In many randomised trials researchers measure a continuous variable at baseline and again as an outcome assessed at follow up. Baseline measurements are common in trials of chronic conditions where researchers want to see whether a treatment can reduce pre-existing levels of pain, anxiety, hypertension, and the like. Statistical comparisons in such trials can be made in several ways. Comparison of follow up (post-treatment) scores will give a result such as “at the end of the trial, mean pain scores were 15 mm (95% confidence interval 10 to 20 mm) lower in the treatment group.” Alternatively a change score can be calculated by subtracting the follow up score from the baseline score, leading to a statement such as “pain reductions were 20 mm (16 to 24 mm) greater on treatment than control.” If the average baseline scores are the same in each group the estimated treatment effect will be the same using these two simple approaches. If the treatment is effective the statistical significance of the treatment effect by the two methods will depend on the correlation between baseline and follow up scores. If the correlation is low using the change score will …
Vickers et al. (Sat,) studied this question.