bluuebunny/crossref_metadata_2025_split huggingface dataset:
The probability of inevitability: The inherent impossibility of validating criteria for brain death or ‘irreversibility’ through clinical studies
Authors: Shewmon D. Alan 
Published: April 2007

AbstractA great need persists for diagnostic criteria for both brain death in young children and irreversible loss of consciousness at all ages. This article examines the inferences derived from a hypothetical confirmatory study in which all of the N patients who fulfilled the criterion did in fact experience brain death (irreversibility). A Bayesian methodology proves that, for N in the range of a large clinical study, estimations of prior probabilities are, for all practical purposes, irrelevant to the calculation of the posterior probabilities. The risk of a false positive diagnosis for the next patient who meets the criterion is approximately 1/(N + 2). The chance of at least one false positive diagnosis among the next (N + 1) patients who meet the criterion is around 50 per cent. Thus, achievement of the requisite moral certainty of a declaration of death (irreversibility) necessitates an impossibly large N for the study. This does not mean that one cannot diagnose death, but rather that the validity of the diagnostic criteria must be self‐evident on a priori grounds, and that confirmatory studies are necessarily either inadequate or superfluous.
Multiple comparisons for relative risk regression: Extension of the k‐ratio method
Authors: Dixon Dennis O. , Divine George W. 
Published: April 2007

AbstractWe propose a k‐ratio method for multiple comparisons among disjoint groups in survival analysis, specifically among relative risk estimates from a proportional hazards regression analysis. The new method relates the magnitude of critical values to an overall measure of group heterogeneity. That is, large critical values result from small values of a chi‐square statistic for testing between‐groups homogeneity. Conversely, large values of the overall statistic lead to small critical values for individual comparisons, even if there are many groups. The adaptivity of the k‐ratio method contrasts sharply with the conservatism of competing methods.
Monitoring distributional assumptions and early stopping for a prospective clinical trial using Monte Carlo simulation
Authors: Gebski Val , McNeil Don , Coates Alan , Forbes John 
Published: April 2007

AbstractWe have applied the technique of Monte Carlo simulation to the determination of sample size for a partially completed clinical trial of chemotherapy for breast cancer. Simulations based on results observed after the entry of 243 patients in 2 years indicated a power greater than that predicted by the calculations made before the protocol was activated, and allowed a recommendation for an eventual trial closure earlier than would have been permitted by traditional methods. Both estimative and predictive approaches to the simulation of expected survival times for censored patients are presented. The use of simulation is recommended as an aid in reassessing the exact nature of the underlying survival distributions (as these affect the sample size calculations) and in optimizing stopping rules relating to patient accrual to a clinical trial in progress.
Variance estimators for attributable fraction estimates consistent in both large strata and sparse data
Authors: Greenland Sander 
Published: April 2007

AbstractA number of variance formulae for the attributable fraction have been presented, but none is consistent in sparse data, such as found in individually matched case‐control studies. This paper employs Mantel–Haenszel estimation to derive variance estimators for attributable fractions that are dually consistent, that is, consistent in both sparse data and large strata. The method may also be applied using conditional maximum likelihood. Extensions of these estimators to situations involving effect modification and preventive exposures are also derived. Examples of applications to individually matched case‐control studies are given.
Age, period and cohort analysis of trends in mortality from major diseases in Japan, 1955 to 1979: Peculiarity of the cohort born in the early Showa Era
Authors: Tang Toshiro , Kurashina Shiusuke 
Published: April 2007

AbstractJapanese researchers have reported that recent mortality rates from diabetes mellitus, ischemic heart disease, peptic ulcer, cirrhosis of the liver and suicide for middle‐aged Japanese men have increased by comparison with those for other age groups. There has been some controversy over the etiology of this unusual trend, and in particular whether it is due primarily to recent undesirable socio‐economic factors (period effects) or to factors specific to these cohorts born in the early Showa Era, around 1925 to 1940 (cohort effects). A possible source of this controversy lies in the methods which have been used to describe the trends; these are mostly descriptive and graphical.To elucidate which factors are responsible for these trends, we analysed the mortality data quantitatively applying an age‐period‐cohort model modified so that period effects remain constant within certain age groups but may vary from one age group to the next. Although the identifiability problem still occurs in the modified model, estimable curvature components of time effects may be used to examine these unusual trends. In fact, the peculiarity of the cohort born in the early Showa Era was clearly detected by the curvature components of cohort effects for these major diseases. These findings are consistent with the ‘cohort hypothesis’ for the recent peculiar trend in Japanese male mortality.
Meta‐analysis of clinical trials as a scientific discipline. II: Replicate variability and comparison of studies that agree and disagree
Authors: Chalmers Thomas C. , Berrier Jayne , Sacks Henry S. , Levin Howard , Reitman Dinah , Nagalingam Raguraman 
Published: April 2007

AbstractThe replicate variability of meta‐analyses of controlled clinical trials has been assessed as a measure of scientific precision. 46 of 91 known meta‐analysis papers were divided into 20 cohorts of studies of the same therapies. Ten cohorts contained meta‐analyses with different statistical conclusions; 14 contained differing clinical conclusions with a wider spread than the statistically differing studies. Possible causes of variability, such as different trials included, different policies regarding the inclusion of non‐randomized and unpublished trials, and different statistical methodologies, were not obvious causes of differing conclusions. Further work in this area should include multivariate analyses in order to explore possible interactions in the factors accounting for the variability found in replicate meta‐analyses.
A method of analysis taking into account competing events: Application to the study of digestive complications following irradiation for cervical cancer
Authors: Kramar Andrew , Pejovic Marie‐Hélène , Chassagne Daniel 
Published: April 2007

AbstractOver the past 20 years, mortality rates from uterine cervix carcinoma have been decreasing owing to earlier diagnosis and improved treatment. The incidence of secondary effects from radiation therapy has spurred some interest and injuries resulting from ‘over’‐treatment have been of some concern. The present study concerns the evaluation of bowel complications following treatment for the 272 stage IIb and III patients treated in our centre between 1967 and 1973. Competing risk methodology is applied and the influence of radiotherapy parameters is evaluated by a log‐linear model of the event‐specific failure rates. A single parameter (NSD) which summarizes total dose, total number of sessions and total treatment time is found to be related to the occurrence of complications.
A probability‐based aid for teaching medical students a logical approach to diagnosis
Authors: Crichton Nicola J. , Emerson Peter A. 
Published: April 2007

AbstractIn this paper we present a method of teaching medical students a logical approach to diagnosis. By using the independent Bayes method, commonly employed in decision aids, students can be made aware of how information on each new symptom affects what is likely in the light of what is known already. This approach is used for the diagnosis of thoracic symptoms in patients with normal chest X‐rays and an example is given. Extensions of the system to incorporate information from investigations and error costs are discussed.
Designing a study for evaluating a protocol for the selective performance of preoperative tests
Authors: Charpak Yves , Bléry Christian , Chastang Claude 
Published: April 2007

AbstractSome basic concepts concerning classification of studies evaluating diagnostic procedures are given. The specific problem of assessment of routine preoperative tests is discussed: actual knowledge and methodological criticisms of previous studies, hypothesis for further evaluations, difficulties in the choice of a design and realization of a clinical study to assess a protocol for selective ordering of preoperative tests during one year in a teaching hospital. 3866 consecutive patients were included. The protocol led to perform only 33 per cent of all potential tests and did not apparently produce major adverse effects on the quality of care as appreciated by a clinical decision analysis.
Predicting the dynamic effects of rubella vaccination programmes
Authors: De Boo Th. M. , Van Druten J. A. M. , Plantinga A. D. 
Published: April 2007

AbstractIn the Netherlands, prepubertal girls have been vaccinated against rubella since 1974 (the UK strategy). Recently the Dutch Health Council advocated the introduction of an elimination strategy: vaccination of 1‐and 9‐year‐old children. Dynamic effects of both strategies are studied using deterministic and stochastic models. Estimates of several epidemiological parameters are given. All computations and simulations were performed using as much field data as possible. Under the old strategy a new equilibrium is expected around the years 1995 to 2000; the new strategy is estimated to eliminate rubella (CRS) in large parts of the population 3 to 5 years after its initiation. Possible consequences of the new strategy on a cluster of people who refuse vaccination are investigated.
Modelling the effect of intervention on the transmission of malaria in east malaysia
Authors: Collett D. , Lye M. S. 
Published: April 2007

AbstractTo assess the public health importance of malaria on Banggi Island, Sabah, baseline epidemiological and entomological data were obtained in a study of three villages. These data were used to model the transmission of malaria using a non‐seasonal version of the deterministic model of Dietz, Molineaux and Thomas. The model provided a satisfactory description of prevalence rates of Plasmodium falciparum parasitaemia. Modifications to the basic model enable the effects of mass chemotherapy with various combinations of schizonticidal and gametocidal drugs to be simulated. In this way, the relative merits of different procedures of mass drug administration can be compared. The fitted model is also used to examine the relationship between the overall prevalence of infection and the vectorial capacity, and to predict the consequences of a reduction in the size of the vector population.
Using the adverse reactions register to study the effects of age and sex on adverse drug reactions
Authors: Simpson Judy M. , Bateman D. N. , Rawlins M. D. 
Published: April 2007

AbstractMany countries maintain a register of reports of adverse reactions to drugs. Although reports are made voluntarily by doctors and dentists these registers contain much information that may be useful in pharmacoepidemiological studies. We show how the epidemiology of adverse drug reactions (ADRs) can be studied using data from such a register, together with estimates of the numbers of prescriptions of the drug, categorized by age and sex of the patient. Reporting rates of ADRs are compared for different ages and sexes by logistic analysis, using extrapyramidal reactions to metoclopramide as an example. Highly significant effects of sex and age on reporting rates are found, with young women being most at risk. We consider possible alternative explanations of this finding, and show that relative overdosage does not account for the differences between the age and sex groups. Other possible errors in the data are also considered unlikely to alter these conclusions; these include differential bias in reporting ADRs for various age‐sex groups, and errors in the prescription data. Studies based on the adverse reactions registers are useful for formulating hypotheses which can be tested in a prospective study.
The Cardiff health survey: Teaching survey methodology by participation
Authors: Lewis P. A. , Charny M. 
Published: April 2007

AbstractMedical students were taught survey methodology by participating in all phases of a large community survey. The survey examined health beliefs, knowledge and behaviour in a sample of 5150 people drawn from the electoral register of the City of Cardiff. The study achieved several educational objectives for the medical students: they met well people in their own homes and had an opportunity to get to know a community; by taking part in a study from the initial phases to the conclusion they could appreciate the context of the theoretical teaching they were being given concurrently in their undergraduate course; they learnt to analyse raw data and produce reports; and they gained insights into the health knowledge, behaviour, attitudes and beliefs of a population. In addition, the survey produced a substantial quantity of valuable data which staff and students are analysing and intend to publish.
Evaluating the survival of cancer cases detected by screening
Authors: Walter S. D. , Stitt L. W. 
Published: April 2007

AbstractEarly detection of cancer by screening advances the date of diagnosis, but may or may not affect survival. To assess the survival benefit associated with early detection, one must estimate the distribution of time survived post lead‐time, that is, after the unknown date when clinical diagnosis would have occurred in the absence of screening. One can then compare the adjusted survival of screen‐detected cancer cases to other groups of cases not diagnosed by screening. This paper describes a model for the survival of screen‐detected cases, with a hazard function that depends on an individual's lead time, the duration of preclinical disease, and the time since diagnosis. The model is fitted to the ten year survival data from the 132 screen‐detected cases of breast cancer in the well‐known HIP (Health Insurance Plan of Greater New York) study. Comparison with the survival of several groups of cancer cases not detected by screening (interval cases arising clinically in persons previously screened, cases among persons who refuse screening, and cases among randomized controls not offered screening) yields various estimates of benefit. Use of the interval cases for comparison gives an estimate of about 21 breast cancer deaths prevented among 20, 166 women screened in the HIP study; use of the data from the randomized controls gives an estimate of about 25 prevented deaths. The former estimate derives from the screened group of women only, and so the same method of evaluation may also be applied to community screening programmes and other situations that do not entail randomization.
Early termination of clinical trials with prolonged observation of individual patients: A case study
Authors: Van Es Gerrit‐Anne , Tijssen Jan G. P. , Lubsen Jacobus , van Strik Roel 
Published: April 2007

AbstractStopping rules for a placebo controlled clinical trial of anticoagulants after acute myocardial infarction were evaluated by means of computer simulation for the case of five interim analyses. The trial will be terminated and the null hypothesis of no treatment effect rejected when the one‐sided P‐value (logrank test) is lower than 0.005, 0.005, 0.005, 0.014, and 0.023 at the respective interim analyses, and 0.032 at final evaluation. This implies a total size α = 0.05 and a power close to that of fixed sample size testing. The trial will also be terminated, without rejecting the null hypothesis, when the one‐sided P‐value exceeds 0.95, 0.88, 0.81, 0.74, and 0.67 at the respective interim analyses. This modification hardly affects size and power.
Improved estimates of discordance ratios in twin studies
Authors: Franti C. E. , Wiggins A. D. , Kraus J. F. 
Published: April 2007

AbstractIn the study of monozygotic twins relative to disease and risk factors, particular interest focuses on the subset who are discordant for some suspected risk factor (for example, smoking), since such twins constitute a natural case‐control pair. In such studies, questionnaires designed to identify the status of all twin pairs are sometimes error prone and can yield misleading estimates of the concordance‐discordance ratios. Greater efforts to verify the characteristics of apparently discordant pairs than to verify those of apparently concordant pairs can result in the ‘unequal ascertainment’ fallacy.Using the results of a questionnaire with known error rates and the ‘apparent’ frequencies yielded, we present unbiased, maximum likelihood estimates of the ‘true’ proportions of concordant and discordant pairs. We also present approximate covariances among these estimates.
A longitudinal view of blood pressure during childhood: The muscatine study
Authors: Lauer Ronald M. , Clarke William R. 
Published: April 2007

AbstractFour thousand three hundred and thirteen children beginning at five to fourteen years of age have been examined on three to six occasions in Muscatine, Iowa, on alternate years. To compare blood pressures throughout the period of observation each value was expressed as a percentile rank. For each subject the average percentile rank (level), the trend in rank and the variability over time were calculated. Values for height, weight, relative weight and triceps skinfold thickness measurements were expressed in the same fashion. There is a relationship between average rank of blood pressure and average rank of body size as well as between trend of blood pressure and trend of body size percentiles. These observations indicate the importance of relative rate of growth in the establishment of the rank order of blood pressure during childhood.
Autoregressive modelling for the analysis of longitudinal data with unequally spaced examinations
Authors: Rosner B. , Muǹoz A. 
Published: April 2007

AbstractMissing and/or unequally spaced examinations are often present in longitudinal studies. An autoregressive model is presented for the analysis of such data for continuous outcome variables. The fitting of the model can be accomplished by weighted non‐linear regression methods available in standard statistical packages. Some features of the model include consideration of both time‐dependent and fixed covariates, assessment of the relationships between changes in outcome and exposure over short periods of time, and use of all available person‐time for an individual. An illustration looking at the role of personal cigarette smoking on changes in pulmonary function in children is included.
Autoregressive growth curves and Kalman filtering
Authors: Wilson P. David 
Published: April 2007

AbstractThe first part of this paper describes how a Kalman filter can be used to construct maximum likelihood (ML) estimates of autoregressive (AR) and polynomial parameters in polynomial growth curves with AR‐1 errors and irregularly‐spaced data. The second part introduces a disturbed highest derivative polynomial (DHDP) as a model for growth curves. This model does not depend on regression coefficients. Variances of the highest derivative disturbance and the observation error are estimated (by ML) using a Kalman filter. The estimated DHDP growth curve is obtained by optimally smoothing the output of the filter. Equally spaced data is not required. The DHDP model and analysis are developed for an individual and extended to a population growth curve using data from many individuals with covariates.
Comparison of baseline and repeated measure covariate techniques in the Framingham heart study
Authors: Cupples L. Adrienne , D'Agostino Ralph B. , Anderson Keaven , Kannel William B. 
Published: April 2007

AbstractThe purpose of this paper is to indicate how repeated measures on risk factors have been employed in the prediction of the development of disease in the Framingham Heart Study. Since these measures vary over time, the method accounts for time dependent covariates. The technique is a generalized person‐years approach in that it treats each observation interval (of equal length) as a mini‐follow‐up study in which the current risk factor measurements are employed to predict an event in the interval. Observations over multiple intervals are pooled into a single sample to predict the short term risk of an event. This approach is compared to the long‐term prediction of disease which utilizes only the baseline measurements and ignores subsequent repeated measures on the risk factors.
Models of the interaction of mortality and the evolution of risk factor distribution: A general stochastic process formulation
Authors: Manton Kenneth G. , Woodbury Max A. , Stallard Eric 
Published: April 2007

AbstractGenerally analyses of longitudinal studies of chronic disease risks do not directly model the change with time of risk factor values and the interactions of those changes with risk levels. Failure to account for such process characteristics can lead to incorrect inferences about the specific effects of risk factors on mortality, the inability to accurately forecast the future risk of the cohort, and inaccurate statements about the effects of specific risk factor interventions on mortality. We present a model which does describe such a process and show how it can be estimated from longitudinal studies. We also illustrate the effects of certain risk factor process features on the evolution of disease risk data from males in the Framingham, Massachusetts study.
Analysis of incomplete multivariate data using linear models with structured covariance matrices
Authors: Schluchter Mark D. 
Published: April 2007

AbstractIncomplete and unbalanced multivariate data often arise in longitudinal studies due to missing or unequally‐timed repeated measurements and/or the presence of time‐varying covariates. A general approach to analysing such data is through maximum likelihood analysis using a linear model for the expected responses, and structural models for the within‐subject covariances. Two important advantages of this approach are: (1) the generality of the model allows the analyst to consider a wider range of models than were previously possible using classical methods developed for balanced and complete data, and (2) maximum likelihood estimates obtained from incomplete data are often preferable to other estimates such as those obtained from complete cases from the standpoint of bias and efficiency. A variety of applications of the model are discussed, including univariate and multivariate analysis of incomplete repeated measures data, analysis of growth curves with missing data using random effects and time‐series models, and applications to unbalanced longitudinal data.