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 of low reproducibility and instability of identified cancer subgroups and molecular features. In order to address this challenge, we developed Integrative Genomics Robust iDentification of cancer subgroups (InGRiD), a statistical approach that integrates information from biological pathway databases with high-throughput genomic data to improve the robustness for identification and interpretation of molecularly-defined subgroups of cancer patients. We applied InGRiD to the gene expression data of high-grade serous ovarian cancer from The Cancer Genome Atlas and the Australian Ovarian Cancer Study. The results indicate clear benefits of the pathway-level approaches over the gene-level approaches. In addition, using the proposed InGRiD framework, we also investigate and address the issue of gene sharing among pathways, which often occurs in practice, to further facilitate biological interpretation of key molecular features associated with cancer progression. The R package "InGRiD" implementing the proposed approach is currently available in our research group GitHub webpage ( https://dongjunchung.github.io/INGRID/ ).
journal_name
Stat Methods Med Resjournal_title
Statistical methods in medical researchauthors
Wei W,Sun Z,da Silveira WA,Yu Z,Lawson A,Hardiman G,Kelemen LE,Chung Ddoi
10.1177/0962280217752980subject
Has Abstractpub_date
2019-07-01 00:00:00pages
2137-2149issue
7eissn
0962-2802issn
1477-0334journal_volume
28pub_type
杂志文章abstract::With the emergence of rich information on biomarkers after treatments, new types of prognostic tools are being developed: dynamic prognostic tools that can be updated at each new biomarker measurement. Such predictions are of interest in oncology where after an initial treatment, patients are monitored with repeated b...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280214535763
更新日期:2016-12-01 00:00:00
abstract::Agreement between two methods of clinical measurement can be quantified using the differences between observations made using the two methods on the same subjects. The 95% limits of agreement, estimated by mean difference +/- 1.96 standard deviation of the differences, provide an interval within which 95% of differenc...
journal_title:Statistical methods in medical research
pub_type: 杂志文章,评审
doi:10.1177/096228029900800204
更新日期:1999-06-01 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
pub_type: 杂志文章
doi:10.1177/0962280214526193
更新日期:2016-12-01 00:00:00
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
pub_type: 杂志文章,评审
doi:10.1177/096228020000900603
更新日期:2000-12-01 00:00:00
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,...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280217735560
更新日期:2019-03-01 00:00:00
abstract::Guarding against false positive selections is important in many applications. We discuss methods based on subsampling and sample splitting for controlling the expected number of false positives and assigning p-values. They are generic and especially useful for high-dimensional settings. We review encouraging results f...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280211428371
更新日期:2013-10-01 00:00:00
abstract::Increasing the clinical applicability of functional neuroimaging technology is an emerging objective, e.g. for diagnostic and treatment purposes. We propose a novel Bayesian spatial hierarchical framework for predicting follow-up neural activity based on an individual's baseline functional neuroimaging data. Our appro...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280212448972
更新日期:2013-08-01 00:00:00
abstract::Propensity score methods are common for estimating a binary treatment effect when treatment assignment is not randomized. When exposure is measured on an ordinal scale (i.e. low-medium-high), however, propensity score inference requires extensions which have received limited attention. Estimands of possible interest w...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280214560046
更新日期:2017-04-01 00:00:00
abstract::The statistical analysis of genome-wide association studies (GWASs) with multiple diseases and shared controls (SCs) is discussed. The usual method for analyzing data from these studies is to compare each individual disease with either the SCs or the pooled controls which include other diseases. We observed that apply...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280212474061
更新日期:2016-04-01 00:00:00
abstract::A growing body of evidence suggests that genetic factors have an important influence on the onset and course of smoking. Here we review some of the statistical methods that have been used to test for genetic influences on smoking behaviour, with a particular focus on studies of large national twin samples. We show how...
journal_title:Statistical methods in medical research
pub_type: 杂志文章,评审
doi:10.1177/096228029800700205
更新日期:1998-06-01 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
pub_type: 杂志文章
doi:10.1177/0962280220921912
更新日期:2020-11-01 00:00:00
abstract::This paper reviews recent developments by the Washington/Brown groups for the study of anatomical shape in the emerging new discipline of computational anatomy. Parametric representations of anatomical variation for computational anatomy are reviewed, restricted to the assumption of small deformations. The generation ...
journal_title:Statistical methods in medical research
pub_type: 杂志文章,评审
doi:10.1177/096228029700600305
更新日期:1997-09-01 00:00:00
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
更新日期:2020-04-01 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
pub_type: 杂志文章
doi:10.1177/0962280214524178
更新日期:2016-12-01 00:00:00
abstract::We propose a hierarchical Bayesian methodology to model spatially or spatio-temporal clustered survival data with possibility of cure. A flexible continuous transformation class of survival curves indexed by a single parameter is used. This transformation model is a larger class of models containing two special cases ...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280212445658
更新日期:2016-02-01 00:00:00
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
更新日期:2019-05-01 00:00:00
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
更新日期:2016-08-01 00:00:00
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
更新日期:2016-12-01 00:00:00
abstract::We often seek to estimate the impact of an exposure naturally occurring or randomly assigned at the cluster-level. For example, the literature on neighborhood determinants of health continues to grow. Likewise, community randomized trials are applied to learn about real-world implementation, sustainability, and popula...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280218774936
更新日期:2019-06-01 00:00:00
abstract::One purpose of a longitudinal study is to gain a better understanding of how an outcome of interest changes among a given population over time. In what follows, a trajectory will be taken to mean the series of measurements of the outcome variable for an individual. Group-based trajectory modelling methods seek to iden...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280215598806
更新日期:2017-08-01 00:00:00
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
更新日期:2018-06-01 00:00:00
abstract:BACKGROUND:Recent literature on the comparison of machine learning methods has raised questions about the neutrality, unbiasedness and utility of many comparative studies. Reporting of results on favourable datasets and sampling error in the estimated performance measures based on single samples are thought to be the m...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280213502437
更新日期:2016-10-01 00:00:00
abstract::We propose a novel likelihood method for analyzing time-to-event data when multiple events and multiple missing data intervals are possible prior to the first observed event for a given subject. This research is motivated by data obtained from a heart monitor used to track the recovery process of subjects experiencing...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280212466089
更新日期:2016-04-01 00:00:00
abstract::In recent years, disease mapping studies have become a routine application within geographical epidemiology and are typically analysed within a Bayesian hierarchical model formulation. A variety of model formulations for the latent level have been proposed but all come with inherent issues. In the classical BYM (Besag...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280216660421
更新日期:2016-08-01 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
pub_type: 杂志文章
doi:10.1177/0962280210370265
更新日期:2011-04-01 00:00:00
abstract::Sensitive questions are often involved in healthcare or medical survey research. Much empirical evidence has shown that the randomized response technique is useful for the collection of truthful responses. However, few studies have discussed methods to estimate the dependence of sensitive responses of multiple types. ...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280219847492
更新日期:2020-03-01 00:00:00
abstract::We review recent work on the application of pseudo-observations in survival and event history analysis. This includes regression models for parameters like the survival function in a single point, the restricted mean survival time and transition or state occupation probabilities in multi-state models, e.g. the competi...
journal_title:Statistical methods in medical research
pub_type: 杂志文章,评审
doi:10.1177/0962280209105020
更新日期:2010-02-01 00:00:00
abstract::Exposure measurement error in epidemiological studies is recognized as a feature that must be considered because of the potential bias that can result in estimates of the exposure-disease association. Most of the work to date has focused on methods of analysis that adjust for the resultant bias, but the implications o...
journal_title:Statistical methods in medical research
pub_type: 杂志文章,评审
doi:10.1177/096228029500400405
更新日期:1995-12-01 00:00:00
abstract::Simple mechanistic epidemic models are widely used for forecasting and parameter estimation of infectious diseases based on noisy case reporting data. Despite the widespread application of models to emerging infectious diseases, we know little about the comparative performance of standard computational-statistical fra...
journal_title:Statistical methods in medical research
pub_type: 杂志文章
doi:10.1177/0962280217747054
更新日期:2018-07-01 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
pub_type: 杂志文章
doi:10.1177/0962280214527385
更新日期:2014-12-01 00:00:00