Applying a cost-based pricing model for innovative cancer treatments subject to indication expansion: A case study for pembrolizumab and daratumumab.

BACKGROUND: Expanding the indication of already approved immuno-oncology drugs presents treatment opportunities for patients but also strains healthcare systems. Cost-based pricing models are discussed as a possibility for cost containment. This study focuses on two drugs, pembrolizumab (Keytruda) and daratumumab (Darzalex), to explore the potential effect of indication broadening on the estimated price when using the cost-based pricing (CBP) model proposed by Uyl-de Groot and Löwenberg (2018). METHODS: The model was used to calculate cumulative yearly prices, cumulative prices per indication, and non-cumulative indication-based prices using inputs such as research and development (R&D) costs, manufacturing costs, eligible patient population, and a profit margin. A deterministic stepwise analysis and scenario analysis were conducted to examine how sensitive the estimated price is to the different input assumptions. RESULTS: The yearly cumulative cost-based prices (CBPs) ranged from €52 to €885 for pembrolizumab per vial and €823 to €31,941 for daratumumab per vial. Prices were higher in initial years or indications due to smaller patient populations, decreased over time or after additional indications. Sensitivity analysis showed that the number of eligible patients had the most significant impact on the estimated price. In the scenario analysis the profit margin contributed most to a higher CBPs for both drugs. Lower estimates resulted from assumed lower R&D costs. DISCUSSION: The estimated CBPs are consistently lower than Dutch list prices for pembrolizumab (€2,861), mainly resulting from larger patient populations in registered indications. However, daratumumab's list prices fall within the range of modeled CBPs depending on the year or indication (€4,766). Both CBPs decrease over time or with additional indications. The number of eligible patients and initial R&D costs have the most significant influence on the CBPs. These findings contribute to the ongoing discussions on pharmaceutical pricing, especially concerning cancer drugs with expanding indications.

Extrapolating empirical long-term survival data: the impact of updated follow-up data and parametric extrapolation methods on survival estimates in multiple myeloma.

BACKGROUND: In economic evaluations, survival is often extrapolated to smooth out the Kaplan-Meier estimate and because the available data (e.g., from randomized controlled trials) are often right censored. Validation of the accuracy of extrapolated results can depend on the length of follow-up and the assumptions made about the survival hazard. Here, we analyze the accuracy of different extrapolation techniques while varying the data cut-off to estimate long-term survival in newly diagnosed multiple myeloma (MM) patients. METHODS: Empirical data were available from a randomized controlled trial and a registry for MM patients treated with melphalan + prednisone, thalidomide, and bortezomib- based regimens. Standard parametric and spline models were fitted while artificially reducing follow-up by introducing database locks. The maximum follow-up for these locks varied from 3 to 13 years. Extrapolated (conditional) restricted mean survival time (RMST) was compared to the Kaplan-Meier RMST and models were selected according to statistical tests, and visual fit. RESULTS: For all treatments, the RMST error decreased when follow-up and the absolute number of events increased, and censoring decreased. The decline in RMST error was highest when maximum follow-up exceeded six years. However, even when censoring is low there can still be considerable deviations in the extrapolated RMST conditional on survival until extrapolation when compared to the KM-estimate. CONCLUSIONS: We demonstrate that both standard parametric and spline models could be worthy candidates when extrapolating survival for the populations examined. Nevertheless, researchers and decision makers should be wary of uncertainty in results even when censoring has decreased, and the number of events has increased.

Treatment of sporadic Burkitt lymphoma in adults, a retrospective comparison of four treatment regimens.

Burkitt lymphoma is an aggressive B cell malignancy accounting for 1-2% of all adult lymphomas. Treatment with dose-intensive, multi-agent chemotherapy is effective but associated with considerable toxicity. In this observational study, we compared real-world efficacy, toxicity, and costs of four frequently employed treatment strategies for Burkitt lymphoma: the Lymphome Malins B (LMB), the Berlin-Frankfurt-Münster (BFM), the HOVON, and the CODOX-M/IVAC regimens. We collected data from 147 adult patients treated in eight referral centers. Following central pathology assessment, 105 of these cases were accepted as Burkitt lymphoma, resulting in the following treatment groups: LMB 36 patients, BFM 19 patients, HOVON 29 patients, and CODOX-M/IVAC 21 patients (median age 39 years, range 14-74; mean duration of follow-up 47 months). There was no significant difference between age, sex ratio, disease stage, or percentage HIV-positive patients between the treatment groups. Five-year progression-free survival (69%, p = 0.966) and 5-year overall survival (69%, p = 0.981) were comparable for all treatment groups. Treatment-related toxicity was also comparable with only hepatotoxicity seen more frequently in the CODOX/M-IVAC group (p = 0.004). Costs were determined by the number of rituximab gifts and the number of inpatients days. Overall, CODOX-M/IVAC had the most beneficial profile with regards to costs, treatment duration, and percentage of patients completing planned treatment. We conclude that the four treatment protocols for Burkitt lymphoma yield nearly identical results with regards to efficacy and safety but differ in treatment duration and costs. These differences may help guide future choice of treatment.

How to prepare a systematic review of economic evaluations for clinical practice guidelines: database selection and search strategy development (part 2/3).

INTRODUCTION: This article is part of the series "How to prepare a systematic review of economic evaluations (EES) for informing evidence-based healthcare decisions", in which a five-step approach is proposed. Areas covered: This paper focuses on the selection of relevant databases and developing a search strategy for detecting EEs, as well as on how to perform the search and how to extract relevant data from retrieved records. Expert commentary: Thus far, little has been published on how to conduct systematic review EEs. Moreover, reliable sources of information, such as the Health Economic Evaluation Database, have ceased to publish updates. Researchers are thus left without authoritative guidance on how to conduct SR-EEs. Together with van Mastrigt et al. we seek to fill this gap.