IGFBP7 participates in the reciprocal interaction between acute lymphoblastic leukemia and BM stromal cells and in leukemia resistance to asparaginase

The interaction of acute lymphoblastic leukemia (ALL) blasts with bone marrow (BM) stromal cells (BMSCs) has a positive impact on ALL resistance to chemotherapy. We investigated the modulation of a series of putative asparaginase-resistance/sensitivity genes in B-precursor ALL cells upon coculture with BMSCs. Coculture with stromal cells resulted in increased insulin-like growth factor (IGF)-binding protein 7 (IGFBP7) expression by ALL cells. Assays with IGFBP7 knockdown ALL and stromal cell lines, or with addition of recombinant rIGFBP7 (rIGFBP7) to the culture medium, showed that IGFBP7 acts as a positive regulator of ALL and stromal cells growth, and significantly enhances in-vitro resistance of ALL to asparaginase. In these assays, IGFBP7 function occurred mainly in an insulin-and stromal-dependent manner. ALL cells were found to contribute substantially to extracellular IGFBP7 levels in the conditioned coculture medium. Diagnostic BM plasma from children with ALL had higher levels of IGFBP7 than controls. IGFBP7, in an insulin/IGF-dependent manner, enhanced asparagine synthetase expression and asparagine secretion by BMSCs, thus providing a stromal-dependent mechanism by which IGFBP7 protects ALL cells against asparaginase in this coculture system. Importantly, higher IGFBP7 mRNA levels were associated with lower leukemia-free survival (Cox regression model, P = 0.003) in precursor B-cell Ph(-) ALL patients (n = 147) treated with a contemporary polychemotherapy protocol.

Urinary MCP-1 and RBP: Independent predictors of renal outcome in macroalbuminuric diabetic nephropathy

Background: Albuminuria has been considered a sine qua non condition for the diagnosis of diabetic nephropathy (DN) and has been widely used as a surrogate outcome of chronic kidney disease (CKD). However, recent data suggest that albuminuria may fail as a biomarker in a subset of patients, and the search for novel markers is intense. Methods: We analyzed the role of urinary RBP and of serum and urinary cytokines (TGF-beta, MCP-1 and VEGF) as predictors of the risk of dialysis. doubling of serum creatinine or death (primary outcome. PO) in 56 type 2 diabetic patients with macroalbuminuric DN. Results: Mean follow-up time was 30.7 +/- 10 months. Urinary RBP and MCP-1 were significantly higher in patients presenting the PO, whereas no difference was shown for TGF-beta or VEGF. In the Cox regression, urinary RBP. MCP-1 and VEGF were positively associated and serum VEGF was inversely related to the risk of the PO. However, after adjustments for creatinine clearance, proteinuria, and blood pressure only urinary RBP (OR 11.6; 95% CI 2.7-49.2, p = 0.001 for log RBP) and urinary MCP-1 (OR 11.0; 95% CI 1.6-76.4, p = 0.02 for log MCP-1) remained as significant independent predictors of the PO. Conclusion: Urinary RBP and MCP-1 are independently related to the risk of CKD progression in patients with macroalbuminuric DN. Whether these biomarkers have a role in the setting of normoalbuminuria and microalbuminuria in DN should be further investigated. (C) 2012 Elsevier Inc. All rights reserved.

Duration of dual antiplatelet therapy and outcomes after coronary stenting with the genous (TM) bio-engineered R stent (TM) in patients from the e-healing registry

Objective: We investigated the relation between duration of dual antiplatelet therapy (DAPT) and clinical outcomes up to 12 months after Genous (TM) endothelial progenitor cell capturing R stent (TM) placement in patients from the e-HEALING registry. Background: Cessation of (DAPT) has been shown to be associated with the occurrence of stent thrombosis (ST). After Genous placement, 1 month of DAPT is recommended. Methods: Patients were analyzed according to continuation or discontinuation of DAPT at a 30-day and 6-month landmark, excluding patients with events before the landmark. Each landmark was a new baseline, and outcomes were followed up to 12 months after stenting. The main outcome for our current analysis was target vessel failure (TVF), defined as target vessel-related cardiac death or myocardial infarction and target vessel revascularization. Secondary outcomes included ST. (Un)adjusted hazard ratios (HR) for TVF were calculated with Cox regression. Results: No difference was observed in the incidence of TVF [HR: 1.03; 95% confidence intervals (CI): 0.651.65, P = 0.89] in patients continuing DAPT (n = 4,249) at 30 days versus patients stopped (n = 309), and HR: 0.82 (95% CI: 0.551.23, P = 0.34) in patients continuing DAPT (n = 2,654) at 6 months versus patients stopped [n = 1,408] DAPT). Furthermore, no differences were observed in ST. Even after addition of identified independent predictors for TVF, adjusted TVF hazards were comparable. Conclusions: In a post-hoc analysis of e-HEALING, duration of DAPT was not associated with the occurrence of the outcomes TVF or ST. The Genous stent may be an attractive treatment especially in patients at increased risk for (temporary) cessation of DAPT or bleeding. (C) 2011 Wiley Periodicals, Inc.

Retrospective Clinical Study of 988 Dual Acid-Etched Implants Placed in Grafted and Native Bone for Single-Tooth Replacement

Purpose: To evaluate the influence of sex, implant characteristics, and bone grafting on the survival rate of dual acid-etched (DAE) implants. Materials and Methods: Patients treated with internal-hex DAE implants for single-tooth replacement in a military dental clinic between January 2005 and December 2010 were included in this study. Clinical data related to implant characteristics, implant location, presence of grafted bone, and implant failures were collected. The primary outcome was implant loss. The survival rate was analyzed using the Kaplan-Meier method. Cox regression modeling was used to determine which factors would predict implant failure. Results: DAE implants were evaluated in a total of 988 patients (80.3% men). Twenty-four (2.4%) implants failed, most were cylindric (54.2%) with regular platforms (70.8%) and were 10 mm long (58.3%). The failure rate was 2.4% for the anterior maxilla, 3.3% for the posterior maxilla, 1.6% for the anterior mandible, and 2.0% for posterior mandible. The cumulative survival rate was 97.6%. The failure rate was 8.8% in implants placed after sinus augmentation, 7.3% in bone block-grafted areas, and 1.6% in native bone. Based on multivariable analysis (Cox regression), sinus augmentation and bone block grafting had a statistically significant effect on implant failure; the hazard ratios were 5.5 and 4.6, respectively. Conclusion: The results revealed that DAE implants had high survival rates, and no influence of sex, location, shape, diameter, or length on failure rates could be observed. However, a significant association was observed between failure and presence of bone graft in the implant area. Int J Oral Maxillofac Implants 2012;27:1243-1248

Association between systemic corticosteroids and outcomes of intensive care unit-acquired pneumonia

Objective: The use of corticosteroids is frequent in critically-ill patients. However, little information is available on their effects in patients with intensive care unit acquired pneumonia. We assessed patients' characteristics, microbial etiology, inflammatory response, and outcomes of previous corticosteroid use in patients with intensive care unit acquired pneumonia. Design: Prospective observational study. Setting: Intensive care units of a university teaching hospital. Patients: Three hundred sixteen patients with intensive care unit acquired pneumonia. Patients were divided according to previous systemic steroid use at onset of pneumonia. Interventions: None. Measurements and Main Results: Survival at 28 days was analyzed using Cox regression, with adjustment for the propensity for receiving steroid therapy. One hundred twenty-five (40%) patients were receiving steroids at onset of pneumonia. Despite similar baseline clinical severity, steroid treatment was associated with decreased 28-day survival (adjusted hazard ratio for propensity score and mortality predictors 2.503; 95% confidence interval 1.176-5.330; p = .017) and decreased systemic inflammatory response. In post hoc analyses, steroid treatment had an impact on survival in patients with nonventilator intensive care unit acquired pneumonia, those with lower baseline severity and organ dysfunction, and those without etiologic diagnosis or bacteremia. The cumulative dosage of corticosteroids had no significant effect on the risk of death, but bacterial burden upon diagnosis was higher in patients receiving steroid therapy. Conclusions: In critically-ill patients, systemic corticosteroids should be used very cautiously because this treatment is strongly associated with increased risk of death in patients with intensive care unit acquired pneumonia, particularly in the absence of established indications and in patients with lower baseline severity. Decreased inflammatory response may result in delayed clinical suspicion of intensive care unit acquired pneumonia and higher bacterial count. (Crit Care Med 2012; 40:2552-2561)

The relationship between lymphatic vascular density and vascular endothelial growth factor A (VEGF-A) expression with clinical-pathological features and survival in pancreatic adenocarcinomas

Abstract: Background Pancreatic cancer is a rare tumor with an extremely low survival rate. Its known risk factors include the chronic use of tobacco and excessive alcohol consumption and the presence of chronic inflammatory diseases, such as pancreatitis and type 2 diabetes. Angiogenesis and lymphangiogenesis, which have been the focus of recent research, are considered prognostic factors for cancer development. Knowing the angiogenic and lymphangiogenic profiles of a tumor may provide new insights for designing treatments according to the different properties of the tumor. The aim of this study was to evaluate the density of blood and lymphatic vessels, and the expression of VEGF-A, in pancreatic adenocarcinomas, as well as the relationship between blood and lymphatic vascular density and the prognostically important clinical-pathological features of pancreatic tumors. Methods Paraffin blocks containing tumor samples from 100 patients who were diagnosed with pancreatic cancer between 1990 and 2010 were used to construct a tissue microarray. VEGF expression was assessed in these samples by immunohistochemistry. To assess the lymphatic and vascular properties of the tumors, 63 cases that contained sufficient material were sectioned routinely. The sections were then stained with the D2-40 antibody to identify the lymphatic vessels and with a CD34 antibody to identify the blood vessels. The vessels were counted individually with the Leica Application Suite v4 program. All statistical analyses were performed using SPSS 18.0 (Chicago, IL, USA) software, and p values ≤ 0.05 were considered significant. Results In the Cox regression analysis, advanced age (p=0.03) and a history of type 2 diabetes (p=0.014) or chronic pancreatitis (p=0.02) were shown to be prognostic factors for pancreatic cancer. Blood vessel density (BVD) had no relationship with clinical-pathological features or death. Lymphatic vessel density (LVD) was inversely correlated with death (p=0.002), and by Kaplan-Meyer survival analysis, we found a significant association between low LVD (p=0.021), VEGF expression (p=0.023) and low patient survival. Conclusions Pancreatic carcinogenesis is related to a history of chronic inflammatory processes, such as type 2 diabetes and chronic pancreatitis. In pancreatic cancer development, lymphangiogenesis can be considered an early event that enables the dissemination of metastases. VEGF expression and low LVD can be considered as poor prognostic factors as tumors with this profile are fast growing and highly aggressive. Virtual slides. The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/5113892881028514

Survival Analysis of Patients with Heart Failure: Implications of Time-Varying Regression Effects in Modeling Mortality

Background: Several models have been designed to predict survival of patients with heart failure. These, while available and widely used for both stratifying and deciding upon different treatment options on the individual level, have several limitations. Specifically, some clinical variables that may influence prognosis may have an influence that change over time. Statistical models that include such characteristic may help in evaluating prognosis. The aim of the present study was to analyze and quantify the impact of modeling heart failure survival allowing for covariates with time-varying effects known to be independent predictors of overall mortality in this clinical setting. Methodology: Survival data from an inception cohort of five hundred patients diagnosed with heart failure functional class III and IV between 2002 and 2004 and followed-up to 2006 were analyzed by using the proportional hazards Cox model and variations of the Cox's model and also of the Aalen's additive model. Principal Findings: One-hundred and eighty eight (188) patients died during follow-up. For patients under study, age, serum sodium, hemoglobin, serum creatinine, and left ventricular ejection fraction were significantly associated with mortality. Evidence of time-varying effect was suggested for the last three. Both high hemoglobin and high LV ejection fraction were associated with a reduced risk of dying with a stronger initial effect. High creatinine, associated with an increased risk of dying, also presented an initial stronger effect. The impact of age and sodium were constant over time. Conclusions: The current study points to the importance of evaluating covariates with time-varying effects in heart failure models. The analysis performed suggests that variations of Cox and Aalen models constitute a valuable tool for identifying these variables. The implementation of covariates with time-varying effects into heart failure prognostication models may reduce bias and increase the specificity of such models.

The role of clouds in improving the regression model for hourly values of diffuse solar radiation

The study introduces a new regression model developed to estimate the hourly values of diffuse solar radiation at the surface. The model is based on the clearness index and diffuse fraction relationship, and includes the effects of cloud (cloudiness and cloud type), traditional meteorological variables (air temperature, relative humidity and atmospheric pressure observed at the surface) and air pollution (concentration of particulate matter observed at the surface). The new model is capable of predicting hourly values of diffuse solar radiation better than the previously developed ones (R-2 = 0.93 and RMSE = 0.085). A simple version with a large applicability is proposed that takes into consideration cloud effects only (cloudiness and cloud height) and shows a R-2 = 0.92. (C) 2011 Elsevier Ltd. All rights reserved.

Estimation and diagnostics for heteroscedastic nonlinear regression models based on scale mixtures of skew-normal distributions

An extension of some standard likelihood based procedures to heteroscedastic nonlinear regression models under scale mixtures of skew-normal (SMSN) distributions is developed. This novel class of models provides a useful generalization of the heteroscedastic symmetrical nonlinear regression models (Cysneiros et al., 2010), since the random term distributions cover both symmetric as well as asymmetric and heavy-tailed distributions such as skew-t, skew-slash, skew-contaminated normal, among others. A simple EM-type algorithm for iteratively computing maximum likelihood estimates of the parameters is presented and the observed information matrix is derived analytically. In order to examine the performance of the proposed methods, some simulation studies are presented to show the robust aspect of this flexible class against outlying and influential observations and that the maximum likelihood estimates based on the EM-type algorithm do provide good asymptotic properties. Furthermore, local influence measures and the one-step approximations of the estimates in the case-deletion model are obtained. Finally, an illustration of the methodology is given considering a data set previously analyzed under the homoscedastic skew-t nonlinear regression model. (C) 2012 Elsevier B.V. All rights reserved.

The geometric Birnbaum-Saunders regression model with cure rate

In this paper, we propose a cure rate survival model by assuming the number of competing causes of the event of interest follows the Geometric distribution and the time to event follow a Birnbaum Saunders distribution. We consider a frequentist analysis for parameter estimation of a Geometric Birnbaum Saunders model with cure rate. Finally, to analyze a data set from the medical area. (C) 2011 Elsevier B.V. All rights reserved.

THE LOG-BURR XII REGRESSION MODEL FOR GROUPED SURVIVAL DATA

The log-Burr XII regression model for grouped survival data is evaluated in the presence of many ties. The methodology for grouped survival data is based on life tables, where the times are grouped in k intervals, and we fit discrete lifetime regression models to the data. The model parameters are estimated by maximum likelihood and jackknife methods. To detect influential observations in the proposed model, diagnostic measures based on case deletion, so-called global influence, and influence measures based on small perturbations in the data or in the model, referred to as local influence, are used. In addition to these measures, the total local influence and influential estimates are also used. We conduct Monte Carlo simulation studies to assess the finite sample behavior of the maximum likelihood estimators of the proposed model for grouped survival. A real data set is analyzed using a regression model for grouped data.

Local power properties of some asymptotic tests in symmetric linear regression models

In this paper we obtain asymptotic expansions, up to order n(-1/2) and under a sequence of Pitman alternatives, for the nonnull distribution functions of the likelihood ratio, Wald, score and gradient test statistics in the class of symmetric linear regression models. This is a wide class of models which encompasses the t model and several other symmetric distributions with longer-than normal tails. The asymptotic distributions of all four statistics are obtained for testing a subset of regression parameters. Furthermore, in order to compare the finite-sample performance of these tests in this class of models, Monte Carlo simulations are presented. An empirical application to a real data set is considered for illustrative purposes. (C) 2011 Elsevier B.V. All rights reserved.

Error Autocorrelation and Linear Regression for Temperature-Based Evapotranspiration Estimates Improvement

Estimates of evapotranspiration on a local scale is important information for agricultural and hydrological practices. However, equations to estimate potential evapotranspiration based only on temperature data, which are simple to use, are usually less trustworthy than the Food and Agriculture Organization (FAO)Penman-Monteith standard method. The present work describes two correction procedures for potential evapotranspiration estimates by temperature, making the results more reliable. Initially, the standard FAO-Penman-Monteith method was evaluated with a complete climatologic data set for the period between 2002 and 2006. Then temperature-based estimates by Camargo and Jensen-Haise methods have been adjusted by error autocorrelation evaluated in biweekly and monthly periods. In a second adjustment, simple linear regression was applied. The adjusted equations have been validated with climatic data available for the Year 2001. Both proposed methodologies showed good agreement with the standard method indicating that the methodology can be used for local potential evapotranspiration estimates.

The Poisson-exponential regression model under different latent activation schemes

In this paper, a new family of survival distributions is presented. It is derived by considering that the latent number of failure causes follows a Poisson distribution and the time for these causes to be activated follows an exponential distribution. Three different activation schemes are also considered. Moreover, we propose the inclusion of covariates in the model formulation in order to study their effect on the expected value of the number of causes and on the failure rate function. Inferential procedure based on the maximum likelihood method is discussed and evaluated via simulation. The developed methodology is illustrated on a real data set on ovarian cancer.

Examination of the performance of different pointwise linear regression progression criteria to detect glaucomatous visual field change

Background: We aimed to investigate the performance of five different trend analysis criteria for the detection of glaucomatous progression and to determine the most frequently and rapidly progressing locations of the visual field. Design: Retrospective cohort. Participants or Samples: Treated glaucoma patients with =8 Swedish Interactive Thresholding Algorithm (SITA)-standard 24-2 visual field tests. Methods: Progression was determined using trend analysis. Five different criteria were used: (A) =1 significantly progressing point; (B) =2 significantly progressing points; (C) =2 progressing points located in the same hemifield; (D) at least two adjacent progressing points located in the same hemifield; (E) =2 progressing points in the same Garway-Heath map sector. Main Outcome Measures: Number of progressing eyes and false-positive results. Results: We included 587 patients. The number of eyes reaching a progression endpoint using each criterion was: A = 300 (51%); B = 212 (36%); C = 194 (33%); D = 170 (29%); and E = 186 (31%) (P = 0.03). The numbers of eyes with positive slopes were: A = 13 (4.3%); B = 3 (1.4%); C = 3 (1.5%); D = 2 (1.1%); and E = 3 (1.6%) (P = 0.06). The global slopes for progressing eyes were more negative in Groups B, C and D than in Group A (P = 0.004). The visual field locations that progressed more often were those in the nasal field adjacent to the horizontal midline. Conclusions: Pointwise linear regression criteria that take into account the retinal nerve fibre layer anatomy enhances the specificity of trend analysis for the detection glaucomatous visual field progression.