Empirical evaluation of the Q-Genie tool: a protocol for assessment of effectiveness.
Meta-analyses of genetic association studies are affected by biases and quality shortcomings of the individual studies. We previously developed and validated a risk of bias tool for use in systematic reviews of genetic association studies. The present study describes a larger empirical evaluation of the Q-Genie tool.



MEDLINE, Embase, Global Health and the Human Genome Epidemiology Network will be searched for published meta-analyses of genetic association studies. Twelve reviewers in pairs will apply the Q-Genie tool to all studies in included meta-analyses. The Q-Genie will then be evaluated on its ability to (i) increase precision after exclusion of low quality studies, (ii) decrease heterogeneity after exclusion of low quality studies and (iii) good agreement with experts on quality rating by Q-Genie. A qualitative assessment of the tool will also be conducted using structured questionnaires.



This systematic review will quantitatively and qualitatively assess the Q-Genie's ability to identify poor quality genetic association studies. This information will inform the selection of studies for inclusion in meta-analyses, conduct sensitivity analyses and perform metaregression. Results of this study will strengthen our confidence in estimates of the effect of a gene on an outcome from meta-analyses, ultimately bringing us closer to deliver on the promise of personalised medicine.



An updated Q-Genie tool will be made available from the Population Genomics Program website and the results will be submitted for a peer-reviewed publication.
Department of Clinical Epidemiology & Biostatistics, McMaster University, Hamilton, Ontario, Canada Chanchalani Research Centre, McMaster University, Hamilton, Ontario, Canada Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada.
Z N
ZN
Sohani
DeGroote School of Medicine, McMaster University, Hamilton, Ontario, Canada.
S
S
Sarma
Department of Clinical Epidemiology & Biostatistics, McMaster University, Hamilton, Ontario, Canada Chanchalani Research Centre, McMaster University, Hamilton, Ontario, Canada.
A
A
Alyass
Department of Clinical Epidemiology & Biostatistics, McMaster University, Hamilton, Ontario, Canada Chanchalani Research Centre, McMaster University, Hamilton, Ontario, Canada.
R J
RJ
de Souza
Department of Clinical Epidemiology & Biostatistics, McMaster University, Hamilton, Ontario, Canada Chanchalani Research Centre, McMaster University, Hamilton, Ontario, Canada.
S
S
Robiou-du-Pont
Department of Clinical Epidemiology & Biostatistics, McMaster University, Hamilton, Ontario, Canada Chanchalani Research Centre, McMaster University, Hamilton, Ontario, Canada.
A
A
Li
Department of Clinical Epidemiology & Biostatistics, McMaster University, Hamilton, Ontario, Canada Chanchalani Research Centre, McMaster University, Hamilton, Ontario, Canada.
A
A
Mayhew
Department of Clinical Epidemiology & Biostatistics, McMaster University, Hamilton, Ontario, Canada Chanchalani Research Centre, McMaster University, Hamilton, Ontario, Canada.
F
F
Yazdi
Department of Clinical Epidemiology & Biostatistics, McMaster University, Hamilton, Ontario, Canada Chanchalani Research Centre, McMaster University, Hamilton, Ontario, Canada.
H
H
Reddon
Department of Clinical Epidemiology & Biostatistics, McMaster University, Hamilton, Ontario, Canada Chanchalani Research Centre, McMaster University, Hamilton, Ontario, Canada.
A
A
Lamri
Department of Clinical Epidemiology & Biostatistics, McMaster University, Hamilton, Ontario, Canada Chanchalani Research Centre, McMaster University, Hamilton, Ontario, Canada.
C
C
Stryjecki
Department of Clinical Epidemiology & Biostatistics, McMaster University, Hamilton, Ontario, Canada Chanchalani Research Centre, McMaster University, Hamilton, Ontario, Canada.
A
A
Ishola
Department of Clinical Epidemiology & Biostatistics, McMaster University, Hamilton, Ontario, Canada Chanchalani Research Centre, McMaster University, Hamilton, Ontario, Canada.
Y K
YK
Lee
Department of Clinical Epidemiology & Biostatistics, McMaster University, Hamilton, Ontario, Canada Chanchalani Research Centre, McMaster University, Hamilton, Ontario, Canada.
N
N
Vashi
Department of Clinical Epidemiology & Biostatistics, McMaster University, Hamilton, Ontario, Canada Chanchalani Research Centre, McMaster University, Hamilton, Ontario, Canada Department of Medicine, McMaster University, Hamilton, Ontario, Canada.
S S
SS
Anand
Department of Clinical Epidemiology & Biostatistics, McMaster University, Hamilton, Ontario, Canada Chanchalani Research Centre, McMaster University, Hamilton, Ontario, Canada Department of Pathology & Molecular Medicine, McMaster University, Hamilton, Ontario, Canada Faculté de Médecine, Inserm U-954, University of Lorraine and University Hospital Center of Nancy, Nancy, France.
D
D
Meyre
D036262:Empirical Research; D019317:Evidence-Based Medicine; D056726:Genetic Association Studies; D006801:Humans; D015201:Meta-Analysis as Topic; D017594:Publication Bias; D015203:Reproducibility of Results; D000078202:Systematic Reviews as Topic
Genetic association studies; Genomics; Meta-analyses; Risk of bias; Systematic reviews