Modelling breast cancer tumour growth for a stable disease population.

Abstract:

:Statistical models of breast cancer tumour progression have been used to further our knowledge of the natural history of breast cancer, to evaluate mammography screening in terms of mortality, to estimate overdiagnosis, and to estimate the impact of lead-time bias when comparing survival times between screen detected cancers and cancers found outside of screening programs. Multi-state Markov models have been widely used, but several research groups have proposed other modelling frameworks based on specifying an underlying biological continuous tumour growth process. These continuous models offer some advantages over multi-state models and have been used, for example, to quantify screening sensitivity in terms of mammographic density, and to quantify the effect of body size covariates on tumour growth and time to symptomatic detection. As of yet, however, the continuous tumour growth models are not sufficiently developed and require extensive computing to obtain parameter estimates. In this article, we provide a detailed description of the underlying assumptions of the continuous tumour growth model, derive new theoretical results for the model, and show how these results may help the development of this modelling framework. In illustrating the approach, we develop a model for mammography screening sensitivity, using a sample of 1901 post-menopausal women diagnosed with invasive breast cancer.

journal_name

Stat Methods Med Res

authors

Isheden G,Humphreys K

doi

10.1177/0962280217734583

subject

Has Abstract

pub_date

2019-03-01 00:00:00

pages

681-702

issue

3

eissn

0962-2802

issn

1477-0334

journal_volume

28

pub_type

杂志文章
  • A Bayesian semiparametric approach with change points for spatial ordinal data.

    abstract::The change-point model has drawn much attention over the past few decades. It can accommodate the jump process, which allows for changes of the effects before and after the change point. Intellectual disability is a long-term disability that impacts performance in cognitive aspects of life and usually has its onset pr...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280212463415

    authors: Cai B,Lawson AB,McDermott S,Aelion CM

    更新日期:2016-04-01 00:00:00

  • Cluster analysis and related techniques in medical research.

    abstract::In this paper we review methods of cluster analysis in the context of classifying patients on the basis of clinical and/or laboratory type observations. Both hierarchical and non-hierarchical methods of clustering are considered, although the emphasis is on the latter type, with particular attention devoted to the mix...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章,评审

    doi:10.1177/096228029200100103

    authors: McLachlan GJ

    更新日期:1992-01-01 00:00:00

  • Practical issues arising in an exploratory analysis evaluating progression-free survival as a surrogate endpoint for overall survival in advanced colorectal cancer.

    abstract::This paper is based on a conference presentation in which several authors presented results from analyses of the same dataset concerning the evaluation of progression-free survival (PFS) as a surrogate endpoint for overall survival in advanced colorectal cancer clinical trials. In evaluating a potential surrogate endp...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280207081860

    authors: Hughes MD

    更新日期:2008-10-01 00:00:00

  • Penalized count data regression with application to hospital stay after pediatric cardiac surgery.

    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

    pub_type: 杂志文章

    doi:10.1177/0962280214530608

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

    更新日期:2016-12-01 00:00:00

  • Gene selection for survival data under dependent censoring: A copula-based approach.

    abstract::Dependent censoring arises in biomedical studies when the survival outcome of interest is censored by competing risks. In survival data with microarray gene expressions, gene selection based on the univariate Cox regression analyses has been used extensively in medical research, which however, is only valid under the ...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280214533378

    authors: Emura T,Chen YH

    更新日期:2016-12-01 00:00:00

  • Multilevel growth curve models that incorporate a random coefficient model for the level 1 variance function.

    abstract::Aim To present a flexible model for repeated measures longitudinal growth data within individuals that allows trends over time to incorporate individual-specific random effects. These may reflect the timing of growth events and characterise within-individual variability which can be modelled as a function of age. Subj...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280217706728

    authors: Goldstein H,Leckie G,Charlton C,Tilling K,Browne WJ

    更新日期:2018-11-01 00:00:00

  • The application of multidimensional scaling methods to epidemiological data.

    abstract::This paper illustrates the use of multidimensional scaling methods (MDS) to examine space-time patterns in epidemic data. The paper begins by outlining the principles of MDS. The model is then formally specified and illustrated by application to two data sets. The first is partly a tutorial example. It uses monthly re...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/096228029500400202

    authors: Cliff AD,Haggett P,Smallman-Raynor MR,Stroup DF,Williamson GD

    更新日期:1995-06-01 00:00:00

  • Statistical methods for HIV dynamic studies in AIDS clinical trials.

    abstract::Studies of HIV dynamics in AIDS research are very important for understanding pathogenesis of HIV infection and for assessing the potency of antiviral therapies. Since the viral dynamic results from clinical data were first published by Ho et al. and Wei et al., the study of HIV-1 dynamics in vivo has drawn a great at...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章,评审

    doi:10.1191/0962280205sm390oa

    authors: Wu H

    更新日期:2005-04-01 00:00:00

  • Unconditional tests for comparing two ordered multinomials.

    abstract::We consider two exact unconditional procedures to test the difference between two multinomials with ordered categorical data. Exact unconditional procedures are compared to other approaches based on the Wilcoxon mid-rank test and the proportional odds model. We use a real example from an arthritis pain study to illust...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280212450957

    authors: Shan G,Ma C

    更新日期:2016-02-01 00:00:00

  • Maximum likelihood estimation based on Newton-Raphson iteration for the bivariate random effects model in test accuracy meta-analysis.

    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

    pub_type: 杂志文章

    doi:10.1177/0962280219853602

    authors: Willis BH,Baragilly M,Coomar D

    更新日期:2020-04-01 00:00:00

  • Statistical modelling of measles and influenza outbreaks.

    abstract::This paper reviews the application of statistical models to outbreaks of two common respiratory viral diseases, measles and influenza. For each disease, we look first at its epidemiological characteristics and assess the extent to which these either aid or hinder modelling. We then turn to the models that have been de...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章,评审

    doi:10.1177/096228029300200104

    authors: Cliff AD,Haggett P

    更新日期:1993-01-01 00:00:00

  • Bayesian spatially dependent variable selection for small area health modeling.

    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

    pub_type: 杂志文章

    doi:10.1177/0962280215627184

    authors: Choi J,Lawson AB

    更新日期:2018-01-01 00:00:00

  • A monotone data augmentation algorithm for longitudinal data analysis via multivariate skew-t, skew-normal or t distributions.

    abstract::The mixed effects model for repeated measures has been widely used for the analysis of longitudinal clinical data collected at a number of fixed time points. We propose a robust extension of the mixed effects model for repeated measures for skewed and heavy-tailed data on basis of the multivariate skew-t distribution,...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280219865579

    authors: Tang Y

    更新日期:2020-06-01 00:00:00

  • Nonparametric estimation of risk tracking indices for longitudinal studies.

    abstract::Tracking a subject's risk factors or health status over time is an important objective in long-term epidemiological studies with repeated measurements. An important issue of time-trend tracking is to define appropriate statistical indices to quantitatively measure the tracking abilities of the targeted risk factors or...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280219839427

    authors: Wu CO,Tian X,Tian L,Reis JP,Zhao L,Allen NB,Bae S,Liu K

    更新日期:2020-02-01 00:00:00

  • Optimal quantile level selection for disease classification and biomarker discovery with application to electrocardiogram data.

    abstract::Classification with a large number of predictors and biomarker discovery become increasingly important in biological and medical research. This paper focuses on performing classification of cardiovascular diseases based on electrocardiogram analysis which deals with many variables and a lot of measurements within vari...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280217699996

    authors: Zhou Y,Huang R,Yu S,Ma Y

    更新日期:2018-11-01 00:00:00

  • Correcting for non-participation bias in health surveys using record-linkage, synthetic observations and pattern mixture modelling.

    abstract::Surveys are key means of obtaining policy-relevant information not available from routine sources. Bias arising from non-participation is typically handled by applying weights derived from limited socio-demographic characteristics. This approach neither captures nor adjusts for differences in health and related behavi...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280219854482

    authors: Gray L,Gorman E,White IR,Katikireddi SV,McCartney G,Rutherford L,Leyland AH

    更新日期:2020-04-01 00:00:00

  • Semi-supervised identification of cancer subgroups using survival outcomes and overlapping grouping information.

    abstract::Identification of cancer patient subgroups using high throughput genomic data is of critical importance to clinicians and scientists because it can offer opportunities for more personalized treatment and overlapping treatments of cancers. In spite of tremendous efforts, this problem still remains challenging because o...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280217752980

    authors: Wei W,Sun Z,da Silveira WA,Yu Z,Lawson A,Hardiman G,Kelemen LE,Chung D

    更新日期:2019-07-01 00:00:00

  • Bayesian nonparametric inference for the three-class Youden index and its associated optimal cutoff points.

    abstract::The three-class Youden index serves both as a measure of medical test accuracy and a criterion to choose the optimal pair of cutoff values for classifying subjects into three ordinal disease categories (e.g. no disease, mild disease, advanced disease). We present a Bayesian nonparametric approach for estimating the th...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280217742538

    authors: Carvalho VI,Branscum AJ

    更新日期:2018-03-01 00:00:00

  • Functional data analysis in longitudinal settings using smoothing splines.

    abstract::Data in many experiments arise as curves and therefore it is natural to use a curve as a basic unit in the analysis, which is termed functional data analysis (FDA). In longitudinal studies, recent developments in FDA have extended classical linear models and linear mixed effects models to functional linear models (als...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章,评审

    doi:10.1191/0962280204sm352ra

    authors: Guo W

    更新日期:2004-02-01 00:00:00

  • Random-effects models for multivariate repeated measures.

    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

    pub_type: 杂志文章

    doi:10.1177/0962280206075305

    authors: Fieuws S,Verbeke G,Molenberghs G

    更新日期:2007-10-01 00:00:00

  • Stochastic models of sequence evolution including insertion-deletion events.

    abstract::Comparison of sequences that have descended from a common ancestor based on an explicit stochastic model of substitutions, insertions and deletions has risen to prominence in the last decade. Making statements about the positions of insertions-deletions (abbr. indels) is central in sequence and genome analysis and is ...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280208099500

    authors: Miklós I,Novák A,Satija R,Lyngsø R,Hein J

    更新日期:2009-10-01 00:00:00

  • A composite likelihood approach to predict the sex of the baby.

    abstract::Couples with diseases associated with the sexual chromosomes, as well as families in countries where the desire for a male is extreme, are interested in influencing the sex of the baby. We propose an original composite likelihood approach to analyse the relation between sex of the newborn and timing of the intercourse...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280217702415

    authors: Tiberi S,Scarpa B,Sartori N

    更新日期:2018-11-01 00:00:00

  • Quantile residual lifetime regression with functional principal component analysis of longitudinal data for dynamic prediction.

    abstract::Optimal therapeutic decisions can be made according to disease prognosis, where the residual lifetime is extensively used because of its straightforward interpretation and formula. To predict the residual lifetime in a dynamic manner, a longitudinal biomarker that is repeatedly measured during the post-baseline follow...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280217753466

    authors: Lin X,Li R,Yan F,Lu T,Huang X

    更新日期:2019-04-01 00:00:00

  • The application of methods to quantify attributable risk in medical practice.

    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

    pub_type: 杂志文章

    doi:10.1177/096228020101000305

    authors: Uter W,Pfahlberg A

    更新日期:2001-06-01 00:00:00

  • Continuous(ly) missing outcome data in network meta-analysis: A one-stage pattern-mixture model approach.

    abstract::Appropriate handling of aggregate missing outcome data is necessary to minimise bias in the conclusions of systematic reviews. The two-stage pattern-mixture model has been already proposed to address aggregate missing continuous outcome data. While this approach is more proper compared with the exclusion of missing co...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280220983544

    authors: Spineli LM,Kalyvas C,Papadimitropoulou K

    更新日期:2021-01-06 00:00:00

  • Underestimation of treatment effects in sequentially monitored clinical trials that did not stop early for benefit.

    abstract::In recent years, there has been a prominent discussion in the literature about the potential for overestimation of the treatment effect when a clinical trial stops at an interim analysis due to the experimental treatment showing a benefit over the control. However, there has been much less attention paid to the conver...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280218795320

    authors: Marschner IC,Schou IM

    更新日期:2019-10-01 00:00:00

  • Statistical methods for multivariate meta-analysis of diagnostic tests: An overview and tutorial.

    abstract::In this article, we present an overview and tutorial of statistical methods for meta-analysis of diagnostic tests under two scenarios: (1) when the reference test can be considered a gold standard and (2) when the reference test cannot be considered a gold standard. In the first scenario, we first review the conventio...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章,评审

    doi:10.1177/0962280213492588

    authors: Ma X,Nie L,Cole SR,Chu H

    更新日期:2016-08-01 00:00:00

  • Unbiasedness and efficiency of non-parametric and UMVUE estimators of the probabilistic index and related statistics.

    abstract::In reliability theory, diagnostic accuracy, and clinical trials, the quantity P ( X > Y ) + ...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280220966629

    authors: Verbeeck J,Deltuvaite-Thomas V,Berckmoes B,Burzykowski T,Aerts M,Thas O,Buyse M,Molenberghs G

    更新日期:2020-12-01 00:00:00

  • A test of inflated zeros for Poisson regression models.

    abstract::Excessive zeros are common in practice and may cause overdispersion and invalidate inference when fitting Poisson regression models. There is a large body of literature on zero-inflated Poisson models. However, methods for testing whether there are excessive zeros are less well developed. The Vuong test comparing a Po...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280217749991

    authors: He H,Zhang H,Ye P,Tang W

    更新日期:2019-04-01 00:00:00

  • Projections of cancer mortality risks using spatio-temporal P-spline models.

    abstract::Cancer mortality risk estimates are essential for planning resource allocation and designing and evaluating cancer prevention and management strategies. However, mortality figures generally become available after a few years, making necessary to develop reliable procedures to provide current and near future mortality ...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280212446366

    authors: Ugarte MD,Goicoa T,Etxeberria J,Militino AF

    更新日期:2012-10-01 00:00:00