Statistical methodology for meta-analysis of epidemiological studies using individual participant data.

Lead Research Organisation: University of Cambridge
Department Name: Institute of Public Health

Abstract

An increasing number of factors are being proposed as important predictors and/or causes of chronic diseases, particularly with the advent of technologies that enable rapid measurement of large numbers of blood proteins and genetic factors. To enable a more comprehensive and powerful evaluation of the relevance of such factors, it is often necessary to pool data from different studies. If such studies can reliably demonstrate that a particular factor is relevant to a condition (such as heart disease), then this could have important implications for the prediction and prevention of disease (exemplified by measurement and modification of blood cholesterol values). We plan to advance the development of statistical methods for use in such data pooling approaches by working on detailed information previously collated on up to 40,000 cases of heart attack among 1 million participants from about 100 studies. The main aim is to develop methods that will enable more reliable conclusions to be drawn about (i) whether a straight line (or some more complicated relationship) best describes the relationship between a factor and the risk of disease, and (ii) whether associations of particular factors with disease risk are likely to reflect cause-and-effect relationships. The methods that will be developed will have applications to many different situations and to different diseases, and will become increasingly important as the trend continues towards data sharing and pooling in large, collaborative multi-centre studies.

Technical Summary

Combination of individual participant data from multiple observational studies is increasingly used to evaluate the relevance of risk markers to disease, such as the 1-million-participant, 95-cohort Emerging Risk Factors Collaboration (ERFC), which is coordinated by our group. Optimum biostatistical methods are needed to help maximize the value of such databases. Our proposal addresses unresolved questions in relation to: (i) characterisation of the shape of relationships between quantitative exposures (such as biomarkers) and disease outcomes, and (ii) control of the impact of possible confounding factors on exposure-disease relationships.

Reliable characterisation of the shape of exposure-disease relationships can have important scientific and public health implications, as exemplified by the log-linear relationship of blood pressure with major cardiovascular outomes. Such assessments can, however, be misleading in the presence of exposure measurement error (which typically dilutes the strength of associations) and diversity across studies in exposure distributions (which complicates selection of an appropriate scale in which to combine studies). Our preliminary work has suggested, moreover, that standard measurement error correction methods can mis-estimate non-linear dose-response relationships. Through implementation in the ERFC database and through simulation, we will develop approaches that overcome these limitations by systematic investigation using parametric models for exposure and measurement error alongside flexible fractional polynomials or spline models for the exposure-disease relationship. We will investigate selection of appropriate scales by estimation of the unstandardised exposure-disease association and the standard deviation of the usual exposure for each study, performing random effects meta-analyses on the unstandardised and standardised scales, and comparing measures of heterogeneity.

Error in the measurement of potential confounding factors (or measurement of only a subset of known confounders in some studies) can lead to misleading or artefactual associations, and, hence, erroneous inferences about disease causation. Previous meta-analyses have generally not corrected for such biases. To help correct for confounder measurement error, we will extend methods we developed to correct for exposure measurement error, by using cohort-specific correction matrices inferred from multivariate random-effects meta-analysis. To address missing data on confounders, we propose to estimate the unadjusted association in each study and the adjusted association in studies with recorded confounders, and then to combine these associations using bivariate random-effects meta-analysis.

The products of this methodological work will have rapid application, initially to the ERFC and then to other existing data pooling initatives. Our findings should become increasingly useful as the trend continues towards data pooling in large, collaborative multi-centre analyses.

Publications

10 25 50
 
Guideline Title ESC Clinical Practice Guidelines
Description SCORE2
Geographic Reach Europe 
Policy Influence Type Citation in clinical guidelines
Impact • Improved and updated risk calculators allow tailored use among people aged 40+ to accurately predict who is at risk of having a heart attack or stroke in the next 5 or 10 years • People flagged as having increased risk are recommended personalised preventative treatment • Our tool, called 'SCORE2', has been adopted by the European Guidelines on Cardiovascular
URL https://www.escardio.org/Education/ESC-Prevention-of-CVD-Programme/Risk-assessment/esc-cvd-risk-calc...
 
Description Training in the analysis of individual participant data from multiple studies
Geographic Reach Multiple continents/international 
Policy Influence Type Influenced training of practitioners or researchers
 
Description Translational research tools in the analysis of individual participant data from multiple studies
Geographic Reach Multiple continents/international 
Policy Influence Type Participation in a advisory committee
 
Description BHF, Centre of Excellence - Pump Priming (A Wood)
Amount £49,813 (GBP)
Organisation British Heart Foundation (BHF) 
Sector Charity/Non Profit
Country United Kingdom
Start 03/2014 
End 03/2019
 
Description Characterisation, determinants, mechanisms and consequences of the long-term effects of COVID-19: providing the evidence base for health care
Amount £10,000,000 (GBP)
Funding ID MC_PC_20051 
Organisation Medical Research Council (MRC) 
Sector Public
Country United Kingdom
Start 03/2021 
End 02/2024
 
Description EU: Innovative Medicines Initiative - "BigData@Heart"
Amount € 19,000,000 (EUR)
Funding ID 116074 
Organisation European Union 
Sector Public
Country European Union (EU)
Start  
 
Description Large-scale integrative studies of risk factors in coronary heart disease: from discovery to application
Amount £2,017,846 (GBP)
Funding ID MR/L003120/1 
Organisation Medical Research Council (MRC) 
Sector Public
Country United Kingdom
Start 07/2013 
End 08/2018
 
Description Looking beyond the mean: what within-person variability can tell us about dementia, cardiovascular disease and cystic fibrosis
Amount £486,957 (GBP)
Funding ID MR/V020595/1 
Organisation Medical Research Council (MRC) 
Sector Public
Country United Kingdom
Start 08/2021 
End 03/2024
 
Description MRC Industrial Strategy PhD Award
Amount £360,000 (GBP)
Organisation Medical Research Council (MRC) 
Sector Public
Country United Kingdom
Start 09/2018 
End 10/2021
 
Description Methodology Research Strategic Grant (A Wood)
Amount £395,794 (GBP)
Funding ID MR/K014811/1 
Organisation Medical Research Council (MRC) 
Sector Public
Country United Kingdom
Start 09/2013 
End 09/2016
 
Description NIHR BTRU in Donor Health & Genomics
Amount £4,000,000 (GBP)
Organisation National Institute for Health Research 
Sector Public
Country United Kingdom
Start  
 
Description New Investigator Research Grant (A Wood)
Amount £364,471 (GBP)
Funding ID G0701619 
Organisation Medical Research Council (MRC) 
Sector Public
Country United Kingdom
Start 05/2009 
End 09/2013
 
Description Phase 1 COVID-19 Longitudinal Health and Wellbeing - National Core Study
Amount £9,074,000 (GBP)
Funding ID MC_PC_20059 
Organisation Medical Research Council (MRC) 
Sector Public
Country United Kingdom
Start 03/2021 
End 09/2022
 
Description RCUK Innovation / Rutherford Fund Fellowships
Amount £760,000 (GBP)
Organisation Research Councils UK (RCUK) 
Sector Public
Country United Kingdom
Start 07/2018 
End 08/2021
 
Description Towards early identification of adolescent mental health problems
Amount £100,577 (GBP)
Funding ID MR/T046430/1 
Organisation Medical Research Council (MRC) 
Sector Public
Country United Kingdom
Start 06/2020 
End 10/2021
 
Description Using machine learning for personalised CVD risk management
Amount £91,414 (GBP)
Funding ID BDCSA_100005 Wood 
Organisation Medical Research Council (MRC) 
Sector Public
Country United Kingdom
Start  
 
Title Quantifying net benefits 
Description A framework for quantifying net benefits of alternative prognostic models 
Type Of Material Improvements to research infrastructure 
Provided To Others? No  
Impact Publication 21905066 
 
Title Statistical programs made freely available to researchers 
Description Bespoke statistical programs for the meta-analysis of individual participant data have been made freely available to researchers via the ERFC website 
Type Of Material Improvements to research infrastructure 
Year Produced 2009 
Provided To Others? Yes  
Impact N/A 
URL http://www.phpc.cam.ac.uk/ceu/research/erfc/stata/
 
Title CVD-COVID-UK/COVID-IMPACT 
Description See https://www.hdruk.ac.uk/projects/cvd-covid-uk-project/ CVD-COVID-UK established a novel population wide resource in partnership with NHS Digital, comprising of a range of linked datasets covering the entire population of England, including o hospital data o death registrations o primary care data o community dispensing data o Covid-19 vaccination data and lab test o Data from intensive care units and from cardiovascular specialist registries • 
Type Of Material Data analysis technique 
Year Produced 2021 
Provided To Others? Yes  
Impact Results from analyses using this research database have informed national COVID-19 Advisory Groups and public health agencies on COVID-19 vaccine safety. 
URL https://www.hdruk.ac.uk/projects/cvd-covid-uk-project/
 
Title Statistical Methods and Database 
Description Dataset from >130 studies with over 2.3M individuals and 100,000 cases of cardiovascular disease with information on conventional risk factors for CVD and other circulating biomarkers and lifestyle factors. 
Type Of Material Database/Collection of data 
Year Produced 2009 
Provided To Others? Yes  
Impact N/A 
 
Description Interviews for general magazine articles 
Form Of Engagement Activity A magazine, newsletter or online publication
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Public/other audiences
Results and Impact Undertook several interviews for healthy living style magazines about recommended limits of alcohol consumption.
Year(s) Of Engagement Activity 2018,2019
 
Description Interviews for international and national news 
Form Of Engagement Activity A press release, press conference or response to a media enquiry/interview
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Media (as a channel to the public)
Results and Impact Involved in 20+ national and international media interviews related to recommended levels of alcohol consumption, focused mainly on the debate about whether policy guidelines should lower recommended drinking limits
Year(s) Of Engagement Activity 2018,2019
 
Description Seminar at Department of Health 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Type Of Presentation Keynote/Invited Speaker
Geographic Reach National
Primary Audience Policymakers/politicians
Results and Impact 20-30 staff at the department of health attended the seminar and discussed the relevance of the work

No notable impacts
Year(s) Of Engagement Activity 2010