Rajkumar, S. Vincent

Abstract Background: The presence of circulating myeloma cells (CMC) detected by flow cytometry at the time of diagnosis of multiple myeloma is associated with a shortened response to therapy and reduced overall survival (OS). We hypothesized that the presence of CMC at the time of stem cell collection prior to high dose therapy (HDT) and autologous stem cell transplantation (ASCT) would identifies a cohort of patients with a high risk of rapid progression. Methods: The Mayo Clinic myeloma transplant database was queried for patients who were mobilized using cyclophosphamide and hematopoietic growth factors. CMC was determined using flow cytometry by gating on a population of CD38 bright and CD45 negative cells. The impact of CMC on OS and time to progression (TTP) and its role in the context of established prognostic parameters was evaluated. Results: Of 246 patients with MM undergoing ASCT, 95 had CMC. Patients with CMC had significantly higher plasma cell labeling index, adverse cytogenetics, B2-M and resistant disease. Complete response (CR) rates post transplant were 32% and 36% for patients with and without CMC (p=0.5034). OS was 33.2 and 58.6 months (p=0.0052) while TTP was 14.1 and 22 months respectively (p=0.0005). Figure Figure On multivariate analysis, CMC remained an independent prognostic factor in a model that included cytogenetics and disease status at time of transplant (p=0.0314). A prognostic system based on the presence or absence of CMC and karyotype abnormalities was developed. Patients with neither, one or both parameters had a median, OS of 55, 48 and 21.5 months respectively (p<0.0001) while TTP was 22, 15.4 and 6.5 months for the same groups (p<0.0001). Conclusion: The presence of CMC at the time of HDT and ASCT is an independent prognostic factor. The combination of CMC and cytogenetics provides a simple yet powerful scoring system that stratifies patients and guides their management.

Abstract Background: Thalidomide and dexamethasone combination has been shown to be an effective therapy for multiple myeloma (MM). In newly diagnosed patients with MM, the combination results in overall response rates of over 70% of patients. However, a considerable number of patients do not respond and will need to proceed to other therapies. The ability to identify patients who are unlikely to respond to particular therapies will allow tailoring of therapeutic approaches and in turn will reduce unnecessary toxicity and morbidity from lack of rapid disease control. With the availability of new technology such as gene expression profiling (GEP), this has become a possibility. We employed this approach to identify genes that can reliably predict lack of response to the thalidomide dexamethasone combination. Methods: Patient samples from the Eastern Co-operative Oncology Group clinical trial (E1A00), that compared thalidomide-dexamethasone combination with dexamethasone, and patient samples from the phase II Mayo Clinic study of thalidomide and dexamethasone, both for newly diagnosed MM, were used for this study. Thirty newly diagnosed patients who were evaluable for response were included in the analysis. GEP was performed using the Affymetrix U133A microarray platform as per manufacturer’s recommendation. The Affymetrix output (CEL files) was imported into Genespring 7.2 (Agilent Technologies) microarray analysis software, normalized across chips using GCRMA followed by per gene normalization to median. For the purposes of this study, responses were defined as reduction in the serum paraprotein (or the urinary M protein in the absence of a serum M protein) of >=50% (PR), 25 to 49% (MR), increase of >=50% (PD) and stable disease for the remaining. Results: Five of the 30 patients had no response to the thalidomide Dexamethasone therapy. Using the class prediction tool available in Genespring (Support Vector Machines), we identified 25 genes that reliable predicted non responders (PD, NC) from the responders (MR, PR, and CR). See table for a list of predictive genes with identified genes. Conclusion: Using a combination of two datasets we have identified a set of genes that can be used to reliably predict lack of response to thalidomide and dexamethasone in patients with newly diagnosed MM. We think that this represents a step towards creation of custom microarrays spotted with genes that are capable of predicting lack of response (or response) for the purpose of tailoring therapy to the patient. Gene Predictive strength hypothetical protein FLJ20719 1.655 Tubulin alpha 6 1.653 SEC3-like 1 (S. cerevisiae) 1.649 Ribosomal protein L18 1.546 Ribosomal protein L4 1.432 Tubulin alpha 6 1.409 cleavage stimulation factor 1.393 Tubulin, alpha, ubiquitous 1.393 CD99 antigen 1.38 hmel2 1.346 Leptin receptor 1.291 Integrin-linked kinaseSMC4 structural maintenance of chromosomes 4-like 1 1.269 Cornichon homolog 1.255 Williams-Beuren syndrome chromosome region 5 1.217 Ubiquitin specific protease 1 1.2 Sarcoma antigen NY-SAR-91 1.2

Abstract Background: Solitary plasmacytoma of bone (SBP) is a localized collection of monoclonal plasma cells that is potentially curable with local radiation therapy but associated with a high risk of progression to multiple myeloma. We hypothesized that an abnormal immunoglobulin free light (FLC) ratio at diagnosis may be a prognostic indicator of transformation risk. Methods: We identified a cohort of 133 patients with SBP for whom stored serum taken at the time of diagnosis was available. The diagnosis was ascertained and serum FLC determined in 126 patients. Results: From this cohort, 48 patients have progressed to myeloma and the median time to progression among those who progressed was 1.9 years. On univariate analysis, age (p<0.001), gender (p=0.035), abnormal FLC ratio at diagnosis (p=0.009) and persistence of serum or urine M-protein after therapy (p=0.0070 were all associated with a shorter overall survival (OS) and time to progression to multiple myeloma. Progression by Normal FLC(0.26–1.65) Progression by Normal FLC(0.26–1.65) On multivariate analysis, an abnormal FLC ratio retained its independence in a model that includes age at diagnosis but lost its significance when combined with persistence of the serum or urine M-protein. However, serum or urine M-proteins are not detectable in a significant number of patients with SBP and therefore not informative. Conclusion: The FLC ratio at the time of diagnosis of SBP is a powerful predictor of risk and a useful aid to management of patients with this condition.

Abstract Waldenström’s macroglobulinemia (WM) is an incurable low-grade lymphoproliferative disorder characterized by bone marrow (BM) infiltration of a clonal population of small B-lymphocytes, plasmacytoid lymphocytes and plasma cells that secrete monoclonal IgM antibody. Because it is difficult to obtain tumor metaphases for karyotype studies, few recurrent chromosomal abnormalities have been reported and the genetic basis of the disease remains poorly defined. Therefore, we performed a comprehensive high-resolution study to identify genomic abnormalities involved in WM pathogenesis. Fifty-seven WM patients were analyzed using a combination of array-based comparative genomic hybridization (aCGH)(N=42); gene expression profiling (GEP)(N=22), DNA sequencing (N=24) and cIgM-FISH (N=57). Agilent 244A and Affymetrix U133 platforms were used in the aCGH and GEP experiments, respectively. An NF-κB index was calculated from GEP data, as a surrogate marker of NF-κB transcription activity. NFKB2 sub cellular localization was determined by immunofluorescence staining. Overall, 83% of samples have aCGH defined chromosomal abnormalities, with a median of 3 abnormalities per patient (range 0 to 27). We identified 16 recurrent regions of copy number change found in >5% (3 or more patients); 10 deleted and 6 amplified regions. The most common abnormality was the entire or partial deletion of 6q, identified in 40% of cases. Four nonoverlapped minimal deleted regions were identified on 6q (MDR1 to MDR4), each of them being present in at least 14 of 17 patients with the abnormality. Gain of 6p was the second most common abnormality (17%) and its presence was always concomitant with 6q loss. Other recurrent deletions were 13q14 (10%) and 7q22, 8p, 11q22-q23, 11q23-q24 and 17p11-p13 (7% each). Copy gains were identified as partial or entire gains of chromosomes 18 (17%), 4 (12%) and 3 (10%), 8q (10%) and Xq27.1-q28 (10%). Three patients had either homozygous deletions or LOH with mutations affecting both alleles of TRAF3 on 14q32. TRAF3 inactivation was correlated with an increased NF-kB transcriptional signature and it was associated with activation of the non-canonical NFkB pathway. Additionally, we identified the inactivation of TNFAIP3, another negative regulator of the NF-kB pathways, in one of 24 patients. Finally, interstitial deletions identified in 4 patients at 13q14 identified a 1.1 Mb MDR, including MIRN15A and MIRN16-1. These findings confirm that focal 13q14 deletion is not restrict to B-CLL and that the MIRN15A/MIRN16-1 abnormalities might be common to several indolent B-cell diseases. Overall, we identified TRAF3 and TNFAIP3 inactivation in 5.3% and 2.4%, respectively. To our knowledge, this is the first study showing the inactivation of bona fide tumor suppressor genes in WM patients. Furthermore, these genes are negative regulators of NF-kB signaling pathway, highlighting its biologic importance in sustaining and limiting growth in WM. Mutational activation of this pathway, which is normally activated by ligand-receptor interactions within the BM microenvironment, suggest a therapeutic role for inhibitors of NF-KB pathway activation in the treatment of WM.

Abstract Title: Primary Therapy with Bortezomib—The Role of Induction, Maintenance, and Re-Induction in Patients with High Risk Myeloma. Update of Results from E2A02. Angela Dispenzieri, MD1, Susanna Jacobus, PhD2, David Vesole, MD3 and Philip R. Greipp, MD1. 1Hematology, Mayo Clinic, Rochester, MN, United States, 55905 and 2Biostatistics, Eastern Cooperative Oncology Group, Boston, MA, United States, 02115. 3Saint Vincent’s Hospital, New York, NY 10010 Background: Single agent bortezomib as upfront therapy in patients with multiple myeloma (MM) results in response rates of 38% and the drug has been touted to be especially effective in patients with high risk disease. We sought to explore response rate, the role of maintenance and reinduction in a cohort of patients with high-risk MM. Methods: Patients with newly diagnosed high-risk myeloma (beta-2 microglobulin [B2M] >= 5.5., plasma cell labeling index [PCLI] >= 1, or deletion 13q) and adequate organ and functional status were eligible. Patients were treated with bortezomib 1.3 mg/m2 day 1, 4, 8, and 11 every 21 days for 8 cycles as induction. After induction, patients were scheduled to receive bortezomib 1.3 mg/m2 every other week indefinitely. Elective peripheral stem cell mobilization (growth factor alone) was allowed after 4 cycles of bortezomib. Patients relapsing on maintenance schedule had full induction schedule resumed. Responses as defined by the EBMT criteria were determined after each cycle and needed to be confirmed after at least 6 weeks. Results: Between March 15, 2004 and March 10, 2005, 44 patients enrolled on study. Among the 42 eligible treated patients, median age was 63; 51% were male. All patients had high risk disease: deletion 13q (6/41); PCLI >=1% (17/33); t(4:14) (4/27) and B2M >= 5.5 (34/43). Nineteen patients completed induction, i.e. 8 cycles of bortezomib. The most common causes for discontinuing therapy were: progressive disease (n=17), AE (n=7), alternate therapy (n=4), death (n=1), and other (n=11). Forty-eight percent of patients achieved a partial response (PR) or better with induction (0 complete responses, 2 very good PR, 17 PR, 3 minimal responses, 5 no response, 9 progressive disease, and 6 inevaluable or missing). Response rates across risk groups did not differ with a PR or better for patients with deletion 13q (2/6); PCLI >=1% (8/17); t(4:14) (2/4) and B2M >= 5.5 (15/33). One patient’s response was upgraded to CR during maintenance. The rate of painful peripheral neuropathy during all courses of therapy was: grade 1, n=25; grade 2, n=2; and grade 3, n=2. With a median follow-up of 41.6 months (95%CI 36.6–43), 43% of patients have died. Median overall survival (OS) has not been reached (Figure), and the 1- and 2-year OS rates were 88.1% (95%CI 73.7–94.9%) and 76.2% (95%CI 60.3–86.4%) respectively. The median progression free survival (PFS) was 16.3 months (95%CI 6.2–26.6) and the 1- and 2-PFS were 76.7% (95%CI 58.8–87.6%) and 38.3% (95%CI 20.6–55.9%), respectively. Fifteen patients went on to maintenance. The distribution by risk group for patients entering maintenance was not different across groups: deletion 13q, 3/6; high PCLI, 6/17; high B2M, 11/33; t(4;14), 1/4; and p53, 0/2. For those entering maintenance, the median PFS was 19.8 months (Figure), and the 1 year PFS rate was 75% (95%CI 40.8–91.2%). Of the 7 patients progressing on maintenance who received reinduction with bortezomib, no patient responded. Only 2 remain on therapy. Figure Figure Conclusions: In high risk patients, upfront bortezomib results in response rates comparable to those reported for unselected cohorts of newly diagnosed myeloma patients. For patients responding to therapy, maintenance therapy is feasible. Reinduction was unsuccessful in high risk patients failing maintenance.

Abstract Background: The free light chain (FLC) assay allows a nephelometric measurement of this free kappa and lambda light chains that circulate as monomers or dimers, not bound to the immunoglobulin heavy chain. Estimation of the free light chain levels and their ratio has utility in screening, prognostication and treatment response assessment in multiple myeloma, and is particularly useful in light chain myeloma. Previous studies have suggested that absence of a functional rearrangement on at least one of the IgH allele is the basis of light chain myeloma. Translocations involving the immunoglobulin heavy chain (IgH) locus on chromosome 14 can be detected using FISH in over half of the patients with myeloma. We hypothesized that presence of an IgH translocation may be associated with compromised production of heavy chains and leads to unbalanced, excess production of clonal light chain. Methods: From February 1988 to May 1992, 653 patients with previously untreated multiple myeloma were enrolled on the phase III clinical trial E9486. Serum free light chains were run on stored sera obtained at baseline in 495 patients as part of a previous study. Among these patients, 314 patients were previously studied using FISH for presence or absence of IgH translocations, p53 abnormalities and deletion 13 and were included in the current analysis. Results: The median difference between the involved and uninvolved FLC (FLCdiff) was higher among the group of patients with any IgH translocation abnormality compared to those with none (Figure 1). This was particularly evident among the patients with a t(14;16) who had the highest FLCdiff. In a multivariate analysis, we examined if the prognostic value seen with FLCdiff was independent of the presence of IgH translocations t(4:14) and t(14;16), which are associated with a worse outcome. The presence of t(4;14) or t(14;16) was associated with FLCdiff groups using a cutoff point of 185, with 13% of those with FLCd ≤185 and 27% of those with FLCd > 185 having the translocations (P= 0.008). At the cutoff value of 185, the prognostic value of the FLC-diff on progression free and overall survival appears to be independent of these high risk IgH translocations (P-value=0.03 and 0.003, respectively for PFS and OS) We then examined the prognostic value of the FLC-diff in the group of patients without these two high risk abnormalities and were able to confirm that they remained prognostic for PFS (P=0.009) and OS (p=0.005). However, among the group of patients with either of the two high risk IgH abnormalities, FLCdiff estimate added little to assessment of their outcome (P=0.97 and 0.20, respectively for PFS and OS). Conclusion: Elevated free light chain levels are associated with presence of IgH translocations and these patients are more likely to harbor the high risk genetic abnormalities. Routine FISH testing for patients with newly diagnosed myeloma will allow us to confirm these and allow better risk stratification of the patients. Additional work needs to be done to help us better understand the molecular basis for unbalanced light chain excretion by myeloma cells and the current finding of the association with IgH translocation abnormalities should form the basis for this work. Figure 1. Distribution of FLC ratio (inv vs. uninv) and FLC difference (inv − uninv) among patients. Solid squares represent patients with t(4;14) or t(14;16) or t(11;14) or other 14q32 translocation; open circles represent patients without t(4;14), t(14;16), t(11;14) and any other 14q32 translocations. The horizontal dashed lines refer to FLC ratio original values of 100 and 1000, and vertical dashed lines refer to FLC difference original values of 10 and 100. Solid line indicates significant association (P<=0.05) between the dichotomized FLC groups and translocation status. Figure 1. Distribution of FLC ratio (inv vs. uninv) and FLC difference (inv − uninv) among patients. Solid squares represent patients with t(4;14) or t(14;16) or t(11;14) or other 14q32 translocation; open circles represent patients without t(4;14), t(14;16), t(11;14) and any other 14q32 translocations. The horizontal dashed lines refer to FLC ratio original values of 100 and 1000, and vertical dashed lines refer to FLC difference original values of 10 and 100. Solid line indicates significant association (P<=0.05) between the dichotomized FLC groups and translocation status.

Abstract Background: Monoclonal gammopathy of undetermined significance (MGUS) is a common pre-malignant plasma cell disorder associated with a 1% per year risk of progression to multiple myeloma or related malignancy. Since the risk factors for MGUS are poorly defined, the goal of the present study was to determine if the risk of MGUS is increased in first degree relatives of patients with known multiple myeloma (MM) or MGUS. Methods: MGUS probands (index cases) were recruited from a population-based prevalence study of MGUS in Olmsted County, MN while MM probands were recruited through the Mayo Clinic practice. Consenting probands were asked to provide contact information on all first-degree relatives ages 40 years and older. Serum samples were then collected from first-degree relatives with informed consent and subjected to agaraose-gel electrophoresis and immunofixation. The prevalence of MGUS in first-degree relatives of MM and MGUS probands was compared to population-based rates from Olmsted County using risk ratios (RR). For comparisons to the reference population, only cases detected by protein electrophoresis and confirmed by immunofixation were included so that the diagnostic strategy was identical in the two groups being compared. Results: Serum samples were obtained from 911 relatives of 329 unique families, including 493 siblings, 324 children and 94 parents of patients with MGUS or MM. Using protein electrophoresis, monoclonal protein was detected in the serum of 55 (6%) while immunofixation identified 28 additional relatives (3%), for an age- and sex-adjusted prevalence rate of 8.1% (95%CI: 6.3, 9.8). The age-specific prevalence of MGUS in first-degree relatives increased with age (1.9%, 6.9%, 11.6%, 14.6%, and 21.0% for ages 40–49, 50–59, 60–69, 70–79 and ≥80, respectively; P<0.001). Based on similar MGUS detection methodology as the reference population, there was a significantly higher risk of MGUS in first-degree relatives (age-adjusted RR, 2.6, 95%CI: 1.9, 3.4) compared to the reference population. The increased risk (P<0.001) was seen both in relatives of MM probands (RR, 2.0, 95%CI: 1.4, 2.8), as well as MGUS probands (RR, 3.3, 95%CI: 2.1, 4.8). This association was similar across age of proband, age and gender of relative, and relationship of the first-degree relative. When examining whether the increased risk of MGUS in relatives was specific to probands with a large monoclonal protein concentration or specific monoclonal immunoglobulin isotype (i.e. high-risk MGUS phenotype), there was suggestion of a greater risk for relatives of probands with a high (3 1.5 g/dL) M-protein (RR, 2.8, 95%CI: 2.0,3.8) compared to lower M-protein levels (RR, 1.8, 95%CI: 1.1,2.8) although the difference did not reach statistical significance (P=0.12). The risk of MGUS in relatives did not differ by proband’s isotype (IgG vs. other). Conclusions: First-degree relatives of patients with MM or MGUS have a greater than two-fold risk of MGUS compared to the general population, implying underlying genetic predisposition for these diseases and providing rationale for identifying genetic determinants of MGUS. This study also provides important baseline rates of MGUS in first-degree relatives that impact the clinical care of these patients.

Abstract In an effort to identify novel genetic abnormalities in multiple myeloma (MM) we analyzed an initial set, as part of the Multiple Myeloma Research Consortium (MMRC) Genomics Initiative, of 94 MM patient samples on high-resolution array-based comparative genomic hybridization (aCGH) and gene expression profiling (GEP) technologies. The MMRC Genomics Initiative is a three-year research program spanning a full-spectrum of genomic technologies with the goal of analyzing 250 MM patient samples by 2009. Raw data from the Initiative are released in near real time through the MMRC Multiple Myeloma Genomics Portal. This initial aCGH dataset from the Agilent 244K platform represents the highest resolution gene copy number analysis with corresponding GEP released to date in MM. It has confirmed the cytogenetic definitions of MM with the data set being split between patients with hyperdiploid and non-hyperdiploid MM. Furthermore, the 244K platform has helped to refine minimal regions of change present on 1p, 1q, 6q, 8p, 13q, 14q, and 16q. A comprehensive screen of the dataset for genes residing in regions of homozygous deletion identified 105 genes. The most commonly affected gene was CDKN2C(p18) (8.3%) while 12 other regions were recurrently targeted. Several of these regions were recently implicated in the pathogenesis of MM but the large majority represents novel observations. The aCGH and GEP data were integrated using two different programs developed by the core institutions (The Broad Institute of Harvard & MIT and Translational Genomics Research Institute). First, Genomic Identification of Significant Targets in Cancer (GISTIC), which identifies highly significant regions of change and a limited set of candidate genes within these regions, was used to identify 285 genes associated with DNA content alterations. Second, Breakpoint Expression Correlation (BEC), which identifies dysregulated genes on either side of a copy number alteration, was used to identify 194 genes with expression changes associated with a breakpoint. This latter gene list includes all known IgH translocation target genes identified to date in myeloma. Overlapping the gene lists generated by GISTIC, BEC, and the homozygous deletion screen identified a number of genes previously implicated in MM such as CDKN2C(p18), CYLD, BIRC2/BIRC3, and two novel genes, FAM46C and RNF6. Ongoing data integration with RNAi and high content sequencing projects of the current Initiative holds great promise in furthering our understanding of MM. The MMRC Genomics Initiative and resulting efforts from the myeloma research community will increase our understanding of MM at the molecular level, help to identify new targets, and ultimately lead to the development of better, more effective therapies for myeloma.

Abstract Introduction: The kidney is affected by immunoglobulin light chain amyloidosis (AL) in more than 50% of patients who present with the disease, but long-term predictors for and outcomes after renal replacement therapy have not been well described in this patient group Patients: 145 patients with AL who participated in Mayo Clinic treatment trials and were monitored for at least 11 years. No patient was lost to follow-up Results: Among patients presenting with renal AL, 42% ultimately received renal replacement therapy compared with 5% of patients who did not have an initial presentation involving the kidney. Table 1. Monoclonal Protein Studies in 145 Patients With Immunoglobulin Light Chain Amyloidosisa Patients, No. (%) Monoclonal Protein Renal Amyloid at Presentation (n=84) Nonrenal Amyloid at Presentation (n=61) a P=.02 l more likely to cause renal presentation None 7 (8) 2 (3) k 6 (7) 12 (20) l 71 (85) 47 (77) Table 2. Characteristics of All 145 Patients With Immunoglobulin Light Chain Amyloidosis Amyloid Renal (n=84) Nonrenal (n=61) P Value Abbreviations: IQR, interquartile range; NA, not applicable. a included in the definition of renal amyloidosis Patients with l immunoglobulin light chain amyloid were significantly more likely to have renal involvement and had significantly greater urinary protein loss than patients with κ or no monoclonal light chain amyloid Age, median (IQR), y 61 (52–67) 62 (55–68) .47 Sex, male/female 52/32 40/21 .72 24-hr urine protein loss, median (IQR), g/d 7.0 (4.4–11.7) 0.3 (0.1–6.4) NAa Creatinine, median (IQR), mg/dL 1.1 (0.9–2.2) 1.1 (0.9–1.3) .22 Cardiac involvement (yes/no) 35/48 48/16 .0001 Table 3 Distribution of Urinary Protein and Creatinine Based on Monoclonal Protein Monoclonal Protein Test k (n=18) l (n=118) None (n=9) P Value Abbreviation: IQR, interquartile range. Patients with renal amyloid who ultimately received dialysis support had significantly higher serum creatinine and 24-hour urine protein levels at presentation. Absence of cardiac involvement at diagnosis predicted an increased likelihood of dialysis All patients (N=145) 24-hr urine protein loss, median (IQR), g/d 0.73 (0.16–2.37) 3.61 (0.35–7.8) 5.68 (0.3–12.2) .001 Creatinine, median (IQR), mg/dL 1.1 (0.9–1.3) 1.1 (0.9–1.3) 1.5 (1.2–1.6) NS Patients with renal amyloid at presentation (n=84) 24-hr urine protein loss, median (IQR), g/d 2.93 (1.1–5.0) 7.2 (4.8–11.8) 7.8 (3.8–12.6) .04 Creatinine, median (IQR), mg/dL 1.0 (0.8–2.6) 1.1 (0.9–2.2) 1.5 (1.1–1.6) NS Table 4 Characteristics of 84 Patients Presenting With Renal Amyloidosis Dialysis Subsequently Not Required Characteristic Required (n=35) (n=49) P Value Abbreviation: IQR, interquartile range. The median time from diagnosis to dialysis was 29.5 months for those that went into renal failure.). However, the actuarial risk reached 50% at 12 years Kaplan-Meier failure curve demonstrating the actuarial time from diagnosis to the start of dialysis therapy N=145 For 38 patients who received dialysis, median survival from day 1 of dialysis was 10.4 months Kaplan-Meier survival of 38 patients from the start of dialysis therapy Age, median (IQR), y 60 (52–67) 62 (52–67) .90 Sex, male/female 21/14 31/18 .76 24-hr urine protein loss, median (IQR), g/d 7.4 (5.0–14.8) 5.9 (3.7–9.1) .03 Creatinine, median (IQR), mg/dL 1.4 (0.9–2.8) 1.1 (0.9–1.5) .01 Cardiac involvement (yes/no) 9/26 26/23 .01 Conclusion: In our study, 26% of all patients with AL ultimately received renal replacement therapy compared with 42% of patients who presented with renal AL specifically. The presenting 24-hour urine protein loss and creatinine values predict which patients will require dialysis. Median survival for patients starting dialysis is less than 1 year. Presence of l light chain amyloid predicts an increased likelihood of renal involvement and, when the kidney is affected, increased proteinuria.

Abstract Background: Traditionally response to therapy in multiple myeloma (MM) is based on changes in the serum and urine monoclonal protein by immunoelectrophoresis. Immunofixation allows for detection of small amounts of monoclonal protein that cannot be quantitated on immunoelectrophoresis. Serum immunoglobulin free light chain (FLC) assay allows for detection of unbound kappa and lambda free light chain and has allowed disease measurement in patients with oligosecretory myelomas and can potentially allow detection of low levels of tumor burden, below the threshold of the standard tests. We examined this hypothesis in patients who had obtained a negative immunofixation in serum and urine following treatment of their MM. Methods: For the purposes of the study, we included selected patients with MM who had measurable monoclonal (M) protein levels at baseline (defined as >1 gm/dL in the serum or >200 mg/24 hour in the urine or involved free light chain > 10 mg/dL) on protein electrophoresis; patients with non-secretory and oligo-secretory myeloma were excluded. We then identified patients who since 1995 had a negative immunofixation in the serum and urine, all done at the same time (within 30 days of each other). Baseline demographics and clinical characteristics; date of diagnosis, last follow up, and follow up status; serum and urine M protein levels at diagnosis; and results of serum and urine immunofixation, and serum free light chain (FLC) ratio within 30 days of the immunofixation were all collected from the existing databases. Results: Eighty-four patients met the criteria for the study, all of whom had measurable disease at baseline and subsequently achieved negative immunofixation in serum and urine. Among these, 46 patients (55%) also had a normal FLC ratio (K/L ratio; 0.26–1.65). Th median time from diagnosis to the documented immunofixation was 7.5 months (range, 1–157). The median overall survival from diagnosis among those with a normal FLC ratio along with negative immunofixation was not reached compared to 76 months for those with abnormal FLC ratio, P = 0.02. The median overall survival from the documentation of negative immunofixation was not reached for the group with normal FLC ratio compared to 46.5 months for those with an abnormal FLC, P = 0.03. Conclusion: Attainment of a normal FLC ratio at the time of serum and urine immunofixation negative status identifies a group of patients with better outcome. The presence of an abnormal FLC ratio likely represents persistence of the clonal population that is secreting none or very small amounts of monoclonal protein. The data presented here supports the inclusion of FLC measurements as part of response criteria for MM as has been done for the definition of stringent CR in the IMWG response criteria. Figure: Overall survival from diagnosis in patients with or with out a normal FLC ratio at the time of serum and urine immunofixation. Figure:. Overall survival from diagnosis in patients with or with out a normal FLC ratio at the time of serum and urine immunofixation.