Faculty Bibliography

For resource allocation under a constrained budget, optimal decision rules for mutually exclusive programs require that the treatment with the highest incremental cost-effectiveness ratio (ICER) below a willingness-to-pay (WTP) criterion be funded. This is equivalent to determining the treatment with the smallest net health cost. The designer of a cost-effectiveness study needs to select a sample size so that the power to reject the null hypothesis, the equality of the net health costs of two treatments, is high. A recently published formula derived under normal distribution theory overstates sample-size requirements. Using net health costs, the authors present simple methods for power analysis based on conventional normal and on nonparametric statistical theory

Both incremental cost-effectiveness ratios and net benefits have been proposed as summary measures for use in cost-effectiveness analyses. We present a unifying proof of the optimality and equivalence of ICER- and net benefit-based approaches to the health resource allocation problem, including both 'fixed budget' and 'fixed price' decision rules. If internally consistent willingness-to-pay values are used, ratio- and net benefit-based decision rules identify the same optimal allocation. Because they have identical resource allocation implications, use of one or other of the two approaches must be based on other criteria, such as their behaviour under conditions of uncertainty

We demonstrate that average cost-effectiveness ratios (CERs) play an important role in the evaluation of the cost-effectiveness of treatments. Criticisms of the usefulness of CERs derive mostly from the context of resource allocation under a constrained budget in which some decisions are based on incremental CERs. However, we show that in many cases, these decision rules are equivalent to decision rules on CERs. This follows for mutually exclusive treatments first, because a treatment is eliminated by extended dominance if and only if there is a mixed treatment with a smaller CER, where the mixing parameter lies in a certain interval. Second, after elimination of treatments by dominance and by extended dominance, resources can be allocated in order of increasing CERs. Moreover, the CER is a parameter that characterizes clinical and economical properties of a treatment independent of its comparators

Methods for statistical inference for cost-effectiveness (C/E) ratios for individual treatment and for incremental cost-effectiveness (delta C/ delta E) ratios when two treatments are compared are presented. In a lemma, we relate the relative magnitude of two C/E ratios to the delta C/ delta E ratio. We describe a statistical procedure to test for dominance, or admissibility, that can be used to eliminate an inferior treatment. The one-sided Bonferroni's confidence interval procedure is generalized to the two-sided case. The method requires only that two confidence intervals be available, one for cost and one for effectiveness. We describe Fieller-based confidence intervals and show them to be shorter than Bonferroni intervals. When distribution assumptions hold and variance and covariance estimates are available, Fieller intervals are preferable. However, Bonferroni intervals can be applied in more diverse situations and are easier to calculate. A simple Bonferroni based technique, and a likelihood ratio statistic given by Siegel, Laska and Meisner, for testing the null hypothesis that the C/E ratios of two treatments are equal is presented. The approaches are applied to the data from a phase II clinical trial of a new treatment for sepsis considered previously by others

OBJECTIVE: This paper compares the prevalence of mental illnesses and alcohol and drug abuse and the residential histories of homeless individuals identified as having a mental illness and individuals who are not so identified. The cohort consisted of single persons applying for shelter over a 12-week period in Westchester County, a suburban county in New York State. METHODS: The sample of 201 persons (89 percent male, with a mean age of 37) represented 77 percent of consecutive single shelter applicants in a single-point-of-entry system over the study period. Information from an intake assessment was augmented by a semistructured interview to reconstruct subjects' residential history for the last five years, including periods of homelessness and time in institutions. RESULTS: Twenty-one percent of the cohort was classified as having mental illness. Seventy-two percent had a diagnosis of drug abuse or dependence, and 51 percent had alcohol abuse or dependence. For individuals with a mental illness, the use of cocaine and heroin was significantly lower, but alcohol use was somewhat greater, compared with other homeless persons. Persons with mental illness also experienced homelessness of some kind over a significantly longer period (a mean of seven years versus a mean of three years for other subjects), and they spent almost twice as many weeks during the previous five years literally homeless. Institutional time, most of which consisted of time in jail or prison, was equivalent for both groups. CONCLUSIONS: Not only is residential instability heightened among shelter users with mental illness, but over time public institutions play a critical role in their accommodations. For some homeless persons with mental illness, the circuit of shelters, rehabilitation programs, jails, and prisons may function as a makeshift alternative to inpatient care or supportive housing and may reinforce the marginalization of this population

BACKGROUND: Data on the two-year pattern of course of illness have been collected in the WHO study of the Determinants of Outcomes of Severe Mental Disorder (DOSMD). These data are reanalysed using recursive partitioning, a method not yet applied to psychiatric data to test the hypothesis that subjects from participating centres in developing countries had better outcomes than those in developed countries. METHOD: Subjects were those from the DOSMD study for whom two-year follow-up data were available (n = 1056). The classification and regression trees recursive partitioning technique was used to examine the predictor variables associated with the outcome variable two year pattern of course. RESULTS: Pattern of course was best predicted by centre, but two developed centres (Prague and Nottingham) grouped with the developing country centres excluding Cali, having better outcomes than in the remaining developed country centres and Cali. Type of onset (insidious v. non-insidious) was the next strongest predictor, but its effect differed across these two centre groupings. Effects for some groups were modified by other predictor variables, including age, child and/or adolescent problems, and gender. CONCLUSIONS: The predominant predictor effects on two-year pattern of course continued to be centre and type of onset, but complex interactions between these variables and other predictor variables are seen in specific centre groupings not strictly defined by 'developing' and 'developed'.

A statistical framework is presented for examining cost and effect data on competing interventions obtained from an RCT or from an observational study. Parameters of the join distribution of costs and effects or a regression function linking costs and effects are used to define cost-effectiveness (c-e) measures. Several new c-e measures are proposed that utilize the linkage between costs and effects on the patient level. These measures reflect perspectives that are different from those of the commonly used measures, such as the ratio of expected cost to expected effect, and they can lead to different relative rankings of the interventions. The cost-effectiveness of interventions are assessed statistically in a two stage procedure that first eliminates clearly inferior interventions. Members of the remaining admissible set are then rank ordered according to a c-e preference measure. Statistical techniques, particularly in the multivariate normal case, are given for several commonly used c-e measures. These techniques provide methods for obtaining confidence intervals, for testing the hypothesis of admissibility and for the equality of interventions, and for ranking interventions. The ideas are illustrated for a hypothetical clinical trial of antipsychotic agents for community-based persons with mental illness

An unexpected finding of the International Pilot Study of Schizophrenia, launched by the World Health Organization (WHO) in 1967, was that patients in countries outside Europe and the United States have a more favourable short- and medium-term course of the disease than those seen in developed countries. Since then, WHO has intensified its schizophrenia research programme and has initiated a set of international studies that have confirmed these initial findings and explored possible reasons for such differences in the course and outcome of schizophrenia. While such work has provided important findings and has generated additional pertinent hypotheses, it did not explain the differences in outcome. The present paper describes a new initiative in which approximately 2500 subjects involved in previous WHO multicentre schizophrenia studies are being followed up for between 15 and 25 years after initial examination. Nineteen research centres in 16 countries are taking part in this work. The research methodology is described

In addition to describing treatment efficacy in terms of changes in rating scale scores, the distributions of time to occurrence of major clinical events such as onset and response are clinically important information. Issues in the design, conduct and analysis of clinical trials in which the time to onset of effect or time to response is to be characterized are discussed. A criterion must be defined to signal that the clinical event has occurred. Onset properties are given in terms of (1) the probability of obtaining onset and (2) for patients who obtain onset, the distribution of time to onset. A statistical model and methods to estimate parameters and compare onset times of treatments are described. A simple formula that can be used to aid in clinical decision making as to when to alter treatment if onset has not yet occurred is presented

Current statistical designs for studying whether two or more agents in combination act synergistically nearly always require the study of several doses of many dose ratios. The analysis is usually based on an assumed parametric model of the dose-response surface. In this paper, for both quantal and quantitative response variables, sufficient conditions are given for establishing synergy at a dose of the combination without the need to specify the model. This enables the use of simple designs with few doses even when there is sparse knowledge of the dose-response curves of the individual agents. The Min test, used for testing whether an identified treatment is best, may be used for testing synergy. Power issues are discussed