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Intention-to-treat analysis

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variation of this is the participants who receive the treatment from the group they were not allocated to, who should be kept in their original group for the analysis. This issue causes no problems provided that the systematic reviewer can extract the appropriate data from the trial reports. The rationale for this approach is that, in the first instance, the goal is to estimate the effects of allocating an intervention in practice, not the effects in the subgroup of the participants who adhere to it.
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status for units assigned to different treatments or incorporation of compliance into the analysis. Although ITT analysis is widely employed in published clinical trials, it can be incorrectly described and there are some issues with its application. Furthermore, there is no consensus on how to carry
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ITT analysis requires participants to be included even if they did not fully adhere to the protocol. Participants who strayed from the protocol (for instance, by not adhering to the prescribed intervention, or by being withdrawn from active treatment) should still be kept in the analysis. An extreme
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In an ITT population, none of the patients are excluded and the patients are analyzed according to the randomization scheme. In other words, for the purposes of ITT analysis, everyone who is randomized in the trial is considered to be part of the trial regardless of whether he or she is dosed or
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For example, if people who have a more refractory or serious problem tend to drop out of a study at a higher rate, even a completely ineffective treatment may appear to be providing benefits if one merely compares the condition before and after the treatment for only those who finish the study
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Chêne, Geneviève; Morlat, Philippe; Leport, Catherine; Hafner, Richard; Dequae, Laurence; Charreau, Isabelle; Aboulker, Jean-Pierre; Luft, Benjamin; Aubertin, Jean; Vildé, Jean-Louis; Salamon, Roger (June 1998). "Intention-to-Treat vs. On-Treatment Analyses of Clinical Trial Data".
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which selects the subset of the patients who received the treatment of interest—regardless of initial randomization—and who have not dropped out for any reason. This approach can introduce biases to the statistical analysis. It can also inflate the chance of
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Alshurafa, Mohamad; Briel, Matthias; Akl, Elie A.; Haines, Ted; Moayyedi, Paul; Gentles, Stephen J.; Rios, Lorena; Tran, Chau; Bhatnagar, Neera; Lamontagne, Francois; Walter, Stephen D.; Guyatt, Gordon H. (15 November 2012).
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Alshurafa, Mohamad; Briel, Matthias; Akl, Elie A.; Haines, Ted; Moayyedi, Paul; Gentles, Stephen J.; Rios, Lorena; Tran, Chau; Bhatnagar, Neera; Lamontagne, Francois; Walter, Stephen D.; Guyatt, Gordon H. (2012).
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is based on the initial treatment assignment and not on the treatment eventually received. ITT analysis is intended to avoid various misleading artifacts that can arise in intervention research such as non-random
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In order to include such participants in an analysis, outcome data could be imputed which involves making assumptions about the outcomes in the lost participants. Another approach would be
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to the treatment groups in a study. ITT analysis provides information about the potential effects of treatment policy rather than on the potential effects of specific treatment.
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analyzed by the intention-to-treat (ITT) approach provide unbiased comparisons among the treatment groups. Intention to treat analyses are done to avoid the effects of
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Medical investigators often have difficulties in completing ITT analysis because of clinical trial issues like missing data or poor treatment protocol adherence.
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To address some of these issues, many clinical trials have excluded participants after the random assignment in their analysis, which is often referred to as
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Heritier, Stephane R; Gebski, Val J; Keech, Anthony C (October 2003). "Inclusion of patients in clinical trial analysis: the intention-to-treat principle".
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of participants from the study or crossover. ITT is also simpler than other forms of study design and analysis, because it does not require observation of
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Since it started in the 1960s, the principle of ITT has become widely accepted for the analysis of controlled clinical trials.
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An important problem is the occurrence of missing data for participants in a clinical trial. This can happen when patients are
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Montedori A; Bonacini MI; Casazza G; Luchetta ML; Duca P; Cozzolino F; Abraha I. (February 2011).
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Lachin JM (June 2000). "Statistical Considerations in the Intent-to-Treat Principle".
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out an ITT analysis in the presence of missing outcome data.
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Index

Intention to treat analysis
randomized controlled trial
attrition
compliance
Randomized clinical trials
crossover
dropout
random assignment
industry sponsorship
conflicts of interest
Missing data
lost to follow-up
a false positive
per-protocol analysis
Analysis of clinical trials
Protocol (natural sciences)
Clinical trial
Randomized controlled trial
"What is meant by intention to treat analysis? Survey of published randomised controlled trials"
doi
10.1136/bmj.319.7211.670
PMC
28218
PMID
10480822
"Inconsistent Definitions for Intention-To-Treat in Relation to Missing Outcome Data: Systematic Review of the Methods Literature"
Bibcode
2012PLoSO...749163A
doi
10.1371/journal.pone.0049163

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