Citations

Abstract Gastrointestinal complications of multiple myeloma (MM) treatment are common and include nausea, constipation, and diarrhea. However, acute gastrointestinal events like perforations are rare. We aimed to describe the characteristics and outcomes of patients with MM that had colonic perforations during their treatment. This is a retrospective study that included patients from all three Mayo Clinic sites who had MM and developed a colonic perforation. All patients were diagnosed with colonic perforations based on CT scans and were surgically treated. Patients diagnosed with AL amyloidosis, a perforated colon complicating neutropenic colitis during ASCT and those with perforation due to colonic cancer were excluded. A high dose of dexamethasone was defined as ≥40 mg dexamethasone once a week. Thirty patients met inclusion criteria. All patients received steroids at doses ≥10 mg once weekly prior to the perforation, while four (11%) were on high‐dose dexamethasone without chemotherapy. Fourteen patients were given high doses of dexamethasone. Twenty‐five patients required ostomies with all surviving surgery. Twenty‐four perforations (80%) were associated with diverticulitis. Treatment with steroids was resumed in 23 patients with no further gastrointestinal complications. The median OS was 20 months following perforation (IQR 8–59). Within the same timeframe 5854 patients were treated at Mayo Clinic for MM, making the risk of bowel perforation 0.5%. Intestinal perforations in MM are rare and, in our series, always occurred with dexamethasone ≥10 mg per week. Urgent surgery is lifesaving and resumption of anti‐myeloma treatment appears to be safe.

As of May 13, 2020, the number of confirmed SARS-CoV-2 (novel corona virus, COVID-19) infections has risen to 4 300 000 worldwide, with over 1 300 000 confirmed cases in the United States. Various prediction models of spread indicate more hospitalization, increased ventilator use, and the shifting of medical resources to most efficiently serve the patient’s needs. Additionally, mitigation strategies such as monitoring for symptoms, social distancing, safer at home, and the wearing of masks caused our institution to implement significant operational changes to our usual practice. This included screening patients and staff for symptoms, rescheduling routine medical visits, postponing procedures, converting face-to-face visits to telephone or video visits, and changing visitor visit policies. In this article, we describe the various ways we deployed empathic communication messaging and resources across the institution during the COVID-19 pandemic.

Abstract Purpose: Rearrangements involving the MYC protooncogene are common in newly diagnosed multiple myeloma, but their prognostic significance is still unclear. The purpose of this study was to assess the impact of MYC rearrangement on clinical characteristics, treatment response, and survival in patients with newly diagnosed multiple myeloma. Experimental Design: This is a retrospective study including 1,342 patients seen in Mayo Clinic in Rochester, MN, from January 2006 to January 2018, who had cytogenetic testing by FISH at diagnosis, including MYC testing using the break apart FISH probe (8q24.1). Results: A rearrangement involving MYC was found in 8% of patients and was associated with elevated β2-microglobulin, ≥50% bone marrow plasma cells, IgA multiple myeloma, and the cooccurrence of trisomies. There were no differences in overall response rates between patients with and without MYC rearrangement when induction chemotherapy was proteasome inhibitor (PI)-based, immunomodulatory drug (IMiD)-based or PI + IMiD-based. Overall survival was shorter in patients with MYC rearrangement compared with patients without MYC rearrangement (5.3 vs. 8.0 years, P < 0.001). MYC rearrangement was associated with increased risk of death on multivariate analysis when high-risk cytogenetic abnormalities, ISS stage III, and ≥70 years of age were included (risk ratio: 1.5; P = 0.007). Conclusions: MYC rearrangement is associated with high disease burden and is an independent adverse prognostic factor in patients with newly diagnosed multiple myeloma.

Abstract A gain in chromosome 1q (+1q) is among the most common cytogenetic abnormalities in multiple myeloma (MM). It is unclear whether +1q is independently associated with decreased overall survival (OS). The objective of this study was to evaluate the impact of +1q on clinical characteristics, treatment response, and survival outcomes. We included 1376 Mayo Clinic patients diagnosed with MM from 2005 to 2018 who underwent fluorescence in situ hybridization testing at diagnosis with a panel including the +1q probe. A gain in 1q was found in 391 patients (28%) and was associated with anemia, hypercalcemia, high tumor burden, International Staging System (ISS) stage 3, high-risk (HR) translocations, and chromosome 13 abnormalities. There was no difference in overall response or deeper responses to proteasome inhibitor (PI)–, immunomodulatory drug (iMiD)–, or PI plus IMiD–based induction. Time to next treatment was shorter in patients with +1q compared with those without +1q (19.9 vs 27.7 months; P < .001). On univariate analysis, +1q was associated with increased risk of death (risk ratio [RR], 1.9; P < .001), and decreased OS was seen in all treatment groups. +1q was independently associated with decreased OS on multivariate analysis when other HR cytogenetic abnormalities, ISS stage 3, and age ≥70 years were included (RR, 1.5; P < .001). Gain of >1 copy of 1q was not associated with worse OS compared with gain of 1 copy (4.9 vs 4.3 years; P = .21). +1q was associated with high tumor burden, advanced disease stage, and HR translocations. It is independently associated with decreased OS, even in the setting of novel therapy and transplant.

AbstractResponse assessment in light chain (AL) amyloidosis is based on serum and urine monoclonal protein studies. Newly diagnosed patients (n = 373) who achieved very good partial response or complete response (CR) to first line therapy were assessed for the survival impact of each of the monoclonal protein studies. At end of therapy (EOT), negative serum/urine immunofixation (IFE) was achieved in 61% of patients, 72% achieved normal serum free light chain ratio (sFLCR), and the median involved free light chain (iFLC) and difference between involved to uninvolved light chain (dFLC) were 17 mg/L and 5 mg/L, respectively. Overall, 46% of patients achieved a CR at EOT. At EOT, iFLC ≤20 mg/L and dFLC ≤10 mg/L were additive in survival discrimination to negative serum/urine IFE and were independent predictors of overall survival. In contrast, normalization of sFLCR did not add survival discrimination to serum/urine IFE and was not independent predictor of survival. We propose a new definition for hematological CR to include serum/urine IFE negativity plus iFLC ≤20 mg/L or dFLC ≤10 mg/L, instead of the current definition of serum/urine IFE negativity and normal sFLCR. Complete response using dFLC ≤10 mg/L had the best performance in those with significant renal dysfunction and by light chain isotype, making it the preferred partner to IFE. Validation of these results in a multicenter cohort is warranted.

e20520 Background: Cytogenetic abnormalities detected by FISH are found in the majority of multiple myeloma (MM) patients. Although their prognostic value has been studied extensively, less is known about their association with disease characteristics and treatment response. Methods: To address these questions, we designed a retrospective study including 2031 Mayo Clinic patients diagnosed with MM from 2004 to 2018. We compared baseline characteristics and treatment outcomes between primary cytogenetic groups: t(11;14), t(4;14), t(14;16), (14;20), t(6;14), unknown IgH translocation/del and trisomy (without IgH translocation). These included 373, 177, 78, 20, 18, 228 and 791 patients respectively. Kruskal-Wallis and Fisher’s exact tests were used for categorical and continuous variables respectively. Time to next treatment (TTNT) was estimated using Kaplan-Meier method and compared using Log-Rank test. Results: t(4;14), t(14;16), t(6;14) and t(14;20) groups were associated with hemoglobin < 10 g/dL, beta2microglobulin > 5.5 µg/ml, ISS stage 3 and ≥50% bone marrow plasma cells. The latter 3 groups were also associated with renal dysfunction (Cr ≥2 mg/dL) and higher urinary monoclonal protein. t(4;14) was associated with IgA isotype, serum monoclonal protein ≥1g/dL and plasma cell labeling index ≥1%. Light chain myeloma was more prevalent in patients with t(11;14). Overall response rate (ORR) to proteasome inhibitor (PI) induction was higher for those with IgH translocations (any) compared to trisomies (85% vs 77% P = 0.02), while ORR was higher for those with trisomies with immunomodulatory drug (IMiD) induction (90% vs 78% P < 0.01). The rate of ≥ very good partial response was higher for patients with high risk IgH translocations [t(4;14), t(14;16) or t(14;20)] compared to standard risk with PI-IMiD combination treatment (88% vs 65% P < 0.01). Otherwise, response rates did not differ between these 2 groups. TTNT was longer in patients with trisomies compared to those with IgH translocation with IMiD or PI-IMiD treatments (32.2 vs 19 and 44 vs 27.4 months, respectively P < 0.01). For all cytogenetic groups, better treatment responses and longer TTNT were seen with PI-IMiD combinations compared to other treatments. Conclusions: t(4;14), t(14;16), t(6;14), and t(14;20) are associated with high risk disease characteristics. Patients with IgH translocations may have better response to PI induction compared to those with trisomies, while those with trisomies may have better response to IMiD treatment, with best outcomes for both seen with PI-IMiD combinations.

e20515 Background: IgA monoclonal proteins (MCPs), unlike IgG MCPs, often migrate in the beta region on serum protein electrophoresis (SPEP) which can lead to underestimation of their size due to the co-migration with physiologic proteins. In IgA multiple myeloma (MM), the utility of quantitative IgA levels in assessing disease response in comparison to SPEP is not well studied. Methods: We retrospectively analyzed 304 IgA MM patients, diagnosed between 2004 and 2018, with available serial MCP and quantitative IgA levels. Kaplan Meier analysis was used to estimate the median progression free survival (mPFS) using the IMWG criteria and our study definition of IgA progression (2 consecutive IgA values that are > 25% above the nadir IgA value and above upper limit of normal (ULN) of 356 mg/dL, and a detectable IgA MCP on serum immunofixation). The mPFS was defined as the time from treatment initiation until disease progression or death. Results: IgA MCP migrated in the beta region in 134 (44%) patients, and in the gamma region in 150 (56%) patients. At diagnosis the median MCP was 3 (IQR 1.9-4) g/dL and the median IgA was 3240 (IQR 2008-4420) mg/dL. The median time from treatment initiation to MCP nadir was 80 (IQR 42-144) days and median time to IgA nadir was 154 (IQR 90-238) days. At MCP nadir 40% of patients had an IgA above the ULN. All complete responders (n = 104) had normal IgA levels, with a median IgA of 54 (IQR 27-88) g/dL. A ≥90% decrease in IgA between treatment initiation and IgA nadir, compared to a < 90% decrease, was associated with a longer mPFS (34 vs. 20 months, p = 0.006) and overall survival (97 vs. 33 months, p = 0.003). Patients with serial MCP and IgA levels available prior to progression (n = 195) were used to compare the mPFS using the IMWG and IgA progression criteria. The mPFS using the IgA criteria was 32 (95% CI 29-39) months, versus 39 (95% CI 33-45) months using IMWG criteria. Overall, 92 (47%) patients progressed by both IMWG and IgA criteria. At the time of progression using the IgA criteria compared to at IMWG progression, the median hemoglobin was higher (13.3 vs. 11.6 g/dL, respectively, p < 0.001) and fewer patients had new symptomatic bone lesions (2% vs. 33%, respectively, p < 0.001). Conclusions: In IgA MM patients, monitoring quantitative IgA levels predicts disease response and allows for earlier detection of disease progression, prior to the development of end organ damage.

Abstract Absolute lymphocyte count (ALC) post-autologous stem cell transplantation is an independent predictor for survival in Hodgkin’s Disease (HD). Lymphopenia at diagnosis is associated with worse prognosis in patients with newly diagnosed HD. The role of ALC recovery during standard chemotherapy for HD is unknown. We analyzed all patients managed for HD at the Mayo Clinic from 1986 to 2003. Of the 141 consecutive patients, two patients were excluded due to missing ALC data. Of the 139 patients, 63 patients were females and 76 males. The median age of patients at diagnosis was 31 years (range 6–75 years). 118 (85%) patients presented with nodular sclerosis HD, 10 (7%) with mixed cellularity, 2 (1%) with lymphocyte predominance, 1(1%) with lymphocyte depletion, 4 (3%) with lymphocyte predominant (nodular variant), and 4 (3%) unclassified. Frontline chemotherapy included ABVD (N = 79), MOPP-ABV (N = 47), COPP-ABV (N = 8), BEACOPP (N = 3), and Stanford V (N =2). The median number of cycles was 6 (range: 2–10). The median follow-up for the cohort was 62 months (range: 4–221 months). The ALC recovery was analyzed during the first 4 cycles as 90% of the patients received at least 4 cycles of therapy. Patients with an ALC ≥ 1.3 x 109/l at any time point within the first four cycles of chemotherapy (N = 93) demonstrated improved overall survival (OS) and progression-free survival (PFS) compared to patients with an ALC &lt; 1.3 x 109/L at all time points within the first four cycles of chemotherapy (N =46) (10 years OS and PFS: 91% vs 51%, p &lt; 0.0001; 85% vs 52%, p &lt; 0.0001, respectively). Both groups were balanced for the Hasenclever Index: albumin &lt; 4g/dl (p = 0.1), hemoglobin &lt; 10.5 g/dl (p = 0.46), male gender (p =0.21), age ≥ 45 years (p = 0.06), stage IV disease (p = 0.68), leukocytosis ≥ 15 x 109/L (p = 0.58), and lymphopenia &lt; 600 cell/ml (p = 0.211). Multivariate analysis demonstrated ALC recovery to be independent predictor of OS and PFS when compared to the Hasenclever index. These data suggest a critical role of lymphocyte (immune) recovery during standard chemotherapy in HD.

AbstractThe diagnosis of primary plasma cell leukemia (pPCL) has been made by quantifying circulating plasma cells (cPCs) morphologically on a peripheral blood (PB) smear. However, this technique is not sufficiently sensitive. Multiparametric flow cytometry (MFC) provides a readily available and highly sensitive method to identify and quantify cPCs that could complement PB smear assessment. However, an optimal quantitative cutoff for cPCs by MFC to identify pPCL has not been established. Thus, a total of 591 patients newly diagnosed multiple myeloma (NDMM) patients who had their PB samples evaluated morphologically by PB smear, and immunophenotypically by MFC prior to beginning therapy were evaluated. The presence of ≥200 cPCs/μL by MFC (N = 25 or 5% of the total population) was chosen to identify patients with ≥5% cPCs by PB smear with a specificity of 99% and a sensitivity of 77%. For patients with ≥200 cPCs/μL by MFC compared to the remainder of the cohort, the median Time to next therapy (TTNT) was 18 vs 30 months and the median OS was 38 vs 70 months respectively. Thus, MFC assessment of PB can be utilized in conjunction with the morphological assessment of a PB smear to aid in improving the identification of pPCL among NDMM patients.

Introduction: With the expanding use of CAR-T cell therapy, which is associated with serious adverse effects (AEs), there is a need to characterize the patient's experience over time to guide patient/provider education, and help optimize symptom management. This study reports on longitudinal evaluation of patient-reported quality of life (QOL) and symptom burden of CAR-T cell therapy compared with established forms of cellular therapy i.e autologous stem cell transplant (autoSCT) and allogeneic SCT (alloSCT). Methods: Patients with hematologic malignancies were prospectively recruited in three cohorts: CAR-T, autoSCT and alloSCT. The primary endpoint was change in QOL from baseline, using the FACT-G questionnaire. Secondary endpoints were patient-reported AEs (PRO-AEs) using 7 items from the PRO-CTCAE and assessment of cognition/memory using the NeuroQOLv2 questionnaire. PRO-CTCAE data was graded using a composite score (combining frequency, severity, and interference) and rates, using a method adjusting for pre-existing baseline symptoms, were compared using Fisher's exact test. We also evaluated the time profile of PRO-AEs using the Toxicity over Time (ToxT) approach, a longitudinal approach to AE analysis (Thanarajasingam Lancet Onc 2016). Patients completed questionnaires at baseline, week 2 and monthly thereafter. Results: From 07/2018 to 06/2019, 93 patients were recruited (CAR-T: 20; autoSCT: 37; alloSCT: 36). At data cut-off, week 2 and months 1, 2 and 3 data were available in 74, 62, 46 and 35 patients, respectively. There was no difference in patient age across the 3 groups (median age 63, range 23-77; p=0.26). Baseline QOL by FACT-G total score (mean=83.4, SD=14.7; p=0.77), side effect bother by FACT-G GP5 (66/93 [71%] a little bit or less; p=0.72), activities and function (70/93 [75%] fairly normal activities or no limitations; p=0.68) and cognition by NeuroQOL t-score (mean=52.2, SD=8.13; p=0.39) were similar across 3 groups at baseline. The CAR-T group experienced significantly less worsening in QOL (FACT-G) than both autoSCT and alloSCT groups (Fig. 1a). Worsening in overall QOL nadired at week 2, after which QOL gradually returned to baseline in all groups. When comparing changes from baseline in overall QOL, statistically significant differences between groups were evident at week 2 (CAR-T vs autoSCT p&lt;0.001; vs alloSCT p&lt;0.001), month 1 (CAR-T vs autoSCT p=0.02; vs alloSCT p=0.003), month 2 (CAR-T vs autoSCT p=0.02; vs alloSCT p=0.001) and month 3 (CAR-T vs autoSCT p=NS; vs alloSCT p=0.03). Results for physical (Fig. 1b) and functional well-being (WB) were similar, with significantly less QOL worsening at week 2 in CAR-T vs autoSCT and alloSCT groups. The most common PRO-AEs (Table 1) in the CAR-T group were decreased appetite (59%), diarrhea (53%) and fatigue (44%). There was no statistically significant difference in the PRO-AEs between CAR-T and autoSCT groups. However, patients undergoing alloSCT had significantly higher proportion of PRO-AEs vs the CAR-T group, except for neuropathy and sad feelings. AutoSCT and alloSCT groups had significant worsening of FACT-G side effect bother (GP5) at week 2, which was significantly different from that of the CAR-T group, following which the side effect bother gradually returned to baseline. (Fig. 1c) This was the first application of ToxT to PRO-CTCAE data (graphs not shown). Bar charts of maximum grade frequency and stream plots of mean grade over time demonstrate that mouth sores, fatigue, diarrhea and decreased appetite peak at week 2 and improve by month 3, and are of lesser severity in the CAR-T vs autoSCT and alloSCT groups. The trajectory of maximum grade across all PRO-AEs was similar by group as overall side effect burden by FACT-G GP5. Heatmap visualization demonstrated significant intra-patient variability and allowed inspection of data completeness. No difference in cognition and memory was observed across the three groups over the first three months. (Fig. 1d) Conclusion: This study is the first to our knowledge to provide comprehensive PRO data comparing QOL, patient-reported AEs and cognition in CAR-T cell therapy vs. auto- and alloSCT, and the first application of ToxT to PRO-CTCAE data. Short-term QOL, including physical and functional WB domains was better in the CAR-T group vs. SCT groups. These data can serve as a guide for patient education and symptom management in CAR-T cell therapy. Co-senior authors: SKK & ACD Disclosures Paludo: Celgene: Research Funding; Celgene: Research Funding; Verily Life Sciences: Research Funding; Verily Life Sciences: Research Funding. Gertz:Johnson and Johnson: Speakers Bureau; Celgene: Consultancy; Appellis: Consultancy; Amyloidosis Foundation: Research Funding; DAVA oncology: Speakers Bureau; Physicians Education Resource: Consultancy; Amgen: Consultancy; Janssen: Consultancy; Abbvie: Other: personal fees for Data Safety Monitoring board; Medscape: Consultancy, Speakers Bureau; Prothena Biosciences Inc: Consultancy; Teva: Speakers Bureau; Research to Practice: Consultancy; Annexon: Consultancy; Alnylam: Consultancy; International Waldenstrom Foundation: Research Funding; Ionis/Akcea: Consultancy; Spectrum: Consultancy, Research Funding; i3Health: Other: Development of educational programs and materials; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees; Proclara: Membership on an entity's Board of Directors or advisory committees; Springer Publishing: Patents & Royalties. Dispenzieri:Akcea: Consultancy; Intellia: Consultancy; Janssen: Consultancy; Pfizer: Research Funding; Takeda: Research Funding; Celgene: Research Funding; Alnylam: Research Funding. Ansell:Trillium: Research Funding; LAM Therapeutics: Research Funding; Mayo Clinic Rochester: Employment; LAM Therapeutics: Research Funding; Seattle Genetics: Research Funding; Affimed: Research Funding; Regeneron: Research Funding; Trillium: Research Funding; LAM Therapeutics: Research Funding; Seattle Genetics: Research Funding; Regeneron: Research Funding; Seattle Genetics: Research Funding; Mayo Clinic Rochester: Employment; Regeneron: Research Funding; Bristol-Myers Squibb: Research Funding; LAM Therapeutics: Research Funding; Bristol-Myers Squibb: Research Funding; Trillium: Research Funding; LAM Therapeutics: Research Funding; Regeneron: Research Funding; Mayo Clinic Rochester: Employment; Seattle Genetics: Research Funding; Affimed: Research Funding; Bristol-Myers Squibb: Research Funding; Bristol-Myers Squibb: Research Funding; Bristol-Myers Squibb: Research Funding; Regeneron: Research Funding; LAM Therapeutics: Research Funding; LAM Therapeutics: Research Funding; Trillium: Research Funding; Seattle Genetics: Research Funding; Regeneron: Research Funding; Regeneron: Research Funding; Regeneron: Research Funding; Trillium: Research Funding; Seattle Genetics: Research Funding; Seattle Genetics: Research Funding; Trillium: Research Funding; Trillium: Research Funding; Trillium: Research Funding; Mayo Clinic Rochester: Employment; Mayo Clinic Rochester: Employment; Regeneron: Research Funding; Affimed: Research Funding; Trillium: Research Funding; Mayo Clinic Rochester: Employment; Affimed: Research Funding; Mayo Clinic Rochester: Employment; Seattle Genetics: Research Funding; Mayo Clinic Rochester: Employment; Mayo Clinic Rochester: Employment; Affimed: Research Funding; Seattle Genetics: Research Funding; Bristol-Myers Squibb: Research Funding; LAM Therapeutics: Research Funding. Bennani:Bristol-Myers Squibb: Research Funding; Bristol-Myers Squibb: Research Funding; Adicet Bio: Other: Advisory board; Adicet Bio: Other: Advisory board; Purdue Pharma: Other: Advisory board; Purdue Pharma: Other: Advisory board; Seattle Genetics: Other: Advisory board; Seattle Genetics: Other: Advisory board; Seattle Genetics: Other: Advisory board; Kite Pharma: Other: Advisory board; Adicet Bio: Other: Advisory board; Kite Pharma: Other: Advisory board; Bristol-Myers Squibb: Research Funding; Kite Pharma: Other: Advisory board; Purdue Pharma: Other: Advisory board. Kumar:Takeda: Research Funding; Celgene: Consultancy, Research Funding; Janssen: Consultancy, Research Funding.