Fool’s gold? Why blinded trials are not always bestBMJ 2020; 368 doi: https://doi.org/10.1136/bmj.l6228 (Published 21 January 2020) Cite this as: BMJ 2020;368:l6228
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Clinical trials require blinding of treatment groups when the outcomes are determined by qualitative or semi-quantitative interpretation. Here the problem lies in the expectation of the interpretation. We expect treatment to be beneficial and thus different research papers show opposing results when the treatment used is financially supported by opposing vested interests [1,2].
Problems remain even when best efforts are made to blind or double-blind interpretations due to errors in interpretation. Biased qualitative and semi-quantitative results have erroneously introduced errors in clinical trials just as they have introduced errors into clinical care where sensitivity and specificity errors remain problematic.
The introduction of these errors – the inability to find a problem when present (sensitivity) or the inclusion of a problem when it doesn’t exist (specificity) – is too often a limiting factor in our decision-making. For that reason multiple physician groups including ASNC, SNMMI and CMS have called for medical imaging to apply true quantification . Such quantification removes the error introduced by qualitative and semi-quantitative imaging; removing the human error introduced both intentionally and unintentionally and replacing it with a New Standard for Research and Clinical Care.
Acknowledgement: FMTVDM issued to first author.
1. Zeraatkar D, Han MA, Guyatt GH, et al. Red and Processed Meat Consumption and Risk for All-Cause Mortality and Cardiometabolic Outcomes: A Systematic Review and Meta-analysis of Cohort Studies. Ann Intern Med. 2019;171:703–710. [Epub ahead of print 1 October 2019]. doi: https://doi.org/10.7326/M19-0655
2. Zhong VW, Van Horn L, Greenland P, et al. Associations of Processed Meat, Unprocessed Red Meat, Poultry, or Fish Intake With Incident Cardiovascular Disease and All-Cause Mortality. JAMA Internal Medicine 2020; Published online February 3, 2020. doi:10.1001/jamainternmed.2019.6969.
3. Fleming RM, Fleming MR, Dooley WC, Chaudhuri TK. Invited Editorial. The Importance of Differentiating Between Qualitative, Semi-Quantitative and Quantitative Imaging – Close Only Counts in Horseshoes. Eur J Nucl Med Mol Imaging. DOI:10.1007/s00259-019-04668-y. Published online 17 January 2020 https://link.springer.com/article/10.1007/s00259-019-04668-y
Competing interests: FMTVDM issued to first author.
Anand and colleagues make a well argued and timely contribution to the discussion around the importance of blinding in clinical trials. 
A critical consideration is that not all trials can be blinded. Otherwise well conducted trials of technology, such as telemonitoring of blood pressure, where blinding to allocation of the patient is impossible (and indeed knowledge of ongoing surveillance may be part of the intervention), are labelled ‘low quality’ even when relatively hard outcomes such as ambulatory monitoring are used as outcomes. This is important as this narrow interpretation of quality is often used by those who conduct systematic reviews  or construct guidelines  and may lead to important findings being casually dismissed whereas some trials, where blinding may be compromised by side-effects and changes in physiological parameters, continue to be hailed as ‘gold standard’.
1. Anand R, Norrie J, Bradley JM, McAuley DF, Clarke M. Fool’s gold? Why blinded trials are not always best. BMJ 2020;368:l6228
2.Hanley J, Ure J, Pagliari C, Sheikh A, McKinstry B. Experiences of patients and professionals participating in the HITS home blood pressure telemonitoring trial: a qualitative study. BMJ Open. 2013;3(5). doi: 10.1136/bmjopen-2013-002671. PubMed PMID: 23793649; PubMed Central PMCID: PMC3657666.
3.Higgins JPT, Altman DG, Gøtzsche PC, Jüni P, Moher D et al. The Cochrane Collaboration’s tool for assessing risk of bias in randomised trials. BMJ 2011; 343 doi: https://doi.org/10.1136/bmj.d5928
4.National Institute for Health and Care Excellence. Developing NICE guidelines: the manual. 2012. https://www.nice.org.uk/process/pmg20/chapter/reviewing-research-evidence
Competing interests: No competing interests