Survival Analysis with Large Dimensional Covariates: An Application in Microarray Studies

Use of microarray technology often leads to high-dimensional and low- sample size data settings. Over the past several years, a variety of novel approaches have been proposed for variable selection in this context. However, only a small number of these have been adapted for time-to-event data where censoring is present. Among standard variable selection methods shown both to have good predictive accuracy and to be computationally efficient is the elastic net penalization approach. In this paper, adaptation of the elastic net approach is presented for variable selection both under the Cox proportional hazards model and under an accelerated failure time (AFT) model. Assessment of the two methods is conducted through simulation studies and through analysis of microarray data obtained from a set of patients with diffuse large B-cell lymphoma where time to survival is of interest. The approaches are shown to match or exceed the predictive performance of a Cox-based and an AFT-based variable selection method. The methods are moreover shown to be much more computationally efficient than their respective Cox- and AFT- based counterparts.

On the Accelerated Failure Time Model for Current Status and Interval Censored Data

This paper introduces a novel approach to making inference about the regression parameters in the accelerated failure time (AFT) model for current status and interval censored data. The estimator is constructed by inverting a Wald type test for testing a null proportional hazards model. A numerically efficient Markov chain Monte Carlo (MCMC) based resampling method is proposed to simultaneously obtain the point estimator and a consistent estimator of its variance-covariance matrix. We illustrate our approach with interval censored data sets from two clinical studies. Extensive numerical studies are conducted to evaluate the finite sample performance of the new estimators.

Designed Extension of Survival Studies: Application to Clinical Trials with Unrecognized Heterogeneity

It is well known that unrecognized heterogeneity among patients, such as is conferred by genetic subtype, can undermine the power of randomized trial, designed under the assumption of homogeneity, to detect a truly beneficial treatment. We consider the conditional power approach to allow for recovery of power under unexplained heterogeneity. While Proschan and Hunsberger (1995) confined the application of conditional power design to normally distributed observations, we consider more general and difficult settings in which the data are in the framework of continuous time and are subject to censoring. In particular, we derive a procedure appropriate for the analysis of the weighted log rank test under the assumption of a proportional hazards frailty model. The proposed method is illustrated through application to a brain tumor trial.

Analyzing Panel Count Data with Informative Observation Times

In this paper, we study panel count data with informative observation times. We assume nonparametric and semiparametric proportional rate models for the underlying recurrent event process, where the form of the baseline rate function is left unspecified and a subject-specific frailty variable inflates or deflates the rate function multiplicatively. The proposed models allow the recurrent event processes and observation times to be correlated through their connections with the unobserved frailty; moreover, the distributions of both the frailty variable and observation times are considered as nuisance parameters. The baseline rate function and the regression parameters are estimated by maximizing a conditional likelihood function of observed event counts and solving estimation equations. Large sample properties of the proposed estimators are studied. Numerical studies demonstrate that the proposed estimation procedures perform well for moderate sample sizes. An application to a bladder tumor study is presented to illustrate the use of the proposed methods.

Modeling multilevel sleep transitional data via Poisson log-linear multilevel models

This paper proposes Poisson log-linear multilevel models to investigate population variability in sleep state transition rates. We specifically propose a Bayesian Poisson regression model that is more flexible, scalable to larger studies, and easily fit than other attempts in the literature. We further use hierarchical random effects to account for pairings of individuals and repeated measures within those individuals, as comparing diseased to non-diseased subjects while minimizing bias is of epidemiologic importance. We estimate essentially non-parametric piecewise constant hazards and smooth them, and allow for time varying covariates and segment of the night comparisons. The Bayesian Poisson regression is justified through a re-derivation of a classical algebraic likelihood equivalence of Poisson regression with a log(time) offset and survival regression assuming piecewise constant hazards. This relationship allows us to synthesize two methods currently used to analyze sleep transition phenomena: stratified multi-state proportional hazards models and log-linear models with GEE for transition counts. An example data set from the Sleep Heart Health Study is analyzed.

Kernel Estimation of Rate Function for Recurrent Event Data

Recurrent event data are largely characterized by the rate function but smoothing techniques for estimating the rate function have never been rigorously developed or studied in statistical literature. This paper considers the moment and least squares methods for estimating the rate function from recurrent event data. With an independent censoring assumption on the recurrent event process, we study statistical properties of the proposed estimators and propose bootstrap procedures for the bandwidth selection and for the approximation of confidence intervals in the estimation of the occurrence rate function. It is identified that the moment method without resmoothing via a smaller bandwidth will produce curve with nicks occurring at the censoring times, whereas there is no such problem with the least squares method. Furthermore, the asymptotic variance of the least squares estimator is shown to be smaller under regularity conditions. However, in the implementation of the bootstrap procedures, the moment method is computationally more efficient than the least squares method because the former approach uses condensed bootstrap data. The performance of the proposed procedures is studied through Monte Carlo simulations and an epidemiological example on intravenous drug users.

Activation of the orphan endothelial receptor Tie1 modifies Tie2-mediated intracellular signaling and cell survival

A critical role for Tie1, an orphan endothelial receptor, in blood vessel morphogenesis has emerged from mutant mouse studies. Moreover, it was recently demonstrated that certain angiopoietin (Ang) family members can activate Tie1. We report here that Ang1 induces Tie1 phosphorylation in endothelial cells. Tie1 phosphorylation was, however, Tie2 dependent because 1) Ang1 failed to induce Tie1 phosphorylation when Tie2 was down-regulated in endothelial cells; 2) Tie1 phosphorylation was induced in the absence of Ang1 by either a constitutively active form of Tie2 or a Tie2 agonistic antibody; 3) in HEK 293 cells Ang1 phosphorylated a form of Tie1 without kinase activity when coexpressed with Tie2, and Ang1 failed to phosphorylate Tie1 when coexpressed with kinase-defective Tie2. Ang1-mediated AKT and 42/44MAPK phosphorylation is predominantly Tie2 mediated, and Tie1 down-regulates this pathway. Finally, based on a battery of in vitro and in vivo data, we show that a main role for Tie1 is to modulate blood vessel morphogenesis by virtue of its ability to down-regulate Tie2-driven signaling and endothelial survival. Our new observations help to explain why Tie1 null embryos have increased capillary densities in several organ systems. The experiments also constitute a paradigm for how endothelial integrity is fine-tuned by the interplay between closely related receptors by a single growth factor.

Endothelial survival factors and spatial completion, but not pericyte coverage of retinal capillaries determine vessel plasticity

Pericyte loss and capillary regression are characteristic for incipient diabetic retinopathy. Pericyte recruitment is involved in vessel maturation, and ligand-receptor systems contributing to pericyte recruitment are survival factors for endothelial cells in pericyte-free in vitro systems. We studied pericyte recruitment in relation to the susceptibility toward hyperoxia-induced vascular remodeling using the pericyte reporter X-LacZ mouse and the mouse model of retinopathy of prematurity (ROP). Pericytes were found in close proximity to vessels, both during formation of the superficial and the deep capillary layers. When exposure of mice to the ROP was delayed by 24 h, i.e., after the deep retinal layer had formed [at postnatal (p) day 8], preretinal neovascularizations were substantially diminished at p18. Mice with a delayed ROP exposure had 50% reduced avascular zones. Formation of the deep capillary layers at p8 was associated with a combined up-regulation of angiopoietin-1 and PDGF-B, while VEGF was almost unchanged during the transition from a susceptible to a resistant capillary network. Inhibition of Tie-2 function either by soluble Tie-2 or by a sulindac analog, an inhibitor of Tie-2 phosphorylation, resensitized retinal vessels to neovascularizations due to a reduction of the deep capillary network. Inhibition of Tie-2 function had no effect on pericyte recruitment. Our data indicate that the final maturation of the retinal vasculature and its resistance to regressive signals such as hyperoxia depend on the completion of the multilayer structure, in particular the deep capillary layers, and are independent of the coverage by pericytes.

A systematic review of the survival and complication rates of resin-bonded bridges after an observation period of at least 5 years

OBJECTIVES: The objectives of this systematic review were to assess the 5-year survival of resin-bonded bridges (RBBs) and to describe the incidence of technical and biological complications. METHODS: An electronic Medline search complemented by manual searching was conducted to identify prospective and retrospective cohort studies on RBBs with a mean follow-up time of at least 5 years. Patients had to have been examined clinically at the follow-up visit. Assessment of the identified studies and data extraction were performed independently by two reviewers. Failure and complication rates were analyzed using random-effects Poissons regression models to obtain summary estimates of 5-year proportions. RESULTS: The search provided 6110 titles and 214 abstracts. Full-text analysis was performed for 93 articles, resulting in 17 studies that met the inclusion criteria. Meta-analysis of these studies indicated an estimated survival of RBBs of 87.7% (95% confidence interval (CI): 81.6-91.9%) after 5 years. The most frequent complication was debonding (loss of retention), which occurred in 19.2% (95% CI: 13.8-26.3%) of RBBs over an observation period of 5 years. The annual debonding rate for RBBs placed on posterior teeth (5.03%) tended to be higher than that for anterior-placed RBBs (3.05%). This difference, however, did not reach statistical significance (P=0.157). Biological complications, like caries on abutments and RBBs lost due to periodontitis, occurred in 1.5% of abutments and 2.1% of RBBs, respectively. CONCLUSION: Despite the high survival rate of RBBs, technical complications like debonding are frequent. This in turn means that a substantial amount of extra chair time may be needed following the incorporation of RBBs. There is thus an urgent need for studies with a follow-up time of 10 years or more, to evaluate the long-term outcomes.

A systematic review of the 5-year survival and complication rates of implant-supported single crowns

OBJECTIVES: The objective of this systematic review was to assess the 5-year survival of implant-supported single crowns (SCs) and to describe the incidence of biological and technical complications. METHODS: An electronic MEDLINE search complemented by manual searching was conducted to identify prospective and retrospective cohort studies on SCs with a mean follow-up time of at least 5 years. Failure and complication rates were analyzed using random-effects Poisson's regression models to obtain summary estimates of 5-year proportions. RESULTS: Twenty-six studies from an initial yield of 3601 titles were finally selected and data were extracted. In a meta-analysis of these studies, survival of implants supporting SCs was 96.8% [95% confidence interval (CI): 95.9-97.6%] after 5 years. The survival rate of SCs supported by implants was 94.5% (95% CI: 92.5-95.9%) after 5 years of function. The survival rate of metal-ceramic crowns, 95.4% (95% CI: 93.6-96.7%), was significantly (P=0.005) higher than the survival rate, 91.2% (95% CI: 86.8-94.2%), of all-ceramic crowns. Peri-implantitis and soft tissue complications occurred adjacent to 9.7% of the SCs and 6.3% of the implants had bone loss exceeding 2 mm over the 5-year observation period. The cumulative incidence of implant fractures after 5 years was 0.14%. After 5 years, the cumulative incidence of screw or abutment loosening was 12.7% and 0.35% for screw or abutment fracture. For supra-structure-related complications, the cumulative incidence of ceramic or veneer fractures was 4.5%. CONCLUSION: It can be concluded that after an observation period of 5 years, high survival rates for implants and implant-supported SCs can be expected. However, biological and particularly technical complications are frequent.

Virtopsy: fatal stab wounds to the skull--the relevance of ante-mortem and post-mortem radiological data in case reconstructions

Homicides with a survival of several days are not uncommon in forensic routine work. Reconstructions of these cases by autopsy alone are very difficult and may occasionally lead to unsatisfying results. For the medico-legal reconstruction of these cases, ante-mortem and post-mortem radiological imaging should always be included in the expertise. We report on a case of fatal penetrating stab wounds to the skull in which a case reconstruction was only possible by combining the radiological ante- and post-mortem data with the autopsy findings.