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Methodological approach to determine minor, considerable, and major treatment effects in the early benefit assessment of new drugs

机译：在新药的早期获益评估中确定次要，重大和主要治疗效果的方法学方法

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At the beginning of 2011, the early benefit assessment of new drugs was introduced in Germany with the Act on the Reform of the Market for Medicinal Products (AMNOG). The Federal Joint Committee (G-BA) generally commissions the Institute for Quality and Efficiency in Health Care (IQWiG) with this type of assessment, which examines whether a new drug shows an added benefit (a positive patient-relevant treatment effect) over the current standard therapy. IQWiG is required to assess the extent of added benefit on the basis of a dossier submitted by the pharmaceutical company responsible. In this context, IQWiG was faced with the task of developing a transparent and plausible approach for operationalizing how to determine the extent of added benefit. In the case of an added benefit, the law specifies three main extent categories (minor, considerable, major). To restrict value judgements to a minimum in the first stage of the assessment process, an explicit and abstract operationalization was needed. The present paper is limited to the situation of binary data (analysis of 2 x 2 tables), using the relative risk as an effect measure. For the treatment effect to be classified as a minor, considerable, or major added benefit, the methodological approach stipulates that the (two-sided) 95% confidence interval of the effect must exceed a specified distance to the zero effect. In summary, we assume that our approach provides a robust, transparent, and thus predictable foundation to determine minor, considerable, and major treatment effects on binary outcomes in the early benefit assessment of new drugs in Germany. After a decision on the added benefit of a new drug by G-BA, the classification of added benefit is used to inform pricing negotiations between the umbrella organization of statutory health insurance and the pharmaceutical companies.
机译：2011年初，德国根据《药品市场改革法案》（AMNOG）引入了新药的早期获益评估。联邦联合委员会（G-BA）通常委托医疗质量和效率研究所（IQWiG）进行此类评估，该评估旨在检查新药是否相对于新药显示出更多的益处（与患者相关的治疗效果为正）。当前的标准疗法。 IQWiG必须根据负责的制药公司提交的档案评估附加收益的程度。在这种情况下，IQWiG面临着一项任务，即开发一种透明且合理的方法来实施如何确定附加收益的程度。对于附加利益，法律规定了三个主要程度类别（次要，相当大，主要）。为了在评估过程的第一阶段将价值判断限制在最低限度，需要进行明确而抽象的操作。本文仅将二进制数据的情况（分析2 x 2表）作为一种手段，使用相对风险作为一种效果度量。为了将治疗效果分类为次要，重大或主要附加收益，该方法论方法规定，该效果的（双面）95％置信区间必须超过到零效果的指定距离。总而言之，我们假设我们的方法为在德国新药的早期获益评估中确定对二元结局的次要，重大和主要治疗效果提供了可靠，透明且可预测的基础。在G-BA决定新药的附加利益后，附加利益的分类将用于为法定健康保险总括组织与制药公司之间的定价谈判提供依据。

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