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Background: Recently published results of quality of life (QoL) studies indicated different outcomes of palliative radiotherapy for brain metastases. This prospective multi-center QoL study of patients with brain metastases was designed to investigate which QoL domains improve or worsen after palliative radiotherapy and which might provide prognostic information.
Methods: From 01/2007-01/2009, n=151 patients with previously untreated brain metastases were recruited at 14 centers in Germany and Austria. Most patients (82 %) received whole-brain radiotherapy. QoL was measured with the EORTC-QLQ-C15-PAL and brain module BN20 before the start of radiotherapy and after 3 months.
Results: At 3 months, 88/142 (62 %) survived. Nine patients were not able to be followed up. 62 patients (70.5 % of 3-month survivors) completed the second set of questionnaires. Three months after the start of radiotherapy QoL deteriorated significantly in the areas of global QoL, physical function, fatigue, nausea, pain, appetite loss, hair loss, drowsiness, motor dysfunction, communication deficit and weakness of legs. Although the use of corticosteroid at 3 months could be reduced compared to pre-treatment (63 % vs. 37 %), the score for headaches remained stable. Initial QoL at the start of treatment was better in those alive than in those deceased at 3 months, significantly for physical function, motor dysfunction and the symptom scales fatigue, pain, appetite loss and weakness of legs. In a multivariate model, lower Karnofsky performance score, higher age and higher pain ratings before radiotherapy were prognostic of 3-month survival.
Conclusions: Moderate deterioration in several QoL domains was predominantly observed three months after start of palliative radiotherapy for brain metastases. Future studies will need to address the individual subjective benefit or burden from such treatment. Baseline QoL scores before palliative radiotherapy for brain metastases may contain prognostic information.
Leukemia inhibitory factor (LIF) and Ciliary Neurotrophic factor (CNTF) are members of the interleukin-6 family of cytokines, defined by use of the gp130 molecule as an obligate receptor. In the murine experimental autoimmune encephalomyelitis (EAE) model, antagonism of LIF and genetic deletion of CNTF worsen disease. The potential mechanism of action of these cytokines in EAE is complex, as gp130 is expressed by all neural cells, and could involve immuno-modulation, reduction of oligodendrocyte injury, neuronal protection, or a combination of these actions. In this study we aim to investigate whether the beneficial effects of CNTF/LIF signalling in EAE are associated with axonal protection; and whether this requires signalling through oligodendrocytes. We induced MOG\(_{35-55}\) EAE in CNTF, LIF and double knockout mice. On a CNTF null background, LIF knockout was associated with increased EAE severity (EAE grade 2.1\(\pm\)0.14 vs 2.6\(\pm\)0.19; P<0.05). These mice also showed increased axonal damage relative to LIF heterozygous mice, as indicated by decreased optic nerve parallel diffusivity on MRI (1540\(\pm\)207 \(\mu\)m\(^2\)-/s vs 1310\(\pm\)175 \(\mu\)m\(^2\)-/s; P<0.05), and optic nerve (-12.5%) and spinal cord (-16%) axon densities; and increased serum neurofilament-H levels (2.5 fold increase). No differences in inflammatory cell numbers or peripheral auto-immune T-cell priming were evident. Oligodendrocyte-targeted gp130 knockout mice showed that disruption of CNTF/LIF signalling in these cells has no effect on acute EAE severity. These studies demonstrate that endogenous CNTF and LIF act centrally to protect axons from acute inflammatory destruction via an oligodendrocyte-independent mechanism.
Recently, several classifiers that combine primary tumor data, like gene expression data, and secondary data sources, such as protein-protein interaction networks, have been proposed for predicting outcome in breast cancer. In these approaches, new composite features are typically constructed by aggregating the expression levels of several genes. The secondary data sources are employed to guide this aggregation. Although many studies claim that these approaches improve classification performance over single genes classifiers, the gain in performance is difficult to assess. This stems mainly from the fact that different breast cancer data sets and validation procedures are employed to assess the performance. Here we address these issues by employing a large cohort of six breast cancer data sets as benchmark set and by performing an unbiased evaluation of the classification accuracies of the different approaches. Contrary to previous claims, we find that composite feature classifiers do not outperform simple single genes classifiers. We investigate the effect of (1) the number of selected features; (2) the specific gene set from which features are selected; (3) the size of the training set and (4) the heterogeneity of the data set on the performance of composite feature and single genes classifiers. Strikingly, we find that randomization of secondary data sources, which destroys all biological information in these sources, does not result in a deterioration in performance of composite feature classifiers. Finally, we show that when a proper correction for gene set size is performed, the stability of single genes sets is similar to the stability of composite feature sets. Based on these results there is currently no reason to prefer prognostic classifiers based on composite features over single genes classifiers for predicting outcome in breast cancer.
Objective:
To determine the survival in a population of German patients with Duchenne muscular dystrophy.
Patients and methods:
Information about 94 patients born between 1970 and 1980 was obtained by telephone interviews and questionnaires. In addition to age of death or actual age during the investigation, data concerning clinical course and medical interventions were collected.
Results:
67 patients with molecularly confirmed diagnoses had a median survival of 24.0 years. Patients without molecular confirmation (clinical diagnosis only) had a chance of 67 % to reach that age. Grouping of our patient cohort according to the year of death (before and after 2000), ventilation was recognized as main intervention affecting survival with ventilated reaching a median survival of 27.0 years. For those without ventilation it was 19.0 years.
Conclusion and clinical relevance:
our study provides survival data for a cohort of DMD patients in Germany stratified by year of death. Median survival was 24.0 years in patients confirmed by molecular testing. Ventilated patients had a median survival of 27 years. We consider this piece of information helpful in the medical care of DMD patients.