bluuebunny/crossref_metadata_2025_split huggingface dataset:
Bimodality of blood pressure levels
Authors: McManus I. C. 
Published: April 2007

AbstractI examine distribution of systolic blood pressure by means of maximum likelihood fitting of various statistical models to the extensive data of Bøe et al., and find evidence for a compound or mixed log‐normal distribution, rather than the single log‐normal distribution proposed by Pickering. I find a second distribution with a mean blood pressure above the ordinary range. I demonstrate further evidence for the existence of this subgroup in the abnormalities of regression to the mean found in the same data set.
Stratified analysis of multivariate clinical data: Application of a mantel‐haenszel approach
Authors: Mantel Nathan , Mocarelli Paolo , Marocchi Alessandro , Brambilla Paolo , Baretta Roberto 
Published: April 2007

AbstractLaboratory determinations on children aged 6 to 10 years obtained over a 5‐year period are analysed by a method described in detail for differentiating between children from exposed and control areas of Seveso, Italy. In the analysis, stratification is employed to distinguish the separate days of laboratory measurement. The analyses permit the study of differences based on all variables simultaneously as well as on each variable separately. Results are obtained for each individual year and for longer intervals of 2 successive years, 3 successive years, 4 successive years, and all 5 years. The results and some statistical aspects of the analysis are discussed.
The need for randomization in the study of intended effects
Authors: Miettinen Olli S. 
Published: April 2007

AbstractThe need for randomization as a means of controlling confounders is accentuated in the study of intended effects (efficacy) as compared with unintended ones (toxicity). The basic reason is that the indication for intervention is inherently a confounder in the study of efficacy but not of toxicity, whereas contraindications represent only a minor confounder even in toxicity research. Moreover, control of the indication in non‐experimental terms is commonly infeasible owing to the complexity and subtlety of the indication.
Analysis of survival data by the proportional odds model
Authors: Bennett Steve 
Published: April 2007

AbstractA model is presented for the analysis of lifetime data in which the rates of mortality for separate groups of patients converge with time. A non‐parametric estimate is given for the survivor function. The theoretical basis for the model assumes that prognostic factors have a multiplicative effect on the odds against survival beyond any given time. The model is fitted to data using maximum likelihood estimation, and an example of its use in the analysis of a lung cancer trial is given.
An analysis of survival differences between clinically and screen‐detected cancer patients
Authors: Habbema J. D. F. , Van Oortmarssen G. J. , Van Putten D. J. 
Published: April 2007

AbstractSurvival differences between clinically and screen‐detected cancer patients partly result from biases. Well known are lead‐time, length bias and overdiagnosis.The survival of the clinically detected patients in the study group of the HIP breast cancer screening project is corrected for these biases. The resulting survival curve is only slightly worse than the survival of the screen‐detected patients. This suggests a very modest mortality reduction by screening.A much larger reduction is obtained from an analysis of the complete HIP results, including those of the control group.It is concluded that a large unexpected selection bias is present. This bias would not have been detected if the HIP study had not contained a randomized control group. A misleading and pessimistic conclusion on the effectiveness of breast cancer screening would thus have resulted. This conclusion reinforces the need for randomized studies.
Fitting regression models to censored survival data
Authors: Hudec M. , Platz H. 
Published: April 2007

AbstractA short review of regression models for the analysis of censored survival data is given. These include multiplicative hazard rate models, log‐linear models (accelerated failure time models), linear models and polynomial models. An application of some of these models to the analysis of a large retrospective study on carcinomas of the oral cavity is described. The results obtained by parametric and semiparametric analyses are compared.
Prognostic factors and risk groups: Some results given by using an algorithm suitable for censored survival data
Authors: Marubini E. , Morabito A. , Valsecchi M. G. 
Published: April 2007

AbstractThe problem of identifying the role of various prognostic factors when the response variable is the patient's survival time is discussed. Morgan and Sonquist's approach1of constructing groups at similar risk is useful and an algorithm which implements the method for survival time data with censored observations is described. Examples of its application to two sets of medical data are given, arising from studies of prognosis following renal transplantation and treatment for stage I malignant melanoma of the skin.
Statistical consulting in clinical research: The two‐way street
Authors: Moses Lincoln , Louis Thomas A. 
Published: April 2007

AbstractClinical research often rests on statistical interpretation of numerical data. Thus, effective collaboration between clinician and statistician can have central importance. Interaction in the planning phases of a project can identify tractable scientific and statistical problems that will need attention and can help avoid intractable ones. The central need is for clear, broad, specific two‐way communication on scientific issues and research roles.
A comparison of standardized and proportional mortality ratios
Authors: Roman Eve , Beral Valerie , Inskip Hazel , McDowall Michael , Adelstein Abe 
Published: April 2007

AbstractProportional mortality analyses are traditionally considered to be unreliable because they lack information on persons at risk. Standardized mortality ratios (SMRs) are often used in preference to proportional mortality ratios (PMRs) even when the denominator or numerator of rates is known to be biased. Examination of data from 30 randomly selected occupational units described by the U.K. Office of Population Censuses and Surveys (OPCS) revealed, however, that age‐standardized cause‐specific SMRs and PMRs have an almost constant relationship: the ratio of the cause‐specific SMR to the cause‐specific PMR closely approximating the all‐cause SMR of the group under consideration. Hence, a PMR above 100 almost always indicates that the corresponding cause‐specific SMR is greater than the all‐cause SMR (and vice versa). Furthermore, approximately 70 per cent of conditions with significantly high PMRs above 200 have corresponding SMRs which are also significantly high. When cautiously interpreted, the PMR may, therefore, be a useful indicator of an increased frequency of disease in a particular occupational or other group.
Case definition and power in case‐control studies
Authors: Rosenbaum Paul R. 
Published: April 2007

AbstractA narrow case definition can lead to greater in clarity in case‐control studies, but it can also lead to either a gain or a loss in the power of statistical tests. Under plausible assumptions, the loss of power can be in excess of 30 per cent, and the gain can be in excess of 50 per cent. If at least one third of the total study size consists of narrowly defined cases, the loss of power will often be negligible, whereas the gain can be substantial.
A non‐parametric graphical representation of the relationship between survival and the occurrence of an event: Application to responder versus non‐responder bias
Authors: Simon Richard , Makuch Robert W. 
Published: April 2007

AbstractReports of cancer clinical trials often attempt to evaluate whether tumour response is associated with prolonged survival. Proper analysis requires accounting for the time‐dependent nature of response status. We review a valid and relatively simple method of significance testing for this problem, and develop a corresponding non‐parametric method for displaying the association between survival and occurrence of response. The new method applies to many other clinical problems involving representation and the association between survival and the occurrence of an event. We illustrate the method with data from two clinical trials.
Clinical trials designed to evaluate therapeutic preferences
Authors: Baskerville J. C. , Toogood J. H. , Mazza J. , Jennings Barbara 
Published: April 2007

AbstractWe present an experimental design for the evaluation of therapeutic preferences among well established similar modes of therapy. The measure of the degree of preference is based on clinical decisions to continue or discontinue the current treatment at each patient visit. Such a trial simulates decision‐making in ordinary clinical practice, while adhering to the scientific principles of experimental design, and it alleviates some of the ethical problems inherent in randomized allocation of a treatment for a period of fixed length in conventional controlled trials. We discuss the design and methods of analysis and illustrate their application with data from a trial comparing three alternative drug treatments for chronic asthma.Such clinical trials provide a mechanism for examining concordance between the relative efficacy of treatments predicted from conventional controlled clinical trials and their ultimate performance in ordinary clinical practice, expressed in terms of therapeutic preferences.
Analysis of linkage and association for diseases of genetic aetiology
Authors: Sturt Elizabeth 
Published: April 2007

AbstractThis presentation attempts to clarify certain caveats that apply to the use of linkage analysis when the genetics of one of the characters is not completely known. The effects of linkage and association can be difficult to distinguish both within pedigrees and across the general population. Linkage analysis methods are not robust to departures from the assumptions of the model. These assumptions do not allow for the possibility that association may be present which is due to both genetic systems having an effect on one of the phenotypes. Analysis directed towards detecting the presence of such association may be affected by stratification when unrelated individuals are analysed and is confounded by linkage if this is present when related individuals are analysed. Testing for and estimating linkage simultaneously with association using whole pedigree data is advocated and an outline of the required approach is given.
An application of kappa‐type analyses to interobserver variation in classifying chest radiographs for pneumoconiosis
Authors: Musch David C. , Landis J. Richard , Higgins Ian T. T. , Gilson John C. , Jones Robert N. 
Published: April 2007

AbstractWe investigated interobserver variation between three physician readers in the independent classification of chest radiographs from 1771 taconite workers for pneumoconiosis. We analysed variation with a general methodology for the analysis of categorical data, and quantified interobserver agreement in terms of kappatype statistics. The results revealed considerable variation in the profusion of opacities reported by each observer. This was especially so for the earliest radiographic changes, but variation also occurred with the small number of films in the series showing category 2 pneumoconiosis or over. Variation in the classification of profusion of small opacities was greater in films of poor quality, and also increased with the length of time between taking and reading the film (film age). We could not account for the effect of film age by controlling for film quality, as subjectively assessed by the readers.
The choice between analysis of variance and analysis of covariance with special reference to the analysis of organ weights in toxicology studies
Authors: Shirley Eryl A. C. , Newnham Peter 
Published: April 2007

AbstractThe problem of when to include a covariate in the analysis of variance is considered in the special case of organ weight analysis in animal toxicology studies. The covariate is bodyweight prior to death, which may be subject to treatment effects. A simulation study is carried out to compare four rules for deciding whether or not to include the covariate. It is concluded that if there is background information which shows a linear relationship between variate and covariate it is advisable to adjust for the covariate, however weak the relationship may appear to be on the current set of data. Alternative procedures lead to unacceptably high Type I error rates.
Bias in methods for deriving standardized morbidity ratio and attributable fraction estimates
Authors: Greenland Sander 
Published: April 2007

AbstractThis paper examines several methods for deriving standardized morbidity ratios (SMR) and attributable fraction (attributable risk percentage) estimates. We show that some of the proposed methods will, in general, produce biased estimators, although the low variance of certain estimators sometimes compensates for their bias. A few methods are based on statistical fallacies and should be avoided, especially the method of deriving the expected number of cases from a regression equation that does not include the exposure under study.
Survivorship analysis when cure is a possibility: A monte carlo study
Authors: Goldman Anne I. 
Published: April 2007

AbstractParametric survivorship analyses of clinical trial commonly involves the assumption of a hazard function constant with time. When the empirical curve obviously levels off, one can modify the hazard function model by use of a Gompertz or Weibull distribution with hazard decreasing over time. Some cancer treatments are thought to cure some patients within a short time of initiation. Then, instead of all patients having the same hazard, decreasing over time, a biologically more appropriate model assumes that an unknown proportion (1 ‐ π) have constant high risk whereas the remaining propotion (π) have essentially no risk. This paper discusses the maximum likelihood estimation of π and the power curves of the likelihood ratio test. Monte Carlo studies provide results for a variety of simulated trials; empirical data illustrate the methods.
The analysis of repeated measures designs in medical research
Authors: Keselman H. J. , Keselman Joanne C. 
Published: April 2007

AbstractMedical researchers can employ repeated measures designs to study the effects of a treatment over time or when each subject receives all treatments. Univariate F tests and multiple comparison procedures for comparing means constitute the methods to test for the presence of treatment effects. For validity, however, these tests must satisfy the sphericity assumption. To circumvent the biasing effects of non‐sphericity, this paper shows the applicability of the Greenhouse and Geisser three stage approach for univariate omnibus hypothesis testing in repeated measures designs containing any number of repeated factors. In addition, we present a multiple comparison procedure which provides a valid or robust test and thus controls the overall probability of a Type I error.
Allocation of treatment to patients when not all balancing factors are known to the co‐ordinating centre
Authors: Van Lier Henk J. J. , Van Elteren Philip , Hoitsma Andries J. , Koene Robert A. P. 
Published: April 2007

AbstractThe allocation of treatment to patients in a clinical trial while balancing for prognostic factors is usually done by a co‐ordinating centre when all the factors are known. In a trial comparing two treatments of acute rejection of renal allografts some prognostic factors become available to the physician only at the moment of the diagnosis of the rejection. This diagnosis is often made out of office hours, whereas immediate start of treatment is essential. It is shown here that the co‐ordinating centre is still able to control the allocation of patients to treatment groups if a small number of prognostic factors is known only to the physician.
Medical registers as historical controls: Analysis of an open clinical trial of inosiplex in subacute sclerosing panencephalitis
Authors: Hoehler Fred K. , Mantel Nathan , Gehan Edmund , Kahana Esther , Alter Milton 
Published: April 2007

AbstractClinical trials of treatments for rare or fatal diseases must often use historical rather than randomized concurrent controls. Randomized trials may not be possible if (1) the number of patients available is quite small, (2) ethical considerations discourage the assignment of patients to control treatments known to be ineffective or (3) some evidence suggests that the proposed new treatment is substantially more effective than the control. We suggest that, when randomization is not feasible, adequately maintained medical registers can serve as a source of control patients. Investigators must pay careful attention to prognostic factors that might bias the results. However, statistical techniques for controlling such bias exist and, if these are properly employed, registry‐derived historical controls can be used to evaluate the effectiveness of treatment.
Automatic classification of biomedical information when classification error is unknown
Authors: Stoddard Anne M. 
Published: April 2007

AbstractThis paper describes a distribution‐free method for the automatic classification of individuals by phenotype of the serum protein α1‐antitrypsin. This method achieved 74 per cent agreement and a Kappa value of 0.24 when compared to the conventional classification procedure on an independent testing sample. The methodology is appropriate for many classification problems, particularly when the true classes and the reliability of the conventional procedure are unknown.
A comparison of chi‐square partitioning and two logit analyses of ordinal pain data from a pharmaceutical study
Authors: Cox Christopher , Chuang Christy 
Published: April 2007

AbstractWe study three approaches for the analysis of ordinal pain data. The first is essentially non‐parametric, based on partitioning the goodness‐of‐fit statistic for testing the homogeneity model. The other two involve the modelling of quite different logit functions of the multinomial probabilities. We discuss and compare the characteristics of these three approaches using actual data from an analgesic trial.
An application of ridge regression analysis in the study of syphilis data
Authors: Hadgu Alula 
Published: April 2007

AbstractWe provide a brief summary of the theory of ridge regression, regress reported rates of congenital syphilis on three stages of adult syphilis using both ridge regression and least squares techniques, and discuss the results. We also develop a principal components regression model for the same example and compare the results.The example demonstrates the usefulness of ridge regression to handle multicollinearity in data. Problems of overestimation and instability associated with ordinary least squares estimates of these non‐orthogonal data diminish with use of the ridge regression techniques.
Tying clinical research to patient care by use of an observational database
Authors: Hlatky Mark A. , Lee Kerry L. , Harrell Frank E. , Califf Robert M. , Pryor David B. , Mark Daniel B. , Rosati Robert A. 
Published: April 2007

AbstractThe proposition that some inherent logical incompetence attaches to an inference based on observational, as distinguished from experimental, evidence seems to have little to commend it beyond the great positiveness with which it is sometimes asserted.
A community trial strategy for evaluating treatment for symptomatic conditions
Authors: Charlton J. R. H. , D'souza M. F. , Tooley M. , Silver R. 
Published: April 2007

AbstractA method has been developed for simultaneously comparing the usefulness of many treatments of established value for symptomatic medical conditions. Medical assessment of outcome is not employed. Instead patients are required to assess treatments prescribed during the course of ordinary general practice rather than under the strictly controlled settings of most clinical trials. Outcome incorporates patient compliance and treatment acceptability and is based on patients' subjective judgements of the usefulness of randomly allocated treatments as recorded in self‐completed diaries, which are mailed directly to a trial centre. Thus large and more representative samples are achieved through minimizing the efforts required, both of participating doctors and of patients. Although the approach was originally developed and tested for the comparison of hay fever treatment regimens, we believe that it can be adapted to compare many other treatments where patient‐reported symptoms validly describe the outcome of interest. The feasibility of the approach was tested in two pilot studies, and it has been employed successfully in a two‐year trial comparing seven hay fever treatments. Aspects of analysing such trials are discussed.
Dynamic evaluation of short‐term prognosis after myocardial infarction
Authors: Hougaard Philip , Madsen Erling Birk 
Published: April 2007

AbstractThe risk of cardiac arrest, cardiogenic shock or death in the first 44 days after myocardial infarction is evaluated using a version of the Cox regression model. The (time‐dependent) covariates include complications that have occurred, making it possible to give an individual assessment of prognosis that can be updated each day.Low risk patients can be discharged from hospital after a few days, whereas high risk patients must remain in hospital until their risk has fallen to an acceptable level. For the former group of patients it is possible to reduce the number of days in hospital without increased mortality and for the latter group mortality can be reduced by longer hospitalization.
The bootstrap and identification of prognostic factors via cox's proportional hazards regression model
Authors: Chen Chen‐Hsin , George Stephen L. 
Published: April 2007

AbstractThis paper describes the use of the bootstrap,1,2a new computer‐based statistical methodology, to help validate a regression model resulting from the fitting of Cox's proportional hazards model3to a set of censored survival data. As an example, we define a prognostic model for outcome in childhood acute lymphocytic leukemia with the Cox model and use of a training set of 224 patients. To validate the accuracy of the model, we use a bootstrap resampling technique to mimic the population under study in two stages. First, we select the important prognostic factors via a stepwise regression procedure with 100 bootstrap samples. Secondly we estimate the corresponding regression parameters for these important factors with 400 bootstrap samples. The bootstrap result suggests that the model constructed from the training set is reasonable.
The effect of validation group bias on screening tests for coronary artery disease
Authors: Green Manfred S. 
Published: April 2007

AbstractThe exercise electrocardiogram (ECG) is frequently used as a screening tool for coronary artery disease (CAD) in epidemiological studies and routine health evaluation. Estimates of the validity of this diagnostic test have usually been obtained by correlating the exercise ECG with the results of coronary angiography. However, coronary angiography is usually performed only on selected individuals with symptomatic CAD. If symptomatic subjects are more likely to respond positively to the exercise ECG than asymptomatic individuals with comparable severity of disease, then biased estimates of the test validity for an unselected population may be obtained. In this paper the validation group bias is shown to be a function both of the proportion of the population with symptomatic CAD and of the relative validity of the test for the symptomatic and asymptomatic subjects. The extent of this bias is examined.