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In 2010, the Federal Parliament (Bundestag) of Germany passed a new law (Arzneimittelmarktneuordnungsgesetz, AMNOG) on the regulation of medicinal products that applies to all pharmaceutical products with active ingredients that are launched beginning January 1, 2011. The law describes the process to determine the price at which an approved new product will be reimbursed by the statutory health insurance system. The process consists of two phases. The first phase assesses the additional benefit of the new product versus an appropriate comparator (zweckmäßige Vergleichstherapie, zVT). The second phase involves price negotiation. Focusing on the first phase, this paper investigates requirements of benefit assessment of a new product under this law with special attention on the methods applied by the German authorities on issues such as the choice of the comparator, patient relevant endpoints, subgroup analyses, extent of benefit, determination of net benefit, primary and secondary endpoints, and uncertainty of the additional benefit. We propose alternative approaches to address the requirements in some cases and invite other researchers to help develop solutions in other cases.

Background : Pharmaceutical companies design clinical development programs to generate the data that they believe will support reimbursement for the experimental compound. Objective : The objective of the study was to present a process for using multicriteria decision analysis (MCDA) by a pharmaceutical company to estimate the probability of a positive recommendation for reimbursement for a new drug given drug and environmental attributes. Methods : The MCDA process included 1) selection of decisions makers who were representative of those making reimbursement decisions in a specific country; 2) two pre-workshop questionnaires to identify the most important attributes and their relative importance for a positive recommendation for a new drug; 3) a 1-day workshop during which participants undertook three tasks: i) they agreed on a final list of decision attributes and their importance weights, ii) they developed level descriptions for these attributes and mapped each attribute level to a value function, and iii) they developed profiles for hypothetical products ‘just likely to be reimbursed’; and 4) use of the data from the workshop to develop a prediction algorithm based on a logistic regression analysis. The MCDA process is illustrated using case studies for three countries, the United Kingdom, Germany, and Spain. The extent to which the prediction algorithms for each country captured the decision processes for the workshop participants in our case studies was tested using a post-meeting questionnaire that asked the participants to make recommendations for a set of hypothetical products. Results : The data collected in the case study workshops resulted in a prediction algorithm: 1) for the United Kingdom, the probability of a positive recommendation for different ranges of cost-effectiveness ratios; 2) for Spain, the probability of a positive recommendation at the national and regional levels; and 3) for Germany, the probability of a determination of clinical benefit. The results from the post-meeting questionnaire revealed a high predictive value for the algorithm developed using MCDA. Conclusions : Prediction algorithms developed using MCDA could be used by pharmaceutical companies when designing their clinical development programs to estimate the likelihood of a favourable reimbursement recommendation for different product profiles and for different positions in the treatment pathway. Keywords: multicriteria decision analysis; Spain; United Kingdom; Germany; reimbursement; additional benefit; cost-effectiveness (Published: 31 October 2014) Citation: Journal of Market Access & Health Policy 2014, 2 : 25270 - http://dx.doi.org/10.3402/jmahp.v2.25270

BACKGROUND: Non-inferiority (NI) trials in drug research are used to demonstrate that a new treatment is not less effective than an active comparator. Since phase IV trials typically aim at informing a clinical decision, the value of a phase IV non-inferiority trial hinges also on its clinical relevance. In such trials, clinical relevance would refer to the added benefit claims of a specific drug, apart from efficacy, relative to its comparator drug in the trial. METHODS: In this study, we reviewed 41 phase IV trials and extracted information on whether the authors mentioned any additional benefit beyond the NI (efficacy) claim of the drug and whether the additional benefit was proven in the trial. We checked whether the additional claim was based on descriptions only or on formal statistical analyses. RESULTS: Our results showed that 22 out of the 41 NI trials mentioned additional benefit of the test drug and most of these claims were related to the safety profile. Of all the post-authorization NI trials that claimed additional benefit, 10 out of 22 NI trials used formal statistical analyses to show additional benefit, and only one included a sample size calculation for the additional benefit prior to the trial. CONCLUSION: We conclude that there is room for improvement in terms of designing phase IV NI trials with added benefit claims and in proving these additional claims.