A Cox Model for Biostatistics of the Future

Professor Sir David R. Cox (DRC) is widely acknowledged as among the most important scientists of the second half of the twentieth century. He inherited the mantle of statistical science from Pearson and Fisher, advanced their ideas, and translated statistical theory into practice so as to forever change the application of statistics in many fields, but especially biology and medicine. The logistic and proportional hazards models he substantially developed, are arguably among the most influential biostatistical methods in current practice. This paper looks forward over the period from DRC's 80th to 90th birthdays, to speculate about the future of biostatistics, drawing lessons from DRC's contributions along the way. We consider "Cox's model" of biostatistics, an approach to statistical science that: formulates scientific questions or quantities in terms of parameters gamma in probability models f(y; gamma) that represent in a parsimonious fashion, the underlying scientific mechanisms (Cox, 1997); partition the parameters gamma = theta, eta into a subset of interest theta and other "nuisance parameters" eta necessary to complete the probability distribution (Cox and Hinkley, 1974); develops methods of inference about the scientific quantities that depend as little as possible upon the nuisance parameters (Barndorff-Nielsen and Cox, 1989); and thinks critically about the appropriate conditional distribution on which to base infrences. We briefly review exciting biomedical and public health challenges that are capable of driving statistical developments in the next decade. We discuss the statistical models and model-based inferences central to the CM approach, contrasting them with computationally-intensive strategies for prediction and inference advocated by Breiman and others (e.g. Breiman, 2001) and to more traditional design-based methods of inference (Fisher, 1935). We discuss the hierarchical (multi-level) model as an example of the future challanges and opportunities for model-based inference. We then consider the role of conditional inference, a second key element of the CM. Recent examples from genetics are used to illustrate these ideas. Finally, the paper examines causal inference and statistical computing, two other topics we believe will be central to biostatistics research and practice in the coming decade. Throughout the paper, we attempt to indicate how DRC's work and the "Cox Model" have set a standard of excellence to which all can aspire in the future.

Evaluation of two fully automated novel enzyme-linked immunosorbent assays for the determination of human adiponectin in serum

BACKGROUND: In contrast to RIA, recently available ELISAs provide the potential for fully automated analysis of adiponectin. To date, studies reporting on the diagnostic characteristics of ELISAs and investigating on the relationship between ELISA- and RIA-based methods are rare. METHODS: Thus, we established and evaluated a fully automated platform (BEP 2000; Dade-Behring, Switzerland) for determination of adiponectin levels in serum by two different ELISA methods (competitive human adiponectin ELISA; high sensitivity human adiponectin sandwich ELISA; both Biovendor, Czech Republic). Further, as a reference method, we also employed a human adiponectin RIA (Linco Research, USA). Samples from 150 patients routinely presenting to our cardiology unit were tested. RESULTS: ELISA measurements could be accomplished in less than 3 h, measurement of RIA had a duration of 24 h. The ELISAs were evaluated for precision, analytical sensitivity and specificity, linearity on dilution and spiking recovery. In the investigated patients, type 2 diabetes, higher age and male gender were significantly associated with lower serum adiponectin concentrations. Correlations between the ELISA methods and the RIA were strong (competitive ELISA, r=0.82; sandwich ELISA, r=0.92; both p<0.001). However, Deming regression and Bland-Altman analysis indicated lack of agreement of the 3 methods preventing direct comparison of results. The equations of the regression lines are: Competitive ELISA=1.48 x RIA-0.88; High sensitivity sandwich ELISA=0.77 x RIA+1.01. CONCLUSIONS: Fully automated measurement of adiponectin by ELISA is feasible and substantially more rapid than RIA. The investigated ELISA test systems seem to exhibit analytical characteristics allowing for clinical application. In addition, there is a strong correlation between the ELISA methods and RIA. These findings might promote a more widespread use of adiponectin measurements in clinical research.

EFFICIENT EVALUATION OF RANKING PROCEDURES WHEN THE NUMBER OF UNITS IS LARGE WITH APPLICATION TO SNP IDENTIFICATION

Simulation-based assessment is a popular and frequently necessary approach to evaluation of statistical procedures. Sometimes overlooked is the ability to take advantage of underlying mathematical relations and we focus on this aspect. We show how to take advantage of large-sample theory when conducting a simulation using the analysis of genomic data as a motivating example. The approach uses convergence results to provide an approximation to smaller-sample results, results that are available only by simulation. We consider evaluating and comparing a variety of ranking-based methods for identifying the most highly associated SNPs in a genome-wide association study, derive integral equation representations of the pre-posterior distribution of percentiles produced by three ranking methods, and provide examples comparing performance. These results are of interest in their own right and set the framework for a more extensive set of comparisons.

Applied Graph Theory in Computer Vision and Pattern Recognition

This book will serve as a foundation for a variety of useful applications of graph theory to computer vision, pattern recognition, and related areas. It covers a representative set of novel graph-theoretic methods for complex computer vision and pattern recognition tasks. The first part of the book presents the application of graph theory to low-level processing of digital images such as a new method for partitioning a given image into a hierarchy of homogeneous areas using graph pyramids, or a study of the relationship between graph theory and digital topology. Part II presents graph-theoretic learning algorithms for high-level computer vision and pattern recognition applications, including a survey of graph based methodologies for pattern recognition and computer vision, a presentation of a series of computationally efficient algorithms for testing graph isomorphism and related graph matching tasks in pattern recognition and a new graph distance measure to be used for solving graph matching problems. Finally, Part III provides detailed descriptions of several applications of graph-based methods to real-world pattern recognition tasks. It includes a critical review of the main graph-based and structural methods for fingerprint classification, a new method to visualize time series of graphs, and potential applications in computer network monitoring and abnormal event detection.

Refining abacavir hypersensitivity diagnoses using a structured clinical assessment and genetic testing in the Swiss HIV Cohort Study

BACKGROUND: We aimed to assess the value of a structured clinical assessment and genetic testing for refining the diagnosis of abacavir hypersensitivity reactions (ABC-HSRs) in a routine clinical setting. METHODS: We performed a diagnostic reassessment using a structured patient chart review in individuals who had stopped ABC because of suspected HSR. Two HIV physicians blinded to the human leukocyte antigen (HLA) typing results independently classified these individuals on a scale between 3 (ABC-HSR highly likely) and -3 (ABC-HSR highly unlikely). Scoring was based on symptoms, onset of symptoms and comedication use. Patients were classified as clinically likely (mean score > or =2), uncertain (mean score > or = -1 and < or = 1) and unlikely (mean score < or = -2). HLA typing was performed using sequence-based methods. RESULTS: From 131 reassessed individuals, 27 (21%) were classified as likely, 43 (33%) as unlikely and 61 (47%) as uncertain ABC-HSR. Of the 131 individuals with suspected ABC-HSR, 31% were HLA-B*5701-positive compared with 1% of 140 ABC-tolerant controls (P < 0.001). HLA-B*5701 carriage rate was higher in individuals with likely ABC-HSR compared with those with uncertain or unlikely ABC-HSR (78%, 30% and 5%, respectively, P < 0.001). Only six (7%) HLA-B*5701-negative individuals were classified as likely HSR after reassessment. CONCLUSIONS: HLA-B*5701 carriage is highly predictive of clinically diagnosed ABC-HSR. The high proportion of HLA-B*5701-negative individuals with minor symptoms among individuals with suspected HSR indicates overdiagnosis of ABC-HSR in the era preceding genetic screening. A structured clinical assessment and genetic testing could reduce the rate of inappropriate ABC discontinuation and identify individuals at high risk for ABC-HSR.

Contribution of Ectodomain Mutations in Epidermal Growth Factor Receptor to Signaling in Glioblastoma Multiforme

CONTRIBUTION OF ECTODOMAIN MUTATIONS IN EPIDERMAL GROWTH FACTOR RECEPTOR TO SIGNALING IN GLIOBLASTOMA MULTIFORME Publication No._________ Marta Rojas, M.S. Supervisory Professor: Oliver Bögler, Ph.D. The Cancer Genome Atlas (TCGA) has conducted a comprehensive analysis of a large tumor cohort and has cataloged genetic alterations involving primary sequence variations and copy number aberrations of genes involved in key signaling pathways in glioblastoma (GBM). This dataset revealed missense ectodomain point mutations in epidermal growth factor receptor (EGFR), but the biological and clinical significance of these mutations is not well defined in the context of gliomas. In our study, we focused on understanding and defining the molecular mechanisms underlying the functions of EGFR ectodomain mutants. Using proteomic approaches to broadly analyze cell signaling, including antibody array and mass spectrometry-based methods, we found a differential spectrum of tyrosine phosphorylation across the EGFR ectodomain mutations that enabled us to stratify them into three main groups that correlate with either wild type EGFR (EGFR) or the long-studied mutant, EGFRvIII. Interestingly, one mutant shared characteristics of both groups suggesting a continuum of behaviors along which different mutants fall. Surprisingly, no substantial differences were seen in activation of classical downstream signaling pathways such as Akt and S6 pathways between these classes of mutants. Importantly, we demonstrated that ectodomain mutations lead to differential tumor growth capabilities in both in vitro (anchorage independent colony formation) and in vivo conditions (xenografts). Our data from the biological characterization allowed us to categorize the mutants into three main groups: the first group typified by EGFRvIII are mutations with a more aggressive phenotype including R108K and A289T; a second group characterized by a less aggressive phenotype exemplified by EGFR and the T263P mutation; and a third group which shared characteristics from both groups and is exemplified by the mutation A289D. In addition, we treated cells overexpressing the mutants with various agents employed in the clinic including temozolomide, cisplatin and tarceva. We found that cells overexpressing the mutants in general displayed resistance to the treatments. Our findings yield insights that help with the molecular characterization of these mutants. In addition, our results from the drug studies might be valuable in explaining differential responses to specific treatments in GBM patients.

Identification of cryptic Anopheles mosquito species by molecular protein profiling.

Vector control is the mainstay of malaria control programmes. Successful vector control profoundly relies on accurate information on the target mosquito populations in order to choose the most appropriate intervention for a given mosquito species and to monitor its impact. An impediment to identify mosquito species is the existence of morphologically identical sibling species that play different roles in the transmission of pathogens and parasites. Currently PCR diagnostics are used to distinguish between sibling species. PCR based methods are, however, expensive, time-consuming and their development requires a priori DNA sequence information. Here, we evaluated an inexpensive molecular proteomics approach for Anopheles species: matrix assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). MALDI-TOF MS is a well developed protein profiling tool for the identification of microorganisms but so far has received little attention as a diagnostic tool in entomology. We measured MS spectra from specimens of 32 laboratory colonies and 2 field populations representing 12 Anopheles species including the A. gambiae species complex. An important step in the study was the advancement and implementation of a bioinformatics approach improving the resolution over previously applied cluster analysis. Borrowing tools for linear discriminant analysis from genomics, MALDI-TOF MS accurately identified taxonomically closely related mosquito species, including the separation between the M and S molecular forms of A. gambiae sensu stricto. The approach also classifies specimens from different laboratory colonies; hence proving also very promising for its use in colony authentication as part of quality assurance in laboratory studies. While being exceptionally accurate and robust, MALDI-TOF MS has several advantages over other typing methods, including simple sample preparation and short processing time. As the method does not require DNA sequence information, data can also be reviewed at any later stage for diagnostic or functional patterns without the need for re-designing and re-processing biological material.

Clinical relevance of brain volume measures in multiple sclerosis.

Multiple sclerosis (MS) is a chronic disease with an inflammatory and neurodegenerative pathology. Axonal loss and neurodegeneration occurs early in the disease course and may lead to irreversible neurological impairment. Changes in brain volume, observed from the earliest stage of MS and proceeding throughout the disease course, may be an accurate measure of neurodegeneration and tissue damage. There are a number of magnetic resonance imaging-based methods for determining global or regional brain volume, including cross-sectional (e.g. brain parenchymal fraction) and longitudinal techniques (e.g. SIENA [Structural Image Evaluation using Normalization of Atrophy]). Although these methods are sensitive and reproducible, caution must be exercised when interpreting brain volume data, as numerous factors (e.g. pseudoatrophy) may have a confounding effect on measurements, especially in a disease with complex pathological substrates such as MS. Brain volume loss has been correlated with disability progression and cognitive impairment in MS, with the loss of grey matter volume more closely correlated with clinical measures than loss of white matter volume. Preventing brain volume loss may therefore have important clinical implications affecting treatment decisions, with several clinical trials now demonstrating an effect of disease-modifying treatments (DMTs) on reducing brain volume loss. In clinical practice, it may therefore be important to consider the potential impact of a therapy on reducing the rate of brain volume loss. This article reviews the measurement of brain volume in clinical trials and practice, the effect of DMTs on brain volume change across trials and the clinical relevance of brain volume loss in MS.

Localization of Epileptogenic Zone on Pre-surgical Intracranial EEG Recordings: Toward a Validation of Quantitative Signal Analysis Approaches

In patients diagnosed with pharmaco-resistant epilepsy, cerebral areas responsible for seizure generation can be defined by performing implantation of intracranial electrodes. The identification of the epileptogenic zone (EZ) is based on visual inspection of the intracranial electroencephalogram (IEEG) performed by highly qualified neurophysiologists. New computer-based quantitative EEG analyses have been developed in collaboration with the signal analysis community to expedite EZ detection. The aim of the present report is to compare different signal analysis approaches developed in four different European laboratories working in close collaboration with four European Epilepsy Centers. Computer-based signal analysis methods were retrospectively applied to IEEG recordings performed in four patients undergoing pre-surgical exploration of pharmaco-resistant epilepsy. The four methods elaborated by the different teams to identify the EZ are based either on frequency analysis, on nonlinear signal analysis, on connectivity measures or on statistical parametric mapping of epileptogenicity indices. All methods converge on the identification of EZ in patients that present with fast activity at seizure onset. When traditional visual inspection was not successful in detecting EZ on IEEG, the different signal analysis methods produced highly discordant results. Quantitative analysis of IEEG recordings complement clinical evaluation by contributing to the study of epileptogenic networks during seizures. We demonstrate that the degree of sensitivity of different computer-based methods to detect the EZ in respect to visual EEG inspection depends on the specific seizure pattern.

Computed Ultrasound Tomography in Echo mode (CUTE) of speed of sound for diagnosis and for aberration correction in pulse-echo sonography

Sound speed as a diagnostic marker for various diseases of human tissue has been of interest for a while. Up to now, mostly transmission ultrasound computed tomography (UCT) was able to detect spatially resolved sound speed, and its promise as a diagnostic tool has been demonstrated. However, UCT is limited to acoustically transparent samples such as the breast. We present a novel technique where spatially resolved detection of sound speed can be achieved using conventional pulse-echo equipment in reflection mode. For this purpose, pulse-echo images are acquired under various transmit beam directions and a two-dimensional map of the sound speed is reconstructed from the changing phase of local echoes using a direct reconstruction method. Phantom results demonstrate that a high spatial resolution (1 mm) and contrast (0.5 % of average sound speed) can be achieved suitable for diagnostic purposes. In comparison to previous reflection-mode based methods, CUTE works also in a situation with only diffuse echoes, and its direct reconstruction algorithm enables real-time application. This makes it suitable as an addition to conventional clinical ultrasound where it has the potential to benefit diagnosis in a multimodal approach. In addition, knowledge of the spatial distribution of sound speed allows full aberration correction and thus improved spatial resolution and contrast of conventional B-mode ultrasound. © (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

Urinary diversion: how experts divert

OBJECTIVE To determine the rates of the available urinary diversion options for patients treated with radical cystectomy for bladder cancer in different settings (pioneering institutions, leading urologic oncology centers, and population based). METHODS Population-based data from the literature included all patients (n = 7608) treated in Sweden during the period 1964-2008, from Germany (n = 14,200) for the years 2008 and 2011, US patients (identified from National Inpatient Sample during 1998-2005, 35,370 patients and 2001-2008, 55,187 patients), and from Medicare (n = 22,600) for the years 1992, 1995, 1998, and 2001. After the International Consultation on Urologic Diseases-European Association of Urology International Consultation on Bladder Cancer 2012, the urinary diversion committee members disclosed data from their home institutions (n = 15,867), including the pioneering institutions and the leading urologic oncology centers. They are the coauthors of this report. RESULTS The receipt of continent urinary diversion in Sweden and the United States is <15%, whereas in the German high-volume setting, 30% of patients receive a neobladder. At leading urologic oncology centers, this rate is also 30%. At pioneering institutions up to 75% of patients receive an orthotopic reconstruction. Anal diversion is <1%. Continent cutaneous diversion is the second choice. CONCLUSION Enormous variations in urinary diversion exist for >2 decades. Increased attention in expanding the use of continent reconstruction may help to reduce these disparities for patients undergoing radical cystectomy for bladder cancer. Continent reconstruction should not be the exclusive domain of cystectomy centers. Efforts to increase rates of this complex reconstruction must concentrate on better definition of the quality-of-life impact, technique dissemination, and the centralization of radical cystectomy.

A review of fluorescent ligands for studying 5-HT3 receptors

The use of fluorescence is a valuable and increasingly accessible means of probing the pharmacology and physiology of cells and their receptors. To date, the use of fluorescence-based methods for 5-HT3 receptor research has been quite limited and, although a variety of approaches have been described, these are broadly distributed throughout the literature. In this review we condense these findings into a single, accessible source of reference with the hope of promoting the use of these valuable molecular probes.

Kuishi Pamoja: To live together

Comic book for farmers demonstrating community-based methods for alleviating human-elephant conflict.

Fine-grained Indoor Tracking by Fusing Inertial Sensor and Physical Layer Information in WLANs

Indoor positioning has become an emerging research area because of huge commercial demands for location-based services in indoor environments. Channel State Information (CSI) as a fine-grained physical layer information has been recently proposed to achieve high positioning accuracy by using range-based methods, e.g., trilateration. In this work, we propose to fuse the CSI-based ranges and velocity estimated from inertial sensors by an enhanced particle filter to achieve highly accurate tracking. The algorithm relies on some enhanced ranging methods and further mitigates the remaining ranging errors by a weighting technique. Additionally, we provide an efficient method to estimate the velocity based on inertial sensors. The algorithms are designed in a network-based system, which uses rather cheap commercial devices as anchor nodes. We evaluate our system in a complex environment along three different moving paths. Our proposed tracking method can achieve 1:3m for mean accuracy and 2:2m for 90% accuracy, which is more accurate and stable than pedestrian dead reckoning and range-based positioning.

Structural elucidation and antisense properties of a sugar-modified DNA analogue

Antisense oligonucleotides deserve great attention as potential drug candidates for the treatment of genetic disorders. For example, muscle dystrophy can be treated successfully in mice by antisense-induced exon skipping in the pre-mRNA coding for the structural protein dystrophin in muscle cells. For this purpose a sugar- and backbone-modified DNA analogue was designed, in which a tricyclic ring system substitutes the deoxyribose. These chemical modifications stabilize the dimers formed with the targeted RNA relative to native nucleic acid duplexes and increase the biostability of the antisense oligonucleotide. While evading enzymatic degradation constitutes an essential property of antisense oligonucleotides for therapeutic application, it renders the oligonucleotide inaccessible to biochemical sequencing techniques and requires the development of alternative methods based on mass spectrometry. The set of sequences studied includes tcDNA oligonucleotides ranging from 10 to 15 nucleotides in length as well as their hybrid duplexes with DNA and RNA complements. All samples were analyzed on a LTQ Orbitrap XL instrument equipped with a nano-electrospray source. For tandem mass spectrometric experiments collision-induced dissociation was performed, using helium as collision gas. Mass spectrometric sequencing of tcDNA oligomers manifests the applicability of the technique to substrates beyond the scope of enzyme-based methods. Sequencing requires the formation of characteristic backbone fragments, which take the form of a-B- and w-ions in the product ion spectra of tcDNA. These types of product ions are typically associated with unmodified DNA, which suggests a DNA-like fragmentation mechanism in tcDNA. The loss of nucleobases constitutes the second prevalent dissociation pathway observed in tcDNA. Comparison of partially and fully modified oligonucleotides indicates a pronounced impact of the sugar-moiety on the base loss. As this event initiates cleavage of the backbone, the presented results provide new mechanistic insights into the fragmentation of DNA in the gas-phase. The influence of the sugar-moiety on the dissociation extends to tcDNA:DNA and tcDNA:RNA hybrid duplexes, where base loss was found to be much more prominent from sugar-modified oligonucleotides than from their natural complements. Further prominent dissociation channels are strand separation and backbone cleavage of the single strands, as well as the ejection of backbone fragments from the intact duplex. The latter pathway depends noticeably on the base sequence. Moreover, it gives evidence of the high stability of the hybrid dimers, and thus directly reflects the affinity of tcDNA for its target in the cell. As the cellular target of tcDNA is a pre-mRNA, the structure was designed to discriminate RNA from DNA complements, which could be demonstrated by mass spectrometric experiments.