Darsy Darssan1, Gita D Mishra1, Darren C Greenwood2, Sven Sandin3, Eric J Brunner4, Sybil L Crawford5, Samar R El Khoudary6, Maria Mori Brooks6, Ellen B Gold7, Mette Kildevæld Simonsen8, Hsin-Fang Chung1, Elisabete Weiderpass9, Annette J Dobson10. 1. University of Queensland, School of Public Health, Faculty of Medicine, Queensland, Australia. 2. School of Medicine, University of Leeds, Leeds, UK. 3. Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, USA; Seaver Autism Center for Research and Treatment at Mount Sinai, New York, USA. 4. Department of Epidemiology and Public Health, University College London, London, UK. 5. Graduate School of Nursing, University of Massachusetts Medical School, Worcester, MA. 6. Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, PA, USA. 7. Department of Public Health Sciences, University of California, Davis, CA, USA. 8. The Parker Institute and Aarhus University, Frederiksberg Hospital, 2000 Frederiksberg, Denmark. 9. International Agency for Research on Cancer, World Health Organisation, Lyon, France. 10. University of Queensland, School of Public Health, Faculty of Medicine, Queensland, Australia. Electronic address: a.dobson@sph.uq.edu.au.
Abstract
OBJECTIVE: Methods for meta-analysis of studies with individual participant data and continuous exposure variables are well described in the statistical literature but are not widely used in clinical and epidemiological research. The purpose of this case study is to make the methods more accessible. STUDY DESIGN AND SETTING: A two-stage process is demonstrated. Response curves are estimated separately for each study using fractional polynomials. The study-specific curves are then averaged pointwise over all studies at each value of the exposure. The averaging can be implemented using fixed effects or random effects methods. RESULTS: The methodology is illustrated using samples of real data with continuous outcome and exposure data and several covariates. The sample data set, segments of Stata and R code, and outputs are provided to enable replication of the results. CONCLUSION: These methods and tools can be adapted to other situations, including for time-to-event or categorical outcomes, different ways of modelling exposure-outcome curves, and different strategies for covariate adjustment.
OBJECTIVE: Methods for meta-analysis of studies with individual participant data and continuous exposure variables are well described in the statistical literature but are not widely used in clinical and epidemiological research. The purpose of this case study is to make the methods more accessible. STUDY DESIGN AND SETTING: A two-stage process is demonstrated. Response curves are estimated separately for each study using fractional polynomials. The study-specific curves are then averaged pointwise over all studies at each value of the exposure. The averaging can be implemented using fixed effects or random effects methods. RESULTS: The methodology is illustrated using samples of real data with continuous outcome and exposure data and several covariates. The sample data set, segments of Stata and R code, and outputs are provided to enable replication of the results. CONCLUSION: These methods and tools can be adapted to other situations, including for time-to-event or categorical outcomes, different ways of modelling exposure-outcome curves, and different strategies for covariate adjustment.
Authors: Matteo Rota; Rino Bellocco; Lorenza Scotti; Irene Tramacere; Mazda Jenab; Giovanni Corrao; Carlo La Vecchia; Paolo Boffetta; Vincenzo Bagnardi Journal: Stat Med Date: 2010-11-20 Impact factor: 2.373
Authors: Gita D Mishra; Debra Anderson; Danielle A J M Schoenaker; Hans-Olov Adami; Nancy E Avis; Daniel Brown; Fiona Bruinsma; Eric Brunner; Janet E Cade; Sybil L Crawford; Annette J Dobson; Jane Elliott; Graham G Giles; Ellen B Gold; Kunihiko Hayashi; Diana Kuh; Kathryn A Lee; Jung Su Lee; Melissa K Melby; Hideki Mizunuma; Lynette L Sievert; Elisabete Weiderpass Journal: Maturitas Date: 2013-01-10 Impact factor: 4.342
Authors: Dongshan Zhu; Hsin-Fang Chung; Nirmala Pandeya; Annette J Dobson; Diana Kuh; Sybil L Crawford; Ellen B Gold; Nancy E Avis; Graham G Giles; Fiona Bruinsma; Hans-Olov Adami; Elisabete Weiderpass; Darren C Greenwood; Janet E Cade; Ellen S Mitchell; Nancy F Woods; Eric J Brunner; Mette Kildevæld Simonsen; Gita D Mishra Journal: Eur J Epidemiol Date: 2018-02-19 Impact factor: 8.082
Authors: Thomas P A Debray; Karel G M Moons; Gert van Valkenhoef; Orestis Efthimiou; Noemi Hummel; Rolf H H Groenwold; Johannes B Reitsma Journal: Res Synth Methods Date: 2015-08-19 Impact factor: 5.273