Power Analysis for Population-Based Longitudinal Studies Investigating Gene-Environment Interactions in Chronic Diseases: A Simulation Study
Identifieur interne : 000236 ( Main/Exploration ); précédent : 000235; suivant : 000237Power Analysis for Population-Based Longitudinal Studies Investigating Gene-Environment Interactions in Chronic Diseases: A Simulation Study
Auteurs : Jinhui Ma [Canada] ; Lehana Thabane [Canada] ; Joseph Beyene [Canada] ; Parminder Raina [Canada]Source :
- PLoS ONE [ 1932-6203 ] ; 2016.
Abstract
Conventional methods for sample size calculation for population-based longitudinal studies tend to overestimate the statistical power by overlooking important determinants of the required sample size, such as the measurement errors and unmeasured etiological determinants, etc. In contrast, a simulation-based sample size calculation, if designed properly, allows these determinants to be taken into account and offers flexibility in accommodating complex study design features. The Canadian Longitudinal Study on Aging (CLSA) is a Canada-wide, 20-year follow-up study of 30,000 people between the ages of 45 and 85 years, with in-depth information collected every 3 years. A simulation study, based on an illness-death model, was conducted to: (1) investigate the statistical power profile of the CLSA to detect the effect of environmental and genetic risk factors, and their interaction on age-related chronic diseases; and (2) explore the design alternatives and implementation strategies for increasing the statistical power of population-based longitudinal studies in general. The results showed that the statistical power to identify the effect of environmental and genetic risk exposures, and their interaction on a disease was boosted when: (1) the prevalence of the risk exposures increased; (2) the disease of interest is relatively common in the population; and (3) risk exposures were measured accurately. In addition, the frequency of data collection every three years in the CLSA led to a slightly lower statistical power compared to the design assuming that participants underwent health monitoring continuously. The CLSA had sufficient power to detect a small (1
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DOI: 10.1371/journal.pone.0149940
PubMed: 26901422
PubMed Central: 4762766
Affiliations:
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Thabane</name><affiliation wicri:level="4"><nlm:aff id="aff001"><addr-line>Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Ontario, Canada</addr-line></nlm:aff><country xml:lang="fr">Canada</country><wicri:regionArea>Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Ontario</wicri:regionArea><orgName type="university">Université McMaster</orgName><placeName><settlement type="city">Hamilton (Ontario)</settlement><region type="state">Ontario</region></placeName></affiliation><affiliation wicri:level="1"><nlm:aff id="aff003"><addr-line>Biostatistics Unit, St. Joseph's Healthcare Hamilton, Hamilton, Ontario, Canada</addr-line></nlm:aff><country xml:lang="fr">Canada</country><wicri:regionArea>Biostatistics Unit, St. Joseph's Healthcare Hamilton, Hamilton, Ontario</wicri:regionArea><wicri:noRegion>Ontario</wicri:noRegion></affiliation><affiliation wicri:level="1"><nlm:aff id="aff004"><addr-line>Centre for Evaluation of Medicines, St Joseph’s Healthcare Hamilton, Ontario, Canada</addr-line></nlm:aff><country xml:lang="fr">Canada</country><wicri:regionArea>Centre for Evaluation of Medicines, St Joseph’s Healthcare Hamilton, Ontario</wicri:regionArea><wicri:noRegion>Ontario</wicri:noRegion></affiliation><affiliation wicri:level="1"><nlm:aff id="aff005"><addr-line>Population Health Research Institute, Hamilton Health Sciences, Hamilton, Ontario, Canada</addr-line></nlm:aff><country xml:lang="fr">Canada</country><wicri:regionArea>Population Health Research Institute, Hamilton Health Sciences, Hamilton, Ontario</wicri:regionArea><wicri:noRegion>Ontario</wicri:noRegion></affiliation></author><author><name sortKey="Beyene, Joseph" sort="Beyene, Joseph" uniqKey="Beyene J" first="Joseph" last="Beyene">Joseph Beyene</name><affiliation wicri:level="4"><nlm:aff id="aff001"><addr-line>Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Ontario, Canada</addr-line></nlm:aff><country xml:lang="fr">Canada</country><wicri:regionArea>Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Ontario</wicri:regionArea><orgName type="university">Université McMaster</orgName><placeName><settlement type="city">Hamilton (Ontario)</settlement><region type="state">Ontario</region></placeName></affiliation></author><author><name sortKey="Raina, Parminder" sort="Raina, Parminder" uniqKey="Raina P" first="Parminder" last="Raina">Parminder Raina</name><affiliation wicri:level="4"><nlm:aff id="aff001"><addr-line>Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Ontario, Canada</addr-line></nlm:aff><country xml:lang="fr">Canada</country><wicri:regionArea>Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Ontario</wicri:regionArea><orgName type="university">Université McMaster</orgName><placeName><settlement type="city">Hamilton (Ontario)</settlement><region type="state">Ontario</region></placeName></affiliation><affiliation wicri:level="1"><nlm:aff id="aff002"><addr-line>McMaster University Evidence-based Practice Center, Hamilton, Ontario, Canada</addr-line></nlm:aff><country xml:lang="fr">Canada</country><wicri:regionArea>McMaster University Evidence-based Practice Center, Hamilton, Ontario</wicri:regionArea><wicri:noRegion>Ontario</wicri:noRegion></affiliation></author></analytic><series><title level="j">PLoS ONE</title><idno type="eISSN">1932-6203</idno><imprint><date when="2016">2016</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p>Conventional methods for sample size calculation for population-based longitudinal studies tend to overestimate the statistical power by overlooking important determinants of the required sample size, such as the measurement errors and unmeasured etiological determinants, etc. In contrast, a simulation-based sample size calculation, if designed properly, allows these determinants to be taken into account and offers flexibility in accommodating complex study design features. The Canadian Longitudinal Study on Aging (CLSA) is a Canada-wide, 20-year follow-up study of 30,000 people between the ages of 45 and 85 years, with in-depth information collected every 3 years. A simulation study, based on an illness-death model, was conducted to: (1) investigate the statistical power profile of the CLSA to detect the effect of environmental and genetic risk factors, and their interaction on age-related chronic diseases; and (2) explore the design alternatives and implementation strategies for increasing the statistical power of population-based longitudinal studies in general. The results showed that the statistical power to identify the effect of environmental and genetic risk exposures, and their interaction on a disease was boosted when: (1) the prevalence of the risk exposures increased; (2) the disease of interest is relatively common in the population; and (3) risk exposures were measured accurately. In addition, the frequency of data collection every three years in the CLSA led to a slightly lower statistical power compared to the design assuming that participants underwent health monitoring continuously. The CLSA had sufficient power to detect a small (1</p> </div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Grigorenko, El" uniqKey="Grigorenko E">EL Grigorenko</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Collins, Fs" uniqKey="Collins F">FS Collins</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Khoury, Mj" uniqKey="Khoury M">MJ Khoury</name></author><author><name sortKey="Little, J" uniqKey="Little J">J Little</name></author><author><name sortKey="Gwinn, M" uniqKey="Gwinn M">M Gwinn</name></author><author><name sortKey="Ioannidis, Jp" uniqKey="Ioannidis J">JP Ioannidis</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Feinberg, Ap" uniqKey="Feinberg A">AP Feinberg</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Calvanese, V" uniqKey="Calvanese V">V Calvanese</name></author><author><name sortKey="Lara, E" uniqKey="Lara E">E Lara</name></author><author><name sortKey="Kahn, A" uniqKey="Kahn A">A Kahn</name></author><author><name sortKey="Fraga, Mf" uniqKey="Fraga M">MF Fraga</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Thompson, Ea" uniqKey="Thompson E">EA Thompson</name></author><author><name sortKey="Elston, Rc" uniqKey="Elston R">RC Elston</name></author><author><name sortKey="Olson, Jm" uniqKey="Olson J">JM Olson</name></author><author><name sortKey="Palmer, L" uniqKey="Palmer L">L Palmer</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Raina, Ps" uniqKey="Raina P">PS Raina</name></author><author><name sortKey="Wolfson, C" uniqKey="Wolfson C">C Wolfson</name></author><author><name sortKey="Kirkland, Sa" uniqKey="Kirkland S">SA Kirkland</name></author><author><name sortKey="Griffith, Le" uniqKey="Griffith L">LE Griffith</name></author><author><name sortKey="Oremus, M" uniqKey="Oremus M">M 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uniqKey="Mckeigue P">PM McKeigue</name></author><author><name sortKey="Davey, Sg" uniqKey="Davey S">SG Davey</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Barsh, Gs" uniqKey="Barsh G">GS Barsh</name></author><author><name sortKey="Copenhaver, Gp" uniqKey="Copenhaver G">GP Copenhaver</name></author><author><name sortKey="Gibson, G" uniqKey="Gibson G">G Gibson</name></author><author><name sortKey="Williams, Sm" uniqKey="Williams S">SM Williams</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Van Den Hout, A" uniqKey="Van Den Hout A">A van den Hout</name></author><author><name sortKey="Matthews, Fe" uniqKey="Matthews F">FE Matthews</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Garcia Closas, M" uniqKey="Garcia Closas M">M Garcia-Closas</name></author><author><name sortKey="Rothman, N" uniqKey="Rothman N">N Rothman</name></author><author><name sortKey="Lubin, J" uniqKey="Lubin J">J Lubin</name></author></analytic></biblStruct></listBibl></div1></back></TEI><affiliations><list><country><li>Canada</li></country><region><li>Ontario</li></region><settlement><li>Hamilton (Ontario)</li></settlement><orgName><li>Université McMaster</li></orgName></list><tree><country name="Canada"><region name="Ontario"><name sortKey="Ma, Jinhui" sort="Ma, Jinhui" uniqKey="Ma J" first="Jinhui" last="Ma">Jinhui Ma</name></region><name sortKey="Beyene, Joseph" sort="Beyene, Joseph" uniqKey="Beyene J" first="Joseph" last="Beyene">Joseph Beyene</name><name sortKey="Ma, Jinhui" sort="Ma, Jinhui" uniqKey="Ma J" first="Jinhui" last="Ma">Jinhui Ma</name><name sortKey="Ma, Jinhui" sort="Ma, Jinhui" uniqKey="Ma J" first="Jinhui" last="Ma">Jinhui Ma</name><name sortKey="Raina, Parminder" sort="Raina, Parminder" uniqKey="Raina P" first="Parminder" last="Raina">Parminder Raina</name><name sortKey="Raina, Parminder" sort="Raina, Parminder" uniqKey="Raina P" first="Parminder" last="Raina">Parminder Raina</name><name sortKey="Thabane, Lehana" sort="Thabane, Lehana" uniqKey="Thabane L" first="Lehana" last="Thabane">Lehana Thabane</name><name sortKey="Thabane, Lehana" sort="Thabane, Lehana" uniqKey="Thabane L" first="Lehana" last="Thabane">Lehana Thabane</name><name sortKey="Thabane, Lehana" sort="Thabane, Lehana" uniqKey="Thabane L" first="Lehana" last="Thabane">Lehana Thabane</name><name sortKey="Thabane, Lehana" sort="Thabane, Lehana" uniqKey="Thabane L" first="Lehana" last="Thabane">Lehana Thabane</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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