Adherence with capecitabine: A population-based analysis based on prescription refill data

Abstract

Background

Patient adherence is important with the increasing use of oral anticancer drugs. Recent studies reported different capecitabine adherence rates based on self-reporting and microelectronic monitoring of the medication bottle. Patient’s awareness of being monitored may confound these results. Prescription records provide a larger and more objective dataset for adherence investigation. We report the use of computer algorithm and manual review of prescription and medical documentation to determine the rate of capecitabine adherence.

Methods

Two years of capecitabine prescription records from five ambulatory cancer centres were reviewed. Prescription data were extracted using a custom Java-based software tool to compare the predicted vs. actual dispensing date. The difference between the dates was the primary adherence measure (altered treatment date incident) and estimated using a computer algorithm and by manual review of medical charts.

Results

Of 4412 refill prescriptions, 45.2% was associated with an altered treatment date incident based on the initial computer algorithm. This was reduced to 29.5% after adjusting for clinic scheduling processes and 10.2% after manual chart review to adjust for valid reasons for delay. The reasons for altered treatment date incident were not identified in 52.2% of prescriptions.

Conclusions

Adherence rate of capecitabine based on refill data seem to be high and consistent with other findings based on patient self-report. Population analysis of prescription data with custom computer algorithm may identify trends in capecitabine adherence with some efficiency. Manual review would likely be required to verify these results. The accuracy of using altered prescription refill dates as an adherence measure requires further studies.