Andrade Chittaranjan
Department of Psychopharmacology, National Institute of Mental Health and Neurosciences, Bangalore, India.
J Clin Psychiatry. 2017 Jan;78(1):e73-e75. doi: 10.4088/JCP.16f11380.
The likelihood of being helped or harmed (LHH) ratio is an indirect measure of effect size. It tells the reader how much as likely a patient is to benefit from a treatment as to suffer from an adverse outcome with that treatment; larger values for LHH indicate more favorable treatment outcomes. The numerator for LHH is usually a measure of response or remission with a treatment, and the denominator is usually a measure of all-cause discontinuation or discontinuation due to adverse events; so, there can be more than 1 LHH statistic for a study. As an example, an LHH of 5 could indicate that after removal of placebo effects a patient is 5 times as likely to respond to a treatment as to drop out of treatment because of the experience of an adverse event. This article explains the LHH with the help of a worked example, shows how the LHH can be derived from the numbers needed to treat and harm (NNT, NNH) statistics, discusses practical issues related to the concept, and considers its limitations. The LHH is little used in clinical psychopharmacology, and authors who report or review clinical trial data should consider presenting all the LHH information that is clinically relevant in addition to NNT, NNH, and other information. Because LHH statistics present the results of risk-benefit trade-off analyses, they can help clinicians and patients more easily evaluate potential treatments during decision-making processes.
获益或受损可能性（LHH）比值是效应大小的一种间接度量。它向读者表明患者从一种治疗中获益的可能性与因该治疗而出现不良结局的可能性之比；LHH值越大表明治疗结局越有利。LHH的分子通常是治疗反应或缓解的一种度量，分母通常是全因停药或因不良事件停药的一种度量；因此，一项研究可能有不止一个LHH统计量。例如，LHH为5可能表明去除安慰剂效应后，患者对治疗产生反应的可能性是因不良事件经历而退出治疗可能性的5倍。本文借助一个实例解释LHH，展示LHH如何从治疗与伤害所需数量（NNT、NNH）统计量中推导得出，讨论与该概念相关的实际问题，并考虑其局限性。LHH在临床精神药理学中很少使用，报告或综述临床试验数据的作者除了NNT、NNH和其他信息外，还应考虑呈现所有临床相关的LHH信息。由于LHH统计量呈现了风险 - 获益权衡分析的结果，它们可以帮助临床医生和患者在决策过程中更轻松地评估潜在治疗方法。
