Abstract
Background: For complex diseases like cancer, pooled-analysis of individual data represents a powerful tool to investigate the joint contribution of genetic, phenotypic and environmental factors to the development of a disease. Pooled-analysis of epidemiological studies has many advantages over meta-analysis, and preliminary results may be obtained faster and with lower costs than with prospective consortia. Design and methods. Based on our experience with the study design of the Melanocortin-1 receptor (MC1R) gene, SKin cancer and Phenotypic characteristics (M-SKIP) project, we describe the most important steps in planning and conducting a pooled-analysis of genetic epidemiological studies. We then present the statistical analysis plan that we are going to apply, giving particular attention to methods of analysis recently proposed to account for between-study heterogeneity and to explore the joint contribution of genetic, phenotypic and environmental factors in the development of a disease. Within the M-SKIP project, data on 10,959 skin cancer cases and 14,785 controls from 31 international investigators were checked for quality and recoded for standardization. We first proposed to fit the aggregated data with random-effects logistic regression models. However, for the M-SKIP project, a two-stage analysis will be preferred to overcome the problem regarding the availability of different study covariates. The joint contribution of MC1R variants and phenotypic characteristics to skin cancer development will be studied via logic regression modeling. Discussion. Methodological guidelines to correctly design and conduct pooled-analyses are needed to facilitate application of such methods, thus providing a better summary of the actual findings on specific fields.
| Original language | English |
|---|---|
| Article number | 116 |
| Journal | BMC Medical Research Methodology |
| Volume | 12 |
| DOIs | |
| Publication status | Published - 2012 |
Keywords
- Genetic epidemiology
- Melanoma
- Meta-analysis
- Pooled-analysis
- Skin cancer
- Study design
ASJC Scopus subject areas
- Epidemiology
- Health Informatics
Cite this
Melanocortin-1 receptor, skin cancer and phenotypic characteristics (M-SKIP) project : Study design and methods for pooling results of genetic epidemiological studies. / Raimondi, Sara; Gandini, Sara; Fargnoli, Maria Concetta; Bagnardi, Vincenzo; Maisonneuve, Patrick; Specchia, Claudia; Kumar, Rajiv; Nagore, Eduardo; Han, Jiali; Hansson, Johan; Kanetsky, Peter A.; Ghiorzo, Paola; Gruis, Nelleke A.; Dwyer, Terry; Blizzard, Leigh; Fernandez-De-Misa, Ricardo; Branicki, Wojciech; Debniak, Tadeusz; Morling, Niels; Landi, Maria Teresa; Palmieri, Giuseppe; Ribas, Gloria; Stratigos, Alexander; Cornelius, Lynn; Motokawa, Tomonori; Anno, Sumiko; Helsing, Per; Wong, Terence H.; Autier, Philippe; García-Borrón, José C.; Little, Julian; Newton-Bishop, Julia; Sera, Francesco; Liu, Fan; Kayser, Manfred; Nijsten, Tamar.
In: BMC Medical Research Methodology, Vol. 12, 116, 2012.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Melanocortin-1 receptor, skin cancer and phenotypic characteristics (M-SKIP) project
T2 - Study design and methods for pooling results of genetic epidemiological studies
AU - Raimondi, Sara
AU - Gandini, Sara
AU - Fargnoli, Maria Concetta
AU - Bagnardi, Vincenzo
AU - Maisonneuve, Patrick
AU - Specchia, Claudia
AU - Kumar, Rajiv
AU - Nagore, Eduardo
AU - Han, Jiali
AU - Hansson, Johan
AU - Kanetsky, Peter A.
AU - Ghiorzo, Paola
AU - Gruis, Nelleke A.
AU - Dwyer, Terry
AU - Blizzard, Leigh
AU - Fernandez-De-Misa, Ricardo
AU - Branicki, Wojciech
AU - Debniak, Tadeusz
AU - Morling, Niels
AU - Landi, Maria Teresa
AU - Palmieri, Giuseppe
AU - Ribas, Gloria
AU - Stratigos, Alexander
AU - Cornelius, Lynn
AU - Motokawa, Tomonori
AU - Anno, Sumiko
AU - Helsing, Per
AU - Wong, Terence H.
AU - Autier, Philippe
AU - García-Borrón, José C.
AU - Little, Julian
AU - Newton-Bishop, Julia
AU - Sera, Francesco
AU - Liu, Fan
AU - Kayser, Manfred
AU - Nijsten, Tamar
PY - 2012
Y1 - 2012
N2 - Background: For complex diseases like cancer, pooled-analysis of individual data represents a powerful tool to investigate the joint contribution of genetic, phenotypic and environmental factors to the development of a disease. Pooled-analysis of epidemiological studies has many advantages over meta-analysis, and preliminary results may be obtained faster and with lower costs than with prospective consortia. Design and methods. Based on our experience with the study design of the Melanocortin-1 receptor (MC1R) gene, SKin cancer and Phenotypic characteristics (M-SKIP) project, we describe the most important steps in planning and conducting a pooled-analysis of genetic epidemiological studies. We then present the statistical analysis plan that we are going to apply, giving particular attention to methods of analysis recently proposed to account for between-study heterogeneity and to explore the joint contribution of genetic, phenotypic and environmental factors in the development of a disease. Within the M-SKIP project, data on 10,959 skin cancer cases and 14,785 controls from 31 international investigators were checked for quality and recoded for standardization. We first proposed to fit the aggregated data with random-effects logistic regression models. However, for the M-SKIP project, a two-stage analysis will be preferred to overcome the problem regarding the availability of different study covariates. The joint contribution of MC1R variants and phenotypic characteristics to skin cancer development will be studied via logic regression modeling. Discussion. Methodological guidelines to correctly design and conduct pooled-analyses are needed to facilitate application of such methods, thus providing a better summary of the actual findings on specific fields.
AB - Background: For complex diseases like cancer, pooled-analysis of individual data represents a powerful tool to investigate the joint contribution of genetic, phenotypic and environmental factors to the development of a disease. Pooled-analysis of epidemiological studies has many advantages over meta-analysis, and preliminary results may be obtained faster and with lower costs than with prospective consortia. Design and methods. Based on our experience with the study design of the Melanocortin-1 receptor (MC1R) gene, SKin cancer and Phenotypic characteristics (M-SKIP) project, we describe the most important steps in planning and conducting a pooled-analysis of genetic epidemiological studies. We then present the statistical analysis plan that we are going to apply, giving particular attention to methods of analysis recently proposed to account for between-study heterogeneity and to explore the joint contribution of genetic, phenotypic and environmental factors in the development of a disease. Within the M-SKIP project, data on 10,959 skin cancer cases and 14,785 controls from 31 international investigators were checked for quality and recoded for standardization. We first proposed to fit the aggregated data with random-effects logistic regression models. However, for the M-SKIP project, a two-stage analysis will be preferred to overcome the problem regarding the availability of different study covariates. The joint contribution of MC1R variants and phenotypic characteristics to skin cancer development will be studied via logic regression modeling. Discussion. Methodological guidelines to correctly design and conduct pooled-analyses are needed to facilitate application of such methods, thus providing a better summary of the actual findings on specific fields.
KW - Genetic epidemiology
KW - Melanoma
KW - Meta-analysis
KW - Pooled-analysis
KW - Skin cancer
KW - Study design
UR - http://www.scopus.com/inward/record.url?scp=84864519188&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84864519188&partnerID=8YFLogxK
U2 - 10.1186/1471-2288-12-116
DO - 10.1186/1471-2288-12-116
M3 - Article
VL - 12
JO - BMC Medical Research Methodology
JF - BMC Medical Research Methodology
SN - 1471-2288
M1 - 116
ER -