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A tutorial on sensitivity analyses in clinical trials: the what, why, when and how

Identifieur interne : 000489 ( Pmc/Curation ); précédent : 000488; suivant : 000490

A tutorial on sensitivity analyses in clinical trials: the what, why, when and how

Auteurs : Lehana Thabane [Canada] ; Lawrence Mbuagbaw [Canada] ; Shiyuan Zhang [Canada] ; Zainab Samaan [Canada] ; Maura Marcucci [Canada] ; Chenglin Ye [Canada] ; Marroon Thabane [Canada] ; Lora Giangregorio [Canada] ; Brittany Dennis [Canada] ; Daisy Kosa [Canada] ; Victoria Borg Debono [Canada] ; Rejane Dillenburg [Canada] ; Vincent Fruci [Canada] ; Monica Bawor [Canada] ; Juneyoung Lee [Corée du Sud] ; George Wells [Canada] ; Charles H. Goldsmith [Canada]

Source :

RBID : PMC:3720188

Abstract

Background

Sensitivity analyses play a crucial role in assessing the robustness of the findings or conclusions based on primary analyses of data in clinical trials. They are a critical way to assess the impact, effect or influence of key assumptions or variations—such as different methods of analysis, definitions of outcomes, protocol deviations, missing data, and outliers—on the overall conclusions of a study.

The current paper is the second in a series of tutorial-type manuscripts intended to discuss and clarify aspects related to key methodological issues in the design and analysis of clinical trials.

Discussion

In this paper we will provide a detailed exploration of the key aspects of sensitivity analyses including: 1) what sensitivity analyses are, why they are needed, and how often they are used in practice; 2) the different types of sensitivity analyses that one can do, with examples from the literature; 3) some frequently asked questions about sensitivity analyses; and 4) some suggestions on how to report the results of sensitivity analyses in clinical trials.

Summary

When reporting on a clinical trial, we recommend including planned or posthoc sensitivity analyses, the corresponding rationale and results along with the discussion of the consequences of these analyses on the overall findings of the study.


Url:
DOI: 10.1186/1471-2288-13-92
PubMed: 23855337
PubMed Central: 3720188

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PMC:3720188

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<nlm:aff id="I4">Biostatistics Unit, Father Sean O’Sullivan Research Center, St Joseph’s Healthcare Hamilton, Hamilton, ON, Canada</nlm:aff>
<country xml:lang="fr">Canada</country>
<wicri:regionArea>Biostatistics Unit, Father Sean O’Sullivan Research Center, St Joseph’s Healthcare Hamilton, Hamilton, ON</wicri:regionArea>
</affiliation>
</author>
<author>
<name sortKey="Kosa, Daisy" sort="Kosa, Daisy" uniqKey="Kosa D" first="Daisy" last="Kosa">Daisy Kosa</name>
<affiliation wicri:level="1">
<nlm:aff id="I1">Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, ON, Canada</nlm:aff>
<country xml:lang="fr">Canada</country>
<wicri:regionArea>Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, ON</wicri:regionArea>
</affiliation>
<affiliation wicri:level="1">
<nlm:aff id="I4">Biostatistics Unit, Father Sean O’Sullivan Research Center, St Joseph’s Healthcare Hamilton, Hamilton, ON, Canada</nlm:aff>
<country xml:lang="fr">Canada</country>
<wicri:regionArea>Biostatistics Unit, Father Sean O’Sullivan Research Center, St Joseph’s Healthcare Hamilton, Hamilton, ON</wicri:regionArea>
</affiliation>
<affiliation wicri:level="1">
<nlm:aff id="I10">Department of Nephrology, Toronto General Hospital, Toronto, ON, Canada</nlm:aff>
<country xml:lang="fr">Canada</country>
<wicri:regionArea>Department of Nephrology, Toronto General Hospital, Toronto, ON</wicri:regionArea>
</affiliation>
</author>
<author>
<name sortKey="Debono, Victoria Borg" sort="Debono, Victoria Borg" uniqKey="Debono V" first="Victoria Borg" last="Debono">Victoria Borg Debono</name>
<affiliation wicri:level="1">
<nlm:aff id="I1">Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, ON, Canada</nlm:aff>
<country xml:lang="fr">Canada</country>
<wicri:regionArea>Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, ON</wicri:regionArea>
</affiliation>
<affiliation wicri:level="1">
<nlm:aff id="I4">Biostatistics Unit, Father Sean O’Sullivan Research Center, St Joseph’s Healthcare Hamilton, Hamilton, ON, Canada</nlm:aff>
<country xml:lang="fr">Canada</country>
<wicri:regionArea>Biostatistics Unit, Father Sean O’Sullivan Research Center, St Joseph’s Healthcare Hamilton, Hamilton, ON</wicri:regionArea>
</affiliation>
</author>
<author>
<name sortKey="Dillenburg, Rejane" sort="Dillenburg, Rejane" uniqKey="Dillenburg R" first="Rejane" last="Dillenburg">Rejane Dillenburg</name>
<affiliation wicri:level="1">
<nlm:aff id="I11">Department of Pediatrics, McMaster University, Hamilton, ON, Canada</nlm:aff>
<country xml:lang="fr">Canada</country>
<wicri:regionArea>Department of Pediatrics, McMaster University, Hamilton, ON</wicri:regionArea>
</affiliation>
</author>
<author>
<name sortKey="Fruci, Vincent" sort="Fruci, Vincent" uniqKey="Fruci V" first="Vincent" last="Fruci">Vincent Fruci</name>
<affiliation wicri:level="1">
<nlm:aff id="I12">Michael G. DeGroote School of Medicine, McMaster University, Hamilton, ON, Canada</nlm:aff>
<country xml:lang="fr">Canada</country>
<wicri:regionArea>Michael G. DeGroote School of Medicine, McMaster University, Hamilton, ON</wicri:regionArea>
</affiliation>
</author>
<author>
<name sortKey="Bawor, Monica" sort="Bawor, Monica" uniqKey="Bawor M" first="Monica" last="Bawor">Monica Bawor</name>
<affiliation wicri:level="1">
<nlm:aff id="I13">McMaster Integrative Neuroscience Discovery & Study (MiNDS) Program, McMaster University, Hamilton, ON, Canada</nlm:aff>
<country xml:lang="fr">Canada</country>
<wicri:regionArea>McMaster Integrative Neuroscience Discovery & Study (MiNDS) Program, McMaster University, Hamilton, ON</wicri:regionArea>
</affiliation>
</author>
<author>
<name sortKey="Lee, Juneyoung" sort="Lee, Juneyoung" uniqKey="Lee J" first="Juneyoung" last="Lee">Juneyoung Lee</name>
<affiliation wicri:level="1">
<nlm:aff id="I14">Department of Biostatistics, Korea University, Seoul, Korea</nlm:aff>
<country xml:lang="fr">Corée du Sud</country>
<wicri:regionArea>Department of Biostatistics, Korea University, Seoul</wicri:regionArea>
</affiliation>
</author>
<author>
<name sortKey="Wells, George" sort="Wells, George" uniqKey="Wells G" first="George" last="Wells">George Wells</name>
<affiliation wicri:level="1">
<nlm:aff id="I15">Department of Clinical Epidemiology, University of Ottawa, Ottawa, ON, Canada</nlm:aff>
<country xml:lang="fr">Canada</country>
<wicri:regionArea>Department of Clinical Epidemiology, University of Ottawa, Ottawa, ON</wicri:regionArea>
</affiliation>
</author>
<author>
<name sortKey="Goldsmith, Charles H" sort="Goldsmith, Charles H" uniqKey="Goldsmith C" first="Charles H" last="Goldsmith">Charles H. Goldsmith</name>
<affiliation wicri:level="1">
<nlm:aff id="I1">Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, ON, Canada</nlm:aff>
<country xml:lang="fr">Canada</country>
<wicri:regionArea>Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, ON</wicri:regionArea>
</affiliation>
<affiliation wicri:level="1">
<nlm:aff id="I4">Biostatistics Unit, Father Sean O’Sullivan Research Center, St Joseph’s Healthcare Hamilton, Hamilton, ON, Canada</nlm:aff>
<country xml:lang="fr">Canada</country>
<wicri:regionArea>Biostatistics Unit, Father Sean O’Sullivan Research Center, St Joseph’s Healthcare Hamilton, Hamilton, ON</wicri:regionArea>
</affiliation>
<affiliation wicri:level="1">
<nlm:aff id="I16">Faculty of Health Sciences, Simon Fraser University, Burnaby, BC, Canada</nlm:aff>
<country xml:lang="fr">Canada</country>
<wicri:regionArea>Faculty of Health Sciences, Simon Fraser University, Burnaby, BC</wicri:regionArea>
</affiliation>
</author>
</analytic>
<series>
<title level="j">BMC Medical Research Methodology</title>
<idno type="eISSN">1471-2288</idno>
<imprint>
<date when="2013">2013</date>
</imprint>
</series>
</biblStruct>
</sourceDesc>
</fileDesc>
<profileDesc>
<textClass></textClass>
</profileDesc>
</teiHeader>
<front>
<div type="abstract" xml:lang="en">
<sec>
<title>Background</title>
<p>Sensitivity analyses play a crucial role in assessing the robustness of the findings or conclusions based on primary analyses of data in clinical trials. They are a critical way to assess the impact, effect or influence of key assumptions or variations—such as different methods of analysis, definitions of outcomes, protocol deviations, missing data, and outliers—on the overall conclusions of a study.</p>
<p>The current paper is the second in a series of tutorial-type manuscripts intended to discuss and clarify aspects related to key methodological issues in the design and analysis of clinical trials.</p>
</sec>
<sec>
<title>Discussion</title>
<p>In this paper we will provide a detailed exploration of the key aspects of sensitivity analyses including: 1) what sensitivity analyses are, why they are needed, and how often they are used in practice; 2) the different types of sensitivity analyses that one can do, with examples from the literature; 3) some frequently asked questions about sensitivity analyses; and 4) some suggestions on how to report the results of sensitivity analyses in clinical trials.</p>
</sec>
<sec>
<title>Summary</title>
<p>When reporting on a clinical trial, we recommend including planned or
<italic>posthoc</italic>
sensitivity analyses, the corresponding rationale and results along with the discussion of the consequences of these analyses on the overall findings of the study.</p>
</sec>
</div>
</front>
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<pmc-dir>properties open_access</pmc-dir>
<front>
<journal-meta>
<journal-id journal-id-type="nlm-ta">BMC Med Res Methodol</journal-id>
<journal-id journal-id-type="iso-abbrev">BMC Med Res Methodol</journal-id>
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<issn pub-type="epub">1471-2288</issn>
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<article-id pub-id-type="pmc">3720188</article-id>
<article-id pub-id-type="publisher-id">1471-2288-13-92</article-id>
<article-id pub-id-type="doi">10.1186/1471-2288-13-92</article-id>
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<subject>Commentary</subject>
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<article-title>A tutorial on sensitivity analyses in clinical trials: the what, why, when and how</article-title>
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</contrib-group>
<aff id="I1">
<label>1</label>
Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, ON, Canada</aff>
<aff id="I2">
<label>2</label>
Departments of Pediatrics and Anesthesia, McMaster University, Hamilton, ON, Canada</aff>
<aff id="I3">
<label>3</label>
Center for Evaluation of Medicine, St Joseph’s Healthcare Hamilton, Hamilton, ON, Canada</aff>
<aff id="I4">
<label>4</label>
Biostatistics Unit, Father Sean O’Sullivan Research Center, St Joseph’s Healthcare Hamilton, Hamilton, ON, Canada</aff>
<aff id="I5">
<label>5</label>
Population Health Research Institute, Hamilton Health Sciences, Hamilton, ON, Canada</aff>
<aff id="I6">
<label>6</label>
Department of Psychiatry and Behavioral Neurosciences, McMaster University, Hamilton, ON, Canada</aff>
<aff id="I7">
<label>7</label>
Population Genomics Program, McMaster University, Hamilton, ON, Canada</aff>
<aff id="I8">
<label>8</label>
GSK, Mississauga, ON, Canada</aff>
<aff id="I9">
<label>9</label>
Department of Kinesiology, University of Waterloo, Waterloo, ON, Canada</aff>
<aff id="I10">
<label>10</label>
Department of Nephrology, Toronto General Hospital, Toronto, ON, Canada</aff>
<aff id="I11">
<label>11</label>
Department of Pediatrics, McMaster University, Hamilton, ON, Canada</aff>
<aff id="I12">
<label>12</label>
Michael G. DeGroote School of Medicine, McMaster University, Hamilton, ON, Canada</aff>
<aff id="I13">
<label>13</label>
McMaster Integrative Neuroscience Discovery & Study (MiNDS) Program, McMaster University, Hamilton, ON, Canada</aff>
<aff id="I14">
<label>14</label>
Department of Biostatistics, Korea University, Seoul, Korea</aff>
<aff id="I15">
<label>15</label>
Department of Clinical Epidemiology, University of Ottawa, Ottawa, ON, Canada</aff>
<aff id="I16">
<label>16</label>
Faculty of Health Sciences, Simon Fraser University, Burnaby, BC, Canada</aff>
<pub-date pub-type="collection">
<year>2013</year>
</pub-date>
<pub-date pub-type="epub">
<day>16</day>
<month>7</month>
<year>2013</year>
</pub-date>
<volume>13</volume>
<fpage>92</fpage>
<lpage>92</lpage>
<history>
<date date-type="received">
<day>11</day>
<month>12</month>
<year>2012</year>
</date>
<date date-type="accepted">
<day>10</day>
<month>7</month>
<year>2013</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright © 2013 Thabane et al.; licensee BioMed Central Ltd.</copyright-statement>
<copyright-year>2013</copyright-year>
<copyright-holder>Thabane et al.; licensee BioMed Central Ltd.</copyright-holder>
<license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by/2.0">
<license-p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (
<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/2.0">http://creativecommons.org/licenses/by/2.0</ext-link>
), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
</license>
</permissions>
<self-uri xlink:href="http://www.biomedcentral.com/1471-2288/13/92"></self-uri>
<abstract>
<sec>
<title>Background</title>
<p>Sensitivity analyses play a crucial role in assessing the robustness of the findings or conclusions based on primary analyses of data in clinical trials. They are a critical way to assess the impact, effect or influence of key assumptions or variations—such as different methods of analysis, definitions of outcomes, protocol deviations, missing data, and outliers—on the overall conclusions of a study.</p>
<p>The current paper is the second in a series of tutorial-type manuscripts intended to discuss and clarify aspects related to key methodological issues in the design and analysis of clinical trials.</p>
</sec>
<sec>
<title>Discussion</title>
<p>In this paper we will provide a detailed exploration of the key aspects of sensitivity analyses including: 1) what sensitivity analyses are, why they are needed, and how often they are used in practice; 2) the different types of sensitivity analyses that one can do, with examples from the literature; 3) some frequently asked questions about sensitivity analyses; and 4) some suggestions on how to report the results of sensitivity analyses in clinical trials.</p>
</sec>
<sec>
<title>Summary</title>
<p>When reporting on a clinical trial, we recommend including planned or
<italic>posthoc</italic>
sensitivity analyses, the corresponding rationale and results along with the discussion of the consequences of these analyses on the overall findings of the study.</p>
</sec>
</abstract>
<kwd-group>
<kwd>Sensitivity analysis</kwd>
<kwd>Clinical trials</kwd>
<kwd>Robustness</kwd>
</kwd-group>
</article-meta>
</front>
</pmc>
</record>

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