Characterization of the definitive classical calpain family of vertebrates using phylogenetic, evolutionary and expression analyses

Peer reviewedPublisher PD

Analysis of uncertainty in health care cost-effectiveness studies: an introduction to statistical issues and methods

Cost-effectiveness analysis is now an integral part of health technology assessment and addresses the question of whether a new treatment or other health care program offers good value for money. In this paper we introduce the basic framework for decision making with cost-effectiveness data and then review recent developments in statistical methods for analysis of uncertainty when cost-effectiveness estimates are based on observed data from a clinical trial. Although much research has focused on methods for calculating confidence intervals for cost-effectiveness ratios using bootstrapping or Fieller’s method, these calculations can be problematic with a ratio-based statistic where numerator and=or denominator can be zero. We advocate plotting the joint density of cost and effect differences, together with cumulative density plots known as cost-effectiveness acceptability curves (CEACs) to summarize the overall value-for-money of interventions. We also outline the net-benefit formulation of the cost-effectiveness problem and show that it has particular advantages over the standard incremental cost-effectiveness ratio formulation

Stigma, epistemic injustice, and “looked after children”: the need for a new language

This article examines the processes that contribute to the stigmatization of a group of people typically identified as “children in care” or “looked after children.” In particular, we will look at the ways that we (adults, professionals, and carers) interact with these children, based on their status as both children and members of a socially marginalized and disadvantaged group, and how these modes of interaction can inhibit dialogue—a dialogue that is needed if we are to base our conceptions regarding the needs of these children on a more accurate understanding of their experiences and perspective. The problem is particularly challenging because the very terminology we use in the care community to identify this group is a product of the damaging preconceptions that have affected our interactions with its members and, we argue, it serves to reinforce those preconceptions. Using Fricker's work on epistemic injustice, in conjunction with evidence regarding how accusations of abuse and neglect of these children have been addressed in numerous cases, we illustrate the problems we have in hearing the voices of members of this group and the harmful effects this has on their own ability to understand and articulate their experiences. These problems represent “barriers to disclosure” that need to be surmounted if we are to establish a more inclusive dialogue. Currently, dialogue between these children and those of us charged to “look after” them is too often characterized by a lack of trust: not only in terms of the children feeling that their word is not taken seriously, that their claims are not likely to be believed, but also in their feeling that they cannot trust those to whom they might disclose abuse or neglect. The goals of the paper are modest in that we aim simply to open up the debate on how to meet this epistemic challenge, noting that there are specific problems that extend beyond those already identified for hearing the voices of other victims of epistemic injustice. Explicitly recognizing the nature and extent of the problem still leaves us a long way from its solution, but it is a crucial start

Confidence interval estimation for the changepoint of treatment stratification in the presence of a qualitative covariate-treatment interaction

The goal in stratified medicine is to administer the \textquotedblbest\textquotedbl treatment to a patient. Not all patients might benefit from the same treatment; the choice of best treatment can depend on certain patient characteristics. In this article, it is assumed that a time-to-event outcome is considered as a patient-relevant outcome and a qualitative interaction between a continuous covariate and treatment exists, ie,~that patients with different values of one specific covariate should be treated differently. We suggest and investigate different methods for confidence interval estimation for the covariate value, where the treatment recommendation should be changed based on data collected in a randomized clinical trial. An adaptation of Fieller's theorem, the delta method, and different bootstrap approaches (normal, percentile-based, wild bootstrap) are investigated and compared in a simulation study. Extensions to multivariable problems are presented and evaluated. We observed appropriate confidence interval coverage following Fieller's theorem irrespective of sample size but at the cost of very wide or even infinite confidence intervals. The delta method and the wild bootstrap approach provided the smallest intervals but inadequate coverage for small to moderate event numbers, also depending on the location of the true changepoint. For the percentile-based bootstrap, wide intervals were observed, and it was slightly conservative regarding coverage, whereas the normal bootstrap did not provide acceptable results for many scenarios. The described methods were also applied to data from a randomized clinical trial comparing two treatments for patients with symptomatic, severe carotid artery stenosis, considering patient's age as predictive marker

Simultaneous confidence sets for several effective doses.

Construction of simultaneous confidence sets for several effective doses currently relies on inverting the Scheffé type simultaneous confidence band, which is known to be conservative. We develop novel methodology to make the simultaneous coverage closer to its nominal level, for both two-sided and one-sided simultaneous confidence sets. Our approach is shown to be considerably less conservative than the current method, and is illustrated with an example on modeling the effect of smoking status and serum triglyceride level on the probability of the recurrence of a myocardial infarction

Mathematical Analysis of Copy Number Variation in a DNA Sample Using Digital PCR on a Nanofluidic Device

Copy Number Variations (CNVs) of regions of the human genome have been associated with multiple diseases. We present an algorithm which is mathematically sound and computationally efficient to accurately analyze CNV in a DNA sample utilizing a nanofluidic device, known as the digital array. This numerical algorithm is utilized to compute copy number variation and the associated statistical confidence interval and is based on results from probability theory and statistics. We also provide formulas which can be used as close approximations

Methods for confidence interval estimation of a ratio parameter with application to location quotients

BACKGROUND: The location quotient (LQ) ratio, a measure designed to quantify and benchmark the degree of relative concentration of an activity in the analysis of area localization, has received considerable attention in the geographic and economics literature. This index can also naturally be applied in the context of population health to quantify and compare health outcomes across spatial domains. However, one commonly observed limitation of LQ is its widespread use as only a point estimate without an accompanying confidence interval. METHODS: In this paper we present statistical methods that can be used to construct confidence intervals for location quotients. The delta and Fieller's methods are generic approaches for a ratio parameter and the generalized linear modelling framework is a useful re-parameterization particularly helpful for generating profile-likelihood based confidence intervals for the location quotient. A simulation experiment is carried out to assess the performance of each of the analytic approaches and a health utilization data set is used for illustration. RESULTS: Both the simulation results as well as the findings from the empirical data show that the different analytical methods produce very similar confidence limits for location quotients. When incidence of outcome is not rare and sample sizes are large, the confidence limits are almost indistinguishable. The confidence limits from the generalized linear model approach might be preferable in small sample situations. CONCLUSION: LQ is a useful measure which allows quantification and comparison of health and other outcomes across defined geographical regions. It is a very simple index to compute and has a straightforward interpretation. Reporting this estimate with appropriate confidence limits using methods presented in this paper will make the measure particularly attractive for policy and decision makers