Targeted Maximum Likelihood Estimation for Dynamic Treatment Regimes in Sequential Randomized Controlled Trials

Sequential Randomized Controlled Trials (SRCTs) are rapidly becoming essential tools in the search for optimized treatment regimes in ongoing treatment settings. Analyzing data for multiple time-point treatments with a view toward optimal treatment regimes is of interest in many types of afflictions: HIV infection, Attention Deficit Hyperactivity Disorder in children, leukemia, prostate cancer, renal failure, and many others. Methods for analyzing data from SRCTs exist but they are either inefficient or suffer from the drawbacks of estimating equation methodology. We describe an estimation procedure, targeted maximum likelihood estimation (TMLE), which has been fully developed and implemented in point treatment settings, including time to event outcomes, binary outcomes and continuous outcomes. Here we develop and implement TMLE in the SRCT setting. As in the former settings, the TMLE procedure is targeted toward a pre-specified parameter of the distribution of the observed data, and thereby achieves important bias reduction in estimation of that parameter. As with the so-called Augmented Inverse Probability of Censoring Weight (A-IPCW) estimator, TMLE is double-robust and locally efficient. We report simulation results corresponding to two data-generating distributions from a longitudinal data structure

Orienting polyhedral parts by pushing

A common task in automated manufacturing processes is to orient parts prior to assembly. We consider sensorless orientation of an asymmetric polyhedral part by a sequence of push actions, and show that is it possible to move any such part from an unknown initial orientation into a known final orientation if these actions are performed by a jaw consisting of two orthogonal planes. We also show how to compute an orienting sequence of push actions.We propose a three-dimensional generalization of conveyor belts with fences consisting of a sequence of tilted plates with curved tips; each of the plates contains a sequence of fences. We show that it is possible to compute a set-up of plates and fences for any given asymmetric polyhedral part such that the part gets oriented on its descent along plates and fences

Percolation in suspensions of hard nanoparticles: From spheres to needles

We investigate geometric percolation and scaling relations in suspensions of nanorods, covering the entire range of aspect ratios from spheres to extremely slender needles. A new version of connectedness percolation theory is introduced and tested against specialised Monte Carlo simulations. The theory accurately predicts percolation thresholds for aspect ratios of rod length to width as low as 10. The percolation threshold for rod-like particles of aspect ratios below 1000 deviates significantly from the inverse aspect ratio scaling prediction, thought to be valid in the limit of infinitely slender rods and often used as a rule of thumb for nanofibres in composite materials. Hence, most fibres that are currently used as fillers in composite materials cannot be regarded as practically infinitely slender for the purposes of percolation theory. Comparing percolation thresholds of hard rods and new benchmark results for ideal rods, we find that i) for large aspect ratios, they differ by a factor that is inversely proportional to the connectivity distance between the hard cores, and ii) they approach the slender rod limit differently

Permutation-based Pathway Testing using the Super Learner Algorithm

Many diseases and other important phenotypic outcomes are the result of a combination of factors. For example, expression levels of genes have been used as input to various statistical methods for predicting phenotypic outcomes. One particular popular variety is the so-called gene set enrichment analysis (GSEA). This paper discusses an augmentation to an existing strategy to estimate the significance of an associations between a disease outcome and a predetermined combination of biological factors, based on a specific data adaptive regression method (the Super Learner, van der Laan et al., 2007). The procedure uses an aggressive search procedure, potentially resulting in final models that imply associations that would not be discovered using non data-adaptive procedures (e.g., multiple linear regression). A test statistic derived from the fit of the Super Learner model to the original data is compared to the permutation distribution of the same statistic, the latter being generated by permuting the outcome labels with respect to the covariate vectors. This comparison is the basis for rejection criteria for the null hypothesis of no association between a set of biological factors (e.g., gene expression levels) and binary phenotypic outcomes. We include simulations that compare the statistical power of the test derived from the Super Learner method with that of other methods for two different data generating distributions

Different strategies to improve the use of the umbilical cord and cord blood for hematopoietic and other regenerative cell therapies

The umbilical cord and cord blood contain stem cells that can be used for regenerative cell therapies such as hematopoietic stem cell transplantation. However, the application of cord blood is hindered by the slow engraftment of the cells and delayed immune reconstitution compared to stem cells of other sources such as bone marrow. This thesis focuses on ways to improve CB application from both the perspective of the patient (i.e. better engraftment) as well as from the cost perspective (i.e. wider applicability). To this aim, we investigated (combinations of) methods for the improvement of CB engraftment in a murine engraftment model for human hematopoietic cells. Besides our focus on the PB recovery of platelets and CD45+ cells, we furthermore looked at practical aspects of the application of CB such as the possibility of banking expanded cells, banking CB for other purposes than HST and the use of other extra-fetal (embryonic) tissues such as the umbilical cord.Sanquin Blood Supply FoundationUBL - phd migration 201

Code generation for large scale applications

Efficient execution of large-scale application codes is a primary requirement in many cases. High efficiency can only be achieved by utilizing architecture-independent efficient algorithms and exploiting specific architecture-dependent characteristics of a given computer architecture. However, platform specific versions of source code must be avoided to limit development and maintenance complexity. Usually, the problem can be formulated on an abstract level (mathematical equations, English). At that level, the problem is completely known, and there is no reference to the hardware on which the problem will be solved. Unfortunately, often the advantages of a high level of abstraction are overshadowed by a loss of performance compared to handwritten code. Therefore, a problem-specific code generator, called Ctadel, has been developed in order to exploit architecture-independent and dependent optimizations. We show how to extend Ctadel with more advanced numerical techniques and a interfaces to numerical libraries. A number of numerical models from Hirlam, a numerical weather prediction application in use by a number of meteorological institutes like the Dutch royal meteorological institute (KNMI) where specified using our specification language. We compared the performance of the generated program code with hand-written code. In most case, the code generated by Ctadel performs as well or even better than the hand-written code.NWOUBL - phd migration 201

Evaluating variation in use of definitive therapy and risk-adjusted prostate cancer mortality in England and the USA.

OBJECTIVES: Prostate cancer mortality (PCM) in the USA is among the lowest in the world, whereas PCM in England is among the highest in Europe. This paper aims to assess the association of variation in use of definitive therapy on risk-adjusted PCM in England as compared with the USA. DESIGN: Observational study. SETTING: Cancer registry data from England and the USA. PARTICIPANTS: Men diagnosed with non-metastatic prostate cancer (PCa) in England and the USA between 2004 and 2008. OUTCOME MEASURES: Competing-risks survival analyses to estimate subhazard ratios (SHR) of PCM adjusted for age, ethnicity, year of diagnosis, Gleason score (GS) and clinical tumour (cT) stage. RESULTS: 222,163 men were eligible for inclusion. Compared with American patients, English patients were more likely to present at an older age (70-79 years: England 44.2%, USA 29.3%, p<0.001), with higher tumour stage (cT3-T4: England 25.1%, USA 8.6%, p<0.001) and higher GS (GS 8-10: England 20.7%, USA 11.2%, p<0.001). They were also less likely to receive definitive therapy (England 38%, USA 77%, p<0.001). English patients were more likely to die of PCa (SHR=1.9, 95% CI 1.7 to 2.0, p<0.001). However, this difference was no longer statistically significant when also adjusted for use of definitive therapy (SHR=1.0, 95% CI 1.0 to 1.1, p=0.3). CONCLUSIONS: Risk-adjusted PCM is significantly higher in England compared with the USA. This difference may be explained by less frequent use of definitive therapy in England