bluuebunny/crossref_metadata_2025_split huggingface dataset:
Efficient means of studying ancillary questions in clinical trials
Authors: Davis C. E. 
Published: April 2007

AbstractAncillary questions in clinical trials can often be answered by studying subcohorts of the participants. If the question compares responses between treatment groups, a subcohort that preserves the randomization can be used. However, if the question can be answered by analysis within a treatment group or by combining treatment groups, efficient methods developed for observational studies can be used. These methods include case‐control and case‐cohort methods.
How much data should we collect in a randomized clinical trial?
Authors: Verter Joel 
Published: April 2007

AbstractMulticentre randomized controlled clinical trials are usually designed to answer a specific question. In accomplishing this they often collect a large quantity of data during screening, baseline and follow‐up visits. These data are not all necessarily related to the main study question. This collection impacts on the overall recruitment process and the participants' time. During the planning phase of the trial we need to consider the reasons for collecting data and the use of that data for the current study as well as its potential use in future investigations. We discuss briefly some of the possible reasons that data may be collected: screening or determining eligibility; conducting a run‐in or dose titration phase; assessing group comparability; aiding patient management; evaluating the natural history of the disease; monitoring the study; testing the study hypotheses; evaluating adherence; estimating side effects and the use of other therapies; analysis of other study questions.
A clinic's perspective on screening, recruitment and data collection
Authors: Eaton Terry , Pratt Craig M. 
Published: April 2007

AbstractThis paper summarizes the approach of one university cardiology section with over a decade of experience in conducting National Institutes of Health and pharmaceutical cardiovascular trials. Many of the organizational and personnel issues discussed can be directly applied to most university cardiovascular clinical research settings. Other aspects reflect a very specialized approach but key features can be modified or adapted to smaller individual research clinics. In terms of organizational features, our multi‐hospital recruitment effort is co‐ordinated by a weekly clinical research conference which is attended by all nurse coordinators and cardiology fellows. Centralization of all clinic facilities and non‐invasive laboratories, the central computer facility, and the availability of clinical research inpatient hospital beds facilitate our clinical research effort.An expanded role of the nurse co‐ordinator is considered pivotal to trial performance. Suggestions are made as to the identification and recruitment of ideal nurse co‐ordinators, maximizing their productivity, and retaining them. The key feature is the physicians' acceptance of the nurse co‐ordinator as a colleague. The roles of the principal investigator and clinical cardiology fellows are delineated, and suggestions made for data entry and computer technical expertise to optimize nurse co‐ordinator efficiency, allowing total focus on recruitment and follow‐up.
Opportunities for enhancing efficiency and reducing cost in large scale disease prevention trials: A statistical perspective
Authors: Prentice Ross L. 
Published: April 2007

AbstractRandomized intervention trials play an important role in the identification of practical approaches to reducing major chronic diseases in our society. Very few such trials are likely to be possible, however, in coming years unless we adopt procedures less demanding and less costly than those used in the past. Towards this end some elements of an efficient prevention trial are discussed, including aspects of study design, criteria for eligibility and exclusion, procedures for data collection, follow‐up, endpoint ascertainment, and data analysis, and for ancillary studies. For example, possibilities for enhancing efficiency in the use of endpoint events include the selection of an appropriately weighted test statistic, the use of case‐control or case‐cohort sampling procedures in the processing of covariate data and specimens, and the notion of replacing a disease endpoint by an earlier or less expensive surrogate endpoint. Ideas for enhancing the efficiency of prevention trials will be illustrated in the context of a proposed Dietary Fat Intervention Trial for disease prevention in women.
Survival analysis techniques in angina pectoris trials
Authors: Bristol D. R. , Castellana J. V. 
Published: April 2007

AbstractThe variable ‘walking time to moderate angina’ on an exercise stress test is the primary means to judge the efficacy of new treatments for angina pectoris. Unfortunately, ‘walking time to moderate angina’; is often censored by fatigue or other reasons for premature termination of the exercise stress test. If time to fatigue is not treatment‐dependent, we propose use of survival analysis techniques in such trials. We present an example from a placebo‐controlled multicentre clinical trial and results of simulations that compare various methods of analysis.
Receiver operator characteristic (ROC) curves and non‐normal data: An empirical study
Authors: Goddard M. J. , Hinberg I. 
Published: April 2007

AbstractThis paper evaluates the performance of several diagnostic kits for assessing levels of serum prostatic acid phosphatase on patients at different stages of cancer of the prostate. Each patient was studied with several kits. We compare results obtained for receiver operator characteristic (ROC) curve methodology with data assumed to follow a normal distribution, with log‐transformed data assumed to follow a normal distribution, and when neither of these assumptions holds. There were important differences between the results of the different approaches. For these data, the normal distribution assumption should be used with extreme caution. The log‐transformed based results compared favourably with the non‐parametric, but unconsidered application of the method should be avoided.
On the use of a logistic risk score in predicting risk of coronary heart disease
Authors: Chambless Lloyd E. , Dobson Annette J. , Patterson C. C. , Raines Byron 
Published: April 2007

AbstractMany studies over the last 20 years have used logistic regression to model the relationship between the risk of developing coronary heart disease (CHD) and the levels of risk factors such as high blood pressure, high serum cholesterol, and cigarette smoking. Subsequently, several investigators have proposed the use of some of the published estimated logistic risk functions to predict risk in new populations. Because of great variation in definition of event, duration of follow‐up, population characteristics, definition of risk variables, and selection of other variables in the logistic functions, direct use of such established functions would generally not have validity for the prediction of absolute risk levels. A review of fifteen of these studies indicates on the one hand generally similar results in direction and order of magnitude of effects of the major risk factors, confirming the importance of these risk factors of CHD. On the other hand the reviews indicate sufficient variation to suggest that extrapolation to new populations even to predict relative risk is not justified.
Application of the theory of finite mixtures for the estimation of ‘cure’ rates of treated cancer patients
Authors: Gordon N. H. 
Published: April 2007

AbstractI assume the survival function of treated cancer patients to be a mixture of two subpopulations, withcequal to the proportion who will die of other causes, and 1 —cthe proportion who will die of their disease. Using census data, I estimate the parameters of the survival distribution of those patients dying of other causes, and then use follow‐up data to determine the maximum likelihood estimates of the proportion constantcand the parameters of the survival function of those dying of their disease. I illustrate the methodology using data from a prospective clinical trial in breast cancer.
The power to detect differences in average rates of change in longitudinal studies
Authors: Lefante John J. 
Published: April 2007

AbstractWith considerable current interest in longitudinal epidemiologic studies, little is available regarding sample size requirements. This paper considers a method for analysis of longitudinal data, where one compares the mean rates of change for two or more groups, and proposes a statistic for use in determining sample size requirements. One calculates individual rates of change with least squares estimates of slopes of individuals' responses regressed over time. The assumption of linear change over time, while clearly not applicable for some data, applies to many biological measurements, either as recorded or with some transformation. The variances of these estimated slopes have two components: within‐individual variability based on measurement error and length and frequency of follow‐up, and true between‐individual slope variability. It is assumed that measurement error is the same for all subjects, so that the total variances differ due to differences in follow‐up. The question addressed is: when can one use the usual ANOVA F statistic to compare group means of estimated slopes? Expected mean squares demonstrate that this F is appropriate when either each group has the same number of subjects, or when each subject has the same length and frequency of follow‐up. A procedure for computing power and sample size is presented, where one can specify the maximum detectable difference in any two average slopes. Moment estimation and maximum likelihood estimation of variance components from prior data are discussed.
Factorial designs for crossover clinical trials
Authors: Fletcher D. J. , Lewis S. M. , Matthews J. N. S. 
Published: April 2007

AbstractWhen measuring the joint effect of two factors it is advantageous to use a factorial design. If the application is suitable, efficiency may be further improved by using a crossover design. This paper presents a flexible method for amalgamating these two devices. Designs are constructed from smaller designs, known as bricks, generated cyclically from tabulated initial sequences. The bricks have known efficiencies for estimation of direct treatment main effects and interactions; the efficiencies can be simply combined to approximate the efficiencies of the whole design. This allows the user to build a design that is tailored to the particular objectives of the experiment. Three and four periods, and two factors with up to four levels are considered.
Symmetry and quasi‐symmetry: An example in modelling pairs of sounds from children's early speech
Authors: Stasny Elizabeth A. , Bauer Harold R. 
Published: April 2007

AbstractThe models of symmetry and quasi‐symmetry may have use in the analysis of categorical data in square tables where the row and column classifications are the same. Under the model of symmetry, the probability that an observation falls in, say, the (i, j) cell of a square table is the same as the probability that it falls in the (j, i) cell. The model of symmetry requires that the expected marginal total for any one row of the table be the same as the expected marginal total for the corresponding column. The model of quasi‐symmetry, which is a generalization of the model of symmetry, does not require this equality of expected row and column totals. In this paper, we illustrate the use of the models of symmetry and quasi‐symmetry in the analysis of categorical data that summarize pairs of sounds in infants' and toddlers' early utterances. In the past, the complexity of infants' early vocalizations has been difficult to measure because of a lack of methods to quantify prelinguistic phonetic variables. We use the models of symmetry and quasi‐symmetry as a first attempt to quantify the complexity of infants' early speech. We hope that the discovery of models appropriate for quantification of language development in normal children will have later use in identification of children at risk for communicative disorders.
A comparison of poisson regression models fitted to multiway summary tables and cox's survival model using data from a blood pressure screening in the city of Bergen, Norway
Authors: Selmer Randi 
Published: April 2007

AbstractMultiplicative models for the association between blood pressure and coronary heart disease mortality in 5201 men aged 40–49 years at time of examination were compared. Piecewise exponential models fitted to summary tables formed by cross‐classification by three systolic and three diastolic blood pressure groups, two age groups and three time intervals gave results close to the Cox model for continuous data. The parametric integrated baseline hazard functions estimated from grouped data were close to Breslow's non‐parametric estimate in the Cox model.
A note on point estimation of the hazard ratio in exponential distributions
Authors: Lui Kung‐Jong , Rhodes Phil 
Published: April 2007

AbstractThe maximum likelihood estimator (MLE) of the ratio of the hazard rates in two exponential distributions is biased. This bias can be important when sample sizes are small or the ratio of these two hazard rates is large. When there is either no censoring or type II censoring, we propose using the uniformly minimum variance unbiased estimator (UMVUE). We show that using the UMVUE instead of the MLE reduces the mean‐squared error (MSE). We have found that the UMVUE always has MSEs smaller than the MLE. We have also found that the UMVUE leads to important reductions in the MSE when the sample size used to calculate the hazard rate in the numerator of the hazard ratio is small (say ⩾ 20) regardless of the sample size in the denominator. In the presence of type I censoring, the proposed estimator and the MLE are both biased. On the basis of a Monte Carlo study, however, we obtain similar reductions in the MSE using the UMVUE, as for no censoring or type II censoring.
Analysing clinical decision analyses
Authors: Habbema J. D. F. , Bossuyt P. M. M. , Dippel D. W. J. , Marshall S. , Hilden J. 
Published: April 2007

AbstractWe present a critical review of aspects of clinical decision analysis which uses an application to screening for familial intracranial aneurysms. The analysis is reported together with methods for assessing decision trees. These methods appear to be powerful checks on the usually rather intuitive way in which decision trees are built. The problem of assessing the uncertainty in the results of a decision analysis is discussed in detail. In practice, sensitivity analysis covers nearly every calculation apart from the standard evaluation of the decision tree. Different forms of sensitivity analysis are distinguished and given appropriate names: influence analysis, threshold analysis, full Bayesian analysis, Bayesian influence analysis, attribute analysis, generalization analysis and scenario analysis. The biostatistical community may well contribute to the much needed methodological improvement in decision analysis and its different forms of sensitivity analysis, especially if prepared to look beyond the standard statistical techniques.
The marriage of clinical trials and clinical decision science
Authors: Hilden Jørgen , Habbema J. Dik F. 
Published: April 2007

AbstractClinical decision science is concerned with rational clinical decisions. All branches of medical research contribute here, but controlled clinical trials of the pragmatic variety carry a particular responsibility. Usually, however, they are not conducted and reported so that they can be used directly as input to a decision analysis. We suggest that the forces of the two methodologies should be united, and point out some areas where this ‘marriage’ will have a non‐trivial impact: choice of end points, style of outcome recording, adaptive designs, and style of result presentation. Special attention is given to the decision‐analytic setting of research priorities, the role of utility calculus in quantifying the ethical dilemmas that surround clinical trials, and the use of patient attitude towards outcomes of treatment as a covariate in its own right.
Quality adjusted survival analysis
Authors: Glasziou P. P. , Simes R. J. , Gelber R. D. 
Published: April 2007

AbstractWe present a technique, quality adjusted survival analysis, for the analysis of controlled trials where patients may experience several health states which differ in their quality of life. When the data are censored, a survival analysis of the quality adjusted life years achieved may involve informative censoring, and produce biased estimates. To overcome this, we partition the survival curve; the resulting areas, which represent the mean time in each state, are multiplied by utility weights to provide an unbiased estimate of (restricted) quality adjusted survival.If the appropriate weights are in doubt, the results are best presented as a threshold analysis over the utility weights, allowing individual recommendation to be read from a simple graph. The certainty of the conclusions can be presented as confidence bands on the threshold line. The techniques are illustrated with a re‐analysis of a large three‐arm trial of adjuvant chemoendocrine therapy for stage II breast cancer in post‐menopausal women. This shows that if the value of time spent in toxicity is greater than the time spent in relapse, we can be 95 per cent confident that chemoendocrine therapy is the preferred option.
Design methods for some dose‐response models
Authors: Strijbosch Leo W. G. , Does Ronald J. M. M. , Albers Willem 
Published: April 2007

AbstractA recently described design method for one‐parameter biomedical models such as limiting or serial dilution assays is generalized to two‐parameter models for which the dose‐response relationship can be expressed as a linear regression model with parameters α (intercept) and β (slope). Design formulae are proposed for three different cases in which prior information about the unknown regression parameters α and β is available (α known, β known and neither known, respectively). A suitable transformation of the two‐parameter model enables the direct application of the one‐parameter design method to the first two cases, while the third needs more advanced considerations. Two experimental designs, taken from the literature, are reproduced as closely as possible using the methods described, thus showing under which circumstances these designs are suitable.
Some statistical issues in studies of the epidemiology of aids
Authors: Jewell Nicholas P. 
Published: April 2007

AbstractAnalyses of studies of the epidemiology and natural history of infection with the Human Immunodeficiency Virus and subsequent onset of AIDS are complicated by many statistical issues. Several such problems are associated with the nature of data collection which is often incomplete. Here we briefly survey some of the statistical methods that have been developed to meet the needs of analysis of AIDS data. In particular, we consider projection of the number of future cases, and estimation and identification of two key epi‐demiological unknowns, namely the properties of the incubation distribution and those of the infectivity associated with transmission.
Group sequential designs using a family of type I error probability spending functions
Authors: Hwang Irving K. , Shih Weichung J. , De Cani John S. 
Published: April 2007

AbstractPerforming planned or unplanned interim analyses on accumulating data in clinical trials is a frequent practice. In this paper, we propose a general one‐parameter family of type I error probability spending functions to construct customized group sequential boundaries with unequal increments in information time. This proposed family generalizes the spending functions of Lan and DeMets1 and Kim and DeMets.2 We give an example to illustrate the use of this family.
Estimation of the linear relationship between the measurements of two methods with proportional errors
Authors: Linnet Kristian 
Published: April 2007

AbstractThe linear relationship between the measurements of two methods is estimated on the basis of a weighted errors‐in‐variables regression model that takes into account a proportional relationship between standard deviations of error distributions and true variable levels. Weights are estimated by an iterative procedure. As shown by simulations, the regression procedure yields practically unbiased slope estimates in realistic situations. Standard errors of slope and location difference estimates are derived by the jackknife principle. For illustration, the linear relationship is estimated between the measurements of two albumin methods with proportional errors.
Survival time models for analysing drug combination treatments
Authors: Kübler Jürgen , Schumacher Martin 
Published: April 2007

AbstractSeveral relative risk models for survival time data in drug combination therapy are derived and their properties are discussed. The main intention of this paper is to clarify the differences among the models in order to help to choose the appropriate one in a given situation. The models are motivated by discussing their relation to well‐known physiological concepts. In an example of two‐drug treatment the models are compared with each other. For this chemotherapy animal survival study, dose‐risk surfaces are fitted and optimal drug combinations are estimated. Methods for checking the model assumptions are mentioned.
European concerted action on offshore wind energy deployment: inventory and analysis of power transmission barriers in eight member states
Authors: Woyte Achim , Gardner Paul , Snodin Helen 
Published: April 2007

AbstractThe European Concerted Action for Offshore Wind Energy Deployment (COD) was carried out by eight sea‐bordering European Union member states, with the objective to remove not explicitly technical barriers to offshore wind energy. Within the COD, an inventory of relevant aspects affecting the grid integration of offshore wind energy on a large scale in the eight countries has been made. Collected data items for this inventory are national plans and prospects for offshore wind energy, information about the transmission system, possibilities for grid connection, aspects of the grid codes, balancing, connection and energy pricing. The comprehensive COD reports were published and presented in October 2005 during the Copenhagen Offshore wind conference. This paper provides a short description of the situation for each country. Thereafter, country‐specific information is grouped based on geography and membership in a synchronous zone. Additionally, a view is developed on the desirable facilities for the trans‐European exchange of power from large wind farms. Finally, we elaborate overall conclusions in order to arrive at generalized observations, recommendations for policy makers and issues that will emerge in the near future. As a general conclusion, many things need to be done on a technical level in order to integrate large amounts of offshore wind power into our power systems. However, none of these measures is technically unknown. Therefore, the feasibility of integrating large amounts of offshore wind power is mainly a question of finance and hence based on political decisions. Copyright © 2007 John Wiley & Sons, Ltd.