Statistical Methods for Longitudinal Data and Meta-Analysis
Lead Research Organisation:
MRC Biostatistics Unit
Department Name: UNLISTED
Abstract
One aspect of my work is to develop statistical methods to analyse data from the UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS). Data from this trial consists of up to six annual sets of questionnaires from each participant. The questionnaires assess anxiety, sexual function and acceptability of the screening process. I will model how these three processes change over time, and how they depend on one another. There are several approaches to analysing this type of data, and I will explore the pros and cons of three different methods. The challenge in this work lies in the complexity of the UKCTOCS data-set. I will also use some of these methods to analyse data from the MRC Cognitive Function and Ageing Study.
A second aspect of my work is to develop methods for use in meta-analysis. Meta-analysis refers to the pooling of data from different studies, and is used to provide an overview of the available evidence. I will investigate methods for the meta-analysis of data which consists of times to events. I will also explore the meta-analysis of treatment `networks', investigating the relative effects of a set of treatments for a given condition.
A second aspect of my work is to develop methods for use in meta-analysis. Meta-analysis refers to the pooling of data from different studies, and is used to provide an overview of the available evidence. I will investigate methods for the meta-analysis of data which consists of times to events. I will also explore the meta-analysis of treatment `networks', investigating the relative effects of a set of treatments for a given condition.
Technical Summary
Objective: to carry out a diverse program of original research in biostatistics, incorporating two broad research areas, longitudinal data analysis and meta-analysis.
Longitudinal data analysis: My research will be motivated by two studies, the MRC Cognitive Function and Ageing Study (CFAS) and the UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS). Regarding MRC CFAS, our aim is to model simultaneously two processes - cognitive impairment and death. From this study we have interval-censored data with possibly informative loss-to-followup. We will use a five-state model, with loss-to-followup as an explicit state in the model. We will fit the model using maximum likelihood, imposing constraints to make all parameters identifiable. For the UKCTOCS trial we again have longitudinal data in the form of annual questionnaires. Our aim is to model simultaneously three outcomes of the trial, anxiety, sexual function, and the acceptability of two screening procedures. We will compare three different methods of analysis, random effects, dynamic variables and multi-state models. We will explore the pros and cons of these three methods in addressing the objectives of the UKCTOCS study, such as the effect of treatment allocation on outcomes, and identifying causal relations between the outcomes. Additional complexities which we will address are the inclusion of baseline covariates, adjustments for individual/treatment interactions, the possibility of informative loss-to-followup and multiplicity.
Meta-analysis: My research will focus on the individual patient data meta-analysis of time-to-event outcomes and on multiple treatment meta-analysis. For the meta-analysis of time-to-event outcomes we will explore alternatives to the use of the proportional hazards assumption, for example the use of accelerated failure time models. We will also develop non-parametric methods for constructing a summary survival curve. In multiple treatment meta-analysis we will investigate methods of allowing for inconsistency between direct and indirect evidence. We will model the inconsistency as a treatment by study `design' interaction, where the `design' of a study here means the set of treatments used in the study.
Scientific opportunities: The applications of my research are very topical, and results will be of interest to the wider medical community. In addition, methodological developments will be of use to the statistical community in a variety of other applications.
Longitudinal data analysis: My research will be motivated by two studies, the MRC Cognitive Function and Ageing Study (CFAS) and the UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS). Regarding MRC CFAS, our aim is to model simultaneously two processes - cognitive impairment and death. From this study we have interval-censored data with possibly informative loss-to-followup. We will use a five-state model, with loss-to-followup as an explicit state in the model. We will fit the model using maximum likelihood, imposing constraints to make all parameters identifiable. For the UKCTOCS trial we again have longitudinal data in the form of annual questionnaires. Our aim is to model simultaneously three outcomes of the trial, anxiety, sexual function, and the acceptability of two screening procedures. We will compare three different methods of analysis, random effects, dynamic variables and multi-state models. We will explore the pros and cons of these three methods in addressing the objectives of the UKCTOCS study, such as the effect of treatment allocation on outcomes, and identifying causal relations between the outcomes. Additional complexities which we will address are the inclusion of baseline covariates, adjustments for individual/treatment interactions, the possibility of informative loss-to-followup and multiplicity.
Meta-analysis: My research will focus on the individual patient data meta-analysis of time-to-event outcomes and on multiple treatment meta-analysis. For the meta-analysis of time-to-event outcomes we will explore alternatives to the use of the proportional hazards assumption, for example the use of accelerated failure time models. We will also develop non-parametric methods for constructing a summary survival curve. In multiple treatment meta-analysis we will investigate methods of allowing for inconsistency between direct and indirect evidence. We will model the inconsistency as a treatment by study `design' interaction, where the `design' of a study here means the set of treatments used in the study.
Scientific opportunities: The applications of my research are very topical, and results will be of interest to the wider medical community. In addition, methodological developments will be of use to the statistical community in a variety of other applications.
Organisations
- MRC Biostatistics Unit (Lead Research Organisation)
- National and Kapodistrian University of Athens (Collaboration)
- University of Copenhagen (Collaboration)
- Lancaster University (Collaboration)
- Newcastle University (Collaboration)
- Toronto Western Hospital (Collaboration)
- Hospital Sirio Libanes, Sao Paulo (Collaboration)
- UNIVERSITY OF CAMBRIDGE (Collaboration)
- The Cochrane Collaboration (Collaboration)
- University of California, Berkeley (Collaboration)
- University of Sussex (Collaboration)
- UNIVERSITY OF LIVERPOOL (Collaboration)
- Medical Research Council (MRC) (Collaboration)
People |
ORCID iD |
Jessica Barrett (Principal Investigator) |
Publications
Jackson D
(2014)
A design-by-treatment interaction model for network meta-analysis with random inconsistency effects.
in Statistics in medicine
Barrett JK
(2011)
A semi-competing risks model for data with interval-censoring and informative observation: an application to the MRC cognitive function and ageing study.
in Statistics in medicine
Fallowfield L
(2010)
Awareness of ovarian cancer risk factors, beliefs and attitudes towards screening: baseline survey of 21,715 women participating in the UK Collaborative Trial of Ovarian Cancer Screening.
in British journal of cancer
Higgins J
(2012)
Consistency and inconsistency in network meta-analysis: concepts and models for multi-arm studies
in Research Synthesis Methods
White IR
(2012)
Consistency and inconsistency in network meta-analysis: model estimation using multivariate meta-regression.
in Research synthesis methods
Barrett J
(2013)
Doubly Robust Estimation of Optimal Dynamic Treatment Regimes
in Statistics in Biosciences
Barrett J
(2017)
Dynamic predictions using flexible joint models of longitudinal and time-to-event data.
in Statistics in medicine
Taylor-Robinson D
(2020)
Explaining the Sex Effect on Survival in Cystic Fibrosis: a Joint Modeling Study of UK Registry Data.
in Epidemiology (Cambridge, Mass.)
Jackson D
(2016)
Extending DerSimonian and Laird's methodology to perform network meta-analyses with random inconsistency effects.
in Statistics in medicine
Description | Allele associations with psoriatic disease |
Geographic Reach | Multiple continents/international |
Policy Influence Type | Citation in clinical reviews |
Description | Methods for detecting inconsistency in meta-analysis |
Geographic Reach | Multiple continents/international |
Policy Influence Type | Citation in systematic reviews |
Description | Methods for detecting inconsistency in network meta-analysis |
Geographic Reach | Multiple continents/international |
Policy Influence Type | Citation in systematic reviews |
Description | Methods for detecting the presence of inconsistency in network meta-analysis |
Geographic Reach | Multiple continents/international |
Policy Influence Type | Citation in systematic reviews |
Description | Stem cell therapy for Parkinsons disease |
Geographic Reach | Multiple continents/international |
Policy Influence Type | Citation in clinical reviews |
Description | MRC Early Career Centenary Award Fellowship Scheme |
Amount | £53,000 (GBP) |
Organisation | Medical Research Council (MRC) |
Sector | Public |
Country | United Kingdom |
Start | 09/2012 |
End | 09/2013 |
Title | Discrete-time joint modelling |
Description | New method for fitting joint models of longitudinal and survival data when there is a discrete survival timescale. |
Type Of Material | Data analysis technique |
Year Produced | 2015 |
Provided To Others? | Yes |
Impact | The method is being applied in one clinical paper in preparation and the method has been further developed in one published paper and one paper in preparation. |
Title | Inconsistency in network meta-analysis |
Description | Development of a new method for detecting inconsistecny in netowrk meta-analysis. |
Type Of Material | Data analysis technique |
Year Produced | 2012 |
Provided To Others? | Yes |
Impact | The papers describing the method have been highly cited in over 200 paperss, including systematic reviews, the PRISMA extension statement for reporting of systematic reviews incorporating network meta-analyses of health care interventions and the GRADE Working Group approach for rating the quality of treatment effect estimates from network meta-analysis. |
Title | Two-stage Bayesian modelling |
Description | New method for fitting a Bayesian model in two stages. |
Type Of Material | Data analysis technique |
Year Produced | 2013 |
Provided To Others? | Yes |
Impact | The methods in this paper underpin new reserch on Markov melding, a more general modular approach to fitting Bayesian models. |
Description | Breast cancer systematic reviews |
Organisation | Hospital Sirio Libanes, Sao Paulo |
Country | Brazil |
Sector | Hospitals |
PI Contribution | Intellectual input, writing and data analysis. |
Collaborator Contribution | Intellectual input, literature searches, data extraction and analyses. |
Impact | One Cochrane review has been published. A second Cochrane review is under review. A third paper has been published in Reports of Practical Oncology and Radiotherapy. |
Start Year | 2012 |
Description | Breast cancer systematic reviews |
Organisation | The Cochrane Collaboration |
Department | Brazilian Cochrane Centre (BCC) |
Country | Brazil |
Sector | Charity/Non Profit |
PI Contribution | Intellectual input, writing and data analysis. |
Collaborator Contribution | Intellectual input, literature searches, data extraction and analyses. |
Impact | One Cochrane review has been published. A second Cochrane review is under review. A third paper has been published in Reports of Practical Oncology and Radiotherapy. |
Start Year | 2012 |
Description | CFAS |
Organisation | National and Kapodistrian University of Athens |
Department | Department of Mathematics |
Country | Greece |
Sector | Academic/University |
PI Contribution | Intellectual input |
Collaborator Contribution | Intellectual input |
Impact | 1 article published in Statistics in Medicine, DOI 10.1002/sim.4071 |
Start Year | 2008 |
Description | CFAS |
Organisation | University of Cambridge |
Department | MRC Biostatistics Unit |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Intellectual input |
Collaborator Contribution | Intellectual input |
Impact | 1 article published in Statistics in Medicine, DOI 10.1002/sim.4071 |
Start Year | 2008 |
Description | Cystic fibrosis |
Organisation | Lancaster University |
Department | Faculty of Health and Medicine |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Intellectual input, data analysis, writing. |
Collaborator Contribution | Intellectual input, writing |
Impact | Article published in JRSSB, DOI 10.1111/rssb.12060. A second paper is ready for submission. |
Start Year | 2011 |
Description | Cystic fibrosis |
Organisation | Newcastle University |
Department | School of Mathematics and Statistics |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Intellectual input, data analysis, writing. |
Collaborator Contribution | Intellectual input, writing |
Impact | Article published in JRSSB, DOI 10.1111/rssb.12060. A second paper is ready for submission. |
Start Year | 2011 |
Description | Cystic fibrosis |
Organisation | University of Liverpool |
Department | Institute of Psychology, Health and Society |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Intellectual input, data analysis, writing. |
Collaborator Contribution | Intellectual input, writing |
Impact | Article published in JRSSB, DOI 10.1111/rssb.12060. A second paper is ready for submission. |
Start Year | 2011 |
Description | Dynamic treatment regimes |
Organisation | Newcastle University |
Department | School of Mathematics and Statistics |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Intellectual input |
Collaborator Contribution | Intellectual input |
Impact | 2 papers published for Statistics in Biosciences, DOIs 10.1007/s12561-013-9097-6 and 10.1007/s12561-013-9107-8. |
Start Year | 2011 |
Description | Dynamic treatment regimes |
Organisation | University of Copenhagen |
Department | Department of Public Health |
Country | Denmark |
Sector | Academic/University |
PI Contribution | Intellectual input |
Collaborator Contribution | Intellectual input |
Impact | 2 papers published for Statistics in Biosciences, DOIs 10.1007/s12561-013-9097-6 and 10.1007/s12561-013-9107-8. |
Start Year | 2011 |
Description | Meta-analysis of survival data |
Organisation | Medical Research Council (MRC) |
Department | MRC Clinical Trials Unit |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Intellectual input |
Collaborator Contribution | Provision of data and Intellectual input |
Impact | 2 journal articles published in Statistics in Medicine (DOIs 10.1002/sim.4086 and 10.1002/sim.5516) |
Start Year | 2007 |
Description | Meta-analysis of survival data |
Organisation | National and Kapodistrian University of Athens |
Department | Department of Mathematics |
Country | Greece |
Sector | Academic/University |
PI Contribution | Intellectual input |
Collaborator Contribution | Provision of data and Intellectual input |
Impact | 2 journal articles published in Statistics in Medicine (DOIs 10.1002/sim.4086 and 10.1002/sim.5516) |
Start Year | 2007 |
Description | Meta-analysis of survival data |
Organisation | University of Cambridge |
Department | MRC Biostatistics Unit |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Intellectual input |
Collaborator Contribution | Provision of data and Intellectual input |
Impact | 2 journal articles published in Statistics in Medicine (DOIs 10.1002/sim.4086 and 10.1002/sim.5516) |
Start Year | 2007 |
Description | Network meta-analysis |
Organisation | University of Cambridge |
Department | MRC Biostatistics Unit |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Intellectual input and statistical program code |
Collaborator Contribution | Intellectual input |
Impact | 2 journal articles published in Research Synthesis Methods (DOIs 10.1002/jrsm.1044 and 10.1002/jrsm.1045), 2 articles published for Statistics in Medicine (DOIs 10.1002/sim.6188 and 10.1002/sim.6752) |
Start Year | 2009 |
Description | Parkinsons |
Organisation | University of Cambridge |
Department | Department of Clinical Neurosciences |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Intellectual input and data analysis |
Collaborator Contribution | Intellectual input |
Impact | 1 paper published in the Lancet Neurology, DOI 10.1016/S1474-4422(12)70295-8 |
Start Year | 2009 |
Description | Psoriatic Arthritis |
Organisation | Toronto Western Hospital |
Department | University of Toronto Psoriatic Arthritis Clinic |
Country | Canada |
Sector | Public |
PI Contribution | Data analysis |
Collaborator Contribution | Provision of data and intellectual input |
Impact | 3 journal articles (DOIs 10.3899/jrheum.090412 , 10.1111/j.1399-0039.2011.01670.x and 10.1111/tan.12126) |
Start Year | 2007 |
Description | Psoriatic Arthritis |
Organisation | University of Cambridge |
Department | MRC Biostatistics Unit |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Data analysis |
Collaborator Contribution | Provision of data and intellectual input |
Impact | 3 journal articles (DOIs 10.3899/jrheum.090412 , 10.1111/j.1399-0039.2011.01670.x and 10.1111/tan.12126) |
Start Year | 2007 |
Description | Splines for joint modelling |
Organisation | Medical Research Council (MRC) |
Country | United Kingdom |
Sector | Public |
PI Contribution | Intellectual input and writing computer code |
Collaborator Contribution | Intellectual input |
Impact | One paper published in Statistics in Medicine, and one paper published in Biometrics. |
Start Year | 2013 |
Description | Splines for joint modelling |
Organisation | University of California, Berkeley |
Department | Department of Integrative Biology |
Country | United States |
Sector | Academic/University |
PI Contribution | Intellectual input and writing computer code |
Collaborator Contribution | Intellectual input |
Impact | One paper published in Statistics in Medicine, and one paper published in Biometrics. |
Start Year | 2013 |
Description | Two-stage Bayesian meta-analysis |
Organisation | University of Cambridge |
Department | MRC Biostatistics Unit |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Intellectual input |
Collaborator Contribution | Intellectual input |
Impact | 1 article published, DOI 10.1111/rssc.12007. |
Start Year | 2010 |
Description | UKCTOCS |
Organisation | University of Cambridge |
Department | MRC Biostatistics Unit |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Data analysis and intellectual input |
Collaborator Contribution | Provision of data and intellectual input |
Impact | 3 journal articles (DOIs 10.1038/sj.bjc.6605809 , 10.1111/1471-0528.12870 and 10.1097/IGC.0000000000000507) |
Start Year | 2008 |
Description | UKCTOCS |
Organisation | University of Sussex |
Department | Brighton and Sussex Medical School |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Data analysis and intellectual input |
Collaborator Contribution | Provision of data and intellectual input |
Impact | 3 journal articles (DOIs 10.1038/sj.bjc.6605809 , 10.1111/1471-0528.12870 and 10.1097/IGC.0000000000000507) |
Start Year | 2008 |
Description | Cambridge Science Fair |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | Yes |
Geographic Reach | Regional |
Primary Audience | Schools |
Results and Impact | Helped run an a display highlighting the work of the Unit at Cambridge Science on Saturday Recognition for my fellowship and the work of the Unit |
Year(s) Of Engagement Activity | 2007,2008,2009,2010,2011,2012,2013 |
Description | Insitute of Public Health's Bradford Hill Seminar series |
Form Of Engagement Activity | A formal working group, expert panel or dialogue |
Part Of Official Scheme? | No |
Geographic Reach | Local |
Primary Audience | Health professionals |
Results and Impact | Regular seminar series which takes place at the University of Cambridge's Institute of Public health on Friday lunchtimes, regularly attended by a variety of health professionals Further strengthening of intellectual collaboration with external institutions, e.g. the University of York and the University of Salford. |
Year(s) Of Engagement Activity | 2009,2010,2011 |