Triumph of the aggregate

It is easy to misinterpret the application of aggregate data to individuals by equating group probabilities to individuals.10 Thus, if a trial of excisional surgery for melanoma showed that 95% of participants (similar to your patient) were clear from disease at 5 years, one cannot then tell your patient "You have a 95% chance of being clear at 5 years with this treatment" since this 95% refers to the group and not the individual. The patient in front of you will either clear or not clear - the patient's fate or response is already determined at that moment by that patient's microdisease and other cofactors such as immunological status, much of which may be under genetic influence. However, it is correct to tell that patient that "95% of people similar to you are clear at 5 years".

This inability to directly map aggregate data directly to individuals is not unique to RCTs - it applies to most basic science.11 Our everyday "clinical experience" with a particular drug is, after all, a form of aggregation of data based on recollection of treatment responses amongst groups of previous patients. The same difficulties in predicting whether the next patient will respond to that drug and by how much exists more in anecdote-based clinical practice than in an RCT-based approach.

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