Cargando…

Diagnosing fraudulent baseline data in clinical trials

The first table in many articles reporting results of a randomized clinical trial compares baseline factors across arms. Results that appear inconsistent with chance trigger suspicion, and in one case, accusation and confirmation of data falsification. We confirm theoretically results of simulation...

Descripción completa

Detalles Bibliográficos
Autores principales: Proschan, Michael A., Shaw, Pamela A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7527254/
https://www.ncbi.nlm.nih.gov/pubmed/32998158
http://dx.doi.org/10.1371/journal.pone.0239121
_version_ 1783589018525499392
author Proschan, Michael A.
Shaw, Pamela A.
author_facet Proschan, Michael A.
Shaw, Pamela A.
author_sort Proschan, Michael A.
collection PubMed
description The first table in many articles reporting results of a randomized clinical trial compares baseline factors across arms. Results that appear inconsistent with chance trigger suspicion, and in one case, accusation and confirmation of data falsification. We confirm theoretically results of simulation analyses showing that inconsistency with chance is extremely difficult to prove in the absence of any information about correlations between baseline covariates. We offer a reasonable diagnostic to trigger further investigation.
format Online
Article
Text
id pubmed-7527254
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-75272542020-10-02 Diagnosing fraudulent baseline data in clinical trials Proschan, Michael A. Shaw, Pamela A. PLoS One Research Article The first table in many articles reporting results of a randomized clinical trial compares baseline factors across arms. Results that appear inconsistent with chance trigger suspicion, and in one case, accusation and confirmation of data falsification. We confirm theoretically results of simulation analyses showing that inconsistency with chance is extremely difficult to prove in the absence of any information about correlations between baseline covariates. We offer a reasonable diagnostic to trigger further investigation. Public Library of Science 2020-09-30 /pmc/articles/PMC7527254/ /pubmed/32998158 http://dx.doi.org/10.1371/journal.pone.0239121 Text en https://creativecommons.org/publicdomain/zero/1.0/ This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 (https://creativecommons.org/publicdomain/zero/1.0/) public domain dedication.
spellingShingle Research Article
Proschan, Michael A.
Shaw, Pamela A.
Diagnosing fraudulent baseline data in clinical trials
title Diagnosing fraudulent baseline data in clinical trials
title_full Diagnosing fraudulent baseline data in clinical trials
title_fullStr Diagnosing fraudulent baseline data in clinical trials
title_full_unstemmed Diagnosing fraudulent baseline data in clinical trials
title_short Diagnosing fraudulent baseline data in clinical trials
title_sort diagnosing fraudulent baseline data in clinical trials
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7527254/
https://www.ncbi.nlm.nih.gov/pubmed/32998158
http://dx.doi.org/10.1371/journal.pone.0239121
work_keys_str_mv AT proschanmichaela diagnosingfraudulentbaselinedatainclinicaltrials
AT shawpamelaa diagnosingfraudulentbaselinedatainclinicaltrials