Cited by 894Statistical Methods in Clinical TrialsMeta-analysis and systematic reviewsStatistical Methods and Bayesian Inference

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

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Thabane, Lehana, Mbuagbaw, Lawrence, Zhang, Shiyuan, Samaan, Zainab, Marcucci, Maura, Ye, Chenglin, Thabane, Marroon, Giangregorio, Lora, Dennis, Brittany, Kosa, Daisy, Debono, Victoria Borg, Dillenburg, Rejane, Fruci, Vincent, Bawor, Monica, Lee, Juneyoung, Wells, George, Goldsmith, Charles H·2013·BMC Medical Research Methodology

DOI 10.1186/1471-2288-13-92PMC PMC3720188

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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.

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Authors: Thabane, L., Mbuagbaw, L., Zhang, S., Samaan, Z., Marcucci, M., Ye, C., Thabane, M., Giangregorio, L., Dennis, B., Kosa, D., Debono, V. B., Dillenburg, R., Fruci, V., Bawor, M., Lee, J., Wells, G., & Goldsmith, C. H.
Affiliations: Population Health Research Institute (CA)
St. Joseph’s Healthcare Hamilton (CA)
McMaster University (CA)
GlaxoSmithKline (Canada) (CA)
University of Waterloo (CA)
Korea University (KR)
University of Ottawa (CA)
Simon Fraser University (CA)
Corresponding author: Thabane, Lehana
ORCID: Thabane, Lehana
Mbuagbaw, Lawrence
Zhang, Shiyuan
Samaan, Zainab
Marcucci, Maura
Giangregorio, Lora
Dennis, Brittany
Debono, Victoria Borg
Bawor, Monica
Lee, Juneyoung
Wells, George
Venue: BMC Medical Research Methodology
Publisher: Springer Science and Business Media LLC
Published: 2013-07-16
Volume: 13
Issue: 1
Pages: 92-92
ISSN: 1471-2288 (ISSN-L)
DOI: 10.1186/1471-2288-13-92
PMC: PMC3720188
OpenAlex: W2095437242
Cited by: 893
References: 76
Citations by year: 2026: 76 · 2025: 113 · 2024: 107 · 2023: 109 · 2022: 90 · 2021: 84 · 2020: 90 · 2019: 52 · 2018: 57 · 2017: 43 · 2016: 31 · 2015: 28 · 2014: 11 · 2013: 1
FWCI: 20.82
Type: journal article
Language: en
Open access: gold
doi.org
Licence: cc-by
creativecommons.org/licenses/by/2.0 (tdm)
Locations: BMC Medical Research Methodology (publishedVersion, cc-by)
Europe PMC (PubMed Central) (publishedVersion, cc-by)
PubMed Central (publishedVersion, cc-by)
PubMed (publishedVersion)
uO Research (University of Ottawa) (submittedVersion, public-domain)
Archivio Istituzionale della Ricerca (Universita Degli Studi Di Milano) (submittedVersion, other-oa)
Topics: Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
Keywords: sensitivity analysis, clinical trials, missing data, outliers, protocol deviations, outcome definitions
MeSH terms: Clinical Trials as Topic, Humans, Outcome and Process Assessment, Health Care, Research Design, Sensitivity and Specificity

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

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