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Introduction Data on the economic burden of disease progression among multiple myeloma (MM) patients who have had a stem cell transplant (SCT) in the US are limited. This study evaluated the impact of disease progression on healthcare resource utilization (HRU) and costs among these patients in the US. Methods Adult patients (pts) with a confirmed MM diagnosis (Dx), defined as ≥1 inpatient or ≥2 non-diagnostic outpatient claims 30-365 days apart who initiated a course of MM therapy (Rx) during the study period (Jan 1, 2006 to Dec 31, 2016) and received SCT during the first year after the initial diagnosis of MM were identified from the Truven Analytics MedStat MarketScan® Commercial Claims and Encounters and Medicare and Coordination of Benefits databases. The first date with Dx for MM was defined as the "Dx date" and line of therapy (LOT) was identified based on an adaptation of a previously-developed algorithm. Pts were excluded if they had a gap in enrollment during the period beginning 6-month before the Dx date through 30-days after the first LOT (1L) initiation date, received MM Rx, unclassified antineoplastic medications, or SCT before the Dx date, or had missing information required to identify LOT or assess baseline characteristics or study outcomes. The 12 months after initiation of each LOT was designated the "event identification period" for progression. Disease progression was defined as advancement to next LOT, diagnosis or procedure codes indicative of bone metastasis, hypercalcemia, soft tissue plasmacytoma, skeletal related events, or acute kidney disease while off MM Rx, or death. The "event date" for progression was defined as date with evidence of progression. For each pt with progression, one pt without progression was randomly selected and assigned an event date to ensure that the distribution of time from LOT initiation to event date for pts without progression was the same as the distribution of time from LOT initiation to event date for pts with progression. For each LOT (L1-L3), annual HCRU and costs from index date, defined as 30-day before the event date, through disenrollment or end of the study period were compared for pts with vs without progression using inverse probability of treatment weighting (IPTW) to adjust for differences between groups in baseline characteristics including year of index date, age, gender, region, plan type, Medicare status, comorbidities, and pre-index HRU and healthcare costs. All costs were adjusted to 2016 US $. In a subgroup analysis, HCRU and costs were evaluated for LOTs initiated from 2013 to 2016 to reflect patterns of treatment in current era. Results Of the 28,184 adult MM pts who received ≥1 MM Rx during the study period, 3226 qualified for the study, including 837 pts with progression and 2389 without progression during 1L. The corresponding numbers for 2L, and 3L were 412 and 589, and 226 and 196, respectively. Mean age at index date was 57 years; 57% were male. After IPTW, all baseline characteristics were well balanced in all LOTs with standardized mean differences <0.1 for most baseline characteristics. The mean number of hospitalizations per year was greater for pts with progression in all LOTs, with differences ranging from 1.11 (95%CI 0.85, 1.37) for 2L to 0.34 (95%CI 0.21, 0.47) for 1L. In all LOTs, annual costs of inpatient and outpatient services were greater for pts with progression while costs of outpatient prescriptions were greater among patient without progression. Total healthcare costs were greater for pts with vs without progression in all LOTs with hospitalizations and outpatient visit costs being key drivers. Total incremental annual costs in those who progressed were higher by $13,386 (1L), $105,004 (2L), and $70,206 (3L). When the analysis was restricted to LOTs initiated between 2013 and 2016, the incremental costs in pts who progressed were generally greater in the most recent era: $43,381 (1L), $113,797 (2L), and $115,327 (3L). Conclusions For MM pts receiving drug Rx and SCT the economic burden of disease progression is substantial across all LOTs. Incremental costs of progression are largely attributable to hospitalizations and outpatient visits. Treatments that prevent or delay progression are likely to yield important reductions in downstream disease management costs. These savings should be considered in frameworks assessing the value of innovative treatments for MM. Disclosures Fonseca: AbbVie, Amgen, Bayer, Celgene, Kite, Janssen, Juno, Merck, Pharmacylics, Sanofi, Takeda: Other: Consultant/Advisor; Prognosticatin of MM based on Genetic Categorization by FISH: Patents & Royalties; Adaptive Biotechnologies: Other: Scientific Advisory Board. Hagiwara:Amgen Inc.: Research Funding. Panjabi:Amgen Inc.: Employment, Other: Owns Amgen stock, Research Funding. Yucel:Amgen Inc.: Employment, Other: Owns Amgen stock, Research Funding. Buchanan:Amgen Inc.: Employment, Other: Owns Amgen stock, Research Funding. Delea:Amgen Inc.: Research Funding.

PURPOSE Observation is the current standard of care for smoldering multiple myeloma. We hypothesized that early intervention with lenalidomide could delay progression to symptomatic multiple myeloma. METHODS We conducted a randomized trial that assessed the efficacy of single-agent lenalidomide compared with observation in patients with intermediate- or high-risk smoldering multiple myeloma. Lenalidomide was administered orally at a dose of 25 mg on days 1 to 21 of a 28-day cycle. The primary end point was progression-free survival, with disease progression requiring the development of end-organ damage attributable to multiple myeloma and biochemical progression. RESULTS One hundred eighty-two patients were randomly assigned—92 patients to the lenalidomide arm and 90 to the observation arm. Median follow-up is 35 months. Response to therapy was observed in 50% (95% CI, 39% to 61%) of patients in the lenalidomide arm, with no responses in the observation arm. Progression-free survival was significantly longer with lenalidomide compared with observation (hazard ratio, 0.28; 95% CI, 0.12 to 0.62; P = .002). One-, 2-, and 3-year progression-free survival was 98%, 93%, and 91% for the lenalidomide arm versus 89%, 76%, and 66% for the observation arm, respectively. Only six deaths have been reported, two in the lenalidomide arm versus four in the observation arm (hazard ratio for death, 0.46; 95% CI, 0.08 to 2.53). Grade 3 or 4 nonhematologic adverse events occurred in 25 patients (28%) on lenalidomide. CONCLUSION Early intervention with lenalidomide in smoldering multiple myeloma significantly delays progression to symptomatic multiple myeloma and the development of end-organ damage.

Abstract Introduction - IMIDs are critical in the treatment of multiple myeloma (MM). Unfortunately, many patients become resistant and this is a major challenge in MM therapy. IMID resistance can be caused by CRBN mutations (rarely) and by upregulation of specific antioxidative mechanisms. We hypothesized that measuring baseline antioxidative capacity might be a useful predictor of IMID sensitivity in the clinic. Methods - To develop a quantitative assay for determining cellular antioxidative capacity of MM cells we measured total cellular oxidized flavin adenine dinucleotide (FAD) after treatment with H2O2. FAD has auto-fluorescent properties that can be measured via flow cytometry. Cells with high antioxidative capacity generate more FAD, and cells with low anti-oxidative capacity generate less FAD. MM cells with an increase in FAD after H2O2 were considered IMID resistant and those with no change in FAD were considered IMID sensitive (Figure 1). Clinical IMID resistance/sensitivity was defined clinically during blinded retrospective review, with disease progression based on the IMWG criteria. After blinded review of clinical outcomes, the patient flow cytometry results were disclosed to evaluate the predictive value of the flow cytometry assay for detection of IMID resistance. Results - Of 40 patients who underwent testing, 26 were IMID resistant via flow and were considered as being clinical resistant 17 (65%). Conversely, 14 patients were IMID sensitive via flow and 12 (86%) were considered to be clinical sensitive. There was a significant correlation between clinical assessment and flow cytometry in determination of IMID resistance patterns (Table 1). The sensitivity and specificity of our assay was 89% and 57% with a positive and negative predictive value of 65% and 86% respectively. A limitation of our clinical assessment was that 16 patients (38%) were treated with combination therapy; IMIDs plus a proteasome inhibitor or a monoclonal antibody. Of the 11 patients with discordant results by flow and clinical outcome, 7 (64%) were not on therapy at the time of testing and 6 (55%) had flow testing on the bone marrow sample performed on day 100 following an autologous transplant. Two (7%) of the 29 patients with correlative results were off all therapy at the time of testing, 1 with testing on the day 100 marrow sample after transplant. Conclusions - This early testing of our assay shows promising results predicting clinical sensitivity via our flow based assay. The testing demonstrates a high sensitivity and negative predictive value, with less ability to assess for resistance. However, there were limitations to this study. The majority of patients with discordant results were off IMID therapy at the time of flow cytometry and many of these were assessed on transplant day 100 marrow samples. Depth of measureable residual disease was not readily available on all marrow samples tested. It is probable that flow testing for IMID resistance is inaccurate in patients with deeper responses to therapy, especially those who are minimum residual disease (MRD) negative. Additionally, several patients were on combination IMID, proteasome inhibitor, and monoclonal antibody. It is possible that clinical IMID resistance was not detected due to the anti-MM activity of the additional therapies. Additional larger scale prospective studies are needed to validate these findings as this method of testing could potentially provide providers with powerful information allowing them to personalize therapy for their patients. Disclosures Fonseca: Mayo Clinic: Employment; Amgen: Consultancy.

Abstract Background: Each additional line of therapy is associated with lower rates of deeper responses, shorter durations of treatment-free intervals, and increased rates of toxicities/comorbidities in patients with multiple myeloma (MM; Yong K, et al. Br J Haematol 2016. 175[2]:252-264), all of which are factors that contribute to treatment discontinuation. In order to characterize the newly diagnosed MM (NDMM) patient population in the United States not treated with a stem-cell transplant based on the number of subsequent lines of therapy (LOT) received, we examined baseline patient characteristics and pre-existing comorbidities, frontline treatment patterns, and attrition rates for these patients according to whether subsequent LOT was received or not received. Methods: NDMM patients were identified from 3 US patient-level data sources: the Surveillance, Epidemiology, and End Results (SEER)-Medicare Linked database (from January 2007 through December 2014), the OPTUM™ Commercial Claims database (from January 2000 through March 2017), and the OPTUM™ Electronic Medical Records (EMR) database (from January 2007 through March 2016). Patients included in the assessment had 1) an index diagnosis of MM on or after 1 January 2007, 2) known gender, 3) medical prescription coverage in place at diagnosis, 4) a 1-year look-back period prior to the index diagnosis, 5) no prior malignancies in the 1-year period prior to index diagnosis, and 6) received ≥1 LOT. The analysis was limited to patients who did not receive stem cell transplantation at any time during their follow-up. Descriptive and logistic regression analyses were conducted to characterize and compare patients who received or did not receive a subsequent LOT. Results: The analysis included a total of 7,724 patients (1 LOT only: n = 3,906; 2+ LOT: n = 3,818). A summary of baseline patient characteristics and pre-existing comorbidities by LOT is summarized in Table 1. Patients who received a subsequent LOT vs those that did not were significantly younger (median age 72.0 vs 74.0 years; P <0.0001) and had significantly lower mean Charleston Comorbidity Index (CCI) score due to lower occurrence of renal, cardiac, and hepatic comorbidities (Table 1). Older age at diagnosis and presence of renal, congestive heart failure (CHF), hepatic, and pulmonary comorbidities were associated with higher attrition. The regimens used in frontline treatment included bortezomib/dexamethasone (26%), lenalidomide/dexamethasone (21%), bortezomib/lenalidomide/dexamethasone (11%), a bortezomib/alkylator ± steroid combination (6%), bortezomib monotherapy (10%), lenalidomide monotherapy (6%), thalidomide monotherapy (4%), and other (17%). The proportions of patients progressing to each subsequent line of therapy are shown in Table 2. In total, 49% of patients went on to receive a second line of therapy, and 55% of patients receiving a second line of therapy went on to receive a third line of therapy. The incidence of patients not receiving subsequent lines of therapy due to death or being lost to follow up by LOT is summarized in Table 2. Conclusions: A majority of non-transplant patients with NDMM in the study did not progress to subsequent lines of therapy, with attrition as high as 50% per line of therapy and only <8% of patients reaching LOT 5. This high level of attrition is associated with older age and poor comorbidity status of non-transplant patients with NDMM. Therefore, utilizing the most optimal regimens upfront (rather than reserving them for later lines) is warranted. Disclosures Fonseca: Mayo Clinic: Employment; Amgen: Consultancy. Usmani:Abbvie, Amgen, Celgene, Genmab, Merck, MundiPharma, Janssen, Seattle Genetics: Consultancy; Amgen, BMS, Celgene, Janssen, Merck, Pharmacyclics,Sanofi, Seattle Genetics, Takeda: Research Funding. Mehra:Janssen Global Services, LLC: Employment. Slavcev:Janssen Global Services, LLC: Employment. Ukropec:Janssen Scientific Affairs, LLC: Employment. Lam:Janssen Global Services, LLC: Employment. Potluri:SmartAnalyst Inc.: Employment.

Abstract Despite recent advances and improvement in treatment options, chronic lymphocytic leukemia (CLL) is still an incurable disease. Recent advancement in parallel sequencing technology has provided better understanding of genetic landscape and clonal architecture underlying disease course. Furthermore, mutation status of TP53, SF3B1, NOTCH1, and BIRC3 has improved current CLL risk stratification. In order to better understand the genetic basis and clonal evolution underlying disease progression we analyzed a homogeneously treated cohort of CLL cases at multiple time points before and after therapy. We performed WES in 30 sequential samples from 12 CLL cases. All 12 cases received PCR (pentostatin, cyclophosphamide and rituximab) based chemoimmunotherapy as initial treatment. Of these 12 cases, two had samples available both >6 months prior to enrollment and at treatment initiation, seven patients who experienced relapse had samples available at both treatment initiation and at and the time of relapse, and three patients had samples >6 months prior to enrollment, at treatment initiation, and at relapse. These cases were previously characterized by aCGH/FISH. R function Mclust and kernel density estimate (KDE) plots were used to identify subclonal heterogeneity. An average of 102-fold depth coverage was obtained with an average of 80% of the targeted regions being covered by at least 30X. Overall, we detected a total of 219 nonsynonymous Single Nucleotide Variants (SNV) and indels (average 19, range 11-33). Del13q (42%) was identified as most prevalent copy number abnormality followed by trisomy 12 (33%), del11q and del17p (17% each). Recurrent mutations were identified in NOTCH1 (33%), DDX3X (25%), TP53, SF3B1 XPO1 and MED12 (17% each). Other tumor implicated genes such as CARD11, NOTCH2, NOTCH4, DIS3, TRAF2, NFKBID, CHK2 and RB1 were found mutated in individual cases. In all 12 cases we identified at least one relevant cytogenetic abnormalities (del11q32, del13q14, del17p13, trisomy 12) and/or a mutated driver gene. Interestingly we found NOTCH1, DDX3X and XPO1 mutated at a significantly higher prevalence than previous studies (10%, 2% and 4%, respectively). Since all cases in our cohort correspond to individuals with progressive disease, a plausible explanation for the higher prevalence of mutations in our cohort is that these mutations are associated with disease progression. By WES we identified multiple subclones in 58% of cases (7 of 12 cases), as compared to previously identified 33% (4 of 12 cases) by CGH/FISH. In 5 chemotherapy naïve cases, no significant increase in genomic complexity was detected with disease progression. In contrast, 5 out of 10 cases with samples analyzed before CIT and at the time of relapse had changes in clonal dynamics, with initially dominant subclones diminishing in response to therapy and the available empty niche being occupied by expansion of another “fitter” subclone at the time of relapse. No acquisition of tumor associated gene mutations was seen post therapy or associated with relapse in 9 of 10 cases. In the remaining case we identified an interesting example of convergent evolution. The pre-therapy sample was comprised of a unique clone characterized with del11q13, mutations in SF3B1 (G742D) and DDX3X (pE196fs). After therapy that clone was either eradicated or reduced to below detection level. Interestingly another clone emerged after relapse that harbored an independent del11q22 and mutations affecting different aminoacids of SF3B1 (K700E) and DDX3X (pL21fs). The strong selection of impairment in these genes during disease progression suggests a key role of these pathways/genes in the pathogenesis of this patient. In conclusion, these studies provide additional insight into the genomic landscape and clonal architecture in a cohort of homogeneously treated CLL cases before and after therapy. Stable clonal architecture was seen in prior to treatment, whereas clonal evolution leading to increased tumor heterogeneity occurred after the under selection selective pressure of therapy in relapsed cases. Early identification of tumoral heterogeneity and underlying genetic abnormalities might provide better targets for therapy to decrease the likelihood of relapse. Disclosures: Fonseca: Medtronic: Consultancy; Otsuka: Consultancy; Celgene: Consultancy; Genzyme: Consultancy; BMS: Consultancy; Lilly: Consultancy; Onyx: Consultancy, Research Funding; Binding Site: Consultancy; Millennium: Consultancy; AMGEN: Consultancy; Cylene: Research Funding; Prognostication of MM based on genetic categorization of the disease: Prognostication of MM based on genetic categorization of the disease, Prognostication of MM based on genetic categorization of the disease Patents & Royalties. Shanafelt:Genentech: Research Funding; Glaxo-Smith-Kline: Research Funding; Cephalon: Research Funding; Hospira: Research Funding; Celgene: Research Funding; Polyphenon E International: Research Funding.

In multiple myeloma (MM) the interaction of plasma cells, bone marrow stromal cells and tumor associated macrophages (TAMs) plays a significant role in conferring resistance to therapy and in the maintenance of residual disease. Folate receptors (FR) are specifically expressed on metabolically active malignant cells and TAMs and their expression in normal tissues and resting macrophages is limited. FR mediates folate uptake by receptor-mediated endocytosis. This qualifies the receptor to be exploited for drug delivery of folate conjugated cancer therapeutics. Our primary goal in this study is to evaluate the expression of functional FR in MM cells and TAMs with a view to exploit this for folate conjugated targeted therapy for MM. First we evaluated the presence of TAMs in paraffin embedded bone marrow slides of newly diagnosed MM patients with CD68 (pan-Macrophage marker) and CD163 antibodies (specific marker of TAMs) and found extensive infiltration of macrophages in bone marrow from MM patients. Next to evaluate expression of FR in MM cells, we employed an FR antibody and evaluated MM cell lines with immunoblot, flow cytometry and confocal microscopy. In a panel of ten MM cell lines, we found that out of the three FR isoforms (α, β and γ), FR beta (FR-β) is expressed by all of them. Next to test whether this expressed receptor is indeed functional, we incubated the cells with folate deficient media, added different concentrations of EC17 (folate conjugated to FITC, Endocyte Inc.) to the medium and looked for the uptake by flow cytometry after washing off the drug at different time points (after 10, 20, 40 and 60 min).We observed that the uptake begins in 10 min and is saturated at 1 hour with 100nM Folate-FITC. With confocal imaging, Folate-FITC was found in the cytoplasm of MM cells suggesting internalization of Folate-FITC and localization in the cytoplasm. In addition to myeloma cell lines, we also confirmed the uptake of Folate-FITC in CD138+ plasma cells of a newly diagnosed myeloma patient by flow cytometry. This strongly suggests that MM cells express functional FR-β. To test the specificity of this FR mediated uptake, we pre-incubated cells with 0.1mM folic acid in medium for 30 min and then added EC17. This maneuver blocked the activity mediated by FR and no uptake was observed , which proves that the Folate-FITC is internalized only through the FR. To evaluate the expression of FR in-vivo samples, we stained paraffin embedded bone marrow slides of newly diagnosed MM patients with FR-β antibody and TAM specific markers. We observe that FR is expressed on both MM cells as well as TAMs. To assess the endurance of cytotoxic effect of folate conjugated chemotherapeutic agents, we treated MM cell lines with folate conjugated vinka alkaloids and compared them to unconjugated drug and found no significant difference in their action suggesting conjugation with folate does not alter its efficacy. To assess potential toxicity of folate conjugated therapeutics, we obtained CD34+ cells and looked for the uptake of Folate-FITC with flow cytometry. We found no uptake and this is in line with previous reports suggesting that CD34 positive cells express nonfunctional FR. So we propose that FR qualify as potential targets for cancer treatment. Folate targeted therapy using folate-conjugated drugs which can selectively act against both MM cells and supporting TAMs has the potential of specific anti-MM tumoricidal activity. This therapeutic approach would broaden the use of drugs that could be conjugated with folate for MM therapy. Additionally assessment of TAMs in bone marrow sections of MM patients would add another feature for grading, classifying and prognosticating MM. Disclosures: Fonseca: Cylene: Research Funding; AMGEN: Consultancy; Millennium: Consultancy; Binding Site: Consultancy; Onyx: Consultancy, Research Funding; Lilly: Consultancy; BMS: Consultancy; Genzyme: Consultancy; Celgene: Consultancy; Medtronic: Consultancy; Otsuka: Consultancy; Prognostication of MM based on genetic categorization of the disease: Prognostication of MM based on genetic categorization of the disease, Prognostication of MM based on genetic categorization of the disease Patents & Royalties.

Abstract Abstract 3527 Increasing evidence compiled from our lab and several others is illuminating the importance of epigenetic mechanisms in the pathogenesis of multiple myeloma (MM). The biochemical modifications that govern epigenetics are DNA methylation, and post-translational modifications of histone proteins on arginine and lysine residues. Modifications are generally associated with activation or repression of gene transcription depending upon the specific position of the modification. Histone methylation, catalyzed by histone methyltransferases (HMT) and histone demethylases (HDMT) are crucial for the proper programming of the genome during development. Deregulation of the methylation machinery can alter chromatin configuration and disrupt normal transcriptional programs, both features of cancer cells. Misregulated methylation may result from several genetic alterations in chromatin-modifying enzymes, which can include mutations, over-expression or chromosomal abnormalities. Indeed, genomic alterations of MLL, NSD1, CREBBP(CBP) MMSET and UTX, all encoding proteins involved in post-translational histone modifications, have been implicated in MM. The purpose of our study was to interrogate existing genomics datasets to identify additional HMT or HDMT genes that may be important in the pathogenesis of MM and, thus could become potential therapeutic targets. To identify novel HMT or HDMT in MM we mined existing expression, copy number and whole genome sequencing data generated as part of the Multiple Myeloma Research Consortium Genomics Initiative. Collectively, the datasets converged on numerous alterations involving histone methylation on lysine 9 (H3K9). One of these genes, a HDMT called JMJD1C, was over-expressed in approximately 15% of MM samples examined. We validated over-expression of JMJD1C expression by RT-PCR in over 50 clinical MM samples and 10 human myeloma cell lines (HMCLs). We also confirmed over-expression of JMJD1C by immunohistochemistry (IHC) of a tissue microarray (TMA) consisting of over 60 MM samples. Next we examined the levels of JMJD1C expression and H3K9 methylation by IHC, RT-PCR and western blot to determine the extent to which JMJD1C expression is associated with a decrease in H3K9 methylation (or vice versa). We demonstrated this negative correlation in 6/10 HMCL including OCIMY7 and KMS11 and in over 60% of clinical samples examined on the TMA. Furthermore, we demonstrated that H3K9 methylation, a repressive mark associated with heterochromatin, is low in a large percentage of samples. In addition, we generated double knockout isogenic cell line pairs using zinc finger nuclease technology to evaluate the direct role of JMJD1C on H3K9 methylation, cell function and chromatin and expression level changes using ChIP-seq and RNA-seq analyses. In summary our preliminary results demonstrate that JMJD1C is highly expressed in a significant percentage of MM patients. Our results demonstrate a noticeable inverse relationship of JMJD1C expression to H3K9. This reflects the importance of JMJD1C in modifying the H3K9 repressive mark and suggests that loss of repression due to JMJD1C-mediated histone demethylation disrupts the chromatin machinery and leads to neoplastic processes. Further studies are ongoing to realize JMJD1C as a potential and novel therapeutic target in MM. Disclosures: No relevant conflicts of interest to declare.

Abstract Introduction Previous studies have documented substantial economic burden for multiple myeloma (MM) patients (pts). However, data on the economic burden of disease progression in the US are limited. In this study, we estimated effects of disease progression on healthcare resource utilization (HRU) and costs among pts with MM who have received at least one line of therapy (LOT) in the US. Methods Data from the Truven Analytics MedStat MarketScan® Commercial Claims and Encounters and Medicare and Coordination of Benefits databases were used. A retrospective incident user cohort of adult pts with a confirmed diagnosis (Dx), defined as ≥1 inpatient or ≥2 non-diagnostic outpatient claims 30-365 days apart with diagnosis, of MM who initiated a course of MM therapy during the study period (Jan 1, 2006 to Dec 31, 2016) was identified. The first date with Dx for MM was defined as the "Dx date" and LOT was identified based on a published algorithm. Pts were excluded if they had a gap in enrollment during the period beginning 6-month before the Dx date through 30-days after the first LOT (1L) initiation date, received MM therapy or unclassified antineoplastic medications before the Dx date or stem cell transplant (SCT) at any time during the study period, or had missing information required to identify LOT or assess baseline characteristics or study outcomes. The 12 months after initiation of each LOT was designated the "event identification period" for progression. Disease progression was defined as advancement to the next LOT, ICD-9/10 or CPT/HCPCS diagnosis or procedure codes indicative of bone metastasis, hypercalcemia, soft tissue plasmacytoma, skeletal related events, or acute kidney disease while off MM therapy, or death. The "event date" for progression was defined as date with evidence of progression. For each pt with progression, one pt without progression was randomly selected and assigned an index date to ensure that distribution of time from LOT initiation to event date for pts with progression was the same as that for pts without progression. For each LOT (L1-L4), annual HRU and costs from index date through disenrollment or the end of the study period were compared for pts with vs without progression using inverse probability of treatment weighting (IPTW) to adjust for differences between groups in baseline characteristics including year of index date, age, gender, region, plan type, Medicare status, comorbidities, and pre-index HRU and healthcare costs. All costs were adjusted to 2016 US dollars. In a subgroup analysis, HRU and costs were evaluated for LOTs initiated from 2013 to 2016 to reflect patterns of treatment in current era. Results Of the 28,184 adult MM pts who received one or more MM therapy during the study period, 11,179 qualified for the study, including 4468 and 6598 pts with and without progression during 1L, respectively. The corresponding numbers for 2L, 3L, and 4L were 1563 and 2207, 618 and 714, and 244 and 260, respectively. Mean age at index date was 68 years; 57% were male. After IPTW, all baseline characteristics were well balanced in all LOTs with standardized mean differences <0.1 for all characteristics. The mean number of hospitalizations per year was greater for patents with progression in all LOTs, with differences ranging from 0.46 (95%CI 0.40, 0.52) for 1L to 0.89 (95%CI 0.67, 1.11) for 3L. In all LOTs, annual costs of inpatient and outpatient services were greater for pts with progression while costs of outpatient prescriptions were greater among patient without progression. Total healthcare costs were greater for pts with vs without progression in all LOTs with hospitalizations and outpatient visit costs being key drivers. Total incremental annual costs in those who progressed were higher by $30,381 (1L), $33,064 (2L), $34,495 (3L), and $25,163 (4L). When the analysis was restricted to LOTs initiated between 2013 and 2016, the incremental costs in patients who progressed were greater in the most recent era: $52,739 (1L), $49,012 (2L), $25,329 (3L), and $65,400. Conclusions For MM pts receiving drug therapy, the economic burden of disease progression is substantial across all LOTs and this burden is greater in the most recent era (2013 to 2016). Treatments that prevent or delay progression are likely to yield important reductions in downstream disease management costs. These savings should be considered in frameworks assessing the value of innovative treatments for MM. Disclosures Hagiwara: Jazz Pharmaceuticals: Research Funding; Jazz Pharmaceuticals: Consultancy; Amgen: Research Funding; Amgen: Consultancy; Policy Analysis, Inc: Employment. Delea:Novartis: Consultancy, Research Funding; Amgen: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding; Sanofi: Consultancy, Research Funding; Takeda: Research Funding; Seattle Genetics: Research Funding; Policy Analysis Inc.: Employment. Panjabi:Amgen: Employment, Equity Ownership. Yucel:Amgen: Employment, Equity Ownership. Fonseca:Mayo Clinic: Employment; Amgen: Consultancy.

Background The precise molecular mechanism and targets of lenalidomide specific anti-Multiple Myeloma (MM) activity remain largely unknown, although, cereblon (CRBN) has been identified as a central mediator of activity with IRF-4 acting as a downstream molecule. Lenalidomide resistance in MM cells which, despite CRBN depletion, are able to restore their IRF-4 levels suggests the existence of alternative pathways. Methods To measure apoptosis and gene expression analysis 1x 106cells were incubated with 10μm to 50μm of lenalidomide for 24 to 96 hours before they were examined by annexin-PI and FACS analysis. Gene and protein expression were measured by RT-PCR, western blot, and immunohistochemistry. For lenalidomide followed bortezomib serial studies, cells were incubated with 10μm of lenalidomide for 48 hours and later treated with bortezomib for 24 to 48 hrs. CRBN and immunoglobulin light chain knock-down were performed by lentiviral mediated shRNA. Results We found lenalidomide induces Endoplasmic reticulum stress (ERS) via accumulation of intracellular immunoglobulin proteins, but only in the presence of CRBN in a panel of MM cell lines. This accumulation of intracellular proteins resulted in ERS as documented by western blot and RT-PCR in OPM2 and MMIS cell lines. We next utilized OPM2 cells knocked down for CRBN and control, non-target (NT), and treated with different doses of lenalidomide. After three days of treatment an ERS response was occurring in OPM2-NT cells but not in CRBN knockdown cells. Using Western blot we found decreased XBP-1u and increased XBP-1s, ERS marker proteins, in CRBN positive (NT) cells after 72 hours of lenalidomide treatment, but not in CRBN knock-down cells. Another ERS marker GRP78/BiP was also clearly accumulated after lenalidomide treatment in CRBN positive cells. Inactivation of the tumor suppressor p53 by degradation is a mechanism utilized by cells to adapt to ERS has been reported. We also found that p53 protein down regulated after lenalidomide treatment in CRBN positive OPM2 and MMIS cells. We have analyzed other isogenic cell lines MM1.S (lenalidomide-sensitive) and isogenic MM1.Sres (lenalidomide-resistant) HMCLs and found that lenalidomide induces ERS in MM1.S but not MM1.Sres cells. CRBN is important for lenalidomide to induce immunoglobulin protein accumulation and ERS was further proved by over-expressing CRBN in OCI-My5 MM cell line and subsequent lenalidomide treatment. To test the effect of light chain accumulation as ER stressors, we knocked down immunoglobulin light chain lambda in human MM cell line OPM2. Knock-down of lambda light chain in OPM2 cells resulted in lenalidomide resistance and it induced endoplasmic reticulum stress mediated anti-myeloma activity. Our preliminary data reveals that lenalidomide mediated progressive ERS can positively enhance bortezomib induced apoptosis in an in-vitro MM model. We pre-treated myeloma cell lines with lenalidomide and subsequently treated with bortezomib. MM cells pre-treated with lenalidomide for two days and there after treated with bortezomib clearly shown increased sensitivity to bortezomib induced apoptosis than non-pre-lenalidomide treated cells. Conclusion Here we show that lenalidomide causes accumulation of immunoglobulin light chains, inducing progressive ER stress, resulting in anti-myeloma activity and that effect depends on the presence of CRBN. Proteasome inhibitors such as bortezomib also sensitize MM cells to endoplasmic reticulum stress-mediated apoptosis. Our data demonstrated the synergistic effect of lenalidomide and proteasome inhibitors, likely due to the augmented protein stress. This data support the use of serial therapy utilizing pre-lenalidomide treatment followed by bortezomib or carfilzomib treatment. Disclosures: Fonseca: Medtronic: Consultancy; Otsuka: Consultancy; Celgene: Consultancy; Genzyme: Consultancy; BMS: Consultancy; Lilly: Consultancy; Onyx: Consultancy, Research Funding; Binding Site: Consultancy; Millennium: Consultancy; AMGEN: Consultancy; Cylene: Research Funding; Prognostication of MM based on genetic categorization of the disease: Prognostication of MM based on genetic categorization of the disease, Prognostication of MM based on genetic categorization of the disease Patents & Royalties.

Abstract Abstract 3150 Introduction. Affordability of health care in the United States (US), and the impact of patient insurance coverage on it have been shown to be associated with the delivery and timeliness of access to care. With increasing costs of novel therapies in hematology and oncology, this concern has been raised in hematologic cancers. This analysis evaluates whether the health-related quality of life (HRQOL) of patients with active, symptomatic multiple myeloma (MM) patients in the US varies by their insurance coverage as they initiate treatment. Methods. Baseline data were collected in Connect MM®, a prospective observational registry initiated in September 2009 involving centers in the US. Data on patient demographics and clinical characteristics were provided by clinicians. HRQOL was reported by patients in the clinic at enrollment, within two months of diagnosis. Patients completed 3 psychometrically validated instruments: the Brief Pain Inventory (BPI), EQ-5D, and Functional Assessment of Cancer Therapy-Multiple Myeloma (FACT-MM). Standard analyses were conducted of each instrument given clinical characteristics at that time. Patients were characterized as to the main source of their insurance coverage: Medicare, Medicaid or Commercial. The Medicare cohort included those with supplemental commercial coverage, and the Medicaid cohort included those with dual Medicare-Medicaid coverage. Reported mean BPI, EQ-5D and FACT-MM scores were analyzed by patient insurance coverage. Statistical significance of score differences among sub-cohorts was ascertained by ANOVA using SAS 9.1. Results. HRQOL data and insurance status were reported by 863 patients, enrolled from 189 centers. Patients were predominantly male (57%) and white (82%) with mean age at 67.0 (standard deviation [SD] 11.3) yrs. HRQOL scores by insurance status are presented: Overall FACT-MM results indicate that Medicaid insurance status is associated with greater decrement in baseline HRQOL compared to the other groups. Statistically significant differences are noted in the FACT-G general cancer HRQOL score, and its physical, social/family and emotional component scores. BPI data (on a scale of 0 [no pain] to 10 [worst pain] indicate that average pain may be worse among Medicaid patients compared to either Medicare or commercially insured patients. There are no statistically significant differences on EQ-5D scores (on a scale of 1 [no problem] to 2 [some problems] to 3 [incapacity] between cohorts based on insurance status. Conclusions. Initial results from the Connect MM® Registry indicate that HRQOL at baseline prior to initiation of treatment is worse among Medicaid patients compared to those with either Medicare or commercial coverage. This should be investigated to determine whether Medicaid patients are accessing care later in disease progression than others covered by Medicare or commercial insurance. Furthermore, future analyses should be conducted of patients by insurance coverage to determine whether status may be associated with access to medical care, subsequent clinical outcomes, and HRQOL over time. Results reported here should serve as a baseline reference. Disclosures: Pashos: Celgene: Membership on an entity's Board of Directors or advisory committees. Durie:Celgene: Membership on an entity's Board of Directors or advisory committees. Rifkin:Celgene: Membership on an entity's Board of Directors or advisory committees. Terebelo:Celgene: Membership on an entity's Board of Directors or advisory committees. Gasparetto:Celgene: Membership on an entity's Board of Directors or advisory committees. Mehta:Celgene: Membership on an entity's Board of Directors or advisory committees. Toomey:Celgene: Membership on an entity's Board of Directors or advisory committees. Abonour:Celgene: Membership on an entity's Board of Directors or advisory committees. Fonseca:Celgene: Membership on an entity's Board of Directors or advisory committees. Narang:Celgene: Membership on an entity's Board of Directors or advisory committees. Shah:Celgene: Membership on an entity's Board of Directors or advisory committees. Swern:Celgene Corporation: Employment, Equity Ownership. Sullivan:Celgene: Employment, Equity Ownership. Street:Celgene: Employment, Equity Ownership. Khan:Celgene: Employment, Equity Ownership.