Value and Price of Multi-indication Cancer Drugs in the USA, Germany, France, England, Canada, Australia, and Scotland

Abstract

Purpose: Oncology drugs are often approved for multiple indications, for which their clinical benefit varies. Aligning a single price to this differing value remains a challenge. This study examines the clinical and economic value, price, and reimbursement of multi-indication cancer drugs across seven countries, representing different approaches to value assessment, pricing, and coverage decisions: the USA, Germany, France, England, Canada, Australia, and Scotland.

Methods: Twenty-five multi-indication cancer drugs across 100 indications were identified with US Food and Drug Administration (FDA) approval between 2009 and 2019. For each indication data on Health Technology Assessment (HTA) recommendations, disease prevalence, and drug prices were obtained. Quality-adjusted life years (QALYs) gained, disease prevalence, list prices, and HTA outcomes were then compared across indications and regions.

Results: First approved indications provide a higher clinical benefit whilst targeting a smaller patient group than indication extensions. Quality-adjusted life year gains were higher for first (0.99, 95% CI 0.05-3.25) compared to second (0.51, 95% CI 0.02-1.63, p < 0.001) and third (0.58, 95% CI 0.05-2.07, p < 0.01) approved indications. Disease prevalence per 100,000 inhabitants was 20.7 (95% CI 0.2-63.3) for first compared to 27.1 (95% CI 1.5-109.6, p = 0.907) for second and 128.3 (95% CI 3.1-720.1, p < 0.001) for third approved indications. With each approved indication drug prices declined in Germany and France, remained constant in the UK, Canada, and Australia, whilst they increased in the USA. Negative HTA outcomes, clinical restrictions, and managed entry agreements (MEAs) were more frequently observed for indication extensions.

Conclusions: Results suggest that indication development is prioritised according to clinical value and disease prevalence. Countries employ different mechanisms to account for each indication's differential benefit, e.g., weighted-average prices (Germany, France, Australia), differential discounts (England, Scotland), clinical restrictions, and MEAs (England, Scotland, Australia, Canada). Value-based indication-specific pricing can help to align the benefit and price for multi-indication cancer drugs.

Fig. 1

Indication launch decisions under single-price policies: A theory and B evidence. A shows the differential value and number of patients for a given drug per indication. Indication development follows the natural order A, B, C, then D - priced at $P_A$ then $P_D$. Theory suggests that manufacturers may be incentivised to sequence and withhold indications according to clinical value and number of patients to extract the highest possible prices ($P_B$ and $P_C$) under a single pricing mechanism [6, 7, 12]. B illustrates evidence from a sample of 25 multi-indication cancer drugs. This evidence suggests that launch sequences are indeed prioritized by number of patients (measured by disease prevalence [23]) and clinical value (measured by incremental QALYs extracted from health technology assessment reports). Indications offering marginal incremental QALYs for a small population group are not launched. QALY quality-adjusted life year. Source(s) [6, 7, 12, 23]

Fig. 2

Flow diagram of multi-indication drugs included in the analysis, 2009–2019. CADTH Canadian Agency for Drugs and Technologies in Health, EMA European Medicines Agency, FDA US Food & Drug Administration, G-BA Federal joint Committee (“Gemeinsamer Bundesausschuss”), HAS Haute Autorité de Santé, HC Health Canada, NICE National Institute of Health and Care Excellence, PBAC Pharmaceutical Benefits Advisory Committee, SMC Scottish Medicines Consortium, TGA Therapeutic Goods Administration

Fig. 3

Indication characteristics by launch sequence. Average incremental QALYs gained (A), incremental LYs gained (B), disease prevalence (C), and ICERs (D) are compared across indication launch sequence. p values presented on the error bars compare the first to second, first to third, and first to not launch indications. p values on top of the graphs compare launched to not launched indications. p values calculated based on ANOVA with Dunnett’s-test and Student’s t test: *p < 0.05, **p < 0.01, ***p < 0.001. Bars show 95% confidence intervals. ICER incremental cost-effectiveness ratio, LY life year, QALY quality-adjusted life year

Fig. 4

Change in drug list prices by indication launch sequence. A illustrates the percentage change of list prices from first to second, first to third, and first to fourth launched indication according to health technology assessment approval date in the UK, France, Germany, Canada, and the USA. B presents list prices relative to UK values for first, second, and subsequently launched indications. Bars show 95% confidence intervals. p values: *p < 0.05, **p < 0.01, ***p < 0.001

Fig. 5

HTA outcomes by indication launch sequence. A presents the percentage of positive HTA outcomes across countries. Positive outcomes include “list” and “list with condition”. B shows the percentage of decisions with clinical restrictions in England, Scotland, Canada, and Australia. No restrictions were found in France and Germany. C displays financial and outcome-based managed entry agreements for England, Scotland, Canada, and Australia. Indication launch sequence was determined according to HTA approval date. p values calculated based on χ²-tests: *p < 0.05, **p < 0.01, ***p < 0.001. HTA health technology assessment