Evidence map›Paper›PMID 39678155›Full record

ArticleContemporary clinical trials communications2024

Baseline-dependent improvement in CF studies, plausibility of bias.

Ellen Graham, Sonya L Heltshe, Amalia S Magaret

Abstract read
In one paragraph

Article in Contemporary clinical trials communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Impact of day-to-day variation in FEV1 on measures of change: A conceptual description.Journal of cystic fibrosis : official journal of the European Cystic Fibrosis Society · 2024
    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

3 authors.

Ellen GrahamMS University of Washington, Department of Biostatistics, United States of America.
Sonya L HeltsheUniversity of Washington, Departments of Pediatrics and Biostatistics Seattle Children's Research Institute, Center for Respiratory Biology and Therapeutics, United States of America.
Amalia S MagaretUniversity of Washington, Departments of Pediatrics and Biostatistics Seattle Children's Research Institute, Center for Respiratory Biology and Therapeutics, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: It has been commonly reported that therapeutic treatments in cystic fibrosis (CF) have ceiling effects, such that their efficacy is diminished for persons with high pre-treatment health (Montgomery et al., 2012 and Newsome et al., 2019). Floor effects have also been reported where decline is of lower magnitude in those with below-average pre-treatment health (Harun et al., 2016; Konstan et al., 2012 and Szczesniak et al., 2017). When measurement error is present, the statistical literature has warned of exaggerated or spurious associations between pre-treatment measures and subsequent change (Chambless and Davis, 2003 and Yanez et al., 1998). Measurement error, equivalently described as day-to-day variation, has been described to occur in CF outcome measurements such as forced expiratory volume in 1 s taken by spirometry (FEV Methods: We conducted a simulation study to assess the potential for spurious floor or ceiling effects in studies of CF therapeutics. We considered uncontrolled or single-arm studies, and evaluated estimated association between pre-treatment FEV Results: When day-to-day variation was present in FEV Conclusion: Exaggerated ceiling effects are possible. Further studies could provide meaningful confirmation of ceiling effects in CF, perhaps reducing day-to-day variation by incorporating multiple pre- and post-treatment measurements.

Indexed as

Clinical trialCystic fibrosisMeasurement errorSingle-arm

Identifiers

PMID39678155
PMCPMC11639362

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Registered trials

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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.