OBJECTIVES:

When including data from an external control arm to estimate comparative effectiveness, there is a choice of when to set ‘time zero’, the point at which a patient would be eligible/enrolled in a contemporary study and from which outcomes are counted. Where patients receive multiple lines of eligible therapy, multiple potential starting points exist, and which time point to chose is a complex issue.

METHODS:

A simulation study was conducted, where patients received multiple prior lines of therapy before entering either a intervention or control cohort. The results from control and intervention datasets were compared using eight methods for selecting time zero. The base case comparison was set up to be biased against the intervention (which is generally received later), with methods compared in their ability to estimate the true intervention effectiveness. Sensitivity analyses explored the impact of study attributes (such as sample size and effect size) and degree of overlap in time varying covariates (such as prior lines of therapy) on study results.

RESULTS:

Of the eight methods, five (all lines, random line, systematically selecting groups based on mean absolute error, root mean square error, or propensity scores) showed good performance in accounting for differences between the line at which patients were included. First eligible line was seen to be statistically inefficient by frequently having a poor overlap with the intervention study. All lines (with censoring) cannot be used for survival outcomes. Last Eligible line cannot be recommended. These findings were consistent over sensitivity analyses.

CONCLUSIONS:

Multiple methods are available for selecting the most appropriate time zero from an external control arm. Based on the simulation we demonstrate that some methods frequently perform poorly, with several viable methods remaining. In selecting between the viable methods, analysts should consider the context of their analysis, and justify the approach selected.