Literature DB >> 24080600

Reproducibility of research and preclinical validation: problems and solutions.

Lajos Pusztai1, Christos Hatzis, Fabrice Andre.   

Abstract

Lack of reproducibility in the scientific and lay literature of many scientific reports is an increasing concern, as are the high rates of failure to validate highly promising preclinical observations in clinical trials. There are many technical reasons why experimental results, particularly in cancer research, cannot be reproduced, including unrecognized variables in the complex experimental model, poor documentation of procedures, selective reporting of the most-positive findings, misinterpretation of technical noise as biological signal and, in the most extreme cases, fabrication of data. We suggest that cognitive biases in research and flaws in the academic incentive system also contribute to the publication of immature results. Recognition of these factors, which are often not discussed, provides additional strategies to improve reproducibility. We suggest that in addition to establishing better standards of data presentation and creating venues for publication of negative results, some changes to the grant submission and funding system could further improve the reproducibility of research findings.

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Year:  2013        PMID: 24080600     DOI: 10.1038/nrclinonc.2013.171

Source DB:  PubMed          Journal:  Nat Rev Clin Oncol        ISSN: 1759-4774            Impact factor:   66.675


  22 in total

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Review 9.  Biomarker studies: a call for a comprehensive biomarker study registry.

Authors:  Fabrice Andre; Lisa M McShane; Stefan Michiels; David F Ransohoff; Douglas G Altman; Jorge S Reis-Filho; Daniel F Hayes; Lajos Pusztai
Journal:  Nat Rev Clin Oncol       Date:  2011-03       Impact factor: 66.675

10.  Why most published research findings are false.

Authors:  John P A Ioannidis
Journal:  PLoS Med       Date:  2005-08-30       Impact factor: 11.613

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  31 in total

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Journal:  J Am Soc Nephrol       Date:  2015-11-04       Impact factor: 10.121

Review 2.  Valid statistical approaches for analyzing sholl data: Mixed effects versus simple linear models.

Authors:  Machelle D Wilson; Sunjay Sethi; Pamela J Lein; Kimberly P Keil
Journal:  J Neurosci Methods       Date:  2017-01-16       Impact factor: 2.390

3.  An experimental toolbox for characterization of mammalian collagen type I in biological specimens.

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Review 4.  Introducing Therioepistemology: the study of how knowledge is gained from animal research.

Authors:  Joseph P Garner; Brianna N Gaskill; Elin M Weber; Jamie Ahloy-Dallaire; Kathleen R Pritchett-Corning
Journal:  Lab Anim (NY)       Date:  2017-03-22       Impact factor: 12.625

Review 5.  The significance of meaning: why do over 90% of behavioral neuroscience results fail to translate to humans, and what can we do to fix it?

Authors:  Joseph P Garner
Journal:  ILAR J       Date:  2014

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Review 7.  Models to identify treatments for the acute and persistent effects of seizure-inducing chemical threat agents.

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8.  Reproducibility and Research Integrity.

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9.  Unvalidated antibodies and misleading results.

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Journal:  Breast Cancer Res Treat       Date:  2014-08-03       Impact factor: 4.872

10.  Sex Differences in Using Systemic Inflammatory Markers to Prognosticate Patients with Head and Neck Squamous Cell Carcinoma.

Authors:  Ching Ying Lin; Hyunwoo Kwon; Guillermo O Rangel Rivera; Xue Li; Dongjun Chung; Zihai Li
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2018-07-26       Impact factor: 4.254

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