Clinical Diagnosis and Staging of Intrahepatic Cholangiocarcinoma.

Intrahepatic cholangiocarcinomas are the second most common primary liver malignancies with an increasing incidence over the past decades. Due to a lack of early symptoms and their aggressive oncobiological behavior, the diagnostic approach is challenging and the outcome remains unsatisfactory with a poor prognosis. Thus, a consistent staging system for a comparison between different therapeutic approaches is needed, but independent predictors for worse survival are still controversial. Currently, four different staging systems are primarily used, which differ in the way they determine the 'T' category. Furthermore, different nomograms and prognostic models have been recently proposed and may be helpful in providing additional information for predicting the prognosis and therefore be helpful in approaching an adequate treatment strategy. This review will discuss the diagnostic approach to intrahepatic cholangiocarcinoma as well as compare and contrast the most current staging systems and prognostic models.

How often parametrial involvement leads to post-operative adjuvant treatment in locally advanced cervical cancer after neoadjuvant chemotherapy and type C radical hysterectomy?

OBJECTIVE Parametrial involvement (PMI) is one of the most important factors influencing prognosis in locally advanced stage cervical cancer (LACC) patients. We aimed to evaluate PMI rate among LACC patients undergoing neoadjuvant chemotherapy (NACT), thus evaluating the utility of parametrectomy in tailor adjuvant treatments. METHODS Retrospective evaluation of consecutive 275 patients affected by LACC (IB2-IIB), undergoing NACT followed by type C/class III radical hysterectomy. Basic descriptive statistics, univariate and multivariate analyses were applied in order to identify factors predicting PMI. Survival outcomes were assessed using Kaplan-Meier and Cox models. RESULTS PMI was detected in 37 (13%) patients: it was associated with vaginal involvement, lymph node positivity and both in 10 (4%), 5 (2%) and 12 (4%) patients, respectively; while PMI alone was observed in only 10 (4%) patients. Among this latter group, adjuvant treatment was delivered in 3 (1%) patients on the basis of pure PMI; while the remaining patients had other characteristics driving adjuvant treatment. Considering factors predicting PMI we observed that only suboptimal pathological responses (OR: 1.11; 95% CI: 1.01, 1.22) and vaginal involvement (OR: 1.29 (95%) CI: 1.17, 1.44) were independently associated with PMI. PMI did not correlate with survival (HR: 2.0; 95% CI: 0.82, 4.89); while clinical response to NACT (HR: 3.35; 95% CI: 1.59, 7.04), vaginal involvement (HR: 2.38; 95% CI: 1.12, 5.02) and lymph nodes positivity (HR: 3.47; 95% CI: 1.62, 7.41), independently correlated with worse survival outcomes. CONCLUSIONS Our data suggest that PMI had a limited role on the choice to administer adjuvant treatment, thus supporting the potential embrace of less radical surgery in LACC patients undergoing NACT. Further prospective studies are warranted.

Accuracy of linear measurements using three imaging modalities: two lateral cephalograms and one 3D model from CBCT data

BACKGROUND The aim of this study was to evaluate the accuracy of linear measurements on three imaging modalities: lateral cephalograms from a cephalometric machine with a 3 m source-to-mid-sagittal-plane distance (SMD), from a machine with 1.5 m SMD and 3D models from cone-beam computed tomography (CBCT) data. METHODS Twenty-one dry human skulls were used. Lateral cephalograms were taken, using two cephalometric devices: one with a 3 m SMD and one with a 1.5 m SMD. CBCT scans were taken by 3D Accuitomo® 170, and 3D surface models were created in Maxilim® software. Thirteen linear measurements were completed twice by two observers with a 4 week interval. Direct physical measurements by a digital calliper were defined as the gold standard. Statistical analysis was performed. RESULTS Nasion-Point A was significantly different from the gold standard in all methods. More statistically significant differences were found on the measurements of the 3 m SMD cephalograms in comparison to the other methods. Intra- and inter-observer agreement based on 3D measurements was slightly better than others. LIMITATIONS Dry human skulls without soft tissues were used. Therefore, the results have to be interpreted with caution, as they do not fully represent clinical conditions. CONCLUSIONS 3D measurements resulted in a better observer agreement. The accuracy of the measurements based on CBCT and 1.5 m SMD cephalogram was better than a 3 m SMD cephalogram. These findings demonstrated the linear measurements accuracy and reliability of 3D measurements based on CBCT data when compared to 2D techniques. Future studies should focus on the implementation of 3D cephalometry in clinical practice.

Tuberculosis-related mortality in people living with HIV in Europe and Latin America: an international cohort study

BACKGROUND Management of tuberculosis in patients with HIV in eastern Europe is complicated by the high prevalence of multidrug-resistant tuberculosis, low rates of drug susceptibility testing, and poor access to antiretroviral therapy (ART). We report 1 year mortality estimates from a multiregional (eastern Europe, western Europe, and Latin America) prospective cohort study: the TB:HIV study. METHODS Consecutive HIV-positive patients aged 16 years or older with a diagnosis of tuberculosis between Jan 1, 2011, and Dec 31, 2013, were enrolled from 62 HIV and tuberculosis clinics in 19 countries in eastern Europe, western Europe, and Latin America. The primary endpoint was death within 12 months after starting tuberculosis treatment; all deaths were classified according to whether or not they were tuberculosis related. Follow-up was either until death, the final visit, or 12 months after baseline, whichever occurred first. Risk factors for all-cause and tuberculosis-related deaths were assessed using Kaplan-Meier estimates and Cox models. FINDINGS Of 1406 patients (834 in eastern Europe, 317 in western Europe, and 255 in Latin America), 264 (19%) died within 12 months. 188 (71%) of these deaths were tuberculosis related. The probability of all-cause death was 29% (95% CI 26-32) in eastern Europe, 4% (3-7) in western Europe, and 11% (8-16) in Latin America (p<0·0001) and the corresponding probabilities of tuberculosis-related death were 23% (20-26), 1% (0-3), and 4% (2-8), respectively (p<0·0001). Patients receiving care outside eastern Europe had a 77% decreased risk of death: adjusted hazard ratio (aHR) 0·23 (95% CI 0·16-0·31). In eastern Europe, compared with patients who started a regimen with at least three active antituberculosis drugs, those who started fewer than three active antituberculosis drugs were at a higher risk of tuberculosis-related death (aHR 3·17; 95% CI 1·83-5·49) as were those who did not have baseline drug-susceptibility tests (2·24; 1·31-3·83). Other prognostic factors for increased tuberculosis-related mortality were disseminated tuberculosis and a low CD4 cell count. 18% of patients were receiving ART at tuberculosis diagnosis in eastern Europe compared with 44% in western Europe and 39% in Latin America (p<0·0001); 12 months later the proportions were 67% in eastern Europe, 92% in western Europe, and 85% in Latin America (p<0·0001). INTERPRETATION Patients with HIV and tuberculosis in eastern Europe have a risk of death nearly four-times higher than that in patients from western Europe and Latin America. This increased mortality rate is associated with modifiable risk factors such as lack of drug susceptibility testing and suboptimal initial antituberculosis treatment in settings with a high prevalence of drug resistance. Urgent action is needed to improve tuberculosis care for patients living with HIV in eastern Europe. FUNDING EU Seventh Framework Programme.

Therapists under influence – Patient strategies and therapist reactions

Therapists having a positive influence on patients is a common view of psychotherapy. There is, however, an influence of patients on therapists too, which has received less attention. The more restricted and rigid patients are, the more limited the interpersonal behavior of others with which the get along well. In line with social psychological, interpersonal and clinical models they try to bring the therapist into an interpersonal position which suits them well. With 60 patients, common strategies have been rated: Good mood, Positive feedback, Negative feedback, Agenda setting, Provoking a response from the therapist, Negative reports about third persons, Fait accompli, Supplication, Self-promotion, Avoidance of contents, und Emotional avoidance. The rating procedure, frequencies, and therapist reactions upon these patient strategies will be reported

Modeling asteroid collisions and impact processes

As a complement to experimental and theoretical approaches, numerical modeling has become an important component to study asteroid collisions and impact processes. In the last decade, there have been significant advances in both computational resources and numerical methods. We discuss the present state-of-the-art numerical methods and material models used in "shock physics codes" to simulate impacts and collisions and give some examples of those codes. Finally, recent modeling studies are presented, focussing on the effects of various material properties and target structures on the outcome of a collision.

Some Identification Issues in Nonparametric Linear Models with Endogenous Regressors

In applied work economists often seek to relate a given response variable y to some causal parameter mu* associated with it. This parameter usually represents a summarization based on some explanatory variables of the distribution of y, such as a regression function, and treating it as a conditional expectation is central to its identification and estimation. However, the interpretation of mu* as a conditional expectation breaks down if some or all of the explanatory variables are endogenous. This is not a problem when mu* is modelled as a parametric function of explanatory variables because it is well known how instrumental variables techniques can be used to identify and estimate mu*. In contrast, handling endogenous regressors in nonparametric models, where mu* is regarded as fully unknown, presents di±cult theoretical and practical challenges. In this paper we consider an endogenous nonparametric model based on a conditional moment restriction. We investigate identification related properties of this model when the unknown function mu* belongs to a linear space. We also investigate underidentification of mu* along with the identification of its linear functionals. Several examples are provided in order to develop intuition about identification and estimation for endogenous nonparametric regression and related models.

Tracking of plasma lipids and lipoproteins, within-person and year-to-year variability in plasma cholesterol levels among participants from age 8 to 18 in Project HeartBeat!

Coronary heart disease remains the leading cause of death in the United States and increased blood cholesterol level has been found to be a major risk factor with roots in childhood. Tracking of cholesterol, i.e., the tendency to maintain a particular cholesterol level relative to the rest of the population, and variability in blood lipid levels with increase in age have implications for cholesterol screening and assessment of lipid levels in children for possible prevention of further rise to prevent adulthood heart disease. In this study the pattern of change in plasma lipids, over time, and their tracking were investigated. Also, within-person variance and retest reliability defined as the square root of within-person variance for plasma total cholesterol, HDL-cholesterol, LDL-cholesterol, and triglycerides and their relation to age, sex and body mass index among participants from age 8 to 18 years were investigated. ^ In Project HeartBeat!, 678 healthy children aged 8, 11 and 14 years at baseline were enrolled and examined at 4-monthly intervals for up to 4 years. We examined the relationship between repeated observations by Pearson's correlations. Age- and sex-specific quintiles were calculated and the probability of participants to remain in the uppermost quintile of their respective distribution was evaluated with life table methods. Plasma total cholesterol, HDL-C and LDL-C at baseline were strongly and significantly correlated with measurements at subsequent visits across the sex and age groups. Plasma triglyceride at baseline was also significantly correlated with subsequent measurements but less strongly than was the case for other plasma lipids. The probability to remain in the upper quintile was also high (60 to 70%) for plasma total cholesterol, HDL-C and LDL-C. ^ We used a mixed longitudinal, or synthetic cohort design with continuous observations from age 8 to 18 years to estimate within person variance of plasma total cholesterol, HDL-C, LDL-C and triglycerides. A total of 5809 measurements were available for both cholesterol and triglycerides. A multilevel linear model was used. Within-person variance among repeated measures over up to four years of follow-up was estimated for total cholesterol, HDL-C, LDL-C and triglycerides separately. The relationship of within-person and inter-individual variance with age, sex, and body mass index was evaluated. Likelihood ratio tests were conducted by calculating the deviation of −2log (likelihood) within the basic model and alternative models. The square root of within-person variance provided the retest reliability (within person standard deviation) for plasma total cholesterol, HDL-C, LDL-C and triglycerides. We found 13.6 percent retest reliability for plasma cholesterol, 6.1 percent for HDL-cholesterol, 11.9 percent for LDL-cholesterol and 32.4 percent for triglycerides. Retest reliability of plasma lipids was significantly related with age and body mass index. It increased with increase in body mass index and age. These findings have implications for screening guidelines, as participants in the uppermost quintile tended to maintain their status in each of the age groups during a four-year follow-up. The magnitude of within-person variability of plasma lipids influences the ability to classify children into risk categories recommended by the National Cholesterol Education Program. ^

Testing for Balance Sheet Effects in Emerging Market Countries

This paper tests the presence of balance sheets effects and analyzes the implications for exchange rate policies in emerging markets. The results reveal that the emerging market bond index (EMBI) is negatively related to the banks' foreign currency leverage, and that these banks' foreign currency exposures are relatively unhedged. Panel SVAR methods using EMBI instead of advanced country lending rates find, contrary to the literature, that the amplitude of output responses to foreign interest rate shocks are smaller under relatively fixed regimes. The findings are robust to the local projections method of obtaining impulse responses, using country specific and GARCH-SVAR models.

The Great Moderation Flattens Fat Tails: Disappearing Leptokurtosis

Recently, Fagiolo et al. (2008) find fat tails of economic growth rates after adjusting outliers, autocorrelation and heteroskedasticity. This paper employs US quarterly real output growth, showing that this finding of fat tails may reflect the Great Moderation. That is, leptokurtosis disappears after GARCH adjustment once we incorporate the break in the variance equation.

Molecular and genetic analyses of Fgf signaling during cardiac outflow tract development

Epithelial-mesenchymal tissue interactions regulate the development of derivatives of the caudal pharyngeal arches (PAs) to govern the ultimate morphogenesis of the aortic arch and outflow tract (OFT) of the heart. Disruption of these signaling pathways is thought to contribute to the pathology of a significant proportion of congenital cardiovascular defects in humans. In this study, I tested whether Fibroblast Growth Factor 15 (Fgf15), a secreted signaling molecule expressed within the PAs, is an extracellular mediator of tissue interactions during PA and OFT development. Analyses of Fgf15−/− mouse embryonic hearts revealed abnormalities primarily localized to the OFT, correlating with aberrant cardiac neural crest cell behavior. The T-box-containing transcription factor Tbx1 has been implicated in the cardiovascular defects associated with the human 22q11 Deletion Syndromes, and regulates the expression of other Fgf family members within the mouse PAs. However, expression and genetic interaction studies incorporating mice deficient for Tbx1, its upstream regulator, Sonic Hedgehog (Shh), or its putative downstream effector, Fgf8, indicated that Fgf15 functions during OFT development in a manner independent of these factors. Rather, analyses of compound mutant mice indicated that Fgf15 and Fgf9, an additional Fgf family member expressed within the PAs, genetically interact, providing insight into the factors acting in conjunction with Fgf15 during OFT development. Finally, in an effort to further characterize this Fgf15-mediated developmental pathway, promoter deletion analyses were employed to isolate a 415bp sequence 7.1Kb 5′ to the Fgf15 transcription start site both necessary and sufficient to drive reporter gene expression within the epithelium of the PAs. Sequence comparisons among multiple mammalian species facilitated the identification of evolutionarily conserved potential trans-acting factor binding sites within this fragment. Subsequent studies will investigate the molecular pathway(s) through which Fgf15 functions via identification of factors that bind to this element to govern Fgf15 gene expression. Furthermore, targeted deletion of this element will establish the developmental requirement for pharyngeal epithelium-derived Fgf15 signaling function. Taken as a whole, these data demonstrate that Fgf15 is a component of a novel, Tbx1-independent molecular pathway, functioning within the PAs in a manner cooperative with Fgf9, required for proper development of the cardiac OFT. ^

Maternal ingestion of radon-222 in drinking water and the absorbed radiation dose to the embryo

Maternal ingestion of high concentrations of radon-222 (Rn-222) in drinking during pregnancy may pose a significant radiation hazard to the developing embryo. The effects of ionizing radiation to the embryo and fetus have been the subject of research, analyses, and the development of a number of radiation dosimetric models for a variety of radionuclides. Currently, essentially all of the biokinetic and dosimetric models that have been developed by national and international radiation protection agencies and organizations recommend calculating the dose to the mother's uterus as a surrogate for estimating the dose to the embryo. Heretofore, the traditional radiation dosimetry models have neither considered the embryo a distinct and rapidly developing entity, the fact that it is implanted in the endometrial layer of the uterus, nor the physiological interchanges that take place between maternal and embryonic cells following the implantation of the blastocyst in the endometrium. The purpose of this research was to propose a new approach and mathematical model for calculating the absorbed radiation dose to the embryo by utilizing a semiclassical treatment of alpha particle decay and subsequent scattering of energy deposition in uterine and embryonic tissue. The new approach and model were compared and contrasted with the currently recommended biokinetic and dosimetric models for estimating the radiation dose to the embryo. The results obtained in this research demonstrate that the estimated absorbed dose for an embryo implanted in the endometrial layer of the uterus during the fifth week of embryonic development is greater than the estimated absorbed dose for an embryo implanted in the uterine muscle on the last day of the eighth week of gestation. This research provides compelling evidence that the recommended methodologies and dosimetric models of the Nuclear Regulatory Commission and International Commission on Radiological Protection employed for calculating the radiation dose to the embryo from maternal intakes of radionuclides, including maternal ingestion of Rn-222 in drinking water would result in an underestimation of dose. ^

Bayesian generalized linear models for meta-analysis of diagnostic tests

With the recognition of the importance of evidence-based medicine, there is an emerging need for methods to systematically synthesize available data. Specifically, methods to provide accurate estimates of test characteristics for diagnostic tests are needed to help physicians make better clinical decisions. To provide more flexible approaches for meta-analysis of diagnostic tests, we developed three Bayesian generalized linear models. Two of these models, a bivariate normal and a binomial model, analyzed pairs of sensitivity and specificity values while incorporating the correlation between these two outcome variables. Noninformative independent uniform priors were used for the variance of sensitivity, specificity and correlation. We also applied an inverse Wishart prior to check the sensitivity of the results. The third model was a multinomial model where the test results were modeled as multinomial random variables. All three models can include specific imaging techniques as covariates in order to compare performance. Vague normal priors were assigned to the coefficients of the covariates. The computations were carried out using the 'Bayesian inference using Gibbs sampling' implementation of Markov chain Monte Carlo techniques. We investigated the properties of the three proposed models through extensive simulation studies. We also applied these models to a previously published meta-analysis dataset on cervical cancer as well as to an unpublished melanoma dataset. In general, our findings show that the point estimates of sensitivity and specificity were consistent among Bayesian and frequentist bivariate normal and binomial models. However, in the simulation studies, the estimates of the correlation coefficient from Bayesian bivariate models are not as good as those obtained from frequentist estimation regardless of which prior distribution was used for the covariance matrix. The Bayesian multinomial model consistently underestimated the sensitivity and specificity regardless of the sample size and correlation coefficient. In conclusion, the Bayesian bivariate binomial model provides the most flexible framework for future applications because of its following strengths: (1) it facilitates direct comparison between different tests; (2) it captures the variability in both sensitivity and specificity simultaneously as well as the intercorrelation between the two; and (3) it can be directly applied to sparse data without ad hoc correction. ^

Comparison of Bayesian and frequentist approaches in clinical outcomes between hospitals

Many public health agencies and researchers are interested in comparing hospital outcomes, for example, morbidity, mortality, and hospitalization across areas and hospitals. However, since there is variation of rates in clinical trials among hospitals because of several biases, we are interested in controlling for the bias and assessing real differences in clinical practices. In this study, we compared the variations between hospitals in rates of severe Intraventricular Haemorrhage (IVH) infant using Frequentist statistical approach vs. Bayesian hierarchical model through simulation study. The template data set for simulation study was included the number of severe IVH infants of 24 intensive care units in Australian and New Zealand Neonatal Network from 1995 to 1997 in severe IVH rate in preterm babies. We evaluated the rates of severe IVH for 24 hospitals with two hierarchical models in Bayesian approach comparing their performances with the shrunken rates in Frequentist method. Gamma-Poisson (BGP) and Beta-Binomial (BBB) were introduced into Bayesian model and the shrunken estimator of Gamma-Poisson (FGP) hierarchical model using maximum likelihood method were calculated as Frequentist approach. To simulate data, the total number of infants in each hospital was kept and we analyzed the simulated data for both Bayesian and Frequentist models with two true parameters for severe IVH rate. One was the observed rate and the other was the expected severe IVH rate by adjusting for five predictors variables for the template data. The bias in the rate of severe IVH infant estimated by both models showed that Bayesian models gave less variable estimates than Frequentist model. We also discussed and compared the results from three models to examine the variation in rate of severe IVH by 20th centile rates and avoidable number of severe IVH cases. ^

Assessment of the effect on statistical power of regression model misspecification by using techniques of mathematical statistics and simulation study

Objectives. This paper seeks to assess the effect on statistical power of regression model misspecification in a variety of situations. ^ Methods and results. The effect of misspecification in regression can be approximated by evaluating the correlation between the correct specification and the misspecification of the outcome variable (Harris 2010).In this paper, three misspecified models (linear, categorical and fractional polynomial) were considered. In the first section, the mathematical method of calculating the correlation between correct and misspecified models with simple mathematical forms was derived and demonstrated. In the second section, data from the National Health and Nutrition Examination Survey (NHANES 2007-2008) were used to examine such correlations. Our study shows that comparing to linear or categorical models, the fractional polynomial models, with the higher correlations, provided a better approximation of the true relationship, which was illustrated by LOESS regression. In the third section, we present the results of simulation studies that demonstrate overall misspecification in regression can produce marked decreases in power with small sample sizes. However, the categorical model had greatest power, ranging from 0.877 to 0.936 depending on sample size and outcome variable used. The power of fractional polynomial model was close to that of linear model, which ranged from 0.69 to 0.83, and appeared to be affected by the increased degrees of freedom of this model.^ Conclusion. Correlations between alternative model specifications can be used to provide a good approximation of the effect on statistical power of misspecification when the sample size is large. When model specifications have known simple mathematical forms, such correlations can be calculated mathematically. Actual public health data from NHANES 2007-2008 were used as examples to demonstrate the situations with unknown or complex correct model specification. Simulation of power for misspecified models confirmed the results based on correlation methods but also illustrated the effect of model degrees of freedom on power.^