bluuebunny/crossref_metadata_2025 huggingface dataset:
Proteomic investigation of glucose metabolism in the butyrate‐producing gut anaerobe Fusobacterium varium
Authors: Potrykus Joanna , Mahaney Brandi , White Robert L. , Bearne Stephen L.
Published: April 2007

A proteome survey and MS analysis were conducted to investigate glucose metabolism in Fusobacterium varium, a butyrate‐producing constituent of the indigenous human gut microflora. The bacterium was capable of catabolizing glucose as the main energy source via the Embden–Meyerhof–Parnas pathway. 2‐DE analyses revealed that the apparent concentrations of the six identified glycolytic enzymes (pyruvate kinase, enolase, glucose‐6‐phosphate isomerase, phosphoglycerate kinase, triosephosphate isomerase, and glyceraldehyde‐3‐phosphate dehydrogenase) were specifically increased in response to the presence of glucose in the chemically defined minimal growth medium, and did not diminish when the medium was additionally supplemented with L‐glutamate, an amino acid readily fermented by members of the Fusobacterium genus. A substrate pool depletion study revealed that the sugar, and not the amino acid, is the more efficient growth substrate. Both proteomics and substrate pool depletion studies revealed that F. varium can simultaneously utilize both glucose and L‐glutamate as energy sources. Enzymes involved in L‐glutamate metabolism were also identified, including an NAD‐dependent glutamate dehydrogenase and two enzymes of the methylaspartate pathway of L‐glutamate catabolism (glutamate mutase and methylaspartate ammonia‐lyase). Their apparent intracellular concentrations were elevated when the bacterium was cultured in media supplemented with excess L‐glutamate. Our observation that the apparent concentrations of specific proteins were elevated in response to a particular growth substrate supplied as an energy source provides the first evidence for the presence of a nutrient‐responsive mechanism governing intracellular protein concentration in F. varium.
A review of distress and its management in couples facing end‐of‐life cancer
Authors: McLean Linda M. , Jones Jennifer M.
Published: April 2007

The aim of this review paper is to (1) provide an overview of the impact of cancer on the couple, (2) to identify potential outcomes for couple's interventions targeted specifically when one spouse is facing end of life, (3) to review and critique the empirical literature on psychosocial interventions for couple's facing end of life to date, and (4) to provide direction for research in this area. Based on our review, we found that there is clear evidence of significant distress arising from the impact of terminal illness on the marital relationship, which can result in greater suffering in the last months and weeks of life. Currently, there is a very small body of evidence on the effectiveness of couple interventions for those where one is in palliative care. Future randomized controlled trials are needed to examine the impact of couple therapy adapted for couples facing the end of life, and to guide in providing information on the number of sessions and format required for this population. Outcomes, such as more effective communication, reduction in the experience of hopelessness, uncertainty, isolation, depression, anxiety, and more adaptive coping strategies should be considered. Copyright © 2007 John Wiley & Sons, Ltd.
An explicit demonstration of integrability for the linear Heisenberg chain of N = 9 nodes
Authors: Topolewicz Stanislaw , Lulek Tadeusz
Published: April 2007

We propose the system of N – 1 = 8 mutually commuting operators which classify all eigenstates of the Heisenberg Hamiltonian for the linear magnetic chain of N = 9 nodes, each with the spin 1/2. These eigenstates, determined exactly by Bethe Ansatz and classified combinatorially by rigged string configurations of Kerov, Kirillov and Reshetikhin, can be also associated with the spectrum of this set of commuting operators. (© 2007 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)
Nitride emitters go nonpolar
Authors: Schwarz Ulrich T. , Kneissl Michael
Published: April 2007

The Expert Opinion is written by distinguished scientists and presents their personal view on important and relevant new results of research, highlighting their significance and putting the work into perspective for a broader audience. Please send comments to pss.rapid@wiley‐vch.de or to the authors.

The text by Ulrich T. Schwarz and Michael Kneissl refers to the Rapid Research Letter by K. C. Kim et al., published in this issue of phys. stat. sol. (RRL) 1, 125 (2007). (© 2007 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)
Matrix‐assisted laser desorption/ionization on‐target method for the investigation of oligosaccharides and glycosylation sites in glycopeptides and glycoproteins
Authors: Lattová Erika , Chen Vincent C. , Varma Sonal , Bezabeh Tedros , Perreault Hélène
Published: April 2007

The significance of glycoproteins in living systems instigates the ceaseless expansion of new techniques and procedures for the analysis of biological samples. Many of these applications are focused on improving the detection limit of analyzed material. In a previous study, we described a procedure for the detection of oligosaccharides cleaved from tryptic glycopeptides. Treatment of deglycosylated fractions with phenylhydrazine gave rise to peaks consistent with labeled glycans, and both types of compounds—deglycosylated peptides and oligosaccharides—were recorded from one spot and observed in one matrix‐assisted laser desorption/ionization (MALDI) mass spectrum for the first time. Here, we added an additional step to this simple procedure of deglycosylating glycopeptides directly from the target spot of the first analyzed glycosylated peptides. For the purpose of this new study, a mixture of 2‐aza‐2‐thiothymine and phenylhydrazine hydrochloride showed to be an excellent matrix for glycopeptides, oligosaccharides, deglycosylated peptides and moreover it allowed PNGaseF to be active enough to cleave oligosaccharides from peptides. The efficiency of this procedure is demonstrated on a series of intact glycoproteins and on the analysis of tryptic peptides obtained from IgG and total mouse serum. This one‐step on‐target deglycosylation method with subsequent derivatization on the same spot makes MALDI‐MS analyses of glycopeptides fast, simple and accessible for biological samples, where classical procedures cannot produce useful results. Copyright © 2007 John Wiley & Sons, Ltd.
The value of aids incidence data in assessing the spread of HIV infection
Authors: de Gruttola Victor , Lagakos Stephen W.
Published: April 2007

Changes over time in the cumulative number of cases of AIDS depend in a complex way on several features of the epidemic, including the distribution of the induction time between infection with the human immunodeficiency virus (HIV) and onset of symptoms of AIDS, heterogeneity in such behaviours as sexual practices, selection of partners, and IV drug use, and changes over time in these behaviours. Consequently, the observed increase in the doubling time in cumulative AIDS incidence from 5 to 13 months, since AIDS was first recognized in 1982, demonstrates neither that the epidemic has begun to ‘run its course’ nor that behavioural changes have had a major impact in reducing incidence. Even in a homogeneous population with known induction distribution, AIDS incidence data currently are of little value in determining the number of persons infected with HIV unless additional information is available about the shape of cumulative incidence curve of HIV infection.
Some stochastic models of AIDS spread
Authors: Tan W. Y. , Hsu H.
Published: April 2007

In this paper we propose a stochastic model for the AIDS spread in a homosexual population. The probability generating function (PGF) of the numbers of latent persons, infective persons and AIDS cases is derived. By using the PGF, it is shown that the expected numbers and variances and covariances of these persons satisfy some ordinary differential equations. These equations have been solved numerically to assess effects of various factors on AIDS spread.
Required duration and power determinations for historically controlled studies of survival times
Authors: Emrich Lawrence J.
Published: April 2007

This paper provides power formulae for historically controlled studies with survival time endpoints, and considers two designs. The first design involves no further follow‐up of control group subjects; the second design involves collection of additional information on control group subjects who had not failed at the time of design of the prospective portion of the study. The power functions differ from those for concurrently controlled studies, since, under the first design, the control group data are constant for purposes of power calculations, while under the second design, some of the control group data are constant while the remainder are random. I contrast the required duration of these studies with the required duration for comparable concurrently controlled studies under a wide range of conditions.
Application of a two‐stage random effects model to longitudinal pulmonary function data from sarcoidosis patients
Authors: Vacek Pamela M. , Mickey Ruth M. , Bell Dianne Y.
Published: April 2007

We applied a two‐stage random effects model to pulmonary function data from 31 sarcoidosis patients to illustrate its usefulness in analysing unbalanced longitudinal data. For the first stage, repeated measurements of percentage of predicted forced vital capacity (FVC%) from an individual were modelled as a function of time since initial clinical assessment. At the second stage, parameters of this function were modelled as a function of certain patient characteristics. We used three methods for estimating the model parameters: maximum likelihood; empirical Bayes; and a two‐step least‐squares procedure. Similar results were obtained from each, but we recommend the empirical Bayes, since it provides unbiased estimates of variance components. Results indicated that deterioration in FVC% is associated with a higher initial FVC% value and large numbers of both total cells and eosinophils in bronchoalveolar lavage at the initial assessment. Improvement is associated with higher values of pulmonary Gallium uptake at initial assessment and race. Blacks are more likely to improve than whites.
A method for the estimation of chronic disease morbidity and trends from mortality data
Authors: Verdecchia Arduino , Capocaccia Riccardo , Egidi Viviana , Golini Antonio
Published: April 2007

Measures of chronic degenerative disease diffusion, such as incidence and prevalence rates, are a basic need for epidemiologists and others working in many fields of human sciences. Equations relating death probabilities to incidence and survival probabilities for chronic degenerative diseases are derived from a cohort point of view. A maximum likelihood approach is adopted for the estimation of incidence as a function of time related covariates. When time series of mortality data are available, the model can be used to describe and analyse levels and dynamics of morbidity. A trial application to lung and breast cancer is given for the province of Varese, Italy, where incidence data are available from the Lombardy Cancer Register.
Estimation of parameters and missing values under a regression model with non‐normally distributed and non‐randomly incomplete data
Authors: Azen Stanley P. , van Guilder Michael , Hill Mary Ann
Published: April 2007

We carried out a simulation study to compare the performance of three algorithms (complete cases, ALLVALUE, and expectation maximization, EM) in estimating regression parameters and missing values for situations that have varying amounts of missing data, distributions (normal, mixture of normals and lognormal), patterns of incomplete data (random, related and censored), and degrees of correlational structure among the dependent and independent variables. We found that the EM and complete cases algorithms performed equally well regardless of the correlational structure, when the percentage of incomplete data was only 5 per cent. When this percentage increased to 25 per cent, the EM algorithm was generally best for estimation, but the complete cases algorithm was safe and conservative. This finding may be attributed to the study design, which required that the slopes be the same in the population of all cases, and in the population of complete cases. In addition, the one‐step imputing method (ALLVALUE) was competitive only for situations with weak correlational structure and/or little missing data. In that situation the bias caused with use of all available information was less than that caused with use of only complete cases. On the other hand, for imputation, the EM algorithm performed optimally, even in situations of censored or log‐normally distributed data.
A model‐based approach to the imputation of missing data: Home injury incidences
Authors: Conn Judith M. , Lui Kung‐Jong , McGee Daniel L.
Published: April 2007

Missing or incomplete data cases are a problem in all types of statistical analyses. In disease surveillance, this problem inhibits determining the actual incidence of a disease event and monitoring the disease occurrence. Several statistical techniques have been developed to impute values for incomplete data cases. We present a model‐based approach to the imputation of missing data elements as applied to determining the incidence of home injury deaths.
An analysis of disease surveillance data that uses the geographic locations of the reporting units
Authors: Raubertas Richard F.
Published: April 2007

The primary purpose of a disease surveillance system is to provide data for the detection of changes in the incidence of the disease. Methods for the analysis of data from surveillance systems are reviewed. A new procedure is proposed for use when the system includes geographically dispersed reporting units, such as hospitals or administrative regions. The method is based on the cusum statistic, and combines information from different units according to their geographic relationships.
Analysis of surveillance data: A rationale for statistical tests with comments on confidence intervals and statistical models
Authors: Hall David B.
Published: April 2007

In the examination of differences between subgroups in surveillance data, whether through simple counting or through sophisticated statistical modelling, the comparison is not between simple random samples from two or more populations. The rationale for statistical tests rests on an appeal to a model of random permutation of demographic and disease factors for the observed population during the surveillance period. The testing evaluates chance as a possible explanation for the observed results. In the analysis of internal structure in a surveillance data set, statistical tests produce a conceptually simple result that lends itself to concise presentation and flexible interpretation. Tests limit emphasis on probabilistic manipulation and on parameter estimates. They cannot stand alone, and thus encourage descriptive presentation of observations. In contrast, statistical models and confidence intervals emphasize parameters rather than distributions and compete with the data for limited space.
Cholesterol‐based personal risk assessment in coronary heart disease
Authors: Caudill Samuel P. , Smith S. Jay , Cooper Gerald R.
Published: April 2007

Using data from the National Health and Nutrition Examination Survey (NHANES II) 1976–1980, we demonstrate how cross‐sectional total serum cholesterol surveillance data can be used by an individual to assess current and future personal cholesterol risk status. We propose statistical models, based on a person's current measured cholesterol level and the relationship between cross‐sectional age and cholesterol percentile estimates, that will allow prediction of future cholesterol levels or the age at which specified cholesterol risk levels will be reached if no cholesterol‐altering intervention is taken. These models incorporate the observed variation in the NHANES II data and expected intraperson biological variation and intralaboratory analytical variation. We illustrate the adequacy of the models using data from the longitudinal Framingham Study.
Detection of aberrations in the occurrence of notifiable diseases surveillance data
Authors: Stroup Donna F. , Williamson G. David , Herndon Joy L. , Karon John M.
Published: April 2007

The detection of unusual patterns in the occurrence of diseases and other health events presents an important challenge to public health surveillance. This paper discusses three analytic methods for identifying aberrations in underlying distributions. The methods are illustrated on selected infectious diseases included in the National Notifiable Diseases Surveillance System of the Centers for Disease Control. Results suggest the utility of such an analytic approach. Further work will determine the sensitivity of such methods to variations in the occurrence of disease. These methods are useful for evaluating and monitoring public health surveillance data.
A time series analysis of gonorrhea surveillance data
Authors: Schnell Daniel , Zaidi Akbar , Reynolds Gladys
Published: April 2007

Gonorrhea is the most frequently reported communicable disease in the United States. In response to rapidly rising rates in the late 1960s, the Public Health Service instituted a gonorrhea control programme. An important component of the programme is the screening of women for gonococcal infections. We use a time series intervention model to estimate the initial increase in reporting of cases in women associated with the control programme. From the middle 1970s to the middle 1980s, a regular seasonal pattern in the data is conspicuous. We use a second time series model to quantify the seasonal variation during this period and to construct forecasts.
Surrogate endpoints in clinical trials: Cancer
Authors: Ellenberg Susan S. , Hamilton J. Michael
Published: April 2007

Investigators use a surrogate endpoint when the endpoint of interest is too difficult and/or expensive to measure routinely and when they can define some other, more readily measurable, endpoint, that is sufficiently well correlated with the first to justify its use as a substitute. A surrogate endpoint is usually proposed on the basis of a biologic rationale. In cancer studies with survival time as the primary endpoint, surrogate endpoints frequently employed are tumour response, time to progression, or time to reappearance of disease, since these events occur earlier and are unaffected by use of secondary therapies. In early drug development studies, tumour response is often the true primary endpoint. We discuss the investigation of the validity of carcinoembryonic antigen (a tumour marker present in the blood) as a surrogate for tumour response. In considering the validity of surrogate endpoints, one must distinguish between study endpoints that provide a basis for reliable comparisons of therapeutic effect, and clinical endpoints that are useful for patient management but have insufficient sensitivity and/or specificity to provide reproducible assessments of the effects of particular therapies.
Surrogate endpoints in clinical trials: Cardiovascular diseases
Authors: Wittes Janet , Lakatos Edward , Probstfield Jeffrey
Published: April 2007

A surrogate endpoint in a cardiovascular clinical trial is defined as endpoint measured in lieu of some other so‐called ‘true’ endpoint. A surrogate is especially useful if it is easily measured and highly correlated with the true endpoint. Often the ‘true’ endpoint is one with clinical importance to the patient, for example, mortality or a major clinical outcome, while a surrogate is one biologically closer to the process of disease, for example, ejection fraction. Use of the surrogate can often lead to dramatic reductions in sample size and much shorter studies than use of the true endpoint. We discuss several problems common in trials with surrogate endpoints. Most important is the effect of missing data, especially in the face of informative censoring. Possible solutions are the assignment of scores or formal penalties to missing data.
Surrogate endpoints in clinical trials: Ophthalmologic disorders
Authors: Hillis Argye , Seigel Daniel
Published: April 2007

We examined three examples of surrogate observations in ophthalmology. The first'represents a simple case: the status of one eye is used as a surrogate for the (unobservable) status of the opposite eye in the same individual. The second and third examples represent possible extrapolation of long term results on the basis of early changes. These examples are used to illustrate the assumptions intrinsic in the use of surrogate variables.
Surrogate endpoints in clinical trials: Definition and operational criteria
Authors: Prentice Ross L.
Published: April 2007

I discuss the idea of using surrogate endpoints in the context of clinical trials to compare two or more treatments or interventions in respect to some ‘true’ endpoint, typically a disease occurrence. In order that treatment comparison based on a surrogate response variable have a meaningful implication for the corresponding true endpoint treatment comparison, a rather restrictive criterion is proposed for use of the adjective ‘surrogate’. Specifically, I propose that a surrogate for a true endpoint yield a valid test of the null hypothesis of no association between treatment and the true response. This criterion essentially requires the surrogate variable to ‘capture’ any relationship between the treatment and the true endpoint, a notion that can be operationalized by requiring the true endpoint rate at any follow‐up time to be independent of treatment, given the preceding history of the surrogate variable. I then discuss this operational criterion in the examples of the accompanying papers1–3 and in the setting of trials aimed at the primary and secondary prevention of cancer.
How study design affects outcomes in comparisons of therapy. I: Medical
Authors: Colditz Graham A. , Miller James N. , Mosteller Frederick
Published: April 2007

We analysed 113 reports published in 1980 in a sample of medical journals to relate features of study design to the magnitude of gains attributed to new therapies over old. Overall we rated 87 per cent of new therapies as improvements over standard therapies. The mean gain (measured by the Mann—Whitney statistic) was relatively constant across study designs, except for non‐randomized controlled trials with sequential assignment to therapy, which showed a significantly higher likelihood that a patient would do better on the innovation than on standard therapy (p = 0.004). Randomized controlled trials that did not use a double‐blind design had a higher likelihood of showing a gain for the innovation than did double‐blind trials (p = 0.02). Any evaluation of an innovation may include both bias and the true efficacy of the new therapy, therefore we may consider making adjustments for the average bias associated with a study design. When interpreting an evaluation of a new therapy, readers should consider the impact of the following average adjustments to the Mann—Whitney statistic: for trials with non‐random sequential assignment a decrease of 0.15, for non‐double‐blind randomized controlled trials a decrease of 0.11.
How study design affects outcomes in comparisons of therapy. II: Surgical
Authors: Miller James N. , Colditz Graham A. , Mosteller Frederick
Published: April 2007

We analysed the results of 221 comparisons of an innovation with a standard treatment in surgery published in six leading surgery journals in 1983 to relate features of study design to the magnitude of gain. For each comparison we measured the gain attributed to the innovation over the standard therapy by the Mann—Whitney statistic and the difference in proportion of treatment successes. For primary treatments (aimed at curing or ameliorating a patient's principal disease), an average gain of 0.56 was produced by 20 randomized controlled trials. This was less than the 0.62 average for four non‐randomized controlled trials, 0.63 for 19 externally controlled trials, and 0.57 for 73 record reviews (0.50 represents a toss‐up between innovation and standard). For secondary therapies (used to prevent or treat complications of therapy), the average gain was 0.53 for 61 randomized controlled trials, 0.58 for eleven non‐randomized controlled trials, 0.54 for eight externally controlled trials, and 0.55 for 18 record reviews. Readers of studies evaluating new treatments, particularly for primary treatments, may consider adjustment of the gain according to the study type.
A two‐stage trial design for testing treatment, self‐selection and treatment preference effects
Authors: Rücker Gerta
Published: April 2007

We propose a two‐stage randomized clinical trial design for separating treatment effects from those resulting from choosing treatment. At the first stage all patients are randomly allocated to one of two groups, the random group and the option group. At the second stage, patients in the random group are randomized a second time to treatment A or B, whereas patients in the option group are given a free choice between the two treatments. If there are differences in treatment response between the random group and the option group, there are two potential sources of bias: self‐selection by choosing treatment, and effects of suggestion by receiving the preferred treatment. A linear model is presented to estimate these effects separately along with test statistics which are approximately normally distributed.
A two‐period crossover design for the comparison of two active treatments and placebo
Authors: Koch Gary G. , Amara Ingrid A. , Brown Byron W. , Colton Theodore , Gillings Dennis B.
Published: April 2007

This paper discusses a two‐period crossover design for the comparison of two active treatments (A and B) and placebo (P) for relief of recurrent symptoms of a chronic health disorder. It is based on blocks of ten patients for which the treatment sequences A:B and B:A are each assigned to three patients and the sequences A:P, P:A, B:P, and P:B are each assigned to one patient; thus, treatment periods have a 2:2:1 allocation for A, B, and P. The principal model for analysis of this design involves additive subject effects, period effects, and treatment effects. Analysis of within‐patient differences provides an estimate of the comparison between active treatments with variance (2vw/7r) and an estimate of the comparison between an active treatment and placebo with variance (4vW/7r); here vw, is the within‐patient variance and r is the number of blocks of ten patients. Analyses which address carryover effects and treatment effects adjusted for carryover effects are also described. An example using simulated data on relief of recurrent gastrointestinal pain illustrates the methodology.
Empirical comparisons of proportional hazards and logistic regression models
Authors: Ingram Deborah D. , Kleinman Joel C.
Published: April 2007

We compare parameter estimates from the proportional hazards model, the cumulative logistic model and a new modified logistic model (referred to as the person‐time logistic model), with the use of simulated data sets and with the following quantities varied: disease incidence, risk factor strength, length of follow‐up, the proportion censored, non‐proportional hazards, and sample size. Parameter estimates from the person‐time logistic regression model closely approximated those from the Cox model when the survival time distribution was close to exponential, but could differ substantially in other situations. We found parameter estimates from the cumulative logistic model similar to those from the Cox and person‐time logistic models when the disease was rare, the risk factor moderate, and censoring rates similar across the covariates. We also compare the models with analysis of a real data set that involves the relationship of age, race, sex, blood pressure, and smoking to subsequent mortality. In this example, the length of follow‐up among survivors varied from 5 to 14 years and the Cox and person‐time logistic approaches gave nearly identical results. The cumulative logistic results had somewhat larger p‐values but were substantively similar for all but one coefficient (the age‐race interaction). The latter difference reflects differential censoring rates by age, race and sex.
The bias of the sample proportion following a group sequential phase II clinical trial
Authors: Chang Myron N. , Wieand Harry S. , Chang Vivian T.
Published: April 2007

Group sequential testing procedures have seen wide use in Phase II clinical trials. The sample proportion p̂ of responders is the commonly used estimator for the binomial response probability p. It can be shown that p̂ is the maximum likelihood estimator (MLE) of p. It is well known that MLE can be in general (Whitehead1) and p̂ in particular (Dupont2) biased estimators, if their computation follows a group sequential procedure. In this paper we numerically investigate the bias of p̂. We find that the magnitude of the bias of p̂ is less than 0.025 in all cases we investigated. We apply the idea in Whitehead1 to propose a bias‐adjusted estimator that reduces the bias substantially and reduces the mean square error as well in a certain range of p. We also evaluate the uniformly minimum variance unbiased (UMVU) estimator. If one does not mind a bias of 0.025, one may find the sample proportion a suitable estimator for p because of its simplicity and easy explanation. If one is concerned with bias, the bias‐adjusted estimator may be a good choice.
How to establish equivalence between treatments: A one‐sided clinical trial in paediatric oncology
Authors: Rodary Chantal , Com‐Nougue Catherine , Tournade Marie‐France
Published: April 2007

The design of a clinical trial to establish the equivalence of two treatments differs from that of an efficacy trial. The conventional null hypothesis of equivalent treatment efficacy is replaced by a null hypothesis of inequivalence which must be tested by appropriate statistics. In addition, the maximum allowable value of the true difference between the efficacy of two equivalent treatments must be specified. In oncology, such a trial is necessary when a standard treatment is replaced by a new less toxic one of equivalent efficacy. The statistical formulation is one‐sided. A trial comparing two pre‐operative treatments in childhood nephroblastoma is presented here and analysed according to this methodology.
Goodman and Kruskal's λ: A new look at an old measure of association
Authors: Makuch Robert W. , Rosenberg Philip S. , Scott Gwendolyn
Published: April 2007

We examine Goodman and Kruskal's λ using Efron's approach to regression and analysis of variance (ANOVA) for zero‐one outcome data. For a binary response cross‐classified by a single nominal predictor, we present a computationally simple ANOVA table in which λ is analogous to Pearson's R‐square. We characterize the relationship between λ and the commonly used apparent error rate in logistic regression, and show that λ is based implicitly on a prediction rule for a saturated model with classification level 0.5. This relationship suggests that we can correct the apparent error rate for chance by defining a natural generalization of λ that we call PRE, the proportional reduction in error. We illustrate the use of λ and PRE in an analysis of prognostic factors for one‐year survival in children with the acquired immunodeficiency syndrome (AIDS).
Converting relative risks to absolute risks: A graphical approach
Authors: Dupont William D.
Published: April 2007

This paper presents a graphical method for converting relative risks to absolute risks. These absolute risk estimates are a function of the patient's current age, the patient's risk of developing cancer relative to some baseline population, the age specific cancer hazard in the baseline population, and the patient's competing mortal risk from all other causes. Graphs for breast cancer morbidity in women, cardiovascular mortality in men, and lung cancer morbidity in men illustrate the method. These graphs provide the probability of developing cancer in the next twenty years given the patient's current age and relative risk. They are derived under the proportional hazards model. A graph for lung cancer in men that uses a plausible exponential hazards model is also provided. The paper illustrates the importance of competing mortal hazard from other causes on absolute cancer risk. The strengths and weaknesses of this method are discussed. The graphs presented in this paper may be used as an aid in clinical decision making and in patient counselling.
Cautions on the reanalysis of epidemiologic databases
Authors: Michalek Joel E. , Mihalko Daniel , Tripathi Ram C.
Published: April 2007

The statistical and epidemiologic literatures contain many examples of the reanalyses of medical databases. Some are confirmatory, such as the many reanalyses of the Stanford heart transplant data. Others, however, concern issues that differ from those that the data originally intended to address. We demonstrate in this paper that the second kind of reanalysis, if undertaken uncritically, can produce biased results. Utilizing a log‐linear model, we show analytically that the reanalysis of a designed study without adjustment for the design variable can produce biased results. We express the magnitude of this bias as a function of second‐ and third‐order interactions in the data. We demonstrate further that preliminary testing for the existence of second‐ and third‐order interactions can provide substantial bias reduction.
Estimation of sojourn time distributions and false negative rates in screening programmes which use two modalities
Authors: Alexander Freda E.
Published: April 2007

Day and Walter derived methods of joint maximum likelihood estimation for the sojourn time distribution and the false negative rate for a screening programme. Their methods are not directly applicable to a programme which uses alternate screening by two modalities whose sojourn times and false negative rates will differ. A modification is proposed and the results applied to data from the Edinburgh Randomised Trial of Breast Cancer Screening. This enables the effects of mammography and clinical examination to be separated. It is estimated that in a programme using both modalities 79 per cent of tumours arising in regularly screened women would be detected by screening and if the clinical examination were omitted this figure would be reduced by 5 per cent. The confidence intervals are, however, quite wide.
Bootstrap investigation of the stability of a cox regression model
Authors: Altman Douglas G. , Andersen Per Kragh
Published: April 2007

We describe a bootstrap investigation of the stability of a Cox proportional hazards regression model resulting from the analysis of a clinical trial of azathioprine versus placebo in patients with primary biliary cirrhosis. We have considered stability to refer both to the choice of variables included in the model and, more importantly, to the predictive ability of the model. In stepwise Cox regression analyses of 100 bootstrap samples using 17 candidate variables, the most frequently selected variables were those selected in the original analysis, and no other important variable was identified. Thus there was no reason to doubt the model obtained in the original analysis. For each patient in the trial, bootstrap confidence intervals were constructed for the estimated probability of surviving two years. It is shown graphically that these intervals are markedly wider than those obtained from the original model.
On correcting for misclassification in twin studies and other matched‐pair studies
Authors: Greenland Sander
Published: April 2007

In twin studies (and other matched‐pair studies) of the effect of a K‐level risk factor on disease risk, one must estimate the proportion of pairs in each of K2 possible pair categories, of which K(K −1) categories represent discordant pairs. In particular, for a binary factor, one must estimate proportions within two discordant‐pair categories and the variances of functions of these estimates. This paper shows how to do so when misclassification is present and stable estimates of the classification rates are available. Unlike methods that estimate only the discordance ratio, one can use the methods presented here to improve estimates of epidemiologic effects.
Comparison of the information in two lung function experiments
Authors: Lim Lynette L‐Y , Whitehead John
Published: April 2007

The amount of ventilation relative to perfusion (the ventilation‐perfusion ratio) received by the lung is a useful indicator of the efficiency of lung function. Two alternative techniques for recovering the ventilation‐perfusion ratio are outlined. While both techniques rely on the use of inert gases, one is well established and the other is only in a developmental stage. This paper focuses on a comparison of the amount of statistical information provided by these two techniques about the ventilation‐perfusion ratio. The criterion applied here for measuring amount of information has roots in communication theory and uses ideas inherent to Bayesian inference.
Correcting reported aids incidence: A statistical approach
Authors: Heisterkamp S. H. , Jager J. C. , Ruitenberg E. J. , Van Druten J. A. M. , Downs A. M.
Published: April 2007

This study is motivated by the time lag between date of diagnosis of AIDS cases and date of reporting, which results in incomplete data about the epidemic. A maximum likelihood procedure has been developed to adjust the actual numbers of diagnosed AIDS cases for reporting delay. If a parametric function for describing past and future incidence is assumed, its parameters and the adjustment for reporting delay can be estimated simultaneously. Data from the WHO Collaborating Centre on AIDS, Paris, are used. Practical problems related to data collection are dealt with.
Efficiency gains from the addition of controls to matched sets in cohort studies
Authors: Raboud J. , Breslow N. E.
Published: April 2007

We evaluate relative efficiencies of added controls in matched cohort studies in terms of the asymptotic variance of the estimate of the log relative risk associated with a single binary exposure variable. We calculate expected contributions to the information based on the Cox proportional hazards model under the assumption that the failure times for exposed and unexposed individuals have independent exponential or Weibull distributions and that the censoring variable, when present, also has an exponential distribution or a Weibull distribution with a shape parameter common to that of the failure time distribution. With estimation of a relative risk of four or less, one gains little with an increase in the ratio of unexposed to exposed cohort members beyond five or so.
A comparison of maximum likelihood and Jewell's estimators of the odds ratio and relative risk in single 2 × 2 tables
Authors: Becker Stan
Published: April 2007

This paper compares the maximum likelihood estimators of the odds ratio and relative risk in 2 × 2 tables with less biased estimators recently proposed by Jewell for small samples. In addition to bias, location in the confidence interval, and relative likelihood are calculated for ranges of sample sizes, probabilities (of exposure or disease) and true values of the odds ratio and relative risk. Jewell's estimators perform poorly from the perspectives of confidence intervals and likelihood. Given these and other problems, continued use of the maximum likelihood estimators is recommended.
Validity of mortality analysis based on retrospective smoking information
Authors: Machlin Steven R. , Kleinman Joel C. , Madans Jennifer H.
Published: April 2007

We assess the validity of mortality analysis based on retrospective reporting of smoking habits by subjects and proxies after a time lag of approximately ten years. The analysis is based on 2855 subject respondents and 615 proxy respondents to the NHANES I Epidemiologic Followup Survey (NHEFS), a national followup study of persons examined in the National Health and Nutrition Examination Survey (NHANES I). Persons 45–77 years of age at baseline were selected for analysis. Using three categories of smoking at baseline (current, former, never), the retrospective classification (NHEFS) matched the NHANES I classification for 89 per cent of the subject respondents and 83 per cent of the proxy respondents. Agreement levels were higher for women (92 per cent of subjects and 89 per cent of proxies) than for men (85 and 80 per cent).

We used Cox regression models to assess the use of retrospective smoking information in an analysis of the relationship between selected risk factors and mortality for persons 45–64 years of age. There were few substantive differences in results with use of NHEFS smoking data versus NHANES I smoking data. In particular, the effects of age, systolic blood pressure, education; and race on mortality were not sensitive to the source of the smoking data (NHANES I or NHEFS) or the form of the smoking variable (two‐, three‐, or six‐level categorization). The effects of body mass index on mortality were sensitive to the form of the smoking variable but results based on NHANES I and NHEFS were quite similar. These results suggest that smoking information obtained from proxy respondents is adequate for analyses of the risk of total mortality associated with smoking and other risk factors. Further assessment is needed to determine the adequacy of such data for analyses of mortality from specific causes that are sensitive to amount smoked or duration of smoking.
Testing for central mixtures of compartment model parameters
Authors: Zelterman Daniel
Published: April 2007

I discuss alternatives to the one compartment model, ℰYt = α + β exp(−γt). Instead of comparing the one and two compartment models, I derive statistics for testing mixtures of the parameters (β, γ) in the one compartment model. I apply the proposed methods to the problem of hydrogen clearance in blood flow measurement and to vanadium depuration data.
The use of dual or multiple reports in epidemiologic studies
Authors: Marshall James R.
Published: April 2007

Weak measurement of epidemiologic exposures is an impediment to appreciation of the effects of those exposures. This paper discusses two strategies to assess the true effects of weakly measured exposure. The first is to use external information about the extent of mismeasurement to adjust estimates of the effects of exposure. The second strategy is to use multiple measurement — to repeat the measurement in such a way that measurement errors are not repeated. The major disadvantage of the adjustment strategy is its sensitivity to incorrect specification of mismeasurement structure. The primary disadvantage of the multiple measurement strategy is its inefficiency. Unless epidemiologists are quite confident, about the extent and structure of measurement error in their data, they should rely primarily on multiple measurement, and secondarily on adjustment procedures.
Predicting the range of plasma carbamazepine concentrations in patients with epilepsy
Authors: Racine‐Poon A. , Dubois J. P.
Published: April 2007

A statistical model is proposed for predicting the range of plasma carbamazepine concentrations after administration of a controlled‐release formulation at steady state. The model is based on previous clinical studies in patients with epilepsy. The predicted range may be used to monitor and adjust treatment in a patient.
The use of baselines in clinical trials of bronchodilators
Authors: Senn S. J.
Published: April 2007

Two important qualities of controlled clinical trials are that they reduce dependence on historical standards for evaluating therapy and separate the effect of treatment from the confounding influence of time. Whatever the theory of the clinical trial, however, time has not easily been banished from the analysis of medical experiments in practice, and many doctors still prefer to evaluate treatments by comparing now with then rather than treatment with control. This is especially so in trials of bronchodilators in the treatment of asthma where, it is shown, baselines are used in ways which can increase the variability of measurement and even bias the results.
The analysis of relapse clinical trials, with application to a comparison of two ulcer treatments
Authors: Whitehead John
Published: April 2007

Patients cured of ulcers, carcinomas or other recurrent conditions are randomized between two treatments designed to maintain their recovery. Spontaneous reporting of relapse is supplemented by periodic asymptomatic screening. Interest centres on the difference in times to relapse between the two treatments. However, the analysis is complicated by the times to diagnoses at screens being qualitatively different from the times to symptomatic diagnoses between screens. In this paper a number of approaches to the analysis of such data are explored, and one of them is recommended. An extensive example with data on ulcer recurrence is presented to illustrate the method.
The superiority of a drug combination over each of its components
Authors: Gibson Janet M. , Overall John E.
Published: April 2007

The requirement for approval of a combination drug treatment AB is its demonstrated superiority over each of its components A and B at their most appropriate dose levels. This has led to frequent use of a three‐group experimental design that permits separate testing of Ho: AB ⩽ A and Ho: AB ⩽ B. A type I error can occur if no true treatment effect is present in either or both of the contrasts. The sampling distribution for the larger of the two observed p‐values, however, depends on whether a non‐null treatment effect is or is not present in one of the contrasts. We propose a strategy in which a conservative experiment‐wide type I error is achieved by defining the criterion for significance of the smaller observed treatment effect contingent on the magnitude of the larger observed treatment effect. We also discuss sample size requirements for the three‐group design.
Comparison of correlated correlations
Authors: Cohen Ayala
Published: April 2007

We consider a problem where k highly correlated variables are available, each being a candidate for predicting a dependent variable. Only one of the k variables can be chosen as a predictor and the question is whether there are significant differences in the quality of the predictors. We review several tests derived previously and propose a method based on the bootstrap. The motivating medical problem was to predict 24 hour proteinuria by protein—creatinine ratio measured at either 08:00,12:00 or 16:00. The tests which we discuss are illustrated by this example and compared using a small Monte Carlo study.
Time series analysis of injuries
Authors: Martinez‐Schnell Beverly , Zaidi Akbar
Published: April 2007

We used time series models in the exploratory and confirmatory analysis of selected fatal injuries in the United States from 1972 to 1983. We built autoregressive integrated moving average (ARIMA) models for monthly, weekly, and daily series of deaths and used these models to generate hypotheses. These deaths resulted from six causes of injuries: motor vehicles, suicides, homicides, falls, drownings, and residential fires. For each cause of injury, we estimated calendar effects on the monthly death counts. We confirmed the significant effect of vehicle miles travelled on motor vehicle fatalities with a transfer function model. Finally, we applied intervention analysis to deaths due to motor vehicles.