Citations

8032 Background: Human adipocytes can contribute directly to the in vitro growth and progression of multiple myeloma (MM) cell lines. Clinically, an elevated body mass index (BMI) has been associated with an increased risk of MGUS and a shorter time to progression (TTP) of MGUS to MM. However, the impact of BMI on the risk of early progression to MM from a more advanced plasma cell disorder such as smoldering MM (SMM) remains unknown. Methods: This study included patients (pts) with a known or new diagnosis of SMM evaluated at the Mayo Clinic, Rochester from January 2000-December 2010. Pts were classified based on their BMI as: normal (< 25) and elevated (>/= 25) BMI. Progression to symptomatic MM was defined by the development of hypercalcemia, renal insufficiency, anemia or lytic bone lesions. Results: There were 306 pts with a diagnosis of SMM who were included in this analysis. The median follow up was 106 months. There were 203 (66%) pts who progressed to symptomatic MM at last follow up. The median BMI of the group was 27.5 (Range: 17.2 – 56.4). There were 228 (75%) pts with an elevated BMI. There were 76 (28%) pts who had myeloma defining events (MDEs) such as a serum free light chain ratio > 100 or > 60% clonal bone marrow plasma cells at initial evaluation. MDEs were present in 17% and 33% of pts with a normal and elevated BMI respectively (P = 0.011). The median TTP of SMM to MM in pts with a normal and elevated BMI was 64 and 36 months respectively (P = 0.0006). The 2-year progression rate of SMM to symptomatic MM in pts with a normal and elevated BMI was 16% and 42% respectively (P < 0.0001). Upon limiting the analysis to only SMM pts without MDEs at initial evaluation (N =187), the 2-year progression rate to symptomatic MM with a normal and elevated BMI was 15% and 33% respectively (P = 0.013). In a multivariable model, only elevated BMI (P = 0.004) and increasing clonal bone marrow plasma cells (P = 0.001) was statistically significant in predicting for a 2-year progression to MM. Conclusions: SMM pts with an elevated BMI appear to have a higher risk of early progression to MM than those with a normal BMI. This study provides evidence of a potentially modifiable risk factor for the progression of SMM to MM and warrants confirmation in larger studies.

8014 Background: t(11;14) is a standard risk cytogenetic marker in MM. Methods: We reviewed 366 patients with MM who had t(11;14) by FISH and 732 age and period-matched controls without t(11;14), seen at our institution from 2004 to 2014 and outcomes were analyzed using time to first progression or death (PFS1) and overall survival (OS). Results: For the t(11;14) group at diagnosis, the median age was 63.7 yr (range, 22.1-95.4) with 64.5% of patients being male. Eighty nine (24.3%) patients were above 70 yr of age at diagnosis. 33.8%, 40.3% and 25.9% patients belonged to ISS 1, II and III stages respectively. 13% patients had elevated LDH. Monosomy 17 or del 17p were identified in 10.6% patients. The median follow up period was 56.9 months (m) (95% CI: 54.6-62.2) and 209 (57.1%) patients were alive at last follow-up. Among patients receiving proteasome inhibitor (PI)-based, immunomodulator (IMiD)-based, PI+IMiD based or other agent based induction therapy, 71.2%, 70.3%, 90.4% and 37.5% patients respectively attained ≥PR as best response to induction (p < 0.01). During their course, 223 (60.9%) patients underwent stem cell transplant. Median PFS1 and OS were 23.1 (CI: 20.8-27.9) and 78.6 (CI: 66.7-105.9) m respectively. Among the controls, high risk cytogenetics (HRC) was present in 142 (19.4%), and the median OS was 83.8 m (CI: 70.8-97.0) being comparable to t(11;14) group (p = 0.8). For all 1098 patients, using a Cox-proportional hazards model with age > 70 years, induction therapy (novel agent-based vs others), cytogenetics [HRC vs t(11;14) without HRC vs no HRC or t(11;14)], and ISS stage III vs II/I as predictors, age > 70 years [HR-2.2 (CI: 1.8-2.8) and p < 0.01], ISS III vs ISS II/I [HR-1.4 (CI: 1.1-1.8) and p < 0.01] and HRC [HR of 2.1 (CI: 1.6-2.8) vs no HRC or t(11;14) (p < 0.01) and 1.9 (CI = 1.4-2.6) for t(11;14) without HRC (p < 0.01)were associated with reduced OS. The risk for reduced OS did not differ between t(11;14) without HRC, and those without t(11;14) or HRC [HR-1.1 (CI: 0.9-1.4), p = 0.4]. Conclusions: Our study characterizes the outcomes of a large cohort of MM patients with t(11;14) at diagnosis. Advanced age, HRC and advanced stage at diagnosis were associated with worse OS in our cohort. t(11;14) MM without HRC does not differ in outcome compared to non-t(11;14) MM without HRC.

6572 Background: Cancer patients (pts) receive complex care that may cause physical, emotional, & financial sequelae. Current practice limits clinician time to address patient concerns. The Patient Reported Outcome Quality Of Life (PROQOL) system was developed as a self-reported electronic questionnaire to assess symptoms, QOL and provide data about bothersome issues. Our aim was to determine if the PROQOL system improves QOL without negatively impacting routine clinic workflow. Methods: Eligible pts had multiple myeloma, amyloidosis, head & neck or gynecologic cancer seen in Hematology/Oncology clinics at Mayo Clinic, and were stratified by stem cell transplant and active treatment status. Pts were randomized 2:1 to PROQOL system or usual care. PROQOL system was offered prior to every visit. Pts select from various categories about their single biggest concern, and receive a printed list of actionable resources based on selected concern. Clinicians also receive the PROQOL results to review with pts. Providers and pts randomized to PROQOL completed a “was it worth it survey” (WIWI). An 8 item Linear Analogue Self-Assessment was used to assess QOL. The study was powered to detect a 0.5 standard deviation difference in QOL between groups. Herein we report the planned results of first 6 months. Results: Among the first 118 pts accrued, 55% were female, median age was 63 (32-86), & 93% were on therapy. Median time from diagnosis to PROQOL was 26 months. The PROQOL system took 3.6 minutes to complete. Baseline median QOL (range) was 7 (3-10) for both groups. The most common PROQOL issue selected was “cancer & diagnosis” (36.5%) followed by “physical health” (35.3%). Specific concerns were related to treatment plan, prognosis, fatigue, sleep, and neuropathy. WIWI showed: 71% of pts thought it was worthwhile, 83% would participate again, 80% would recommend it, & 65% used resources provided. 80% of providers reported the PROQOL did not interfere with care & 75% believed the pt wellbeing may improve. Conclusions: Notably treatment plan & prognosis remain pts' greatest concern despite being over 2 year from diagnosis.The PROQOL system demonstrates integrated PRO reporting in clinic is quick & worthwhile to pts & providers.

1573 Background: There are no epidemiologic studies of SWM due to lack ofICD codes specific for smoldering status. Methods: The NCDB represents ~70% of cancer cases in the US. It records the time to initial treatment or reasons for not receiving treatment. Using the 2004-2012 database, we estimated the overall proportion of new adult WM cases that are smoldering and analyzed outcomes according to socio-geo-demographic subgroups. Patients who were recommended treatment (irrespective of administration status) or died within 120 days of diagnosis were considered to have active WM while those who did not require treatment and had follow-up ≥120 days after diagnosis were considered to have SWM. Results: 2322 (28%) of 8302 patients diagnosed with WM were SWM. Median age at diagnosis was 71 (range 28-90) years. Median age did not change significantly during 2004-2012 (P = 0.83) but the proportion of smoldering disease decreased with time (P = 0.02). The proportions of SWM according to socio-geo-demographic subgroups are shown in the Table. Conditional survival (given survival to 4 months) at 5-years was 66% vs. 70% and at 10-years was 38% vs. 46% for active WM vs. SWM, respectively. The OS for SWM was significantly better among females and those who were younger, privately insured, with less co-morbidities and residing closer to a health facility. However, the OS did not differ by racial groups or era of diagnosis 2004-2008 vs 2009-2012. On multivariate analysis, sex, age group and co-morbidity index were significant factors affecting OS while race, insurance, distance from health facility and era of diagnosis were not. Conclusions: Approximately 28% of WM cases in the US are smoldering at diagnosis. The prevalence of SWM varied among socio-geo-demographic subgroups. Sex, age and co-morbidities significantly affect survival of SWM. [Table: see text]