Collaboration for Outcomes Research and Evaluation, Faculty of Pharmaceutical Sciences, University of British Columbia, 2146 East Mall, Vancouver, BC, Canada.
J Clin Epidemiol. 2012 Aug;65(8):863-8. doi: 10.1016/j.jclinepi.2012.01.022. Epub 2012 May 30.
The uncertainty around number needed to treat (NNT) is often represented through a confidence interval (CI). However, it is not clear how the CI can help inform treatment decisions. We developed decision-theoretic measures of uncertainty for the NNT.
We build our argument on the basis that a risk-neutral decision maker should always choose the treatment with the highest expected benefit, regardless of uncertainty. From this perspective, uncertainty can be seen as a source of "opportunity loss" owing to its associated chance of choosing the suboptimal treatment. Motivated from the concept of the expected value of perfect information (EVPI) in decision analysis, we quantify such opportunity loss and propose novel measures of uncertainty around the NNT: the Lost NNT and the Lost Opportunity Index (LOI).
The Lost NNT is the quantification of the lost opportunity expressed on the same scale as the NNT. The LOI is a scale-free measure quantifying the loss in terms of the relative efficacy of treatment. We illustrate the method using a sample of published NNT values.
Decision-theoretic concepts have the potential to be applied in this context to provide measures of uncertainty that can have relevant implications.
治疗需要人数（NNT）的不确定性通常通过置信区间（CI）来表示。然而，目前尚不清楚 CI 如何帮助做出治疗决策。我们开发了用于 NNT 的决策理论不确定性度量方法。
我们的论点基于风险中性决策者应该始终选择预期收益最高的治疗方法的观点，无论不确定性如何。从这个角度来看，不确定性可以被视为选择次优治疗方法的机会损失的来源。受决策分析中完美信息期望价值（EVPI）概念的启发，我们量化了这种机会损失，并提出了用于 NNT 不确定性的新度量方法：损失的 NNT 和损失机会指数（LOI）。
损失的 NNT 是在与 NNT 相同的范围内量化的机会损失的量度。LOI 是一种无标度的度量方法，根据治疗效果的相对效用来量化损失。我们使用已发表的 NNT 值示例说明了该方法。
决策理论概念有可能在这种情况下得到应用，以提供具有相关意义的不确定性度量方法。
