Quantitative summaries of treatment effect estimates obtained with network meta-analysis of survival curves to inform decision-making.
Quantitative summaries of treatment effect estimates obtained with network meta-analysis of survival curves to inform decision-making.
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DOI：
10.1186/1471-2288-13-147
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发表时间：
2013-12-01
影响因子：
4
通讯作者：
Jansen JP
中科院分区：
文献类型：
--
作者：
Cope S;Jansen JP
越来越多的已发表生存数据的网络荟萃分析（NMA）基于参数生存曲线，而不是报告的风险比，以避免依赖于比例风险假设。如果贝叶斯框架用于NMA，则可以获得与替代治疗相关联的等级概率，这直接支持决策。在生存分析的背景下，多个治疗效果指标可用于告知秩概率。在晚期黑色素瘤中进行总体存活的分数多项式NMA作为说明性实例。计算并列出了以下效应指标的秩概率：1）中位生存期; 2）预期生存期; 3）最短随访试验随访时间点的平均生存期; 4）随时间推移的风险或风险比; 5）随时间推移的累积风险或生存比例; 6）后续时间点的平均生存期。讨论了替代措施的优缺点。由于风险和生存估计值可能会随着时间的推移而变化，因此生存曲线的NMA的秩概率计算可能取决于效果测量。使用方法1-3，秩概率不随时间变化，这比使用方法4-6获得的随时间变化的秩概率更容易理解和传达。然而，基于方法4-6的秩概率提供了关于随时间推移的相对治疗效果的有用信息。用秩概率总结生存曲线NMA结果的不同方法各有利弊。与基于崩溃指标（如中位生存期或预期生存期）的单秩概率相比，随时间推移治疗效果的秩概率提供了一种更透明和信息量更大的方法来帮助指导决策。基于生存比例的排序概率是最直观和最直接的沟通方式，但基于风险函数或随时间推移的平均生存率的替代方案也可能有用。
Increasingly, network meta-analysis (NMA) of published survival data are based on parametric survival curves as opposed to reported hazard ratios to avoid relying on the proportional hazards assumption. If a Bayesian framework is used for the NMA, rank probabilities associated with the alternative treatments can be obtained, which directly support decision-making. In the context of survival analysis multiple treatment effect measures are available to inform the rank probabilities. A fractional polynomial NMA of overall survival in advanced melanoma was performed as an illustrative example. Rank probabilities were calculated and presented for the following effect measures: 1) median survival; 2) expected survival; 3) mean survival at the follow-up time point of the trial with the shortest follow-up; 4) hazard or hazard ratio over time; 5) cumulative hazard or survival proportions over time; and 6) mean survival at subsequent time points. The advantages and disadvantages of the alternative measures were discussed. Since hazard and survival estimates may vary over time for the compared interventions, calculations of rank probabilities for an NMA of survival curves may depend on the effect measure. With methods 1–3 rank probabilities do not vary over time, which are easier to understand and communicate than rank probabilities that vary over time as obtained with methods 4–6. However, rank probabilities based on methods 4–6 provide useful information regarding the relative treatment effects over time. Different approaches to summarize results of a NMA of survival curves with rank probabilities have pros and cons. Rank probabilities of treatment effects over time provide a more transparent and informative approach to help guide decision-making than single rank probabilities based on collapsed measures, such as median survival or expected survival. Rank probabilities based on survival proportions are the most intuitive and straightforward to communicate, but alternatives based on the hazard function or mean survival over time may also be useful.
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影响因子：
2.2
作者：
Sileni, VC;Nortilli, R;Monfardini, S
通讯作者：
Monfardini, S
影响因子：
45.3
作者：
Chapman, PB;Einhorn, LH;Kirkwood, JM
通讯作者：
Kirkwood, JM
影响因子：
45.3
作者：
Falkson, CI;Ibrahim, J;Blum, RH
通讯作者：
Blum, RH
影响因子：
3.6
作者：
Latimer, Nicholas R.
通讯作者：
Latimer, Nicholas R.
影响因子：
4.5
作者：
Jansen, Jeroen P.;Fleurence, Rachael;Cappelleri, Joseph C.
通讯作者：
Cappelleri, Joseph C.