Reporting both baseline-adjusted effect and change-from-baseline group estimates

I recently analysed a randomised controlled trial whereby I adjusted the effect estimates to their respective baseline measures in a regression model, a practice I usually perform when analysing trial data (bunch of literature on this incl CONSORT statement).

When writing up the clinical study report I generally provide the the point and interval estimates of the effect adjusted to baseline measure (and other covariates if prespecified) and the point and interval estimates of the endpoints for each group. Furthermore, I plot the descriptive endpoint statistics per group over the various visits of the trial.

However, the investigators of the recent trial have asked me to provide, besides the effect estimate, the change-from-baseline estimates per trial arm.

I find this a little problematic as the difference between the two arm point estimates for change-from-baseline is often not the same as the point estimate of the effect adjusted to baseline (for reference see Twisk, J. et al. Different ways to estimate treatment effects in randomised controlled trials. Contemporary Clinical Trials Communications 10 , 80–85 (2018), specifically Table 5 Eq 1a vs 3a).

I’m a bit stuck on this as I think readers might be confused to what they may see as a discrepancy between the effect estimate adjusted to baseline and the difference between the two change-from-baseline group estimates. The investigators’ justification is that they would like to show the change from baseline for each arm.

I’m sympathetic to their request as the trial has an active comparator, and a side-by-side demonstration of change from baseline may be interesting. However, this is ultimately not the research question of the trial; the difference between the groups is and I think showing these changes in a graph can also be more informative.

I’d be very grateful for any advice on this and on how you would normally report these findings?

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Do not report the change from baseline. Because of reasons laid out in detail here, section 14.4 change from baseline is misleading. Regression to the mean is one of the prime issues.

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I generally analyze and report RCT results much as you describe, but you could also analyze change scores while still adjusting for baseline scores. This is just a re-parameterization of the model that analyzes post-treatment scores adjusted for baseline, and so the results will be the same, but expressed in terms of change scores. In Table 5 of the paper you reference, these correspond to models 1a and 3b, which show identical treatment effect estimates and standard errors.

No, that only works in the special case of a linear model with interval-scaled variables, and most importantly, readers will take your results out of context, quote them at medical conferences, make false conclusions, … Just say no.

Got it. Thanks. Yes, I was assuming a linear model; but your point about inviting misinterpretation is a good one.

Many thanks for your responses and advice. @f2harrell this is indeed in line with what Twisk et al observe. I’ll get back to the investigators about this.