Cancer trial errors revealed

Reich, Eugenie Samuel

doi:10.1038/469139a

Cited by 24 publications

(8 citation statements)

References 5 publications

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“…Again, however, the lack of a universally recognized tagging system linking investigators to their deposited data has hindered authors from receiving due credit [9]. Recent scandals relating to falsified data that went long undetected in medicine [10] and psychology [11] also highlight the need to make data easily accessible for purposes of validation and to maintain public trust in science. One notable attempt to address the issues of gaining complete access to data is the Dryad repository, which serves as a storehouse for smaller datasets directly affiliated with publications in the biosciences [12].…”

Section: Discussionmentioning

confidence: 99%

Adventures in data citation: sorghum genome data exemplifies the new gold standard

et al. 2012

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Scientific progress is driven by the availability of information, which makes it essential that data be broadly, easily and rapidly accessible to researchers in every field. In addition to being good scientific practice, provision of supporting data in a convenient way increases experimental transparency and improves research efficiency by reducing unnecessary duplication of experiments. There are, however, serious constraints that limit extensive data dissemination. One such constraint is that, despite providing a major foundation of data to the advantage of entire community, data producers rarely receive the credit they deserve for the substantial amount of time and effort they spend creating these resources. In this regard, a formal system that provides recognition for data producers would serve to incentivize them to share more of their data.The process of data citation, in which the data themselves are cited and referenced in journal articles as persistently identifiable bibliographic entities, is a potential way to properly acknowledge data output. The recent publication of several sorghum genomes in Genome Biology is a notable first example of good data citation practice in the field of genomics and demonstrates the practicalities and formatting required for doing so. It also illustrates how effective use of persistent identifiers can augment the submission of data to the current standard scientific repositories.

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Section: Discussionmentioning

confidence: 99%

Adventures in data citation: sorghum genome data exemplifies the new gold standard

et al. 2012

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“…Second, diagnostic and prognostic gene signatures contain a large number of genes and the prediction algorithms are complex and not easy to use routinely in clinics (16). Third, the development of complex molecular tests based on DNA, RNA, proteins or metabolite profiles carries a series of problems inherent to all high-throughput techniques where large datasets are analyzed (17). Selecting the statistically significant results from a large dataset containing also nonsignificant data is challenging, because when multiple significance tests are calculated the probability that at least one reaches by chance significance increases with the number of tests performed (18).…”

Section: Transcriptomics and Proteomicsmentioning

confidence: 99%

“…It is therefore critical to control this multiplicity problem as well as to use one or more model validation technique for assessing how the results of a statistical analysis will generalize to an independent dataset (18). However, in the race to apply genomics technology, genomics works are too frequently published in which massive quantities of data containing avoidable errors are handled (17). Yet, when used correctly microarray technologies may be translated into score systems that can reproducibly predict clinical outcomes.…”

Section: Transcriptomics and Proteomicsmentioning

confidence: 99%

Systems biology for hepatologists

Mato

Martínez‐Chantar

Lu³

2014

Hepatology

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Medicine is expected to benefit from combining usual cellular and molecular studies with high-throughput methods (genomics, transcriptomics, proteomics and metabolomics). These methods, collectively known as omics, permit the determination of thousands of molecules (variations within genes, RNAs, proteins, metabolites) within a tissue, cell or biological fluid. The utilization of these methods is very demanding in terms of the design of the study, acquisition, storage, analysis and interpretation of the data. When carried out properly, these studies can reveal new etiological pathways, help to identify patients at risk for disease, and predict the response to specific treatments. Here we review these omics methods and mention several applications in hepatology research.

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“…The original paper was published in 2006 14 , and received high acknowledgement by other scientists as having significant contribution to the research field of cancer treatment. However, the research was shown in 2009 by two bioinformatic statisticians, Baggerly and Coombes, to contain incorrect data 15 17 . In this case, patient health may not have been compromised, because the treatment program at Duke was terminated as soon as it was discovered that there is suspicion of data manipulation.…”

mentioning

confidence: 94%

A Need to Archive Correct Biomedical Scientific Data and to Prevent Continued Citation of Retracted Scientific Publications

Tchao¹

2014

IJHAC

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The number of retracted peer reviewed scientific publications in the biomedical field has exponentially increased 15 times since early 2000 while the total number of publications only increased 1.44 times over the same period. Although retractions are rare (only 1 in 5,000 of all publications), the data and the science propounded by the retracted papers have significant impact because many retracted papers are published in high impact journals and are highly cited by other scientists. The scientific data contained in a retracted paper should be erased from the data bank. Even after retraction, many of these papers continue to be cited or can re-appear in future literature citation after a number of years. Recent analysis shows that in the fields of life science and medicine, 67.4% of the retracted papers are due to misconduct, of which 43.4% are due to fraud or suspected fraud. These flawed papers have high impact on public health and patient care as illustrated here by the cases of Wakefield and Potti. It is suggested here that a more stringent process of publication is necessary, including the review process and author certification of responsible citations of the literature that does not contain retractions.

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Cancer trial errors revealed

Cited by 24 publications

References 5 publications

Adventures in data citation: sorghum genome data exemplifies the new gold standard

Adventures in data citation: sorghum genome data exemplifies the new gold standard

Systems biology for hepatologists

A Need to Archive Correct Biomedical Scientific Data and to Prevent Continued Citation of Retracted Scientific Publications

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