Characterization of membrane vesicles circulating in the serum of patients with common acute lymphoblastic leukemia.

Common acute lymphoblastic leukemia antigen detected by radioimmunoassay in the serum of patients with common acute lymphoblastic leukemia was found to be exclusively associated with the pellet of the serum samples obtained by ultracentrifugation at 100,000 X g. The pellets were shown to contain membrane vesicles or fragments which were characterized by electron microscopy and determination of enzymatic activity. The pelleted fragments had an apparent diameter ranging between 60 and 260 nm and showed a trilaminar membrane structure. On freeze-fracture preparations, the fragments with concave profile, corresponding to the external fracture face of plasma membrane, displayed an intramembrane particle density (ranging from 0 to 750 particles per micron2) which is similar to that recorded on the corresponding fracture face of intact cells from the common lymphoblastic leukemia antigen positive leukemic cell line (Nalm-1) or of vesicles shed in the culture medium by Nalm-1 cells. Furthermore, analysis of the membrane enzyme marker 5'-nucleotidase in the pellet of patient's sera, showed that the presence of this enzyme correlated with that of common lymphoblastic leukemia antigen, but the quantitative relationship between the two surface constituents was not linear. The results suggest that the two markers are located on the same membrane fragments, but that their individual distribution on the shed fragments is heterogeneous.

G-CSF-induced remission in two cases of acute myeloid leukemia.

We report on two elderly patients with newly diagnosed acute myeloid leukemia (AML) who were treated in palliative intention because of comorbidities and intermediate or poor risk cytogenetics. Both received G-CSF to reduce the risk of infection related to neutropenia. Interestingly, one patient achieved a full hematological remission and the other a peripheral remission with dramatic reduction of the bone marrow blast count. Although a direct therapeutic effect of myeloid growth factors seems to be unusual in AML, the use of G-CSF or GM-CSF may be recommended in patients such as elderly patients who are not suited for intensive chemotherapy.

Targeted therapy against multi-resistant bacteria in leukemic and hematopoietic stem cell transplant recipients: guidelines of the 4th European Conference on Infections in Leukemia (ECIL-4, 2011).

The detection of multi-resistant bacterial pathogens, particularly those to carbapenemases, in leukemic and stem cell transplant patients forces the use of old or non-conventional agents as the only remaining treatment options. These include colistin/polymyxin B, tigecycline, fosfomycin and various anti-gram-positive agents. Data on the use of these agents in leukemic patients are scanty, with only linezolid subjected to formal trials. The Expert Group of the 4(th) European Conference on Infections in Leukemia has developed guidelines for their use in these patient populations. Targeted therapy should be based on (i) in vitro susceptibility data, (ii) knowledge of the best treatment option against the particular species or phenotype of bacteria, (iii) pharmacokinetic/pharmacodynamic data, and (iv) careful assessment of the risk-benefit balance. For infections due to resistant Gram-negative bacteria, these agents should be preferably used in combination with other agents that remain active in vitro, because of suboptimal efficacy (e.g., tigecycline) and the risk of emergent resistance (e.g., fosfomycin). The paucity of new antibacterial drugs in the near future should lead us to limit the use of these drugs to situations where no alternative exists.

Quelques abus de la statistique dans la recherche médicale [Various abuses of statistics in medical research].

Statistics has become an indispensable tool in biomedical research. Thanks, in particular, to computer science, the researcher has easy access to elementary "classical" procedures. These are often of a "confirmatory" nature: their aim is to test hypotheses (for example the efficacy of a treatment) prior to experimentation. However, doctors often use them in situations more complex than foreseen, to discover interesting data structures and formulate hypotheses. This inverse process may lead to misuse which increases the number of "statistically proven" results in medical publications. The help of a professional statistician thus becomes necessary. Moreover, good, simple "exploratory" techniques are now available. In addition, medical data contain quite a high percentage of outliers (data that deviate from the majority). With classical methods it is often very difficult (even for a statistician!) to detect them and the reliability of results becomes questionable. New, reliable ("robust") procedures have been the subject of research for the past two decades. Their practical introduction is one of the activities of the Statistics and Data Processing Department of the University of Social and Preventive Medicine, Lausanne.

Superiority of the Triple Combination of Bortezomib-Thalidomide-Dexamethasone Over the Dual Combination of Thalidomide-Dexamethasone in Patients With Multiple Myeloma Progressing or Relapsing After Autologous Transplantation: The MMVAR/IFM 2005-04 Randomized Phase III Trial From the Chronic Leukemia Working Party of the European Group for Blood and Marrow Transplantation.

PURPOSE This prospective multicenter phase III study compared the efficacy and safety of a triple combination (bortezomib-thalidomide-dexamethasone [VTD]) versus a dual combination (thalidomide-dexamethasone [TD]) in patients with multiple myeloma (MM) progressing or relapsing after autologous stem-cell transplantation (ASCT). PATIENTS AND METHODS Overall, 269 patients were randomly assigned to receive bortezomib (1.3 mg/m(2) intravenous bolus) or no bortezomib for 1 year, in combination with thalidomide (200 mg per day orally) and dexamethasone (40 mg orally once a day on 4 days once every 3 weeks). Bortezomib was administered on days 1, 4, 8, and 11 with a 10-day rest period (day 12 to day 21) for eight cycles (6 months), and then on days 1, 8, 15, and 22 with a 20-day rest period (day 23 to day 42) for four cycles (6 months). Results Median time to progression (primary end point) was significantly longer with VTD than TD (19.5 v 13.8 months; hazard ratio, 0.59; 95% CI, 0.44 to 0.80; P = .001), the complete response plus near-complete response rate was higher (45% v 25%; P = .001), and the median duration of response was longer (17.2 v 13.4 months; P = .03). The 24-month survival rate was in favor of VTD (71% v 65%; P = .093). Grade 3 peripheral neuropathy was more frequent with VTD (29% v 12%; P = .001) as were the rates of grades 3 and 4 infection and thrombocytopenia. CONCLUSION VTD was more effective than TD in the treatment of patients with MM with progressive or relapsing disease post-ASCT but was associated with a higher incidence of grade 3 neurotoxicity.

Detection of clusters using space-time scan statistics

This paper aims at detecting spatio-temporal clustering in fire sequences using space?time scan statistics, a powerful statistical framework for the analysis of point processes. The methodology is applied to active fire detection in the state of Florida (US) identified by MODIS (Moderate Resolution Imaging Spectroradiometer) during the period 2003?06. Results of the present study show that statistically significant clusters can be detected and localized in specific areas and periods of the year. Three out of the five most likely clusters detected for the entire frame period are localized in the north of the state, and they cover forest areas; the other two clusters cover a large zone in the south, corresponding to agricultural land and the prairies in the Everglades. In order to analyze if the wildfires recur each year during the same period, the analyses have been performed separately for the 4 years: it emerges that clusters of forest fires are more frequent in hot seasons (spring and summer), while in the southern areas, they are widely present during the whole year. The recognition of overdensities of events and the ability to locate them in space and in time can help in supporting fire management and focussing on prevention measures.

Arsenic trioxide-based therapy of relapsed acute promyelocytic leukemia: registry results from the European LeukemiaNet.

In 2008, a European registry of relapsed acute promyelocytic leukemia was established by the European LeukemiaNet. Outcome data were available for 155 patients treated with arsenic trioxide in first relapse. In hematological relapse (n=104), 91% of the patients entered complete hematological remission (CR), 7% had induction death and 2% resistance, 27% developed differentiation syndrome and 39% leukocytosis, whereas no death or side effects occurred in patients treated in molecular relapse (n=40). The rate of molecular (m)CR was 74% in hematological and 62% in molecular relapse (P=0.3). All patients with extramedullary relapse (n=11) entered clinical and mCR. After 3.2 years median follow-up, the 3-year overall survival (OS) and cumulative incidence of second relapse were 68% and 41% in hematological relapse, 66% and 48% in molecular relapse and 90 and 11% in extramedullary relapse, respectively. After allogeneic or autologous transplantation in second CR (n=93), the 3-year OS was 80% compared with 59% without transplantation (n=55) (P=0.03). Multivariable analysis demonstrated the favorable prognostic impact of first remission duration ⩾1.5 years, achievement of mCR and allogeneic or autologous transplantation on OS of patients alive after induction (P=0.03, P=0.01, P=0.01) and on leukemia-free survival (P=0.006, P<0.0001, P=0.003), respectively.

Populating ACT-R's Declarative Memory with Internet Statistics

Decision situations are often characterized by uncertainty: we do not know the values of the different options on all attributes and have to rely on information stored in our memory to decide. Several strategies have been proposed to describe how people make inferences based on knowledge used as cues. The present research shows how declarative memory of ACT-R models could be populated based on internet statistics. This will allow to simulate the performance of decision strategies operating on declarative knowledge based on occurrences and co-occurrences of objects and cues in the environment.

Conditioning of multiple-point statistics facies simulations to tomographic images

Geophysical tomography captures the spatial distribution of the underlying geophysical property at a relatively high resolution, but the tomographic images tend to be blurred representations of reality and generally fail to reproduce sharp interfaces. Such models may cause significant bias when taken as a basis for predictive flow and transport modeling and are unsuitable for uncertainty assessment. We present a methodology in which tomograms are used to condition multiple-point statistics (MPS) simulations. A large set of geologically reasonable facies realizations and their corresponding synthetically calculated cross-hole radar tomograms are used as a training image. The training image is scanned with a direct sampling algorithm for patterns in the conditioning tomogram, while accounting for the spatially varying resolution of the tomograms. In a post-processing step, only those conditional simulations that predicted the radar traveltimes within the expected data error levels are accepted. The methodology is demonstrated on a two-facies example featuring channels and an aquifer analog of alluvial sedimentary structures with five facies. For both cases, MPS simulations exhibit the sharp interfaces and the geological patterns found in the training image. Compared to unconditioned MPS simulations, the uncertainty in transport predictions is markedly decreased for simulations conditioned to tomograms. As an improvement to other approaches relying on classical smoothness-constrained geophysical tomography, the proposed method allows for: (1) reproduction of sharp interfaces, (2) incorporation of realistic geological constraints and (3) generation of multiple realizations that enables uncertainty assessment.