Understanding the Continual Reassessment Method for Dose Finding Studies: An Overview for Non-Statisticians

The Continual Reassessment Method (CRM) has gained popularity since its proposal by O’Quigley et al. [1]. Many variations have been published and discussed in the statistical literature, but there has been little attention to making the design considerations accessible to non-statisticians. As a result, some clinicians or reviewers of clinical trials tend to be wary of the CRM due to safety concerns. This paper presents the CRM in a non-technical way, describing the original CRM with some of its modified versions. It also describes the specifications that define a CRM design, along with two simulated examples of CRMs for illustration.

Statistical shape analysis via principal factor analysis

Statistical shape analysis techniques commonly employed in the medical imaging community, such as active shape models or active appearance models, rely on principal component analysis (PCA) to decompose shape variability into a reduced set of interpretable components. In this paper we propose principal factor analysis (PFA) as an alternative and complementary tool to PCA providing a decomposition into modes of variation that can be more easily interpretable, while still being a linear efficient technique that performs dimensionality reduction (as opposed to independent component analysis, ICA). The key difference between PFA and PCA is that PFA models covariance between variables, rather than the total variance in the data. The added value of PFA is illustrated on 2D landmark data of corpora callosa outlines. Then, a study of the 3D shape variability of the human left femur is performed. Finally, we report results on vector-valued 3D deformation fields resulting from non-rigid registration of ventricles in MRI of the brain.

From Statistical Data to Spatial Knowledge - informing decision making in Vietnam

Vietnam has developed rapidly over the past 15 years. However, progress was not uniformly distributed across the country. Availability, adequate visualization and analysis of spatially explicit data on socio-economic and environmental aspects can support both research and policy towards sustainable development. Applying appropriate mapping techniques allows gleaning important information from tabular socio-economic data. Spatial analysis of socio-economic phenomena can yield insights into locally-specifi c patterns and processes that cannot be generated by non-spatial applications. This paper presents techniques and applications that develop and analyze spatially highly disaggregated socioeconomic datasets. A number of examples show how such information can support informed decisionmaking and research in Vietnam.

Immediate and early non-occlusal loading of Straumann implants with a chemically modified surface (SLActive) in the posterior mandible and maxilla: interim results from a prospective multicenter randomized-controlled study

OBJECTIVE: Immediate and early loading of dental implants can simplify treatment and increase overall patient satisfaction. The purpose of this 3-year prospective randomized-controlled multicenter study was to assess the differences in survival rates and bone level changes between immediately and early-loaded implants with a new chemically modified surface (SLActive). This investigation shows interim results obtained after 5 months. MATERIAL AND METHODS: Patients > or =18 years of age missing at least one tooth in the posterior maxilla or mandible were enrolled in the study. Following implant placement, patients received a temporary restoration either on the day of surgery (immediate loading) or 28-34 days after surgery (early loading); restorations consisted of single crowns or two to four unit fixed dental prostheses. Permanent restorations were placed 20-23 weeks following surgery. The primary efficacy variable was change in bone level (assessed by standardized radiographs) from baseline to 5 months; secondary variables included implant survival and success rates. RESULTS: A total of 266 patients were enrolled (118 males and 148 females), and a total of 383 implants were placed (197 and 186 in the immediate and early loading groups, respectively). Mean patient age was 46.3+/-12.8 years. After 5 months, implant survival rates were 98% in the immediate group and 97% in the early group. Mean bone level change from baseline was 0.81+/-0.89 mm in the immediate group and 0.56+/-0.73 mm in the early group (P<0.05). Statistical analysis revealed a significant center effect (P<0.0001) and a significant treatment x center interaction (P=0.008). CONCLUSIONS: The results suggested that Straumann implants with an SLActive can be used predictably in time-critical (early or immediate) loading treatment protocols when appropriate patient selection criteria are observed. The mean bone level changes observed from baseline to 5 months (0.56 and 0.81 mm) corresponded to physiological observations from other studies, i.e., were not clinically significant. The presence of a significant center effect and treatment x center interaction indicated that the differences in bone level changes between the two groups were center dependent.

Utilizing Gaussian-Schell model beams to mitigate atmospheric turbulence in free space optical communications / by Kyle R. Drexler.

Turbulence affects traditional free space optical communication by causing speckle to appear in the received beam profile. This occurs due to changes in the refractive index of the atmosphere that are caused by fluctuations in temperature and pressure, resulting in an inhomogeneous medium. The Gaussian-Schell model of partial coherence has been suggested as a means of mitigating these atmospheric inhomogeneities on the transmission side. This dissertation analyzed the Gaussian-Schell model of partial coherence by verifying the Gaussian-Schell model in the far-field, investigated the number of independent phase control screens necessary to approach the ideal Gaussian-Schell model, and showed experimentally that the Gaussian-Schell model of partial coherence is achievable in the far-field using a liquid crystal spatial light modulator. A method for optimizing the statistical properties of the Gaussian-Schell model was developed to maximize the coherence of the field while ensuring that it does not exhibit the same statistics as a fully coherent source. Finally a technique to estimate the minimum spatial resolution necessary in a spatial light modulator was developed to effectively propagate the Gaussian-Schell model through a range of atmospheric turbulence strengths. This work showed that regardless of turbulence strength or receiver aperture, transmitting the Gaussian-Schell model of partial coherence instead of a fully coherent source will yield a reduction in the intensity fluctuations of the received field. By measuring the variance of the intensity fluctuations and the received mean, it is shown through the scintillation index that using the Gaussian-Schell model of partial coherence is a simple and straight forward method to mitigate atmospheric turbulence instead of traditional adaptive optics in free space optical communications.

Development of a continuum mechanics model of passive skeletal muscle

Skeletal muscle force evaluation is difficult to implement in a clinical setting. Muscle force is typically assessed through either manual muscle testing, isokinetic/isometric dynamometry, or electromyography (EMG). Manual muscle testing is a subjective evaluation of a patient’s ability to move voluntarily against gravity and to resist force applied by an examiner. Muscle testing using dynamometers adds accuracy by quantifying functional mechanical output of a limb. However, like manual muscle testing, dynamometry only provides estimates of the joint moment. EMG quantifies neuromuscular activation signals of individual muscles, and is used to infer muscle function. Despite the abundance of work performed to determine the degree to which EMG signals and muscle forces are related, the basic problem remains that EMG cannot provide a quantitative measurement of muscle force. Intramuscular pressure (IMP), the pressure applied by muscle fibers on interstitial fluid, has been considered as a correlate for muscle force. Numerous studies have shown that an approximately linear relationship exists between IMP and muscle force. A microsensor has recently been developed that is accurate, biocompatible, and appropriately sized for clinical use. While muscle force and pressure have been shown to be correlates, IMP has been shown to be non-uniform within the muscle. As it would not be practicable to experimentally evaluate how IMP is distributed, computational modeling may provide the means to fully evaluate IMP generation in muscles of various shapes and operating conditions. The work presented in this dissertation focuses on the development and validation of computational models of passive skeletal muscle and the evaluation of their performance for prediction of IMP. A transversly isotropic, hyperelastic, and nearly incompressible model will be evaluated along with a poroelastic model.

Quantification of relativistic perturbation forces on spacecraft trajectories

The intent of the work presented in this thesis is to show that relativistic perturbations should be considered in the same manner as well known perturbations currently taken into account in planet-satellite systems. It is also the aim of this research to show that relativistic perturbations are comparable to standard perturbations in speciffc force magnitude and effects. This work would have been regarded as little more then a curiosity to most engineers until recent advancements in space propulsion methods { e.g. the creation of a artiffcial neutron stars, light sails, and continuous propulsion techniques. These cutting-edge technologies have the potential to thrust the human race into interstellar, and hopefully intergalactic, travel in the not so distant future. The relativistic perturbations were simulated on two orbit cases: (1) a general orbit and (2) a Molniya type orbit. The simulations were completed using Matlab's ODE45 integration scheme. The methods used to organize, execute, and analyze these simulations are explained in detail. The results of the simulations are presented in graphical and statistical form. The simulation data reveals that the speciffc forces that arise from the relativistic perturbations do manifest as variations in the classical orbital elements. It is also apparent from the simulated data that the speciffc forces do exhibit similar magnitudes and effects that materialize from commonly considered perturbations that are used in trajectory design, optimization, and maintenance. Due to the similarities in behavior of relativistic versus non-relativistic perturbations, a case is made for the development of a fully relativistic formulation for the trajectory design and trajectory optimization problems. This new framework would afford the possibility of illuminating new more optimal solutions to the aforementioned problems that do not arise in current formulations. This type of reformulation has already showed promise when the previously unknown Space Superhighways arose as a optimal solution when classical astrodynamics was reformulated using geometric mechanics.

IDENTIFICATION OF GENES CONTROLLING BIOLOGICAL PROCESSES AND PATHWAYS THROUGH STATISTICAL ANALYSIS AND NETWORK RECONSTRUCTION

The developmental processes and functions of an organism are controlled by the genes and the proteins that are derived from these genes. The identification of key genes and the reconstruction of gene networks can provide a model to help us understand the regulatory mechanisms for the initiation and progression of biological processes or functional abnormalities (e.g. diseases) in living organisms. In this dissertation, I have developed statistical methods to identify the genes and transcription factors (TFs) involved in biological processes, constructed their regulatory networks, and also evaluated some existing association methods to find robust methods for coexpression analyses. Two kinds of data sets were used for this work: genotype data and gene expression microarray data. On the basis of these data sets, this dissertation has two major parts, together forming six chapters. The first part deals with developing association methods for rare variants using genotype data (chapter 4 and 5). The second part deals with developing and/or evaluating statistical methods to identify genes and TFs involved in biological processes, and construction of their regulatory networks using gene expression data (chapter 2, 3, and 6). For the first part, I have developed two methods to find the groupwise association of rare variants with given diseases or traits. The first method is based on kernel machine learning and can be applied to both quantitative as well as qualitative traits. Simulation results showed that the proposed method has improved power over the existing weighted sum method (WS) in most settings. The second method uses multiple phenotypes to select a few top significant genes. It then finds the association of each gene with each phenotype while controlling the population stratification by adjusting the data for ancestry using principal components. This method was applied to GAW 17 data and was able to find several disease risk genes. For the second part, I have worked on three problems. First problem involved evaluation of eight gene association methods. A very comprehensive comparison of these methods with further analysis clearly demonstrates the distinct and common performance of these eight gene association methods. For the second problem, an algorithm named the bottom-up graphical Gaussian model was developed to identify the TFs that regulate pathway genes and reconstruct their hierarchical regulatory networks. This algorithm has produced very significant results and it is the first report to produce such hierarchical networks for these pathways. The third problem dealt with developing another algorithm called the top-down graphical Gaussian model that identifies the network governed by a specific TF. The network produced by the algorithm is proven to be of very high accuracy.

On trend estimation under monotone Gaussian subordination with long-memory: application to fossil pollen series

Fossil pollen data from stratigraphic cores are irregularly spaced in time due to non-linear age-depth relations. Moreover, their marginal distributions may vary over time. We address these features in a nonparametric regression model with errors that are monotone transformations of a latent continuous-time Gaussian process Z(T). Although Z(T) is unobserved, due to monotonicity, under suitable regularity conditions, it can be recovered facilitating further computations such as estimation of the long-memory parameter and the Hermite coefficients. The estimation of Z(T) itself involves estimation of the marginal distribution function of the regression errors. These issues are considered in proposing a plug-in algorithm for optimal bandwidth selection and construction of confidence bands for the trend function. Some high-resolution time series of pollen records from Lago di Origlio in Switzerland, which go back ca. 20,000 years are used to illustrate the methods.

Statistical inference for the optimal approximating model

In the setting of high-dimensional linear models with Gaussian noise, we investigate the possibility of confidence statements connected to model selection. Although there exist numerous procedures for adaptive (point) estimation, the construction of adaptive confidence regions is severely limited (cf. Li in Ann Stat 17:1001–1008, 1989). The present paper sheds new light on this gap. We develop exact and adaptive confidence regions for the best approximating model in terms of risk. One of our constructions is based on a multiscale procedure and a particular coupling argument. Utilizing exponential inequalities for noncentral χ2-distributions, we show that the risk and quadratic loss of all models within our confidence region are uniformly bounded by the minimal risk times a factor close to one.

Bacillus Calmette-Guérin Failure in Patients with Non-Muscle-invasive Urothelial Carcinoma of the Bladder May Be Due to the Urologist's Failure to Detect Urothelial Carcinoma of the Upper Urinary Tract and Urethra

BACKGROUND: Various reasons exist for so-called bacillus Calmette-Guérin (BCG) failure in patients with non-muscle-invasive urothelial bladder carcinoma (NMIBC). OBJECTIVE: To explore whether urothelial carcinoma of the upper urinary tract (UUT) and/or prostatic urethra may be a cause for BCG failure. DESIGN, SETTING, AND PARTICIPANTS: Retrospective analysis of 110 patients with high-risk NMIBC repeatedly treated with intravesical BCG, diagnosed with disease recurrence, and followed for a median time of 9.1 yr. INTERVENTION: Two or more intravesical BCG induction courses without maintenance. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Primary outcome was pattern of disease recurrence (BCG failure) within the urinary tract categorised into UUT and/or urethral carcinoma (with or without intravesical recurrence), and intravesical recurrence alone. Secondary outcome was survival. Predictors of UUT and/or urethral carcinoma and the effect of pattern of disease recurrence on cancer-specific survival were assessed with multivariable Cox regression analysis adjusting for multiple clinical and tumour characteristics. RESULTS AND LIMITATIONS: Of the 110 patients, 57 (52%) had UUT and/or urethral carcinoma (with or without intravesical recurrence), and 53 (48%) had intravesical recurrence alone. In patients with UUT and/or urethral carcinoma, bladder carcinoma in situ (Tis) before the first and second BCG course was present in 42 of 57 (74%) and 47 of 57 (82%) patients, respectively. On multivariable analysis, bladder Tis before the first and/or second BCG course was the only independent predictor of UUT and/or urethral carcinoma. Of the 110 patients, 69 (63%) were alive at last follow-up visit, 18 (16%) had died due to metastatic urothelial carcinoma, and 23 (21%) had died of other causes. Pattern of disease recurrence within the urinary tract was not an independent predictor of cancer-specific survival. Main study limitations were retrospective design and limited power for survival analysis. CONCLUSIONS: In our patients with high-risk NMIBC failing after two or more courses of intravesical BCG, UUT and/or urethral carcinoma was detected in >50% of the cases during follow-up. The vast majority of these patients had bladder Tis before the first and/or second BCG course. In patients experiencing the so-called BCG failure, a diagnostic work-up of UUT and prostatic urethra should always be performed to exclude urothelial carcinoma before additional intravesical therapy or even a radical cystectomy is considered.