OBJECTIVES

Single-arm and open-label clinical studies are common in oncology drug development, leading to a frequent need for contextualization of results and provision of other means of comparison for cost-effectiveness models. The utility of current approaches such as naïve comparisons, historical control benchmarking, and matching adjusted indirect comparison is limited. An alternative approach is the use of routinely collected data from Electronic Medical Records (EMRs). This study sought to determine if overall survival (OS) in advanced non-small cell lung cancer patients from a clinical trial comparator arm could be replicated using EMR data

METHODS

De-identified EMR-derived patient data from Flatiron Health were matched via propensity scores to Project Data Sphere clinical trial data for study NCT00457392 of sunitinib plus erlotinib versus erlotinib alone to compare overall survival outcomes. A Cox regression model stratified for dataset was used to estimate the hazard ratio and 95% confidence interval for OS.

RESULTS

The Kaplan Meier curves were comparable for the first period after start of treatment, but differed after median survival was reached, with the Flatiron dataset achieving longer median OS. This deviation was strongly associated with differences in post-erlotinib treatment options introduced between the clinical trial period and the EMR period. Splitting the Flatiron data in two, related to the period from which the data were obtained (pre- or post-2013), resulted in a better match for the period closer to the trial (HR: 1.12 P=0.219) than for the later period (HR: 1.23 P=0.039).

CONCLUSIONS

Our results demonstrate that the time period in which EMR data are collected is important when matching to trial data. EMR data can contextualize the OS benefit for single-arm or uncontrolled trials run in the same time period. Further exploration of time-varying effects on OS is warranted.