Division of Clinical Epidemiology and Biostatistics, Institute of Social and Preventive Medicine (ISPM), University of Bern, Bern, Switzerland.
Int J Epidemiol. 2012 Oct;41(5):1445-59. doi: 10.1093/ije/dys124.
Clinicians find standardized mean differences (SMDs) calculated from continuous outcomes difficult to interpret. Our objective was to determine the performance of methods in converting SMDs or means to odds ratios of treatment response and numbers needed to treat (NNTs) as more intuitive measures of treatment effect.
Meta-epidemiological study of large-scale trials (≥ 100 patients per group) comparing active treatment with placebo, sham or non-intervention control. Trials had to use pain or global symptoms as continuous outcomes and report both the percentage of patients with treatment response and mean pain or symptom scores per group. For each trial, we calculated odds ratios of observed treatment response and NNTs and approximated these estimates from SMDs or means using all five currently available conversion methods by Hasselblad and Hedges (HH), Cox and Snell (CS), Furukawa (FU), Suissa (SU) and Kraemer and Kupfer (KK). We compared observed and approximated values within trials by deriving pooled ratios of odds ratios (RORs) and differences in NNTs. ROR <1 and positive differences in NNTs imply that approximations are more conservative than estimates calculated from observed treatment response. As measures of agreement, we calculated intraclass correlation coefficients.
A total of 29 trials in 13 654 patients were included. Four out of five methods were suitable (HH, CS, FU, SU), with RORs between 0.92 for SU [95% confidence interval (95% CI), 0.86-0.99] and 0.97 for HH (95% CI, 0.91-1.04) and differences in NNTs between 0.5 (95% CI, -0.1 to -1.6) and 1.3 (95% CI, 0.4-2.1). Intraclass correlation coefficients were ≥ 0.90 for these four methods, but ≤ 0.76 for the fifth method by KK (P for differences ≤ 0.027).
The methods by HH, CS, FU and SU are suitable to convert summary treatment effects calculated from continuous outcomes into odds ratios of treatment response and NNTs, whereas the method by KK is unsuitable.
临床医生发现，从连续结果计算得出的标准化均数差值（SMD）难以解释。我们的目的是确定将 SMD 或均值转换为治疗反应的优势比（OR）和治疗所需人数（NNT）的方法的性能，这些方法作为更直观的治疗效果衡量指标。
对大型试验（每组≥100 名患者）进行元流行病学研究，比较了活性治疗与安慰剂、假治疗或非干预对照的效果。试验必须使用疼痛或总体症状作为连续结果，并报告治疗反应的患者百分比和每组的平均疼痛或症状评分。对于每个试验，我们计算了观察到的治疗反应的 OR 和 NNT，并使用 Hasselblad 和 Hedges（HH）、Cox 和 Snell（CS）、Furukawa（FU）、Suissa（SU）和 Kraemer 和 Kupfer（KK）这五种目前可用的转换方法来近似这些估计值。我们通过从观察到的治疗反应中计算出比值比（OR）和 NNT 的差异，在试验内比较观察到的和近似的值。OR<1 和 NNT 的正值差异意味着近似值比从观察到的治疗反应计算出的估计值更保守。作为一致性的衡量标准，我们计算了组内相关系数。
共纳入了 29 项试验，涉及 13654 名患者。五种方法中有四种是合适的（HH、CS、FU、SU），SU 的 ROR 为 0.92（95%置信区间[95%CI]，0.86-0.99），HH 的 ROR 为 0.97（95%CI，0.91-1.04），NNT 的差异为 0.5（95%CI，-0.1 至-1.6）和 1.3（95%CI，0.4-2.1）。这四种方法的组内相关系数≥0.90，而 KK 方法的组内相关系数为 0.76（P<0.027）。
HH、CS、FU 和 SU 的方法适用于将从连续结果计算得出的汇总治疗效果转换为治疗反应的 OR 和 NNT，而 KK 的方法不适用。
