Analysis Of Myeloma Research Articles

Heteroscedasticity-Adjusted Ranking and Thresholding for Large-Scale Multiple Testing

Standardization has been a widely adopted practice in multiple testing, for it takes into account the variability in sampling and makes the test statistics comparable across different study units. However, despite conventional wisdom to the contrary, we show that there can be a significant loss in information from basing hypothesis tests on standardized statistics rather than the full data. We develop a new class of heteroscedasticity-adjusted ranking and thresholding (HART) rules that aim to improve existing methods by simultaneously exploiting commonalities and adjusting heterogeneities among the study units. The main idea of HART is to bypass standardization by directly incorporating both the summary statistic and its variance into the testing procedure. A key message is that the variance structure of the alternative distribution, which is subsumed under standardized statistics, is highly informative and can be exploited to achieve higher power. The proposed HART procedure is shown to be asymptotically valid and optimal for false discovery rate (FDR) control. Our simulation results demonstrate that HART achieves substantial power gain over existing methods at the same FDR level. We illustrate the implementation through a microarray analysis of myeloma.

1025P - The cost-effectiveness of combination therapy: Challenges of the present, solutions for the future? A myeloma analysis

The number of treatments for cancer has increased over recent years. Monotherapy for some malignancies delivers only marginal benefit, whilst combination therapy (CT) improves results by using synergistic mechanisms of action. CT increases treatment cost however, and in an era of health care constrained by cost-containment, national reimbursement of CT conditional on cost-effectiveness is challenging. This research assesses drivers of CT cost-effectiveness, using myeloma as an example, to inform approaches to evidence based approaches to reimbursement. A 3-state cost-effectiveness model (pre-progression; post-progression; dead) for front-line treatment of myeloma was developed. Continuous lenalidomide + dexamethasone (Ld) data were extracted from published results and, using parametric modelling, extrapolated to 20 years, with costs based on UK prices. Add-on drug X was assumed to deliver survival benefit (PFS HR = 0.7; OS HR = 0.7), be dosed Q4W until disease progression, and cost £2,000/dose. Post-progression costs were £4,000/month. Scenario analyses considering differing evidence and treatment approaches included: improved PFS and OS; reduced dosing schedules; limited treatment duration; use as a doublet (i.e. Xd); reduced Drug X cost. Combination therapy XLd compared with Xd resulted in a base-case incremental cost-effectiveness ratio (ICER) of £111K/quality-adjusted life year (QALY). Scenario analysis representing 28.5% improvement in both PFS (ICER = £131K/QALY) and OS (ICER = £96K/QALY) did not substantially improve CE. In contrast, scenarios which induced substantial cost savings improved CE (X dosed Q8W, ICER = £69K/QALY; X cost = £1000/dose, ICER = £64k/QALY; halved Ld dosing, ICER = £8K/QALY; 24-month treatment cap, ICER = -£89K/QALY; doublet, ICER = -£96k/QALY). Clinical trials assess clinical outcomes, however these results suggest clinical outcomes alone may be insufficient to establish CT cost-effectiveness in myeloma. Pursuit of economic benefit beyond clinical outcomes, including resource-sparing approaches to treatment, may mitigate this risk and facilitate national reimbursement, and should therefore be considered in clinical trial design.

Clonal Evolution Paths Significantly Impact the Outcome of Myeloma

BackgroundMultiple myeloma is a malignancy of clone plasma cells that were composed of various multisteps development and had different molecular genetical variation in different phases in the course of disease. Clonal evolution promotes the disease development from prophase to advanced stage. We investigated the paths of clonal evolution in a cohort myeloma patients by a unique multicolor FISH (mFISH) to identify the clonal architecture of different time points, and first reported the survival and prognostic value of various clonal evolution paths.MethodsTotally 85 myeloma patients with CD138+ cells at diagnosis versous relapse or former relapse versous latter relapse were enrolled in this study between January 2004 and December 2014. Firstly, the clonal evolution were analyzed by conventional iFISH (cFISH) with a panel probes of 1q21, RB-1 and TP53. The clonal architecture of different time points were detected by mFISH in 62 samples from different time points of selected 25 patients among the 85 patients. The survival significance and prognostic value of 3 different clonal evolution paths identified by mFISH were analyzed.Results: 1). Clonal evolution were detected in 34/85(40%) cases by cFISH analysis. The survival analysis showed that patients with clonal evolution had significant shorter over survival (OS) than those with clonal stabilization. The meadian OS of these 2 groups were 42.67 (95% CI:32.15-53.19) and 71.46 (95%CI:58.99-83.93) months respectively, the difference between these 2 groups was significant (p=0.010). Comparing the survival since post relapse/clonal evolution, significant difference (p=0.003) also existed in these 2 groups with a median survival of 14.79 (95% CI:10.01-19.56) months and 37.61 (95%CI:27.30-47.92) months respectively.2). Three clonal evolution paths were identified by mFISH in different phase samples from 25 myeloma patients. 36% (9/25) of them were clonal stabilization, 32% (8/25) were linear clonal evolution, 32% (8/25) were branching clonal evolution. mFISH had more powerful efficacy of clonal evolution detection than cFISH. Of these 25 cases, 14 cases were clonal stabilization and 11 were clonal evolution identified by cFISH. 7/14 (50%) with clonal stabilization by cFISH were identified into clonal evolution by mFISH, 1 with linear evolution and 6 with branching evolution. The 11 cases with clonal evolution identified by cFISH were further classified into 7 with linear evolution and 4 with branching evolution by mFISH detection.3). Our results indicated that clonal evolution type had significant impact on survival of myeloma patients. The median OS of patients with clonal stabilization, linear evolution and branching evolution were 87.00 (95%CI:74.53-99.47), 24.99 (95% CI:16.58-33.39) and 35.70 (95% CI:27.10-44.30) months respectively. There were significant difference among these 3 groups (p=0.004). The median survival post relapse/clonal evolution in these 3 groups were 34.00 (95%CI:20.14-47.86), 8.06 (95% CI:4.91-11.22) and 22.75 (95% CI:13.49-32.01) months, the difference among them was significant (p=0.007).ConclusionsmFISH is a simple and clinical practicable tool for clonal detection and analysis of myeloma. Our results firstly demonstrated that the clonal evolution type had significant impact on survival of patients with myeloma. According to the 3 different clonal evolution paths, individualized treatment strategy would be required for different patients with myeloma. DisclosuresNo relevant conflicts of interest to declare.

Updated survivals and prognostic factor analysis in myeloma treated by a staged approach use of bortezomib/thalidomide/dexamethasone in transplant eligible patients

BackgroundBortezomib, an NFkB inhibitor, is an active agent for the treatment of myeloma (MM). We have reported a promising complete remission (CR) rate for newly diagnosed myeloma patients treated by a staged approach, in which chemosensitive patients underwent autologous haematopoietic stem cell transplantation (auto-HSCT) while less chemosensitive patients received salvage therapy with bortezomib/thalidomide/dexamethasone prior to auto-HSCT.MethodsHerein, with an additional 13 months of follow-up, we reported the updated survivals, and examined potential prognostic factors impacting event-free (EFS) and overall survival (OS).ResultsWith a median follow-up of 30 months, the projected OS was 73% and EFS was 50.2%. Age, gender, clinical stage and DAPK methylation could not account for the differential chemosensitivity. Advanced ISS stage and DAPK methylation adversely impacted OS whereas oligoclonal reconstitution predicted superior EFS.ConclusionsOur staged approach illustrated an economical use of expensive targeted agents while preserving a good CR rate and OS. The comparable survivals of chemosensitive and less chemosensitive patients suggested the staged approach might have abolished the adverse prognostic impact of suboptimal chemosensitivity. Finally, the adverse impact of DAPK methylation and favorable impact of oligoclonal reconstitution in myeloma warrants further study.

Variation in DNA repair genes XRCC3, XRCC4, XRCC5 and susceptibility to myeloma

Cytogenetic analysis in myeloma reveals marked chromosomal instability. Both widespread genomic alterations and evidence of aberrant class switch recombination, the physiological process that regulates maturation of the antibody response, implicate the DNA repair pathway in disease pathogenesis. We therefore assessed 27 SNPs in three genes (XRCC3, XRCC4 and XRCC5) central to DNA repair in patients with myeloma and controls from the EpiLymph study and from an Irish hospital registry (n = 306 cases, 263 controls). For the haplotype-tagging SNP (htSNP) rs963248 in XRCC4, Allele A was significantly more frequent in cases than in controls (86.4 versus 80.8%; odds ratio 1.51; 95% confidence interval 1.10-2.08; P = 0.0133), as was the AA genotype (74 versus 65%) (P = 0.026). Haplotype analysis was performed using Unphased for rs963248 in combination with additional SNPs in XRCC4. The strongest evidence of association came from the A-T haplotype from rs963248-rs2891980 (P = 0.008). For XRCC5, the genotype GG from rs1051685 was detected in 10 cases from different national populations but in only one control (P = 0.015). This SNP is located in the 3'-UTR of XRCC5. Overall, these data provide support for the hypothesis that common variation in the genes encoding DNA repair proteins contributes to susceptibility to myeloma.

Urinary free light chain analysis by the Freelite® immunoassay: a preliminary study in multiple myeloma

Objectives: Evaluate the Freelite® free light chain immunoassay for urine analysis in myeloma. Design and methods Urine specimens from 20 patients were analyzed by Freelite® (The Binding Site) and SDS-agarose gel electrophoresis (Hydragel protéinurie®, Sebia). Results Using the κ/λ ratio, Freelite® was more sensitive than electrophoresis to detect free light chains, but concentration was overestimated in 75% of cases. Conclusions Despite high sensitivity and full automation, Freelite® inaccurately measures monoclonal free light chains in urine.

Overexpression of the PRAD1 Oncogene in a Patient with Multiple Myeloma and t(11;14)(q13;q32)

The t(11;14)(q13;q32) chromosomal translocation is associated with several B-cell lymphoproliferative disorders and is thought to result in upregulation of expression of PRAD1/cyclin D1 proto-oncogene. A patient with multiple myeloma of IgG kappa-type with t(11;14)(q13;q32) is now shown to overexpress PRAD1. The clinical stage of the disease was advanced (IIIA), with a myeloma cell count of 94.6% in the bone marrow. Chromosomal analysis of bone marrow cells showed t(11;14)(q13;q32) in five of 20 metaphases as well as other karyotypic features. Northern blot analysis of RNA prepared from myeloma cells revealed overexpression of PRAD1. Multiple myeloma with t(11;14)(q13;q32) has been associated with an aggressive clinical course. Although neither myeloma cells in the peripheral blood nor extramedullary lesions were apparent in the present patient, the myeloma was refractory to several chemotherapeutic regimens from the beginning. Detection of PRAD1 expression may offer an easier alternative to cytogenetic analysis in myeloma and is a potentially useful indicator of a poor prognosis.