Sinclair J C, Cook R J, Guyatt G H, Pauker S G, Cook D J
Department of Clinical Epidemiology and Biostatistics, McMaster University, Room 3N11F, 1200 Main Street West, Hamilton, L8N 3Z5, Ontario, Canada.
J Clin Epidemiol. 2001 Mar;54(3):253-62. doi: 10.1016/s0895-4356(01)00347-x.
Clinicians and patients must decide when treatment effects are large enough to more than offset the adverse effects and costs of therapy. Calculation of the number of patients one needs to treat (NNT) in order to prevent one patient from having the target event is one tool to help with this decision. Clinicians should treat patients when the NNT is lower than a threshold NNT at which point the therapeutic risk equals the therapeutic benefit. We aimed: (1) to identify the determinants of the threshold NNT, and (2) to derive equations for the explicit estimation of the threshold NNT and of the minimum expected rate of target event, without treatment, above which treatment is justified. We conceived the threshold number needed to treat to prevent one target event as the point at which the benefits of treating that number of patients equal the negative consequences of treating that same number of patients. After identifying the various elements comprising the treatment impact, we equated the benefits and negative consequences and solved the equation for threshold NNT. We then derived the minimum expected rate of target event which would justify treatment. We derived an equation that relates the threshold NNT to the treatment-attributable adverse event rates (AER) and the relative values (RV) of the adverse events compared to that of the target event prevented. Specifically, the threshold NNT, denoted NNT(T) is given by NNT(T) = 1/(AER(1).RV(1) +...+ AER(n).RV(n)). We also derived a more complex equation which addresses the costs incurred by treatment and costs avoided by preventing target events. Solving the equation that includes costs requires specifying both the value of preventing a target event and the values of adverse treatment effects in economic units. The threshold NNT and the relative risk reduction (RRR) for the target event determine the minimum target event rate above which treatment is justified. This minimum event rate for treatment is 1/(NNT(T).RRR). The values that clinicians and patients use determine the threshold NNT and therefore also the minimum target event rate, without treatment, above which treatment is justified. Quantification of the determinants of the threshold NNT and of the minimum event rate to justify treatment can assist clinicians and patients in the explicit use of underlying values when making treatment decisions.
临床医生和患者必须确定治疗效果何时足够大，足以抵消治疗的不良反应和成本。计算为预防一名患者发生目标事件所需治疗的患者数量（NNT）是帮助做出这一决策的一种工具。当NNT低于某个阈值NNT时，临床医生应开始治疗，此时治疗风险等于治疗获益。我们的目标是：（1）确定阈值NNT的决定因素；（2）推导用于明确估计阈值NNT以及未治疗时目标事件的最低预期发生率的方程，高于该发生率治疗才合理。我们将预防一次目标事件所需治疗的阈值数量设想为治疗该数量患者的获益等于治疗相同数量患者的负面后果的那个点。在确定构成治疗影响的各种因素后，我们使获益与负面后果相等，并求解阈值NNT的方程。然后我们推导出了证明治疗合理的目标事件的最低预期发生率。我们推导了一个将阈值NNT与治疗归因的不良事件发生率（AER）以及不良事件与预防的目标事件相比的相对值（RV）相关联的方程。具体而言，阈值NNT（记为NNT(T)）由NNT(T) = 1/(AER(1).RV(1) +... + AER(n).RV(n))给出。我们还推导了一个更复杂的方程，该方程考虑了治疗产生的成本以及预防目标事件所避免的成本。求解包含成本的方程需要指定预防目标事件的价值以及经济单位中不良治疗效果的价值。阈值NNT和目标事件的相对风险降低（RRR）决定了证明治疗合理的最低目标事件发生率。治疗的这个最低事件发生率为1/(NNT(T).RRR)。临床医生和患者所使用的值决定了阈值NNT，因此也决定了未治疗时证明治疗合理的最低目标事件发生率。对阈值NNT的决定因素以及证明治疗合理的最低事件发生率进行量化，可以帮助临床医生和患者在做出治疗决策时明确使用潜在价值。
