A comparison of subgroup identification methods in clinical drug development: Simulation study and regulatory considerations

With advancement of technologies such as genomic sequencing, predictive biomarkers have become a useful tool for the development of personalized medicine. Predictive biomarkers can be used to select subsets of patients, which are most likely to benefit from a treatment. A number of approaches for subgroup identification were proposed over the last years. Although overviews of subgroup identification methods are available, systematic comparisons of their performance in simulation studies are rare. Interaction trees (IT), model‐based recursive partitioning, subgroup identification based on differential effect, simultaneous threshold interaction modeling algorithm (STIMA), and adaptive refinement by directed peeling were proposed for subgroup identification. We compared these methods in a simulation study using a structured approach. In order to identify a target population for subsequent trials, a selection of the identified subgroups is needed. Therefore, we propose a subgroup criterion leading to a target subgroup consisting of the identified subgroups with an estimated treatment difference no less than a pre‐specified threshold. In our simulation study, we evaluated these methods by considering measures for binary classification, like sensitivity and specificity. In settings with large effects or huge sample sizes, most methods perform well. For more realistic settings in drug development involving data from a single trial only, however, none of the methods seems suitable for selecting a target population. Using the subgroup criterion as alternative to the proposed pruning procedures, STIMA and IT can improve their performance in some settings. The methods and the subgroup criterion are illustrated by an application in amyotrophic lateral sclerosis.     

Closing the Loophole: A Case Study of Organizing for More Equitable and Affordable Access to Health Care in San Francisco

This paper presents in-depth case study of a successful hybrid political and community organizing campaign to ensure equitable access to health care through the perspective of a grassroots San Francisco community-based organization, the Chinese Progressive Association (CPA), which has been organizing low-income Chinese immigrants for over four decades. First, it outlines the Health Care Security Ordinance (HCSO), which, since its passage in 2006, has established a near-universal health care access program, helping to make health care accessible and affordable to individuals living and working in San Francisco. Then it presents the campaign to save the HCSO, focusing on CPA’s participation in the HCSO coalition. Finally, it discusses health care as it relates to the San Francisco’s affordability crisis and the political economic context in which it is taking place. Despite the limitations inherent in small case studies like this one, it nevertheless provides a valuable opportunity to better understand how one politically progressive city attempted to address the problem of grossly inequitable health care access through the lens of community organizing, advocacy, and coalition building. San Francisco, like many major American cities today, is being confronted with rapid gentrification and growing economic inequality—the backdrop to the HCSO. Through innovative experiments in social responsibility like the HCSO, however, the city has made leaps in health care access. It concludes with lessons learned from local organizing and advocacy to save the HCSO as these may inform other local efforts to promote health care for all.     

The Message in Daily Exchange Rates: A Conditional-Variance Tale

Formal testing procedures confirm the presence of a unit root in the autoregressive polynomial of the univariate time series representation of daily exchange-rate data. The first differences of the logarithms of daily spot rates are approximately uncorrelated through time, and a generalized autoregressive conditional heteroscedasticity model with daily dummy variables and conditionally t-distributed errors is found to provide a good representation to the leptokurtosis and time-dependent conditional heteroscedasticity. The parameter estimates and characteristics of the models are found to be very similar for six different currencies. These apparent stylized facts carry over to weekly, fortnightly, and monthly data in which the degree of leptokurtosis and time-dependent heteroscedasticity is reduced as the length of the sampling interval increases.     

GAMMA-BASED CLUSTERING VIA ORDERED MEANS WITH APPLICATION TO GENE-EXPRESSION ANALYSIS

Discrete mixture models provide a well-known basis for effective clustering algorithms, although technical challenges have limited their scope. In the context of gene-expression data analysis, a model is presented that mixes over a finite catalog of structures, each one representing equality and inequality constraints among latent expected values. Computations depend on the probability that independent gamma-distributed variables attain each of their possible orderings. Each ordering event is equivalent to an event in independent negative-binomial random variables, and this finding guides a dynamic-programming calculation. The structuring of mixture-model components according to constraints among latent means leads to strict concavity of the mixture log likelihood. In addition to its beneficial numerical properties, the clustering method shows promising results in an empirical study.     

Modelling and simulation for one‐day cricket

This article is concerned with the simulation of one‐day cricket matches. Given that only a finite number of outcomes can occur on each ball that is bowled, a discrete generator on a finite set is developed where the outcome probabilities are estimated from historical data involving one‐day international cricket matches. The probabilities depend on the batsman, the bowler, the number of wickets lost, the number of balls bowled and the innings. The proposed simulator appears to do a reasonable job at producing realistic results. The simulator allows investigators to address complex questions involving one‐day cricket matches. The Canadian Journal of Statistics © 2009 Statistical Society of Canada     

The Contours and Correlates of Informal Work in Rural Pennsylvania*

Abstract Social scientists have increasingly come to recognize the informal economy as a prominent and permanent structural feature of modern society. Rural sociologists have made a considerable contribution to this literature, demonstrating informal work to factor prominently in the livelihood strategies of rural Americans. Despite this scholarly attention significant gaps persist in our understanding of the informal economy. Drawing on data from a survey of family households in nonmetropolitan Pennsylvania, this paper examines the contours and correlates of informal work. The results make a strong case that participation in informal work is widespread and most often combined with formal work as a household livelihood strategy. While income is not found to be a significant correlate of informal work, it is found to influence the reasons cited for participation. Important correlates of informal work are identified and differences in the factors associated with informal work done to generate income (cash or in‐kind) versus savings are revealed.     

Facing Up to Underfunding: Equity and Retrenchment in Community Care

Local social services departments in the UK are expected to distribute their cash-limited budgets for community care in ways that achieve an equitable allocation of resources in situations where, with present levels of funding, they cannot meet all the needs with which they are presented. This paper discusses a case study of the introduction of a "needs-based" formula to allocate a local authority's budget for home care services and a follow-up survey to investigate whether services reached the people intended to benefit. The article argues that the "gatekeeping" role of community care assessments is important to safeguard equity without the inflexibility of highly standardized tests of eligibility. However, with the new Labour government seeking to reduce dependency on public expenditure, and a growing lobby for national standards of social care, it will be increasingly important that local authorities justifiy their different practices with evidence about how they relate to local needs.