Much of the published medical research is apparently flawed, cannot be replicated and/or has limited or no utility. This article presents an overview of the current landscape of biomedical research, identifies problems associated with common study designs and considers potential solutions. Randomized clinical trials, observational studies, systematic reviews and meta-analyses are discussed in terms of their inherent limitations and potential ways of improving their conduct, analysis and reporting. The current emphasis on statistical significance needs to be replaced by sound design, transparency and willingness to share data with a clear commitment towards improving the quality and utility of clinical research.

Protect us from poor-quality medical research / J.P.A. Ioannidis, S. Bhattacharya, J.L.H. Evers, F.V. der Veen, E. Somigliana, C.L.R. Barratt, G. Bontempi, D.T. Baird, P. Crosignani, P. Devroey, K. Diedrich, R.G. Farquharson, L.R. Fraser, J.P.M. Geraedts, L. Gianaroli, C. La Vecchia, L. Kersti, C. Magli, E. Negri, A. Sunde, J.S. Tapanainen, B.C. Tarlatzis, A.V. Steirteghem, A. Veiga. - In: HUMAN REPRODUCTION. - ISSN 0268-1161. - 33:5(2018 May), pp. 770-776. [10.1093/humrep/dey056]

Protect us from poor-quality medical research

E. Somigliana;P. Crosignani;C. La Vecchia;E. Negri;
2018

Abstract

Much of the published medical research is apparently flawed, cannot be replicated and/or has limited or no utility. This article presents an overview of the current landscape of biomedical research, identifies problems associated with common study designs and considers potential solutions. Randomized clinical trials, observational studies, systematic reviews and meta-analyses are discussed in terms of their inherent limitations and potential ways of improving their conduct, analysis and reporting. The current emphasis on statistical significance needs to be replaced by sound design, transparency and willingness to share data with a clear commitment towards improving the quality and utility of clinical research.
medical research; randomized clinical trial; meta-analysis; P-value; equipose
Settore MED/01 - Statistica Medica
mag-2018
29-mar-2018
Article (author)
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/569290
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