Estimated generic prices of cancer medicines deemed cost-ineffective in England: a cost estimation analysis. Issue 1 (20th January 2017) - Hill, Andrew; Redd, Christopher; Gotham, Dzintars; Erbacher, Isabelle; Meldrum, Jonathan; Harada, Ryo
Abstract : Objectives: The aim of this study was to estimate lowest possible treatment costs for four novel cancer drugs, hypothesising that generic manufacturing could significantly reduce treatment costs. Setting: This research was carried out in a non-clinical research setting using secondary data. Participants: There were no human participants in the study. Four drugs were selected for the study: bortezomib, dasatinib, everolimus and gefitinib. These medications were selected according to their clinical importance, novel pharmaceutical actions and the availability of generic price data. Primary and secondary outcome measures: Target costs for treatment were to be generated for each indication for each treatment. The primary outcome measure was the target cost according to a production cost calculation algorithm. The secondary outcome measure was the target cost as the lowest available generic price; this was necessary where export data were not available to generate an estimate from our cost calculation algorithm. Other outcomes included patent expiry dates and total eligible treatment populations. Results: Target prices were £411 per cycle for bortezomib, £9 per month for dasatinib, £852 per month for everolimus and £10 per month for gefitinib. Compared with current list prices in England, these target prices would represent reductions of 74–99.6%. Patent expiry dates were bortezomib 2014–22, dasatinib 2020–26, everolimus 2019–25 and gefitinib 2017. The total global eligible treatment population in 1 year is 769 736. Conclusions: Our findings demonstrate that affordable drug treatment costs are possible for novel cancer drugs, suggesting that new therapeutic options can be made available to patients and doctors worldwide. Assessing treatment cost estimations alongside cost-effectiveness evaluations is an important area of future research.