Mellors, Patrick

AbstractThromboses are prevalent in POEMS syndrome, but few risk factors for POEMS‐associated thrombosis have been identified. The objective of this study is to identify novel risk factors for POEMS‐associated thrombosis. In this retrospective cohort of 230 POEMS patients, 27% developed thrombosis. Arterial events were slightly more common than venous. Stroke accounted for 26% of all thromboses and 53% of arterial events. There were differences in baseline features between the thrombosis group and the no thrombosis group, and these were driven by patients with arterial thrombosis. Risk factors for arterial thrombosis included thrombocytosis, elevated hemoglobin/hematocrit, extravascular volume overload, and splenomegaly. Hyperprolactinemia appeared to be a risk factor for venous thrombosis. The risk of thrombosis was most striking among men with elevated hemoglobin (32% vs. 5%, p < .001) and hematocrit (42% vs. 5%, p < .001) compared to men without. Most thromboses occurred prior to POEMS directed therapy, and most that occurred during therapy happened within 3 months of diagnosis. Twenty‐one percent of patients with thrombosis had recurrence. In recognition of high overall rates of thrombosis in this population, all patients with POEMS syndrome should receive prophylactic antiplatelet therapy, and clinicians should consider anticoagulation in patients with risk factors for POEMS‐associated thrombosis.

Introduction: Since 2018, immunoenrichment-based matrix assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS), termed MASS-FIX, has replaced immunofixation for the detection and isotyping of serum monoclonal proteins at Mayo Clinic. MASS-FIX has advantages including increased sensitivity, specificity, and the ability to distinguish therapeutic monoclonal antibodies. Herein, we report the laboratory characteristics and distribution of diagnoses of patients tested clinically at Mayo Clinic. Methods: MASS-FIX was performed on patient samples as previously described (Kohlhagen et. al. Clin Chem Lab 2020). Demographics and laboratory data, including quantitative M-spike, serum free light chains (FLC), and quantitative immunoglobulins at the time of MASS-FIX were recorded. For patients with multiple samples during the study period, only the initial MASS-FIX was evaluated. We identified 9195 unique patients with MASS-FIX performed between 7/24/2018 and 3/6/2020. Seven-thousand nine hundred and forty-six patients provided consent for study enrollment, and 7689 had data available on index diagnosis. Given considerable variability in the interpretation of diagnostic criteria for light chain (LC) MGUS, patients with this diagnosis (1360, 18%) were excluded. Patients were considered to have negative results (2211 in total) on MASS-FIX if: 1) no monoclonal protein was identified (1081, 49%); 2) the interpretation was "cannot rule out monoclonal protein" (945, 43%); 3) multiple, nonspecific spectral peaks were identified consistent with immune reconstitution (29, 1%); or 4) the only monoclonal protein identified was consistent with a therapeutic monoclonal antibody (156, 7%). Results: The final cohort consisted of 4118 patients with a positive MASS-FIX and 2211 patients with a negative MASS-FIX, all in the setting of underlying PCDs. Figure 1 illustrates the numbers and percentages of patients who are MASS-FIX positive versus MASS-FIX negative by diagnosis. MGUS and multiple myeloma (MM) were the most common diagnoses overall, and both were more common in the MASS-FIX positive cohort. More than 90% of patients with Waldenstrom's macroglobulinemia (WM), smoldering WM, smoldering MM, and cold agglutinin disease were positive by MASS-FIX. For MASS-FIX positive patients, IgG isotype was identified in 2575 patients (63%), IgA in 703 (17%) and IgM in 710 (17%). Bence Jones proteinemia was identified in 283 patients (7%) with lambda restriction being the most common (57%). 3625 patients (88%) had a monoclonal pattern, 228 patients (6%) had a bi-clonal pattern, and 7 (&lt;1%) had a tri-clonal pattern. The majority of patients (58%) were kappa LC restricted by MASS-FIX, 222 (5%) had N-glycosylated LC, and 2 patients (&lt;1%) had a heavy chain with no light chain. Conclusions: This single institution experience illustrates the practicality of MASS-FIX in detecting and following monoclonal proteins for a wide range of PCDs in a tertiary center. In this cohort, the percentage of patients who were MASS-FIX positive varied by diagnosis, reflecting cross sectional sampling of patients throughout their disease course. Disclosures Gertz: Research to Practice: Other; Springer Publishing: Patents & Royalties; Aurora Bio: Other; Johnson and Johnson: Speakers Bureau; Sanofi: Other; Amgen: Other: personal fee; Appellis: Other: personal fee; Annexon: Other: personal fee; Spectrum: Other: personal fee, Research Funding; Janssen: Other: personal fee; Prothena: Other: personal fee; Alnylam: Other: personal fee; Ionis/Akcea: Other: personal fee; Proclara: Other; DAVA oncology: Speakers Bureau; Celgene: Other; Teva: Speakers Bureau; Abbvie: Other; Physicians Education Resource: Other: personal fee; Medscape: Other: personal fee, Speakers Bureau. Kumar:AbbVie: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Dr. Reddy's Laboratories: Honoraria; Takeda: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Carsgen: Other, Research Funding; Karyopharm: Consultancy; Merck: Consultancy, Research Funding; Oncopeptides: Consultancy, Other: Independent Review Committee; IRC member; Kite Pharma: Consultancy, Research Funding; BMS: Consultancy, Research Funding; Janssen Oncology: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Amgen: Consultancy, Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments, Research Funding; Genecentrix: Consultancy; Adaptive Biotechnologies: Consultancy; Novartis: Research Funding; MedImmune: Research Funding; Sanofi: Research Funding; Tenebio: Other, Research Funding; Cellectar: Other; Genentech/Roche: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Celgene/BMS: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments. Kapoor:Sanofi: Consultancy, Research Funding; Amgen: Research Funding; Takeda: Honoraria, Research Funding; GlaxoSmithKline: Research Funding; Cellectar: Consultancy; Janssen: Research Funding; Celgene: Honoraria. Dingli:Karyopharm Therapeutics: Research Funding; Bristol Myers Squibb: Research Funding; Rigel: Consultancy; Alexion: Consultancy; Sanofi-Genzyme: Consultancy; Janssen: Consultancy; Apellis: Consultancy; Millenium: Consultancy. Lin:Merck: Research Funding; Legend BioTech: Consultancy; Juno: Consultancy; Bluebird Bio: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Novartis: Consultancy; Janssen: Consultancy, Research Funding; Kite, a Gilead Company: Consultancy, Research Funding; Gamida Cells: Consultancy; Takeda: Research Funding; Sorrento: Consultancy, Membership on an entity's Board of Directors or advisory committees; Vineti: Consultancy. Murray:The Binding Site: Patents & Royalties: Patent Use of Mass Spec to identify monoclonal proteins licensed to The Binding Site. Dispenzieri:Alnylam, Intellia, Janssen, Takeda, Pfizer, Prothena, Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding.

Introduction: Since 2018, immunoenrichment-based matrix assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS), termed MASS-FIX, has replaced standard gel-based immunofixation for the detection and isotyping of serum monoclonal proteins at Mayo Clinic. MASS-FIX can readily identify N-glycosylation of involved light chains (LC N-glycosylation) by its unique, polytypic spectral pattern. LC N-glycosylation is identified more commonly in light chain amyloidosis (AL) than other plasma cell disorders (PCDs), and is associated with an increased risk of progression from MGUS to both AL and other PCDs (Dispenzieri et. al. Leukemia 2020). Herein, we report the mass spectral characteristics and distribution of diagnoses among 222 patients with LC N-glycosylation detected during a 20 month period in our clinical lab. Methods: MASS-FIX was performed on patient samples as previously described (Kohlhagen et. al. Clin Chem Lab 2020). Demographics and laboratory data, including quantitative M-spike, serum free light chains (FLC), and quantitative immunoglobulins at the time of MASS-FIX were recorded. For patients with multiple samples during the study period, only the initial MASS-FIX was evaluated. 9195 unique patients had MASS-FIX performed from 7/24/2018 to 03/06/2020. Inclusion criteria for this retrospective study included: 1) consent for record review; 2) a monoclonal protein identified on MASS-FIX; 3) an underlying PCD. Patients were considered to have negative results (2211 in total) on MASS-FIX if: 1) no monoclonal protein was identified (1081, 49%); 2) the interpretation was "cannot rule out monoclonal protein" (945, 43%); 3) multiple, nonspecific spectral peaks were identified consistent with immune reconstitution (29, 1%); or 4) the only monoclonal protein identified was consistent with a therapeutic monoclonal antibody (156, 7%). The final positive cohort consisted of 4118 patients with definitive monoclonal proteins on MASS-FIX. Results: Two-hundred and twenty-two (5%) of the 4118 patients with a positive MASS-FIX had LC N-glycosylation. 202 patients (91%) had FLC assays performed. Of these, 110 (54%) were kappa LC restricted, 22 (11%) were lambda restricted, and 70 (35%) were normal. A quantifiable M-spike was identified in 110 patients (85%) of 129 patients who had serum protein electrophoresis performed. By MASS-FIX, 139 patients (63%) had an IgG isotype, 18 (8%) an IgA, and 55 (25%) an IgM. Two of these patients had a bi-clonal pattern in which both IgG kappa and IgM kappa LCs were N-glycosylated. 12 patients (5%) had monoclonal light chains with no corresponding heavy chain. Overall, 173 (78%) of 222 patients were kappa LC restricted and 44 (22%) were lambda. 189 patients (85%) had a monoclonal pattern, 18 (8%) had a bi-clonal pattern, and 3 (1%) had a tri-clonal pattern. The most common PCD diagnoses for the 222 patients with LC N-glycosylation were MGUS (45%), multiple myeloma (MM) (31%), and immunoglobulin light chain amyloidosis (AL) (8%). The percentage of MASS-FIX positive patients with LC N-glycosylation by diagnosis, stratified by kappa and lambda LC restriction, is illustrated in Figure 1. Cold agglutinin disease (CAD) had the highest relative percentage of patients with LC N-glycosylation, regardless of LC restriction. Eighteen AL patients (5%) had LC N-glycosylation; the percentage was higher in kappa restricted (13%) than lambda restricted AL patients (2%). Of note, LC N-glycosylation was not detected in patients with plasma cell leukemia, non-AL amyloidosis with associated MGUS, POEMS Syndrome or Castleman's Disease in this cross sectional sampling of patients. Conclusions: This retrospective study demonstrates that 5% of patients in a routine clinical setting with positive MASS-FIX have glycosylated LCs. Consistent with prior observations, CAD had the highest relative percentage of LC N-glycosylated patients. The percentage of AL patients with LC N-glycosylation in this cohort is lower than previously reported for newly diagnosed AL patients (Kumar et. al. Leukemia 2019), which is not surprising given that the current cohort study is a cross sectional evaluation of patients at various stages of diagnosis and treatment rather than a prevalence study. Further study will be done to exclude the presence of latent AL in patients with N-glycosylated LC and diagnoses of MGUS, SMM, MM, and Waldenstrom's macroglobulinemia. Disclosures Gertz: Springer Publishing: Patents & Royalties; Proclara: Other; DAVA oncology: Speakers Bureau; Johnson and Johnson: Speakers Bureau; Teva: Speakers Bureau; Sanofi: Other; Research to Practice: Other; Celgene: Other; Abbvie: Other; Physicians Education Resource: Other: personal fee; Medscape: Other: personal fee, Speakers Bureau; Amgen: Other: personal fee; Appellis: Other: personal fee; Annexon: Other: personal fee; Spectrum: Other: personal fee, Research Funding; Janssen: Other: personal fee; Prothena: Other: personal fee; Alnylam: Other: personal fee; Ionis/Akcea: Other: personal fee; Aurora Bio: Other. Kumar:Adaptive Biotechnologies: Consultancy; Amgen: Consultancy, Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments, Research Funding; Carsgen: Other, Research Funding; Genentech/Roche: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Dr. Reddy's Laboratories: Honoraria; Oncopeptides: Consultancy, Other: Independent Review Committee; IRC member; Merck: Consultancy, Research Funding; Janssen Oncology: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Celgene/BMS: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; AbbVie: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; MedImmune: Research Funding; Genecentrix: Consultancy; Tenebio: Other, Research Funding; Karyopharm: Consultancy; BMS: Consultancy, Research Funding; Takeda: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Sanofi: Research Funding; Novartis: Research Funding; Kite Pharma: Consultancy, Research Funding; Cellectar: Other. Kapoor:Janssen: Research Funding; Sanofi: Consultancy, Research Funding; Amgen: Research Funding; Takeda: Honoraria, Research Funding; GlaxoSmithKline: Research Funding; Celgene: Honoraria; Cellectar: Consultancy. Dingli:Alexion: Consultancy; Karyopharm Therapeutics: Research Funding; Bristol Myers Squibb: Research Funding; Janssen: Consultancy; Sanofi-Genzyme: Consultancy; Apellis: Consultancy; Rigel: Consultancy; Millenium: Consultancy. Lin:Janssen: Consultancy, Research Funding; Novartis: Consultancy; Celgene: Consultancy, Research Funding; Bluebird Bio: Consultancy, Research Funding; Juno: Consultancy; Legend BioTech: Consultancy; Merck: Research Funding; Takeda: Research Funding; Gamida Cells: Consultancy; Sorrento: Consultancy, Membership on an entity's Board of Directors or advisory committees; Vineti: Consultancy; Kite, a Gilead Company: Consultancy, Research Funding. Murray:The Binding Site: Patents & Royalties: Patent Use of Mass Spec to identify monoclonal proteins licensed to The Binding Site. Dispenzieri:Intellia: Research Funding; Pfizer: Research Funding; Takeda: Research Funding; Celgene: Research Funding; Janssen: Research Funding; Alnylam: Research Funding.

AbstractMetaphase cytogenetic abnormalities, plasma cell proliferation index (PCPro), and gain 1q by fluorescence in situ hybridization (FISH) are associated with inferior survival in newly diagnosed multiple myeloma (MM) treated with novel agents; however, their role in risk stratification is unclear in the era of the revised International Staging System (R-ISS). The objective of this study was to determine if these predictors improve risk stratification in newly diagnosed MM when accounting for R-ISS and age. We studied a retrospective cohort of 483 patients with newly diagnosed MM treated with proteasome inhibitors and/or immunomodulators. On multivariable analysis, R-ISS, age, metaphase cytogenetic abnormalities (both in aggregate and for specific abnormalities), PCPro, and FISH gain 1q were associated with inferior progression-free (PFS) and overall survival (OS). We devised a risk scoring system based on hazard ratios from multivariable analyses and assigned patients to low-, intermediate-, and high-risk groups based on their cumulative scores. The addition of metaphase cytogenetic abnormalities, PCPro, and FISH gain 1q to a risk scoring system accounting for R-ISS and age did not improve risk discrimination of Kaplan-Meier estimates for PFS or OS. Moreover, they did not improve prognostic performance when evaluated by Uno’s censoring-adjusted C-statistic. Lastly, we performed a paired analysis of metaphase cytogenetic and interphase FISH abnormalities, which revealed the former to be insensitive for the detection of prognostic chromosomal abnormalities. Ultimately, metaphase cytogenetics lack sensitivity for important chromosomal aberrations and, along with PCPro and FISH gain 1q, do not improve risk stratification in MM when accounting for R-ISS and age.

Introduction: Abnormal metaphase cytogenetics are associated with inferior survival in newly diagnosed multiple myeloma (MM). These abnormalities are only detected in one third of cases due to the low proliferative rate of plasma cells. It is unknown if metaphase cytogenetics improve risk stratification when using contemporary prognostic models such as the revised international staging system (R-ISS), which incorporates interphase fluorescence in situ hybridization (FISH). Aims: The aims of this study were to 1) characterize the association between abnormalities on metaphase cytogenetics and overall survival (OS) in newly diagnosed MM treated with novel agents and 2) evaluate whether the addition of metaphase cytogenetics to R-ISS, age, and plasma cell labeling index (PCLI) improves model discrimination with respect to OS. Methods: We analyzed a retrospective cohort of 483 newly diagnosed MM patients treated with proteasome inhibitors (PI) and/or immunomodulators (IMID) who had metaphase cytogenetics performed prior to initiation of therapy. Abnormal metaphase cytogenetics were defined as MM specific abnormalities, while normal metaphase cytogenetics included constitutional cytogenetic variants, age-related Y chromosome loss, and normal metaphase karyotypes. Multivariable adjusted proportional hazards regression models were fit for the association between known prognostic factors and OS. Covariates associated with inferior OS on multivariable analysis included R-ISS stage, age ≥ 70, PCLI ≥ 2, and abnormal metaphase cytogenetics. We devised a risk scoring system weighted by their respective hazard ratios (R-ISS II +1, R-ISS III + 2, age ≥ 70 +2, PCLI ≥ 2 +1, metaphase cytogenetic abnormalities + 1). Low (LR), intermediate (IR), and high risk (HR) groups were established based on risk scores of 0-1, 2-3, and 4-5 in modeling without metaphase cytogenetics, and scores of 0-1, 2-3, and 4-6 in modeling incorporating metaphase cytogenetics, respectively. Survival estimates were calculated using the Kaplan-Meier method. Survival analysis was stratified by LR, IR, and HR groups in models 1) excluding metaphase cytogenetics 2) including metaphase cytogenetics and 3) including metaphase cytogenetics, with IR stratified by presence and absence of metaphase cytogenetic abnormalities. Survival estimates were compared between groups using the log-rank test. Harrell's C was used to compare the predictive power of risk modeling with and without metaphase cytogenetics. Results: Median age at diagnosis was 66 (31-95), 281 patients (58%) were men, median follow up was 5.5 years (0.04-14.4), and median OS was 6.4 years (95% CI 5.7-6.8). Ninety-seven patients (20%) were R-ISS stage I, 318 (66%) stage II, and 68 (14%) stage III. One-hundred and fourteen patients (24%) had high-risk abnormalities by FISH, and 115 (24%) had abnormal metaphase cytogenetics. Three-hundred and thirteen patients (65%) received an IMID, 119 (25%) a PI, 51 (10%) received IMID and PI, and 137 (28%) underwent upfront autologous hematopoietic stem cell transplantation (ASCT). On multivariable analysis, R-ISS (HR 1.59, 95% CI 1.29-1.97, p < 0.001), age ≥ 70 (HR 2.32, 95% CI 1.83-2.93, p < 0.001), PCLI ≥ 2, (HR 1.52, 95% CI 1.16-2.00, p=0.002) and abnormalities on metaphase cytogenetics (HR 1.35, 95% CI 1.05-1.75, p=0.019) were associated with inferior OS. IR and HR groups experienced significantly worse survival compared to LR groups in models excluding (Figure 1A) and including (Figure 1B) the effect of metaphase cytogenetics (p < 0.001 for all comparisons). However, the inclusion of metaphase cytogenetics did not improve discrimination. Likewise, subgroup analysis of IR patients by the presence or absence of metaphase cytogenetic abnormalities did not improve risk stratification (Figure 1C) (p < 0.001). The addition of metaphase cytogenetics to risk modeling with R-ISS stage, age ≥ 70, and PCLI ≥ 2 did not improve prognostic performance when evaluated by Harrell's C (c=0.636 without cytogenetics, c=0.642 with cytogenetics, absolute difference 0.005, 95% CI 0.002-0.012, p=0.142). Conclusions: Abnormalities on metaphase cytogenetics at diagnosis are associated with inferior OS in MM when accounting for the effects of R-ISS, age, and PCLI. However, the addition of metaphase cytogenetics to prognostic modeling incorporating these covariates did not significantly improve risk stratification. Disclosures Lacy: Celgene: Research Funding. Dispenzieri:Akcea: Consultancy; Intellia: Consultancy; Alnylam: Research Funding; Celgene: Research Funding; Janssen: Consultancy; Pfizer: Research Funding; Takeda: Research Funding. Kapoor:Celgene: Honoraria; Sanofi: Consultancy, Research Funding; Janssen: Research Funding; Cellectar: Consultancy; Takeda: Honoraria, Research Funding; Amgen: Research Funding; Glaxo Smith Kline: Research Funding. Leung:Prothena: Membership on an entity's Board of Directors or advisory committees; Takeda: Research Funding; Omeros: Research Funding; Aduro: Membership on an entity's Board of Directors or advisory committees. Kumar:Celgene: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Takeda: Research Funding.

Abstract Introduction: Thrombocytopenia is a major dose-limiting hematologic toxicity of anti-myeloma therapy. Clinical trial data in the relapsed/refractory setting have linked the development of thrombocytopenia during therapy with bortezomib with improved response to treatment. Less is known about the prognostic significance of early treatment related thrombocytopenia during initial therapy for newly diagnosed multiple myeloma (MM) using novel agents. Aims: The aim of this study was to characterize the effect of new, treatment related thrombocytopenia during initial therapy for newly diagnosed MM with novel agents on survival and clinical response. Methods: We identified 690 patients with newly diagnosed MM treated at Mayo Clinic, Rochester from January 2004 to December 2015 through a retrospective record review. All patients received novel agents including proteasome inhibitors (PI) and/or immunomodulatory drugs, were evaluable using the International Myeloma Working Group uniform response criteria, and had platelet counts greater than 150,000/µL prior to initial treatment. Survival outcomes and response were compared in patients who became thrombocytopenic within two cycles of first line treatment, defined as a nadir platelet count less than 150,000/µL, and in patients who did not develop thrombocytopenia. Survival estimates were calculated using the Kaplan-Meier method, and the log-rank test was used to compare survival in subgroups. Multivariable-adjusted proportional hazards regression models were fit to adjust for known prognostic factors including age, sex, International Staging System (ISS) stage, and the presence of cytogenetic high-risk abnormalities. Logistic regression was performed to evaluate for differences in response between groups. P-values less than 0.05 were considered statistically significant. Results: Of the 690 patients treated with novel agents, 495 patients (72%) received a PI as initial therapy. Median follow up was 3 years (0.1-13.2), median overall survival (OS) was 6.6 years (95% CI 5.9-8.0), and median progression free survival (PFS) was 4.84 years (95% CI 3.53-8.98). 123 patients (18%) developed thrombocytopenia within two cycles of first line therapy; two patients developed platelet counts less than 20,000/µL and none developed counts less than 10,000/µL. Differences in survival estimates for OS and PFS for patients who did not develop thrombocytopenia and those who became thrombocytopenic are illustrated in Figure 1. Median OS in patients who did not develop thrombocytopenia was 7.4 years (95% CI 5.9-8.9), compared to 4.6 years (95% CI 4.1-6.0) in those who became thrombocytopenic (p = 0.003), while median PFS was 5.4 years (95% CI 3.63-NR) and 3.53 years (95% CI 0.49-NR), respectively (p = 0.008). Similar results for both OS and PFS were observed when using a platelet nadir of less than 100,000/µL. These relationships remained statistically significant when adjusting for the effect of known prognostic factors including age, sex, ISS stage, and high-risk cytogenetics, for both OS and PFS (HR = 1.70, 95% CI 1.12-1.59, p = 0.013, n = 387 and HR = 1.56, 95% CI 1.03-2.37, p = 0.036, n = 387, respectively). Multivariable-adjusted estimates were similar for the subset of patients receiving PI containing regimens. Development of thrombocytopenia within two cycles was not associated with very good partial response or better (VGPR+) (p = 0.588) or with complete response (CR) (p = 0.968). This was also true for the subset of patients receiving PIs (p = 0.827 and p = 0.772, respectively). Conclusions: Our results suggest that the development of new, treatment related thrombocytopenia within two cycles of first-line therapy with novel agents is independently associated with inferior survival in newly diagnosed MM. This was also true in the subset of patients receiving PI containing regimens. In contrast to prior studies, there was no association between early treatment-related thrombocytopenia and response to treatment for either novel agents in general or PI based therapies. Figure 1: Kaplan-Meier progression free and overall survival estimates stratified by platelet count ≥ 150,000/µL (no thrombocytopenia) and <150,000/µL (new thrombocytopenia) within two cycles of initial therapy with novel agents. Figure 1. Figure 1. Disclosures Lacy: Celgene: Research Funding. Gertz:Prothena: Honoraria; Teva: Consultancy; Ionis: Honoraria; Alnylam: Honoraria; Research to Practice: Consultancy; Apellis: Consultancy; Physicians Education Resource: Consultancy; janssen: Consultancy; spectrum: Consultancy, Honoraria; Amgen: Consultancy; Abbvie: Consultancy; Medscape: Consultancy; annexon: Consultancy; celgene: Consultancy. Dispenzieri:Celgene, Takeda, Prothena, Jannsen, Pfizer, Alnylam, GSK: Research Funding. Kapoor:Takeda: Research Funding; Celgene: Research Funding. Kumar:AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; KITE: 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.

AbstractResponse rates in newly diagnosed multiple myeloma have improved dramatically with the introduction of highly effective novel therapies. However, survival in patients achieving optimal responses to initial treatment can vary significantly, and new prognostic indicators are required to improve risk stratification. We investigated the relationship between time to plateau (TPlat) and survival in 1099 newly diagnosed patients treated with novel agents at our institution from 2005 to 2015.TPlatwas defined as time from initiation of first‐line therapy to best response to first‐line therapy. The medianTPlatwas 4.9 months (0.7‐58.6) and plateau duration was 1.8 years (0.2‐11.0). Patients who required > 120 days to achieve a plateau had longer modified overall survival (mOS) and progression free survival (mPFS) calculated from a landmark of best response (P < .001 for both comparisons). Statistically significant improvement in mOS was retained in subgroup analysis based on age and whether patients received upfront autologous hematopoietic stem cell transplantation (ASCT) (P < .001 for all comparisons). Our results suggest that patients who respond more gradually to initial therapy (TPlat > 120 days) experience longer survival compared to more rapid responders. Patients with a prolongedTPlatcould represent an “ongoing responder” phenotype that portends a survival advantage independent of treatment with upfront ASCT, depth of response, and biologic markers such as ISS stage and cytogenetic risk.