Loss to follow-up

Abstract

In this issue, we answer three questions with respect to loss to follow-up in a clinical trial: How important is loss to follow-up? How is loss to follow-up calculated? How many patients can be lost to follow-up without mistrusting the results? 1. How important is loss to follow-up? The simple answer to this question is „very important” because loss to follow-up can severely compromise a study’s validity. Incomplete follow-up biases the results when either: The dropout rates are different between study groups; or The patients who drop out are different from those who do not drop out. Why do these situations make a difference? Because in each situation, those lost to follow-up often have a different prognosis than those who complete the study. For example, patients who receive treatment for cervical myelopathy may not return for follow-up because they became asymptomatic and felt no need to return to see the surgeon. Conversely, some patients may not return because they had a particularly bad outcome (worse pain or function) or complication, or because they died. In either case, bias can affect the validity of the inferences drawn from the study. 2. How is loss to follow-up calculated? There is much confusion about how to determine the proportion of patients lost to follow-up. In order to correctly calculate the follow-up rate, one needs to know the denominator. In a randomized controlled trial (RCT), the denominator for each group is the number of patients who were randomized, not the number who received the treatment. For example, suppose we have an RCT comparing two treatment groups, Group A and Group B. The investigators evaluate 178 patients and randomize 120; 61 to Group A and 59 to Group B (Fig 1). Following the figure, we note that 49 patients received treatment A and 52 received treatment B. At the final follow-up 40 were analyzed in Group A and 41 in Group B. How many were considered lost to follow-up? Many would consider the loss to follow-up rate to be 9 (18 %) of 49 in treatment A and 11 (21 %) of 52 in treatment B using as the denominator only those that were treated. However, the real proportion lost to follow-up must consider those who were randomly assigned, even if they did not receive treatment. In the present example, this is calculated as 21 (34 %) of 61 for treatment A and 18 (31 %) of 59 for treatment B.