Evidence map›Paper›PMID 32084191›Full record

ArticlePloS one2020

Using practice effects for targeted trials or sub-group analysis in Alzheimer's disease: How practice effects predict change over time.

Guoqiao Wang, Richard E Kennedy, Terry E Goldberg, Mackenzie E Fowler, Gary R Cutter, Lon S Schneider

Abstract read
In one paragraph

Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

  1. Trial
  2. Trial
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Statistical considerations when estimating time-saving treatment effects in Alzheimer's disease clinical trials.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024
    Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. 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.

Guoqiao WangDivision of Biostatistics, Washington University in St. Louis, St. Louis, Missouri, United States of America.ORCID 0000-0002-6808-8737
Richard E KennedyComprehensive Center of Aging Health, University of Alabama at Birmingham, Birmingham, Alabama, United States of America.
Terry E GoldbergDepartment of Psychiatry, Columbia University, New York, New York, United States of America.
Mackenzie E FowlerDepartment of Epidemiology, University of Alabama at Birmingham, Birmingham, Alabama, United States of America.ORCID 0000-0003-2952-3705
Gary R CutterDepartment of Biostatistics, University of Alabama at Birmingham, Birmingham, Alabama, United States of America.
Lon S SchneiderDepartment of Psychiatry and The Behavioral Sciences, Keck School of Medicine, University of Southern California, Los Angeles, California, United States of America.

Funding

USCADRC Diversity Supplement PachicanoP30AG066530 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI HELENA Chang CHUI, ARTHUR W TOGA · 2020 to 2026
$27.8M
NIA NIH HHS P30 AG066530
6 · The paper itself

Abstract

objectiveTo describe the presence of practice effects in persons with Alzheimer disease (AD) or mild cognitive impairment (MCI) and to evaluate how practice effects affect cognitive progression and the outcome of clinical trials.

methodsUsing data from a meta-database consisting of 18 studies including participants from the Alzheimer disease Cooperative Study (ADCS) and the Alzheimer Disease Neuroimaging Initiative (ADNI) with ADAS-Cog11 as the primary outcome, we defined practice effects based on the improvement in the first two ADAS-Cog11 scores and then estimated the presence of practice effects and compared the cognitive progression between participants with and without practice effects. The robustness of practice effects was investigated using CDR SB, an outcome independent the definition itself. Furthermore, we evaluated how practice effects can affect sample size estimation.

resultsThe overall percent of practice effects for AD participants was 39.0% and 53.3% for MCI participants. For AD studies, the mean change from baseline to 2 years was 12.8 points for the non-practice effects group vs 7.4 for the practice effects group; whereas for MCI studies, it was 4.1 for non-practice effects group vs 0.2 for the practice effects group. AD participants without practice effects progressed 0.9 points faster than those with practice effects over a period of 2 years in CDR-SB; whereas for MCI participants, the difference is 0.7 points. The sample sizes can be different by over 35% when estimated based on participants with/without practice effects.

conclusionPractice effects were prevalent and robust in persons with AD or MCI and affected the cognitive progression and sample size estimation. Planning of future AD or MCI clinical trials should account for practice effects to avoid underpower or considers target trials or stratification analysis based on practice effects.

Indexed as

Clinical Trials as TopicCognitionAlzheimer DiseaseDisease ProgressionHumansNeuroimagingSample Size

Identifiers

PMID32084191
PMCPMC7034859

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.