Evidence map›Paper›PMID 39580440›Full record

ArticleBMC medical research methodology2024

The role of the estimand framework in the analysis of patient-reported outcomes in single-arm trials: a case study in oncology.

Doranne Thomassen, Satrajit Roychoudhury, Cecilie Delphin Amdal, Dries Reynders, Jammbe Z Musoro, Willi Sauerbrei, Els Goetghebeur, Saskia le Cessie, SISAQOL-IMI Work Package 3

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Article in BMC medical research methodology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
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

8 citing papers in PubMed.

  1. Review
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  3. Article
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  5. Observational
  6. Observational
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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

9 authors.

Doranne ThomassenDepartment of Biomedical Data Sciences, Leiden University Medical Center, P.O. box 9600, Postzone S-05-S, Leiden, 2300 RC, The Netherlands. d.thomassen@lumc.nl.
Satrajit RoychoudhuryPfizer Inc, New York, NY, USA.
Cecilie Delphin AmdalResearch Support Services, Oslo University Hospital, Oslo, Norway.
Dries ReyndersDepartment of Applied Mathematics, Computer Science and Statistics, Ghent University, Ghent, Belgium.
Jammbe Z MusoroEuropean Organisation for Research and Treatment of Cancer (EORTC) Headquarters, Brussels, Belgium.
Willi SauerbreiInstitute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany.
Els GoetghebeurDepartment of Applied Mathematics, Computer Science and Statistics, Ghent University, Ghent, Belgium.
Saskia le CessieDepartment of Biomedical Data Sciences, Leiden University Medical Center, P.O. box 9600, Postzone S-05-S, Leiden, 2300 RC, The Netherlands.
SISAQOL-IMI Work Package 3

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPatient-reported outcomes (PROs) play an increasing role in the evaluation of oncology treatments. At the same time, single-arm trials are commonly included in regulatory approval submissions. Because of the high risk of biases, results from single-arm trials require careful interpretation. This benefits from a clearly defined estimand, or target of estimation. In this case study, we demonstrated how the ICH E9 (R1) estimand framework can be implemented in SATs with PRO endpoints.

methodsFor the global quality of life outcome in a real single-arm lung cancer trial, a range of possible estimands was defined. We focused on the choice of the variable of interest and strategies to deal with intercurrent events (death, treatment discontinuation and disease progression). Statistical methods were described for each estimand and the corresponding results on the trial data were shown.

resultsEach intercurrent event handling strategy resulted in its own estimated mean global quality of life over time, with a specific interpretation, suitable for a corresponding clinical research aim. In the setting of this case study, a 'while alive' strategy for death and a 'treatment policy' strategy for non-terminal intercurrent events were deemed aligned with a descriptive research aim to inform clinicians and patients about expected quality of life after the start of treatment.

conclusionsThe results show that decisions made in the estimand framework are not trivial. Trial results and their interpretation strongly depend on the chosen estimand. The estimand framework provides a structure to match a research question with a clear target of estimation, supporting specific clinical decisions. Adherence to this framework can help improve the quality of data collection, analysis and reporting of PROs in SATs, impacting decision making in clinical practice.

Indexed as

Lung NeoplasmsPatient Reported Outcome MeasuresQuality of LifeClinical Trials as TopicHumansMedical OncologyResearch DesignTreatment OutcomeEstimandOncologyPatient-reported outcomesQuality of lifeRepeated measurementsSingle-arm trial

Identifiers

PMID39580440
PMCPMC11585159

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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.