THERMAL MODEL FOR THE DESORPTION OF (MOLECULAR) IONS INDUCED BY MeV HEAVY IONS

Un modèle thermique a été développé pour décrire la désorption d'ions secondaires par des ions lourds de plusieurs MeV. Le modèle est capable de reproduire la dépendance du rendement d'émission avec l'énergie et la charge initiale des ions de plusieurs MeV.A thermal model is developed to describe the desorption of ions by MeV heavy ions. The model is able to reproduce the dependence of measured secondary ion yields on the energy and the initial charge state of the MeV ions

The derived neutrophil to lymphocyte ratio is an independent prognostic factor in patients with diffuse large B-cell lymphoma

BACKGROUND: With growing evidence on the role of inflammation in cancer biology, the systemic inflammatory response has been postulated as having prognostic significance in a wide range of different cancer types. Recently, the derived neutrophil to lymphocyte ratio (dNLR) has been proposed as an easily determinable prognostic factor in cancer patients. Nevertheless, its prognostic significance in diffuse large B-cell lymphoma (DLBCL) patients has never been explored. METHODS: Data from 290 consecutive DLBCL patients, diagnosed between 2004 and 2013 at a single Austrian centre, were evaluated retrospectively. The prognostic influence of the dNLR and other clinico-pathological factors including age, lactate dehydrogenase, cell of origin category and Ann Arbor stage on 5-year overall- (OS) and disease-free (DFS) survival was studied by Kaplan–Meier curves. To evaluate the independent prognostic relevance of dNLR, univariate and multivariate Cox regression models were applied. RESULTS: An independent significant association between high dNLR and poor clinical outcome in multivariate analysis for OS (HR=2.02, confidence interval (CI) 95%=1.17–3.50, P=0.011), as well as DFS (HR=2.15, CI 95%=1.04–4.47, P=0.038), was identified. CONCLUSION: In the present study, we showed that a high dNLR at diagnosis of DLBCL represents an independent poor prognostic factor for clinical outcome. Our data encourage the further validation of this easily available parameter in prospective studies and as a potential stratification tool in clinical trials