Second ESMO consensus conference on lung cancer: pathology and molecular biomarkers for non-small-cell lung cancer.

To complement the existing treatment guidelines for all tumour types, ESMO organises consensus conferences to focus on specific issues in each type of tumour. The Second ESMO Consensus Conference on Lung Cancer was held on 11-12 May 2013 in Lugano. A total of 35 experts met to address several questions on management of patients with non-small-cell lung cancer (NSCLC) in each of four areas: pathology and molecular biomarkers, early stage disease, locally advanced disease and advanced (metastatic) disease. For each question, recommendations were made including reference to the grade of recommendation and level of evidence. This consensus paper focuses on recommendations for pathology and molecular biomarkers in relation to the diagnosis of lung cancer, primarily non-small-cell carcinomas.

Immunoreactive proteins of Saccharopolyspora rectivirgula for farmer's lung serodiagnosis.

PURPOSE: Saccharopolyspora rectivirgula is the principal cause of farmer's lung disease (FLD). Serodiagnosis is based on immunoprecipitation techniques or enzyme immunoassays with homemade crude antigens and is not standardized. We aimed to produce specific recombinant antigens for the development of a standardized ELISA. EXPERIMENTAL DESIGN: We recruited 41 patients and 43 healthy exposed controls from five university hospital pneumology departments in France and Switzerland. S. rectivirgula proteins were extracted, separated by 2D electrophoresis, and subjected to Western blotting, with sera from FLD patients or controls. FLD-specific proteins were identified by MS and were produced as recombinant antigens. The diagnostic performance of ELISA tests using the recombinant antigens was assessed with all the sera from FLD patients and controls. RESULTS: We identified 25 FLD-specific proteins, some of which play important roles in transport, nutrition, or virulence. We produced 17 of these proteins as recombinant antigens and assessed their suitability for inclusion in the ELISA test. A combination of three of these proteins (SR1FA, SR17, and SR22) proved remarkably effective at discriminating between patients and controls, with a sensitivity of 83% and a specificity of 77%. CONCLUSIONS AND CLINICAL RELEVANCE: The recombinant antigens produced in this study constitute a major step toward the improvement of diagnostic performance and the standardization of FLD serodiagnosis.

Robust response transformations based on optimal prediction

Nonlinear regression problems can often be reduced to linearity by transforming the response variable (e.g., using the Box-Cox family of transformations). The classic estimates of the parameter defining the transformation as well as of the regression coefficients are based on the maximum likelihood criterion, assuming homoscedastic normal errors for the transformed response. These estimates are nonrobust in the presence of outliers and can be inconsistent when the errors are nonnormal or heteroscedastic. This article proposes new robust estimates that are consistent and asymptotically normal for any unimodal and homoscedastic error distribution. For this purpose, a robust version of conditional expectation is introduced for which the prediction mean squared error is replaced with an M scale. This concept is then used to develop a nonparametric criterion to estimate the transformation parameter as well as the regression coefficients. A finite sample estimate of this criterion based on a robust version of smearing is also proposed. Monte Carlo experiments show that the new estimates compare favorably with respect to the available competitors.

Accounting information and the prediction of farm viability

Until recently farm management made little use of accounting and agriculture has been largely excluded from the scope of accounting standards. This article examines the current use of accounting in agriculture and points theneed to establish accounting standards for agriculture. Empirical evidence shows that accounting can make a significant contribution to agricultural management and farm viability and could also be important for other agents involved in agricultural decision making. Existing literature on failureprediction models and farm viability prediction studies provide the starting point for our research, in which two dichotomous logit models were applied to subsamples of viable and unviable farms in Catalonia, Spain. The firstmodel considered only non-financial variables, while the other also considered financial ones. When accounting variables were added to the model, a significant reduction in deviance was observed.

Improving generalized regression analysis for the spatial prediction of forest communities

Aim This study used data from temperate forest communities to assess: (1) five different stepwise selection methods with generalized additive models, (2) the effect of weighting absences to ensure a prevalence of 0.5, (3) the effect of limiting absences beyond the environmental envelope defined by presences, (4) four different methods for incorporating spatial autocorrelation, and (5) the effect of integrating an interaction factor defined by a regression tree on the residuals of an initial environmental model. Location State of Vaud, western Switzerland. Methods Generalized additive models (GAMs) were fitted using the grasp package (generalized regression analysis and spatial predictions, http://www.cscf.ch/grasp). Results Model selection based on cross-validation appeared to be the best compromise between model stability and performance (parsimony) among the five methods tested. Weighting absences returned models that perform better than models fitted with the original sample prevalence. This appeared to be mainly due to the impact of very low prevalence values on evaluation statistics. Removing zeroes beyond the range of presences on main environmental gradients changed the set of selected predictors, and potentially their response curve shape. Moreover, removing zeroes slightly improved model performance and stability when compared with the baseline model on the same data set. Incorporating a spatial trend predictor improved model performance and stability significantly. Even better models were obtained when including local spatial autocorrelation. A novel approach to include interactions proved to be an efficient way to account for interactions between all predictors at once. Main conclusions Models and spatial predictions of 18 forest communities were significantly improved by using either: (1) cross-validation as a model selection method, (2) weighted absences, (3) limited absences, (4) predictors accounting for spatial autocorrelation, or (5) a factor variable accounting for interactions between all predictors. The final choice of model strategy should depend on the nature of the available data and the specific study aims. Statistical evaluation is useful in searching for the best modelling practice. However, one should not neglect to consider the shapes and interpretability of response curves, as well as the resulting spatial predictions in the final assessment.

Family physician involvement in cancer care follow-up: the experience of a cohort of patients with lung cancer.

PURPOSE There has been little research describing the involvement of family physicians in the follow up of patients with cancer especially during the primary treatment phase We undertook a prospective longitudinal study of patients with lung cancer to assess their family physician s involvement in their follow up at the different phases of cancer METHODS In 5 hospitals in the province of Quebec Canada patients with a recent diagnosis of lung cancer were surveyed every 3 to 6 months whether they had metastasis or not, for a maximum of 18 months to assess aspects of their family physician s involvement in cancer care RESULTS Of the 395 participating patients 92% had a regular family physician but only 60% had been referred to a specialist by him/her or a colleague for the diagnosis of their lung cancer A majority of patients identified the oncology team or oncologists as mainly responsible for their cancer care throughout their cancer journey except at the advanced phase where a majority attributed this role to their family physician At baseline only 16% of patients perceived a shared care pattern between their family physician and oncologists but this pro portion increased with cancer progression Most patients would have liked their family physician to be more involved in all aspects of cancer care CONCLUSIONS Although patients perceive that the oncology team is the main party responsible for the follow up of their lung cancer they also wish their family physicians to be involved Better communication and collaboration between family physicians and the oncology team are needed to facilitate shared care in cancer follow up

Killing by lung cancer or by diabetes? The trade-off between smoking and obesity

As the prevalence of smoking has decreased to below 20%, health practitioners interest has shifted towards theprevalence of obesity, and reducing it is one of the major health challenges in decades to come. In this paper westudy the impact that the final product of the anti-smoking campaign, that is, smokers quitting the habit, had onaverage weight in the population. To these ends, we use data from the Behavioral Risk Factors Surveillance System,a large series of independent representative cross-sectional surveys. We construct a synthetic panel that allows us tocontrol for unobserved heterogeneity and we exploit the exogenous changes in taxes and regulations to instrumentthe endogenous decision to give up the habit of smoking. Our estimates, are very close to estimates issued in the 90sby the US Department of Health, and indicate that a 10% decrease in the incidence of smoking leads to an averageweight increase of 2.2 to 3 pounds, depending on choice of specification. In addition, we find evidence that the effectovershoots in the short run, although a significant part remains even after two years. However, when we split thesample between men and women, we only find a significant effect for men. Finally, the implicit elasticity of quittingsmoking to the probability of becoming obese is calculated at 0.58. This implies that the net benefit from reducingthe incidence of smoking by 1% is positive even though the cost to society is $0.6 billions.

Genome-Wide Prediction Methods in Highly Diverse and Heterozygous Species: Proof-of-Concept through Simulation in Grapevine.

Nowadays, genome-wide association studies (GWAS) and genomic selection (GS) methods which use genome-wide marker data for phenotype prediction are of much potential interest in plant breeding. However, to our knowledge, no studies have been performed yet on the predictive ability of these methods for structured traits when using training populations with high levels of genetic diversity. Such an example of a highly heterozygous, perennial species is grapevine. The present study compares the accuracy of models based on GWAS or GS alone, or in combination, for predicting simple or complex traits, linked or not with population structure. In order to explore the relevance of these methods in this context, we performed simulations using approx 90,000 SNPs on a population of 3,000 individuals structured into three groups and corresponding to published diversity grapevine data. To estimate the parameters of the prediction models, we defined four training populations of 1,000 individuals, corresponding to these three groups and a core collection. Finally, to estimate the accuracy of the models, we also simulated four breeding populations of 200 individuals. Although prediction accuracy was low when breeding populations were too distant from the training populations, high accuracy levels were obtained using the sole core-collection as training population. The highest prediction accuracy was obtained (up to 0.9) using the combined GWAS-GS model. We thus recommend using the combined prediction model and a core-collection as training population for grapevine breeding or for other important economic crops with the same characteristics.

A simple randomized algorithm for consistent sequential prediction of ergodic time series

We present a simple randomized procedure for the prediction of a binary sequence. The algorithm uses ideas from recent developments of the theory of the prediction of individual sequences. We show that if thesequence is a realization of a stationary and ergodic random process then the average number of mistakes converges, almost surely, to that of the optimum, given by the Bayes predictor.

Abnormal Lung Function and Risk for Heart Failure in the Elderly: The Health, Aging, and Body Composition Study

Background: Chronic obstructive pulmonary disease (COPD) has been associated with increased risk for heart failure (HF). The impact of subclinical abnormal spirometric findings on HF risk among older adults without history of COPD is not well elucidated. Methods: We evaluated 2125 participants (age 73.6±2.9 years; 50.5% men; 62.3% white; 45.6/9.4% past/current smokers; body mass index [BMI] 27.2±4.6 kg/m2) without prevalent COPD or HF who underwent baseline spirometry in the Health ABC Study. Abnormal lung function was defined either as forced vital capacity (FVC) below lower limit of normal (LLN) or forced expiratory volume in 1st sec (FEV1) to FVC ratio below LLN. Results: On follow-up (median, 9.4 years), 68 of 350 (19.4%) participants with abnormal lung function developed HF, as compared to 172 of 1775 (9.7%) participants with normal lung function (hazard ratio [HR], 2.31; 95% confidence interval [CI], 1.74 -3.06; P<.001). This increased risk persisted after adjusting for all other independent predictors of HF in the Health ABC Study, BMI, incident coronary events, and several inflammatory markers (HR, 1.82; 95% CI, 1.30 -2.54; P<.001), and remained constant over time. Baseline FVC and FEV1 had a linear association with HF risk (Figure). In adjusted models, HF risk increased by 21% (95% CI, 10 -36%) per 10% decrease in FVC and 18% (95% CI, 10 -28%) per 10% decrease in FEV1 (both P<.001); this association persisted among participants with normal lung function at baseline. Findings were consistent across sex, race, and smoking status. Conclusions: Subclinical abnormal spirometric findings are prevalent among older adults and are independently associated with risk for incident HF.

Whole brain radiotherapy with a conformational external beam radiation boost for lung cancer patients with 1-3 brain metastasis: a multi institutional study.

BACKGROUND: To determine the outcome of patients with brain metastasis (BM) from lung cancer treated with an external beam radiotherapy boost (RTB) after whole brain radiotherapy (WBRT). METHODS: A total of 53 BM patients with lung cancer were treated sequentially with WBRT and RTB between 1996 and 2008 according to our institutional protocol. Mean age was 58.8 years. The median KPS was 90. Median recursive partitioning analysis (RPA) and graded prognostic assessment (GPA) grouping were 2 and 2.5, respectively. Surgery was performed on 38 (71%) patients. The median number of BM was 1 (range, 1-3). Median WBRT and RTB combined dose was 39 Gy (range, 37.5-54). Median follow-up was 12.0 months. RESULTS: During the period of follow-up, 37 (70%) patients died. The median overall survival (OS) was 14.5 months. Only 13 patients failed in the brain. The majority of patients (n = 29) failed distantly. The 1-year OS, -local control, extracranial failure rates were 61.2%, 75.2% and 60.8%, respectively. On univariate analysis, improved OS was found to be significantly associated with total dose (< or = 39 Gy vs. > 39 Gy; p < 0.01), age < 65 (p < 0.01), absence of extracranial metastasis (p < 0.01), GPA > or = 2.5 (p = 0.01), KPS > or = 90 (p = 0.01), and RPA < 2 (p = 0.04). On multivariate analysis, total dose (p < 0.01) and the absence of extracranial metastasis (p = 0.03) retained statistical significance. CONCLUSIONS: The majority of lung cancer patients treated with WBRT and RTB progressed extracranially. There might be a subgroup of younger patients with good performance status and no extracranial disease who may benefit from dose escalation after WBRT to the metastatic site.

Ostéo-arthropathie hypertrophiante révélatrice d'un hémangio-endothéliome épithélioïde multifocal hépatique et pulmonaire [Hypertrophic osteoarthropathy disclosing hepatic and pulmonary multifocal epithelioid hemangioendothelioma]

Epithelioid hemangioendothelioma is a rare, low-grade vascular malignancy reported for the first time in 1982 by Weiss and Enzinger. It involves one or, more rarely, several organs. We report a case involving the lungs and liver, in which the first manifestation was symptomatic hypertrophic osteoarthropathy. Findings four years after the diagnosis included very slow tumor spread, resolution of symptoms, and stabilization of radiological changes.

Prediction of functional outcome 18 months after a first psychotic episode: a proton magnetic resonance spectroscopy study.

CONTEXT: Recent magnetic resonance imaging studies have attempted to relate volumetric brain measurements in early schizophrenia to clinical and functional outcome some years later. These studies have generally been negative, perhaps because gray and white matter volumes inaccurately assess the underlying dysfunction that might be predictive of outcome. OBJECTIVE: To investigate the predictive value of frontal and temporal spectroscopy measures for outcome in patients with first-episode psychoses. DESIGN: Left prefrontal cortex and left mediotemporal lobe voxels were assessed using proton magnetic resonance spectroscopy to provide the ratio of N-acetylaspartate (NAA) and choline-containing compounds to creatine and phosphocreatine (Cr) (NAA/Cr ratio). These data were used to predict outcome at 18 months after admission, as assessed by a systematic medical record audit. SETTING: Early psychosis clinic. PARTICIPANTS: Forty-six patients with first-episode psychosis. MAIN OUTCOME MEASURES: We used regression models that included age at imaging and duration of untreated psychosis to predict outcome scores on the Global Assessment of Functioning Scale, Clinical Global Impression scales, and Social and Occupational Functional Assessment Scale, as well as the number of admissions during the treatment period. We then further considered the contributions of premorbid function and baseline level of negative symptoms. RESULTS: The only spectroscopic predictor of outcome was the NAA/Cr ratio in the prefrontal cortex. Low scores on this variable were related to poorer outcome on all measures. In addition, the frontal NAA/Cr ratio explained 17% to 30% of the variance in outcome. CONCLUSIONS: Prefrontal neuronal dysfunction is an inconsistent feature of early psychosis; rather, it is an early marker of poor prognosis across the first years of illness. The extent to which this can be used to guide treatment and whether it predicts outcome some years after first presentation are questions for further research.