bluuebunny/crossref_metadata_2025_split huggingface dataset:
Time from infection with HIV to onset of AIDS in patients with haemophilia in the UK
Authors: Darby S. C. , Doll R. , Thakrar B. , Rizza C. R. , Cox D. R. 
Published: April 2007

AbstractThe two‐stage parametric regression model of Brookmeyer and Goedert has been adapted and fitted to data on the development of AIDS in haemophiliacs in the UK who are seropositive for HIV. The risk of developing AIDS by a given time following seroconversion increases with increasing age at seroconversion. It is likely that the risk increases smoothly with age, although the data have been analysed in three age categories, and it is estimated that by seven years after seroconversion 6 per cent of patients aged under 25 at seroconversion, 20 per cent of those aged 25–44 and 34 per cent of those aged 45 or more have developed AIDS. For a given age at seroconversion the annual risk of developing AIDS increases with increasing time after seroconversion, and at seven years the annual risks of developing AIDS during the next year in the three age groups are estimated to be 2 per cent for those aged less than 25 at seroconversion, and 10 and 11 per cent respectively for those aged 25–44 and 45 or more.
An application of density estimation to geographical epidemiology
Authors: Bithell J. F. 
Published: April 2007

AbstractA relative risk function over a geographical region is defined and it is shown that it can be estimated effectively using kernel density estimation separately for the spatial distribution of disease cases and for a sample of controls. This procedure is demonstrated using data on childhood leukaemia in the vicinity of the Sellafield nuclear reprocessing plant in Cumbria, U.K. Various modifications to the method are proposed, including the use of an adaptive kernel. The final plot demonstrates a sharp peak at Sellafield and a reasonably smooth surface over the rest of the region, despite the small number of cases in the series.
Statistical analysis of quality of life data in cancer clinical trials
Authors: Olschewski M. , Schumacher M. 
Published: April 2007

AbstractIn clinical trials endpoints other than total and/or disease‐free survival are gaining more and more interest. In particular, quality of life (QOL) or the well‐being of patients has emerged as a synonym for variables describing the subjective reactions of patienis towards their disease and its treatment. The statistical analysis of such QOL data is complicated firstly by the large number of variables measured and their obvious lack of objectivity. The construction of suitable aggregate measures allowing a reduction of the measurements into a (preferably) unidimensional index are discussed in the context of an analysis at a fixed time point during the course of treatment. A second problem arises from the consideration that a patient's well‐being is subject to changes over time. We discuss the modelling of QOL by suitable stochastic processes which are extensions of a multistate disease process. This allows QOL events to be incorporated into methods of survival analysis by either estimating the relevant transition probabilities between states or calculating quality‐adjusted survival times. Finally, some brief guidelines for the planning of clinical trials including QOL measurements will be proposed.
Applications of global statistics in analysing quality of life data
Authors: Tandon P. K. 
Published: April 2007

AbstractQuality of life (QOL) instruments usually consist of a number of components, each of which deals specifically with a particular functionally related dysfunction. In a clinical trial whose primary aim is the evaluation of the treatment by means of QOL instruments, analysis of each of the components usually consists of either univariate analysis of variance (ANOVA) or some non‐parametric methods. This multiple testing approach can produce an increase in false positive findings. One attempt to correct for this is the Bonferroni adjustment. Another approach is to apply global statistics (parametric or non‐parametric) for the null hypothesis of no treatment difference versus the alternative hypothesis that one treatment is uniformly better than the other for QOL instruments as a whole.Data from a randomized double‐blind trial of 111 congestive heart failure patients, which involved four QOL instruments, were analysed with univariate ANOVA, Bonferroni adjustment, parametric and non‐parametric global statistics. The global statistics complemented the univariate methods and made the presentation of QOL data very effective. I recommend the general use of global statistics in analysis of QOL data.
A two‐step method for understanding and fitting growth curve models
Authors: Stanek Edward J. 
Published: April 2007

AbstractWith data from a repeated measures design, analysts often overlook growth curve analysis based on the Potthoff‐Roy model. The reluctance to perform a growth analysis may result partially from unfamiliarity with the technique, and partially from the lack of readily available computational programs to fit the models. Although growth curve analysis has traditionally appeared as a special technique in multivariate analysis, one can fit the models with the use of two simple ideas: transformation of variables, and weighted least squares (WLS). When presented in this manner, growth models are a natural extension of univariate repeated measures models. Growth curve analyses share with univariate analyses the common objective to limit estimation to a parsimonious set of parameters that characterize the response profiles. One can readily fit models with commonly available software. The two‐step methodology also allows the fit of more general growth models that are appropriate when groups have different shape profiles. Two examples illustrate this approach to growth curve analysis.
Historical and methodological developments in clinical trials at the national cancer institute
Authors: Gehan Edmund A. , Schneiderman Marvin A. 
Published: April 2007

AbstractThe first randomized clinical trial at the National Cancer Institute (NCI), planned in 1954, commenced in 1955 for the treatment of patients with acute leukaemia. The programme in clinical trials at NCI had strong influence from the clinician and administrator, C. Gordon Zubrod, who introduced the randomized clinical trial at NCI and organized the co‐operative clinical trials programme of the Cancer Chemotherapy National Service Center (CCNSC) beginning about 1955. The biostatistician, Marvin Schneiderman, collaborated on the first randomized trials in acute leukaemia and solid tumours and recruited the biostatisticians and statistical centres in the early phase of the co‐operative clinical trials programme of the CCNSC. From the beginning, there was acceptance of the principles of the randomization of patients and the statistical analysis of data. The sequence of clinical trials for a new agent included the non‐randomized phase I (dosage finding) and phase II (preliminary efficacy) trials as well as the phase III (comparison of treatments) trials. New concepts for the treatment of patients developed from 1955 to the mid‐1960s included the combination of therapies with independent activity to increase response rates and the administration of therapy to patients in a disease‐free (remission) state to prolong the disease‐free state. Methodological developments related to clinical trials up to the mid‐1960s included: a plan for phase II trials (Gehan10); a generalization of the Wilcoxon test for the comparison of survival distributions with right‐censored data (Gehan25); a test of proportional hazards for survival distributions, which later became known as the Mantel‐Haenszel test (Mantel38), and an exponential regression model with an explanatory variable (Feigl and Zelen41).
Application of the triangular test to phase II cancer clinical trials
Authors: Bellissant Eric , Benichou Jacques , Chastang Claude 
Published: April 2007

AbstractPhase II cancer clinical trials are primarily designed to determine whether the response rate p to the treatment under study is greater than a specified value p0, that is to test the null hypothesis H0: p < p0 against an alternative hypothesis H1: p > p0 specified by p = p1. As an alternative to the single and multistage procedures and to Wald's continuous sequential probability ratio test (SPRT), we applied the group sequential methods proposed by Jones and Whitehead, namely the triangular test (TT) and the discrete SPRT, to the comparison of p with p0, and we expressed H0 and H1 in terms of the log odds‐ratio statistic log [p(1 — p0)/Po(1 — p)]. A simulation study showed that both the TT and the discrete SPRT had type I error and power close to the nominal values, and they compared favourably with multistage methods in terms of the average sample size.
The measurement of change of quality of life in clinical trials
Authors: Zwinderman Aeilko H. 
Published: April 2007

AbstractA model is presented for the measurement of change of quality of life in clinical trials with time under the influence of one or more treatments. Quality of life is regarded as a multidimensional latent variable, and is measured through dichotomous item responses on a number of points in time. Change of quality of life is ‘explained’ with a latent logistic regression model which may include parameters for the time process, the effects of clinical treatments, and interaction parameters. By assuming the absence of patient/time interaction within treatment groups, the parameters of the time process and the treatment effects can be estimated independently of the latent quality of life parameters at the start of the treatment. Consequently, differential mortality, censoring mechanisms, and other mechanisms causing missing data can be ignored.
What statistics should we teach medical undergraduates and graduates?
Authors: Appleton Davi D. R. 
Published: April 2007

AbstractIt is suggested that the emphasis on teaching statistics to medical undergraduates has usually been quite wrong: that the courses have become much too long, too detailed, and irrelevant to the needs of the majority. Examples are given which may help to introduce the basic concepts which all medical (and dental) undergraduates require, and which form a basis for the more traditional teaching of analytical methods to the appropriate subset who proceed to undertake medical research.
Who should teach medical statistics, when, how and where should it be taught?
Authors: Clayden A. David 
Published: April 2007

AbstractAs far as we can tell, there is no single answer to any of these questions. This paper describes some of the approaches adopted in the teaching of medical statistics in the U.K. medical schools. It is suggested that collaboration between non‐statistically qualified teachers and medical statisticians is beneficial, with an emphasis in the application of statistical principles to interesting and ‘relevant’ medical topics. A block of ‘laboratory based’ teaching in the early years may be followed by occasional, clinically focused sessions later in the undergraduate course. Research oriented courses, made available when postgraduates have a real and pressing need for information, are thought likely to be most valuable and rewarding for students and statisticians. It is thought that the use of information technology to improve the communication of concepts and ‘facts’ during lectures, and for ad hoc enquiries by students, is likely to make the most of the limited teaching resources. The future is thought to be in the greater use of small group or individualized teaching which confirms or tests the knowledge gained from students use of I.T. supported activities. Unless lecturers collaborate in evaluative studies which compare different teaching methods, it will never be possible to provide valid generalizable advice to teachers of medical statistics.
Statistics for medical students in the 1990's: How should we approach the future?
Authors: Evans Stephen J. W. 
Published: April 2007

AbstractMedical statistics teaching in the U.K. has moved over the past twenty years from needing justification to acceptability. In the future teachers need to involve statistical and medical colleagues to improve the content and presentation of their material. While some techniques must continue to be taught, the conceptual aspects of scientific evaluation and assessment will need to increase.
Statistical interim monitoring of the cardiac arrhythmia suppression trial
Authors: Pawitan Yudi , Hallstrom Alfred 
Published: April 2007

AbstractThe Cardiac Arrythmia Suppression Trial was stopped much earlier than planned. Statistical considerations played a very important role in the decision. Flexible group sequential testing was developed for the trial by implementing a Lan and DeMets procedure with use of the permutation test. We compute P‐values from the joint permutation distribution of the test statistics, so we do not need to estimate the sampling distribution which in general is rather difficult to do without strict assumptions. The method also gives an exact test for small samples and allows us to use more complicated or non‐Gaussian statistics. We also utilized stochastic curtailment ideas to evaluate various scenarios that might occur during the course of the trial, which assisted the Data and Safety Monitoring Board in making appropriate decisions.
Measuring interrater reliability among multiple raters: An example of methods for nominal data
Authors: Posner Karen L. , Sampson Paul D. , Caplan Robert A. , Ward Richard J. , Cheney Frederick W. 
Published: April 2007

AbstractThis paper reviews and critiques various approaches to the measurement of reliability among multiple raters in the case of nominal data. We consider measurement of the overall reliability of a group of raters (using kappa‐like statistics) as well as the reliability of individual raters with respect to a group. We introduce modifications of previously published estimators appropriate for measurement of reliability in the case of stratified sampling frames and we interpret these measures in view of standard errors computed using the jackknife. Analyses of a set of 48 anaesthesia case histories in which 42 anaesthesiologists independently rated the appropriateness of care on a nominal scale serve as an example.
Adjusting for age‐related competing mortality in long‐term cancer clinical trials
Authors: Cheuvart B. , Ryan L. 
Published: April 2007

AbstractMortality related to causes other than the treated disease may have a significant impact on overall survival in long‐term clinical trials. We present a model that adjusts for age‐related competing mortality when cause of death is missing or only partially available. Through use of a piecewise exponential survival model, we extend relative survival methods to continuous follow‐up data, allowing the competing mortality to differ from that of the general population by a scale parameter. An EM algorithm provides a simple way to compute the maximum likelihood estimators (MLEs) and to test hypotheses using widely available software. We compare the bias and relative efficiency of this model to a piecewise exponential Cox model for overall survival. Theoretical results are confirmed by simulations and illustrated with data from a clinical trial in colorectal cancer. This example also shows how age‐related and disease‐related mortality can be confounded in an analysis of overall survival. We conclude with a discussion of the advantages and dis‐advantages of the model.
Estimability and estimation of expected years of life lost due to a hazardous exposure
Authors: Robins James , Greenland Sander 
Published: April 2007

AbstractExpected years of life lost is an important concept in public‐health and legal issues. We describe conditions under which the expected years of life lost due to hazardous exposure is estimable (identifiable) from epidemiologic data. We show that, in general, the average years of life lost among exposed subjects dying at a given age (the age‐specific expected years of life lost) is not identifiable, although the average years of life lost among all exposed subjects (the unconditional expected years of life lost) is identifiable from an unbiased epidemiologic study. We also show that the average years of life lost among all exposed subjects dying of a specific cause (the cause‐specific expected years of life lost) is not identifiable. We discuss the implications of these results for compensation schemes based on years of life lost, and compare such schemes with those based on the probability of causation.
Behavioural and biological determinants of fertility transition in sub‐saharan Africa
Authors: Frank Odile , Bongaarts John 
Published: April 2007

AbstractIn the transition from high to low fertility, different biological and behavioural proximate determinants play roles of varying importance in mediating the change. In most regions of the world, the practice of contraception has come to play the major role, so much so that there is a close relationship worldwide between the level of practice of contraception and the level of fertility. In sub‐Saharan Africa, the prevalence of contraceptive practice is low, and fertility levels are exceptionally high for recorded levels of contraceptive practice, even where levels of contraceptive practice are comparable to other regions. The discrepancies are explained to a very large extent by differences between Africa and other regions in other proximate determinants‐notably exposure to the risk of pregnancy, and abstinence after delivery. It would seem that transition in African countries will follow one of two patterns that are different to the pattern of transition observed in all other regions. First, fertility may rise before it declines, due to abandonment of traditional fertility regulation for some time prior to the eventual adoption of contraceptive practice. Second, the prevalence of contraceptive practice may rise for a time before there is an observable decline in fertility, because at the same time that contraception is adopted, traditional regulation of fertility is being abandoned, offsetting any effect on fertility. Kenya is an example of the first pattern, while Botswana, Ghana, and Zimbabwe are probably examples of the second.
The description of menstrual bleeding patterns: Towards fewer measures
Authors: Belsey Elizabeth M. , Carlson Nancy 
Published: April 2007

AbstractThe disturbance in menstrual bleeding induced by many methods of contraception is an important factor in their acceptability, and women participating in clinical trials of new methods are usually asked to keep a calendar record of the occurrence of bleeding. A recent WHO report recommends that, for analysis and presentation, each menstrual diary should be divided into successive periods, and the woman's bleeding pattern in each period summarized in ten indices. These indices are simple to calculate and easily understood by clinicians, but comparison of several groups is problematic because of the large number of summary statistics generated.Principal components analysis was therefore used to determine whether the indices could be reduced to a smaller number of measures. The analyses showed that three of the indices ‐ the range and maximum value of bleeding/spotting episode lengths and the minimum bleeding‐free interval ‐ rarely measure their intended dimension of the bleeding pattern. Most of the essential information about a woman's bleeding pattern is contained in only four of the ten indices: the number of bleeding/spotting episodes, the mean lengths of episodes and intervals, and the range of bleeding‐free interval lengths. Together, these indices describe the most important dimensions of a pattern: the amount, frequency and variability of the bleeding.
Estimation of the spontaneous abortion risk in the presence of induced abortions
Authors: Hilden J. , Modvig J. , Damsgaard M. T. , Schmidt L. 
Published: April 2007

AbstractWe propose a method of estimating the miscarriage risk in a setting where counts of births, miscarriages and induced abortions are available, and also the gestational week of each induced abortion. Unlike previously proposed methods, ours takes into account the fraction of the miscarriage risk to which each interrupted pregnancy has been exposed. For this purpose, we draw on an extraneous standard foetal survival curve and stipulate that the survival curve of the study population is a scaled version thereof. Three such scaling models are discussed, and it is shown that the choice is largely a matter of computational convenience. Separate attention is given to a competing‐risk model of miscarriages and interruptions, and examples are given of reasons why the crucial assumption that these two sources of termination operate independently is unlikely to be met. Finally, it is argued that pregnancy wishes, especially those of habitual aborters, shape the miscarriage rate to the extent that it becomes as much a cultural parameter as a marker of biological hazards.
A simulation study comparing designs for dose ranging
Authors: Sheiner Lewis B. , Hashimoto Yukiya , Beal Stuart L. 
Published: April 2007

AbstractOnly with knowledge of the (prior) distribution of dose‐response parameters in a population, can one determine both the initial dose of a drug for chronic administration to an individual (such as the dose producing a fixed degree of response in a fixed proportion of the population) and an appropriate subsequent (adjusted) dose (such as the dose yielding a desirable response according to the posterior parameter distribution, given an observed response to an initial dose).The currently FDA‐sanctioned design for a dose‐ranging study, the parallel‐dose design, assigns just one of several doses to each patient. It does not provide good information on the distribution of individual dose‐response parameters. A cross‐over design assigns several dose levels to each patient. It therefore can provide better information, but does not resemble clinical practice. Consequently, study participants must be restricted to patients who can tolerate such non‐therapeutic drug exposure, posing problems in extrapolation of study results to other types of patients. A titration or dose‐escalation design begins all patients on placebo and, except for those patients assigned to a placebo‐only group, escalates the dose for a patient at preset intervals only when clinical response at lower doses is inadequate. It both exposes patients to several dose levels and resembles good clinical practice, allowing study of a representative patient sample.We report here the simulation results of parameter estimation for the three designs when the data arise from complex and realistic dose‐response models and/or with certain complications in study execution. The dose‐escalation design clearly performs better overall than the parallel‐dose design for the models considered here, and generally, just a little worse than the cross‐over design. These results support the conclusion that for dose ranging, depending on the demands of the clinical situation, one should use either the cross‐over or the dose‐escalation design.
A model for the identification of hormone pulses
Authors: Kushler Robert H. , Brown Morton B. 
Published: April 2007

AbstractSeveral hormones are released into the blood in a pulsating manner, that is, in short bursts which cause a rapid increase in the circulating concentration. The concentration then declines due to excretion, chemical breakdown, and redistribution into other compartments. Based on a series of observations of the level of hormone in the blood, investigators desire to quantify characteristics of these pulses, that is, timing, amplitude and rate of decay. We describe a statistical model for hormone pulse data and introduce a new method for estimating the characteristics of the pulses.