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"Open mesh" or "strictly selected population" recruitment? The experience of the randomized controlled MeMeMe trial

Authors Cortellini M, Berrino F, Pasanisi P

Received 22 February 2017

Accepted for publication 31 March 2017

Published 6 July 2017 Volume 2017:11 Pages 1127—1132


Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 2

Editor who approved publication: Dr Johnny Chen

Mauro Cortellini, Franco Berrino, Patrizia Pasanisi

Department of Preventive & Predictive Medicine, Foundation IRCCS National Cancer Institute of Milan, Milan, Italy

Abstract: Among randomized controlled trials (RCTs), trials for primary prevention require large samples and long follow-up to obtain a high-quality outcome; therefore the recruitment process and the drop-out rates largely dictate the adequacy of the results. We are conducting a Phase III trial on persons with metabolic syndrome to test the hypothesis that comprehensive lifestyle changes and/or metformin treatment prevents age-related chronic diseases (the MeMeMe trial, EudraCT number: 2012-005427-32, also registered on [NCT02960711]). Here, we briefly analyze and discuss the reasons which may lead to participants dropping out from trials. In our experience, participants may back out of a trial for different reasons. Drug-induced side effects are certainly the most compelling reason. But what are the other reasons, relating to the participants’ perception of the progress of the trial which led them to withdraw after randomization? What about the time-dependent drop-out rate in primary prevention trials? The primary outcome of this analysis is the point of drop-out from trial, defined as the time from the randomization date to the withdrawal date. Survival functions were non-parametrically estimated using the product-limit estimator. The curves were statistically compared using the log-rank test (P=0.64, not significant). Researchers involved in primary prevention RCTs seem to have to deal with the paradox of the proverbial “short blanket syndrome”. Recruiting only highly motivated candidates might be useful for the smooth progress of the trial but it may lead to a very low enrollment rate. On the other hand, what about enrolling all the eligible subjects without considering their motivation? This might boost the enrollment rate, but it can lead to biased results on account of large proportions of drop-outs. Our experience suggests that participants do not change their mind depending on the allocation group (intervention or control). There is no single answer to sort out the short blanket syndrome.

Keywords: metformin, primary prevention, dropouts, survival analysis, metabolic syndrome

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