Adjustment for treatment changes in epilepsy trials: A comparison of causal methods for time-to-event outcomes.

Abstract:

BACKGROUND:When trials are subject to departures from randomised treatment, simple statistical methods that aim to estimate treatment efficacy, such as per protocol or as treated analyses, typically introduce selection bias. More appropriate methods to adjust for departure from randomised treatment are rarely employed, primarily due to their complexity and unfamiliarity. We demonstrate the use of causal methodologies for the production of estimands with valid causal interpretation for time-to-event outcomes in the analysis of a complex epilepsy trial, as an example to guide non-specialist analysts undertaking similar analyses. METHODS:Two causal methods, the structural failure time model and inverse probability of censoring weighting, are adapted to allow for skewed time-varying confounders, competing reasons for treatment changes and a complicated time to remission outcome. We demonstrate the impact of various factors: choice of method (structural failure time model versus inverse probability of censoring weighting), model for inverse probability of censoring weighting (pooled logistic regression versus Cox models), time interval (for creating panel data for time-varying confounders and outcome), choice of confounders and (in pooled logistic regression) use of splines to estimate underlying risk. RESULTS:The structural failure time model could adjust for switches between trial treatments but had limited ability to adjust for the other treatment changes that occurred in this epilepsy trial. Inverse probability of censoring weighting was able to adjust for all treatment changes and demonstrated very similar results with Cox and pooled logistic regression models. Accounting for increasing numbers of time-varying confounders and reasons for treatment change suggested a more pronounced advantage of the control treatment than that obtained using intention to treat. CONCLUSIONS:In a complex trial featuring a remission outcome, underlying assumptions of the structural failure time model are likely to be violated, and inverse probability of censoring weighting may provide the most useful option, assuming availability of appropriate data and sufficient sample sizes. Recommendations are provided for analysts when considering which of these methods should be applied in a given trial setting.

journal_name

Stat Methods Med Res

authors

Dodd S,Williamson P,White IR

doi

10.1177/0962280217735560

subject

Has Abstract

pub_date

2019-03-01 00:00:00

pages

717-733

issue

3

eissn

0962-2802

issn

1477-0334

journal_volume

28

pub_type

杂志文章
  • Testing hypotheses under adaptive randomization with continuous covariates in clinical trials.

    abstract::Covariate-adaptive designs are widely used to balance covariates and maintain randomization in clinical trials. Adaptive designs for discrete covariates and their asymptotic properties have been well studied in the literature. However, important continuous covariates are often involved in clinical studies. Simply disc...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280218770231

    authors: Li X,Zhou J,Hu F

    更新日期:2019-06-01 00:00:00

  • Bayesian latent structure modeling of walking behavior in a physical activity intervention.

    abstract::The analysis of walking behavior in a physical activity intervention is considered. A Bayesian latent structure modeling approach is proposed whereby the ability and willingness of participants is modeled via latent effects. The dropout process is jointly modeled via a linked survival model. Computational issues are a...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280214529932

    authors: Lawson AB,Ellerbe C,Carroll R,Alia K,Coulon S,Wilson DK,VanHorn ML,George SM

    更新日期:2016-12-01 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

  • Components of variance in a group-randomized trial analysed via a random-coefficients model: the Rapid Early Action for Coronary Treatment (REACT) trial.

    abstract::Rapid Early Action for Coronary Treatment (REACT) was a multisite trial testing a community intervention to reduce the delay between onset of symptoms of acute myocardial infarction (MI) and patients' arrival at a hospital emergency department. The study employed a group-randomized trial design, with ten communities r...

    journal_title:Statistical methods in medical research

    pub_type: 临床试验,杂志文章,随机对照试验

    doi:10.1177/096228020000900204

    authors: Murray DM,Feldman HA,McGovern PG

    更新日期:2000-04-01 00:00:00

  • A new diagnostic accuracy measure and cut-point selection criterion.

    abstract::Most diagnostic accuracy measures and criteria for selecting optimal cut-points are only applicable to diseases with binary or three stages. Currently, there exist two diagnostic measures for diseases with general k stages: the hypervolume under the manifold and the generalized Youden index. While hypervolume under th...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280215611631

    authors: Dong T,Attwood K,Hutson A,Liu S,Tian L

    更新日期:2017-12-01 00:00:00

  • A mixed-effects, spatially varying coefficients model with application to multi-resolution functional magnetic resonance imaging data.

    abstract::Spatial resolution plays an important role in functional magnetic resonance imaging studies as the signal-to-noise ratio increases linearly with voxel volume. In scientific studies, where functional magnetic resonance imaging is widely used, the standard spatial resolution typically used is relatively low which ensure...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280217752378

    authors: Liu Z,Bartsch AJ,Berrocal VJ,Johnson TD

    更新日期:2019-04-01 00:00:00

  • The asymptotic maximal procedure for subject randomization in clinical trials.

    abstract::The maximal procedure is a restricted randomization method that maximizes the number of feasible allocation sequences under the constraints of the maximum tolerated imbalance and the allocation sequence length. It assigns an equal probability to all feasible sequences. However, its implementation is not easy due to th...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280216677107

    authors: Zhao W,Berger VW,Yu Z

    更新日期:2018-07-01 00:00:00

  • A non-parametric model to address overdispersed count response in a longitudinal data setting with missingness.

    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

    pub_type: 杂志文章

    doi:10.1177/0962280215583397

    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

  • Meta-analysis without study-specific variance information: Heterogeneity case.

    abstract::The random effects model in meta-analysis is a standard statistical tool often used to analyze the effect sizes of the quantity of interest if there is heterogeneity between studies. In the special case considered here, meta-analytic data contain only the sample means in two treatment arms and the sample sizes, but no...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280217718867

    authors: Sangnawakij P,Böhning D,Niwitpong SA,Adams S,Stanton M,Holling H

    更新日期:2019-01-01 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

  • Model selection in multivariate semiparametric regression.

    abstract::Variable selection in semiparametric mixed models for longitudinal data remains a challenge, especially in the presence of multiple correlated outcomes. In this paper, we propose a model selection procedure that simultaneously selects fixed and random effects using a maximum penalized likelihood method with the adapti...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280217690769

    authors: Li Z,Liu H,Tu W

    更新日期:2018-10-01 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

  • Sample size calculation for treatment effects in randomized trials with fixed cluster sizes and heterogeneous intraclass correlations and variances.

    abstract::When comparing two different kinds of group therapy or two individual treatments where patients within each arm are nested within care providers, clustering of observations may occur in both arms. The arms may differ in terms of (a) the intraclass correlation, (b) the outcome variance, (c) the cluster size, and (d) th...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280214563100

    authors: Candel MJ,van Breukelen GJ

    更新日期:2015-10-01 00:00:00

  • A quick and accurate method for the estimation of covariate effects based on empirical Bayes estimates in mixed-effects modeling: Correction of bias due to shrinkage.

    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

    pub_type: 杂志文章

    doi:10.1177/0962280218812595

    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

  • Joint latent class models for longitudinal and time-to-event data: a review.

    abstract::Most statistical developments in the joint modelling area have focused on the shared random-effect models that include characteristics of the longitudinal marker as predictors in the model for the time-to-event. A less well-known approach is the joint latent class model which consists in assuming that a latent class s...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章,评审

    doi:10.1177/0962280212445839

    authors: Proust-Lima C,Séne M,Taylor JM,Jacqmin-Gadda H

    更新日期:2014-02-01 00:00:00

  • Pattern discovery of health curves using an ordered probit model with Bayesian smoothing and functional principal component analysis.

    abstract::This article is motivated by the need for discovering patterns of patients' health based on their daily settings of care to aid the health policy-makers to improve the effectiveness of distributing funding for health services. The hidden process of one's health status is assumed to be a continuous smooth function, cal...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280220951834

    authors: Wang S,Nie Y,Sutherland JM,Wang L

    更新日期:2020-09-25 00:00:00

  • Relative efficiency of unequal cluster sizes for variance component estimation in cluster randomized and multicentre trials.

    abstract::Cluster randomized and multicentre trials evaluate the effect of a treatment on persons nested within clusters, for instance patients within clinics or pupils within schools. Although equal sample sizes per cluster are generally optimal for parameter estimation, they are rarely feasible. This paper addresses the relat...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280206079018

    authors: van Breukelen GJ,Candel MJ,Berger MP

    更新日期:2008-08-01 00:00:00

  • Modelling of zero-inflation improves inference of metagenomic gene count data.

    abstract::Metagenomics enables the study of gene abundances in complex mixtures of microorganisms and has become a standard methodology for the analysis of the human microbiome. However, gene abundance data is inherently noisy and contains high levels of biological and technical variability as well as an excess of zeros due to ...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280218811354

    authors: Jonsson V,Österlund T,Nerman O,Kristiansson E

    更新日期:2019-12-01 00:00:00

  • A measure of association for ordered categorical data in population-based studies.

    abstract::Ordinal classification scales are commonly used to define a patient's disease status in screening and diagnostic tests such as mammography. Challenges arise in agreement studies when evaluating the association between many raters' classifications of patients' disease or health status when an ordered categorical scale ...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280216643347

    authors: Nelson KP,Edwards D

    更新日期:2018-03-01 00:00:00

  • Obtaining evidence by a single well-powered trial or several modestly powered trials.

    abstract::There is debate whether clinical trials with suboptimal power are justified and whether results from large studies are more reliable than the (combined) results of smaller trials. We quantified the error rates for evaluations based on single conventionally powered trials (80% or 90% power) versus evaluations based on ...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280212461098

    authors: IntHout J,Ioannidis JP,Borm GF

    更新日期:2016-04-01 00:00:00

  • Separating variability in healthcare practice patterns from random error.

    abstract::Improving the quality of care that patients receive is a major focus of clinical research, particularly in the setting of cardiovascular hospitalization. Quality improvement studies seek to estimate and visualize the degree of variability in dichotomous treatment patterns and outcomes across different providers, where...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280217754230

    authors: Thomas LE,Schulte PJ

    更新日期:2019-04-01 00:00:00

  • Measuring diagnostic accuracy for biomarkers under tree-ordering.

    abstract::In the field of diagnostic studies for tree or umbrella ordering, under which the marker measurement for one class is lower or higher than those for the rest unordered classes, there exist a few diagnostic measures such as the naive AUC ( NAUC), the umbrella volume ( UV), and the recently proposed TAUC, i.e. area unde...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280218755810

    authors: Feng Y,Tian L

    更新日期:2019-05-01 00:00:00

  • Time-dependent efficacy of longitudinal biomarker for clinical endpoint.

    abstract::Joint modelling of longitudinal biomarker and event-time processes has gained its popularity in recent years as they yield more accurate and precise estimates. Considering this modelling framework, a new methodology for evaluating the time-dependent efficacy of a longitudinal biomarker for clinical endpoint is propose...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280216673084

    authors: Kolamunnage-Dona R,Williamson PR

    更新日期:2018-06-01 00:00:00

  • Propensity scores: from naive enthusiasm to intuitive understanding.

    abstract::Estimation of the effect of a binary exposure on an outcome in the presence of confounding is often carried out via outcome regression modelling. An alternative approach is to use propensity score methodology. The propensity score is the conditional probability of receiving the exposure given the observed covariates a...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280210394483

    authors: Williamson E,Morley R,Lucas A,Carpenter J

    更新日期:2012-06-01 00:00:00

  • Small sample sizes: A big data problem in high-dimensional data analysis.

    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

    pub_type: 杂志文章

    doi:10.1177/0962280220970228

    authors: Konietschke F,Schwab K,Pauly M

    更新日期:2020-11-24 00:00:00

  • A kernel-based spatio-temporal surveillance system for monitoring influenza-like illness incidence.

    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

    pub_type: 杂志文章

    doi:10.1177/0962280210370265

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

    更新日期:2011-04-01 00:00:00

  • Towards joint disease mapping.

    abstract::This article discusses and extends statistical models to jointly analyse the spatial variation of rates of several diseases with common risk factors. We start with a review of methods for separate analyses of diseases, then move to ecological regression approaches, where the rates from one of the diseases enter as sur...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章,评审

    doi:10.1191/0962280205sm389oa

    authors: Held L,Natário I,Fenton SE,Rue H,Becker N

    更新日期:2005-02-01 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

  • Inferential tools in penalized logistic regression for small and sparse data: A comparative study.

    abstract::This paper focuses on inferential tools in the logistic regression model fitted by the Firth penalized likelihood. In this context, the Likelihood Ratio statistic is often reported to be the preferred choice as compared to the 'traditional' Wald statistic. In this work, we consider and discuss a wider range of test st...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280216661213

    authors: Siino M,Fasola S,Muggeo VM

    更新日期:2018-05-01 00:00:00

  • A unified approach for assessing heterogeneity in age-period-cohort model parameters using random effects.

    abstract::Age-period-cohort models are a popular tool for studying population-level rates; for example, trends in cancer incidence and mortality. Age-period-cohort models decompose observed trends into age effects that correlate with natural history, period effects that reveal factors impacting all ages simultaneously (e.g. inn...

    journal_title:Statistical methods in medical research

    pub_type: 杂志文章

    doi:10.1177/0962280217713033

    authors: Chernyavskiy P,Little MP,Rosenberg PS

    更新日期:2019-01-01 00:00:00