- An-Wen Chan, assistant professor and Phelan scientist
- 1Women’s College Research Institute, University of Toronto, ON, M5G 1N8, Canada
- anwen.chan{at}utoronto.ca
The high frequency and negative impact of selective reporting of data from clinical trials are well documented.1 The widespread occurrence of data suppression means that healthcare practitioners and policy makers largely make decisions on the basis of an incomplete and biased subset of trial results. Selective reporting can often be identified by reviewing trial protocols and publications; it can be mitigated by defining standard core outcome sets for trials, and by ensuring access to all unpublished and published data⇓.2 3
However, two linked articles highlight major difficulties in obtaining access to protocols and unpublished data for both industry and non-industry trials and provide new insight into trialists’ reasons for suppressing data.4 5 These types of challenges have been described before,6 7 and they reinforce the core principle that full knowledge of both the methods and results for all trials, independent of publication status, is essential for a complete and unbiased evaluation of an intervention.
Sources of information that should be consulted when appraising an intervention include trial protocols, registry records, regulatory agency documents, trial datasets, and journal publications. Smyth and colleagues (doi:10.1136/bmj.c7153) also show …
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