Citations

Objective To examine the effect of HLP, defined as having a pre-existing or a new in-hospital diagnosis based on low density lipoprotein cholesterol (LDL-C) level ≥100 mg/dL during index hospitalisation or within the preceding 6 months, on all-cause mortality after hospitalisation for acute myocardial infarction (AMI) or acute decompensated heart failure (ADHF) and to determine whether HLP modifies mortality associations of other competing comorbidities. A systematic review and meta-analysis to place the current findings in the context of published literature. Design Retrospective study, 1:1 propensity-score matching cohorts; a meta-analysis. Setting Large academic centre, 1996–2015. Participants Hospitalised patients with AMI or ADHF. Main outcomes and measures All-cause mortality and meta-analysis of relative risks (RR). Results Unmatched cohorts: 13 680 patients with AMI (age (mean) 68.5 ± (SD) 13.7 years; 7894 (58%) with HLP) and 9717 patients with ADHF (age, 73.1±13.7 years; 3668 (38%) with HLP). In matched cohorts, the mortality was lower in AMI patients (n=4348 pairs) with HLP versus no HLP, 5.9 versus 8.6/100 person-years of follow-up, respectively (HR 0.76, 95% CI 0.72 to 0.80). A similar mortality reduction occurred in matched ADHF patients (n=2879 pairs) with or without HLP (12.4 vs 16.3 deaths/100 person-years; HR 0.80, 95% CI 0.75 to 0.86). HRs showed modest reductions when HLP occurred concurrently with other comorbidities. Meta-analyses of nine observational studies showed that HLP was associated with a lower mortality at ≥2 years after incident AMI or ADHF (AMI: RR 0.72, 95% CI 0.69 to 0.76; heart failure (HF): RR 0.67, 95% CI 0.55 to 0.81). Conclusions Among matched AMI and ADHF cohorts, concurrent HLP, compared with no HLP, was associated with a lower mortality and attenuation of mortality associations with other competing comorbidities. These findings were supported by a systematic review and meta-analysis.

Introduction: The use of PET-CR as a surrogate endpoint would expedite the development of novel therapies and enable better estimates of sample size based on early outcomes of a trial. Previous studies have reported an association between end-of-therapy (EOT) PET results and long-term progression-free (PFS) and overall survival (OS) in diffuse large B-cell lymphoma (DLBCL) patients receiving standard first-line chemoimmunotherapy. We have also previously shown that the overall predictability of PET-CR for PFS and OS in these trials is similar to that in 18 literature-based studies. (15-ICML 2019, P195). To assess the potential for PET-CR as a surrogate endpoint in registration trials, we conducted a prospectively designed individual patient-level-data meta-analysis of available clinical trials. Methods: We synthesized patient-level data from three prospective phase II and III trials (GOYA [NCT01287741], GATHER [NCT01414855], MAYO [NCT00670358]) conducted in previously untreated DLBCL patients, using a Bayesian hierarchical model. We considered the two treatment arms in GOYA (GOYA-R-CHOP [rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone] and GOYA-G-CHOP [obinutuzumab, cyclophosphamide, doxorubicin, vincristine, and prednisone]) separate; hence a total of four arms, excluding patients without baseline PET scans. We investigated the relationship between PET-CR and long-term survival outcomes overall and within patient subgroups. We used Kaplan-Meier plots to compare survival endpoints by PET-CR status. We considered hypothetical RCTs that have PET-CR and PFS as endpoints to show how our model of the relationship between PET-CR and PFS can be used to predict the trial outcome. Results: We included 1496 patients (GOYA-R, GOYA-G, GATHER, MAYO, respectively: 665, 669, 100, 62). EOT PET-CR status was determined by the Lugano criteria in GOYA and by IHP in the other two studies. The overall rate of PET-CR was 72%; respectively 72%, 73%, 62% and 74% per arm. Panel A of the Figure shows Kaplan-Meier plots of PFS by PET-CR status. The Bayesian modeled hazard ratio (HR) comparing PET-CR versus nonCR was 0.13 (95% CI: 0.10, 0.15). The model can be used in planning a clinical trial as follows. Suppose a new therapy improves the PET-CR rate from 70% to 85%. Based on our model the expected HR for PFS treatment effect would be 0.71 (95% CI: 0.58, 0.84). The trial sample size required to demonstrate such an improvement with 90% power is about 650 patients, assuming an accrual rate of 50 patients per month and a minimum follow-up time of 12 months. Panel B of the Figure shows the model-based PFS HR and its CI (shaded) as it depends on the PET-CR rate of the new therapy. This plot also shows the estimated total trial sample size (in red), again assuming the relationship between PET-CR and PFS in our model. However, our model may not apply for the new therapy; and the trial could have an adaptive design with final sample size tailored to the accruing information about PET-CR and PFS and their relationship for the therapies in the trial. Conclusions: Achieving an EOT PET-CR in newly diagnosed DLBCL is highly predictive of favorable outcome in the populations we considered. The estimated HR is 0.13 for PFS, PET-CR versus nonCR, and it is 0.10 for OS. Based on our model, a treatment that improves PET-CR rate could be reasonably expected to have a benefit on PFS and OS, for the populations we considered. Whether a new therapy, with a different mechanism of action, that improves PET-CR rate will extend PFS in a clinical trial is less clear. An adaptive trial could be initiated based on our model as a hypothesis. This hypothesis can be verified or updated using accruing information in the trial itself. Our model can also help in planning clinical trials for re-estimating sample size during the trial and considering early stopping for futility. Further work should investigate the applicability of PET-CR in predicting PFS and/or OS for treatments that have different mechanisms of action and for other populations of patients. Acknowledgements: This work was funded by Genentech/Roche. Disclosures Berry: Berry Consultants, LLC: Consultancy, Employment, Equity Ownership, Other: Berry Consultants, LLC is a company that provides statistical design and analysis services to pharmaceutical companies (including Genentech/Roche), medical device companies, U.S. NIH cooperative groups, patient advocacy groups, and international consortia. Broglio:Berry Consultants LLC: Employment. Ward:Hoffmann La Roche: Employment, Equity Ownership. Mattiello:F. Hoffmann-La Roche Ltd: Employment. Sahin:F. Hoffmann-La Roche Ltd: Employment, Equity Ownership. Nielsen:F. Hoffmann-La Roche Ltd: Employment, Equity Ownership. McGlothlin:Berry Consultants, LLC: Consultancy, Employment. Elliott:Berry Consultants, LLC: Employment. Sehn:Lundbeck: Consultancy, Honoraria; TG Therapeutics: Consultancy, Honoraria; Kite Pharma: Consultancy, Honoraria; Morphosys: Consultancy, Honoraria; Apobiologix: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Abbvie: Consultancy, Honoraria; Acerta: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Abbvie: Consultancy, Honoraria; TEVA Pharmaceuticals Industries: Consultancy, Honoraria; Janssen-Ortho: Consultancy, Honoraria; Merck: Consultancy, Honoraria; Merck: Consultancy, Honoraria; TG Therapeutics: Consultancy, Honoraria; Astra Zeneca: Consultancy, Honoraria; TEVA Pharmaceuticals Industries: Consultancy, Honoraria; Seattle Genetics: Consultancy, Honoraria; F. Hoffmann-La Roche/Genentech: Consultancy, Honoraria, Research Funding; Astra Zeneca: Consultancy, Honoraria; Kite Pharma: Consultancy, Honoraria; F. Hoffmann-La Roche/Genentech: Consultancy, Honoraria, Research Funding; Verastem: Consultancy, Honoraria; Morphosys: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; Gilead: Consultancy, Honoraria; Lundbeck: Consultancy, Honoraria; Acerta: Consultancy, Honoraria; Karyopharm: Consultancy, Honoraria; Janssen-Ortho: Honoraria; Takeda: Consultancy, Honoraria; Seattle Genetics: Consultancy, Honoraria. Trněný:Abbvie: Consultancy, Honoraria; Gilead Sciences: Consultancy, Honoraria; Incyte: Consultancy, Honoraria; Celgene: Consultancy; Janssen: Consultancy, Honoraria; Bristol-Myers Squibb: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; F. Hoffmann-La Roche: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; MorphoSys: Consultancy, Honoraria. Vitolo:Novartis: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Kite: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Abbvie: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Juno Therapeutics: Membership on an entity's Board of Directors or advisory committees; Gilead: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Celgene: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; F. Hoffmann-La Roche: Speakers Bureau. Martelli:Servier: Honoraria; F. Hoffman-La Roche, Celgene, Janssen, Sandoz, Novartis, Gilead: Honoraria, Membership on an entity's Board of Directors or advisory committees; Servier: Honoraria; F. Hoffman-La Roche, Celgene, Janssen, Sandoz, Novartis, Gilead: Honoraria, Membership on an entity's Board of Directors or advisory committees. Kostakoglu:F. Hoffman-La Roche: Consultancy; Genentech: Consultancy. Nowakowski:F. Hoffmann-La Roche Ltd: Research Funding; Curis: Research Funding; Bayer: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Genentech, Inc.: Research Funding; MorphoSys: Consultancy, Research Funding; Selvita: Membership on an entity's Board of Directors or advisory committees; NanoString: Research Funding.

Background: Venetoclax (Ven) is a highly selective, potent, oral BCL-2 inhibitor that induces apoptosis in multiple myeloma (MM) cells and has shown synergistic activity with the proteasome inhibitor (PI) bortezomib (B) and dexamethasone (d). Ven ± d had encouraging clinical efficacy in both t(11;14) MM and in pts irrespective of genetic background when administered with B, with a tolerable safety profile in Phase 1 studies. Here, we provide updated efficacy and safety of Ven vs placebo (Pbo) + Bd in pts with relapsed/refractory (RR) MM, including subgroup analyses, in the BELLINI study. Methods: BELLINI (NCT02755597) was a Phase 3, randomized, double-blind, multicenter study of Ven or Pbo + Bd in pts with RRMM who received 1 - 3 prior therapies and were either sensitive or naïve to PIs. Pts were randomized 2:1 to receive Ven 800 mg/day or Pbo + Bd. Cycles 1-8 were 21-day with B 1.3 mg/m2 on Days 1, 4, 8, 11 + d 20 mg on Days 1, 2, 4, 5, 8, 9, 11, 12. Cycles 9+ were 35-day with B 1.3 mg/m2 on Days 1, 8, 15, 22 + d 20 mg Day 1, 2, 8, 9, 15, 16, 22, 23. The primary endpoint was progression-free survival (PFS) by independent review committee (IRC). Results: A total of 291 pts were randomized, 194 to the Ven arm and 97 to the Pbo arm. Median age was 66 (range, 36 - 87); 53% had ISS II/III disease; 54% received 2 or 3 prior lines of therapy; 59% had prior stem cell transplant; 70% had prior PI, 68% had prior immunomodulatory drug, 41% had both. Among pts with evaluable results, 18% had high-risk cytogenetics, 13% had MM positive for t(11;14), and 79% had high levels of BCL-2 protein by immunohistochemistry (IHC). In the primary endpoint analysis per IRC, the median PFS was 22.4 months (m) in Ven vs 11.5 m in Pbo (HR=0.630, p=0.01), with a median follow-up of 18.7 m (as of 26 Nov 2018). As of updated analysis based on a data cut-off of 18 March 2019, the median PFS (per investigator [INV]) was 22.9 m in Ven vs 11.4 m in Pbo (HR=0.587, p=0.001; Table 1), with a median follow-up of 22.7 m. Per INV, higher overall response (ORR, 84% vs 70%, p=0.009) and very good partial or better response (≥VGPR, 61% vs 40%, p<0.001; Table 2) rates were observed in Ven vs Pbo. Minimal residual disease negativity rate (by next-generation sequencing) was also higher in the Ven arm vs Pbo (MRD- [10-5], 13% vs 1%). Median duration of response was 23.4 m for Ven and 12.8 m for Pbo. In the overall population, median overall survival (OS) was not reached in either arm but continued to favor Pbo (HR 1.474, 95% CI=0.870-2.498). A total of 70 deaths have been reported, 51 (26%) in the Ven arm and 19 (20%) in the Pbo arm. In the safety population (N=289), the most common treatment-emergent adverse events (TEAEs; Ven/Pbo) were diarrhea (59%/48%), nausea (37%/22%), constipation (35%/31%), and fatigue (31%/32%). The most common Grade 3/4 TEAEs were neutropenia (18%/8%), pneumonia (17%/12%), anemia (16%/15%), thrombocytopenia (15%/30%), and diarrhea (15%/12%); 23%/12% discontinued Ven due to a TEAE. The rates of serious AEs (51%/51%) and serious infections (30%/28%) were comparable between arms. There were 69 deaths in the safety population: in the Ven arm, 14 were treatment-emergent (TE; treatment start to 30 days after discontinuation) and 36 were non-TE (>30 days after treatment discontinuation); in the Pbo arm, 1 was TE and 18 were non-TE. In the t(11;14) subgroup, median PFS has not been reached for pts receiving Ven, but was 9.3 m for Pbo (HR=0.095; per INV). In the t(11;14)-negative (neg) subgroup, median PFS was 22.4 m and 10.7 m for Ven and Pbo, respectively (HR=0.627; per INV). Median OS has not been reached in either arm for the t(11;14) and t(11;14)-neg subgroups, although the HR favored Ven in t(11;14) pts, and Pbo in t(11;14)-neg pts. Analyses indicate that low BCL-2 expression by IHC and high-risk cytogenetics (defined as t(4;14, t(14;16), or del(17p)) were associated with decreased PFS and OS in the Ven arm (Table 1). In the high-risk cytogenetics pts, median PFS was 11.4 m in both arms (HR=0.99), and median OS has not been reached in either arm but favors Pbo (HR=10.6). In the subgroup with low BCL-2 expression by IHC, median PFS was 11.7 m and 17.0 m for Ven and Pbo, respectively (HR=1.42), and median OS was 21.3 m in the Ven arm and not reached in Pbo (HR=4.58). Conclusions: Updated analysis of BELLINI continue to reflect a favorable benefit-risk profile in t(11;14) pts, with meaningful clinical responses and improvement in PFS, as well as a positive trend in OS in this subgroup when treated with Ven + Bd. Disclosures Moreau: Celgene: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria. Harrison:Janssen Cilag: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; GSK: Consultancy, Research Funding; AbbVie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: investigator on studies, Research Funding; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Cavo:sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: travel accommodations, Speakers Bureau; celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: travel accommodations, Speakers Bureau; AbbVie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; bms: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; novartis: Honoraria. De La Rubia:Janssen: Consultancy; Takeda: Consultancy; Celgene Corporation: Consultancy; AMGEN: Consultancy; AbbVie: Consultancy. Popat:Celgene Corporation: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: travel, accommodations, expenses; Janssen: Honoraria, Other: travel support to meetings; Takeda: Honoraria, Other: travel, accommodations, expenses; GSK: Consultancy, Honoraria; AbbVie: Consultancy, Membership on an entity's Board of Directors or advisory committees. Gasparetto:Celgene: Consultancy, Honoraria, Other: Travel, accommodations, or other expenses paid or reimbursed ; BMS: Consultancy, Honoraria, Other: Travel, accommodations, or other expenses paid or reimbursed ; Janssen: Consultancy, Honoraria, Other: Travel, accommodations, or other expenses paid or reimbursed . Hungria:Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; BMS: Consultancy, Honoraria, Speakers Bureau; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; BMS: Consultancy, Honoraria, Speakers Bureau; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Salwender:Amgen: Honoraria, Other: Travel or accommodations; Takeda: Honoraria, Other: Travel or accommodations; Bristol-Myers Squibb: Honoraria, Other: Travel or accommodations; Sanofi: Honoraria, Other: Travel or accommodations; Celgene: Honoraria, Other: Travel or accommodations; AbbVie: Honoraria; Janssen Cilag: Honoraria, Other: Travel or accommodations. Suzuki:Ono: Research Funding; BMS: Honoraria, Research Funding; Takeda: Honoraria; Janssen: Honoraria; Celgene: Honoraria. Gay:Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Roche: Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees; AbbVie: Membership on an entity's Board of Directors or advisory committees; Roche: Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; AbbVie: Membership on an entity's Board of Directors or advisory committees. Mikala:Takeda: Honoraria; Roche: Honoraria; Novartis: Honoraria; Janssen: Honoraria; Celgene: Honoraria, Research Funding; Amgen: Honoraria; AbbVie: Honoraria, Research Funding. Punnoose:Genentech, Inc.: Employment; Roche: Other: Stock/stock options. Hong:Genentech Inc.: Employment, Equity Ownership; Roche: Equity Ownership. Sood:AbbVie: Employment, Other: Stock/stock options. Jalaluddin:AbbVie: Employment, Other: Stock/stock options. Ross:AbbVie: Employment, Other: Stock/stock options. Ward:AbbVie: Employment, Other: Stock/stock options. Maciag:AbbVie: Employment, Other: Stock/stock options. Kumar:Celgene: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Takeda: Research Funding. OffLabel Disclosure: Venetoclax is a BCL-2 inhibitor that is FDA-approved in some indications. This presentation will focus on venetoclax for treatment of multiple myeloma, which is not an approved indication.

Abstract Abstract 4886 Detection of high molecular weight light chain oligomers in urinary exosomes of patients with AL amyloidosis. Background Exosomes are microvesicles that are part of the multivesicular body (MVB) pathway. They are created by the inward budding of the cell surface membrane and contain both surface bound membrane proteins and cytosolic proteins which can be used to identify the cell of origin. Immunoglobulin light chain amyloidosis (AL) occurs as the result of amyloid formation by the misfolding of monoclonal light chains (LC) and deposition of these amyloid fibrils in various soft tissues. This reaction requires the organization of the monoclonal LC's into protofibrils which are then weave into amyloid fibrils. This study was undertaken to determine whether urinary exosomes of glomerular origin contain intermediate species of amyloid formation. Method Urine samples from patients with AL, light chain deposition disease (LCDD), multiple myeloma (MM) and monoclonal clonal gammopathy of undetermined significance (MGUS) were collected. Urinary exosomes were isolated and separated into fractions by gradient centrifugation. Western blots were performed on the urinary exosome fractions using anti-kappa or anti-lambda antibodies. Glomerular fractions were identified using antibodies directed toward podocin. Results Urine samples were collected from 5 patients with AL, 2 from LCDD, 1 from MM and 1 MGUS. On the Western blot, immunoglobulin LC were seen in all exosomal fractions in patients with AL amyloidosis, LCDD, MM but not MGUS which is similar to normal controls (not shown). In patients with AL, oligomeric species were found in the highest concentrations in fraction 4 and 5 (Figure 1). Fraction 4 and 5 were also stained for podocin, a glomerular protein (not shown). The highest molecular weight species was ∼250 kd which corresponds to a LC decamer. High molecular weight species were also identified in 1 of 2 LCDD patients corresponding to a tetramer. The band was identified in fraction 10 which had polycystin-1 expression suggesting a tubular origin. No high molecular weight LC species was found in patients with MM or MGUS. Conclusion Our study found high molecular weight LC species corresponding to the intermediates involved in protofibril formation in urinary exosomes of patients with AL. Smaller (tetramer) high molecular weight LC species were also found in a patient with LCDD but not in patients with MM and MGUS. Not only were the high molecular weight LC species found exclusively in the diseases characterized by deposition of LC aggregates, they were also found in the segments of the nephron where the deposits were expected: glomerulus for AL and tubular epithelium for LCDD. This is consistent with our current understanding of the pathogenic mechanisms of these diseases. We believe urinary exosomes are a powerful tool in the study of diseases involving self-aggregation of monoclonal proteins. It has tremendous potential in both diagnostic and scientific research in this area. Disclosures Gertz: celgene: Honoraria; millenium: Honoraria, Membership on an entity's Board of Directors or advisory committees.

Abstract Background: Immunoglobulin light chain (AL) amyloidosis is a fatal complication of B-cell clonal proliferation. Currently, the best biomarker for treatment monitoring is serum free light chain (FLC) assay. Despite its higher sensitivity, it cannot distinguish clonality thus ultralow levels of monoclonal gammopathy can be missed. Urinary exosomes (UExs) are the smallest members of the extracellular vesicle family that are excreted in the urine. They exhibit different characteristics in patients with AL amyloidosis vs multiple myeloma. This study was undertaken to determine if urinary exosomes have different characteristics in patients AL amyloidosis who progress despite being in complete response (CR) vs those who have a renal response. Methods: UEx were extracted from 4 patients at different stages of AL (Table 1). Immunoglobin light chains (LC) were identified in the UEx using western blotting. Intact immunoglobulin light chains were identified in plasma, UEx, and kidney biopsy amyloid deposits using mass spectrometry (MS). cDNAs from bone marrow plasma cells (BMPC) collected at the time of diagnosis from patient 4 were sequened. Results: Oligomeric LC (250 kd) were identified in the UEx of patient 1 (newly diagnosed, Fig 1a) and 4 (renal progression in CR, Fig 1d) but only monomeric LC (25 kd) were detected in patient 2 (Fig 1b) and 3 (CR and renal response, Fig 1c). MS of the UEx and plasma of patient 4 detected 2 monoclonal λ LC. The mass of one of the LC was consistent with a lambda 6a LC which is also the most common cDNA (IGLV-6-57) found in the BMPC. Amino acid sequences derived from the tryptic digestion of the amyloid deposits matched the predicted sequence of the cDNA. The calculated weight of the peptide produced by the cDNA (23,304 Da ) was within margin of error of the mass of the lambda 6a LC (23,306 Da). The mass of the second LC (23,092 Da) was consistent with a λ4/λ5 LCs. A search of the amino acid and cDNA sequences failed to identify any similarity. The density ratio of the oligomeric LC to monomeric LC in the UEx was 0.47 which was similar to the intensity ratio by MS of the lambda 6a LC (23,306 Da) to the 23,092 Da LC in the blood (0.43). Discussion: Urinary EXs identified oligomeric LC in a patient with progressive renal disease despite achieving a CR. The mass one of the λ LC matched the predicted peptide product of the cDNA obtained from BMPC. The amino acid sequence predicted by the cDNA matched the trypsin digested sequences from the amyloid deposits. This strongly suggests the oligomeric LC represents the amyloidogenic λ6a LC detected in the blood which was being produced by the BMPC clone which is being deposited as amyloid in the kidney. The origin of the second λ LC is unknown but is likely a new monoclonal gammopathy of undetermined significance that developed after the initial bone marrow biopsy. The blood and urine samples were obtained 3 years after the BMPC. The development of a new monoclonal gammopathy in patients with plasma cell dyscrasia is not uncommon. Unfortunately, bone marrow biopsy collected at the time of the urine and blood sample had insufficient number of plasma cells (CR) for analysis. Conclusion: UEx can identify amyloidogenic LC even when current standard methods could not. The persistent presence of the amyloidogenic LC helps explain why patients can progress despite being in CR. The presence of a second λ LC which was not part of the amyloid deposit also has clinical implication. It may explain why some patients do well despite having a persistent monoclonal protein. If these results are confirmed, UEx may have a powerful role in the determination of organ and hematologic response in patients with AL amyloidosis. Disclosures Dispenzieri: Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; Prothena: Membership on an entity's Board of Directors or advisory committees; Alnylam: Research Funding; GSK: Membership on an entity's Board of Directors or advisory committees; pfizer: Research Funding; Jannsen: Research Funding; Celgene: Research Funding.

Abstract Background: Smoking is the most common etiology for lung cancer. Smoking cessation, even when successful, does not eliminate risk of lung cancer. With inconsistent results of lung chemoprevention trials, an emerging area of interest is immunoprevention, in particular vaccines. MUC1 is a transmembrane glycoprotein aberrantly overexpressed in adenocarcinomas, including lung cancer. Abnormal MUC1 expression is also characteristic of premalignant lesions, including bronchial dysplasia and atypical adenomatous hyperplasia. This suggests that immunization with a MUC1 vaccine in the premalignant or high-risk setting, before the tumor and cytotoxic therapy could suppress the immune system, might be effective in inducing strong immunity and reducing cancer risk. Trial design: Leveraging the infrastructure of the NCI-funded Cancer Prevention Network (CPN) consortium, we are conducting a two-center pilot trial to evaluate co-primary endpoints: immunogenicity of the MUC1 peptide plus polyICLC adjuvant vaccine (assessed at 12 weeks) and safety (assessed at up to 24 weeks) in current and former smokers who are at high risk for lung cancer. 50 participants will be screened in order to have 40 evaluable participants for baseline and 12-week immunogenicity assessments. Eligibility: Smoking history of ≥30 pack-years and either current smoker (still smoking or quit &lt; 1 year prior to pre-registration) or former smoker (quit 1-15 years prior to pre-registration); ages 55-80 years; ECOG performance status ≤1; CT scan of the chest done ≤ 6 months prior to pre-registration showing either negative findings (no nodules) or solid or part-solid nodules &lt; 6 mm in size (consistent with &lt; 1% probability of malignancy, Lung-RADs Version 1.0). Exclusion criteria are standard. Immunogenicity and safety: MUC1 peptide plus polyICLC adjuvant vaccine will be administered at week 0, 2 and 10. The primary endpoint is anti-MUC1 IgG titer that is ≥2 fold higher at week 12 compared to baseline. Based on previous studies of this vaccine, we expect that 40 evaluable participants will provide 96% power to detect immunogenicity response rate of 15% versus 40% using a 2-sided test of proportions with type I error rate of 0.05. AEs and toxicities will be monitored for up to 24 weeks from the first vaccine. Secondary Objectives: We will explore differences, if any, in vaccine immunogenicity in current vs. former smokers. Smoking induces chronic inflammation (hallmark of cancer) associated with immunosuppression. We will evaluate pre-vaccination levels of circulating myeloid derived suppressor cells (MDSC) and correlate with the response to the vaccine. We will explore the impact, if any, of this vaccine on the markers of inflammation (hsCRP, IL-6) and the effect of baseline levels of these markers on the ability to successfully vaccinate. We will also assess the relationship between COPD status and immune response in current versus former smokers. The trial is open to accrual. Citation Format: Olivera J. Finn, Julie Ward, Tami Krpata, Lisa Bengtson, John McKolanis, Sharon Kaufman, Colleen Akerley, April Felt, Karrie Fursa, Anne Holland, Nathan Foster, Andres Salazar, Malgorzata Wojtowicz, Eva Szabo, Paul Limburg, David Midthun, Arjun Pennathur. A pilot study of a MUC1 vaccine in current and former smokers at high risk for lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr CT222.

AbstractBackgroundRacial disparities in breast cancer (BC) outcomes persist where non-Hispanic black (NHB) women are more likely to die from BC than non-Hispanic white (NHW) women, and the extent of this disparity varies geographically. We evaluated tumor, treatment, and patient characteristics that contribute to racial differences in BC mortality in Atlanta, Georgia, where the disparity was previously characterized as especially large.MethodsWe identified 4943 NHW and 3580 NHB women in the Georgia Cancer Registry with stage I–IV BC diagnoses in Atlanta (2010–2014). We used Cox proportional hazard regression to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) comparing NHB vs NHW BC mortality by tumor, treatment, and patient characteristics on the additive and multiplicative scales. We additionally estimated the mediating effects of these characteristics on the association between race and BC mortality.ResultsAt diagnosis, NHB women were younger—with higher stage, node-positive, and triple-negative tumors relative to NHW women. In age-adjusted models, NHB women with luminal A disease had a 2.43 times higher rate of BC mortality compared to their NHW counterparts (95% CI = 1.99 to 2.97). High socioeconomic status (SES) NHB women had more than twice the mortality rates than their white counterparts (HR = 2.67, 95% CI = 1.65 to 4.33). Racial disparities among women without insurance, in the lowest SES index, or diagnosed with triple-negative BC were less pronounced.ConclusionsIn Atlanta, the largest racial disparities are observed in luminal tumors and most pronounced among women of high SES. More research is needed to understand drivers of disparities within these treatable features.

Purpose To explore faculty perspectives on which characteristics of high-performing clerkship students are most important when determining an honors or top grade designation for clinical performance. Method In 2016–2017, the authors surveyed faculty (teaching ward attendings) for internal medicine clerkships and 1 pediatrics clerkship in inpatient settings at 5 U.S. academic medical centers. Survey items were framed around competencies, 24 student characteristics, and attitudes toward evaluation. Factor analysis examined constructs defining high-performing students. Results Of 516 faculty invited, 319 (62%) responded. The top 5 characteristics as rated by respondents were taking ownership, clinical reasoning, curiosity, dependability, and high ethical standards (in descending order). Twenty-one characteristics fit into 3 factors (Cronbach alpha, 0.81–0.87). Clinical reasoning did not fit into a factor. Factor 1 was the most important (mean rating, 8.7/10 [95% confidence interval (CI), 8.6–8.8]). It included professionalism components (ownership, curiosity, dependability, high ethical standards), presentation and interviewing skills, seeking feedback, and documentation. Factor 2 (mean, 7.9 [95% CI, 7.7–8.0]) included aspects of teamwork and communication, such as positive attitude and comments from others. Factor 3 (mean, 7.6 [95% CI, 7.4–7.7]) addressed systems-based thinking, including patient safety and care transitions. Conclusions Professionalism components, clinical reasoning, and curiosity were among the most important characteristics distinguishing high-performing clerkship students. These may represent behaviors that are highly valued, observable, and relevant to training stage. Improved definition of the characteristics associated with clinical honors would assist students, faculty, and residency program directors when interpreting clinical performance within core clerkships.