Plasma Levels of Middle Molecules to Estimate Residual Kidney Function in Haemodialysis without Urine Collection

© 2015 Vilar et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, (http://creativecommons.org/Licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.BACKGROUND: Residual Kidney Function (RKF) is associated with survival benefits in haemodialysis (HD) but is difficult to measure without urine collection. Middle molecules such as Cystatin C and β2-microglobulin accumulate in renal disease and plasma levels have been used to estimate kidney function early in this condition. We investigated their use to estimate RKF in patients on HD. DESIGN: Cystatin C, β2-microglobulin, urea and creatinine levels were studied in patients on incremental high-flux HD or hemodiafiltration(HDF). Over sequential HD sessions, blood was sampled pre- and post-session 1 and pre-session 2, for estimation of these parameters. Urine was collected during the whole interdialytic interval, for estimation of residual GFR (GFRResidual = mean of urea and creatinine clearance). The relationships of plasma Cystatin C and β2-microglobulin levels to GFRResidual and urea clearance were determined. RESULTS: Of the 341 patients studied, 64% had urine output>100 ml/day, 32.6% were on high-flux HD and 67.4% on HDF. Parameters most closely correlated with GFRResidual were 1/β2-micoglobulin (r2 0.67) and 1/Cystatin C (r2 0.50). Both these relationships were weaker at low GFRResidual. The best regression model for GFRResidual, explaining 67% of the variation, was: GFRResidual = 160.3 · (1/β2m) - 4.2. Where β2m is the pre-dialysis β2 microglobulin concentration (mg/L). This model was validated in a separate cohort of 50 patients using Bland-Altman analysis. Areas under the curve in Receiver Operating Characteristic analysis aimed at identifying subjects with urea clearance≥2 ml/min/1.73 m2 was 0.91 for β2-microglobulin and 0.86 for Cystatin C. A plasma β2-microglobulin cut-off of ≤19.2 mg/L allowed identification of patients with urea clearance ≥2 ml/min/1.73 m2 with 90% specificity and 65% sensitivity. CONCLUSION: Plasma pre-dialysis β2-microglobulin levels can provide estimates of RKF which may have clinical utility and appear superior to cystatin C. Use of cut-off levels to identify patients with RKF may provide a simple way to individualise dialysis dose based on RKF.Peer reviewe

Artifactual measurement of low serum HDL-cholesterol due to paraproteinemia

High levels of serum low density lipoprotein cholesterol (LDL-C) and low levels of high density lipoprotein cholesterol (HDL-C) are well-known risk factors for premature atherosclerotic vascular disease [1, 2]. They are targets for primary and secondary prevention. Interpreting lipid profiles is part of the daily routine for a cardiologist. The most common cause of low HDL-C in western society is metabolic syndrome. More rare are primary lipid disorders (e.g., Tangier syndrome due to an ABCA transporter deficiency or deficiency of apolipoprotein A1) and secondary causes like (ab)use of androgens (Table 1). Extremely low serum HDL levels are associated with an increased risk of death, sepsis and malignancy [3]. A rare but important cause is interference in the biochemical assay by paraproteins, yielding an artifactually low HDL-C measurement result. We present the case of a patient who had his lipid profile repeatedly tested over the course of 4 years and had progressive decline in HDL-C measurements

Methodology of a novel risk stratification algorithm for patients with multiple myeloma in the relapsed setting

Introduction Risk stratification tools provide valuable information to inform treatment decisions. Existing algorithms for patients with multiple myeloma (MM) were based on patients with newly diagnosed disease, and these have not been validated in the relapsed setting or in routine clinical practice. We developed a risk stratification algorithm (RSA) for patients with MM at initiation of second-line (2L) treatment, based on data from the Czech Registry of Monoclonal Gammopathies. Methods Predictors of overall survival (OS) at 2L treatment were identified using Cox proportional hazards models and backward selection. Risk scores were obtained by multiplying the hazard ratios for each predictor. The K-adaptive partitioning for survival (KAPS) algorithm defined four groups of stratification based on individual risk scores. Results Performance of the RSA was assessed using Nagelkerke’s R2 test and Harrell’s concordance index through Kaplan–Meier analysis of OS data. Prognostic groups were successfully defined based on real-world data. Use of a multiplicative score based on Cox modeling and KAPS to define cut-off values was effective. Conclusion Through innovative methods of risk assessment and collaboration between physicians and statisticians, the RSA was capable of stratifying patients at 2L treatment by survival expectations. This approach can be used to develop clinical decision-making tools in other disease areas to improve patient management

Myeloma cells suppress osteoblasts through sclerostin secretion

Wingless-type (Wnt) signaling through the secretion of Wnt inhibitors Dickkopf1, soluble frizzled-related protein-2 and -3 has a key role in the decreased osteoblast (OB) activity associated with multiple myeloma (MM) bone disease. We provide evidence that another Wnt antagonist, sclerostin, an osteocyte-expressed negative regulator of bone formation, is expressed by myeloma cells, that is, human myeloma cell lines (HMCLs) and plasma cells (CD138+ cells) obtained from the bone marrow (BM) of a large number of MM patients with bone disease. We demonstrated that BM stromal cells (BMSCs), differentiated into OBs and co-cultured with HMCLs showed, compared with BMSCs alone, reduced expression of major osteoblastic-specific proteins, decreased mineralized nodule formation and attenuated the expression of members of the activator protein 1 transcription factor family (Fra-1, Fra-2 and Jun-D). Moreover, in the same co-culture system, the addition of neutralizing anti-sclerostin antibodies restored OB functions by inducing nuclear accumulation of β-catenin. We further demonstrated that the upregulation of receptor activator of nuclear factor κ-B ligand and the downregulation of osteoprotegerin in OBs were also sclerostin mediated. Our data indicated that sclerostin secretion by myeloma cells contribute to the suppression of bone formation in the osteolytic bone disease associated to MM

Comorbidity as a prognostic variable in multiple myeloma: comparative evaluation of common comorbidity scores and use of a novel MM–comorbidity score

Comorbidities have been demonstrated to affect progression-free survival (PFS) and overall survival (OS), although their impact in multiple myeloma (MM) patients is as yet unsettled. We (1) assessed various comorbidities, (2) compared established comorbidity indices (CIs; Charlson comorbidity index (CCI), hematopoietic cell transplantation-specific comorbidity index (HCT-CI)), Kaplan Feinstein (KF) and Satariano index (SI) and (3) developed a MM-CI (Freiburger comorbidity index, FCI) in 127 MM patients. Univariate analysis determined moderate or severe pulmonary disease (hazard ratio (HR): 3.5, P<0.0001), renal impairment (via estimated glomerular filtration rate (eGFR); HR: 3.4, P=0.0018), decreased Karnofsky Performance Status (KPS, HR: 2.7, P=0.0004) and age (HR: 2, P=0.0114) as most important variables for diminished OS. Through multivariate analysis, the eGFR ⩽30 ml/min/1.73m2, impaired lung function and KPS ⩽70% were significant for decreased OS, with HRs of 2.9, 2.8 and 2.2, respectively. Combination of these risk factors within the FCI identified significantly different median OS rates of 118, 53 and 25 months with 0, 1 and 2 or 3 risk factors, respectively, (P<0.005). In light of our study, comorbidities are critical prognostic determinants for diminished PFS and OS. Moreover, comorbidity scores are important treatment decision tools and will be valuable to implement into future analyses and clinical trials in MM

Variations in Suppressor Molecule CTLA-4 Gene Are Related to Susceptibility to Multiple Myeloma in a Polish Population

Various phenotype and functional T-cell abnormalities are observed in multiple myeloma (MM) patients. The aim of this study was to investigate the association between polymorphisms in the gene encoding cytotoxic T-lymphocyte antigen-4 (CTLA-4), a negative regulator of the T-lymphocyte immune response and susceptibility to multiple myeloma in a Polish population. Two hundred MM patients and 380 healthy subjects were genotyped for the following polymorphisms: CTLA-4c.49A>G, CTLA-4g.319C>T, CTLA-4g.*642AT(8_33), CT60 (CTLA-4g.*6230G>A), Jo31 (CTLA-4g.*10223G>T). Our study is the largest and most comprehensive evaluation to date of the association between genetic polymorphisms in the CTLA-4 molecule and multiple myeloma. It was found that CTLA-4c.49A>G[G], CT60[G], and Jo31[G] alleles were more frequently observed in MM patients than in controls (0.50 vs. 0.44, p = 0.03, 0.65 vs. 0.58, p = 0.04, and 0.63 vs. 0.57, p = 0.03, respectively). Moreover, the haplotype CTLA-4c.49A>G[G], CTLA-4g.319C>T[C], CTLA-4g.*642AT(8_33) [8], CT60[G], Jo31[G] including all susceptibility alleles increases the risk of MM about fourfold (OR: 3.79, 95%CI: 2.08–6.89, p = 0.00001). These findings indicate that genetic variations in the CTLA-4 gene play role in susceptibility to multiple myeloma and warrant further investigation through replication studies