The Cancer Drugs Fund in Practice and Under the New Framework

Celia Sabry-Grant (), Kinga Malottki and Alexander Diamantopoulos
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Celia Sabry-Grant: Symmetron Limited
Kinga Malottki: Symmetron Limited
Alexander Diamantopoulos: Symmetron Limited

PharmacoEconomics, 2019, vol. 37, issue 7, No 8, 953-962

Abstract: Abstract Background The Cancer Drugs Fund (CDF) was established in 2010 to improve access to treatments not routinely available. Having widely overspent, stricter budgeting rules were introduced in 2016. The CDF can now only include treatments with potential to be cost effective once sufficient data are collected. Objectives Our objective was to explore the process and criteria used for consideration of treatments under the new CDF framework and to describe the extent of evidence collection. Methods We identified CDF list, UK National Institute for Health and Care Excellence (NICE) and Scottish Medicines Consortium documents (10 May 2018). Data were collected on drugs and indications, reasons for inclusion in the CDF, data collection, incremental cost-effectiveness ratios (ICERs), and corresponding recommendations for Scotland. Results In total, 12 drugs were listed on the CDF in 17 indications, 12 of which were considered end-of-life care. The most common cancers were non-small-cell lung (n = 4), urothelial (n = 3), lymphocytic leukaemia (n = 2) and multiple myeloma (n = 2). The companies’ ICERs were generally lower than those from the committee and the evidence review group. Drugs were included in the CDF for 6–42 months, with the majority included for ≥18 months. Data were frequently collected on overall survival (n = 16) and progression-free survival (n = 5) using NHS systems and, frequently, ongoing trials. Conclusions Data collection frequently included overall survival and exceeded the 2 years recommended in the CDF strategy. It appears the CDF is allowing patients access to drugs long before they may become available for routine use. Our results are limited by the availability of published information and the small dataset.

Date: 2019
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DOI: 10.1007/s40273-019-00793-6

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