Clinical benefit of fulvestrant in postmenopausal women with advanced breast cancer and primary or acquired resistance to aromatase inhibitors: final results of phase II Swiss Group for Clinical Cancer Research Trial (SAKK 21/00).

BACKGROUND: The aim of this study was to evaluate the efficacy and tolerability of fulvestrant, an estrogen receptor antagonist, in postmenopausal women with hormone-responsive tumors progressing after aromatase inhibitor (AI) treatment. PATIENTS AND METHODS: This is a phase II, open, multicenter, noncomparative study. Two patient groups were prospectively considered: group A (n=70) with AI-responsive disease and group B (n=20) with AI-resistant disease. Fulvestrant 250 mg was administered as intramuscular injection every 28 (+/-3) days. RESULTS: All patients were pretreated with AI and 84% also with tamoxifen or toremifene; 67% had bone metastases and 45% liver metastases. Fulvestrant administration was well tolerated and yielded a clinical benefit (CB; defined as objective response or stable disease [SD] for >or=24 weeks) in 28% (90% confidence interval [CI] 19% to 39%) of patients in group A and 37% (90% CI 19% to 58%) of patients in group B. Median time to progression (TTP) was 3.6 (95% CI 3.0 to 4.8) months in group A and 3.4 (95% CI 2.5 to 6.7) months in group B. CONCLUSIONS: Overall, 30% of patients who had progressed following prior AI treatment gained CB with fulvestrant, thereby delaying indication to start chemotherapy. Prior response to an AI did not appear to be predictive for benefit with fulvestrant.

Why the EU does not Have an Independent Competition Agency: French Interests and Transaction Costs in Early European Integration

A major achievement of new institutionalism in economics and political science is the formalisation of the idea that certain policies are more efficient when administered by a politically independent organisation. Based on this insight, several policy actors and scholars criticise the European Community for relying too much on a multi-task, collegial, and politicised organisation, the European Commission. This raises important questions, some constitutional (who should be able to change the corresponding procedural rules?) and some political-economic (is Europe truly committed to free and competitive markets?). Though acknowledging the relevance of legal and normative arguments, this paper contributes to the debate with a positive political-scientific perspective. Based on the view that institutional equilibria raise the question of equilibrium institutions, it shows that collegiality was (a) an equilibrium institution during the Paris negotiations of 1950-51; and (b) an institutional equilibrium for the following 50 years. The conclusion points to some recent changes in the way that European competition policy is implemented, and discusses how these affect the “constitutional” principle of collegial European governance.

Automatic Mallampati Classification Using Active Appearance Models

Difficult tracheal intubation assessment is an important research topic in anesthesia as failed intubations are important causes of mortality in anesthetic practice. The modified Mallampati score is widely used, alone or in conjunction with other criteria, to predict the difficulty of intubation. This work presents an automatic method to assess the modified Mallampati score from an image of a patient with the mouth wide open. For this purpose we propose an active appearance models (AAM) based method and use linear support vector machines (SVM) to select a subset of relevant features obtained using the AAM. This feature selection step proves to be essential as it improves drastically the performance of classification, which is obtained using SVM with RBF kernel and majority voting. We test our method on images of 100 patients undergoing elective surgery and achieve 97.9% accuracy in the leave-one-out crossvalidation test and provide a key element to an automatic difficult intubation assessment system.

Neoadjuvant chemoradiotherapy with or without panitumumab in patients with wild-type KRAS, locally advanced rectal cancer (LARC): a randomized, multicenter, phase II trial SAKK 41/07.

BACKGROUND: We conducted a randomized, phase II, multicenter study to evaluate the anti-epidermal growth factor receptor (EGFR) mAb panitumumab (P) in combination with chemoradiotherapy (CRT) with standard-dose capecitabine as neoadjuvant treatment for wild-type KRAS locally advanced rectal cancer (LARC). PATIENTS AND METHODS: Patients with wild-type KRAS, T3-4 and/or N+ LARC were randomly assigned to receive CRT with or without P (6 mg/kg). The primary end-point was pathological near-complete or complete tumor response (pNC/CR), defined as grade 3 (pNCR) or 4 (pCR) histological regression by Dworak classification (DC). RESULTS: Forty of 68 patients were randomly assigned to P + CRT and 28 to CRT. pNC/CR was achieved in 21 patients (53%) treated with P + CRT [95% confidence interval (CI) 36%-69%] versus 9 patients (32%) treated with CRT alone (95% CI: 16%-52%). pCR was achieved in 4 (10%) and 5 (18%) patients, and pNCR in 17 (43%) and 4 (14%) patients. In immunohistochemical analysis, most DC 3 cells were not apoptotic. The most common grade ≥3 toxic effects in the P + CRT/CRT arm were diarrhea (10%/6%) and anastomotic leakage (15%/4%). CONCLUSIONS: The addition of panitumumab to neoadjuvant CRT in patients with KRAS wild-type LARC resulted in a high pNC/CR rate, mostly grade 3 DC. The results of both treatment arms exceeded prespecified thresholds. The addition of panitumumab increased toxicity.

Models i formes de la pintura catalana del Barroc: el mirall de l'art francès

Estudi elaborat a partir d’una estada a l’Institut National d'Histoire de l'Art- Bibliothèque Nationale de France entre l'1 i el 31 de juliol de 2007. S’ha treballat en la recerca documental sobre les relacions artístiques entre França i Catalunya a l’Època Moderna. Els materials o fons documentals d’interès han estat dos: els fons gràfics d’estampes i gravats de la Bibliothèque Nationale, no tant en el sentit de consulta dels originals –que en alguna ocasió també- com sí en el la visualització de les vastíssimes fototeques, que ha permès a l’autor aplegar un bon nombre d’imatges que en el futur serviran per posar en relació la cultura figurativa francesa –sobretot de la pintura i de l’escultura, però també de la tractadística arquitectònica- amb la catalana de l’època, ja sigui per constatar les semblances com per fer notar les diferències en els usos dels models figuratius. S’ha buidat material bibliogràfic difícil de localitzar a Catalunya. Són publicacions referides a gravat, d’una banda, i a patrimoni artístic. Aquest darrer aspecte s’ha treballat des de dos vessants: en seguir notícies de la presència d’artistes catalans a França i viceversa, i en buscar dades sobre l’espoli d’obres d’art portat a terme a Catalunya durant el període napoleònic.

Seigniorage-maximizing inflation

What is the seigniorage-maximizing level of inflation? Four models formulae for the seigniorage maximizing inflation rate (SMIR) are compared. Two sticky-price models arrive at very different quantitative recommendations although both predict somewhat lower SMIRs than Cagan’s formula and a variant of a .ex-price model due to Kimbrough (2006). The models differ markedly in how inflation distorts the labour market: The Calvo model implies that inflation and output are negatively related and that output is falling in price stickiness whilst the Rotemberg cost-of-price-adjustment model implies exactly the opposite. Interestingly, if our version of the Calvo model is to be believed, the level of inflation experienced recently in advanced economies such as the USA and the UK may be quite close to the SMIR.

The Estimation of Technical Efficiency Effects Models with an Example Applied to the Thai Manufacturing Sector

This paper does two things. First, it presents alternative approaches to the standard methods of estimating productive efficiency using a production function. It favours a parametric approach (viz. the stochastic production frontier approach) over a nonparametric approach (e.g. data envelopment analysis); and, further, one that provides a statistical explanation of efficiency, as well as an estimate of its magnitude. Second, it illustrates the favoured approach (i.e. the ‘single stage procedure’) with estimates of two models of explained inefficiency, using data from the Thai manufacturing sector, after the crisis of 1997. Technical efficiency is modelled as being dependent on capital investment in three major areas (viz. land, machinery and office appliances) where land is intended to proxy the effects of unproductive, speculative capital investment; and both machinery and office appliances are intended to proxy the effects of productive, non-speculative capital investment. The estimates from these models cast new light on the five-year long, post-1997 crisis period in Thailand, suggesting a structural shift from relatively labour intensive to relatively capital intensive production in manufactures from 1998 to 2002.

UK Macroeconomic Forecasting with Many Predictors: Which Models Forecast Best and When Do They Do So?

Block factor methods offer an attractive approach to forecasting with many predictors. These extract the information in these predictors into factors reflecting different blocks of variables (e.g. a price block, a housing block, a financial block, etc.). However, a forecasting model which simply includes all blocks as predictors risks being over-parameterized. Thus, it is desirable to use a methodology which allows for different parsimonious forecasting models to hold at different points in time. In this paper, we use dynamic model averaging and dynamic model selection to achieve this goal. These methods automatically alter the weights attached to different forecasting models as evidence comes in about which has forecast well in the recent past. In an empirical study involving forecasting output growth and inflation using 139 UK monthly time series variables, we find that the set of predictors changes substantially over time. Furthermore, our results show that dynamic model averaging and model selection can greatly improve forecast performance relative to traditional forecasting methods.

Two different 3D biogeochemical models for the NW mediterranean sea: validation with Meris data and intercomparison

Report for the scientific sojourn carried out at the University of New South Wales from February to June the 2007. Two different biogeochemical models are coupled to a three dimensional configuration of the Princeton Ocean Model (POM) for the Northwestern Mediterranean Sea (Ahumada and Cruzado, 2007). The first biogeochemical model (BLANES) is the three-dimensional version of the model described by Bahamon and Cruzado (2003) and computes the nitrogen fluxes through six compartments using semi-empirical descriptions of biological processes. The second biogeochemical model (BIOMEC) is the biomechanical NPZD model described in Baird et al. (2004), which uses a combination of physiological and physical descriptions to quantify the rates of planktonic interactions. Physical descriptions include, for example, the diffusion of nutrients to phytoplankton cells and the encounter rate of predators and prey. The link between physical and biogeochemical processes in both models is expressed by the advection-diffusion of the non-conservative tracers. The similarities in the mathematical formulation of the biogeochemical processes in the two models are exploited to determine the parameter set for the biomechanical model that best fits the parameter set used in the first model. Three years of integration have been carried out for each model to reach the so called perpetual year run for biogeochemical conditions. Outputs from both models are averaged monthly and then compared to remote sensing images obtained from sensor MERIS for chlorophyll.

Stochastic Search Variable Selection in Vector Error Correction Models with an Application to a Model of the UK Macroeconomy

This paper develops methods for Stochastic Search Variable Selection (currently popular with regression and Vector Autoregressive models) for Vector Error Correction models where there are many possible restrictions on the cointegration space. We show how this allows the researcher to begin with a single unrestricted model and either do model selection or model averaging in an automatic and computationally efficient manner. We apply our methods to a large UK macroeconomic model.

The ghost of past species occurrence: improving species distribution models for presence-only data

1. Model-based approaches have been used increasingly in conservation biology over recent years. Species presence data used for predictive species distribution modelling are abundant in natural history collections, whereas reliable absence data are sparse, most notably for vagrant species such as butterflies and snakes. As predictive methods such as generalized linear models (GLM) require absence data, various strategies have been proposed to select pseudo-absence data. However, only a few studies exist that compare different approaches to generating these pseudo-absence data. 2. Natural history collection data are usually available for long periods of time (decades or even centuries), thus allowing historical considerations. However, this historical dimension has rarely been assessed in studies of species distribution, although there is great potential for understanding current patterns, i.e. the past is the key to the present. 3. We used GLM to model the distributions of three 'target' butterfly species, Melitaea didyma, Coenonympha tullia and Maculinea teleius, in Switzerland. We developed and compared four strategies for defining pools of pseudo-absence data and applied them to natural history collection data from the last 10, 30 and 100 years. Pools included: (i) sites without target species records; (ii) sites where butterfly species other than the target species were present; (iii) sites without butterfly species but with habitat characteristics similar to those required by the target species; and (iv) a combination of the second and third strategies. Models were evaluated and compared by the total deviance explained, the maximized Kappa and the area under the curve (AUC). 4. Among the four strategies, model performance was best for strategy 3. Contrary to expectations, strategy 2 resulted in even lower model performance compared with models with pseudo-absence data simulated totally at random (strategy 1). 5. Independent of the strategy model, performance was enhanced when sites with historical species presence data were not considered as pseudo-absence data. Therefore, the combination of strategy 3 with species records from the last 100 years achieved the highest model performance. 6. Synthesis and applications. The protection of suitable habitat for species survival or reintroduction in rapidly changing landscapes is a high priority among conservationists. Model-based approaches offer planning authorities the possibility of delimiting priority areas for species detection or habitat protection. The performance of these models can be enhanced by fitting them with pseudo-absence data relying on large archives of natural history collection species presence data rather than using randomly sampled pseudo-absence data.