In situ RHAMM protein expression in acute myeloid leukemia blasts suggests poor overall survival.

Treatment options for patients with high-risk acute myeloid leukemia (AML) include high-dose chemotherapy regimens in combination with allogeneic hematopoietic stem cell transplantation, which takes advantage of the donor T-cell-mediated graft-versus-leukemia effect. Together with beneficial responses observed in assays targeted at leukemia-associated antigens (LAA), this encouraged research on cancer vaccines and adoptive cellular therapies in AML. The receptor for hyaluronic acid-mediated motility (RHAMM, CD168) was identified as one of the most promising LAA in AML. Thus far, little is known about in situ expression in leukemic bone marrow blasts or the prognostic role of RHAMM and its interaction partners in AML. We immunohistochemically analyzed the expression and prognostic significance of RHAMM on trephine bone marrow biopsies from 71 AML cases that had been evaluated for cytogenetics and presence of FLT3-internal tandem duplications and NPM1 mutations. Fifty-five patients (77%) were treated with curative intent, while 16 (23%) received the most appropriate supportive care. Twenty of 71 (28%) AML cases were considered RHAMM+. Receiver operating characteristic curves showed significant discriminatory power considering overall survival (OS) in AML patients treated curatively for RHAMM (p = 0.015). Multivariable analysis revealed that expression of RHAMM in >5% of leukemic blasts identifies a subgroup of curatively treated cases with adverse OS independent of failures to achieve complete remission. RHAMM not only represents a promising LAA with specific T-cell responses in AML but, if assessed in situ on blasts, also a probable prognostic factor.

Spine bone texture assessed by trabecular bone score (TBS) predicts osteoporotic fractures in men: The Manitoba Bone Density Program.

INTRODUCTION: One quarter of osteoporotic fractures occur in men. TBS, a gray-level measurement derived from lumbar spine DXA image texture, is related to microarchitecture and fracture risk independently of BMD. Previous studies reported the ability of spine TBS to predict osteoporotic fractures in women. Our aim was to evaluate the ability of TBS to predict clinical osteoporotic fractures in men. METHODS: 3620 men aged ≥50 (mean 67.6years) at the time of baseline DXA (femoral neck, spine) were identified from a database (Province of Manitoba, Canada). Health service records were assessed for the presence of non-traumatic osteoporotic fracture after BMD testing. Lumbar spine TBS was derived from spine DXA blinded to clinical parameters and outcomes. We used Cox proportional hazard regression to analyze time to first fracture adjusted for clinical risk factors (FRAX without BMD), osteoporosis treatment and BMD (hip or spine). RESULTS: Mean followup was 4.5years. 183 (5.1%) men sustain major osteoporotic fractures (MOF), 91 (2.5%) clinical vertebral fractures (CVF), and 46 (1.3%) hip fractures (HF). Correlation between spine BMD and spine TBS was modest (r=0.31), less than correlation between spine and hip BMD (r=0.63). Significantly lower spine TBS were found in fracture versus non-fracture men for MOF (p<0.001), HF (p<0.001) and CVF (p=0.003). Area under the receiver operating characteristic curve (AUC) for incident fracture discrimination with TBS was significantly better than chance (MOF AUC=0.59, p<0.001; HF AUC=0.67, p<0.001; CVF AUC=0.57, p=0.032). TBS predicted MOF and HF (but not CVF) in models adjusted for FRAX without BMD and osteoporosis treatment. TBS remained a predictor of HF (but not MOF) after further adjustment for hip BMD or spine BMD. CONCLUSION: We observed that spine TBS predicted MOF and HF independently of the clinical FRAX score, HF independently of FRAX and BMD in men. Studies with more incident fractures are needed to confirm these findings.

Effects of sample size on the performance of species distribution models

A wide range of modelling algorithms is used by ecologists, conservation practitioners, and others to predict species ranges from point locality data. Unfortunately, the amount of data available is limited for many taxa and regions, making it essential to quantify the sensitivity of these algorithms to sample size. This is the first study to address this need by rigorously evaluating a broad suite of algorithms with independent presence-absence data from multiple species and regions. We evaluated predictions from 12 algorithms for 46 species (from six different regions of the world) at three sample sizes (100, 30, and 10 records). We used data from natural history collections to run the models, and evaluated the quality of model predictions with area under the receiver operating characteristic curve (AUC). With decreasing sample size, model accuracy decreased and variability increased across species and between models. Novel modelling methods that incorporate both interactions between predictor variables and complex response shapes (i.e. GBM, MARS-INT, BRUTO) performed better than most methods at large sample sizes but not at the smallest sample sizes. Other algorithms were much less sensitive to sample size, including an algorithm based on maximum entropy (MAXENT) that had among the best predictive power across all sample sizes. Relative to other algorithms, a distance metric algorithm (DOMAIN) and a genetic algorithm (OM-GARP) had intermediate performance at the largest sample size and among the best performance at the lowest sample size. No algorithm predicted consistently well with small sample size (n < 30) and this should encourage highly conservative use of predictions based on small sample size and restrict their use to exploratory modelling.

A comparison of Bayesian and frequentist approaches to incorporating external information for the prediction of prostate cancer risk.

We present the most comprehensive comparison to date of the predictive benefit of genetics in addition to currently used clinical variables, using genotype data for 33 single-nucleotide polymorphisms (SNPs) in 1,547 Caucasian men from the placebo arm of the REduction by DUtasteride of prostate Cancer Events (REDUCE®) trial. Moreover, we conducted a detailed comparison of three techniques for incorporating genetics into clinical risk prediction. The first method was a standard logistic regression model, which included separate terms for the clinical covariates and for each of the genetic markers. This approach ignores a substantial amount of external information concerning effect sizes for these Genome Wide Association Study (GWAS)-replicated SNPs. The second and third methods investigated two possible approaches to incorporating meta-analysed external SNP effect estimates - one via a weighted PCa 'risk' score based solely on the meta analysis estimates, and the other incorporating both the current and prior data via informative priors in a Bayesian logistic regression model. All methods demonstrated a slight improvement in predictive performance upon incorporation of genetics. The two methods that incorporated external information showed the greatest receiver-operating-characteristic AUCs increase from 0.61 to 0.64. The value of our methods comparison is likely to lie in observations of performance similarities, rather than difference, between three approaches of very different resource requirements. The two methods that included external information performed best, but only marginally despite substantial differences in complexity.

Fitness to drive and cannabis: Experimental and real-life case study validation of two blood THCCOOH thresholds to distinguish occasional users from heavy smokers

Introduction: THC-COOH has been proposed as a criterion to help to distinguish between occasional from regular cannabis users. However, to date this indicator has not been adequately assessed under experimental and real-life conditions. Methods: We carried out a controlled administration study of smoked cannabis with a placebo. Twenty-three heavy smokers and 25 occasional smokers, between 18 and 30 years of age, participated in this study [Battistella G et al., PloS one. 2013;8(1):e52545]. We collected data from a second real case study performed with 146 traffic offenders' cases in which the whole blood cannabinoid concentrations and the frequency of cannabis use were known. Cannabinoid levels were determined in whole blood using tandem mass spectrometry methods. Results: Significantly high differences in THC-COOH concentrations were found between the two groups when measured during the screening visit, prior to the smoking session, and throughout the day of the experiment. Receiver operating characteristic (ROC) curves were determined and two threshold criteria were proposed in order to distinguish between these groups: a free THC-COOH concentration below 3 μg/L suggested an occasional consumption (≤ 1 joint/week) while a concentration higher than 40 μg/L corresponded to a heavy use (≥ 10 joints/month). These thresholds were successfully tested with the second real case study. The two thresholds were not challenged by the presence of ethanol (40% of cases) and of other therapeutic and illegal drugs (24%). These thresholds were also found to be consistent with previously published experimental data. Conclusion: We propose the following procedure that can be very useful in the Swiss context but also in other countries with similar traffic policies: If the whole blood THC-COOH concentration is higher than 40 μg/L, traffic offenders must be directed first and foremost toward medical assessment of their fitness to drive. This evaluation is not recommended if the THC-COOH concentration is lower than 3 μg/L. A THC-COOH level between these two thresholds can't be reliably interpreted. In such a case, further medical assessment and follow up of the fitness to drive are also suggested, but with lower priority.

A multi-temporal approach to model endangered species distribution in Europe: the case of the Eurasian otter in Italy

We analysed the relationship between changes in land cover patterns and the Eurasian otter occurrence over the course of about 20 years (1985-2006) using multi-temporal Species Distribution Models (SDMs). The study area includes five river catchments covering most of the otter's Italian range. Land cover and topographic data were used as proxies of the ecological requirements of the otter within a 300-m buffer around river courses. We used species presence, pseudo-absence data, and environmental predictors to build past (1985) and current (2006) SDMs by applying an ensemble procedure through the BIOMOD modelling package. The performance of each model was evaluated by measuring the area under the curve (AUC) of the receiver-operating characteristic (ROC). Multi-temporal analyses of species distribution and land cover maps were performed by comparing the maps produced for 1985 and 2006. The ensemble procedure provided a good overall modelling accuracy, revealing that elevation and slope affected the otter's distribution in the past; in contrast, land cover predictors, such as cultivations and forests, were more important in the present period. During the transition period, 20.5% of the area became suitable, with 76% of the new otter presence data being located in these newly available areas. The multi-temporal analysis suggested that the quality of otter habitat improved in the last 20 years owing to the expansion of forests and to the reduction of cultivated fields in riparian belts. The evidence presented here stresses the great potential of riverine habitat restoration and environmental management for the future expansion of the otter in Italy

Prospective comparison of clinical prognostic scores in elderly patients with pulmonary embolism.

Background: The Geneva Prognostic Score (GPS), the Pulmonary Embolism Severity Index (PESI), and its simplified version (sPESI) are well known clinical prognostic scores for pulmonary embolism (PE).Objectives: To compare the prognostic performance of these scores in elderly patients with PE. Patients/Methods: In a multicenter Swiss cohort of elderly patients with venous thromboembolism, we prospectively studied 449 patients aged ≥65 years with symptomatic PE. The outcome was 30-day overall mortality. We dichotomized patients as low- vs. higher-risk in all three scores using the following thresholds: GPS scores ≤2 vs. >2, PESI risk classes I-II vs. III-V, and sPESI scores 0 vs. ≥1. We compared 30-day mortality in low- vs. higher-risk patients and the areas under the receiver operating characteristic curve (ROC). Results: Overall, 3.8% of patients (17/449) died within 30 days. The GPS classified a greater proportion of patients as low risk (92% [413/449]) than the PESI (36.3% [163/449]) and the sPESI (39.6% [178/449]) (P<0.001 for each comparison). Low-risk patients based on the sPESI had a mortality of 0% (95% confidence interval [CI] 0-2.1%) compared to 0.6% (95% CI 0-3.4%) for low-risk patients based on the PESI and 3.4% (95% CI 1.9-5.6%) for low-risk patients based on the GPS. The areas under the ROC curves were 0.77 (95%CI 0.72-0.81), 0.76 (95% CI 0.72-0.80), and 0.71 (95% CI 0.66-0.75), respectively (P=0.47). Conclusions: In this cohort of elderly patients with PE, the GPS identified a higher proportion of patients as low-risk but the PESI and sPESI were more accurate in predicting mortality.

Validation of a model to predict adverse outcomes in patients with pulmonary embolism.

AIMS: To validate a model for quantifying the prognosis of patients with pulmonary embolism (PE). The model was previously derived from 10 534 US patients. METHODS AND RESULTS: We validated the model in 367 patients prospectively diagnosed with PE at 117 European emergency departments. We used baseline data for the model's 11 prognostic variables to stratify patients into five risk classes (I-V). We compared 90-day mortality within each risk class and the area under the receiver operating characteristic curve between the validation and the original derivation samples. We also assessed the rate of recurrent venous thrombo-embolism and major bleeding within each risk class. Mortality was 0% in Risk Class I, 1.0% in Class II, 3.1% in Class III, 10.4% in Class IV, and 24.4% in Class V and did not differ between the validation and the original derivation samples. The area under the curve was larger in the validation sample (0.87 vs. 0.78, P=0.01). No patients in Classes I and II developed recurrent thrombo-embolism or major bleeding. CONCLUSION: The model accurately stratifies patients with PE into categories of increasing risk of mortality and other relevant complications. Patients in Risk Classes I and II are at low risk of adverse outcomes and are potential candidates for outpatient treatment.

Urinary low-molecular-weight protein excretion in pediatric idiopathic nephrotic syndrome.

BACKGROUND: Minimal change disease (MCD) and focal segmental glomerulosclerosis (FSGS) are the most common causes of idiopathic nephrotic syndrome (INS). We have evaluated the reliability of urinary neutrophil-gelatinase-associated lipocalin (uNGAL), urinary alpha1-microglobulin (uα1M) and urinary N-acetyl-beta-D-glucosaminidase (uβNAG) as markers for differentiating MCD from FSGS. We have also evaluated whether these proteins are associated to INS relapses or to glomerular filtration rate (GFR). METHODS: The patient cohort comprised 35 children with MCD and nine with FSGS; 19 healthy age-matched children were included in the study as controls. Of the 35 patients, 28 were in remission (21 MCD, 7 FSGS) and 16 were in relapse (14 MCD, 2 FSGS). The prognostic accuracies of these proteins were assessed by receiver operating characteristic (ROC) curve analyses. RESULTS: The level of uNGAL, indexed or not to urinary creatinine (uCreat), was significantly different between children with INS and healthy children (p = 0.02), between healthy children and those with FSGS (p = 0.007) and between children with MCD and those with FSGS (p = 0.01). It was not significantly correlated to proteinuria or GFR levels. The ROC curve analysis showed that a cut-off value of 17 ng/mg for the uNGAL/uCreat ratio could be used to distinguish MCD from FSGS with a sensitivity of 0.77 and specificity of 0.78. uβNAG was not significantly different in patients with MCD and those with FSGS (p = 0.86). Only uα1M, indexed or not to uCreat, was significantly (p < 0.001) higher for patients in relapse compared to those in remission. CONCLUSIONS: Our results indicate that in our patient cohort uNGAL was a reliable biomarker for differentiating MCD from FSGS independently of proteinuria or GFR levels.

Clinical implications in the shift of syndecan-1 expression from the cell membrane to the cytoplasm in bladder cancer

Background To determine the diagnostic and prognostic capability of urinary and tumoral syndecan-1 (SDC-1) levels in patients with cancer of the urinary bladder. Methods SDC-1 levels were quantitated by enzyme-linked immunosorbent assay (ELISA) in 308 subjects (102 cancer subjects and 206 non-cancer subjects) to assess its diagnostic capabilities in voided urine. The performance of SDC-1 was evaluated using the area under the curve of a receiver operating characteristic curve. In addition, immunohistochemical (IHC) staining assessed SDC-1 protein expression in 193 bladder specimens (185 cancer subjects and 8 non-cancer subjects). Outcomes were correlated to SDC-1 levels. Results Mean urinary levels of SDC-1 did not differ between the cancer subjects and the non-cancer subjects, however, the mean urinary levels of SDC-1 were reduced in high-grade compared to low-grade disease (p < 0.0001), and in muscle invasive bladder cancer (MIBC) compared to non-muscle invasive bladder cancer (NMIBC) (p = 0.005). Correspondingly, preliminary data note a shift from a membranous cellular localization of SDC-1 in normal tissue, low-grade tumors and NMIBC, to a distinctly cytoplasmic localization in high-grade tumors and MIBC was observed in tissue specimens. Conclusion Alone urinary SDC-1 may not be a diagnostic biomarker for bladder cancer, but its urinary levels and cellular localization were associated with the differentiation status of patients with bladder tumors. Further studies are warranted to define the potential role for SDC-1 in bladder cancer progression.

Clinical implications in the shift of syndecan-1 expression from the cell membrane to the cytoplasm in bladder cancer

Background To determine the diagnostic and prognostic capability of urinary and tumoral syndecan-1 (SDC-1) levels in patients with cancer of the urinary bladder. Methods SDC-1 levels were quantitated by enzyme-linked immunosorbent assay (ELISA) in 308 subjects (102 cancer subjects and 206 non-cancer subjects) to assess its diagnostic capabilities in voided urine. The performance of SDC-1 was evaluated using the area under the curve of a receiver operating characteristic curve. In addition, immunohistochemical (IHC) staining assessed SDC-1 protein expression in 193 bladder specimens (185 cancer subjects and 8 non-cancer subjects). Outcomes were correlated to SDC-1 levels. Results Mean urinary levels of SDC-1 did not differ between the cancer subjects and the non-cancer subjects, however, the mean urinary levels of SDC-1 were reduced in high-grade compared to low-grade disease (p < 0.0001), and in muscle invasive bladder cancer (MIBC) compared to non-muscle invasive bladder cancer (NMIBC) (p = 0.005). Correspondingly, preliminary data note a shift from a membranous cellular localization of SDC-1 in normal tissue, low-grade tumors and NMIBC, to a distinctly cytoplasmic localization in high-grade tumors and MIBC was observed in tissue specimens. Conclusion Alone urinary SDC-1 may not be a diagnostic biomarker for bladder cancer, but its urinary levels and cellular localization were associated with the differentiation status of patients with bladder tumors. Further studies are warranted to define the potential role for SDC-1 in bladder cancer progression.

Ability of different adiposity indicators to identify children with elevated blood pressure.

OBJECTIVE: Body composition measured by dual-energy X-ray absorptiometry (DXA) is believed to be superior to crude measures such as BMI or waist circumference (WC) to assess health risks associated with adiposity in adults. We compared the ability of BMI, WC, waist-to-height ratio (WHtR), percentage body fat from skinfold thickness, and measures of total and central fat assessed by DXA to identify children with elevated blood pressure (BP). STUDY DESIGN: The QUALITY Study follows 630 Caucasian families (father, mother, and child originally aged 8-10 years). BP, height, weight, WC, and skinfold thickness were measured according to standardized protocols. Elevated BP was defined as systolic or diastolic BP at least 90th age, sex, and height-specific percentile. Total and central fat were determined with DXA. The area under the receiver operating characteristic (ROC) curve (AUC) statistic was computed from logistic models that adjusted for age, sex, height, Tanner stage, and physical activity. RESULTS: All adiposity indicators were highly correlated. WC and WHtR did not show superior ability over BMI to identify children with elevated SBP (P = 0.421 and 0.473). Measures of total and central fat from DXA did not show an improved ability over BMI or WC to identify children with elevated SBP (P = 0.325-0.662). CONCLUSION: Results support the use of BMI in clinical and public health settings, at least in this age group. As all indicators had a limited ability to identify children with elevated BP, results also support measurement of BP in all children of this age independent of a weight status.

Assessment of the 10-year probability of osteoporotic hip fracture combining clinical risk factors and heel bone ultrasound: the EPISEM prospective cohort of 12,958 elderly women.

This study aimed to develop a hip screening tool that combines relevant clinical risk factors (CRFs) and quantitative ultrasound (QUS) at the heel to determine the 10-yr probability of hip fractures in elderly women. The EPISEM database, comprised of approximately 13,000 women 70 yr of age, was derived from two population-based white European cohorts in France and Switzerland. All women had baseline data on CRFs and a baseline measurement of the stiffness index (SI) derived from QUS at the heel. Women were followed prospectively to identify incident fractures. Multivariate analysis was performed to determine the CRFs that contributed significantly to hip fracture risk, and these were used to generate a CRF score. Gradients of risk (GR; RR/SD change) and areas under receiver operating characteristic curves (AUC) were calculated for the CRF score, SI, and a score combining both. The 10-yr probability of hip fracture was computed for the combined model. Three hundred seven hip fractures were observed over a mean follow-up of 3.2 yr. In addition to SI, significant CRFs for hip fracture were body mass index (BMI), history of fracture, an impaired chair test, history of a recent fall, current cigarette smoking, and diabetes mellitus. The average GR for hip fracture was 2.10 per SD with the combined SI + CRF score compared with a GR of 1.77 with SI alone and of 1.52 with the CRF score alone. Thus, the use of CRFs enhanced the predictive value of SI alone. For example, in a woman 80 yr of age, the presence of two to four CRFs increased the probability of hip fracture from 16.9% to 26.6% and from 52.6% to 70.5% for SI Z-scores of +2 and -3, respectively. The combined use of CRFs and QUS SI is a promising tool to assess hip fracture probability in elderly women, especially when access to DXA is limited.

A genetic risk score combining 32 SNPs is associated with body mass index and improves obesity prediction in people with major depressive disorder.

BACKGROUND: Obesity is strongly associated with major depressive disorder (MDD) and various other diseases. Genome-wide association studies have identified multiple risk loci robustly associated with body mass index (BMI). In this study, we aimed to investigate whether a genetic risk score (GRS) combining multiple BMI risk loci might have utility in prediction of obesity in patients with MDD. METHODS: Linear and logistic regression models were conducted to predict BMI and obesity, respectively, in three independent large case-control studies of major depression (Radiant, GSK-Munich, PsyCoLaus). The analyses were first performed in the whole sample and then separately in depressed cases and controls. An unweighted GRS was calculated by summation of the number of risk alleles. A weighted GRS was calculated as the sum of risk alleles at each locus multiplied by their effect sizes. Receiver operating characteristic (ROC) analysis was used to compare the discriminatory ability of predictors of obesity. RESULTS: In the discovery phase, a total of 2,521 participants (1,895 depressed patients and 626 controls) were included from the Radiant study. Both unweighted and weighted GRS were highly associated with BMI (P <0.001) but explained only a modest amount of variance. Adding 'traditional' risk factors to GRS significantly improved the predictive ability with the area under the curve (AUC) in the ROC analysis, increasing from 0.58 to 0.66 (95% CI, 0.62-0.68; χ(2) = 27.68; P <0.0001). Although there was no formal evidence of interaction between depression status and GRS, there was further improvement in AUC in the ROC analysis when depression status was added to the model (AUC = 0.71; 95% CI, 0.68-0.73; χ(2) = 28.64; P <0.0001). We further found that the GRS accounted for more variance of BMI in depressed patients than in healthy controls. Again, GRS discriminated obesity better in depressed patients compared to healthy controls. We later replicated these analyses in two independent samples (GSK-Munich and PsyCoLaus) and found similar results. CONCLUSIONS: A GRS proved to be a highly significant predictor of obesity in people with MDD but accounted for only modest amount of variance. Nevertheless, as more risk loci are identified, combining a GRS approach with information on non-genetic risk factors could become a useful strategy in identifying MDD patients at higher risk of developing obesity.

Low C-reactive protein values at admission predict mortality in patients with severe community-acquired pneumonia caused by Streptococcus pneumoniae that require intensive care management.

PURPOSE: To identify risk factors associated with mortality in patients with severe community-acquired pneumonia (CAP) caused by S. pneumoniae who require intensive care unit (ICU) management, and to assess the prognostic values of these risk factors at the time of admission. METHODS: Retrospective analysis of all consecutive patients with CAP caused by S. pneumoniae who were admitted to the 32-bed medico-surgical ICU of a community and referral university hospital between 2002 and 2011. Univariate and multivariate analyses were performed on variables available at admission. RESULTS: Among the 77 adult patients with severe CAP caused by S. pneumoniae who required ICU management, 12 patients died (observed mortality rate 15.6 %). Univariate analysis indicated that septic shock and low C-reactive protein (CRP) values at admission were associated with an increased risk of death. In a multivariate model, after adjustment for age and gender, septic shock [odds ratio (OR), confidence interval 95 %; 4.96, 1.11-22.25; p = 0.036], and CRP (OR 0.99, 0.98-0.99 p = 0.034) remained significantly associated with death. Finally, we assessed the discriminative ability of CRP to predict mortality by computing its receiver operating characteristic curve. The CRP value cut-off for the best sensitivity and specificity was 169.5 mg/L to predict hospital mortality with an area under the curve of 0.72 (0.55-0.89). CONCLUSIONS: The mortality of patients with S. pneumoniae CAP requiring ICU management was much lower than predicted by severity scores. The presence of septic shock and a CRP value at admission <169.5 mg/L predicted a fatal outcome.