multivariate model. Conclusion: We confirm the importance of pre-existing neuropathic symptoms and the combination partners for BTZ on the development of PN in patients with newly diagnosed MM. We provide first evidence that clinical baseline characteristics, like calcium and hemoglobin levels, might predict the development of PN. This is in line with preclinical studies showing that dysregulation of calcium homeostasis and oxidative stress in the dorsal root ganglion plays a role in the pathogenesis of BiPN. Disclosures Merz: Janssen: Other: Travel grants; Celgene: Other: Travel grants. Salwender:Celgene: Honoraria; Janssen Cilag: Honoraria; Bristol Meyer Sqibb: Honoraria; Amgen: Honoraria; Novartis: Honoraria. Blau:Janssen: Honoraria, Research Funding; MSD: Honoraria; Celgene: Honoraria, Research Funding; AMGEN: Honoraria; JAZZ pharm: Honoraria; BMS: Honoraria; Shire: Honoraria; Baxalta: Honoraria. Scheid:Janssen: Honoraria; Celgene: Honoraria. Mai:Mundipharma: Other: Travel Grant; Celgene: Other: Travel Grant; Janssen-Cilag: Other: Travel Grant; Onyx: Other: Travel Grant. Hose:Takeda: Other: Travel grant; EngMab AG: Research Funding. Weisel:Janssen Pharmaceuticals: Consultancy, Honoraria, Other: Travel Support, Research Funding; Novartis: Other: Travel Support; Noxxon: Consultancy; Onyx: Consultancy, Honoraria; Amgen: Consultancy, Honoraria, Other: Travel Support; Celgene: Consultancy, Honoraria, Other: Travel Support, Research Funding; BMS: Consultancy, Honoraria, Other: Travel Support. Duerig:Janssen: Consultancy, Honoraria; Celgene: Honoraria. Goldschmidt:Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Chugai: Honoraria, Research Funding, Speakers Bureau; Janssen-Cilag: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Onyx: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Bristol-Myers Squibb: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Millenium: Honoraria, Research Funding, Speakers Bureau; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees.

Abstract: Abstract 3400 Poster Board III-288 To analyse the impact of complete response (CR), near CR (nCR) and very good partial response (VGPR) before and after first high-dose therapy (HDT) followed by autologous stem cell transplantation (ASCT) on overall survival (OS) and progression-free survival (PFS), we evaluated all patients with multiple myeloma (MM) who underwent an ASCT in frontline treatment at our centre. The transplantations were performed between June 1992 and February 2009 giving a minimum follow up of 5 months after ASCT. The retrospective analysis included a total of 994 patients (579 males and 415 females) with a median age of 58 years at time of first ASCT (range 25 - 76 years). Median follow-up after first ASCT was 5.8 years. All patients suffered from symptomatic MM. Before induction treatment 48%, 31% and 21% of patients were in ISS-stage I, II and III, respectively. The following induction regimes were applied prior to HDT: VAD (n=683), TAD (n=74), PAD (n=64), and other regimes (n= 173). The patients were treated with HDT once (n= 460), twice (n=437) or thrice (n=97). 91 patients received an allogeneic SCT, 30 of these before first progression after ASCT. These were censored for PFS at time of allogeneic SCT. Maintenance therapy (interferon n=332, thalidomide n=203, bortezomib n=48 or others n=13) was administered in 596 patients. Overall survival and progression-free survival were calculated from the time of first ASCT. The median OS time was 5.7 years and the median PFS was 2.2 years. Log-rank test, univariate and multivariate Cox PH regression as well as landmark analyses were utilized to assess the prognostic impact of response. We analysed the effect of achievement of CR, of nCR or CR and of VGPR or CR or nCR before and after HDT, respectively. Achieving CR or nCR is a highly significant prognostic factor for PFS and OS before (p 〈 0.001 and p=0.01, respectively) and after first HDT (both p 〈 0.001). The group including VGPR showed superior outcome when assessed after HDT, driven by the effect of CR/nCR. When adjusting for the effect of age, beta-2 microglobulin before ASCT, albumin before ASCT, new drugs before ASCT (thalidomide and bortezomib; yes/no), second ASCT within 9 months (yes/no), maintenance therapy (yes/no), and date of first ASCT, achieving CR or nCR remained a significant prognostic factor (PFS after ASCT: HR=0.66 [0.54;0.80], p 〈 0.001; OS after ASCT: HR=0.65 [0.51;0.83], p=0.001). In addition, we analyzed the effect of duration of response compared to response achievement per se. Patients who sustained their remission (overall response = PR and better) at 3 yrs after first ASCT had a favourable prognosis with respect to OS compared to patients losing remission. Conclusion: In our single-center cohort achieving CR or nCR before and after first HDT is highly prognostic for PFS and OS in MM. Sustained duration of response is also associated with an improved prognosis (3 years landmark analysis). At our centre we recommend that patients not achieving at least an nCR should be treated with a second cycle of HDT. Disclosures: No relevant conflicts of interest to declare.

Abstract: Background: During the past decade, prognostic tools and outcomes of patients with newly-diagnosed multiple myeloma (NDMM) markedly improved. Data from clinical trials evaluating early morbidity and mortality including patients with transplant-eligible NDMM treated with novel agents are scarce. Thus, we aimed to analyze early morbidity and mortality in this patient cohort, devise and validate a predictive score to identify patients at risk. Patients and methods: Between July 2005 and January 2018, 1333 patients with transplant-eligible NDMM from three subsequent phase III trials, HD4, MM5 and HD6 from the German-speaking Myeloma Multicenter Group (GMMG), received a novel agent-based induction therapy with either bortezomib (BTZ) / doxorubicine / dexamethasone (DEX; PAD: n=192, HD4; PAd: n=296, MM5), BTZ / cyclophosphamide / DEX (VCD: n=300, MM5), BTZ / lenalidomide / DEX (VRD: n=272, HD6) or elotuzumab / VRD (ELO-VRD: n=273, HD6). Severe infections (SI) were defined as any infection grade ≥ 3 according to the Common Terminology Criteria for Adverse Events (CTCAE). SI and early deaths were counted on and up to 30 days post induction therapy. Uni-/multivariable logistic regression models were used to assess predictive factors for SI and early death and to account for trial effects. Data from the European Myeloma Network (EMN) 02 / Dutch-Belgian Cooperative Trial Group for Hematology Oncology Foundation (HOVON) 95 phase III trial including 1497 patients with transplant-eligible NDMM receiving induction therapy with VCD were used to validate a predictive score for SI and early mortality. Results: Overall, early mortality during induction therapy was low (n=24, 1.8%) in the GMMG cohort. SI were the most common cause for early deaths (n=15, 62.5%) as compared to MM progression-related death (n=5, 20.8%) and other causes (n=4, 16.7%). Rates of SI during induction therapy were 11.9% (n=159) and decreased in subsequent trial generations: HD4-PAD: 27.1%, MM5-PAd: 10.8%, MM5-VCD: 9.3%, HD6-VRD: 7.3% and HD6-ELO-VRD: 9.9% of patients. In the EMN02/HO95 trial, early mortality was 1.7% (n=25) and rates of SI were 6.8% (n=101). A multivariate model including patient and disease baseline characteristics identified four major risk factors for SI and/or early death on induction therapy in the GMMG cohort: age ( & gt;60 years; odds ratio [OR]=1.70, 95% confidence interval [95% CI] : 1.21-2.40, p=0.002), International Staging System (stage III; OR=1.92, 95% CI: 1.22-2.94, p=0.005), platelet count ( & lt;150/nl; OR=2.03, 95% CI: 1.27-3.30, p=0.004) and World Health Organization (WHO) performance status ( & gt;1; OR=1.82, 95% CI: 1.10-3.06, p=0.022). A sum score based on these four risk factors (one risk factor = one point) was built and included 519 (39.5%), 550 (41.9%) and 245 (18.6%) patients with a score of 0, 1 and ≥2 points. A higher score gradually predicted an increasing risk for SI and/or death during induction therapy: 0 points=7.9%, 1 point=11.5% and ≥2 points=23.2% (p & lt;0.001, Figure 1A); SI only: 0 points=7.7%, 1 point=10.9% and ≥2 points=21.6% (p & lt;0.001, Figure 1B) and early death only: 0 points=0.4%, 1 point=1.3% and ≥2 points=5.7% (p & lt;0.001, Figure 1C). In the EMN02/HO95 cohort, 673 (45.6%), 587 (39.7%) and 217 (14.7%) patients had a score of 0, 1 and ≥2 points. The score was successfully validated in the EMN02/HO95 cohort: SI and/or death during induction therapy: 0 points=5.0%, 1 point=8.3% and ≥2 points=11.9% (p & lt;0.001); SI only: 0 points=4.5%, 1 point=7.0% and ≥2 points=10.0% (p=0.006) and early death only: 0 points=0.5%, 1 point=2.2% and ≥2 points=2.5% (p=0.01). Conclusions: To date, this is the largest pooled analysis of individual patient data on early morbidity and mortality in patients with transplant-eligible NDMM treated with novel agent-based induction therapy. Our analysis highlights a decreasing incidence of SI and early mortality and proposes a validated, easy-to-use score to identify patients at excessive risk for SI and/or early death during induction therapy. This allows the implementation of intensive monitoring, preventive and supportive strategies for this subgroup of patients in further clinical trials and also routine care. Figure 1 Figure 1. Disclosures Mai: Celgene / BMS: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: travel accommodations and expenses, Research Funding; Glaxo Smith Kline: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: travel accommodations and expenses, Research Funding; Janssen-Cilag: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: travel accommodations and expenses, Research Funding; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: travel accommodations and expenses, Research Funding. Salwender: AbbVie: Honoraria, Other: TRAVEL, ACCOMMODATIONS, EXPENSES; Amgen: Honoraria, Other: TRAVEL, ACCOMMODATIONS, EXPENSES; Takeda: Honoraria; Sanofi: Honoraria, Other: TRAVEL, ACCOMMODATIONS, EXPENSES; GlaxoSmithKline: Honoraria, Other: TRAVEL, ACCOMMODATIONS, EXPENSES; Janssen-Cilag: Honoraria, Other: TRAVEL, ACCOMMODATIONS, EXPENSES; Bristol-Myers Squibb/Celgene: Honoraria, Other: TRAVEL, ACCOMMODATIONS, EXPENSES; Oncopeptides: Honoraria; Chugai: Honoraria; Pfizer: Honoraria. Zweegman: Oncopeptides: Membership on an entity's Board of Directors or advisory committees; Sanofi: Membership on an entity's Board of Directors or advisory committees; BMS: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding. Munder: GSK: Consultancy; BMS: Consultancy, Honoraria; Abbvie: Consultancy; Takeda: Consultancy, Honoraria; Amgen: Honoraria; Sanofi: Consultancy; Janssen: Consultancy, Honoraria; Incyte: Research Funding. Pantani: Janssen: Honoraria; Amgen: Honoraria. Brossart: BMS: Consultancy, Honoraria, Research Funding; Amgen: Consultancy, Honoraria; MSD: Honoraria. Beksac: Amgen: Consultancy, Speakers Bureau; Janssen: Consultancy, Speakers Bureau; Celgene: Consultancy, Speakers Bureau; Sanofi: Consultancy, Speakers Bureau; Takeda: Consultancy, Speakers Bureau; Oncopeptides: Consultancy. Raab: BMS: Consultancy, Membership on an entity's Board of Directors or advisory committees; Roche: Consultancy; Abbvie: Consultancy, Honoraria; Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding; GSK: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Sanofi: Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees. Dürig: Celgene: Membership on an entity's Board of Directors or advisory committees, Other: Travel Support, Speakers Bureau; Janssen: Membership on an entity's Board of Directors or advisory committees, Other: Travel Support, Speakers Bureau; Takeda: Membership on an entity's Board of Directors or advisory committees; BMS: Membership on an entity's Board of Directors or advisory committees. Besemer: Takeda: Honoraria; Janssen: Honoraria; GSK: Honoraria. Fenk: GSK: Honoraria; Amgen: Honoraria; Janssen: Honoraria; BMS/Celgene: Honoraria; Takeda: Honoraria. Haenel: Bayer Vital: Honoraria; Jazz: Consultancy, Honoraria; GSK: Consultancy; Takeda: Consultancy, Honoraria; Roche: Consultancy, Honoraria; Novartis: Consultancy, Honoraria; Amgen: Consultancy; Celgene: Consultancy, Honoraria. Metzler: Takeda: Consultancy; BMS: Consultancy; GSK: Consultancy; Amgen: Consultancy; Janssen: Consultancy; AstraZeneca: Consultancy; Pfizer: Consultancy; Sanofi: Consultancy. Graeven: Amgen: Honoraria; Sanofi Aventis: Honoraria; Celgene: Honoraria, Research Funding; Johnson and Johnson: Honoraria; Astra Zeneca: Honoraria; MSD: Consultancy; Boehringer Ingelheim: Honoraria; BMS: Honoraria; Fujifilm: Honoraria; Roche: Research Funding; Gilead: Research Funding; Ipsen Bioscience: Research Funding; MacroGenics: Research Funding. Boccadoro: Janssen and GSK: Membership on an entity's Board of Directors or advisory committees; Sanofi, Celgene, Amgen, Janssen, Novartis, Bristol-Myers Squibb, and AbbVie: Honoraria; Sanofi, Celgene, Amgen, Janssen, Novartis, Bristol-Myers Squibb, and Mundipharma: Research Funding. Scheid: Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees; BMS: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche: Consultancy; Abbvie: Honoraria; Takeda: 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; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees. Dimopoulos: Janssen: Honoraria; BMS: Honoraria; Amgen: Honoraria; Takeda: Honoraria; Beigene: Honoraria. Weisel: Oncopeptides: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Bristol Myers Squibb: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Roche: Honoraria; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Adaptive Biotechnologies: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; GSK: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Karyopharm: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Abbvie: Consultancy; Novartis: Honoraria; Pfizer: Honoraria. Cavo: Adaptive Biotechnologies: Consultancy, Honoraria; Novartis: Honoraria; GlaxoSmithKline: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel Accommodations, Speakers Bureau; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; AbbVie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: TRAVEL, ACCOMMODATIONS, EXPENSES, Speakers Bureau; Sanofi: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Bristol-Myers Squib: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Sonneveld: SkylineDx: Honoraria, Research Funding; Karyopharm: Consultancy, Honoraria, Research Funding; Celgene/BMS: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria, Research Funding; Amgen: Consultancy, Honoraria, Research Funding; Takeda: Consultancy, Honoraria, Research Funding. Goldschmidt: Mundipharma: Research Funding; Incyte: Research Funding; Janssen: Consultancy, Honoraria, Other: Grants and/or Provision of Investigational Medicinal Product, Research Funding; Johns Hopkins University: Other: Grant; Molecular Partners: Research Funding; MSD: Research Funding; GSK: Honoraria; Chugai: Honoraria, Other: Grants and/or Provision of Investigational Medicinal Product, Research Funding; Celgene: Consultancy, Honoraria, Other: Grants and/or Provision of Investigational Medicinal Product, Research Funding; BMS: Consultancy, Honoraria, Other: Grants and/or Provision of Investigational Medicinal Product, Research Funding; Adaptive Biotechnology: Consultancy; Amgen: Consultancy, Honoraria, Other: Grants and/or Provision of Investigational Medicinal Product, Research Funding; Novartis: Honoraria, Research Funding; Dietmar-Hopp-Foundation: Other: Grant; Sanofi: Consultancy, Honoraria, Other: Grants and/or Provision of Investigational Medicinal Product, Research Funding; Takeda: Consultancy, Research Funding.