Validation of overall survival extrapolations made by TLV in the assessment of cost-effectiveness of oncology drugs in Sweden – A pilot study comparing extrapolated and observed life-years gained

Abstract

Aim The aim of the study is to assess the accuracy of overall survival (OS) extrapolations in cost-effectiveness analysis made by the Dental and Pharmaceutical Benefits Agency (TLV) to decide on the reimbursement and use of oncology drugs in Sweden. Material and methods TLV appraisals for oncology drugs were identified during a 5-year period (2013-2017). To be included each appraisal and health economic model must include a TLV base case extrapolation of OS. Further, Kaplan-Meier (KM) estimates on OS from the original and follow-up clinical trials must be available. Potential follow-up trials on OS were identified in ClinicalTrials.gov and the Lund University Libraries databases, and in the Swedish Medical Products Agency (MPA) and the European Medicines Agency (EMA) databases. In cases where the KM estimates were not available, data points from figures published in TLV’s appraisals were extracted using the semi-automated tools Digitizelt and WebPlotDigitizer. The accuracy of survival extrapolations was assessed by comparing extrapolated and observed life-years (LYs), using three different measures: 1) difference in LYs between the treatment and control group; 2) LYs in the treatment group, 3) LYs in the control group. Results We study TLV’s preferred OS extrapolations and show that on average they overestimate the observed mean gain in LYs by 24%, and underestimate observed LYs by 3% and 11% in the treatment and control group, respectively. Conclusions We conclude that it is feasible to validate OS extrapolations by comparing extrapolated and observed life-years. Even if survival extrapolations are reasonably accurate for the treatment group, this may still imply that extrapolations of LYs gained deviates to a larger extent. Follow-up studies on OS should be carried out to an increased extent to be able to validate, update and improve OS extrapolations in cost-effectiveness analysis of oncology drugs.