bluuebunny/crossref_metadata_2025_split huggingface dataset:
Estimation issues in clinical trials and overviews
Authors: Pocock Stuart J. , Hughes Michael D. 
Published: April 2007

AbstractThere is a general move towards greater emphasis on point and interval estimates of treatment effect in reporting of clinical trials, so that significance testing plays a lesser role. In this article we examine a number of issues which affect the use and interpretation of conventional estimation methods. Should we accept or avoid the stereotypes of 95 per cent confidence? Should the abstract of a trial report include confidence intervals for major endpoints? Are frequentist confidence intervals being interpreted correctly, and should Bayesian probability intervals be more widely used in trial reports? Does the timing of publication, such as early stopping because of a large observed treatment difference, lead to exaggerated point and interval estimates? How can we produce realistic estimates from subgroup analyses? Is publication bias seriously affecting our ability to obtain unbiased estimates? Is the emphasis on estimation methods a powerful tool for encouraging larger sample sizes? Can we resolve the controversy concerning fixed or random effects models for estimation in overviews of related trials? Our arguments are illustrated by results from recent trials in cardiovascular disease.
The design of case‐control studies: The effect of confounding on sample size requirements
Authors: Drescher Karsten , Timm Jürgen , Jöckel Karl‐Heinz 
Published: April 2007

AbstractThis paper considers the extent to which confounding effects of covariates, which are not controlled for by matching in the design, may influence the sample size necessary for case‐control studies. The quantitative calculations are performed for an age‐matched case‐control study on lung cancer and air pollution, and are based on different evaluation methods. For illustrative purposes attention is confined to a dichotomous risk factor and a single dichotomous covariate. By using the numerical values of a pilot study investigating lung cancer and air pollution, it turns out that the sample size required for detecting a relative risk as close as 1.15 to 1 is only slightly influenced by the strength of the association between confounder and risk factor for reasonable variations around our empirical values. On the other hand, sample size considerably increases with increasing relative risk of a confounder even when the association remains small. The sample size required for an individually matched analysis practically equals that for an age‐stratified analysis when the relative risk of the covariate is one. With a relative risk greater than one, however, the size for a matched analysis exceeds that for a stratified analysis and the ratio between them increases with increasing relative risk.
Efficient evaluation of treatment effects in the presence of missing covariate values
Authors: Schemper Michael , Smith Terry L. 
Published: April 2007

AbstractIn clinical trials, treatment comparisons are often performed by models that incorporate important prognostic factors. Since these models require complete covariate information on all patients, statisticians frequently resort to complete case analysis or to omission of an important covariate. A probability imputation technique (PIT) is proposed that involves substituting conditional probabilities for missing covariate values when the covariate is qualitative. Simulation results are presented which demonstrate that the method neither violates the size of the treatment test nor introduces additional bias for the estimation of the treatment effect. It allows use of standard software. A clinical trial of breast cancer treatment, in which an important covariate was partly missing, was analysed by Cox's model. The use of PIT resulted in smaller observed error probability compared with case deletion, and sensitivity analysis supported these results.
A Markovian model for comparing incidences of side effects
Authors: Bristol David R. , Patel H. I. 
Published: April 2007

AbstractFor clinical trials that entail observations at successive visits for the occurrence of a side effect, this paper considers a likelihood‐based method to compare side effect incidence rates. The method, which employs the assumption of a Markov chain of order one for the vectors of binary responses, handles missing data due to premature withdrawals. An actual numerical example and a simulated example illustrate the technique.
More powerful procedures for multiple significance testing
Authors: Hochberg Yosef , Benjamini Yoav 
Published: April 2007

AbstractThe problem of multiple comparisons is discussed in the context of medical research. The need for more powerful procedures than classical multiple comparison procedures is indicated. To this end some new, general and simple procedures are discussed and demonstrated by two examples from the medical literature: the neuropsychologic effects of unidentified childhood exposure to lead, and the sleep patterns of sober chronic alcoholics.
Early methodological developments for clinical trials at the national heart, lung and blood institute
Authors: Halperin Max , Demets David L. , Ware James H. 
Published: April 2007

AbstractThe National Heart Institute, now known as the National Heart, Lung and Blood Institute (NHLBI), initiated its first multicentre randomized clinical trials of rheumatic fever and rheumatic heart disease in 1951. The modern era of multicentre trials began, however, when the Coronary Drug Project was initiated in the 1960s. This trial and subsequent NHLBI trials stimulated a wide variety of research on clinical trial methodology. This paper reviews early methodologic developments in four areas. First, an organizational structure for multicentre clinical trials was developed and codified in the ‘Greenberg Report’ in 1967. Second, design considerations related to patient risk, non‐compliance, a lag in treatment effect, and changing risk were explored. The ‘intention‐to‐treat’; principle was implicit in these investigations. Thirdly, the concept of periodic review of accumulating data, recommended in the Greenberg report, stimulated research on methods for sequential analysis. Three statistical approaches were developed and investigation of their statistical properties continues today. These approaches are usually described as group sequential, stochastic curtailment, and Bayesian methods. Finally, comparison of treatments in longitudinal studies has been an increasing part of NHLBI research and methods have been developed for design and analysis of longitudinal studies.
Estimating benefits of screening from observational cohort studies
Authors: Flanders W. Dana , Longini Ira M. 
Published: April 2007

AbstractAnalysis and interpretation of observational studies of screening effectiveness is difficult because several biases threaten validity, including the structural healthy screenee bias, length bias, and effects of lead time. Although methods for the analysis of observational studies of screening effectiveness have been proposed, most have limitations such as incomplete control of length bias, or a heavy reliance on distributional assumptions. In this report we present a method for the analysis of observational cohort studies of screening effectiveness. Although developed independently and formulated specifically for estimating benefits of screening, our approach is implied by a more general approach developed previously by Robins. Our approach, in contrast to other available methods, avoids the healthy screenee bias, and length and lead time bias, and allows an empirical approach to analysis that need not depend highly on distributional assumptions. We illustrate application of the approach with analysis of published data from a study of breast cancer screening.
The use of logit models to investigate social and biological factors in infant mortality. V: A multilogit analysis of stillbirths, neonatal and post‐neonatal mortality
Authors: Murrells T. J. , Smith T. M. F. , Machin D. 
Published: April 2007

AbstractInfant mortality data for England and Wales, cross classified by mother's age, parity and social class were published for 1949/50 and 1975. Previous analyses of these data have been based on graphical, tabular and logit models of stillbirths, neonatal and post‐neonatal deaths separately. This paper summarizes the overall changes in infant mortality using a multilogit model. The model selected is illustrated by appropriate graphical presentations.
Proportion cured and mean log survival time as functions of tumour size
Authors: Gamel John W. , McLean Ian W. , Rosenberg Saul H. 
Published: April 2007

AbstractWe obtained maximum likelihood estimates (MLEs) of the proportion cured πcand mean log survival time μtfor a sample of 4355 patients with intraocular melanoma whose survival times subsequent to treatment were assumed to follow a log‐normal distribution. Following stratification by tumour size, MLEs of πcand μtderived for each stratum correlate inversely with tumour size. We then expressed πcand μtas continuous functions of tumour size and calculated MLEs for the parameters of these functions from the entire sample. This investigation documents for ocular melanoma a significant relationship of tumour size to both cured fraction and mean log survival time.
Practical bayesian analysis of a simple logistic regression: Predicting corneal transplants
Authors: O'Hagan A. , Woodward E. G. , Moodaley L. C. 
Published: April 2007

AbstractThe Bayesian analysis of a logistic regression model is described using an example of predicting the need for a corneal transplant in keratoconus. Controversy over the use of subjective prior information in Bayesian methods is avoided by a formulation representing negligible prior information. Simple computational procedures are described, and it is argued that the results are more accurate, clearer and make fuller use of the information contained in the data. Analysis of more complex models is considered. In particular, it is argued that classical methods as implemented in the computer package GLIM can be used as approximations to Bayesian methods, particularly at the initial stage of model selection.
Estimation of the design effect in community intervention studies
Authors: Mickey Ruth M. , Goodwin Gregory D. , Costanza Michael C. 
Published: April 2007

AbstractThis paper considers the estimation of the variance of a mortality rate in community intervention studies with little or no replication of intervention regimens. Our approach in estimation of this cluster sampling variance is to determine the variance for simple random sampling and multiply it by a design effect which we calculate with use of information obtained from other sources. When the county is the unit of randomization and the outcome is mortality, we calculate the design effect as the ratio of the age adjusted mortality rates for single stage cluster sampling relative to simple random sampling; we use information from all counties in a state in the calculations. We apply this approach empirically for breast cancer mortality. We found that these design effects were dependent on length of time for accumulation of deaths (1.1 for one year up to 3.5 for eight years) and were quite consistent for the three states and nine years considered in the investigation. We present a model that accounts for the time dependence of the design effect and we show it provides a good representation of the observed relationship.
Some methods of combining class information in multivariate normal discrimination for the classification of human chromosomes
Authors: Kirby S. P. J. , Theobald C. M. , Piper J. , Carothers A. D. 
Published: April 2007

AbstractWe consider the use of discriminant analysis based on an assumption of multivariate Normality for allocating human chromosomes in an automated system. In this context, the assumptions which might be made about the covariance matrices for the different chromosome classes have important implications for the error rate of the system and the time required to allocate a chromosome. Linear discriminant functions based on the assumption of a common covariance matrix for all classes are fast but sometimes give bigger error rates than the assumption of a separate covariance matrix for each class. The latter assumption requires many more calculations to evaluate the associated quadratic discriminant functions. However, it is possible to assume that the covariance matrices for the different classes are, in various senses, similar to one another in order to derive other methods of combining class information on variability. These methods are here incorporated in the estimative maximum‐likelihood approach to discrimination. The methods considered lead to machine classification times of human chromosomes intermediate between those for the assumptions of a common or unrelated covariance matrices. They also require the simultaneous estimation of fewer parameters than the use of a separate covariance matrix for each chromosome class. The methods are illustrated by three data sets of very different quality. Graphs of estimated error rate against classification time show that some of these ways of combining class information can be useful in the trade‐off of error rate against time.
Statistical methods to adjust for date and age misreporting to improve estimates of vital rates in Pakistan
Authors: Pullum Thomas W. 
Published: April 2007

AbstractMisreporting of dates and ages poses serious difficulties for the estimation of the age distribution and birth and death rates in many developing countries. The pervasiveness of these problems is illustrated with data from a well‐designed on‐going survey in Pakistan, the Pakistan Demographic Survey. Methods for reconciling discrepancies, based on the assumptions of constant misreporting and survivorship patterns, are presented. The reasoning behind these methods could be applied much more generally. Research into the cultural interpretations of age and dates, and the nature of possible biases, is called for.
Coping with extra poisson variability in the analysis of factors influencing vaginal ring expulsions
Authors: Campbell M. J. , Machin D. , D'Arcangues C. 
Published: April 2007

AbstractThe vaginal ring is one method of contraception currently under investigation and development by the Human Reproduction Programme of WHO. One factor that reduces its acceptability is that some women experience involuntary expulsions of the ring. WHO have collected prospective data on 1005 women from 19 centres worldwide to investigate various aspects of ring use including factors that might affect expulsions. For each subject the data include number of expulsions, age, parity, ponderal index, number of days of ring use and health care centre. To model the factors influencing expulsion, the number of expulsions was first considered as a Poisson variate with mean directly proportional to the log of the duration of ring use. Such a model gave a poor description of the data and it appeared that the number of expulsions was considerably over‐dispersed for an assumed Poisson variate. This paper examines a variety of strategies for coping with the resulting lack of fit of the model. It turns out that a truncated Poisson model gives a better description of the expulsion data and that health care centre and parity influence the rates.
A note on the analysis of titration studies
Authors: Chuang‐Stein Christy , Shih Weichung Joseph 
Published: April 2007

AbstractWe propose a method to incorporate all types of dropouts in the evaluation of an intervention based on binary data from a titration study. The proposed procedure does not require that the dropouts occur randomly, but instead examines each outcome individually. Our procedure has a built‐in penalty factor in the estimation process that determines the amount of penalty on efficacy parameters due to efficacy‐related dropouts. We also propose a method to estimate the variances associated with the estimates. The results have use in exploration of a potential dose‐response relationship or to answer questions pertinent for phase III studies. We use data from a phase III antihypertension study to illustrate the procedure.
Alternative parameterization of polychotomous models: Theory and application to matched case‐ontrol studies
Authors: Becher Heiko 
Published: April 2007

AbstractA method is proposed for transforming a class of models having an outcome variable with more than two levels into an equivalent binary model. The polychotomous logistic model is used to demonstrate the method. The equivalency to a simple logistic regression model after some data transformation (augmentation) is shown. The method is applied to the data from two case‐ontrol studies each with two control groups, and further applications are indicated.
Are ordinal models useful for classification?
Authors: Campbell M. Karen , Donner Allan , Webster Karen M. 
Published: April 2007

AbstractThere is recent interest in classification procedures intended for use only when the response is ordinal. Ordinal response, however, is evident in the parameters estimated by either multinomial logistic or normal discriminant analyses, both of which classify either ordinal or non‐ordinal responses. Further, there may be harm in applying ordinal models inappropriately and ample opportunity to assume mistakenly ordinality in real data sets. Therefore, it becomes important to ascertain whether there is benefit obtained in the appropriate application of ordinal models. This paper presents the results of a simulation study designed to compare classification accuracy of various models. We show that ordinal models classify less accurately than the multinomial logistic and normal discriminant procedures under a variety of circumstances. Until further studies become available, we presently conclude that ordinal models confer no advantage when the main purpose of the analysis is classification.
Modelling length bias in a longitudinally‐linked record system of HIV cases
Authors: Nedelman Jerry , Burns Alice , Cleary Joan , Gordon Dan , Vernon Philip , Lawrence Charles E. 
Published: April 2007

AbstractWe compare numbers of hospital admissions for intravenous drug using (IVDU) HIV patients and other HIV patients in acute‐are facilities in New York State. Data consist of routinely collected hospital‐discharge reports from New York's Statewide Planning and Research Cooperative System, linked into longitudinal case histories. Because recognition of an IVDU depends on an opioid diagnosis on any record in the case history, the observed distribution of the number of admissions per case for recognized IVDU's is biased towards greater numbers of admissions. We develop and apply a model to overcome this biasing. Our findings reveal that the mean numbers of admissions for the two groups differ significantly, but less so than without recognition of the length biasing.
The problem of therapeutic equivalence with paired qualitative data: An example from a clinical trial using haemophiliacs with an inhibitor to factor VIII
Authors: Lee Martin L. , Lusher Jeanne M. 
Published: April 2007

AbstractThe problem of demonstrating the equivalence of two treatments or drugs occurs fairly frequently in medicine, but is quite often misformulated. The common error is to assume equivalence is demonstrated if the usual null hypothesis of no difference is not rejected, which ignores the potential of a substantial β‐error. We describe here two procedures for testing equivalence when the data are paired and dichotomous, and provide sample size formulas. We give an example based on a clinical trial of haemophiliacs with inhibitor to Factor VIII.
Confidence intervals for weighted sums of poisson parameters
Authors: Dobson Annette J. , Kuulasmaa Kari , Eberle Ernst , Scherer Josef 
Published: April 2007

AbstractDirectly standardized mortality rates are examples of weighted sums of Poisson rate parameters. If the numbers of events are large then normal approximations can be used to calculate confidence intervals, but these are inadequate if the numbers are small. We present a method for obtaining approximate confidence limits for the weighted sum of Poisson parameters as linear functions of the confidence limits for a single Poisson parameter, the unweighted sum. The location and length of the proposed interval depend on the method used to obtain confidence limits for the single parameter. Therefore several methods for obtaining confidence intervals for a single Poisson parameter are compared. For single parameters and for weighted sums of parameters, simulation suggests that the coverage of the proposed intervals is close to the nominal confidence levels. The method is illustrated using data on rates of myocardial infarction obtained as part of the WHO MONICA Project in Augsburg, Federal Republic of Germany.
Practice databases and their uses in clinical research
Authors: Tierney William M. , McDonald Clement J. 
Published: April 2007

AbstractA few large clinical information databases have been established within larger medical information systems. Although they are smaller than claims databases, these clinical databases offer several advantages: accurate and timely data, rich clinical detail, and continuous parameters (for example, vital signs and laboratory results). However, the nature of the data vary considerably, which affects the kinds of secondary analyses that can be performed. These databases have been used to investigate clinical epidemiology, risk assessment, post‐marketing surveillance of drugs, practice variation, resource use, quality assurance, and decision analysis. In addition, practice databases can be used to identify subjects for prospective studies. Further methodologic developments are necessary to deal with the prevalent problems of missing data and various forms of bias if such databases are to grow and contribute valuable clinical information.
Using a claims database to investigate drug‐induced Stevens‐Johnson syndrome
Authors: Strom Brian L. , Carson Jeffrey L. , Halpern Allan C. , Schinnar Rita , Snyder Ellen Sim , Stolley Paul D. , Shaw Michele , Tilson Hugh H. , Joseph Michael , Dai Wanju S. , Chen Diane , Stern Robert S. , Bergman Ulf , Lundin Frank 
Published: April 2007

AbstractIn order to explore a priori hypotheses about drug‐induced Stevens‐Johnson Syndrome (SJS), a case‐ontrol study was initiated using data from COMPASSR, a computerized data base consisting of Medicaid claims data. The records of 3.8 million patients in five U.S. states were searched to identify patients with an inpatient diagnosis of ICD‐9‐M code 695.1 (erythema multiforme‐EM). Out of the total of 367 cases that were identified, primary medical records for 249 were sought and 128 (51.4 per cent) of these were obtained. The remainder could not be obtained because: in 36 (29.8 per cent) the hospital refused to provide medical records; in 33 (27.3 per cent) there were transcription errors; in 20 (16.5 per cent) the state could not translate the identification number, primarily because the patients lost Medicaid eligibility too long before our request; in 27 (22.3 per cent) the hospital could not locate the patient's record; and in 5 (4.1 per cent) there were other reasons. Of those with a medical record, 121 (94.5 per cent) had a skin diagnosis and 109 (85.2 per cent) had a diagnosis compatible with ICD‐9‐CM code 695.1 specified on their discharge summary. However, in 35 (27.3 per cent) an expert reviewer felt that the discharge diagnosis was incorrect. In 50 (39 per cent) the computer diagnosis was incorrect. Only 19 (14.8 per cent) were judged by the expert reviewer to truly have Stevens‐Johnson Syndrome, and an additional 37 (28.9 per cent) were judged to have erythema multiforme minor. Thus, the computerized diagnosis agreed very well with the diagnoses specified on the discharge summary. However, EM is frequently misdiagnosed, ICD‐9‐CM code 695.1 contains multiple other diagnoses which are not EM, and much of hospitalized EM is EM minor. Thus, studies of SJS cannot be performed except in patients whose medical records are available.