Using pharmacy management systems for research: survival outcomes for lenalidomide in multiple myeloma in the clinical setting

Abstract

Background Health records can be used to measure medicine use and health outcomes. The public subsidy of lenalidomide in Australia was based on two phase III trials showing improved survival. Objective To use hospital pharmacy information management systems to determine survival outcomes for lenalidomide as a second line treatment in relapsed or refractory multiple myeloma (RRMM) patients. Setting Five public hospitals in Queensland, Australia. Method We extracted data on medicine use and survival for RRMM patients planned to start lenalidomide from pharmacy management and pathology databases. Descriptive statistical analyses (Kaplan-Meier curves) were used to calculate overall survival. Main outcome measure Overall survival. Results There were 136 patients who received at least one lenalidomide dose and 2234 cycles were ordered. The median age was 69 years and 54% were male. Two lenalidomide containing protocols were considered: 90% of patients had lenalidomide plus dexamethasone; 18% had lenalidomide plus dexamethasone with cyclophosphamide. The median starting lenalidomide dose was 20 mg (range 4.3-25 mg) on days 1-21 of a 28-day cycle. Median time on treatment 9.4 months (range 0.5-71.7 months). Median overall survival was 45.4 months (range 12.0-70.5 months). Conclusion The median survival in our study compared favourably to clinical trials. Patients and clinicians can be reassured that outcomes in this clinical setting are as good as those observed in trials.

Smartphone-Based and Data-Driven Superstructure State Prediction Method for Highway Bridges in Service

“…In addition, the existence of censored data is a common data problem in bridge data samples, which can affect bridge degradation analysis [ 7 ]. Survival analysis theory has been widely used in medicine, pharmacy, patient prognosis, economics, and other fields because it can process censored data and does not require many assumptions about the form of survival function [ 8 , 9 , 10 , 11 , 12 ]. Therefore, survival analysis has been gradually applied to the deterioration analysis of the service performance of engineering structures in recent years [ 13 , 14 ].…”