• Branko Miladinovic, Ambuj Kumar, Rahul Mhaskar, and Benjamin Djulbegovic.
• Division and Center for Evidence-Based Medicine and Outcomes Research, Department of Internal Medicine, Morsani College of Medicine, University of South Florida, Tampa, Florida, USA.
• BMJ Open. 2014 Jan 1;4(10):e005249.

ObjectiveTo understand how often 'breakthroughs,' that is, treatments that significantly improve health outcomes, can be developed.DesignWe applied weighted adaptive kernel density estimation to construct the probability density function for observed treatment effects from five publicly funded cohorts and one privately funded group.Data Sources820 trials involving 1064 comparisons and enrolling 331,004 patients were conducted by five publicly funded cooperative groups. 40 cancer trials involving 50 comparisons and enrolling a total of 19,889 patients were conducted by GlaxoSmithKline.ResultsWe calculated that the probability of detecting treatment with large effects is 10% (5-25%), and that the probability of detecting treatment with very large treatment effects is 2% (0.3-10%). Researchers themselves judged that they discovered a new, breakthrough intervention in 16% of trials.ConclusionsWe propose these figures as the benchmarks against which future development of 'breakthrough' treatments should be measured.Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

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