There is always the unwritten rule that those who do the work of collecting data get the first crack at analyzing it. We are well past the point where that applies to PACE. Those authors have milked about all the positive spin from their data possible.
Now let me try a thought experiment relevant to the alleged objective improvements in patients. With a completely random binary response, like a coin flip, you could expect 50% to appear improved and 50% to appear worse. With a better range of possibilities than a single binary experiment, you should expect something like 40% better, 40% worse and 20% with no detectable change. If you resolutely ignore adverse outcomes, and do some wishful thinking, you can convert this to 60% responders and 40% nonresponders. That is what the PACE authors have reported, without detailed supporting evidence.
By counting those who do not contribute objective data both before and after therapy as participants in the trial you can allow the effort of participating to stratify your cohort so that most of those who decline the optional walk test after therapy also happen to be those who did not benefit. This will produce an apparent improvement in an objective measure -- which will not be replicated. What you would be measuring in that case was the effort patients put into the trial, not any benefits that came out. More rigorous exercise regimes would produce better stratification.
I don't actually know that the PACE authors did this. I don't know what they actually did. They are however behaving exactly as if allowing anyone else to examine data, and independently decide the percentage of patients who responded, would undermine their claims.
A recent study sent data requests to 200 authors of economics articles where it was stated ‘data available upon request’. Most of the authors refused. What does the scientific community think about those withholding their data? Are they guilty of scientific misconduct? Nicole Janz argues that if you don’t share your data, you are breaking professional standards in research, and are thus committing scientific misconduct. Classifying data secrecy as misconduct may be a harsh, but it is a necessary step.
