Predictors of inflammation in response to anthracycline-based chemotherapy for breast cancer

Although chemotherapy for breast cancer can increase inflammation, few studies have examined predictors of this phenomenon. This study examined potential contributions of demographics, disease characteristics, and treatment regimens to markers of inflammation in response to chemotherapy for breast cancer. Thirty-five women with stage I-III-A breast cancer (mean age 50 years) were studied prior to cycle 1 and prior to cycle 4 of anthracycline-based chemotherapy. Circulating levels of inflammatory markers with high relevance to breast cancer were examined, including C-reactive protein (CRP), tumor necrosis factor-alpha (TNF-alpha), Interleukin-1 receptor antagonist (IL1-RA), vascular endothelial growth factor (VEGF), soluble intercellular adhesion molecule-1 (sICAM-1), Interleukin- (IL-6), soluble P-selectin (sP-selectin), and von Willebrand factor (vWf). Chemotherapy was associated with elevations in VEGF (p < or = 0.01), sICAM-1 (p < or = 0.01), sP-selectin (p < or = 0.02) and vWf (p < or = 0.05). Multiple regression analysis controlling for age and body mass index (BMI) showed that higher post-chemotherapy levels of inflammation were consistently related to higher pre-chemotherapy levels of inflammation (ps < or =0.05) as well as to certain disease characteristics. Post-chemotherapy IL-6 levels were higher in patients who had larger tumors (p < or = 0.05) while post-chemotherapy VEGF levels were higher in patients who had smaller tumors (p < or = 0.05). Post-chemotherapy sP-selectin levels were highest in women who had received epirubicin, cytoxan, 5-fluorouracil chemotherapy (p < or = 0.01). These findings indicate that chemotherapy treatment can be associated with elevations in certain markers of inflammation, particularly markers of endothelial and platelet activation. Inflammation in response to chemotherapy is most significantly related to inflammation that existed prior to chemotherapy but also potentially to treatment regimen and to certain disease characteristics.

Can decision making in general surgery be based on evidence? An empirical study of Cochrane Reviews

BACKGROUND: This empirical study analyzes the current status of Cochrane Reviews (CRs) and their strength of recommendation for evidence-based decision making in the field of general surgery. METHODS: Systematic literature search of the Cochrane Database of Systematic Reviews and the Cochrane Collaboration's homepage to identify available CRs on surgical topics. Quantitative and qualitative characteristics, utilization, and formulated treatment recommendations were evaluated by 2 independent reviewers. Association of review characteristics with treatment recommendation was analyzed using univariate and multivariate logistic regression models. RESULTS: Ninety-three CRs, including 1,403 primary studies and 246,473 patients, were identified. Mean number of included primary studies per CR was 15.1 (standard deviation [SD] 14.5) including 2,650 (SD 3,340) study patients. Two and a half (SD 8.3) nonrandomized trials were included per analyzed CR. Seventy-two (77%) CRs were published or updated in 2005 or later. Explicit treatment recommendations were given in 45 (48%). Presence of a treatment recommendation was associated with the number of included primary studies and the proportion of randomized studies. Utilization of surgical CRs remained low and showed large inter-country differences. The most surgical CRs were accessed in UK, USA, and Australia, followed by several Western and Eastern European countries. CONCLUSION: Only a minority of available CRs address surgical questions and their current usage is low. Instead of unsystematically increasing the number of surgical CRs it would be far more efficient to focus the review process on relevant surgical questions. Prioritization of CRs needs valid methods which should be developed by the scientific surgical community.

A systematic review on the accuracy and the clinical outcome of computer-guided template-based implant dentistry

Introduction: The aim of this systematic review was to analyze the dental literature regarding accuracy and clinical application in computer-guided template-based implant dentistry. Materials and methods: An electronic literature search complemented by manual searching was performed to gather data on accuracy and surgical, biological and prosthetic complications in connection with computer-guided implant treatment. For the assessment of accuracy meta-regression analysis was performed. Complication rates are descriptively summarized. Results: From 3120 titles after the literature search, eight articles met the inclusion criteria regarding accuracy and 10 regarding the clinical performance. Meta-regression analysis revealed a mean deviation at the entry point of 1.07 mm (95% CI: 0.76-1.22 mm) and at the apex of 1.63 mm (95% CI: 1.26-2 mm). No significant differences between the studies were found regarding method of template production or template support and stabilization. Early surgical complications occurred in 9.1%, early prosthetic complications in 18.8% and late prosthetic complications in 12% of the cases. Implant survival rates of 91-100% after an observation time of 12-60 months are reported in six clinical studies with 537 implants mainly restored immediately after flapless implantation procedures. Conclusion: Computer-guided template-based implant placement showed high implant survival rates ranging from 91% to 100%. However, a considerable number of technique-related perioperative complications were observed. Preclinical and clinical studies indicated a reasonable mean accuracy with relatively high maximum deviations. Future research should be directed to increase the number of clinical studies with longer observation periods and to improve the systems in terms of perioperative handling, accuracy and prosthetic complications.

A Combinatorial Approach to the Variable Selection in Multiple Linear Regression: Analysis of Selwood et al Data set -A Case Study.

A combinatorial protocol (CP) is introduced here to interface it with the multiple linear regression (MLR) for variable selection. The efficiency of CP-MLR is primarily based on the restriction of entry of correlated variables to the model development stage. It has been used for the analysis of Selwood et al data set [16], and the obtained models are compared with those reported from GFA [8] and MUSEUM [9] approaches. For this data set CP-MLR could identify three highly independent models (27, 28 and 31) with Q2 value in the range of 0.632-0.518. Also, these models are divergent and unique. Even though, the present study does not share any models with GFA [8], and MUSEUM [9] results, there are several descriptors common to all these studies, including the present one. Also a simulation is carried out on the same data set to explain the model formation in CP-MLR. The results demonstrate that the proposed method should be able to offer solutions to data sets with 50 to 60 descriptors in reasonable time frame. By carefully selecting the inter-parameter correlation cutoff values in CP-MLR one can identify divergent models and handle data sets larger than the present one without involving excessive computer time.

Using Dynamic Programming Decomposition for Revenue Management with Opaque Products

Opaque products enable service providers to hide specific characteristics of their service fulfillment from the customer until after purchase. Prominent examples include internet-based service providers selling airline tickets without defining details, such as departure time or operating airline, until the booking has been made. Owing to the resulting flexibility in resource utilization, the traditional revenue management process needs to be modified. In this paper, we extend dynamic programming decomposition techniques widely used for traditional revenue management to develop an intuitive capacity control approach that allows for the incorporation of opaque products. In a simulation study, we show that the developed approach significantly outperforms other well-known capacity control approaches adapted to the opaque product setting. Based on the approach, we also provide computational examples of how the share of opaque products as well as the degree of opacity can influence the results.

The role of peat decomposition in patterned mires: a case study from the central Swiss Alps

A number of hydrological, botanical, macro- and micro-climatological processes are involved in the formation of patterned peatlands. La Grande Tsa at 2336 m a.s.l. is probably the highest bog in the central Swiss Alps and is unique in its pattern. In two of five pools there is in the contact zone between the basal peat and the overlying gyttja an unconformity in the depth-age models based on radiocarbon dates. Palynostratigraphies of cores from a ridge and a pool confirm the occurrence of an unconformity in the contact zone. We conclude that deepening of the pools results from decomposition of peat. The fact that the dated unconformities in the two pools and the unconformity in the ridge-core all fall within the Bronze Age suggest they were caused by events external to the bog. We hypothesize that early transhumance resulted in anthropogenic lowering of the timberline, which resulted in a reduction in the leaf-area index and evapotranspiration, and in higher water levels and thus pool formation.

A chrysophyte stomatocyst-based reconstruction of cold-season air temperature from Alpine Lake Silvaplana (AD 1500–2003); methods and concepts for quantitative inferences

Relatively little is known about past cold-season temperature variability in high-Alpine regions because of a lack of natural cold-season temperature proxies as well as under-representation of high-altitude sites in meteorological, early-instrumental and documentary data sources. Recent studies have shown that chrysophyte stomatocysts, or simply cysts (sub-fossil algal remains of Chrysophyceae and Synurophyceae), are among the very few natural proxies that can be used to reconstruct cold-season temperatures. This study presents a quantitative, high-resolution (5-year), cold-season (Oct–May) temperature reconstruction based on sub-fossil chrysophyte stomatocysts in the annually laminated (varved) sediments of high-Alpine Lake Silvaplana, SE Switzerland (1,789 m a.s.l.), since AD 1500. We first explore the method used to translate an ecologically meaningful variable based on a biological proxy into a simple climate variable. A transfer function was applied to reconstruct the ‘date of spring mixing’ from cyst assemblages. Next, statistical regression models were tested to convert the reconstructed ‘dates of spring mixing’ into cold-season surface air temperatures with associated errors. The strengths and weaknesses of this approach are thoroughly tested. One much-debated, basic assumption for reconstructions (‘stationarity’), which states that only the environmental variable of interest has influenced cyst assemblages and the influence of confounding variables is negligible over time, is addressed in detail. Our inferences show that past cold-season air-temperature fluctuations were substantial and larger than those of other temperature reconstructions for Europe and the Alpine region. Interestingly, in this study, recent cold-season temperatures only just exceed those of previous, multi-decadal warm phases since AD 1500. These findings highlight the importance of local studies to assess natural climate variability at high altitudes.

Repeat chlamydia screening among adolescents: cohort study in a school-based programme in New Orleans

OBJECTIVES To describe uptake of chlamydia screening, determine rates of repeated yearly screening and investigate determinants of repeated participation in an organised school-based screening programme. METHODS The authors analysed data from 1995 to 2005 from female and male students in up to 13 schools in New Orleans, Louisiana, USA. The authors calculated proportions of students tested among all enrolled students and among those with parental consent and the percentage of positive chlamydia tests in each school year. The authors used random effects logistic regression to examine the effect of past screening history on subsequent participation. RESULTS 35 041 students were registered for at least one school year. Overall coverage was >30% in all school years. Among all students registered for 4 years, 10.6% (95% CI 9.3% to 12.0%) of women and 12.7% (95% CI 11.2% to 14.2%) of men had a test every year. Among students with parental consent for 4 years, 49.3% (95% CI 44.6% to 54.1%) of women and 59.3% (95% CI 54.5% to 64.0%) of men had a test every year. Among students registered for 2 or more years, those with a previous positive chlamydia test were less likely to have a subsequent test (female adjusted OR 0.77, 95% CI 0.67 to 0.88 and male adjusted OR 0.84, 95% CI 0.69 to 1.02). Chlamydia positivity increased over time. CONCLUSIONS High levels of uptake can be achieved in school-based chlamydia screening programmes, but repeated yearly screening is difficult to sustain over time.

Development and validation of energy expenditure prediction models based on GT3X accelerometer data in 5- to 9-year-old children

Background: Accelerometry has been established as an objective method that can be used to assess physical activity behavior in large groups. The purpose of the current study was to provide a validated equation to translate accelerometer counts of the triaxial GT3X into energy expenditure in young children. Methods: Thirty-two children aged 5–9 years performed locomotor and play activities that are typical for their age group. Children wore a GT3X accelerometer and their energy expenditure was measured with indirect calorimetry. Twenty-one children were randomly selected to serve as development group. A cubic 2-regression model involving separate equations for locomotor and play activities was developed on the basis of model fit. It was then validated using data of the remaining children and compared with a linear 2-regression model and a linear 1-regression model. Results: All 3 regression models produced strong correlations between predicted and measured MET values. Agreement was acceptable for the cubic model and good for both linear regression approaches. Conclusions: The current linear 1-regression model provides valid estimates of energy expenditure for ActiGraph GT3X data for 5- to 9-year-old children and shows equal or better predictive validity than a cubic or a linear 2-regression model.

ANOVA kernels and RKHS of zero mean functions for model-based sensitivity analysis

Given a reproducing kernel Hilbert space (H,〈.,.〉)(H,〈.,.〉) of real-valued functions and a suitable measure μμ over the source space D⊂RD⊂R, we decompose HH as the sum of a subspace of centered functions for μμ and its orthogonal in HH. This decomposition leads to a special case of ANOVA kernels, for which the functional ANOVA representation of the best predictor can be elegantly derived, either in an interpolation or regularization framework. The proposed kernels appear to be particularly convenient for analyzing the effect of each (group of) variable(s) and computing sensitivity indices without recursivity.

Suicide assisted by right-to-die associations: a population based cohort study

Background: In Switzerland, assisted suicide is legal but there is concern that vulnerable or disadvantaged groups are more likely to die in this way than other people. We examined socio-economic factors associated with assisted suicide. Methods: We linked the suicides assisted by right-to-die associations during 2003–08 to a census-based longitudinal study of the Swiss population. We used Cox and logistic regression models to examine associations with gender, age, marital status, education, religion, type of household, urbanization, neighbourhood socio-economic position and other variables. Separate analyses were done for younger (25 to 64 years) and older (65 to 94 years) people. Results: Analyses were based on 5 004 403 Swiss residents and 1301 assisted suicides (439 in the younger and 862 in the older group). In 1093 (84.0%) assisted suicides, an underlying cause was recorded; cancer was the most common cause (508, 46.5%). In both age groups, assisted suicide was more likely in women than in men, those living alone compared with those living with others and in those with no religious affiliation compared with Protestants or Catholics. The rate was also higher in more educated people, in urban compared with rural areas and in neighbourhoods of higher socio-economic position. In older people, assisted suicide was more likely in the divorced compared with the married; in younger people, having children was associated with a lower rate. Conclusions: Assisted suicide in Switzerland was associated with female gender and situations that may indicate greater vulnerability such as living alone or being divorced, but also with higher education and higher socio-economic position.

Fluid intake and all-cause mortality, cardiovascular mortality, and kidney function: a population-based longitudinal cohort study

BACKGROUND Drinking eight glasses of fluid or water each day is widely believed to improve health, but evidence is sparse and conflicting. We aimed to investigate the association between fluid consumption and long-term mortality and kidney function. METHODS We conducted a longitudinal analysis within a prospective, population-based cohort study of 3858 men and women aged 49 years or older residing in Australia. Daily fluid intake from food and beverages not including water was measured using a food frequency questionnaire. We did multivariable adjusted Cox proportional hazard models for all-cause and cardiovascular mortality and a boot-strapping procedure for estimated glomerular filtration rate (eGFR). RESULTS Upper and lower quartiles of daily fluid intake corresponded to >3 L and <2 L, respectively. During a median follow-up of 13.1 years (total 43 093 years at risk), 1127 deaths (26.1 per 1000 years at risk) including 580 cardiovascular deaths (13.5 per 1000 years at risk) occurred. Daily fluid intake (per 250 mL increase) was not associated with all-cause [adjusted hazard ratio (HR) 0.99 (95% CI 0.98-1.01)] or cardiovascular mortality [HR 0.98 (95% CI 0.95-1.01)]. Overall, eGFR reduced by 2.2 mL/min per 1.73 m(2) (SD 10.9) in the 1207 (31%) participants who had repeat creatinine measurements and this was not associated with fluid intake [adjusted regression coefficient 0.06 mL/min/1.73 m(2) per 250 mL increase (95% CI -0.03 to 0.14)]. CONCLUSIONS Fluid intake from food and beverages excluding water is not associated with improved kidney function or reduced mortality.

Questionnaire-based study to assess the association between management practices and mastitis within tie-stall and free-stall dairy housing systems in Switzerland.

BACKGROUND Prophylactic measures are key components of dairy herd mastitis control programs, but some are only relevant in specific housing systems. To assess the association between management practices and mastitis incidence, data collected in 2011 by a survey among 979 randomly selected Swiss dairy farms, and information from the regular test day recordings from 680 of these farms was analyzed. RESULTS The median incidence of farmer-reported clinical mastitis (ICM) was 11.6 (mean 14.7) cases per 100 cows per year. The median annual proportion of milk samples with a composite somatic cell count (PSCC) above 200,000 cells/ml was 16.1 (mean 17.3) %. A multivariable negative binomial regression model was fitted for each of the mastitis indicators for farms with tie-stall and free-stall housing systems separately to study the effect of other (than housing system) management practices on the ICM and PSCC events (above 200,000 cells/ml). The results differed substantially by housing system and outcome. In tie-stall systems, clinical mastitis incidence was mainly affected by region (mountainous production zone; incidence rate ratio (IRR) = 0.73), the dairy herd replacement system (1.27) and farmers age (0.81). The proportion of high SCC was mainly associated with dry cow udder controls (IRR = 0.67), clean bedding material at calving (IRR = 1.72), using total merit values to select bulls (IRR = 1.57) and body condition scoring (IRR = 0.74). In free-stall systems, the IRR for clinical mastitis was mainly associated with stall climate/temperature (IRR = 1.65), comfort mats as resting surface (IRR = 0.75) and when no feed analysis was carried out (IRR = 1.18). The proportion of high SSC was only associated with hand and arm cleaning after calving (IRR = 0.81) and beef producing value to select bulls (IRR = 0.66). CONCLUSIONS There were substantial differences in identified risk factors in the four models. Some of the factors were in agreement with the reported literature while others were not. This highlights the multifactorial nature of the disease and the differences in the risks for both mastitis manifestations. Attempting to understand these multifactorial associations for mastitis within larger management groups continues to play an important role in mastitis control programs.

Robust Proximal Femur Segmentation in Conventional X-Ray Images via Random Forest Regression on Multi-resolution Gradient Features

In this paper, we propose a fully automatic, robust approach for segmenting proximal femur in conventional X-ray images. Our method is based on hierarchical landmark detection by random forest regression, where the detection results of 22 global landmarks are used to do the spatial normalization, and the detection results of the 59 local landmarks serve as the image cue for instantiation of a statistical shape model of the proximal femur. To detect landmarks in both levels, we use multi-resolution HoG (Histogram of Oriented Gradients) as features which can achieve better accuracy and robustness. The efficacy of the present method is demonstrated by experiments conducted on 150 clinical x-ray images. It was found that the present method could achieve an average point-to-curve error of 2.0 mm and that the present method was robust to low image contrast, noise and occlusions caused by implants.

Fully Automatic Segmentation of AP Pelvis X-rays via Random Forest Regression and Hierarchical Sparse Shape Composition

Knowledge of landmarks and contours in anteroposterior (AP) pelvis X-rays is invaluable for computer aided diagnosis, hip surgery planning and image-guided interventions. This paper presents a fully automatic and robust approach for landmarking and segmentation of both pelvis and femur in a conventional AP X-ray. Our approach is based on random forest regression and hierarchical sparse shape composition. Experiments conducted on 436 clinical AP pelvis x-rays show that our approach achieves an average point-to-curve error around 1.3 mm for femur and 2.2 mm for pelvis, both with success rates around 98%. Compared to existing methods, our approach exhibits better performance in both the robustness and the accuracy.