Dispenzieri, Angela

Abstract Abstract 504 Background: There is limited data on the outcomes of AHCT for MM as a salvage approach following relapse after an initial (upfront) AHCT. We analyzed the outcomes of second salvage AHCT for relapsed MM. Methods: From the CIBMTR database we identified 187 patients (63% male) who had second AHCT (AHCT2) as salvage for MM relapsing after a prior AHCT (AHCT1). Planned tandem AHCT and AHCT2 within 6 months after AHCT1 were excluded. Cumulative incidence of relapse, non-relapse mortality (NRM) and the probabilities of progression-free (PFS) and overall survival (OS) were analyzed and multivariate analysis performed using proportional hazards models. Results: Median age at transplant was 57 (range 28–72) and 59 years (range 28–74) respectively at AHCT1 and AHCT2 respectively. Median follow up after AHCT2 was 47 months (range: 3–97). The proportion of IgG, IgA and free light chain subtypes was 48, 20 and 18% respectively. Durie Salmon stage at diagnosis was stage I (6%), II (21%), III (59%) respectively. Seven and 13% had serum creatinine > 1.5 mg/dl at AHCT1 and AHCT2 respectively. Conditioning regimen was single agent melphalan was in 78% and 84% for AHCT1 and AHCT2 respectively. At the time of AHCT2, majority (60%) were chemotherapy resistant compared with 80% patients with sensitive disease prior to AHCT1. Median time from AHCT1 to relapse was 18 months, with 32% relapsing within the first year, 29% in the second year, 19% in the third year and 19% beyond the third year after AHCT1. There was heterogeneity in the time to AHCT2 after relapse although 67% had AHCT2 within a year after relapse (median 7 months). Median between AHCT1 and AHCT2 was 32 months with the majority (69%) beyond 24 months. After AHCT2, day 28 engraftment rates of neutrophils and platelets were 96% (95% CI: 93–98) and 88% (95% CI: 83–92). Complete remission (CR) rates after AHCT1 were 43% whereas it was only 25% following AHCT2. After AHCT2, cumulative incidence of relapse at 1, 3 and 5 years was 51, 82, and 91% respectively. After AHCT2, one year NRM was 2%. PFS was 47%, 13% and 5% and OS was 83%, 46% and 29% at 1, 3 and 5 years respectively. In multivariate analysis, those relapsing within 36 months of AHCT1 had a higher risk of relapse (HR 1.58, p = 0.036) and higher risk of treatment failure and inferior PFS (HR1.52, p= 0.04). Mortality was higher for those relapsing early after AHCT1 (<36 months, HR 1.91, p = 0.02). OS was superior and mortality lower for AHCT2 performed after 2004-08 (HR 0.61, p=0.02). Conclusion: AHCT2 can be safely performed in relapsed MM with the best outcomes observed in later relapses (>36 months from AHCT1). OS has improved since 2004, but NRM, relapse and PFS after AHCT2 were not impacted by year of AHCT2. Thus the improved OS likely reflects greater availability of novel agents for post AHCT progression. Disclosures: No relevant conflicts of interest to declare.

Abstract Background Pomalidomide (POM) is the newest Immunomodulatory agent (IMiDs) that has shown clinical efficacy in relapsed multiple myeloma (MM) refractory to lenalidomide (LEN) and thalidomide (THAL). Studies of MM cell microenvironment suggest that tumor subclones compete for dominance during changes in drug therapy. It was previously observed that a minor clonal population increased in prominence of MM cells after 1 year of treatment with LEN. We examined whether the patients having THAL or LEN as the most recent prior-line therapy affects response to POM. Methods We studied 208 patients enrolled in a phase II trial of POM / dexamethasone between November 2007 and March 2012 at Mayo Clinic, Rochester. We reviewed the immediate prior-line therapy before enrollment in our trial. Comparison of treatment duration of POM and response rates were conducted between patients who had either THAL or LEN as latest prior-line therapy, and patients who were treated with non-IMiDs immediate before enrollment in POM trial. Treatment duration of POM was estimated using Kaplan Meier method and the survival curves were compared using log-rank test. We used univariate Cox proportional hazard models to estimate the prognostic impact of different variables. Results The median age of patients was 63 (range from 32 to 88). 68 % were males. 80 patients (38.5%) had THAL or LEN immediate prior to POM. Median prior-line therapies were 3. Patients who received THAL or LEN immediately prior to POM had a lower response rate than those who had non-IMiDs as latest therapy (29% vs 44%, p 0.04) and shorter median duration of POM treatment (5.7 months vs 7.3 months, p 0.02). In 190 (91%) patients who were previously treated with LEN and THAL at any time, median time between the end of LEN or THAL treatment and the initiation of POM was higher for POM responders than non-responders (10 months vs 3 months, p 0.0008). Patients responded to POM had a shorter duration of prior LEN or THAL treatment compared to non-responders (9 months vs 15 months, p 0.001). Conclusion THAL or LEN as an immediate prior-line therapy to POM is associated with a lower response rate and shorter effective treatment duration. Longer interval between prior immunomodulatory compounds and POM, and shorter exposure to previous immunomodulatory compounds are associated with better POM treatment response. Disclosures: Gertz: Celgene: Honoraria. Kumar:Merck: Consultancy, Honoraria; Celgene: Consultancy, Research Funding; Millennium: The Takeda Oncology Company: Research Funding; Novartis: Research Funding; Genzyme: Research Funding. Lacy:Celgene Corporation: Research Funding.

Abstract Background Immunoglobulin light chain-associated amyloidosis (AL) is caused by deposition of immunoglobulin light chain molecules with unique, clonotypic variable (V) regions. Detection and identification of the V region, however, has been challenging due heterogeneity inherent in V regions. We developed a new method for detecting IGKV and IGLV region fragments in AL deposits using protein mass spectrometry and novel bioinformatics approach. We report distinct IGKV and IGLV usage in localized versus systemic AL. Methods Shotgun protein mass spectrometry on amyloid plaques was performed as previously described (Blood. 2009; 114: 4957-9). Peptide tandem mass spectra (MS/MS) were searched against a composite sequence database containing SwissProt's human complete proteome augmented with 1764 IG V region sequences obtained from ImMunoGeneTics database and a Mayo Clinic internal database. Reversed sequences were appended to the database for estimating identification false discovery rates (FDRs). Peptide identifications were processed with Scaffold software. Confident protein identifications (probability > 0.9) with at least one unique peptide identifications and five MS/MS matches were considered. Detected variable gene family (if any) with most number of peptide and spectral matches is considered to be present in the deposit. The method was first validated in 8 cases of AL amyloidosis with known IGKV and IGLV region sequences and then applied on 1238 systemic and 393 localized AL cases. Differences between groups were measured by generating hypergeometric p-values. Results In all 8 AL cases with known IGKV and IGLV region usage, gene family identified in the AL deposit via proteomics matched the gene family inferred from bone marrow plasma cells by Sanger sequencing of IGLC genes. Armed with this method, we analyzed the amyloid proteomics data from 1238 patients with systemic AL amyloidosis and 393 patients with localized AL amyloidosis. The anatomical site distribution in systemic cohort was 296 GI tract, 364 heart, 225 kidney, 81 liver and 272 fat aspirate; Localized cohort has 78 bladder, 158 lung and 157 skin cases. Figure 1 shows the normalized frequency of the variable gene families detected between the systemic and localized AL amyloidosis. For AL-kappa, KV1 was more prevalent in systemic cases when compared to localized cases (p=7.2E-12) suggesting KV1 clones as a hallmark for systemic AL-kappa amyloidosis. KV3 was more frequently seen in localized AL-kappa cases when compared to systemic AL-kappa cases (p =2.8E-11). For AL-lambda, LV1 and LV2 gene families were more prevalent in localized cases when compared to systemic cases (p= 0.039 and 2.7E-05). LV6 was more prevalent in systemic AL-lambda cases (p=1.4E-07). We also detected a higher incidence of mixed AL/AH type in localized AL (18%) when compared to systemic AL (5%; Odds Ratio=4.2673, p<0.0001). We next turned to the organ specific IGKV and IGLV gene family usage patterns in patients with localized amyloidosis. For 147 localized AL-kappa cases, KV3 was most dominant in lung (64%) and KV1 was dominant in skin (38%). For 246 localized AL-lambda cases, LV2 was most prevalent in lung (34%) and LV3 was most prevalent in skin (36%). For bladder, both LV1 and LV2 had comparable prevalence (42% and 32%). For 361 systemic AL-kappa cases, KV1 consistently ranked at the top of gene families used in GI tract (55%), heart (71%), kidney (59%), liver (75%) and fat aspirate (50%). For 877 systemic AL-lambda cases, LV2 was predominant in GI tract (30%), LV3 in heart (35%) and LV6 in kidney (33%). The prevalence of LV1, LV2 and LV3 in liver is comparable (36%, 22% and 31%). LV6 and LV3 had comparable prevalence (22% and 24%) in AL-lambda fat aspirates. Conclusion The novel proteomics method detects IGLC V family usage in large cohorts of AL patients. It identifies unique profiles in systemic and localized cases, and in different organ sites. This information will be helpful in determining systemic versus localized nature of AL amyloidosis at diagnosis and to assess risk of specific end organ involvement. We found also a strong association between IGKV and IGLV gene usage and organ involvement. Disclosures: No relevant conflicts of interest to declare.

Abstract Background Multiple myeloma (MM) is uncommon in patients below 40 years of age. Between 1960 and 1992 when stem cell transplantation (SCT) was rarely performed and novel agents were unavailable, overall survival (OS) was reported to be 54 months in the Mayo Clinic series of patients with MM below forty years of age. The impact of novel agents or SCT in this population is unclear. Herein, we report the outcomes of patients under 40 years of age who were evaluated over a span of more than five decades with a focus on the periods contemporaneous with the introduction of SCT and novel agents, the major therapeutic milestones in the management of MM. Methods We analyzed the medical records of patients with MM under 40 years of age who were evaluated at Mayo Clinic, Rochester, MN between 1/1/1960 and 12/31/2011. SCT and novel agents were utilized infrequently prior to the years 1990 and 2000, respectively. Patients were therefore divided into three cohorts by the year of diagnosis of MM: Group A (1960 -1979), Group B (1980 to 1999) and Group C (2000 –2011) to assess the impact of major therapeutic advances (i.e. Increased utilization of SCT and novel agents compared to conventional chemotherapy). OS was calculated by the Kaplan -Meier method. Results Out of 8063 unique MM patients seen at our institution during this period, 174 (2%) patients were under 40 years of age at diagnosis. The median age at diagnosis was 36 years (range: 19-39). The estimated median follow-up of the entire cohort was 179 months (95% CI: 149-196 months). The median OS of the entire cohort was 76 months (95% CI: 45-80 months) from diagnosis. The median OS of patients in Groups A (n=29, 17%), B (n=93, 53%), and C (n=52, 30% ) was 44 months (95% CI: 20- 76), 79 months (95% CI: 46-97), and 92 months (95% CI: 42-NR), respectively (p=0.005). No significant OS difference was noted between Groups B and C (Figure). Sixty-six (38%) patients underwent at least one SCT (autologous: 56 patients and allogeneic 10 patients). The utilization of SCT increased over the three time periods from Group A 0%, Group B 39% and Group C 58% (p<0.001). Of 153 patients in whom front-line therapy-related data were available 118 (77%) received conventional and 35(23%) received novel agents. The median OS of patients who underwent transplantation (n=66) was 93 months compared to 46 months for those who did not (n=108, p=.01). In the 66 patients who underwent SCT, the median OS was 93 months for conventional agents-based induction (95% CI: 73-143) versus 97 months (95% CI: 41-187) for novel agent based induction (p=.4). Sixty-eight (40%) patients received novel agents at some point during the course of their disease [bortezomib 35 (54%), thalidomide 44 (67%), lenalidomide 47 (71%) and pomalidomide 7(11%)]. The median survival of these patients was 131 (95% CI: 88-161) months versus to 46 (CI: 37-74) months for those (n=106) receiving conventional agents only (p=0.0002). Conclusions OS of patients with MM under 40 years of age in the pre-transplant era (Group A) was significantly shorter than that of patients diagnosed in the era of SCT (Group B) and SCT plus novel agents (Group C). Although improvement of survival outcomes is evident with utilization of novel agents, similar outcomes of Groups B and C indicate lack of incremental benefit over SCT with utilization of novel agents. Maximal survival gain coincides with the introduction of SCT in this unique patient cohort. Disclosures: Kumar: Celgene: Consultancy, Research Funding; Millennium: Consultancy, Research Funding; Onyx: Consultancy, Research Funding.

Abstract Abstract 2942 Background: Pomalidomide (pom) is a distinct immunomodulatory (IMid) drug with high response rates in relapsed MM, including patients previously treated with thalidomide, bortezomib and lenalidomide. However, its duration of response and long term outcome is unknown. We evaluated the long term outcomes of the first Mayo Clinic cohort of pts treated with Pom. Methods: Pts with relapsed/refractory myeloma with 1–3 prior therapies were enrolled. Pom 2 mg/d was given orally continuously on 28 day cycle with weekly dexamethasone 40 mg. All pts received DVT prophylaxis with aspirin, heparin or warfarin. Results: 60 pts with relapsed MM were enrolled from Nov 2007-Aug 2008. Median age was 65.5; 36 were male. Median time from diagnosis was 45.6 mo (9.–-192.5). Nineteen (32%) were high-risk according to mSMART (msmart.org), and 78% were ISS Stage 2/3. Prior therapies included transplant (65%), bortezomib (33%), thalidomide (47%), lenalidomide (35%) [previous IMiD 60%] and radiation (38%). Toxicities at least possibly attributed to Pom included G3/4 anemia (5/0%), leukopenia (17/3%) and thrombocytopenia (3/0%). G3/4/5 non-hematological toxicities occurred in 30 (50%) and included fatigue (18/0/0%), pneumonia (8/2/2%), hyperglycemia (5/0/0%) and constipation (5/0/0%). Only one pt had grade 3 neuropathy. Treatment adjustment for occurred in 30 pts (50%) for pom (mostly for neutropenia) and 35 pts (58%) for dex. A median of 11.5 cycles were administered. With median follow up of 30.1 months (mo), overall response was seen in 39 (65%) [4 sCR, 5 CR, 16 VGPR, 14 PR]. Median time to first reponse (≥PR) was 1.7 mo (0.8–14.8). Median duration of response (in responders of ≥PR) was 21.3 mo. Median PFS was 13 mo and the 2 year OS rate was 76%. Standard risk pts had median PFS of 18.4 mo and 2 year OS rate was 85%; high risk pts had median PFS of 9.2 mo and 2 year OS rate was 57%. (Figure 1) Conclusions: Pom/dex is highly effective and well tolerated in relapsed MM, with a response rate of 65% even in pts with multiple prior therapies, including other IMiDs, bortezomib and transplant. The response is also durable, with median duration in excess of 21 months. Pom/dex provides long term benefit with median PFS 13 months and 2 year OS rate of 76%. Disclosures: Kumar: Merck: Consultancy, Membership on an entity's Board of Directors or advisory committees. Stewart:Celgene Corporation: Consultancy, Research Funding; Millenium: Consultancy, Research Funding; Novartis: Consultancy, Research Funding; BMS: Consultancy, Research Funding; Onyx: Consultancy, Research Funding. Fonseca:Consulting :Genzyme, Medtronic, BMS, Amgen, Otsuka, Celgene, Intellikine, Lilly Research Support: Cylene, Onyz, Celgene: Consultancy, Research Funding. Lacy:Celgene: Research Funding.

Abstract Abstract 4120 Introduction: Autologous stem cell transplantation (ASCT) remains an effective treatment for immunoglobulin light chain (AL) amyloidosis but its high treatment related mortality is a concern. The development of acute renal failure can strongly affect the survival of these patients. This study looks at the impact of the timing of dialysis initiation on the overall survival (OS). Methods: AL patients who underwent ASCT from 3/96 to 1/10 were selected. Patients were placed into 4 groups: I - never dialyzed, II - initiated dialysis prior to ASCT, III - dialysis began within 30 days of ASCT and IV - dialysis was started after 30 days of ASCT. Results: Four hundred and ten patients were selected for study and 75 (18.3%) received dialysis. Baseline characteristics are listed in Table 1. In univariate analysis, serum creatinine (Scr) and b-2 microglobulin (b2m) were associated with dialysis post-ASCT. Both became non-significant in the multivariate model suggesting they are co-dependent. Dialysis had a strong influence on survival, p < 0.001 (Fig 1). This was most evident when dialysis was started after ASCT (group III (p = 0.003) and IV (p = 0.004)), but not before (II, p = 0.19).To explore the interactions of dialysis with cardiac biomarkers in their relationship with OS, cardiac troponins T (cTnT) and N terminal-pro-brain natriuretic peptide (NT-pro-BNP) were analyzed with timing of dialysis in a proportional hazard model. Timing of dialysis (p < 0.001), cTnT (p = 0.03) and NT-pro-BNP (p = 0.03) all were associated with OS. Using Receiver Operator Characteristic (ROC) curves, best cut points were chosen for cTnT (0.01 ng/ml) and NT-pro-BNP (1350 pg/ml) for survival. When treated as categorical variables, the proportional hazard model found that only NT-pro-BNP (p = 0.002) and timing of dialysis (p < 0.001) were independent predictors of OS but cTnT had loss its significance (p = 0.07). Using Kaplan Meier method, dialysis was a significant risk factor in patients with low cTnT and both high and low NT-pro-BNP (p < 0.001) but not in patients with elevated cTnT (p = 0.25). Discussion: The timing of acute renal failure strongly affects the OS of AL patients undergoing ASCT. In our study, patients who started dialysis prior to ASCT did not have an inferior OS compared to patients who never needed dialysis. On the other hand, starting dialysis after ASCT significantly shortened OS. The timing of dialysis was an independent predictor of OS even when combined with cardiac biomarkers. NT-pro-BNP appears to be the stronger marker when timing of dialysis is considered in the multivariate analysis. Disclosures: No relevant conflicts of interest to declare.

Abstract Amyloidosis is a group of hereditary and acquired disorders of diverse pathogenesis united by end organ damage due to tissue deposition of misfolded proteins. The diagnosis is typically based on demonstrating Congo red positive amyloid deposits in tissue biopsies of clinically involved sites. Because treatment options for amyloidosis patients are highly varied and intricately tied to the identity of the protein that constitutes the amyloid deposits, adequate diagnostic evaluation now requires identification of the amyloidogenic protein. Traditionally, immunohistochemistry with antibodies to amyloid-associated proteins was the clinical technique of choice for subtyping amyloid deposits in tissue sections. This technique suffers from poor analytical sensitivity and specificity and is a suboptimal technique on which to base treatment decisions for amyloidosis patients. We developed a highly accurate and reproducible liquid chromatography electrospray tandem mass spectrometery (LC-MS/MS)-based shotgun proteomics assay for subtyping amyloid deposits (Blood. 2009; 114: 4957-9) from microdissected paraffin embedded tissue samples. Implementation of this assay in a CAP/CLIA clinical laboratory has subsequently transformed the standard of amyloidosis care at Mayo Clinic. Since 2008, we utilized the assay in routine practice to identify 20 different amyloid types in tissue samples from diverse anatomic sites from 4139 patients (Table 1). Although AL and ATTR were most common, the cases include a large variety of unusual, and in many cases clinically unsuspected amyloid types. In addition, the amyloid protein subtypes had different frequencies in different anatomic sites (A partial list of tissue sites and their amyloid types analyzed in this study includes: bone marrow: AL 82%, ATTR 15%, AA 2%, other 1%; kidney: AL 51%, ALect2 18%, AA 17%, AH 5%, AFib 4%, other 5%; liver: AL 64%, ALect2 23%, AApoA1 6%, AA 3%, ATTR 2%, other 2%; heart: ATTR 60%, AL 37%, AANF1%, other 2%; GI tract: AL 78%, ATTR 13%, AA 6% AApoA4 1%, other 2%; eye [primarily adnexae] AL 63%; eye [primarily cornea] TGFB induced protein ig-h3 34%, other 3%). One caveat is that these distributions of amyloid types may not accurately reflect population prevalence. More likely, the findings reflected a composite prevalence that included challenging amyloidosis cases.Table 1Frequency of amyloid subtypes observed in the Mayo Amyloid Cohort (n=4139). Asterisk denotes non-canonical subtypesAmyloid SubtypeNumber (%) of casesAL2553 (61.68)ATTR1015 (24.52)AA151 (3.65)ALect2148 (3.58)AIns48 (1.09)Keratin*36 (0.87)AApoA130 (0.72)AH27 (0.65)AFib26 (0.63)TGFB1-IP*22 (0.53)AApoA420 (0.48)AANF14 (0.34)Ab2M12 (0.29)AGel12 (0.29)ASem112 (0.29)APro7 (0.17)ALys3 (0.07)ACal2 (0.05)Enfuvirtide*2 (0.05)AIAPP2 (0.05) The prevalence of diverse and unexpected amyloid types in many tissues suggest that shotgun proteomic-based analysis may be the only way to accurately assign amyloid subtype in tissue samples. The technique avoids the analytical problems of immunohistochemistry and the bias introduced by assigning probable amyloid type based on clinical presentation and disease distribution. It provides the clinician with an amyloid subtype that allows for confident individualized patient management. Accurate amyloid subtyping by LC-MS/MS is not only possible, but has proven to be a robust routine clinical tool for the evaluation of numerous amyloidosis patients in our practice. Disclosures: No relevant conflicts of interest to declare.

Abstract Introduction: FISH is able to recognize chromosomal deletions and translocations with a greater sensitivity than conventional cytogenetics. Specific abnormalities have been associated with prognosis. Initial observations suggest a poor outcome for patients with -17p13.1, chromosome 13 abnormalities (Δ13) and t(4;14)(p16.3;q32). In contrast a good outcome has been shown in some series for patients with t(11;14)(q13;q32). We analyzed the value of FISH in patients receiving high dose therapy . Patients and Methods: We studied by cIg-FISH 226 patients undergoing high dose therapy at Mayo Clinic between 1/1990 and 9/2001. All patients had a pretransplant cIg-FISH done on cytospin slides from marrow aspirates for t(11;14)(q13;q32), t(4;14)(p16.3;q32), and -17p13.1(p53). Information was available regarding Δ13 for all patients (+ in 52%). Results: The prevalence of the abnormalities were: t(11;14)(q13;q32) 17% (n=197), t(4;14)(p16.3;q32) 13% (n=153), and -17p13.1 11% (n=168). The overall survival (OS)was significantly shortened in patients with t(4;14)(p16.3;q32) (18.2 vs. 43.3 mo, p=0.001) (figure) and patients with -17p13.1 (14.7 vs. 38.6 mo, p=.01). OS was not different for patients with the t(11;14)(q13;q32) (36.2 vs. 34.8 mo, p=ns). Likewise time to progression (TTP) was shortened in patients with t(4;14)(p16.3;q32) (8.5 vs 17.7 mo, p=.001) and -17p13.1 (8.3 vs. 16.2 mo, p=0.005). TTP was also not affected significantly by the t(11;14)(q13;q32) (20.7 vs. 14.9 mo, p=NS). To dissect the specific contribution of t(4;14)(p16.3;q32) we did a subset analysis of patients who also had Δ13, since 85% of patients with t(4;14)(p16.3;q32) are expected to have Δ13. Of 84 studied for both abnormalities 22 had both Δ13 and t(4;14)(p16.3;q32). The OS was significantly shorter in patients with both abnormalities versus those with Δ13 alone (26.6 vs. 18.2 months, p=0.001). When a multivariable analysis of the impact of Δ13 and t(4;14)(p16.3;q32) were placed into a Cox model the hazard function for t(4;14)(p16.3;q32) was greater than Δ13 (2.6 versus 1.6). Δ13 had only borderline significance in this model (p=0.06). Conclusion: We have been unable to corroborate the improved outcome after transplant for patients with t(11;14)(q13;q32). As has been reported in patients with conventional and high dose therapy -17p13(p53) and t(4;14)(p16.3;q32) have clinical importance for estimation of OS and TTP. In this patient group the t(4;14)(p16.3;q32) carried a greater adverse impact than did Δ13, and identifies a subset of patients whose time to progression is 8.5 months. These patients likely do not benefit from autologous transplant and are candidates for novel therapeutic approaches. Outcome Successful determination Patients with translocation or deletion Survival (months) with/without abnormality Time to Progression (months) with/without abnormality * p<0.01;**p<0.001 t(11;14)(q13;q32) 197 34(17%) 36.2/34.8 20.7/14.9 p53 168 18(11%) 14.7/38.6 * 8.3/16.2 * t(4;14)(p16.3;q32) 153 26(17%) 18.2/43.3 **figure 8.5/17.7 ** t(4;14)(p16.3;q32)/Δ13+ patients 84 22(26%) 18.2/26.6 8.2/12.8 * Figure Figure

Abstract Background: Multiple myeloma (MM) is a heterogeneous disease with very divergent outcomes that are dictated in a large part by specific cytogenetic abnormalities, as well as other prognostic factors such as the proliferative rate of marrow plasma cells. Prognostic systems incorporating these factors have shown clinical utility in identifying high-risk patients, and are increasingly being utilized for treatment decision-making. However, the prognostic relevance of these factors may change with the application of novel therapies. The objective of this study was to determine the impact of risk-stratification (incorporating plasma cell metaphase cytogenetics, interphase fluorescent in-situ hybridization (FISH) and the slide-based plasma cell labeling index (PCLI)) in a cohort of patients with newly diagnosed MM treated initially with lenalidomide + dexamethasone (Rev-Dex). Methods: From March 2004 to November 2007, 100 consecutive patients treated with Rev (25mg/day) on days 1 through 21 of a 4-week cycle in combination with dexamethasone as initial therapy for newly diagnosed myeloma, were identified. High-risk MM was defined as presence of any one or more of the following: hypodiploidy, monoallelic loss of chromosome 13 or its long arm (by metaphase cytogenetics only), deletion of p53 (locus 17p13) or PCLI ≥ 3% or immunoglobulin heavy chain (IgH) translocations, t(4;14) (p16.3;q32) or t(14;16)(q32;q23) on FISH. PFS and OS survival estimates were created using the Kaplan Meier method, and compared by log-rank tests. Results: The median estimated follow-up of the entire cohort (N=100) was 36 months. The median PFS was 31 months; the median OS has not been reached. The 2- and 3-year OS estimates were 93% and 83%, respectively. 16% patients were deemed high-risk by at least one of the 3 tests (cytogenetics, FISH or PCLI). Response rates (PR or better) were 81% versus 89% in the high-risk and standard risk groups, respectively, P=NS; corresponding values for CR plus VGPR rates were 38% and 45% respectively. The median PFS was 18.5 months in high-risk patients compared to 37 months in the standard-risk patients (n=84), P<0.001(Figure). Corresponding values for TTP were 18.5 months and 36.5 months, respectively, P=<0.001. OS was not statistically significant between the two groups; 92% 2-year OS was noted in both the groups. Overall, 95 patients had at least one of the 3 tests to determine risk, while 55 patients could be adequately stratified based on the availability of all the 3 tests, or at least one test result that led to their inclusion in the high-risk category. The significant difference in PFS persisted even when the analysis was restricted to the 55 patients classified using this stringent criterion; 18.5 months vs. 36.5 months in the high-risk and standard- risk groups respectively; P<0.001. In a separate analysis, patients who underwent SCT before the disease progression were censored on the date of SCT to negate its effect, and PFS was still inferior in the high-risk group (p=0.002). Conclusion: The TTP and PFS of high-risk MM patients are inferior to that of the standard-risk patients treated with Rev-Dex, indicating that the current genetic and proliferation-based risk-stratification model remains prognostic with novel therapy. However, the TTP, PFS, and OS obtained in high-risk patients treated with Rev-Dex in this study is comparable to overall results in all myeloma patients reported in recent phase III trials. In addition, no significant impact of high-risk features on OS is apparent so far. Longer follow-up is needed to determine the impact of risk stratification on the OS of patients treated with Rev-Dex. Figure Figure

Abstract Background: Though STI-571 (Gleevec™) was designed to specifically inhibit the bcr-abl gene product, it inhibits other receptor tyrosine kinases at physiologically attainable concentrations, including c-kit (steel factor receptor, stem cell factor receptor, SCF-R or CD 117). Studies have shown that about one-third of patients with multiple myeloma or monoclonal gammopathy of undetermined significance have plasma cells that display reactivity for c-kit. Others have shown that several myeloma cell lines and fresh myeloma bone marrow cells proliferate in response to stem cell factor. mRNA transcripts for c-kit ligand and, more commonly, its receptor have been detected in myeloma cell lines RPMI 8226, JJN3, U266 B1, NCI-H929, ARH77 and HS-Sultan by RT-PCR. Methods: Patients were eligible for study if they presented with relapsed or refractory myeloma, an ECOG performance score < 3, ability to sign informed consent, serum creatinine <3.5 mg/dL, direct bilirubin <2 mg/dL, alkaline phosphatase <750 U/L, absolute neutrophil count > .5 x 10(9)/L and platelet count > 50 x 10(9)/L. Patients were treated with Gleevec™ 400 mg po qd. The purpose of the study was to assess the response rate of the drug Gleevec™ in patients with relapsed multiple myeloma. Secondary objectives included assessment of the tolerability of the regimen in this cohort of patients and to correlation between disease response and c-kit positivity (CD117) by flow cytometry. Results: Overall, 23 patients were enrolled between 12/01 and 11/02, of which 16 were male and 12 had a prior PBSCT. Median age was 63 years (range: 49 – 82), and the baseline performance scores were 0 (8 patients), 1 (10), and 2 (4). Median time from MM diagnosis to enrollment was 57 months (range: 11 – 133). Patients were high risk with a median PCLI of 1.3 (range: 0 – 23%) and a median beta-2 microglobulin of 4.6 (range: 1.4 – 10.1). Eleven of 21 tested patients had positive CD117 (≥20%) staining of their bone marrow plasma cells by flow cytometry. None were PDGF positive. The treatment was well tolerated. After treatment with Gleevec™, there were only 3 non-hematologic grade 3 or 4 toxicities, and they occurred in 1 patient: he developed a capillary leak type syndrome, ascites, and dyspnea as part of his terminal phase of myeloma which included evolution into plasma cell leukemia. Grade 3 myelosuppression was observed in a minority of patients: thrombocytopenia (3), neutropenia (1), and anemia (3). There were no responses, and no patients are currently receiving treatment. Patients ended treatment due to progressive disease (18 patients), death on study (3), adverse reactions (1), and other reasons (1). The median duration of treatment was 48 days (range: 12 to 349). Of the 7 patients who remained on study for more than 60 days, CD117 status was as follows: positive (4); negative (3); not ascertained (1). As of August 2004, 12 patients have died. Conclusions: Though forty-eight percent of the enrolled myeloma patients were CD117 positive, providing a putative target for the Gleevec™, no responses were seen in this high risk population of relapsed patients. Further study will be necessary to determine the significance of the observed stabilization of disease in 36% of the CD117 positive patients.