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

Models of granulocyte DNA structure are highly predictive of myelodysplastic syndrome

We have used statistical models based on Fourier transform-infrared spectra to differentiate between the DNA structure of normal granulocytes and those obtained from patients with myelodysplastic syndrome (MDS). The substantial degree of discrimination achieved between the two DNA groups is attributed to differences in the nucleotide base and backbone structures. These structural differences allowed for the development of a discriminant analysis model that predicted, with high sensitivity and specificity, which DNA came from normal granulocytes vs. granulocytes from MDS patients. The findings are a promising basis for developing a blood test to diagnose and predict the occurrence of MDS, for which there is currently a paucity of molecular markers

Genome profiling of chronic myelomonocytic leukemia: frequent alterations of <it>RAS </it>and <it>RUNX1 </it>genes

<p>Abstract</p> <p>Background</p> <p>Chronic myelomonocytic leukemia (CMML) is a hematological disease close to, but separate from both myeloproliferative disorders (MPD) and myelodysplastic syndromes and may show either myeloproliferative (MP-CMML) or myelodysplastic (MD-CMML) features. Not much is known about the molecular biology of this disease.</p> <p>Methods</p> <p>We studied a series of 30 CMML samples (13 MP- and 11 MD-CMMLs, and 6 acutely transformed cases) from 29 patients by using Agilent high density array-comparative genomic hybridization (aCGH) and sequencing of 12 candidate genes.</p> <p>Results</p> <p>Two-thirds of samples did not show any obvious alteration of aCGH profiles. In one-third we observed chromosome abnormalities (e.g. trisomy 8, del20q) and gain or loss of genes (e.g. <it>NF1</it>, <it>RB1 </it>and <it>CDK6</it>). <it>RAS </it>mutations were detected in 4 cases (including an uncommon codon 146 mutation in <it>KRAS</it>) and <it>PTPN11 </it>mutations in 3 cases. We detected 11 <it>RUNX1 </it>alterations (9 mutations and 2 rearrangements). The rearrangements were a new, cryptic inversion of chromosomal region 21q21-22 leading to break and fusion of <it>RUNX1 </it>to <it>USP16</it>. <it>RAS </it>and <it>RUNX1 </it>alterations were not mutually exclusive. RAS pathway mutations occurred in MP-CMMLs (~46%) but not in MD-CMMLs. <it>RUNX1 </it>alterations (mutations and cryptic rearrangement) occurred in both MP and MD classes (~38%).</p> <p>Conclusion</p> <p>We detected RAS pathway mutations and RUNX1 alterations. The latter included a new cryptic <it>USP16-RUNX1 </it>fusion. In some samples, two alterations coexisted already at this early chronic stage.</p