scholarly journals Association between a Polygenic Risk Score for Multiple Myeloma Risk and Overall Survival

Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. 4366-4366
Author(s):  
Alyssa I. Clay-Gilmour ◽  
Michelle Hildebrandt ◽  
Yan Asmann ◽  
Elizabeth E. Brown ◽  
Jonathan N Hofmann ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Overall Survival ◽  
Quality Control ◽  
Risk Score ◽  
Genetic Variants ◽  
Research Funding ◽  
Stage I ◽  
Polygenic Risk Score ◽  
Polygenic Risk

Background Genome-wide association studies (GWAS) conducted in populations of European ancestry (EA) have identified and confirmed 23 germline susceptibility loci for multiple myeloma (MM). The effect sizes of single nucleotide polymorphisms (SNPs) at these loci are small, therefore combining them into a single summary measure, known as a polygenic risk score (PRS), may provide a more meaningful risk factor. We have previously shown a PRS comprised of the 23 SNPs for MM contributes to increased risk of MM, with a 2.7-fold increase for highest vs. lowest PRS quintiles. Whether the MM-PRS is also associated with overall survival (OS) in MM cases has not been evaluated. We examined the association between MM-PRS and OS in two EA studies. Methods The first study consisted of 2,179 EA MM cases from ten studies included in the Multiple Myeloma Working Group within the International Lymphoma Consortium (InterLymph). Cases were diagnosed between 1970 and 2015 and genotyped using multiple platforms (Oncoarray, Affymetrix, Human660W-quad Beadchip, and Illumina arrays); 885 cases also had stage [based on International Staging System (ISS)] available. Each of the GWAS was subjected to rigorous standard quality control independently (prior to imputation via the Michigan imputation server based on the Haplotype Reference Consortium (HRC). The second study consisted of 515 newly diagnosed EA MM cases from CoMMpass (Relating Clinical Outcomes in Multiple Myeloma to Personal Assessment of Genetic Profile), diagnosed from 2011-2013, who had whole genome sequencing (WGS) performed on germline DNA. The WGS data was used to call common germline genetic variants through the Mayo Clinic bioinformatics pipeline. Briefly, genetic variants were detected with GenomeGPS, aligned to the hg19 reference genome, called using the GATK (V3.6) Haplotype Caller, and merged for multiple-sample joint calling. To reduce the false positive variants, variant quality score recalibration (VQSR) was applied for both SNPs and INDELs. After quality control, 458 EA samples remained. Follow-up was available for both studies and consisted of time from MM diagnosis date until death or date of last known follow-up. The PRS was constructed from the 23 MM SNPs using the published per allele odds ratio associated with MM risk. The published log odds ratios for each SNP were multiplied by the number of risk alleles (0, 1, 2) for the corresponding SNP, and summed, resulting in a unique score per person. Kaplan-Meier curves and Cox proportional hazard models were used to assess the association between PRS with MM OS considering two models: 1) adjusted for age, sex, study and 2) additional adjustment by stage (ISS). Hazard ratios (OR) and 95% confidence intervals (CI) were estimated. The PRS was evaluated both as a continuous variable, per standard deviation (SD), and as a categorical variable (quintiles). Results MM cases (N=2,179) in the InterLymph study were 59% male and 41% female and the median age was 61.0 years (26-90 years). Median follow-up time was 57.2 months (1.0-509.0 months) with 868 reported deaths. MM cases with stage information available consisted of 20% stage I (n=178), 53% stage II (n=466), and 27% stage III (n=241). No association was observed between PRS and OS in MM patients regardless of adjustment for stage (continuous PRS (HR: 1.03, 95% CI: 0.83-1.28, P=0.80) or by quintile PRS (p>0.05)) (Table). The CoMMpass EA MM cases (n=458) had similar distributions for sex (61% male and 39% females) but were slightly older 65 years (27-93 years) and had shorter follow-up time (median=39.75 months (0.13-77.2)) with 117 deaths. Stage was available for 96% of CoMMpass cases including 36% stage I (n=159), 33% stage II (n=146), and 31% stage III (n=134). We also observed no association of PRS and OS in the CoMMpass study (HR=1.02, 95% CI: 0.72 -1.46, P= 0.89), adjusted for age, sex, and stage (Table). Discussion A PRS score for MM risk is not associated with OS for MM cases in two EA populations. Given that prior studies have shown association of genetic variation with MM survival, efforts to identify additional loci associated with OS or MM specific survival are warranted. Future studies should also consider germline variants impact on molecular subtypes, specific therapies, and outcomes. Disclosures Kumar: Celgene: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Takeda: Research Funding.

Performance of polygenic risk scores for cancer prediction in an academic biobank.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. 1528-1528
Author(s):  
Heena Desai ◽  
Anh Le ◽  
Ryan Hausler ◽  
Shefali Verma ◽  
Anurag Verma ◽  
...  
Keyword(s):  
Risk Score ◽  
Genetic Variants ◽  
Association Studies ◽  
Risk Scores ◽  
Polygenic Risk Score ◽  
Genome Wide Association Studies ◽  
Polygenic Risk ◽  
European Americans ◽  
Genome Wide ◽  
Common Genetic Variants

1528 Background: The discovery of rare genetic variants associated with cancer have a tremendous impact on reducing cancer morbidity and mortality when identified; however, rare variants are found in less than 5% of cancer patients. Genome wide association studies (GWAS) have identified hundreds of common genetic variants significantly associated with a number of cancers, but the clinical utility of individual variants or a polygenic risk score (PRS) derived from multiple variants is still unclear. Methods: We tested the ability of polygenic risk score (PRS) models developed from genome-wide significant variants to differentiate cases versus controls in the Penn Medicine Biobank. Cases for 15 different cancers and cancer-free controls were identified using electronic health record billing codes for 11,524 European American and 5,994 African American individuals from the Penn Medicine Biobank. Results: The discriminatory ability of the 15 PRS models to distinguish their respective cancer cases versus controls ranged from 0.68-0.79 in European Americans and 0.74-0.93 in African Americans. Seven of the 15 cancer PRS trended towards an association with their cancer at a p<0.05 (Table), and PRS for prostate, thyroid and melanoma were significantly associated with their cancers at a bonferroni corrected p<0.003 with OR 1.3-1.6 in European Americans. Conclusions: Our data demonstrate that common variants with significant associations from GWAS studies can distinguish cancer cases versus controls for some cancers in an unselected biobank population. Given the small effects, future studies are needed to determine how best to incorporate PRS with other risk factors in the precision prediction of cancer risk. [Table: see text]

scholarly journals Corrected QT Interval–Polygenic Risk Score and Its Contribution to Type 1, Type 2, and Type 3 Long-QT Syndrome in Probands and Genotype-Positive Family Members

2020 ◽  
Vol 13 (4) ◽  
Author(s):  
Kari L. Turkowski ◽  
Steven M. Dotzler ◽  
David J. Tester ◽  
John R. Giudicessi ◽  
J. Martijn Bos ◽  
...  
Keyword(s):  
General Population ◽  
Risk Score ◽  
Long Qt Syndrome ◽  
Genetic Variants ◽  
Qt Interval ◽  
Polygenic Risk Score ◽  
Long Qt ◽  
Polygenic Risk ◽  
Corrected Qt Interval ◽  
Qt Syndrome

Background: Long-QT syndrome (LQTS) is characterized by a prolonged heart rate–corrected QT interval (QTc). Genome-wide association studies identified common genetic variants that collectively explain ≈8% to 10% of QTc variation in the general population. Methods: Overall, 423 patients with LQT1, LQT2, or LQT3 were genotyped for 61 QTc-associated genetic variants used in a prototype QTc–polygenic risk score (QTc-PRS). A weighted QTc-PRS (range, 0–154.8 ms) was calculated for each patient, and the FHS (Framingham Heart Study) population-based reference cohort (n=853). Results: The average QTc-PRS in LQTS was 88.0±7.2 and explained only ≈2.0% of the QTc variability. The QTc-PRS in LQTS probands (n=137; 89.3±6.8) was significantly greater than both FHS controls (87.2±7.4, difference-in-means±SE: 2.1±0.7, P <0.002) and LQTS genotype-positive family members (87.5±7.4, difference-in-mean, 1.8±.7, P <0.009). There was no difference in QTc-PRS between symptomatic (n=156, 88.6±7.3) and asymptomatic patients (n=267; 87.7±7.2, difference-in-mean, 0.9±0.7, P=0.15). LQTS patients with a QTc≥480 ms (n=120) had a significantly higher QTc-PRS (89.3±6.7) than patients with a QTc<480 ms (n=303, 87.6±7.4, difference-in-mean, 1.7±0.8, P <0.05). There was no difference in QTc-PRS or QTc between genotypes. Conclusions: The QTc-PRS explained <2% of the QTc variability in our LQT1, LQT2, and LQT3 cohort, contributing 5× less to their QTc value than in the general population. This prototype QTc-PRS does not distinguish/predict the clinical outcomes of individuals with LQTS.

EBMT Risk Score for Pre Transplant Risk Assessment in Patients with Multiple Myeloma.

Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 3094-3094 ◽  
Author(s):  
Zartash Gul ◽  
Hasan Khan ◽  
Qaiser Bashir ◽  
Nina Shah ◽  
Simrit Parmar ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Bone Marrow ◽  
Board Of Directors ◽  
Risk Score ◽  
Cumulative Incidence ◽  
Research Funding ◽  
Advisory Committees ◽  
All Cause Mortality ◽  
Response Status

Abstract Abstract 3094 Background: Allogeneic hematopoietic stem cell transplantation (allo-HCT) is a potentially curative treatment for patients with multiple myeloma (MM) but its use is limited by high non-relapse mortality (NRM). European Group for Bone Marrow transplant (EBMT) risk score is a validated predictor of outcome for patients undergoing allo-HCT for hematological malignancies. It takes into consideration patient's age, donor's gender and type, disease status and the interval from diagnosis to allo-HCT, with the score ranging from 0 to 7. We assessed the impact of EBMT risk score in MM patients undergoing allo-HCT. Methods: A total of 189 patients with MM who underwent HSCT between November 1985 and June 2010 at MD Anderson Cancer Center were included in the analysis. Results: Patient characteristics are summarized in Table 1. There were 110 males (58%) and 79 females (42%) with a mean age of 50 years (range 28–70). Donors were related in 146 patients (HLA-identical=131, 1 antigen mismatched (AGMM) = 5, 2 AGMM =1, 3AGMM=1, syngeneic=8) and unrelated in 43 patients (HLA identical= 37, 1AGMM=4, 2AGMM=1, unknown=1). One-hundred and twelve patients had prior autologous transplants (auto-HCT). Of these 83 had 1, 28 had 2 and 1 had 3 prior auto-HCT, respectively. Median time from diagnosis to allo-HCT was 24.7 months (range 3.3–232) and median overall follow up was 13 months (0.2–266). Overall 94 patients (49%) had progressed before last follow-up. Incidence of all-cause mortality was 138 (73.4%) with 69 (36%) of all deaths attributed to NRM. KM estimates of 2-year PFS and OS were 25% and 42%, and 5-year PFS and OS were 16% and 27%, respectively. Cumulative incidence (CI) of grade 2–4 and grade 3–4 acute graft versus host disease (aGVHD) was 33% and 13%, respectively. Cumulative incidence of overall and extensive chronic GVHD (cGVHD) was 47% and 17%, respectively. EBMT risk score was, 0–3 for 41 (21.7%), 4 for 72 (38.1%) 4 and 5–7 for 76 (40.2%) patients. EBMT risk score was higher for males, African-Americans and older allo-HCT recipients, patients with higher LDH levels (>618mg/dl), ß2-microglobulin >3.5mg/dl and patients with bone marrow plasmacytosis. Median PFS in patients with EBMT scores 0–3, 4 and 5–7 were 10.1, 8.4 and 6.4 months, respectively (P=0.0036). Median OS in patients with EBMT scores 0–3, 4 and 5–7 were 39, 15.8 and 9.6 months, respectively (p=0.001). Cumulative NRM in patients with EBMT scores 0–3, 4 and 5–7 were 37% (15/41), 36.1% (26/72) and 37.3% (28/75), respectively (p= 0.234). Cumulative incidence of progression in patients with EBMT scores 0–3, 4 and 5–7 were 36.5% (15/41), 50% (36/72) and 56.5% (43/76), p=0.119. Compared to those with EBMT risk score (0–3), individuals with EBMT risk scores >5 had a higher risk of all-cause mortality (HR 2.34, 95% CI 1.44–3.80), and disease progression (HR 3.06, 95% CI 1.67–5.61). Addition of ß2-microglobulin, BM plasma cells or prior response status alone or in combination with EBMT risk score significantly improved the discrimination properties of the model containing EBMT score alone (p<0.05). Conclusions: EBMT risk score is an independent predictor of survival in MM patients undergoing allo-HCT. Addition of myeloma-specific factors predictors (ß2-microglobulin, plasma cell infiltration and prior response status) to EBMT score significantly improves its prognostic impact. Disclosures: Giralt: Millenium: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Onyx: Membership on an entity's Board of Directors or advisory committees, Research Funding.

scholarly journals A polygenic risk score for multiple myeloma risk prediction

2021 ◽  
Author(s):  
Federico Canzian ◽  
Chiara Piredda ◽  
Angelica Macauda ◽  
Daria Zawirska ◽  
Niels Frost Andersen ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Risk Score ◽  
Association Studies ◽  
Polygenic Risk Score ◽  
Genome Wide Association Studies ◽  
Polygenic Risk ◽  
Epidemiologic Evidence ◽  
Risk Variants ◽  
Genome Wide ◽  
Weighted Score

AbstractThere is overwhelming epidemiologic evidence that the risk of multiple myeloma (MM) has a solid genetic background. Genome-wide association studies (GWAS) have identified 23 risk loci that contribute to the genetic susceptibility of MM, but have low individual penetrance. Combining the SNPs in a polygenic risk score (PRS) is a possible approach to improve their usefulness. Using 2361 MM cases and 1415 controls from the International Multiple Myeloma rESEarch (IMMEnSE) consortium, we computed a weighted and an unweighted PRS. We observed associations with MM risk with OR = 3.44, 95% CI 2.53–4.69, p = 3.55 × 10−15 for the highest vs. lowest quintile of the weighted score, and OR = 3.18, 95% CI 2.1 = 34–4.33, p = 1.62 × 10−13 for the highest vs. lowest quintile of the unweighted score. We found a convincing association of a PRS generated with 23 SNPs and risk of MM. Our work provides additional validation of previously discovered MM risk variants and of their combination into a PRS, which is a first step towards the use of genetics for risk stratification in the general population.

scholarly journals Updated Results of a Phase 2 Study of Modified Lenalidomide, Bortezomib, and Dexamethasone (RVd-lite) in Transplant-Ineligible Multiple Myeloma

Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. 3178-3178 ◽  
Author(s):  
Elizabeth K. O'Donnell ◽  
Jacob P. Laubach ◽  
Andrew J. Yee ◽  
Robert Redd ◽  
Carol Ann Huff ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Overall Survival ◽  
Board Of Directors ◽  
Research Funding ◽  
Advisory Board ◽  
Future Perspective ◽  
Low Grade ◽  
Advisory Committees ◽  
Grade 3

PURPOSE: This updated analysis examined survival outcomes after 60 months of follow-up in patients with transplant-ineligible newly diagnosed multiple myeloma (NDMM) treated with the 3-drug regimen of modified lenalidomide-bortezomib-dexamethasone (RVD lite) in this population. METHODS: RVD lite was administered over a 35-day cycle. Lenalidomide 15 mg was given orally days 1-21; bortezomib 1.3 mg/m2 once weekly subcutaneously (SC) on days 1, 8, 15, and 22; dexamethasone 20 mg orally day of and after bortezomib for 9 cycles followed by 6 cycles of consolidation. Eligibility requirements included ECOG performance status ≤ 2 and acceptable hepatic, renal, and hematologic function. Primary objective was to evaluate overall response rate (ORR). Secondary objectives included evaluation of safety, progression free survival (PFS), overall survival (OS), and the pharmacokinetic (PK) profile of intravenous (IV) and SC bortezomib. RESULTS: Fifty-three eligible patients enrolled between 4/17/13 and 7/25/15; 50 received at least one dose of therapy. As previously reported, the median age at study entry was 72 years (range 65-91). ISS stage was I in 19 (38%), II in 17 (34%), and III in 14 (28%) pts. Fatigue was the most commonly reported toxicity occurring in 37 (74%) and was mostly grade 1 or 2 in 29 (58%). Other grade 3 or greater toxicities included hypophosphatemia in 17 (34%), neutropenia in 7 (14%), and rash in 5 (10%) pts. Low grade peripheral neuropathy was reported in 31 (62%) patients with only 1 patient experiencing grade 3 symptoms. There were statistically significant improvements in scores of physical functioning (p=0.013), future perspective (p=0.023) and disease symptoms (p=0.001). Patients reported fewer symptoms across all symptom domains with the exception of diarrhea. The ORR was 86% and 66% of patients achieved a very good partial response (VGPR) or better. The median time to response was 1.1 months. At a follow-up of 61 months, median PFS was 41.9 months (95% CI, 31.2 - ∞) and median OS not reached. The 5-year overall survival was 61.3%. Sixty-six percent of patients received lenalidomide maintenance. CONCLUSIONS: RVD lite is a well-tolerated and highly effective regimen in the transplant-ineligible population with robust PFS and OS. Our data demonstrate that the benefits of more effective combination strategies observed in younger, fitter, transplant-eligible patients can be effectively used in older, transplant-ineligible patients with modifications in dose and schedule, without compromising efficacy. Disclosures O'Donnell: Celgene: Consultancy; Sanofi: Consultancy; BMS: Consultancy; Takeda: Consultancy; Amgen: Consultancy. Yee:Takeda: Consultancy; Celgene: Consultancy, Honoraria, Research Funding; Adaptive: Consultancy; Karyopharm: Consultancy; Bristol-Myers Squibb: Consultancy, Research Funding; Amgen: Consultancy, Honoraria. Huff:Karyopharm, Sanofi, MiDiagnostics: Consultancy; Member of Safety Monitoring Board for Johnson and Johnson: Membership on an entity's Board of Directors or advisory committees. Schlossman:Millennium Pharmaceuticals, Inc., a wholly owned subsidiary of Takeda Pharmaceutical Company Limited: Employment. Munshi:Celgene: Consultancy; Takeda: Consultancy; Abbvie: Consultancy; Janssen: Consultancy; Adaptive: Consultancy; Amgen: Consultancy; Oncopep: Consultancy. Anderson:Gilead Sciences: Other: Advisory Board; Janssen: Other: Advisory Board; Sanofi-Aventis: Other: Advisory Board; OncoPep: Other: Scientific founder ; C4 Therapeutics: Other: Scientific founder . Richardson:Bristol-Myers Squibb: Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; Karyopharm: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Sanofi: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Oncopeptides: Membership on an entity's Board of Directors or advisory committees, Research Funding. Raje:Merck: Consultancy; Janssen: Consultancy; Takeda: Consultancy; Celgene Corporation: Consultancy; Amgen Inc.: Consultancy; Bristol-Myers Squibb: Consultancy.

scholarly journals Predictors of Overall Survival for Multiple Myeloma Patients Depending on Transplant Status According to a Retrospective, Non-Interventional Study in Norway

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 5759-5759
Author(s):  
Fredrik H. Schjesvold ◽  
Anderson Jenna ◽  
Jaak Sõnajalg ◽  
Amy Leval ◽  
Anna Lysén ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Overall Survival ◽  
Renal Impairment ◽  
Research Funding ◽  
Age Group ◽  
Interventional Study ◽  
Cox Models ◽  
Risk Of Death ◽  
Transplant Patients

Abstract Introduction Multiple myeloma (MM) is the second most common hematological malignancy in Europe and the US. The median survival after diagnosis is approximately 4-5 years (Röllig et al The Lancet 2015), with recent improvement observed in younger (Kyle et al Expert Rev Hematol 2014) and older patients (Kumar et al Leukemia 2013). The improvement in outcomes of MM patients is largely due to the introduction of autologous stem cell transplant (ASCT) and novel treatments including proteasome inhibitors and immunomodulators. Norwegian guidelines state that the preferred frontline treatment for MM patients under 65-70 years old is ASCT, but this option may be limited by comorbidity. Here, we report results from a retrospective, non-interventional study using data collected at the MM registry at Oslo University Hospital (OUS), Norway. The aim was to describe patient and disease characteristics, overall survival (OS), and potential predictors of death for the study population in Norway. Methods The study period was from 1 Jan 2008 to 31 Dec 2015. Patients (n=169) aged 18 years or older at MM diagnosis and who were treated at OUS (ASCT or not) or in 1 of 5 regional hospitals (ASCT only, with ASCT received at OUS and other treatments received locally), during the study period, were included. Study entry was defined as date of MM diagnosis and follow-up started from study entry. End of follow-up occurred at the first of: end of study period, loss to follow-up, or death. Variables used were part of routine practice. Descriptive analysis was done at diagnosis for the overall population, for patients who received ASCT (n=100), and for those who did not receive ASCT at any time during the study period (n=69). At treatment line 1, Cox models were used to identify potential predictors for OS. Results In the study, 55.6% of patients were diagnosed with MM at OUS and 25 of those patients (14.8% of total population) received ASCT. Patients who did not receive ASCT were older and included a larger percentage of women than in the transplant cohort (mean age non-ASCT 73.1±11.2 with 55.1% women and for ASCT 55.5±6.7 years with 45.0% women). More MM patients were diagnosed with Bence Jones (BJ) (21.9% of patients) or IgG type myeloma (54.4% of patients) than IgA type (20.1% of patients) (Table 1). Of transplant patients, more were of International Staging System (ISS) stage I or stage II than stage III MM, though 35.0% of patients were of unknown stage. Most non-transplant patients had unknown ISS stage, followed by stages II and III and the least number of patients were of stage I. Of the CRAB symptoms at diagnosis, most ASCT patients showed no hypercalcemia (80.0%), no renal impairment (90.0%), or no anemia (68.0%), and 34.0% presented with skeletal destruction (Table 1). Similarly, most non-transplant patients had no hypercalcemia (87.0%) and no renal impairment (79.7%) at diagnosis. Anemia and skeletal destruction were not measured in 24.6% of non-transplant patients. Of those with recorded results, more non-transplant patients had skeletal destruction than not and approximately the same number of non-transplant patients presented with anemia than not. High-risk cytogenic abnormalities, a criterion of the revised (R)-ISS, was unknown for most patients (80.5%). Median OS from start of treatment line 1 was 75.93 (90% confidence interval (CI): 68.23 to not reached) months for transplant patients and 34.20 (90% CI: 25.57-42.16) months for non-transplant patients. Variables including age group, sex, CRAB symptoms at diagnosis, type of first therapy, and type of MM at diagnosis were included in the Cox models per cohort, if they had a missingness of <20%. Hypercalcemia at diagnosis was a significant predictor for OS for the transplant cohort, while anemia at diagnosis gave a decreased risk of death. Hypercalcemia as well belonging to the older age groups (e.g., 61-70 years and 71-80 years) were significant predictors of death for the non-transplant patients (Table 2). Conclusions For MM patients in Norway, overall survival was much greater for patients receiving transplant in the first line. Hypercalcemia at diagnosis predicted death for both transplant and non-transplant cohorts and anemia at diagnosis was identified as a decreased risk of death for transplant patients, but not well-recorded for non-transplant patients. Belonging to an older age group (>71 or 80 years old) also was a significant predictor of death, but only for non-transplant patients. Disclosures Schjesvold: Oncopeptides: Consultancy; Celgene: Consultancy, Honoraria; Bristol Myers Squibb: Consultancy; Takeda: Consultancy, Honoraria; Bayer: Consultancy; Amgen: Consultancy, Honoraria, Research Funding; Adaptive: Consultancy; Janssen: Consultancy, Honoraria, Research Funding; Abbvie: Honoraria; Novartis: Honoraria. Jenna:Janssen-Cilag: Other: Employee of StatFinn & EPID Research, contracted by Janssen-Cilag. Sõnajalg:Janssen-Cilag: Other: Employee of StatFinn & EPID Research, contracted by Janssen-Cilag. Leval:Janssen-Cilag: Employment. Rana:Janssen-Cilag: Employment. Castren-Kortekangas:Janssen-Cilag: Employment. Borgsten:Janssen-Cilag: Employment.

scholarly journals Changes in Uninvolved Immunoglobulins during Multiple Myeloma Therapy

Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 3251-3251
Author(s):  
Praful Ravi ◽  
Shaji Kumar ◽  
Wilson I Gonsalves ◽  
Francis K Buadi ◽  
Martha Q. Lacy ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Overall Survival ◽  
Treatment Response ◽  
Board Of Directors ◽  
Light Chain ◽  
Research Funding ◽  
Advisory Committees ◽  
Percentage Difference ◽  
Lower Likelihood

Abstract Background Suppression of uninvolved immunoglobulins is a common finding in multiple myeloma and the preservation of uninvolved immunoglobulins at diagnosis is associated with improved progression-free and overall survival. However, little is known about the impact of myeloma treatment on levels of uninvolved immunoglobulins, and the link between changes in uninvolved immunoglobulins during therapy and treatment response, disease progression and survival. Methods We identified patients who received therapy for newly diagnosed multiple myeloma at our institution between 2001 and 2014, and who had data available on absolute lymphocyte count (ALC) and quantitative uninvolved immunoglobulins (Ig) before commencing treatment. The ALC and levels of uninvolved Ig after 4 cycles of therapy were abstracted from the electronic medical record; patients who switched or stopped treatment, or died, before this time point were excluded. To assess change in ALC, the percentage difference in ALC between baseline and 4 cycles was calculated; for uninvolved Ig, the average of the percentage difference between baseline and 4 cycles for each uninvolved Ig (IgA and IgM for IgG myeloma, IgG and IgM for IgA myeloma, IgG and IgA for IgM and IgD myeloma, and IgG, IgM and IgA for light-chain only myeloma) was calculated. Treatment response at 4 cycles was retrospectively assigned according to International Myeloma Working Group criteria. Time to treatment failure (TTF) was defined as time from start of initial therapy to start of next line of therapy or death (if no additional treatment was received). A landmark analysis was used to calculate overall survival (OS) from the date of follow-up after 4 cycles of therapy. The Kruskal-Wallis, Chi-Square, and log rank tests were used to detect differences in medians, proportions, and survival times respectively. Results A total of 421 patients were included in this analysis. The median age was 63 years (range 33-91), 254 patients (60.3%) were male and median follow-up was 6.5 years (95% CI 5.6-7.3); the vast majority of patients had IgG (n=247 [58.7%]), IgA (n=98 [23.3%]) or light-chain only myeloma (n=68 [16.2%]). First line therapy comprised of pulse-dose dexamethasone (DEX, n=92 [21.9%]), lenalidomide-dexamethasone (RD, n=176 [41.8%]), bortezomib-dexamethasone (VD, n=22 [5.2%]), bortezomib-cyclophosphamide-dexamethasone (VCD, n=84 [20.0%]), and bortezomib-lenalidomide-dexamethasone (VRD, n=47 [11.2%]). Across the entire cohort, the median change in ALC and uninvolved Ig after 4 cycles of treatment was -11.0% (range: -92.7 to +718.8) and +9.0% (-77.7 to +1094.4) respectively; treatment with VCD was associated with the greatest median declines in ALC (DEX: -0.1%; RD: -9.9%; VD: -20.8%; VCD: -40.9%; VRD: -15.3%) and uninvolved Ig (DEX: -0.5%; RD: +15.5%; VD: +44.0%; VCD: -14.0%; VRD: +76.0%, both p<0.001). Conversion from suppression to normalization of the primary uninvolved Ig (IgA in IgG myeloma, and IgG in all other myeloma types) after 4 cycles was seen more frequently with the use of RD (13.1%) and VRD (12.8%) compared to DEX (4.7%), VCD (1.3%), or VD (4.8%), χ2=21.8, p=0.040. When considering only patients in whom the primary uninvolved Ig remained suppressed between baseline and 4 cycles, a ≥25% reduction in the primary uninvolved Ig occurred more frequently with the use of DEX (51.5%) and VCD (34.5%) compared to RD (24.8%), VD (23.5%) or VRD (25.7%), χ2=15.1, p=0.005 (Table 1). Although an average reduction in uninvolved Ig between baseline and 4 cycles (ΔIg<0) was independently associated with a lower likelihood of achieving very good partial response (VGPR) of better on multivariate analysis adjusting for age, sex and treatment regimen (OR=0.40 [0.24-0.63], p<0.001), there were no differences in TTF (2.0yrs vs. 2.0yrs, p=0.783) or OS (8.0yrs vs. 8.0yrs, p=0.721) between patients with ΔIg<0 (n=169) and those with ΔIg≥0 (n=222). Conclusions Myeloma treatments produce differential impacts on immune parameters, with VCD causing the greatest reduction in lymphocytes and uninvolved Ig, implying general targeting of plasma cells, in comparison to lenalidomide, which appeared to be more tumor-specific with relative sparing of lymphocytes and uninvolved Ig. While an average decrease in uninvolved Ig was an independent predictor of a lower likelihood of achieving VGPR or better after 4 cycles of therapy, it was not associated with a shorter TTF or poorer OS. Disclosures Kumar: BMS: Consultancy; Glycomimetics: Consultancy; Onyx: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Kesios: Consultancy; Millennium: Consultancy, Research Funding; Noxxon Pharma: Consultancy, Research Funding; Array BioPharma: Consultancy, Research Funding; Skyline: Honoraria, Membership on an entity's Board of Directors or advisory committees; Sanofi: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; AbbVie: Research Funding. Dispenzieri:GSK: Membership on an entity's Board of Directors or advisory committees; Prothena: Membership on an entity's Board of Directors or advisory committees; pfizer: Research Funding; Jannsen: Research Funding; Alnylam: Research Funding; Celgene: Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding. Kapoor:Amgen: Research Funding; Celgene: Research Funding; Takeda: Research Funding. Bergsagel:Amgen, BMS, Novartis, Incyte: Consultancy; Novartis: Research Funding.

Abstract 16685: Shared Genetic Pathways Contribute to Risk of Hypertrophic and Dilated Cardiomyopathies With Opposite Directions of Effect

Circulation ◽  
2020 ◽  
Vol 142 (Suppl_3) ◽  
Author(s):  
Rafik Tadros ◽  
Catherine Francis ◽  
Xiao Xu ◽  
Alexa M Vermeer ◽  
Andrew R Harper ◽  
...  
Keyword(s):  
Risk Score ◽  
Genetic Variants ◽  
Rare Variants ◽  
Genetic Correlations ◽  
Left Ventricular ◽  
Polygenic Risk Score ◽  
Polygenic Risk ◽  
Clinical Events ◽  
Mutation Carriers ◽  
Common Genetic Variants

Introduction: Hypertrophic (HCM) and dilated (DCM) cardiomyopathies are leading causes of sudden death and heart failure requiring transplantation in young individuals. While some cases have a monogenic underlying cause, the majority remain unexplained. Objective: To better understand the contribution of common genetic variants in susceptibility and severity of cardiomyopathy. Methods: We conducted three genome-wide association studies (GWAS) and multi-trait analyses in European-ancestry individuals, including a HCM (1,733 cases) and DCM meta-analyses (5,521 cases), and a GWAS of 9 left ventricular (LV) traits in 19,260 healthy participants from the UK Biobank that underwent cardiac magnetic resonance imaging. We investigated genetic correlations between LV traits, HCM and DCM using LD score regression. We used two-sample mendelian randomization (MR) to assess the causal relationship of increased LV contractility with HCM risk. Lastly, we derived a polygenic risk score and assessed whether it modulates maximal LV wall thickness (maxLVWT) and clinical events in 368 sarcomeric mutation carriers, using linear and Cox mixed effects models, respectively. Results: We identified 16 genetic loci (15 novel) associated with HCM, 13 loci (7 novel) associated with DCM, and 23 loci associated with LV traits. We showed strong genetic correlations between LV volumes and contractility traits in the general population and cardiomyopathies, with opposing effects in HCM and DCM. Using MR, we demonstrated a causal association linking increased LV contractility with HCM risk and estimated that each unit (1%) increase in LV ejection fraction increases the risk of HCM by 37% (95% CI 10%-69%, P=0.004). Lastly, a polygenic risk score (PRS HCM ) derived from the HCM GWAS was associated with maxLVWT (P=0.0001) and clinical events (P=0.009) in carriers of HCM-causing rare variants. Conclusion: Our findings highlight the contribution of common genetic variants in susceptibility for HCM and DCM, and in severity in sarcomeric mutation carriers. Our data also point to increased LV contractility as an important mechanism of HCM independently of sarcomere activating rare variants, and highlight the potential clinical relevance of PRS for risk stratification in HCM.

Analysis of 179 Patients with Newly Diagnosed Multiple Myeloma (MM) Treated with Novel Agents Followed by Autologous Stem Cell Transplantation (ASCT): a Retrospective Study

Blood ◽  
2010 ◽  
Vol 116 (21) ◽  
pp. 1343-1343
Author(s):  
Joyce Habib ◽  
Neil Dunavin ◽  
Gary Phillips ◽  
Patrick Elder ◽  
Meaghan Tranovich ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Overall Survival ◽  
High Risk ◽  
Research Funding ◽  
Progression Free Survival ◽  
Novel Agents ◽  
Genetic Profile ◽  
Newly Diagnosed ◽  
Free Survival

Abstract Abstract 1343 Background: Multiple myeloma (MM) is the second most common hematological malignancy in the United States with an estimated 20,580 new cases in 2009. Over the past decade, the introduction of novel agents (thalidomide, lenalidomide and bortezomib) have played a pivotal role in improving response rates, duration of response, overall survival (OS) and quality of life. In this study we describe a single center experience with novel agents used for induction followed by high dose chemotherapy (HDT) and first autologous stem cell transplant (ASCT) in patients with MM. Method: A retrospective review of the medical records of 179 newly diagnosed patients with MM seen between October 2006 and December 2009 at The Ohio State University was performed. All patients received novel therapy containing thalidomide, bortezomib or lenalidomide as part of an induction regimen followed by ASCT. All patients received melphalan 140mg/m2 or 200mg/m2 as preparative regimen. Kaplan-Meier estimates were used to plot progression free survival and overall survival. Results: Of the 181 patients seen, 2 were excluded because they did not receive a novel agent as part of induction treatment. Of the 179 patients analyzed, median age was 56.8 years (29-80) with 30% of patients older than 60 years. African American represented 19%. Fifty-nine percent were male, 80% had Durie-Salmon (DS) stage III while 25%, 28%, 18% represented International prognostic score (IPS) stage I, II, and III respectively with 27% unknown. Median comorbidity index score was 2 (2-7) and median Karnofsky performance score (KPS) was 90% (70-100). Thirty percent had high risk genetic profile, and 73% received one line of treatment before ASCT. The median time from diagnosis to ASCT was 8.33 months (4-58). The overall response rate (ORR) prior to transplant was 84% (9% complete (CR), 29% very good partial (VGPR), and 46% partial (PR)). The ORR post ASCT was 89% (CR 45%, VGPR 22%, PR 21%). Non relapse mortality was 1% and 3% at 100 days and 1 year respectively. At a median follow up of 31 months (7-90), 69 patients (38%) had relapsed. Median progression free survival (PFS) was 29 months with 1 and 3 years PFS of 79.3% and 61.5% respectively (Fig. 1). The OS was not reached. One and 3 years OS were 93% and 88% respectively (Fig. 1). Univariate analysis showed that time to transplant > 12 months was associated with poor outcome and decreased overall survival (HR 3.30, p = 0.008). High risk genetic profile was also found to be associated with decreased overall survival although this was not statistically significant (HR 2.31, p = 0.070). Multivariate analysis found that only time to transplant > 12 months was an independent predictor of decreased OS. Significant predictors for disease progression were high risk genetic profile and time to transplant > 12 months in patients receiving 2 or more treatments before ASCT. Conclusion: Induction with novel agents followed by HDT and ASCT improves CR rate, in our case from 9% to 45%. Median PFS (29 months) was comparable to other published data. OS was not been reached after a median follow up of 31 months. Predictors of progression include high risk genetic profile and time to transplant > 12 months. The only significant predictor for survival was time to transplant. Our study suggests that an early transplant may improve OS and PFS. An extended analysis will be presented at the meeting. Disclosures: Phillips: NCI/NIH: Research Funding; NCCM Grant: Research Funding; ARRA RC2 Grant: Research Funding. Byrd:Genzyme Corporation: Research Funding.

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