bluuebunny/crossref_metadata_2025 huggingface dataset:
Non‐parametric analysis of transfusion‐related HIV and AIDS incidence data
Authors: Motika Milena , Becker Niels G. , Wylie Brenton , Learmont Jennifer , Kaldor John
Published: April 2007

The method for making non‐parametric inferences about the probability distribution of the incubation period for AIDS from transfusion‐related AIDS data is extended to include data on individuals who have tested positive for HIV but do not have AIDS at the time of analysis. The method is illustrated with data on individuals infected by transfusion in Australia. The shape of the incubation distribution, as represented by the truncated distribution function, can be estimated, but the additional data contribute very little to the estimation of this shape. With a general non‐parametric form for the incubation distribution the additional data do not overcome the identifiability problem that exists for non‐parametric estimation of this distribution from AIDS data alone. If quarterly rates for HIV testing are specified, the additional data make it possible to estimate the cumulative distribution function for the incubation period. This is also possible when a simple parametric form, with one or two unknown parameters, is used for the testing rates. However, the additional data do not allow effective estimation of the HIV testing rates. The estimated shape of the incubation distribution indicates a higher proportion of short incubation periods than an earlier estimate based on U.S. data. Estimates for the incubation distribution itself do not vary much over a plausible range of HIV testing rates.
Marker values at the time of an AIDS diagnosis
Authors: Taylor Jeremy M. G. , Kim Dong Kee
Published: April 2007

In this paper statistical methods are proposed to estimate the distribution of a CD4 T‐cell number at the time of a clinical AIDS endpoint from serial measurements of CD4 T‐cell values in a cohort study. The statistical formulation of the problem is that of survival analysis with interval censored data, but in which the endpoints are obtained with measurement error. A measurement error likelihood is developed, assuming normality of the CD4 distribution at AIDS. A maximum likelihood estimation procedure and a Gibbs sampling approach are implemented.
A model for AIDS pathogenesis
Authors: Schenzle Dieter
Published: April 2007

The idea is put forward and analysed numerically, that within an infected person HIV evolves to increase its reproductivity within the population of CD4+ cells. A mathematical model predicts initial viremia and CD4+ cell drop after HIV infection and thereafter a slow progressive decline in the number of CD4+ cells, although for an extended period HIV is kept at a relatively low level by an active immune response. The time span T until the number of CD4+ cells falls below 20 per cent of its normal value depends on several model parameters. Assuming Gaussian distributions for these parameters, the model predicts a distribution function for T which resembles the observed distribution function for the incubation period to AIDS.
Non‐parametric estimation and doubly‐censored data: General ideas and applications to AIDS
Authors: Jewell Nicholas P.
Published: April 2007

In many epidemiologic studies of human immunodeficiency virus (HIV) disease, interest focuses on the distribution of the length of the interval of time between two events. In many such cases, statistical estimation of properties of this distribution is complicated by the fact that observation of the times of both events is subject to intervalcensoring so that the length of time between the events is never observed exactly. Following DeGruttola and Lagakos, we call such data doubly‐censored. Jewell, Malani and Vittinghoff showed that, with certain assumptions and for a particular doubly‐censored data structure, non‐parametric maximum likelihood estimation of the interval length distribution is equivalent to non‐parametric estimation of a mixing distribution. Here, we extend these ideas to various other kinds of doubly‐censored data. We consider application of the methods to various studies generated by investigations into the natural history of HIV disease with particular attention given to estimation of the distribution of time between infection of an individual (an index case) and transmission of HIV to their sexual partner.
Modelling the female‐to‐male per‐act HIV transmission probability in an emerging epidemic in Asia
Authors: Satten Glen A. , Mastro Timothy D. , Longini Ira M.
Published: April 2007

The per‐sexual‐act probability of transmission of the human immunodeficiency virus type 1 (HIV) from an infected person to a susceptible sex partner can be determined from a simple model if the number of contacts each study participant has with infected partners is known. The unusual epidemiologic situation in the emerging HIV epidemic in Thailand allowed this quantity to be estimated from a cross‐sectional study of young men conscripted into the Thai military in 1991. Although the simple model does not fit the data, an errors‐in‐variables approach provides a model with adequate fit. Other sources of lack of fit, including heterogeneity of the transmission probability, are discussed. With adjustment for measurement error, the per‐act probability is estimated to be 0.056, an order of magnitude higher than similar estimates in North America. Because data indicate that recently infected persons may be more infectious, and because extensive HIV transmission in Thailand began in 1988, this difference may be due, in part, to a higher proportion of recently infected individuals in the emerging Thai epidemic from 1988 to 1991.
Considerations in choice of a clinical endpoint for AIDS clinical trials
Authors: Neaton James D. , Wentworth Deborah N. , Rhame Frank , Hogan Carlton , Abrams Donald I. , Deyton Lawrence
Published: April 2007

In most clinical trials of antiretroviral therapy for patients infected with HIV, the major outcome variable has been the combined clinical endpoint of any new or recurrent AIDS defining event. We review features of combined endpoints and use data from the Terry Beirn Community Programs for Clinical Research on AIDS (CPCRA) to evaluate this outcome measure in terms of relevance, diagnostic certainty and sensitivity. We conclude that this endpoint is not relevant because: (i) the 19 different events constituting the combined endpoint are equally weighted in analyses even though they vary considerably in terms of risk of death; and (ii) events after the first are ignored, thus the event profile of patients is not taken into account in making treatment comparisons. We also conclude that power may be low with use of this endpoint if treatments under study do not have an immediate impact on disease progression, if some events which occur soon after randomization represent a disease process that has already begun to incubate, or if treatment differences for the various events constituting the combined endpoint are differentially effected by treatment. Since the ease and certainty of diagnosis of each of the 19 events also vary, we recommend that survival be the primary endpoint of antiretroviral trials, and that all opportunistic events experienced by patients, not just the first, be collected and summarized. Trial reports should include comparisons of incidence of each event by treatment group so that readers can rank events as they please. A single summary measure which considers severity and the entire event profile, as described here, would also be useful for assessing the impact of treatments on quality of life. Further research on approaches for weighting and combining multiple outcome measures is needed.
The effectiveness of interventions on incubation of AIDS as measured by secular increases within a population
Authors: Hoover Donald R. , Muñtoz Alvaro , He Yanhua , Taylor Jeremy M. G. , Kingsley Lawrence , Chmiel Joan S. , Saah Alfred
Published: April 2007

Methods are developed to estimate and test for the impact of intervention use on a population's survival function (time to AIDS). Each participant's history is divided intoJ+ 1 components: Ωooccurring before the intervention is available and Ω1to ΩJoccurring later, as the intervention becomes successively more available. Distribution free truncated Kaplan‐Meier models based on time since exposure fit separately to the risk sets/outcomes in Ωoto ΩJdirectly show the changing patterns of survival. Multivariate proportional hazards models can be used to adjust for covariates. Application of these methods indicates that availability of proven anti‐AIDS interventions may have delayed time to AIDS by 8 months in an educated HIV‐1 infected homosexual cohort with good access to medical care.
Assessing drug compliance using longitudinal marker data, with application to AIDS
Authors: Kim Hyungjin Myra , Lagakos Stephen W.
Published: April 2007

The assessment of non‐compliance to a study medication is an important issue in the evaluation of clinical trials of self‐administered drugs. Traditional methods for evaluating the compliance of subjects include self‐reported questionnaires and pharmacologic assays of drug levels in randomly‐drawn blood samples, but each of these has important limitations. This paper adapts and extends changepoint methods to assess compliance from longitudinal data on laboratory markers that are affected by the drug. The maximum likelihood estimators for two models are developed and examined. The effect of the drug on the marker process, as well as the spacing of the observations of the marker process relative to the time of noncompliance determine which model parameters are estimable. For the situations examined, the method of maximum likelihood is found to perform well in most cases. However, when non‐compliance begins shortly before the last observation of the marker process, these (as well as any other) estimators cannot reliably distinguish non‐compliance from compliance. The methods are illustrated with an example from a recent clinical trial of persons infected with HIV.
Some statistical issues in HIV vaccine trials
Authors: Rida Wasima N. , Lawrence Dale N.
Published: April 2007

Efficacy trials of prophylactic HIV vaccines will be among the most difficult clinical trials ever attempted. Not only will there be challenges with the recruitment and retention of high‐risk uninfected individuals, there will be many statistical challenges to the design, conduct, analysis, and interpretation of these trials. General features of an efficacy trial are described, including choice for the primary endpoint and testing for and estimating vaccine efficacy. Secondary objectives of trials are also discussed. These include determining the correlates of protective immunity, assessing the impact of HIV genetic variation on vaccine efficacy, and using biological markers such as viral load and CD4+ lymphocyte cell count to gain insight on a vaccine's ability to prevent or delay disease. The use of biological markers as surrogates for disease outcome is discussed. Last, trial designs for studying several candidate vaccines or other HIV prevention strategies in a single trial are examined.
A method for evaluating needle exchange programmes
Authors: Kaplan Edward H.
Published: April 2007

This paper details a statistical method for evaluating needle exchange programmes. The approach relies only on needle exchange operations data and the results of HIV tests conducted on needles. We develop statistical models describing the needle infection process and how needle exchange interrupts this process. The method is illustrated using 20 months of data collected in conjunction with the evaluation of New Haven, Connecticut's needle exchange programme, and the results suggest that needle‐borne HIV transmission among participating clients has been reduced by at least 33 per cent.
Mid‐p confidence intervals for the poisson expectation
Authors: Cohen Geoffrey R. , Yang Shu‐Ying
Published: April 2007

Conventionally a confidence interval (CI) for the standardized mortality ratio is set using the conservative CI for a Poisson expectation, μ. Employing the mid‐P argument we present alternative CIs that are shorter than the conventional ones. The mid‐P intervals do not guarantee the nominal confidence level, but the true coverage probability is only lower than the nominal level for a few short ranges of μ. The implications for mid‐P confidence intervals of various proposed definitions of two‐sided tests for discrete data are discussed.
On prediction of future observation in growth curve model
Authors: Tian Jason J. , Shukla Rakesh , Buncher C. Ralph
Published: April 2007

Rao proposed and compared several approaches for predicting future observations in a growth curve model. The assessment of associated prediction efficiency for different prediction methods were evaluated by Cross‐Validation Assessment Error (CVAE). He used three data sets, each with a limited number of subjects (13‐27) and also with a limited number of repeated measurements (4‐7) per subject, to illustrate the prediction methods. In the present paper, we applied four of the prediction methods discussed by Rao, on a data set with a relatively large number of subjects (174) and also with a larger number of measurements (21) per subject, using the polynomial function and log‐linear function. We propose to use the restricted cubic spline function as an alternative growth curve model and compare its performance with the polynomial function and log‐linear function. It turns out that, at least for larger data sets such as that used in this paper, the prediction methods perform somewhat better when the growth is described by restricted cubic spline function than when the growth is described by polynomial function and log‐linear function.
Testing for omitted variables and non‐linearity in regression models for longitudinal data
Authors: Palta Mari , Yao Tzy‐Jyun , Velu Raja
Published: April 2007

When fitting regression models to investigate the relationship between an outcome variable and independent variables of primary interest, there is often concern whether omitted variables or assuming a different functional relationship could have changed the conclusion or interpretation of the results. In longitudinal studies of ageing, the concern with omitted variables is well known in the context of cohort and period effects, which refer to unmeasured variables systematically related to the individual's year of birth and secular trends in outcome, respectively. We present and compare three approaches to detecting omitted confounders and non‐linearity in the random effects model for longitudinal data (Laird and Ware, 1982) with random slope and intercept across individuals. The first approach compares simple unweighted within and between regression coefficients, the second is the Hausman specification test for regression models, and the third approach involves testing directly the significance of functions of individual specific covariate means x̄i, in the random effects regression model. This last approach is motivated by the models that arise when cohort or period effects are ignored. We compare the three approaches, and illustrate their application.
Cox regression analysis of multivariate failure time data: The marginal approach
Authors: Lin D. Y.
Published: April 2007

Multivariate failure time data are commonly encountered in scientific investigations because each study subject may experience multiple events or because there exists clustering of subjects such that failure times within the same cluster are correlated. In this paper, I present a general methodology for analysing such data, which is analogous to that of Liang and Zeger for longitudinal data analysis. This approach formulates the marginal distributions of multivariate failure times with the familiar Cox proportional hazards models while leaving the nature of dependence among related failure times completely unspecified. The baseline hazard functions for the marginal models may be identical or different. Simple estimating equations for the regression parameters are developed which yield consistent and asymptotically normal estimators, and robust variance‐covarinace estimators are constructed to account for the intra‐class correlation. Simulation results demonstrate that the large‐sample approximations are adequate for practical use and that ignoring the intra‐class correlation could yield rather misleading variance estimators. The proposed methodology has been fully implemented in a simple computer program which also incorporates several alternative approaches. Detailed illustrations with data from four clinical or epidemiologic studies are provided.
On the development of the medical research council trial of α‐interferon in metastatic renal carcinoma
Authors: Fayers P. M. , Cook P. A. , Machin D. , Donaldson N. , Whitehead J. , Ritchie A. , Oliver R. T. D. , Yuen P.
Published: April 2007

This paper describes the steps taken by the British Medical Research Council (MRC) in developing the MRC RE01 trial, a randomized clinical trial for patients with metastatic renal cancer; we discuss the reasons for adopting a triangular sequential design and the impact that this has upon the monitoring of the trial. It had been suggested to the MRC that a trial of biological agents for metastatic renal carcinoma should be initiated. The Cancer Therapy Committee (CTC) of the MRC, through its associated site specific working parties, is responsible for designing and co‐ordinating randomized trials of alternative treatments in cancer in solid tumours. Since no MRC working party for renal carcinoma existed at that time, development began by the formation of an ad hoc group set up under the auspices of the CTC. They assessed, by means of a postal questionnaire, U.K. interest in the trials of, and modalities utilized for, treatment of renal cancer. The responses focused attention on the important questions to ask and indicated the level of potential collaboration. These responses and related clinical and statistical issues suggested a protocol to compare medroxy‐progesterone acetate (MPA) against α‐interferon (α‐IFN). In view of the special problems of comparing an expensive and potentially toxic therapy with an inexpensive and non‐toxic standard, a sequential design was used rather than a fixed sample size design. Statistical issues raised and solutions provided are described. The method of establishing the trial data monitoring committee and a brief review of mortality from renal carcinoma in England and Wales are also included. The trial opened to patient recruitment on 1 January 1992. The formal statements regarding statistical issues that appear in the formal trial protocol (RE01) are set out in the Appendix.
A step‐down procedure for multiple tests of treatment versus control in each of several groups
Authors: Cheung Siu Hung , Holland Burt
Published: April 2007

Cheung and Holland extended Dunnett's treatment versus control multiple comparison procedure to the case of several groups. Dunnett and Tamhane provided a step‐down procedure more powerful than that of Dunnett for situations where the researcher's interest is in testing and not in simultaneous confidence interval estimation. In this paper we show how one can use the approach of Dunnett and Tamhane to devise a testing procedure for the multi‐group problem with power greater than that of Cheung and Holland. We illustrate the new procedure with reanalyses of published data from a clinical experiment.
The paired availability design: A proposal for evaluating epidural analgesia during labor
Authors: Baker Stuart G. , Lindeman Karen S.
Published: April 2007

The paired availability design (PAD) can reduce selection bias when it is not possible to randomize subjects. PAD consists of independent pairs of experimental and control groups. Within each pair, the intervention is the availability of treatment not its receipt. In the experimental group, the new treatment is made available to all subjects although some may not receive it. In the control group, the experimental treatment is generally not available to subjects although some may receive it in special circumstances. We present a statistic to test a null hypothesis that the receipt of intervention will increase response by a specified non‐zero amount δ. We propose this design for use in a study of the effect of epidural analgesia on the rate of Caesarean section.
A direct, general approach based on isobolograms for assessing the joint action of drugs in pre‐clinical experiments
Authors: Machado Stella G. , Robinson Gregory A.
Published: April 2007

Pharmacologists and other biologists frequently use methods based on the interpretation of isobolograms to quantify the extent of synergy or antagonism between drugs used in combination in pre‐clinical studies. Most methods have been unsatisfactory from a statistical viewpoint, many because they have relied solely on visual evaluation, others because the methods have not taken into account the variability of the measurements. We describe a direct approach for quantifying the joint potency of two drugs, a central feature being the use of simple isobole models that lead directly to response surface models for the expected experimental outcomes. The approach is general in the sense that one can use it for discrete or continuous responses, different underlying probability distributions, linear or non‐linear dose‐response functions of the drugs used singly, and a variety of experimental designs. Our approach extends the suggestions made by Hewlett for measuring the joint potency of drugs, and is similar in spirit to the approaches proposed by Greco et al. and Weinstein et al. We describe the analysis of data from an in vitro experiment conducted to evaluate the efficacy of the antiviral drugs AZT and ddI used in combination.
On a model‐based approach to estimating efficacy in clinical trials
Authors: Albert Jeffrey M. , Demets David L.
Published: April 2007

Treatment efficacy is of primary importance in phase III clinical trials. Determining the true size of the treatment effect is often complicated by patient non‐compliance with the regimen. This paper examines a model‐based approach in the spirit of Efron and Feldman utilizing drug and placebo compliance information. One of the assumptioqs of this analysis is ‘comparability’ of drug and placebo compliance. Robustness in estimation of subgroup and population treatment effects when this assumption is violated is investigated in a simulation study. We find that even moderate non‐comparability (for example, normalized compliance correlations of 0.4) may produce severely biased estimates. The bias is modulated by the strength of the relationship between compliance and the response on placebo.
The use of a square array scheme in blood testing
Authors: Phatarfod R. M. , Sudbury Aidan
Published: April 2007

When testing blood samples for the presence of disease, considerable efficiencies may be achieved by pooling samples and testing them as a batch. It is shown that placing the samples in a square array and pooling rows and columns has substantial advantages, particularly in the reduction of false negatives. The commonly used 8 × 12 array is also considered.
Attributable fraction estimates and case definitions for malaria in endemic
Authors: Smith Tom , Schellenberg Joanna Armstrong , Hayes Richard
Published: April 2007

Asymptomatic carriage of malaria parasites occurs frequently in endemic areas and the detection of parasites in a blood film from a febrile individual does not necessarily indicate clinical malaria. In areas of low and moderate endemicity the parasite prevalence in fever cases can be compared with that in community controls to estimate the fraction of cases which are attributable to malaria. In areas of very high transmission such estimates of the attributable fraction may be imprecise because very few individuals are without parasites. Furthermore, non‐malarial fevers appear to suppress low levels of parasitaemia resulting in biased estimates of the attributable fraction. Alternative estimation techniques were therefore explored using data collected during 1989‐1991 from a highly endemic area of Tanzania, where over 80 per cent of young children are parasitaemic. Logistic regression methods which model fever risk as a continuous function of parasite density give more precise estimates than simple analyses of parasite prevalence and overcome problems of bias caused by the effects of non‐malarial fevers. Such models can be used to estimate the probability that any individual episode is malaria‐attributable and can be extended to allow for covariates. A case definition for symptomatic malaria that is used widely in endemic areas requires fever together with a parasite density above a specific cutoff. The choice of a cutoff value can be assisted by using the probabilities derived from the logistic model to estimate the sensitivity and specificity of the case definition.
Age‐related reference ranges: Significance tests for models and confidence intervals for centiles
Authors: Wade A. M. , Ades A. E.
Published: April 2007

A method of fitting age‐related reference ranges using maximized likelihood is presented. The method is illustrated using CD4 counts of uninfected children born to HIV‐1 infected women. The likelihood incorporates exponential functions to describe the Box‐Cox transformation parameter that induces Normality and the mean and standard deviation of the transformed data, at all ages in the range. This guarantees that the centiles are asymptotic to notional adult values and avoids edge effects. Likelihood ratio tests were used to assess the significance of the model parameters, and profile likelihood confidence intervals were constructed around the fitted centiles. The asymptotes of the resulting CD4 reference range for the childhood dataset were compared with CD4 counts available from a group of uninfected adults. The proposed approach limits the need for arbitrary decisions about grouping of the data, degree of smoothing or choice of model.
Determining the size of a cross‐sectional sample to estimate the age‐specific incidence of an irreversible disease
Authors: Marschner Ian C.
Published: April 2007

The design of a cross‐sectional survey to estimate the age‐specific incidence of an irreversible disease is considered, where the incidence rate is not changing over time and the risk of mortality is not affected by the onset of disease. The sample is assumed to give information on the current age and disease status of individuals, but not on age at onset of the disease. We consider the problem of determining overall sample size in this context, as well as how best to choose the distribution of sampling across various age groups. These issues are considered with the aim of obtaining incidence estimates achieving acceptable levels of precision. The proposed methods are illustrated by measles incidence estimation.
Publications from multicentre clinical trials: Statistical techniques and accessibility to the reader
Authors: Marsh Marta J. , Hawkins Barbara S.
Published: April 2007

Articles from multicentre randomized clinical trials were analysed by methods adapted from Emerson and Colditz and Juzych et al. to compare the frequency with which different statistical methods are used by clinical trials investigators with the frequency used by other researchers, and to determine how much statistical knowledge is required to interpret the statistical treatment of data from clinical trials. We observed differences between the frequency of usage of statistical methods and the accessibility of the clinical trials publications and those of all medical research articles published by specific journals. Clinical trials publications are less accessible than others in medical journals to the reader who knows only descriptive statistics, t‐tests, contingency tables, power calculations, and life table methods. Many more statistical methods must be known by a reader to understand fully publications regarding treatment group comparisons for the primary outcomes of interest from clinical trials.
Correspondence analysis applied to grouped cohort data
Authors: Grassi M. , Visentin S.
Published: April 2007

In this paper we investigate application of generalized correspondence analysis (GCA) to model a two‐way table of rates consisting of a cross‐classification of case numerators and person‐time denominators. The GCA reconstitution formula is proposed as a correlation model for analysing these data. This provides two major advantages over the techniques usually applied. The number of interaction parameters to be estimated is reduced, and, moreover, they have useful interpretation; the singular values and the scores are measures of row‐column modification/interaction effects; in addition the scores allow graphical display of these effects. An asymmetrical plot is proposed for optimal representation of interaction parameters as distances. Finally, two examples are presented to illustrate the method of analysing a two‐way table of covariate by exposure and a two‐way table derived from a cross‐classification of two exposure factors.
Penalized likelihood in Cox regression
Authors: Verweij Pierre J. M. , Van Houwelingen Hans C.
Published: April 2007

In a Cox regression model, instability of the estimated regression coefficients can be reduced by maximizing a penalized partial log‐likelihood, where a penalty function of the regression coefficients is substracted from the partial log‐likelihood. In this paper, we choose the optimal weight of the penalty function by maximizing the predictive value of the model, as measured by the crossvalidated partial log‐likelihood. Our methods are illustrated by a study of ovarian cancer survival and by a study of centre effects in kidney graft survival.
Separation of systematic and random differences in ordinal rating scales
Authors: Svensson Elisabeth , Holm Sture
Published: April 2007

We introduce a new statistical method, which separates and measures different types of variability between paired ordered categorical measurements. The key to the separation is a two‐way augmented ranking approach of observations in a contingency table. It means that cases classified in a specific category by one rater will be internally ranked according to the classifications from the other. This enables us to extract the component of interobserver variation which is not systematic. The variance of the rank differences between judgements is a suitable measure of this interrater variability, which we characterize as random. The empirical measure of random interjudge disagreement, which lies between 0 and 1, is called the relative rank variance and is an estimate of a parameter defined on the multinomial probability distribution in the contingency table. The systematic differences are determined by the marginals and described by two empirical measures, relative position and relative concentration; both measures lie between ‐ 1 and 1. Our method is applied to data sets from a reliability study of two clinical rating scales for assessing hydrocephalus and subarachnoid haemorrhage.
Internal pilot studies for estimating sample size
Authors: Birkett Martin A. , Day Simon J.
Published: April 2007

We develop the idea of using data from the first ‘few’ patients entered in a clinical trial to estimate the final trial size needed to have specified power for rejecting H0 in favour of H1 if a real difference exists. When comparing means derived from Normally distributed data, there is no important effect on test size, power or expected trial size, provided that a minimum of about 20 degrees of freedom are used to estimate residual variance. Relative advantages and disadvantages of using larger internal pilot studies are presented. These revolve around crude expectations of the final study size, recruitment rate, duration of follow‐up and practical constraints on the ability to prevent the circulation of unblinded randomization codes to investigators and those involved in editing and checking data.
A critical discussion of intraclass correlation coefficients
Authors: Müller Reinhold , Büttner Petra
Published: April 2007

In general, intraclass correlation coefficients (ICC's) are designed to assess consistency or conformity between two or more quantitative measurements. They are claimed to handle a wide range of problems, including questions of reliability, reproducibility and validity. It is shown that care must be taken in choosing a suitable ICC with respect to the underlying sampling theory. For this purpose a decision tree is developed. It may be used to choose a coefficient which is appropriate for a specific study setting. We demonstrate that different ICC's may result in quite different values for the same data set, even under the same sampling theory. Other general limitations of ICC's are also addressed. Potential alternatives are presented and discussed, and some recommendations are given for the use of an appropriate method.
Growth charts for both cross‐sectional and longitudinal data
Authors: Cole T. J.
Published: April 2007

Reference centile charts are widely used to monitor child growth, and yet they are often used inappropriately. Charts derived from cross‐sectional data ought not to be used to monitor longitudinal data. Such monitoring is only valid if two distinct sets of centiles are available, one for height distance and one for height velocity. There is also the problem of regression to the mean, in that expected height velocity is negatively correlated with initial height during infancy and puberty, and this requires a regression‐based conditional standard. Furthermore, such conditional standards usually assume that the measurement of interest is normally distributed, which may not be appropriate. The paper describes modifications to the conventional growth chart which address these issues, illustrated using height data from the French Longitudinal Study.
A meta‐analysis of clinical trials involving different classifications of response into ordered categories
Authors: Whitehead Anne , Jones Nicola M. B.
Published: April 2007

Statistical methods are available for performing a meta‐analysis when the response variable of interest is the same in each study. Problems arise when studies exploring a common therapeutic question use different patient response types. This article presents statistical methods for combining studies which involve different classifications of response into ordered categories. The assumptions required for the stratified proportional odds model, on which the analysis is based, are discussed. The approach is illustrated using results from a series of studies investigating the prevention of gastrointestinal damage induced by non‐steroidal anti‐inflammatory drugs.
Multistate modelling of liver transplantation data
Authors: Hansen B. E. , Thorogood J. , Hermans J. , Ploeg R. J. , Van Bockel J. H. , Van Houwelingen J. C.
Published: April 2007

This paper concerns the survival analysis of liver transplant patients when patients with a potentially fatal rejection of the transplanted organ may receive a retransplant. A multistate model, analysing the states ‘alive with first graft’ and ‘alive with second graft’ separately, is suggested. Proportional hazards models and logistic regression models are used to evaluate which risk factors related to donor, preservation and recipient, influence the transition intensities. The complete model is used to predict overall survival of a patient and to study the influence of the risk factors on total survival.
Fieller's confidence intervals for the ratio of two means in the assessment of average bioequivalence from crossover data
Authors: Vuorinen Jouni , Tuominen Juhani
Published: April 2007

The two‐period crossover design is the most commonly used study design for bioequivalence of one test formulation to be assessed in comparison to one reference formulation. Consequently, in this paper, all derivation is based on this particular design. It is assumed that for the underlying statistical model the usual assumptions of normality and additivity are satisfied on the original scale of measurement and that it is wanted to base the assessment of average bioavailability on the ratio of the unknown population means for the test and reference formulation. The purpose of this paper is to illustrate that it is reasonable to assume a uniform covariance structure for the two‐period crossover design, because the demand of equal variability in bioavailabilities, in addition to equal average bioavailabilities, for the reference and test formulation makes the assumption of uniform covariance structure very realistic, and also because the properties of a decision rule based upon a Fieller's confidence interval under a uniform covariance structure are competitive with those of the corresponding rule based on a general covariance structure.
Some practical improvements in the continual reassessment method for phase I studies
Authors: Goodman Steven N. , Zahurak Marianna L. , Piantadosi Steven
Published: April 2007

The Continual Reassessment Method (CRM) is a Bayesian phase I design whose purpose is to estimate the maximum tolerated dose of a drug that will be used in subsequent phase II and III studies. Its acceptance has been hindered by the greater duration of CRM designs compared to standard methods, as well as by concerns with excessive experimentation at high dosage levels, and with more frequent and severe toxicity. This paper presents the results of a simulation study in which one assigns more than one subject at a time to each dose level, and each dose increase is limited to one level. We show that these modifications address all of the most serious criticisms of the CRM, reducing the duration of the trial by 50–67 per cent, reducing toxicity incidence by 20–35 per cent, and lowering toxicity severity. These are achieved with minimal effects on accuracy. Most important, based on our experience at our institution, such modifications make the CRM acceptable to clinical investigators.
Multivariate tests for multiple endpoints in clinical trials
Authors: Follmann Dean
Published: April 2007

Clinical trials frequently lack a single definitive endpoint that completely describes treatment efficacy. When a treatment affects a disease in a multitude of ways, several endpoints are necessary to describe efficacy. There is a variety of statistical procedures to provide a single p‐value when a treatment affects several endpoints. This paper reviews several procedures including Hotelling's T2 test, an approximate likelihood ratio test (Tang et al.), the weighted version of O'Brien's test, tests involving the maximum of several test statistics, and a test based on the average of the maximum of several endpoints (Wittes). I propose a risk score test whose rejection boundary corresponds to a contour of constant risk. Calculations and simulation studies help to compare the different tests with an emphasis on the effect of non‐standard alternatives, and on identifying settings where some tests may lack clinical relevance.
A regression method for analysing ordinal data from intervention trials
Authors: Schnell Daniel J. , Magee Elvin , Sheridan John R.
Published: April 2007

We consider the case of a community intervention trial evaluated with a series of cross‐sectional surveys and having outcomes measured on an ordinal scale. We propose a modelling procedure that combines ridit analysis and linear regression methods. We use the multinomial distribution as the basis for variance estimation of the mean ridits and then use simple regression models to estimate differences (for example, between intervention and comparison areas) among the ridits. We illustrate this procedure with data from a community intervention trial promoting condom use, with the adoption of consistent condom use measured on a 5‐point ordinal scale.
Inference for smooth curves in longitudinal data with application to an aids clinical trial
Authors: Wang Yongxiao , Taylor Jeremy M. G.
Published: April 2007

We discuss a longitudinal study where data for many subjects are collected at irregular intervals. The study is a randomized trial of HIV infected subjects and the response variable of interest is serum neopterin. The mean of the outcome variable, taken over patients in each treatment group, is assumed to follow a smooth curve. Piecewise cubic polynomials with a moderate number of knots are used to model the curves. A general parametric form is assumed for the covariance structure. Maximum penalized likelihood estimation is used to smooth the over‐parameterized curves. Statistical inference for the mean curves, including confidence bands and hypothesis tests, is discussed. Two approaches, one using a Bayesian interpretation of the penalized likelihood and the other based on the asymptotic distribution of the maximum penalized likelihood estimates, are discussed and contrasted. The properties of the confidence bands obtained from these two approaches are evaluated by examining their coverage rates in a simulation study.
Variations in Pelvic Dimensions Do Not Predict the Risk of Circumferential Resection Margin (CRM) Involvement in Rectal Cancer
Authors: Salerno G. , Daniels I. R. , Brown G. , Norman A. R. , Moran B. J. , Heald R. J.
Published: April 2007

Background

The objective of this study was to assess the value of preoperative pelvimetry, using magnetic resonance imaging (MRI), in predicting the risk of an involved circumferential resection margin (CRM) in a group of patients with operable rectal cancer.

Methods

A cohort of 186 patients from the MERCURY study was selected. These patients’ histological CRM status was compared against 14 pelvimetry parameters measured from the preoperative MRI. These measurements were taken by one of the investigators (G.S.), who was blinded to the final CRM status.

Results

There was no correlation between the pelvimetry and the CRM status. However, there was a difference in the height of the rectal cancer and the positive CRM rate (p = 0.011). Of 61 patients with low rectal cancer, 10 had positive CRM at histology (16.4% with CI 8.2%–22.1%) compared with 5 of 110 patients with mid/upper rectal cancers (4.5% with CI 0.7%–8.4%).

Conclusions

Magnetic resonance imaging can predict clear margins in most cases of rectal cancer. Circumferential resection margin positivity cannot be predicted from pelvimetry in patients with rectal cancer selected for curative surgery. The only predictive factor for a positive CRM in the patients studied was tumor height.
Epidemiologic Associations of Carpal Tunnel Syndrome and Sleep Position: Is there a Case for Causation?
Authors: McCabe Steven J. , Uebele Anna L. , Pihur Vasyl , Rosales Roberto S. , Atroshi Isam
Published: May 2007

Introduction

Carpal tunnel syndrome (CTS) is thought to be due to compression of the median nerve in the carpal tunnel. It is known that carpal tunnel pressures are elevated in wrist postures of flexion and extension and in those patients with CTS. Classic symptoms of CTS include night waking with pain, tingling, and numbness. These classic symptoms stimulated our interest in the relationship of sleep to the development of CTS.

Method

We reviewed the literature surrounding the epidemiology of CTS and the literature regarding sleep disturbances. Through careful distillation of these studies and a process of reasoning, we have developed a hypothesis for a causal mechanism of CTS.

Results

Epidemiologically, it has been shown that CTS is associated with age, gender, increased body mass index (BMI), diabetes, pregnancy, and is more common in some populations. The same associations noted above for CTS are strongly associated with sleep disturbances. Sleep disturbances due to age, gender, BMI, pregnancy, and population variations are all associated with sleeping in the lateral position supporting the hypothesis that a common causative mechanism of CTS is sleeping in a lateral position.

Discussion

We believe that the epidemiologic associations with CTS act through a common causative mechanism, increased sleeping in the lateral position which puts the wrist at increased risk of flexion or extension, compressing the median nerve in the carpal tunnel. This hypothesis is simple and explains the connection between a previously unconnected group of epidemiologic associations. This realization has real clinical significance in that it focuses our attention on the early disorder when it is completely reversible. It clarifies previously confused clinical circumstances, creates research questions that can be tested, and it invites us to change our clinical perspective in this most common form of nerve compression.
Altered melusin expression in the hearts of aortic stenosis patients
Authors: Brokat Sebastian , Thomas Jenny , Herda Lars R. , Knosalla Christoph , Pregla Reinhard , Brancaccio Mara , Accornero Federica , Tarone Guido , Hetzer Roland , Regitz‐Zagrosek Vera
Published: May 2007

Background:

The role of melusin, a necessary component in pressure‐induced left‐ventricular hypertrophy (LVH) in mice, has not yet been determined in human cardiac hypertrophy. We analyzed for the first time the expression and regional distribution of melusin in human LVH due to aortic stenosis (AS) and determined AKT phosphorylation as a potential downstream effector of melusin signalling.

Methods:

Regional distribution of melusin was evaluated in four normal hearts. Melusin staining, gene expression and protein content were assessed in biopsies from normal and diseased hearts and melusin gene expression was correlated with LV functional changes. The pAKT/AKT ratio was determined in parallel and correlated with melusin protein content.

Results:

In normal hearts, melusin was found in the myocytes with a uniform regional distribution. Melusin staining, mRNA and protein were significantly decreased in human AS hearts. The reduction in melusin mRNA was significantly correlated with LVEF, LVEDD and LVESD. pAKT/AKT ratio was significantly decreased in human AS and was correlated with melusin content.

Conclusion:

Reduction in melusin expression parallels the functional cardiac impairment in human AS. The simultaneous decrease of melusin and AKT phosphorylation suggests a connection between the loss of melusin and the decrease in systolic function.
Rpn13p and Rpn14p are involved in the recognition of ubiquitinated Gcn4p by the 26S proteasome
Authors: Seong Ki Moon , Baek Je-Hyun , Yu Myeong-Hee , Kim Joon
Published: May 2007

The 26S proteasome, composed of the 20S core and 19S regulatory complexes, is important for the turnover of polyubiquitinated proteins. Each subunit of the complex plays a special role in proteolytic function, including substrate recruitment, deubiquitination, and structural contribution. To assess the function of some non‐essential subunits in the 26S proteasome, we isolated the 26S proteasome from deletion strains of RPN13 and RPN14 using TAP affinity purification. The stability of Gcn4p and the accumulation of ubiquitinated Gcn4p were significantly increased, but the affinity in the recognition of proteasome was decreased. In addition, the subcomplexes of the isolated 26S proteasomes from deletion mutants were less stable than that of the wild type. Taken together, our findings indicate that Rpn13p and Rpn14p are involved in the efficient recognition of 26S proteasome for the proteolysis of ubiquitinated Gcn4p.