Transportability of Overall Survival Estimates From US to Canadian Patients With Advanced Non-Small Cell Lung Cancer With Implications for Regulatory and Health Technology Assessment.

IMPORTANCE: The external validity of survival outcomes derived from clinical practice data from US patients with advanced non-small cell lung cancer (NSCLC) is not known and is of potential importance because it may be used to support regulatory decision-making and health technology assessment outside of the US. OBJECTIVE: To evaluate whether overall survival (OS) estimates for a selected group of patients with advanced NSCLC from a large US clinical practice database are transportable to Canadian patients receiving the same systemic therapies. DESIGN, SETTING, AND PARTICIPANTS: This retrospective multicenter cohort study used transportability analysis to assess whether adjustment for pretreatment characteristics of eligible patient cohorts could reliably approximate OS estimated from US-based samples to Canadian populations. A total of 17 432 eligible adult patients who were diagnosed de novo with advanced NSCLC on or after January 1, 2011, were included in the analysis and followed up until September 30, 2020. Because data on race and ethnicity were available in the US database but not the Canadian database and because racial and ethnic distribution was likely to be similar between US and Canadian patients, these characteristics were not analyzed. EXPOSURES: Initiation of platinum-doublet chemotherapy or pembrolizumab monotherapy as first-line systemic treatment for advanced NSCLC. MAIN OUTCOMES AND MEASURES: OS measured from the time of initiation of the respective treatment regimen. RESULTS: Among 17 432 eligible patients, 15 669 patients from the US and 1763 patients from Canada were included in the analysis. Of those, 11 863 patients (sample size-weighted estimates of mean [SD] age, 68.0 [9.3] years; 6606 [55.7%] male; 10 100 from the US and 1763 from Canada) were included in the subset of patients with complete data for baseline covariates. A total of 13 532 US patients received first-line chemotherapy, and 2137 received first-line pembrolizumab monotherapy. Of those, 8447 patients (62.4%) in the first-line chemotherapy group and 1653 patients (77.3%) in the first-line pembrolizumab group had complete data on baseline covariates for outcome model estimation. A total of 1476 Canadian patients who received first-line chemotherapy and 287 patients who received first-line pembrolizumab monotherapy were identified from the target population. After standardization to baseline patient covariates in the Canadian cohorts, transported OS estimates revealed a less than 5% mean absolute difference from the observed OS in the target population (0.56% over 60 months of follow-up in the first-line chemotherapy group and 4.54% over 30 months of follow-up in the first-line pembrolizumab group). Negative control analysis using a mismatched outcome model revealed a 6.64% discrepancy and an incompatible survival curve shape. The results were robust to assumptions of random missingness for baseline covariates, to unadjusted differences in baseline metastases and comorbidities, and to differences in the standard of care between the US and Canada related to administration of second-line anti-programmed cell death 1 ligand 1 immunotherapy for patients who initiated first-line chemotherapy. CONCLUSIONS AND RELEVANCE: The results of this cohort study suggest that, under specific circumstances, OS estimates from US clinical practice data can be adjusted using baseline clinical characteristics to closely approximate OS in selected groups of Canadian patients with advanced NSCLC. These results may have implications for regulatory decision-making and health technology assessment in target populations outside of the US

Visualizing dimensionality reduction of systems biology data

One of the challenges in analyzing high-dimensional expression data is the detection of important biological signals. A common approach is to apply a dimension reduction method, such as principal component analysis. Typically, after application of such a method the data is projected and visualized in the new coordinate system, using scatter plots or profile plots. These methods provide good results if the data have certain properties which become visible in the new coordinate system and which were hard to detect in the original coordinate system. Often however, the application of only one method does not suffice to capture all important signals. Therefore several methods addressing different aspects of the data need to be applied. We have developed a framework for linear and non-linear dimension reduction methods within our visual analytics pipeline SpRay. This includes measures that assist the interpretation of the factorization result. Different visualizations of these measures can be combined with functional annotations that support the interpretation of the results. We show an application to high-resolution time series microarray data in the antibiotic-producing organism Streptomyces coelicolor as well as to microarray data measuring expression of cells with normal karyotype and cells with trisomies of human chromosomes 13 and 21

An effective all-atom potential for proteins

We describe and test an implicit solvent all-atom potential for simulations of protein folding and aggregation. The potential is developed through studies of structural and thermodynamic properties of 17 peptides with diverse secondary structure. Results obtained using the final form of the potential are presented for all these peptides. The same model, with unchanged parameters, is furthermore applied to a heterodimeric coiled-coil system, a mixed alpha/beta protein and a three-helix-bundle protein, with very good results. The computational efficiency of the potential makes it possible to investigate the free-energy landscape of these 49--67-residue systems with high statistical accuracy, using only modest computational resources by today's standards

Concept and optical design of the cross-disperser module for CRIRES

This is the peer reviewed version of the following article: Oliva, Ernesto, A. Tozzi, D. Ferruzzi, L. Origlia, A. Hatzes, R. Follert, T. Loewinger et al. "Concept and optical design of the cross-disperser module for CRIRES+." In SPIE Astronomical Telescopes+ Instrumentation, pp. 91477R-91477R. International Society for Optics and Photonics, 2014, which has been published in final form at 10.1117/12.2054381

Cross-species gene expression analysis of species specific differences in the preclinical assessment of pharmaceutical compounds

Animals are frequently used as model systems for determination of safety and efficacy in pharmaceutical research and development. However, significant quantitative and qualitative differences exist between humans and the animal models used in research. This is as a result of genetic variation between human and the laboratory animal. Therefore the development of a system that would allow the assessment of all molecular differences between species after drug exposure would have a significant impact on drug evaluation for toxicity and efficacy. Here we describe a cross-species microarray methodology that identifies and selects orthologous probes after cross-species sequence comparison to develop an orthologous cross-species gene expression analysis tool. The assumptions made by the use of this orthologous gene expression strategy for cross-species extrapolation is that; conserved changes in gene expression equate to conserved pharmacodynamic endpoints. This assumption is supported by the fact that evolution and selection have maintained the structure and function of many biochemical pathways over time, resulting in the conservation of many important processes. We demonstrate this cross-species methodology by investigating species specific differences of the peroxisome proliferatoractivator receptor (PPAR) a response in rat and human

A large-scale study of a poultry trading network in Bangladesh: implications for control and surveillance of avian influenza viruses

Since its first report in 2007, avian influenza (AI) has been endemic in Bangladesh. While live poultry marketing is widespread throughout the country and known to influence AI dissemination and persistence, trading patterns have not been described. The aim of this study is to assess poultry trading practices and features of the poultry trading networks which could promote AI spread, and their potential implications for disease control and surveillance. Data on poultry trading practices was collected from 849 poultry traders during a cross-sectional survey in 138 live bird markets (LBMs) across 17 different districts of Bangladesh. The quantity and origins of traded poultry were assessed for each poultry type in surveyed LBMs. The network of contacts between farms and LBMs resulting from commercial movements of live poultry was constructed to assess its connectivity and to identify the key premises influencing it

Pre-processing and differential expression analysis of Agilent microRNA arrays using the AgiMicroRna Bioconductor library

<p>Abstract</p> <p>Background</p> <p>The main research tool for identifying microRNAs involved in specific cellular processes is gene expression profiling using microarray technology. Agilent is one of the major producers of microRNA arrays, and microarray data are commonly analyzed by using R and the functions and packages collected in the Bioconductor project. However, an analytical package that integrates the specific characteristics of microRNA Agilent arrays has been lacking.</p> <p>Results</p> <p>This report presents the new bioinformatic tool <it>AgiMicroRNA </it>for the pre-processing and differential expression analysis of Agilent microRNA array data. The software is implemented in the open-source statistical scripting language R and is integrated in the Bioconductor project (<url>http://www.bioconductor.org</url>) under the GPL license. For the pre-processing of the microRNA signal, <it>AgiMicroRNA </it>incorporates the <it>robust multiarray average algorithm</it>, a method that produces a summary measure of the microRNA expression using a linear model that takes into account the probe affinity effect. To obtain a normalized microRNA signal useful for the statistical analysis, <it>AgiMicroRna </it>offers the possibility of employing either the processed signal estimated by the <it>robust multiarray average algorithm </it>or the processed signal produced by the Agilent image analysis software. The <it>AgiMicroRNA </it>package also incorporates different graphical utilities to assess the quality of the data. <it>AgiMicroRna </it>uses the linear model features implemented in the <it>limma </it>package to assess the differential expression between different experimental conditions and provides links to the <it>miRBase </it>for those microRNAs that have been declared as significant in the statistical analysis.</p> <p>Conclusions</p> <p><it>AgiMicroRna </it>is a rational collection of Bioconductor functions that have been wrapped into specific functions in order to ease and systematize the pre-processing and statistical analysis of Agilent microRNA data. The development of this package contributes to the Bioconductor project filling the gap in microRNA array data analysis.</p

A finite strain fibre-reinforced viscoelasto-viscoplastic model of plant cell wall growth

A finite strain fibre-reinforced viscoelasto-viscoplastic model implemented in a finite element (FE) analysis is presented to study the expansive growth of plant cell walls. Three components of the deformation of growing cell wall, i.e. elasticity, viscoelasticity and viscoplasticity-like growth, are modelled within a consistent framework aiming to present an integrative growth model. The two aspects of growth—turgor-driven creep and new material deposition—and the interplay between them are considered by presenting a yield function, flow rule and hardening law. A fibre-reinforcement formulation is used to account for the role of cellulose microfibrils in the anisotropic growth. Mechanisms in in vivo growth are taken into account to represent the corresponding biologycontrolled behaviour of a cell wall. A viscoelastic formulation is proposed to capture the viscoelastic response in the cell wall. The proposed constitutive model provides a unique framework for modelling both the in vivo growth of cell wall dominated by viscoplasticity-like behaviour and in vitro deformation dominated by elastic or viscoelastic responses. A numerical scheme is devised, and FE case studies are reported and compared with experimental data

Performance evaluation of commercial miRNA expression array platforms

<p>Abstract</p> <p>Background</p> <p>microRNAs (miRNA) are short, endogenous transcripts that negatively regulate the expression of specific mRNA targets. The relative abundance of miRNAs is linked to function <it>in vivo </it>and miRNA expression patterns are potentially useful signatures for the development of diagnostic, prognostic and therapeutic biomarkers.</p> <p>Finding</p> <p>We compared the performance characteristics of four commercial miRNA array technologies and found that all platforms performed well in separate measures of performance.</p> <p>Conclusions</p> <p>The Ambion and Agilent platforms were more accurate, whereas the Illumina and Exiqon platforms were more specific. Furthermore, the data analysis approach had a large impact on the performance, predominantly by improving precision.</p

B Cells Regulate Neutrophilia during Mycobacterium tuberculosis Infection and BCG Vaccination by Modulating the Interleukin-17 Response

We have previously demonstrated that B cells can shape the immune response to Mycobacterium tuberculosis, including the level of neutrophil infiltration and granulomatous inflammation at the site of infection. The present study examined the mechanisms by which B cells regulate the host neutrophilic response upon exposure to mycobacteria and how neutrophilia may influence vaccine efficacy. To address these questions, a murine aerosol infection tuberculosis (TB) model and an intradermal (ID) ear BCG immunization mouse model, involving both the μMT strain and B cell-depleted C57BL/6 mice, were used. IL (interleukin)-17 neutralization and neutrophil depletion experiments using these systems provide evidence that B cells can regulate neutrophilia by modulating the IL-17 response during M. tuberculosis infection and BCG immunization. Exuberant neutrophilia at the site of immunization in B cell-deficient mice adversely affects dendritic cell (DC) migration to the draining lymph nodes and attenuates the development of the vaccine-induced Th1 response. The results suggest that B cells are required for the development of optimal protective anti-TB immunity upon BCG vaccination by regulating the IL-17/neutrophilic response. Administration of sera derived from M. tuberculosis-infected C57BL/6 wild-type mice reverses the lung neutrophilia phenotype in tuberculous μMT mice. Together, these observations provide insight into the mechanisms by which B cells and humoral immunity modulate vaccine-induced Th1 response and regulate neutrophila during M. tuberculosis infection and BCG immunization. © 2013 Kozakiewicz et al