Experiences and Support Needs of Caregivers of Patients with Higher-Risk MDS: Qualitative Insights Via Online Bulletin Board in the US, UK, and Canada

Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 21-22
Author(s):  
Pauline Frank ◽  
Emma Sasse
Keyword(s):  
High Risk ◽  
Advanced Cancer ◽  
Bulletin Board ◽  
Publicly Traded ◽  
Exclusion Criteria ◽  
Patient Organizations ◽  
The Us ◽  
Risk Patients ◽  
Online Bulletin Board ◽  
Caregiver Role

Higher-risk MDS patients and caregivers can face many challenges in the course of the disease and disease management. Patients with advanced cancer and their caregivers can both experience physical, emotional, social, spiritual, and functional issues. Research on the burden of caring for advanced cancer patients suggest that there is insufficient support for caregivers, which might be due to the lack of knowledge about their needs and burdens (Friðriksdóttir et al. 2011; Chambers et al. 2012; Sklenarova et al. 2015). The overall experience of caregivers for MDS patients has not been evaluated to date. Our key research questions are related to: Caregiver role before, during, and after diagnosis; and along the disease journeyImpact on the caregiver's life and well-being; consequently their areas of need for supportImpact of decisions made, including treatments We used the online bulletin board (OBB) as the qualitative research methodology for this research. OBB enables data collection via a web-based platform. This innovative type of online focus group, can generate more meaningful and impactful insights compared to traditional focus groups (Reid et al. 2005). A mix of moderator-led Q&A and participant discussion will provide the caregiver insights as online dialogue. OBB is especially advantageous when participants are located in various geographic locations, time zones, and with differing availabilities (Rolland et al. 2013; Nyumba et al. 2018). This methodology will guide the caregiver discussions, optimize the gathering of caregiver insights, and facilitate interactive activities, including appropriate probes and follow up questions. Since it would be challenging to identify caregivers of higher-risk MDS patients, the research uses convenience sampling with the support of patient organizations. Fifteen participants were targeted for recruitment by patient organizations in their respective countries - Myelodysplastic Syndromes (MDS) Foundation in the US, Aplastic Anemia & Myelodysplasia Association of Canada, and MDS UK Support Group - through outreach to their membership. Participants were to be selected based on the inclusion and exclusion criteria, with additional screening by the researchers. Inclusion criteria Caregiver of patient diagnosed with high or very high risk MDS as diagnosed per IPSS-R category or high-risk MDS as per IPSS (intermediate-risk patients on hypomethylating agents (HMAs) will be considered only if it is challenging to recruit caregivers of high and higher-risk patients) Aged 18+ Able to communicate in written English Caregiver is able to provide consent to participate in research Exclusion criteria Caregiver of patient diagnosed with low or very low risk MDS as diagnosed per IPSS-R category or low-risk as per IPSS Caregiver of patients currently active in a clinical trial Paid caregiver who is a nurse or aide We present in this abstract an interim report of the research, which is still ongoing. A total of 16 caregivers participated in the OBB with additional recruitment to cover any potential drop outs or withdrawals - 5 from the US, 6 from the UK, and 5 from Canada. There are 14 female and 2 male caregivers whereby 13 are spouses of the patient, 2 are children of the patient, and 1 is a friend of the patient. Full content analysis will be conducted at the completion of the research. However the interim findings already indicate there are unmet patient and caregiver needs in higher-risk MDS. For example, although the caregiver role for more recently diagnosed patients (≤ 1 year) is perceived as minimal effort, their role increases significantly if a stem cell or bone marrow transplant occurs, and/or if there are changes in the patient's health status (e.g. infection, medication change, managing side effects like nausea). The implications of this vary depending on the personal situation of the caregiver - the ability to continue in any employment and financial consequences if not; the demand on their time if they are balancing family and other commitments; and the impact on their own health particularly if they have their own health issues to manage. Most caregivers can manage the physical and functional aspects of care, however, many state that the bigger unmet need for both patient and caregiver is emotional support, which has not typically been part of the standard of care provided to MDS patients. Disclosures Frank: Novartis Pharma AG: Current Employment, Current equity holder in publicly-traded company. Sasse:Novartis Pharma AG: Current Employment, Current equity holder in publicly-traded company.

scholarly journals Clinical and Radiographic Predictors of Intracerebral Hemorrhage Outcome

2018 ◽  
Vol 7 (1-2) ◽  
pp. 118-136 ◽  
Author(s):  
Fawaz Al-Mufti ◽  
Ahmad M. Thabet ◽  
Tarundeep Singh ◽  
Mohammad El-Ghanem ◽  
Krishna Amuluru ◽  
...  
Keyword(s):  
Patient Outcome ◽  
High Risk ◽  
Mortality Rate ◽  
Intracerebral Hemorrhage ◽  
Functional Independence ◽  
High Morbidity ◽  
High Risk Patients ◽  
The Us ◽  
Risk Patients

Background: Intracerebral hemorrhage (ICH) represents 10-15% of all stroke cases in the US annually. Fewer than 40% of these patients ever reach long-term functional independence, and mortality rate is roughly 40% at 1 month. Due to the high morbidity and mortality rates after ICH, early detection of high-risk patients would be beneficial in directing the management course and goals of care. This review aims to discuss relevant clinical and radiographic characteristics that can serve as predictors of poor prognosis and examine their efficacy in predicting patient outcomes after ICH. Summary: A literature review was conducted on various clinical and radiographic factors. They were examined for their predictive value in relation to ICH outcome. Studies that focused on each of these factors were included, and their results analyzed for trends with regard to incidence, patient outcome, and mortality rate. Key Message: In this review, we examined clinical and radiographic characteristics that have been found to be significantly associated to a varying degree with poor outcome. Clinical and radiographic predictors of poor patient outcome are invaluable when it comes to identifying high-risk patients and triaging accordingly as well as guiding decision-making.

scholarly journals Real-World Treatment Patterns and Outcomes of Patients with Chronic Lymphocytic Leukemia (CLL) Receiving First-Line (1L) Therapy in the United States (US)

Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 4086-4086
Author(s):  
Anthony R. Mato ◽  
Arliene Ravelo ◽  
Tu My To ◽  
Robert Schuldt ◽  
Juliana M.L. Biondo
Keyword(s):  
High Risk ◽  
Research Funding ◽  
Treatment Patterns ◽  
Publicly Traded ◽  
Treatment Regimens ◽  
The Past ◽  
Oral Agents ◽  
The Us ◽  
Testing Patterns ◽  
Over Time

Abstract Background: There have been many advances in CLL treatments over the past decade, with a number of novel agents targeting molecular pathways within CLL cells receiving approval from the US Food and Drug Administration. Here, we assessed the evolution of molecular testing patterns, treatment patterns, and clinical outcomes over time in patients receiving 1L CLL treatment in a real-world US database. Methods: This was a retrospective cohort study using the Flatiron Health database, a longitudinal database comprising de-identified, patient-level, structured and unstructured data, curated via technology-enabled abstraction. During the study period, the de-identified data originated from approximately 280 cancer clinics (~800 sites of care) in the US. Patients aged 18 years and older who were diagnosed with CLL and initiated 1L treatment between December 2015 and December 2020 were selected. Participants who took part in a clinical trial in any line of therapy, or who had any other primary cancer diagnosis, were excluded. Baseline characteristics, including testing patterns, at initiation of 1L treatment were assessed using descriptive statistics. Treatment patterns and outcomes, such as time to next treatment or death (TTNTD), were analyzed. Kaplan-Meier analysis was used to estimate TTNTD. Results: Among 3654 patients with treatment-naive CLL who were selected from the de-identified database, the mean age at 1L treatment initiation was 70 years (range, 29-85); 64.3% of patients were male; 72.1% were White, 8.2% Black, 3.9% Hispanic/Latino, 1.0% Asian, and 14.9% were of other ethnicity/race. Approximately one-third (34.7%) of patients had Rai stage 0-I disease, 6.9% had stage II, 6.3% stage III, 11.5% stage IV, and 40.6% had undocumented Rai stage. Testing patterns: The majority of identified patients (3202/3654; 87.6%) had undergone cytogenetic testing, fluorescence in situ hybridization, or IGHV mutation testing. Compared with 2015-2016, testing rates were higher in 2019-2020 for chromosome 17p deletion (del(17p); 36.1% vs 45.7%, respectively; p<0.001) and for IGHV mutation status (84.7% vs 89.2%, respectively; p=0.003). Overall, 11.0% of patients had del(17p). Of those tested for IGHV (1472/3654; 40.3%), 58.3% had unmutated IGHV. Treatment patterns: The 10 most commonly used 1L CLL treatments, which overall represented 91.8% of all 1L treatments, and their evolution over time, are reported in Table 1. Of the patients receiving these top 10 1L treatment regimens overall, 45.7% received regimens including novel targeted oral agents, 33.4% received chemo-immunotherapy (CIT), and 19.7% received anti-CD20 monotherapy. Evaluation of each 2-year period shows that treatment patterns for the top 10 1L treatment regimens shifted, with use of novel targeted oral agents increasing from 27.1% (2015-2016) to 63.8% (2019-2020) (p<0.001), while use of CIT and chemotherapy decreased over time (Table 2). Approximately 30.0% (1088/3654) of 1L-treated patients went on to receive second-line treatments. Outcomes: Median TTNTD was 34.4 months for all patients receiving 1L CLL treatment, and 36.5 months for patients who received the 10 most common 1L treatments across the 6-year study period (n=3360). Median TTNTD was 47.0 months for patients who received novel targeted oral agents and 41.5 months for patients who received CIT (unadjusted p=0.16). When evaluating outcomes in patients with high-risk cytogenetics, median TTNTD was 29.1 months for patients with del(17p) and 37.2 months for those with unmutated IGHV, but was longer in those patients who received treatment with novel targeted oral agents (median TTNTD of 43.9 and 46.7 months, respectively; Table 3). Conclusions: This analysis provides the current state of 1L CLL testing and treatment patterns and outcomes in the US from 2015 to 2020. As expected, the use of novel targeted oral agents increased over time, with a corresponding increase in TTNTD. Clinical outcomes were improved in patients receiving novel targeted oral agents, both overall and in high-risk subgroups. Following on from this, a comparative study of TTNTD for novel oral agents versus CIT, and analyses of outcomes of different sequencing of therapies, will be conducted. Figure 1 Figure 1. Disclosures Mato: Nurix: Research Funding; Johnson and Johnson: Consultancy, Research Funding; AbbVie: Consultancy, Research Funding; Acerta/AstraZeneca: Consultancy, Research Funding; DTRM BioPharma: Consultancy, Research Funding; Pharmacyclics LLC, an AbbVie Company: Consultancy, Research Funding; Adaptive Biotechnologies: Consultancy, Research Funding; BeiGene: Consultancy, Research Funding; MSKCC: Current Employment; Sunesis: Consultancy, Research Funding; AstraZeneca: Consultancy; TG Therapeutics: Consultancy, Other: DSMB, Research Funding; Genmab: Research Funding; LOXO: Consultancy, Research Funding; Genentech: Consultancy, Research Funding; Janssen: Consultancy, Research Funding. Ravelo: Genentech, Inc.: Current Employment; Roche Holdings: Current equity holder in publicly-traded company, Current holder of stock options in a privately-held company. To: Genentech, Inc.: Current Employment; F. Hoffmann-La Roche Ltd: Current equity holder in publicly-traded company, Divested equity in a private or publicly-traded company in the past 24 months. Schuldt: Genentech, Inc.: Current Employment; F. Hoffmann-La Roche Ltd: Current equity holder in publicly-traded company; Johnson & Johnson: Divested equity in a private or publicly-traded company in the past 24 months. Biondo: Genentech, Inc.: Current Employment; Roche: Current holder of individual stocks in a privately-held company.

scholarly journals Real-World Persistence and Time to Next Treatment with Ibrutinib Treatment in Patients with Chronic Lymphocytic Leukemia/Small Lymphocytic Lymphoma Including Patients at High Risk for Atrial Fibrillation or Stroke

Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 4112-4112
Author(s):  
Anna Narezkina ◽  
Xiaoxiao Lu ◽  
Bruno Emond ◽  
Aurélie Côté-Sergent ◽  
Annalise Hilts ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Clinical Trials ◽  
High Risk ◽  
Lymphocytic Leukemia ◽  
Baseline Risk ◽  
Small Lymphocytic Lymphoma ◽  
Publicly Traded ◽  
Risk Patients ◽  
The Mean ◽  
Line Of Therapy

Abstract Introduction: Ibrutinib, a once-daily Bruton's tyrosine kinase inhibitor (BTKi), is the only targeted therapy that has demonstrated overall survival benefits compared to chemo- and/or immunotherapy across multiple phase 3 clinical trials in first line (1L) and relapsed/refractory chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL). Evidence suggests that atrial fibrillation (AF) is a potential adverse event (AE) associated with all BTKi's used to treat patients with CLL/SLL. While CLL/SLL patients may have a high baseline risk of AF, little is known about the real-world (RW) outcomes of BTKi's such as ibrutinib for these patients. In this study, we describe time to next treatment (TTNT) and time to discontinuation (TTD) for CLL/SLL patients who initiated a 1L or second or later line (2L+) of therapy with ibrutinib or other regimens, in all patients and for subsets of patients with high baseline risk of AF/AF-related stroke. Methods: In this descriptive study, the nationwide Flatiron Electronic Health Record-derived de-identified database (02/12/2013-01/31/2021) was used to select patients with CLL/SLL who had ≥2 clinic visits and started 1L or 2L+ therapy with ibrutinib or other regimens (e.g., chemoimmunotherapy [CIT], other novel targeted agents) on or after 02/12/2014 (index date). For each setting (1L and 2L+) and index regimen (ibrutinib or other regimens), three cohorts were considered: all patients, patients at high risk of AF (CHARGE-AF risk score ≥10.0%), and patients at high risk of AF-related stroke (CHA 2DS 2-VASc risk score ≥3 [females] or ≥2 [males]). TTD was defined as the time from starting index therapy to the earliest of: (1) stopping treatment (when a gap of >120 days was observed after the last day of supply of continuous treatment), (2) the day before switching to a next line of therapy, or (3) the end of data availability if patients did not stop or switch treatment. TTNT was defined as the time from starting index therapy to the start of the next line of therapy. TTNT was compared between cohorts using Kaplan-Meier rates with log-rank P-values. Results: A total of 2,190 (20% high risk CHARGE-AF [N=438], 49.3% high risk CHA 2DS 2-VASc [N=1,080]) and 1,851 (17.5% high risk CHARGE-AF [N=324], 44.5% high risk CHA 2DS 2-VASc [N=824]) patients were treated with ibrutinib in 1L and 2L+, respectively; while 4,388 (15.6% high risk CHARGE-AF [N=686], 44.3% high risk CHA 2DS 2-VASc [N=1,946]); and 4,135 (20.8% high risk CHARGE-AF [N=862], 50.5% high risk CHA 2DS 2-VASc [N=2,089]) patients were treated with other regimens in 1L and 2L+, respectively. Among other regimens, CIT was generally the most common regimen (42.9%-55.4% and 20.8%-26.7% of patients in 1L and 2L+, respectively). The prevalence of high risk del(17p) mutation at baseline was higher for patients treated with ibrutinib (24.0-25.5%) than for other regimens (7.5-14.2%). The mean Quan-Charlson comorbidity index score was ~2.3 and the prevalence of baseline cardiovascular comorbidities (e.g., hypertension, diabetes, and acute coronary syndrome), varied among cohorts in 1L and 2L+ (Table 1, 2L+ data not shown). In the ibrutinib 1L cohorts, the mean follow-up length was 26.9 months in all patients, 22.9 months in high risk CHARGE-AF, and 24.9 months in high risk CHA 2DS 2-VASc, with mean TTD being 20.0, 16.1, and 18.0 months, respectively. Similar results were found in 2L+, for all patients and high risk cohorts. TTNT was longer for all patients on ibrutinib (1L and 2L+ median TTNT not reached) than for all patients on other regimens (1L median TTNT: 45.9 months [Fig 1a]; 2L+ median TTNT: 23.6 months [Fig 1b], all P<0.05). Similar results were observed when comparing high risk patients on ibrutinib to high risk patients on other regimens (all P<0.05). For both ibrutinib and other regimens, there were no differences in TTNT between all patients and high risk cohorts, in 1L and 2L+ (all P>0.05; Fig 1a and 1b). Conclusions: In this analysis, patients at a high risk for AF/AF-related stroke continued to demonstrate benefit with ibrutinib use across all lines of therapy. In addition, TTNT was significantly longer for patients treated with ibrutinib-based regimens than other regimens. Overall, this study confirms the RW benefits as demonstrated across multiple clinical trials and shows that baseline risk of AF/AF-related stroke does not adversely impact TTNT associated with ibrutinib use in patients with CLL/SLL. Figure 1 Figure 1. Disclosures Narezkina: Pharmacyclics, Janssen Scientific Affairs: Consultancy. Lu: Janssen Scientific Affairs: Current Employment; Johnson & Johnson: Current equity holder in publicly-traded company. Emond: Pharmacyclics LLC, an AbbVie Company: Consultancy; Pfizer: Consultancy; Novartis: Consultancy; Janssen: Consultancy; GlaxoSmithKline: Consultancy. Côté-Sergent: GlaxoSmithKline: Consultancy; Janssen: Consultancy. Hilts: Janssen: Consultancy; GlaxoSmithKline: Consultancy; ViiV: Consultancy; Allergan/Abbvie: Consultancy. Liu: Novartis: Consultancy; uniQure: Consultancy; Servier: Consultancy; Janssen: Consultancy; BioMarin: Consultancy. Lafeuille: GlaxoSmithKline: Consultancy; Janssen Scientific Affairs, LLC: Consultancy; Pfizer: Consultancy; Pharmacyclics: Consultancy. Lefebvre: Pharmacyclics: Consultancy; Otsuka: Consultancy; Novartis: Consultancy; Regeneron: Consultancy; Pfizer: Consultancy; Janssen Scientific Affairs, LLC: Consultancy; GlaxoSmithKline: Consultancy. Huang: Janssen Scientific Affairs, LLC: Current Employment; Johnson & Johnson: Current equity holder in publicly-traded company.

scholarly journals Five Gene Probes Carry Most Of The Discriminatory Power Of The 70-Gene Risk Model In Multiple Myeloma

Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 125-125
Author(s):  
Christoph Heuck ◽  
Pingping Qu ◽  
Frits van Rhee ◽  
Sarah Waheed ◽  
Saad Z Usmani ◽  
...  
Keyword(s):  
High Risk ◽  
Research Funding ◽  
Risk Model ◽  
Progression Free Survival ◽  
Dna Probes ◽  
Low Risk ◽  
Free Survival ◽  
The Us ◽  
Risk Patients ◽  
Total Therapy

Abstract Gene expression profiling (GEP) reliably predicts overall and progression free survival in multiple myeloma. Driven by the concept that therapy will reveal biology, we applied the GEP70 risk model to 56 patients enrolled in Total Therapy 6 (TT6), a phase 2 trial for previously treated patients. One year survival estimates were 62% vs.97%, p<0.0001, Figure 1A). To investigate whether fewer than the 70 genes could predict this difference in outcomes, the probe sets of the GEP70 risk model were ranked by p-values, based on univariate Cox regression analysis for OS. The five probe sets with the smallest P values (corresponding to genes ENO1, FABP5, TRIP13, TAGLN2, and RFC4) were combined to create a continuous score (Figure1B). Association of several of these genes with different cancers has previously been reported by others. We re-trained this 5 gene model (GEP5) on a dataset of 275 uniformly treated patients on Total Therapy 3A (TT3A) and identified a new optimal cutoff of 10.68. We validated this new cutoff with patients enrolled in Total Therapy 2 (TT2) (n=351) and Total Therapy 3B (TT3B) (n=166). For TT2 patients, the dataset from which the GEP70 model was developed, clinical outcomes of the GEP5defined low risk patients were very similar to the GEP70 defined low risk patients. Survival estimates were higher for GEP5-defined high risk than for GEP70 high risk patients (5-year estimated OS: 40%, GEP5; 28%, GEP70; 5-year estimated PFS: 26%, GEP5; 15%, GEP70) (Figure 2A and 2B). This was also seen in both TT2 treatment arms. For the second validation cohort (TT3B), GEP5 and GEP70 risk distinction were similar to the TT3A discovery cohort (Figures 2C and 2D). On multivariate analysis, the GEP5-defined high-risk designation was the most adverse variable for PFS, with an estimated hazard ratio of 3.44 (95% CI: 2.02-5.86), whereas the GEP70 model was selected first for OS. (Table 1).Table 1.Multivariate stepwise Cox regression analysis performed on the TT3B validation setOverall survivalProgression-free survivalVariablen/N (%)HR (95% CI)P-valueHR (95% CI)P-valueMultivariateGEP70 high-risk36/159 (23%)4.45 (2.47, 8.02)<.001B2M > 5.5 mg/L49/159 (31%)1.73 (1.01, 2.95)0.045GEP5 high-risk42/159 (26%)3.44 (2.02, 5.86)<.001 Applied to the publicly available dataset from the HOVON group, GEP5 identified a high risk group with a 3-year estimate OS survival of 52% compared to 75% for the low risk group (p<0.001). TT4 and TT5 are phase 2 trials for previously untreated GEP70 defined low-risk and high-risk patients, respectively. GEP5 identified in TT4 a subset (17/303) of high risk patients with significantly worse 3-year estimated OS (69% vs. 86%, p=0.03), and in TT5 GEP5 identifies a low-risk subset (22/57) of patients with significantly better 3-year estimate OS (94% vs. 59%, p=0.01). Recently a large-scale proteomics experiment involving 85 patients with MM identified ENO1, FABP5, and TAGLN2 among a set of 24 proteins that are associated with short OS. It was further shown that gene expression levels correlated closely with protein abundance. In summary, we have identified 5 genes that have the greatest influence on GEP defined risk. The GEP5 score maintains prognostic power even in patients who have been risk stratified using other risk models. The correlation of expression at both mRNA and protein levels indicate that the genes identified in GEP5 are not simply an artifact of the microarray methodology, but rather supports their biologic relevance. This simplified risk model with a reduced number of genes has the potential to open molecular risk testing to a larger audience. Figure 1. Figure 1. Overall Survival in TT6 according to A) GEP70 risk score and B) GEP5 risk score Figure 2. Figure 2. Overall survival (left panels) and progression-free survival (right panels) according to GEP5 risk score in A) TT3A training set set, B) TT2 test set and C) a second test set TT3B Figure 3. Figure 3. Overall survival (left panels) and progression-free survival (right panels) according to GEP5 in A) the publicly available HOVON dataset B) TT4, for previously untreated GEP70 defined low-risk myeloma and C) TT5, for previously untreated GEP70 defined high-risk myeloma Disclosures: van Rhee: Jansen & Jansen: Research Funding. Usmani:Celgene: Consultancy, Research Funding, Speakers Bureau; Onyx: Research Funding, Speakers Bureau. Epstein:University of Arkansas for Medical Sciences: Co-inventor of the DNA probes for FISH of IGHC/IGHV (14q32), MMSET/FGFR3 (4p16), CCND3 (6p21), CCND1 (11q13), MAF (16q23), and MAFB (20q12) loci, sub. to the US Patent & Trademark Office as Prov. App# 61/726,327: Methods of Detecting 14q32 Translocations, Co-inventor of the DNA probes for FISH of IGHC/IGHV (14q32), MMSET/FGFR3 (4p16), CCND3 (6p21), CCND1 (11q13), MAF (16q23), and MAFB (20q12) loci, sub. to the US Patent & Trademark Office as Prov. App# 61/726,327: Methods of Detecting 14q32 Translocations Patents & Royalties. Zhang:University of Arkansas for Medical Sciences: Co-inventor of the DNA probes for FISH of IGHC/IGHV (14q32), MMSET/FGFR3 (4p16), CCND3 (6p21), CCND1 (11q13), MAF (16q23), and MAFB (20q12) loci, sub. to the US Patent & Trademark Office as Prov. App# 61/726,327: Methods of Detecting 14q32 Translocations, Co-inventor of the DNA probes for FISH of IGHC/IGHV (14q32), MMSET/FGFR3 (4p16), CCND3 (6p21), CCND1 (11q13), MAF (16q23), and MAFB (20q12) loci, sub. to the US Patent & Trademark Office as Prov. App# 61/726,327: Methods of Detecting 14q32 Translocations Patents & Royalties. Barlogie:Celgene: Consultancy, Honoraria, Research Funding; Myeloma Health, LLC: Patents & Royalties.

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