Evidence map›Paper›PMID 37244885›Full record

ArticleTherapeutic innovation & regulatory science2023

Defining Clinical Trial Estimands: A Practical Guide for Study Teams with Examples Based on a Psychiatric Disorder.

Elena Polverejan, Michael O'Kelly, Nanco Hefting, Jonathan D Norton, Pilar Lim, Marc K Walton

Open access · hybridAbstract read
In one paragraph

Article in Therapeutic innovation & regulatory science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
8.6field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 15 citations in OpenAlex.

  1. Trial
  2. Article
  3. What should convince a clinician of disease modification in Alzheimer's disease clinical trials?Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
    Review
  4. Article
  5. Article
  6. Estimands for Early-Phase Dose Optimization Trials in Oncology.Biometrical journal. Biometrische Zeitschrift · 2025
    Article
  7. Review
  8. Article
  9. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 3 institutions in 2 countries.

Elena PolverejanStatistics and Decision Sciences, Janssen Pharmaceuticals - Johnson & Johnson, 1125 Trenton-Harbourton Rd, Titusville, NJ, 08560, USA. epolvere@its.jnj.com.ORCID 0000-0002-2813-4364
Michael O'KellyCenter for Statistics in Drug Development, IQVIA, Dublin 3, Ireland.
Nanco HeftingGlobal Clinical Development, Therapeutic Area Psychiatry, H. Lundbeck A/S, Valby, Denmark.
Jonathan D NortonStatistical & Quantitative Sciences, Takeda Pharmaceuticals U.S.A., Inc., Lexington, MA, USA.
Pilar LimStatistics and Decision Sciences, Janssen Pharmaceuticals - Johnson & Johnson, 1125 Trenton-Harbourton Rd, Titusville, NJ, 08560, USA.
Marc K WaltonQuantitative Sciences Consulting, Statistics and Decision Sciences, Janssen Pharmaceuticals - Johnson & Johnson, Titusville, NJ, USA.
Johnson & Johnson (United States) · USLundbeck (Denmark) · DKTakeda (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

While the ICH E9(R1) Addendum on "Estimands and Sensitivity Analysis in Clinical Trials" was released in late 2019, the widespread implementation of defining and reporting estimands across clinical trials is still in progress and the engagement of non-statistical functions in this process is also in progress. Case studies are sought after, especially those with documented clinical and regulatory feedback. This paper describes an interdisciplinary process for implementing the estimand framework, devised by the Estimands and Missing Data Working Group (a group with clinical, statistical, and regulatory representation) of the International Society for CNS Clinical Trials and Methodology. This process is illustrated by specific examples using various types of hypothetical trials evaluating a treatment for major depressive disorder. Each of the estimand examples follows the same template and features all steps of the proposed process, including identifying the trial stakeholder(s), the decisions they need to make about the investigated treatment in their specific role and the questions that would support their decision making. Each of the five strategies for handling intercurrent events are addressed in at least one example; the featured endpoints are also diverse, including continuous, binary and time to event. Several examples are presented that include specifications for a potential trial design, key trial implementation elements needed to address the estimand, and main and sensitivity estimator specifications. Ultimately this paper highlights the need to incorporate multi-disciplinary collaborations into implementing the ICH E9(R1) framework.

Indexed as

Major Depressive DisorderModels, StatisticalData Interpretation, StatisticalHumansResearch DesignDepressionEstimatorICH E9(R1)Intercurrent eventsMajor depressive disorderMissing dataStakeholderTreatment effect

Identifiers

PMID37244885
PMCPMC10224760
OpenAlexW4378575286

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.