Diagnosing fraudulent baseline data in clinical trials

Diagnosing fraudulent baseline data in clinical trials

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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...

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Main Authors: Michael A. Proschan, Pamela A. Shaw, Vance Berger
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2020-01-01
Series:PLoS ONE
Online Access:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7527254/?tool=EBI
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spelling doaj-502381b713f4461ebe8ddec5295bcfa32020-11-25T04:00:26ZengPublic Library of Science (PLoS)PLoS ONE1932-62032020-01-01159Diagnosing fraudulent baseline data in clinical trialsMichael A. ProschanPamela A. ShawVance BergerThe 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.https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7527254/?tool=EBI
collection DOAJ
language English
format Article
sources DOAJ
author Michael A. Proschan
Pamela A. Shaw
Vance Berger
spellingShingle Michael A. Proschan
Pamela A. Shaw
Vance Berger
Diagnosing fraudulent baseline data in clinical trials
PLoS ONE
author_facet Michael A. Proschan
Pamela A. Shaw
Vance Berger
author_sort Michael A. Proschan
title Diagnosing fraudulent baseline data in clinical trials
title_short 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_sort diagnosing fraudulent baseline data in clinical trials
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2020-01-01
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.
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7527254/?tool=EBI
work_keys_str_mv AT michaelaproschan diagnosingfraudulentbaselinedatainclinicaltrials
AT pamelaashaw diagnosingfraudulentbaselinedatainclinicaltrials
AT vanceberger diagnosingfraudulentbaselinedatainclinicaltrials
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