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Estimation of a Relative Risk Effect Size when Using Continuous Outcomes Data: An Application of Methods in the Prevention of Major Depression and Eating Disorders

机译:使用连续结果时,估计相对风险效果的数据:方法在预防重大抑郁和饮食障碍中的应用

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Introduction. The raw mean difference (RMD) and standardized mean difference (SMD) are continuous effect size measures that are not readily usable in decision-analytic models of health care interventions. This study compared the predictive performance of 3 methods by which continuous outcomes data collected using psychiatric rating scales can be used to calculate a relative risk (RR) effect size. Methods. Three methods to calculate RR effect sizes from continuous outcomes data are described: the RMD, SMD, and Cochrane conversion methods. Each conversion method was validated using data from randomized controlled trials (RCTs) examining the efficacy of interventions for the prevention of depression in youth (aged 17 years) and adults (aged 18 years) and the prevention of eating disorders in young women (aged 21 years). Validation analyses compared predicted RR effect sizes to actual RR effect sizes using scatterplots, correlation coefficients (r), and simple linear regression. An applied analysis was also conducted to examine the impact of using each conversion method in a cost-effectiveness model. Results. The predictive performances of the RMD and Cochrane conversion methods were strong relative to the SMD conversion method when analyzing RCTs involving depression in adults (RMD: r = 0.89-0.90; Cochrane: r = 0.73; SMD: r = 0.41-0.67) and eating disorders in young women (RMD: r = 0.89; Cochrane: r = 0.96). Moderate predictive performances were observed across the 3 methods when analyzing RCTs involving depression in youth (RMD: r = 0.50; Cochrane: r = 0.47; SMD: r = 0.46-0.46). Negligible differences were observed between the 3 methods when applied to a cost-effectiveness model. Conclusion. The RMD and Cochrane conversion methods are both valid methods for predicting RR effect sizes from continuous outcomes data. However, further validation and refinement are required before being applied more broadly.
机译:介绍。原始平均差异(RMD)和标准化平均差(SMD)是连续效应尺寸措施,这些措施在医疗干预措施决策分析模型中不易使用。本研究比较了3种方法的预测性能,通过使用精神额定尺度收集的连续结果数据可用于计算相对风险(RR)效果大小。方法。描述了从连续结果数据计算RR效应尺寸的三种方法描述:RMD,SMD和Cochrane转换方法。使用来自随机对照试验(RCT)的数据来验证每种转化方法,检查干预措施对预防青年(17岁)和成人(年龄18岁)的抑郁(18岁)以及预防年轻女性的饮食障碍(21岁)年)。验证分析将预测的RR效应大小与实际RR效应大小使用散点图,相关系数(R)和简单的线性回归。还进行了应用分析以检查在成本效益模型中使用每个转换方法的影响。结果。当分析涉及成人抑郁症的RCT时,RMD和Cochrane转化方法的预测性能相对于SMD转化方法(RMD:R = 0.89-0.90; Cochrane:R = 0.73; SMD:R = 0.41-0.67)和进食年轻女性的障碍(RMD:r = 0.89; Cochrane:r = 0.96)。在分析涉及青少年抑郁的RCT(RMD:r = 0.50; Cochrane:R = 0.47; SMD:R = 0.46-0.46)时,在3种方法上观察到中度预测性表现。在应用于成本效益模型时,在3种方法之间观察到可忽略不计的差异。结论。 RMD和Cochrane转换方法是从连续结果数据预测RR效应大小的有效方法。但是,在更广泛应用之前需要进一步的验证和改进。

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