ICH E9: Statistical Principles for Clinical Trials

ICH E9 (Statistical Principles for Clinical Trials)

ICH E9, "Statistical Principles for Clinical Trials," is the International Council for Harmonisation guideline (finalized 1998) that sets out the core statistical methodology expected of a confirmatory clinical trial submitted to a regulatory authority. A trial's design and statistical analysis plan (SAP) are ICH E9-consistent when they are pre-specified before unblinding and address, at minimum: the trial's overall design and hypothesis structure (superiority, non-inferiority, or equivalence, each with its own margin and testing logic); the randomization and blinding scheme; the sample-size/power justification; the choice of analysis populations, most centrally the Full Analysis Set (FAS, an operationalization of the intention-to-treat principle) and the Per-Protocol Set (PPS); the handling of missing data; and the control of Type I error across multiple endpoints, interim looks, or comparisons (multiplicity). ICH E9 was substantially extended, not replaced, by its 2019 addendum ICH E9(R1), which introduced the estimand framework to address a gap the original guideline left largely implicit: how a trial's statistical objective should be translated into a precisely defined treatment-effect question before an analysis method is chosen to answer it.

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· Last updated 8 Aug 2026

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Worked examples

Is an instance

A phase 3 superiority trial's SAP, written and finalized before database lock, pre-specifies a two-sided alpha of 0.05, a sample size calculated to detect a specified effect size with 90% power, the Full Analysis Set as the primary analysis population (all randomized participants analyzed in their assigned group), and a Bonferroni-type correction across two co-primary endpoints. Each element traces to a specific ICH E9 principle: pre-specification, Type I error control, and the intention-to-treat-consistent population.

Is an instance

An active-controlled non-inferiority trial, following ICH E9's guidance that non-inferiority designs behave differently from superiority designs, pre-specifies a one-sided lower margin justified against historical evidence of the active control's effect, and reports both the Full Analysis Set and Per-Protocol Set as co-primary (rather than PP as merely supportive, as is typical in superiority trials) because diluted adherence in a non-inferiority trial can bias results toward a false finding of non-inferiority.

Looks similar, but isn't

Not an instance

A trial that finalizes its statistical analysis plan, chooses which populations to report as primary, or decides its multiplicity-adjustment method only after seeing unblinded results is not operating consistently with ICH E9, regardless of which specific statistical tests it ultimately reports -- pre-specification before unblinding, not the sophistication of the method itself, is the operative principle.

Most people typing “ICH E9” into a search box in 2026 want the estimand framework — and that is not in the 1998 guideline. It is in the 2019 addendum ICH E9(R1). The distinction matters because E9 itself was never revised: there is no E9(R2). The original Statistical Principles for Clinical Trials stands exactly as adopted at Step 4 on 5 February 1998, and E9(R1) sits beside it with separate numbering — references of the form x.y point into E9, references of the form A.x.y into the addendum.

The two documents, dated

E9 was approved under Step 2 on 16 January 1997, reached Step 4 on 5 February 1998, and was re-codified in November 2005 (code change, not content). In the EU it is CPMP/ICH/363/96, in force since 1 September 1998. The addendum — Addendum on Estimands and Sensitivity Analysis in Clinical Trials to the Guideline on Statistical Principles for Clinical Trials — was endorsed at Step 2 on 30 August 2017 and adopted by the Regulatory Members of the ICH Assembly under Step 4 on 20 November 2019 (the adopted document is dated 17 November 2019). In the EU it is EMA/CHMP/ICH/436221/2017, published 18 February 2020, legally effective 30 July 2020. Both are current; neither is superseded.

What E9 contains, section by section

3.3.1 / 3.3.2 — trials to show superiority, and trials to show equivalence or non-inferiority. E9 is the origin of the rule that these designs are not interchangeable and that a margin must be justified in advance; see non-inferiority vs superiority trial design.
3.5 Sample Size, with 3.4 Group Sequential Designs and 4.4 Sample Size Adjustment — the trio behind nearly every “ICH E9 sample size” search. Sample size must be justified against a pre-specified effect worth detecting; mid-trial adjustment is a planned design feature, not a rescue.
5.1 Prespecification of the Analysis — the principle governing the whole guideline. An analysis is E9-consistent because it was fixed before unblinding, not because it was sophisticated.
5.2.1 Full Analysis Set, 5.2.2 Per Protocol Set, 5.2.3 Roles of the Different Analysis Sets. E9 introduces the full analysis set as the practical form of the intention-to-treat principle — “as complete as possible and as close as possible to the intention-to-treat ideal of including all randomised subjects” — and gives the two aims governing analysis-set choices: minimise bias, avoid inflation of type I error.
5.3 Missing Values and Outliers, 5.6 Adjustment of Significance and Confidence Levels (multiplicity), 4.5 Interim Analysis and Early Stopping, 4.6 Role of Independent Data Monitoring Committee (IDMC).
2.3.1 / 2.3.2 — blinding and randomisation, the two design techniques for avoiding bias.

E9(R1): the gap the addendum closes

The addendum’s own diagnosis is that intention-to-treat, as E9 framed it, describes the effect of a treatment policy — subjects followed, assessed and analysed irrespective of compliance with the planned course of treatment — and that this is one legitimate clinical question among several, not the only one. What E9 lacked was a discipline for stating which treatment effect a trial intends to estimate before a method is chosen to estimate it. That is the estimand framework.

Section A.3.3 gives the attributes that jointly define an estimand: the treatment condition, the population targeted by the clinical question, the variable (endpoint) obtained for each patient, the specification of how intercurrent events are reflected, and the population-level summary providing the basis for comparison. Section A.3.2 names the five strategies for addressing intercurrent events: treatment policy, hypothetical, composite variable, while on treatment, principal stratum. An intercurrent event is a post-randomisation occurrence affecting interpretation — discontinuation, rescue medication, death — and the addendum is explicit that a treatment-policy strategy cannot be used for terminal events, because values of the variable after them do not exist.

A.5.2 and A.5.3 separate two things analysis plans routinely conflate: sensitivity analysis stress-tests the assumptions behind the estimate of the same estimand; supplementary analysis addresses a different question. Filing the latter under the former’s heading is a common way a statistical analysis plan drifts out of alignment with E9(R1).

What E9 does not do

E9 is not a menu of approved tests and prescribes no method for any endpoint. It is about pre-specification, bias, and control of type I error in confirmatory trials supporting a submission; exploratory work is treated separately (2.1.3). It does not displace trial-conduct guidance — it sits alongside ICH GCP. A trial can be fully GCP-compliant and still fail E9 by choosing its primary analysis population after unblinding.

Related terms

Estimand framework — the E9(R1) construct most “ICH E9” searches are aimed at.
Statistical analysis plan (SAP) — where pre-specification is discharged.
Intent-to-treat vs per-protocol analysis — sections 5.2.1 and 5.2.2.
Non-inferiority vs superiority trial design — section 3.3.
Randomization methods in clinical trials — section 2.3.2.
Randomized controlled trial (RCT) — the design E9 assumes.
ICH E2A — the safety-reporting counterpart in the same efficacy series.

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