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Biomedical subjects

R T O'Neill

Publications and source records attributed to R T O'Neill.

At least 19 recordsLinked to original sources
PubMed1995

Efficacy evaluation for monotherapies in two-by-two factorial trials.

For factorial clinical trials in which two monotherapy treatments under study can interact only in the presence of treatment effects for each treatment, the always-pooled test statistic using data from all four groups has a correct size in detecting the simple effect of an individual treatment used alone. However, this test statistic may have an unbounded bias in estimation of the simple effect. The never-pooled test statistic that uses only data from the treatment group not receiving the other treatment has poor precision for estimating the simple effect. Two alternative test statistics under consideration are the two-stage statistic involving a preliminary test of treatment interaction and the maximum test statistic taking the larger of the always-pooled and the never-pooled statistics. The power, bias, and mean square error of all four tests are compared. When negative interactions exist, the two-stage and maximum statistics are generally superior to the always-pooled statistic and compare reasonably well with the never-pooled statistic; the maximum statistic seems slightly more favorable than the two-stage statistic. The two-stage statistic is the best choice when a treatment interaction can be large.

Analysis of Variance↗
PubMed1993

Some FDA perspectives on data monitoring in clinical trials in drug development.

The FDA's interest in data monitoring of clinical trials derives from its public health responsibility to assure the safety and efficacy of new drugs based on evidence from adequate and well-controlled studies. Therefore the FDA is concerned that clinical trials of new drugs are designed and carried out in a manner that will insure the integrity and validity of study inferences. The FDA regulation and guidelines recognize the role of data monitoring and the variety and diversity of situations utilizing a data monitoring process in clinical studies. This paper describes relevant aspects of the regulations and guidelines, some concerns the FDA has with regard to monitoring of both government- and industry-sponsored trials and the consequences of early termination of trials of new drugs in the investigational and marketed stages. Comments include advice on communication between the FDA and data monitoring committees.

Clinical Trials as Topic↗
PubMed1990

Competing risk analysis of life table data: application to lifetime risk computation.

In this pedagogic note we propose to assess the safety of treatment in a clinical trial, or the effect of risk exposure in a chronic animal study, in terms of two lifetime risks. These risks are computable from life table type data and take into account the effects of competing risks. We first describe their computational procedures in detail to demonstrate the need for their implementation in a computer program. We then illustrate their practical application through use of the data obtained from an actual clinical study.

Health Status Indicators↗
PubMed1988

On sample sizes to estimate the protective efficacy of a vaccine.

To estimate vaccine protective efficacy, defined as VE = 1 - ARV/ARU where ARV is the disease attack rate in the vaccinated group and ARU is the disease attack rate in the controls, investigators have used both cohort and case-control designs. For each design, we present a method for calculation of the sample size required to provide an approximate confidence interval for VE of predetermined width and probability of coverage. The required sample size is a function of the desired width of the confidence interval, the probability of coverage, the assumed VE, and, for cohort designs, the assumed disease attack rate in the controls, and for case-control designs, the assumed vaccine exposure prevalence for the controls.

Child, Preschool↗
PubMed1984

Sample sizes for estimation of the odds ratio in unmatched case-control studies.

A method is presented to obtain sample sizes for cases and controls that are required to provide approximate confidence intervals on the log odds ratio of predetermined width 2d and probability of coverage as a function of assumed exposure rates in the control group, assumed odds ratio psi, required d, and ratio C:1 of controls to cases.

Humans↗
PubMed1978

Case-control studies: a sequential approach.

A sequential approach to the design of a matched pair case-control study is proposed as an alternative to fixed sample plans when information on case-control pairs is acquired sequentially in time. The method described is that of Wald using the Sequential Probability Ratio Test (SPRT) for comparing two binomial populations. The test is an open, non-truncated procudure. Several tables are presented for the average sample numbers needed under the sequential plan and fixed sample plan for selected Type 1 and 2 errors, alternative relative risks of interest and exposure probabilities in case and controls. A hypothetical example is presented to illustrate the use of the method and discussion is given as to the possible advantages and disadvantages of the sequential approach to case-control studies.

Epidemiologic Methods↗
PubMed1978

A statistical procedure useful in evaluating time of onset and termination of response in clinical trials.

A statistical model jointly characterizing the onset and termination of treatment response of a subject over a fixed observed time period is presented. The model requires that the observations for each subject are made at a set of pre-selected time points during the observed time period. A useful index characterizing the probability of being in response is developed along with maximum likelihood estimates and variances. A likelihood ratio test is developed to simultaneously compare two treatment groups with respect to this index for all times. The proposed procedure is applied to a set of data from a clinical trial of two bronchodilator drugs from which our procedure is motivated.

Bronchodilator Agents↗