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Harvinaissairauksien taloudellinen arviointi: mitä päätöksien tueksi tulisi tuottaa?
In Finland, the drug retail prices are determined with a regressive pharmaceutical pricing scheme (PPS) that leads to higher absolute sales margins for products with higher wholesale prices. At the same time low-priced products are sold at prices below the true costs of drug delivery. Despite these characteristics retail prices are used to represent all drug costs in health economic evaluations that are required before societal reimbursement of new drugs can be granted. We assessed the impact of PPS induced cost differences on the results of cost-utility analyses in hypothetical examples. The examples show that the Finnish PPS worsens the ICERs obtained for more expensive pharmaceuticals. The Finnish PPS is
problematic when the aim is to provide Finnish patients with optimal, cost-effective treatments. In its current form, the PPS discourages innovation and comparability of results with other settings, and may prevent reimbursement of otherwise cost-effective treatments.
Cost-utility and expected value of perfect information related to trabectedin in the treatment of metastatic soft-tissue sarcoma: the publicly funded comments explored I read with interest the comments by Blomqvist, Johansson and Tarkkanen [1] (later, the commentators). Three key issues had been misunderstood concerning the article [2], which reported the cost-effectiveness analysis (CEA) of trabectedin in the treatment of metastatic soft-tissue sarcoma (mSTS) after anthracycline/ifosfamide: means were mixed with medians [1], the CEA [2] followed the official Finnish setting and guidance for health economic evaluations [3] and the data presented [1] was not comparable/related to the CEA [2]. Ideally, survival times should be reported as exhaustive means together with Kaplan–Meier curves based on a large-enough randomized clinical trial, as this would enable an unbiased analysis of hazard ratios—the time-to-event summary statistic of choice [4]. However, most trials provide median survivals when all patients have not met the end points and the valid estimation of means based on the censored data could result in statistical modelling/estimation. While it is possible to carry out CEAs and indirect comparisons (ICs), including meta-analyses based on mean time-to-event data [5], medians are not a suitable basis for IC [4] or CEA.
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