  Results from clinical trials can be susceptible to bias if investigators
choose their analysis approach after seeing trial data, as this can allow them
to perform multiple analyses and then choose the method that provides the most
favourable result (commonly referred to as 'p-hacking'). Pre-specification of
the planned analysis approach is essential to help reduce such bias, as it
ensures analytical methods are chosen in advance of seeing the trial data.
However, pre-specification is only effective if done in a way that does not
allow p-hacking. For example, investigators may pre-specify a certain
statistical method such as multiple imputation, but give little detail on how
it will be implemented. Because there are many different ways to perform
multiple imputation, this approach to pre-specification is ineffective, as it
still allows investigators to analyse the data in different ways before
deciding on a final approach. In this article we describe a five-point
framework (the Pre-SPEC framework) for designing a pre-specified analysis
approach that does not allow p-hacking. This framework is intended to be used
in conjunction with the SPIRIT (Standard Protocol Items: Recommendations for
Interventional Trials) statement and other similar guidelines to help
investigators design the statistical analysis strategy for the trial's primary
outcome in the trial protocol.
