Probability intervals of toxicity and efficacy design for dose-finding clinical trials in oncology.

abstract：:In the past two decades, it has become increasingly clear that genetic factors contribute to the aetiology of many common diseases including cancers, coronary disease, allergy and psychiatric disorders. While one goal of genetic epidemiological studies is to locate susceptibility genes for these complex diseases, it i...

journal_title：Statistical methods in medical research

authors： Liang KY,Beaty TH

更新日期：2000-12-01 00:00:00

abstract：:Nonlinear mixed-effects modeling is a popular approach to describe the temporal trajectory of repeated measurements of clinical endpoints collected over time in clinical trials, to distinguish the within-subject and the between-subject variabilities, and to investigate clinically important risk factors (covariates) th...

journal_title：Statistical methods in medical research

authors： Yuan M,Xu XS,Yang Y,Xu J,Huang X,Tao F,Zhao L,Zhang L,Pinheiro J

更新日期：2019-12-01 00:00:00

abstract：:We propose a semiparametric multi-state frailty model to analyze clustered event-history data subject to interval censoring. The proposed model is motivated by an attempt to study the life course of dental caries at the tooth level, taking into account the multiplicity of caries states and the intra-oral clustering of...

journal_title：Statistical methods in medical research

authors： Pak D,Li C,Todem D

更新日期：2019-09-01 00:00:00

abstract：:A bivariate generalised linear mixed model is often used for meta-analysis of test accuracy studies. The model is complex and requires five parameters to be estimated. As there is no closed form for the likelihood function for the model, maximum likelihood estimates for the parameters have to be obtained numerically. ...

journal_title：Statistical methods in medical research

authors： Willis BH,Baragilly M,Coomar D

更新日期：2020-04-01 00:00:00

abstract：BACKGROUND:Dyspepsia diagnoses and treatment decisions are made in situations in which multiple factors must be taken into account. Evolving from neuro-biological insights, artificial neural networks (ANNs) can employ multiple factors in resolving medical prediction, classification, pattern recognition, and pattern com...

journal_title：Statistical methods in medical research

authors： García-Altés A,Santín D,Barenys M

更新日期：2007-08-01 00:00:00

abstract：:Post-therapeutic surveillance is one important component of cancer care. However, there still is no evidence-based strategies to schedule patients' follow-up examinations. Our approach is based on the modeling of the probability of the onset of relapse at an early asymptotic or preclinical stage and its transition to ...

journal_title：Statistical methods in medical research

authors： Somda SM,Leconte E,Boher JM,Asselain B,Kramar A,Filleron T

更新日期：2016-12-01 00:00:00

abstract：:Trials run in either rare diseases, such as rare cancers, or rare sub-populations of common diseases are challenging in terms of identifying, recruiting and treating sufficient patients in a sensible period. Treatments for rare diseases are often designed for other disease areas and then later proposed as possible tre...

journal_title：Statistical methods in medical research

authors： Dutton P,Love SB,Billingham L,Hassan AB

更新日期：2018-05-01 00:00:00

abstract：:Several epidemiological parameters have been introduced for quantifying the population impact of a certain exposure on morbidity on a population level, termed 'attributable risk' (AR). Of these definitions, the AR as suggested by Levin in 1953 or some algebraic transformations of it are most commonly used. A structure...

journal_title：Statistical methods in medical research

authors： Uter W,Pfahlberg A

更新日期：2001-06-01 00:00:00

abstract：:In biomedical research, various longitudinal markers measuring different quantities are often collected over time. For example, repeated measures of psychometric scores are very informative about the degradation process toward dementia. These trajectories are generally nonlinear with an acceleration of the decline a f...

journal_title：Statistical methods in medical research

authors： Segalas C,Helmer C,Jacqmin-Gadda H

更新日期：2020-09-01 00:00:00

abstract：:Statistical methods for spatial health data to identify the significant covariates associated with the health outcomes are of critical importance. Most studies have developed variable selection approaches in which the covariates included appear within the spatial domain and their effects are fixed across space. Howeve...

journal_title：Statistical methods in medical research

authors： Choi J,Lawson AB

更新日期：2018-01-01 00:00:00

abstract：:In this paper, we describe a Bayesian hierarchical Poisson model for the prospective analysis of data for infectious diseases. The proposed model consists of two components. The first component describes the behavior of disease during nonepidemic periods and the second component represents the increase in disease coun...

journal_title：Statistical methods in medical research

authors： Corberán-Vallet A,Lawson AB

更新日期：2014-12-01 00:00:00

abstract：:Nonlinear mixed-effects modeling is one of the most popular tools for analyzing repeated measurement data, particularly for applications in the biomedical fields. Multiple integration and nonlinear optimization are the two major challenges for likelihood-based methods in nonlinear mixed-effects modeling. To solve thes...

journal_title：Statistical methods in medical research

authors： Yuan M,Zhu Z,Yang Y,Zhao M,Sasser K,Hamadeh H,Pinheiro J,Xu XS

更新日期：2020-08-24 00:00:00

abstract：:Evaluation of medical imaging devices often involves clinical studies where multiple readers (MR) read images of multiple cases (MC) for a clinical task, which are often called MRMC studies. In addition to sizing patient cases as is required in most clinical trials, MRMC studies also require sizing readers, since both...

journal_title：Statistical methods in medical research

authors： Huang Z,Samuelson F,Tcheuko L,Chen W

更新日期：2020-06-01 00:00:00

abstract：:Monte Carlo evaluation of resampling-based tests is often conducted in statistical analysis. However, this procedure is generally computationally intensive. The pooling resampling-based method has been developed to reduce the computational burden but the validity of the method has not been studied before. In this arti...

journal_title：Statistical methods in medical research

authors： Fung WK,Yu K,Yang Y,Zhou JY

更新日期：2018-05-01 00:00:00

abstract：:Count responses are becoming increasingly important in biostatistical analysis because of the development of new biomedical techniques such as next-generation sequencing and digital polymerase chain reaction; a commonly met problem in modeling them with the popular Poisson model is overdispersion. Although it has been...

journal_title：Statistical methods in medical research

authors： Zhang H,He H,Lu N,Zhu L,Zhang B,Zhang Z,Tang L

更新日期：2017-06-01 00:00:00

abstract：:Clinical trials investigating the efficacy of two or more doses of an experimental treatment compared to a single reference arm are not uncommon. In such situations, if each dose is compared to the reference arm using an un-adjusted significance level, consideration of the Type I familywise error is likely to be requi...

journal_title：Statistical methods in medical research

authors： Fernandes N,Stone A

更新日期：2011-12-01 00:00:00

abstract：:This work presents a brief overview of Markov models in cancer screening evaluation and focuses on two specific models. A three-state model was first proposed to estimate jointly the sensitivity of the screening procedure and the average duration in the preclinical phase, i.e. the period when the cancer is asymptomati...

journal_title：Statistical methods in medical research

authors： Uhry Z,Hédelin G,Colonna M,Asselain B,Arveux P,Rogel A,Exbrayat C,Guldenfels C,Courtial I,Soler-Michel P,Molinié F,Eilstein D,Duffy SW

更新日期：2010-10-01 00:00:00

abstract：:Mixed models are widely used for the analysis of one repeatedly measured outcome. If more than one outcome is present, a mixed model can be used for each one. These separate models can be tied together into a multivariate mixed model by specifying a joint distribution for their random effects. This strategy has been u...

journal_title：Statistical methods in medical research

authors： Fieuws S,Verbeke G,Molenberghs G

更新日期：2007-10-01 00:00:00

abstract：:The threat of pandemics has made influenza surveillance systems a priority in epidemiology services around the world. The emergence of A-H1N1 influenza has required accurate surveillance systems in order to undertake specific actions only when and where they are necessary. In that sense, the main goal of this article ...

journal_title：Statistical methods in medical research

authors： Martinez-Beneito MA,Botella-Rocamora P,Zurriaga O

更新日期：2011-04-01 00:00:00

abstract：:Tree-based methods are very powerful and popular tools for analysing survival data with right-censoring. The existing methods assume that the true time-to-event and the censoring times are independent given the covariates. We propose different ways to build survival forests when dependent censoring is suspected, by us...

journal_title：Statistical methods in medical research

authors： Moradian H,Larocque D,Bellavance F

更新日期：2019-02-01 00:00:00

abstract：:Pediatric cardiac surgery may lead to poor outcomes such as acute kidney injury (AKI) and prolonged hospital length of stay (LOS). Plasma and urine biomarkers may help with early identification and prediction of these adverse clinical outcomes. In a recent multi-center study, 311 children undergoing cardiac surgery we...

journal_title：Statistical methods in medical research

authors： Wang Z,Ma S,Zappitelli M,Parikh C,Wang CY,Devarajan P

更新日期：2016-12-01 00:00:00

abstract：:In genomic analysis, it is significant though challenging to identify markers associated with cancer outcomes or phenotypes. Based on the biological mechanisms of cancers and the characteristics of datasets, we propose a novel integrative interaction approach under a semiparametric model, in which genetic and environm...

journal_title：Statistical methods in medical research

authors： Li Y,Wang F,Li R,Sun Y

更新日期：2020-10-01 00:00:00

abstract：:This paper presents a new model-based generalized functional clustering method for discrete longitudinal data, such as multivariate binomial and Poisson distributed data. For this purpose, we propose a multivariate functional principal component analysis (MFPCA)-based clustering procedure for a latent multivariate Gau...

journal_title：Statistical methods in medical research

authors： Lim Y,Cheung YK,Oh HS

更新日期：2020-11-01 00:00:00

abstract：:Previous work has shown that individual randomized "proof-of-concept" (PoC) studies may be designed to maximize cost-effectiveness, subject to an overall PoC budget constraint. Maximizing cost-effectiveness has also been considered for arrays of simultaneously executed PoC studies. Defining Type III error as the oppor...

journal_title：Statistical methods in medical research

authors： He L,Du L,Antonijevic Z,Posch M,Korostyshevskiy VR,Beckman RA

更新日期：2020-09-21 00:00:00

abstract：:It is now widely accepted that multiple imputation (MI) methods properly handle the uncertainty of missing data over single imputation methods. Several standard statistical software packages, such as SAS, R and STATA, have standard procedures or user-written programs to perform MI. The performance of these packages is...

journal_title：Statistical methods in medical research

authors： Yu LM,Burton A,Rivero-Arias O

更新日期：2007-06-01 00:00:00

abstract：:In many experiments and especially in translational and preclinical research, sample sizes are (very) small. In addition, data designs are often high dimensional, i.e. more dependent than independent replications of the trial are observed. The present paper discusses the applicability of max t-test-type statistics (mu...

journal_title：Statistical methods in medical research

authors： Konietschke F,Schwab K,Pauly M

更新日期：2020-11-24 00:00:00

abstract：:Competing risks data often exist within a center in multi-center randomized clinical trials where the treatment effects or baseline risks may vary among centers. In this paper, we propose a subdistribution hazard regression model with multivariate frailty to investigate heterogeneity in treatment effects among centers...

journal_title：Statistical methods in medical research

authors： Ha ID,Christian NJ,Jeong JH,Park J,Lee Y

更新日期：2016-12-01 00:00:00

abstract：:Purpose The prevalence estimates of binary variables in sample surveys are often subject to two systematic errors: measurement error and nonresponse bias. A multiple-bias analysis is essential to adjust for both biases. Methods In this paper, we linked the latent class log-linear and proxy pattern-mixture models to ad...

journal_title：Statistical methods in medical research

authors： Khalagi K,Mansournia MA,Motevalian SA,Nourijelyani K,Rahimi-Movaghar A,Bakhtiyari M

更新日期：2018-10-01 00:00:00

abstract：:Statistical methods for carrying out asymptotic inferences (tests or confidence intervals) relative to one or two independent binomial proportions are very frequent. However, inferences about a linear combination of K independent proportions L = Σβ(i)p(i) (in which the first two are special cases) have had very little...

journal_title：Statistical methods in medical research

authors： Martín Andrés A,Alvarez Hernández M,Herranz Tejedor I

更新日期：2011-08-01 00:00:00

abstract：:This article re-examines parametric methods for the calculation of time specific reference intervals where there is measurement error present in the time covariate. Previous published work has commonly been based on the standard ordinary least squares approach, weighted where appropriate. In fact, this is an incorrect...

journal_title：Statistical methods in medical research

authors： Gillard J

更新日期：2015-12-01 00:00:00