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Sally Hunsberger

Publications and source records attributed to Sally Hunsberger.

5 recordsLinked to original sources
PubMed2003

Practical midcourse sample size modification in clinical trials.

Power calculations are very important in the planning of a well-designed clinical trial. Sometimes there is limited information available before the trial, making it highly desirable to adjust the sample size after seeing actual trial data. Indeed, there has been a recent proliferation of papers promising great flexibility in midcourse correction of sample size and other design features, such as choice of primary endpoint. We point out the difficulty in accurately estimating the treatment effect midway through a trial, and we encourage the use of a simple, conservative approach whereby sample size can be increased but not decreased from what was originally planned. We show how to compute the p value and confidence interval for this two-stage procedure. If the original sample size is maintained, analysis of the data is the same as for a fixed sample procedure.

Bayes Theorem↗
PubMed2003

The effect of digoxin on the quality of life in patients with heart failure.

BACKGROUND: The Digitalis Investigation Group (DIG) trial was a randomized double-blind placebo-controlled study that examined the effect of digoxin on mortality in 7,788 patients with heart failure and sinus rhythm. A prespecified substudy evaluated the effect of digoxin therapy on health-related quality of life (HQOL) in a subset of these patients. METHODS: Patients in the DIG trial had clinical heart failure and were randomized to either digoxin or placebo in addition to their baseline diuretic and angiotensin-converting enzyme therapy (n = 7,788). The patients in this substudy had HQOL measured using a self-administered questionnaire employing scales that measured general health, physical functioning, depression, anger, anxiety, life satisfaction, and disease specific measures. A subjective assessment by the investigator and a 6-minute walk test evaluated functional status. HQOL was measured at baseline and at the 4- and 12-month follow-up visits. RESULTS: The baseline characteristics of the patients in the quality of life substudy (n = 589) were comparable to the remaining patients in the study (n = 7,199) by age and other clinical measures, including history of prior myocardial infarction or etiology of heart failure; heart failure was of shorter duration and the ejection fraction was slightly better than in the main trial. Within the substudy, patients receiving digoxin (n = 298) or placebo (n = 291) were also similar in baseline characteristics. There was no statistically significant difference in any HQOL measure between the digoxin and the placebo groups at baseline. At the 4-month visit, only perceived health was improved in the digoxin group. At 12 months, there was no statistically significant difference in perceived health, physical functioning, Minnesota Living with Heart Failure, depression, anxiety, anger, Ladder of Life, or the 6-minute walk between the digoxin and placebo groups. CONCLUSION: In this subset of the DIG population, digoxin therapy had no effect on the HQOL in patients with heart failure in sinus rhythm.

Aged↗
PubMed2002

Innovative designs in behavioural trials.

Clinical trials that compare pharmacological and behavioural treatments require extra attention to design on the part of the investigators. Many of the standard control mechanisms for comparison of active drug to placebo and behavioural therapy to control therapy create problems when the two types of interventions are combined. The most important of these problems is the introduction of non-specific effects introduced by behavioural therapists and physicians that can bias the study. Solutions to these problems require procedures that are common to both types of studies and the introduction of more complex statistical designs to adequately control the proposed comparisons. It may also be necessary to have a robust statistical method to address informative censoring since patients assigned to behavioural therapy may drop out of the study for different reasons than patients who drop out of a pharmacological trial. In this paper we use the design of the Raynaud's Treatment Study to demonstrate methods that can be used to control for non-specific effects and differential drop-out from the study.

Behavior↗
PubMed2002

Parametric and semiparametric approaches to testing for seasonal trend in serial count data.

We present two tests for seasonal trend in monthly incidence data. The first approach uses a penalized likelihood to choose the number of harmonic terms to include in a parametric harmonic model (which includes time trends and autogression as well as seasonal harmonic terms) and then tests for seasonality using a parametric bootstrap test. The second approach uses a semiparametric regression model to test for seasonal trend. In the semiparametric model, the seasonal pattern is modeled nonparametrically, parametric terms are included for autoregressive effects and a linear time trend, and a parametric bootstrap test is used to test for seasonality. For both procedures, a null distribution is generated under a null Poisson model with time trends and autoregression parameters. We apply the methods to skin melanoma incidence rates collected by the surveillance, epidemiology, and end results (SEER) program of the National Cancer Institute, and perform simulation studies to evaluate the type I error rate and power for the two procedures. These simulations suggest that both procedures are alpha-level procedures. In addition, the harmonic model/bootstrap test had similar or larger power than the semiparametric model/bootstrap test for a wide range of alternatives, and the harmonic model/bootstrap test is much easier to implement. Thus, we recommend the harmonic model/bootstrap test for the analysis of seasonal incidence data.

Journal Article↗