Intention-to-treat concept: A review — TEI-tagged view

SandeepK Gupta · 2011 · statistics · doi:10.4103/2229-3485.83221 · full text at the source · TEI xml · tagged edition · index · concepts · authors
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This record’s own method is review, and the tags below follow from that. A review’s findings, quantities and statistics are things stated IN this paper, and some of them report results obtained elsewhere. No tag on this page names a different author. Measured across every review in this corpus, 81% of a review’s tags carry no citation at all — most of them are the review speaking. The corpus does not adjudicate the rest: read an unmarked tag as a claim this paper makes, not necessarily one it made first.
Other fields define these differently the same word, defined another way in another discipline
sample size 5 fields · heterogeneity 3 fields
Tags on this paper every tag the record carries, whether or not the words occur in the text below — a number is how many papers in the corpus carry that tag; a tag with no number is unique to this paper
intention-to-treat2 ITT analysis per-protocol modified ITT full analysis set noncompliance prognostic balance type II error3 sample size43 last observation carried forward noninferiority superiority trial heterogeneity9 review319
Method, as described: narrative review of the ITT principle and the regulatory guidance around it - FDA, CPMP and ICH E9 - written to introduce the concept to clinical research beginners

Our tag layer for this paper

Cross-disciplinary analysis
content-tags & facets: phenomenon · claim-type · cross-domain-transfer · mechanism · claim-relation · replication-status · limitation — grounded in the full text
phenomenonone analysis population with four names in circulation, each attached to a different regulator, and a modified variant defined case by case— “The International Conference on Harmonisation (ICH) E9 guideline on “Statistical Principles for Clinical Trials” uses the term “full analysis set” to describe the analysis set which is as complete as possible and as close as possible to the ITT ideal of including all randomized subjects.”
claim-typecritique— “It is a subset of the ITT population and allows the exclusion of some randomized subjects in a justified way (such as patients who were deemed ineligible after randomization or certain patients who never started treatment). However, the definition given to the modified ITT (mITT) in randomized controlled trial has been found to be irregular…
method — evidence— “Committee for Proprietary Medicinal Products (CPMP) note for guidance “Biostatistical Methodology in Clinical Trials for Marketing Authorisations for Medicinal Products” states that decisions concerning the analysis population should be guided by the principles underlying the “intention-to-treat” and the “per-protocol” strategies. When the…
object of study — evidence— “According to Fisher et al . (1990), the ITT analysis includes all randomized patients in the groups to which they were randomly assigned, regardless of their adherence with the entry criteria, regardless of the treatment they…
research question — evidence
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contribution — evidence
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transferfrom biostatistics: intention-to-treat is a statistical concept imported into the conduct and reporting of randomized controlled trials to handle noncompliance and missing outcomes
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transfers[0]
transferfrom randomization theory (trial design): the analysis set is defined by the randomized assignment rather than by the treatment actually received, which is what preserves the randomization
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transfers[1]
mechanismTHE DEFINITION IS A TRIPLE REFUSAL TO CONDITION ON ANYTHING THAT HAPPENED AFTER RANDOMISATION - `regardless of their adherence with the entry criteria, regardless of the treatment they actually received, and regardless of subsequent withdrawal from treatment or deviation from the protocol`
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mechanisms[0]
mechanismand the reason is that the alternative destroys what randomisation bought: `If noncompliant subjects and dropouts are excluded from the final analysis, it might create important prognostic differences among treatment groups` - and subjects `may be noncompliant or may drop out due to their response of treatment`
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mechanisms[1]
mechanismTHE COST IS PAID IN THE SAME COIN. `In ITT analysis, estimate of treatment effect is generally CONSERVATIVE because of DILUTION due to noncompliance` - the property that makes it unbiased is the property that makes it small
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mechanisms[2]
mechanismso the criticism is symmetrical: ITT `has been criticized for being too cautious and thus being more susceptible to type II error`
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mechanisms[3]
mechanismAND THE TWO POPULATIONS FAIL IN OPPOSITE DIRECTIONS, WHICH IS WHY THE CHOICE IS NOT NEUTRAL. `ITT tends to make the two treatments look similar, whereas the PP removes patients who do not complete treatment and is more able to reflect treatment differences`
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mechanisms[4]
mechanismTHE MODIFIED VARIANT HAS NO STABLE DEFINITION AT ALL - `the definition given to the modified ITT (mITT) in randomized controlled trial has been found to be irregular and arbitrary because there is a lack of consistent guidelines for its application. The mITT analysis allows a subjective approach in entry criteria`
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mechanisms[5]
mechanismand it is not one population but many: `multiple mITT populations can be defined for a single study such as clinical mITT and microbiological mITT`
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mechanisms[6]
mechanismTHE SAME OBJECT CARRIES A THIRD NAME FROM A THIRD AUTHORITY - ICH E9 `uses the term FULL ANALYSIS SET to describe the analysis set which is as complete as possible and as close as possible to the ITT ideal`
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mechanisms[7]
critiques the modified ITT population as used in randomised trials, whose definition the paper reports as irregular, arbitrary and lacking consistent guidelines
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claim_relations[0]
supports the CONSORT requirement that participants be analysed by the intention-to-treat principle and that deviations be fully reported
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claim_relations[1]
concedes that ITT dilutes the treatment effect and is more susceptible to type II error - the arguments against it 'appear valid'
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claim_relations[2]
sense`intention-to-treat` (Fisher et al. 1990) - all randomised patients in their assigned groups, `regardless of their adherence with the entry criteria, regardless of the treatment they actually received, and regardless of subsequent withdrawal`
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senses[0]
sense`intention-to-treat` (the slogan) - `once randomized, always analyzed`
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senses[1]
sense`full analysis set` (ICH E9) - the analysis set `as complete as possible and as close as possible to the ITT ideal` - the same object under a third name
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senses[2]
sense`modified ITT` - a subset with exclusions `in a justified way`, whose definition the literature finds `irregular and arbitrary`
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senses[3]
sense`ITT` as a whole-trial strategy - `better regarded as a complete trial strategy for design, conduct and analysis rather than as an approach to analysis alone`
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senses[4]
controlrandomisation itself - allocating subjects to arms after eligibility is assessed but before the intervention is given — held
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— rules out systematic difference between the groups at baseline; ITT exists to protect this and per-protocol analysis is what spends it
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controls[0]
controlrequiring full reporting of every deviation from random allocation and every missing response, as CONSORT does — held
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— rules out an ITT label attached to an analysis whose exclusions the reader cannot see; the guideline makes the departures visible rather than forbidding them
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controls[1]
controlrequiring the ITT and per-protocol analyses to agree before a non-inferiority claim is made — partial
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— rules out a conclusion that depends on which population was chosen - the two are known to fail in opposite directions, so agreement between them is informative
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controls[2]
weightthe modified ITT population as used in randomised trials, whose definition the paper reports as irregular, arbitrary and lacking consistent guidelines — 0.9
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claim_relations[0]
weightthe CONSORT requirement that participants be analysed by the intention-to-treat principle and that deviations be fully reported — 0.9
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claim_relations[1]
weightthat ITT dilutes the treatment effect and is more susceptible to type II error - the arguments against it 'appear valid' — 0.9
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claim_relations[2]
noteITT analysis —distinct-from→ per-protocol — 'ITT tends to…' Not two views of one number - two numbers, and the analyst picks which before seeing either.
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concept_edges[0]
relationITT analysis —distinct-from→ per-protocol — ITT keeps the noncompliers and dilutes the difference; per-protocol removes them and shows it - so the choice of population moves the answer, in a direction that is known in advance
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concept_edges[0]
weightITT analysis —distinct-from→ per-protocol — 0.95
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concept_edges[0]
auditsuperiority trial —distinct-from→ noninferiority — Audit 2026-09-28: DOUBTFUL - read against its full span and kept, but the span writes 'non-inferiority', and the ITT role differs between the two designs; distinct-from is loose.
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concept_edges[1]
notesuperiority trial —distinct-from→ noninferiority — 'WHEREAS the importance…' The same method, the same population, and its authority is a property of the question being asked - which is why 'use ITT' is not an instruction.
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concept_edges[1]
relationsuperiority trial —distinct-from→ noninferiority — ITT's standing depends on what the trial is trying to show: settled as primary in a superiority design, unsettled in a non-inferiority one
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concept_edges[1]
weightsuperiority trial —distinct-from→ noninferiority — 0.95
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concept_edges[1]
outcomecontrol — held
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controls[0]
outcomecontrol — held
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controls[1]
outcomecontrol — partial
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controls[2]
limitationThe guidelines do not agree about where the principle applies. `Whereas the importance of the ITT population analysis in superiority designs has been well accepted, however there is no consensus about its role in non-inferiority trials`
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limitations[0]
limitationand the proposed resolution is to require both and hope they agree - `noninferiority should be concluded only if both ITT and PP analyses permit that` - which is a procedure rather than a principle, and the paper notes the conservative effect of PP on such trials `has not been thoroughly explored`
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limitations[1]
limitationthe remedy offered for the missing data ITT cannot ignore is itself contested - last observation carried forward, `whereby the LAST AVAILABLE MEASUREMENT for each individual at the time point prior to withdrawal IS RETAINED in the analysis`, presented here without its known bias
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limitations[2]
limitationThis is a narrative review for beginners, not a systematic one. No search strategy, no inclusion criteria and no synthesis are reported; the claims about what the literature finds - including the central one about mITT - are carried by citation
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limitations[3]
limitationand the practical advice at the end withdraws the problem rather than solving it: `Anyone who follows these principles intelligently and has a vision to minimize bias should not worry further about 'INTENTION TO TREAT'`
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limitations[4]
Content tags
content-observations: finding · quantity · variable · definition · key-term — grounded in the full text
finding
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content_tags.findings[0]
finding
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content_tags.findings[1]
finding
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content_tags.findings[2]
finding
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content_tags.findings[3]
finding
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content_tags.findings[4]
finding
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content_tags.findings[5]
finding
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content_tags.findings[6]
quantity2 complications — noncompliance and missing outcomes - the two failures of a randomised trial that the principle is a response to
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content_tags.quantities[0]
variableanalysis population
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content_tags.variables[0]
definitionITT analysis
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content_tags.definitions[0]
definitionfull analysis set
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content_tags.definitions[1]
definitionmodified ITT
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content_tags.definitions[2]
definitionlast observation carried forward
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content_tags.definitions[3]
Concepts
terms this paper carries, each with the sentence it was cut from — the layer that joins one paper to another. Terms with no quote yet are on CONCEPTS.html.
conceptintention-to-treat — not defined in this paper's own words; the principle that every randomised subject is analysed in the group they were assigned to, whatever happened afterwards
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concepts[0]
conceptITT analysis — not defined in this paper's own words; Fisher et al. 1990: all randomised patients in their assigned groups, 'regardless of' entry criteria, treatment actually received, and subsequent withdrawal
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concepts[1]
conceptper-protocol — not defined in this paper's own words; the subset who completed the study without major protocol violations - the population ITT is defined against
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concepts[2]
conceptmodified ITT — not defined in this paper's own words; a subset of the ITT population with some exclusions 'in a justified way' - and the paper's finding is that 'justified' has no agreed content
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concepts[3]
conceptfull analysis set — not defined in this paper's own words; ICH E9's name for the analysis set 'as close as possible to the ITT ideal' - a third term for the same object, issued by a third authority
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concepts[4]
conceptnoncompliance — not defined in this paper's own words; subjects not taking the treatment they were assigned - one of the two failures ITT exists to absorb, and the source of its conservatism
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concepts[5]
conceptprognostic balance — not defined in this paper's own words; the comparability between arms that randomisation creates and that excluding dropouts destroys
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concepts[6]
concepttype II error — not defined in this paper's own words; the failure ITT is criticised for making more likely, by being 'too cautious'
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concepts[7]
conceptsample size — not defined in this paper's own words; preserved by ITT, because excluding noncompliers and dropouts reduces it and with it the statistical power
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concepts[8]
conceptlast observation carried forward — not defined in this paper's own words; the substitute for missing data - the last measurement before withdrawal is retained in the analysis
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concepts[9]
conceptnoninferiority — not defined in this paper's own words; the trial design where ITT's authority is unsettled - and where the paper reports that ITT alone is not preferred
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concepts[10]
conceptsuperiority trial — not defined in this paper's own words; the design where ITT is settled as primary and per-protocol as supportive
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concepts[11]
conceptheterogeneity — not defined in this paper's own words; what mixing noncompliers, dropouts and completers introduces into the final analysis - the cost side of the same decision
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concepts[12]
Statistics — cross-field join keys
field-invariant statistical terms, used in their statistical sense (gated on a number / symbol / test). A p-value or a standard deviation means the SAME thing in physics, biology, psychology and sociology — so these are the strongest cross-field join keys. Grounded verbatim.
a bias and a power loss that are the same property seen twice
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content_tags.statistics[0]

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