Noise-Induced Randomization in Regression Discontinuity Designs

Regression discontinuity designs are used to estimate causal effects in settings where treatment is determined by whether an observed running variable crosses a pre-specified threshold. While the resulting sampling design is sometimes described as akin to a locally randomized experiment in a neighborhood of the threshold, standard formal analyses do not make reference to probabilistic treatment assignment and instead identify treatment effects via continuity arguments. Here we propose a new approach to identification, estimation, and inference in regression discontinuity designs that exploits measurement error in the running variable. Under an assumption that the measurement error is exogenous, we show how to consistently estimate causal effects using a class of linear estimators that weight treated and control units so as to balance a latent variable of which the running variable is a noisy measure. We find this approach to facilitate identification of both familiar estimands from the literature, as well as policy-relevant estimands that correspond to the effects of realistic changes to the existing treatment assignment rule. We demonstrate the method with a study of retention of HIV patients and evaluate its performance using simulated data and a regression discontinuity design artificially constructed from test scores in early childhood

Mapping lung cancer epithelial-mesenchymal transition states and trajectories with single-cell resolution.

Elucidating the spectrum of epithelial-mesenchymal transition (EMT) and mesenchymal-epithelial transition (MET) states in clinical samples promises insights on cancer progression and drug resistance. Using mass cytometry time-course analysis, we resolve lung cancer EMT states through TGFβ-treatment and identify, through TGFβ-withdrawal, a distinct MET state. We demonstrate significant differences between EMT and MET trajectories using a computational tool (TRACER) for reconstructing trajectories between cell states. In addition, we construct a lung cancer reference map of EMT and MET states referred to as the EMT-MET PHENOtypic STAte MaP (PHENOSTAMP). Using a neural net algorithm, we project clinical samples onto the EMT-MET PHENOSTAMP to characterize their phenotypic profile with single-cell resolution in terms of our in vitro EMT-MET analysis. In summary, we provide a framework to phenotypically characterize clinical samples in the context of in vitro EMT-MET findings which could help assess clinical relevance of EMT in cancer in future studies

HiCT: High Throughput Protocols For CPE Cloning And Transformation

The purpose of this RFC is to provide instructions for a rapid and cost efficient cloning and transformation method which allows for the manufacturing of multi-fragment plasmid constructs in a parallelized manner: High Throughput Circular Extension Cloning and Transformation (HiCT). Description of construct libraries generated by the HiCT method can be found at http://2013.igem.org/Team:Heidelberg/Indigoidine. This RFC also points out further optimization strategies with regard to construct stability, reduction of transformation background and the generation of competent cells

Using public clinical trial reports to probe non-experimental causal inference methods

Abstract Background Non-experimental studies (also known as observational studies) are valuable for estimating the effects of various medical interventions, but are notoriously difficult to evaluate because the methods used in non-experimental studies require untestable assumptions. This lack of intrinsic verifiability makes it difficult both to compare different non-experimental study methods and to trust the results of any particular non-experimental study. Methods We introduce TrialProbe, a data resource and statistical framework for the evaluation of non-experimental methods. We first collect a dataset of pseudo “ground truths” about the relative effects of drugs by using empirical Bayesian techniques to analyze adverse events recorded in public clinical trial reports. We then develop a framework for evaluating non-experimental methods against that ground truth by measuring concordance between the non-experimental effect estimates and the estimates derived from clinical trials. As a demonstration of our approach, we also perform an example methods evaluation between propensity score matching, inverse propensity score weighting, and an unadjusted approach on a large national insurance claims dataset. Results From the 33,701 clinical trial records in our version of the ClinicalTrials.gov dataset, we are able to extract 12,967 unique drug/drug adverse event comparisons to form a ground truth set. During our corresponding methods evaluation, we are able to use that reference set to demonstrate that both propensity score matching and inverse propensity score weighting can produce estimates that have high concordance with clinical trial results and substantially outperform an unadjusted baseline. Conclusions We find that TrialProbe is an effective approach for probing non-experimental study methods, being able to generate large ground truth sets that are able to distinguish how well non-experimental methods perform in real world observational data

Severe upper limb injuries with or without neurovascular compromise in children and adolescents - Analysis of 32 cases

The healing and regeneration capacity of the injured tissues in childhood, adolescence, and adult life differs significantly. As a result, the prognosis of compound injuries of the upper limb in different age groups varies; therefore, the decision making and management of these cases should be age-specific. This article presents a series of 32 patients aged 1.5-14 years, with compound injuries of the upper limb that have been treated in our hospital during the period of the last 6 years. Ten of the above cases involved major vascular lesions that required revascularization or replantation. The injuries were classified according to the SATT (Severity, Anatomy, Topography, Type) classification system. This study shows that the outcome of compound upper limb injuries is age-related, while the SATT classification system is a valuable tool in the decision making process. Further research should be undertaken to determine age group-specific indications for the management of compound upper limb injuries, based on the SATT classification system. (C) 2008 Wiley-Liss, Inc

Front-line treatment of advanced non-small cell lung cancer with irinotecan and docetaxel: a multicentre phase II study.

To evaluate the efficacy and tolerance of the irinotecan plus docetaxel combination in patients with advanced non-small cell lung cancer (NSCLC).info:eu-repo/semantics/publishe