A Bayesian Re-analysis of the Steroids to Reduce Systemic Inflammation after Infant Heart Surgery (STRESS) Trial.

Kevin D Hill, Jake Koerner, Hwanhee Hong, Jennifer S Li, Christoph Hornik, Prince J Kannankeril, Jeffrey P Jacobs, H Scott Baldwin, Marshall L Jacobs, Eric M Graham, Brian Blasiole, David F Vener, Adil S Husain, S Ram Kumar, Alexis Benscoter, Eric Wald, Tara Karamlou, Andrew H Van Bergen, David Overman, Pirooz Eghtesady, Ryan Butts, John S Kim, John P Scott, Brett R Anderson, Michael F Swartz, Sean M O'Brien
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Abstract

Background: Prophylactic steroids are often used to reduce the systemic inflammatory response to cardiopulmonary bypass in infants undergoing heart surgery. The STRESS trial found that the likelihood of a worse outcome did not differ between infants randomized to methylprednisolone (n=599) versus placebo (n=601) in a risk-adjusted primary analysis (adjusted odds ratio [OR], 0.86; 95% CI, 0.71 to 1.05; P=0.14). However, secondary analyses showed possible benefits with methylprednisolone. To ensure that a potentially efficacious therapy is not unnecessarily avoided, we re-analyzed the STRESS trial using Bayesian analytics to assess the probability of benefit.

Methods: Our Bayesian analysis used the original STRESS trial primary outcome measure, a hierarchically ranked composite of death, transplant, major complications and post-operative length of stay. We evaluated probability of benefit (OR<1) versus harm (OR>1) by comparing the posterior distribution of the OR assuming a neutral probability of benefit versus harm with weak prior belief strength (nearly non-informative prior distribution). Reference results were calculated under the vague prior distribution. To convey magnitude of effect we used model parameters to calculate a predicted risk of death, transplant or major complications for methylprednisolone and placebo. Analyses consisted of 10 Markov Chain Monte Carlo simulations, each consisting of 2000 iterations with a 1000 iteration burn-in to ensure proper posterior convergence. Sensitivity analyses evaluated pessimistic (5%-30% prior likelihood of benefit), neutral and optimistic (70%-95%) prior beliefs, and controlled strength of prior belief as weak (30% variance), moderate (15%) and strong (5%).

Results: In primary analysis, the posterior probability of benefit from methylprednisolone was 91% and probability of harm was 9%. Composite death or major complication occurred in 18.8% of trial subjects with an absolute risk difference of -2% (95% CI -3%, +1%) associated with methylprednisolone. Each of 9 sensitivity analyses demonstrated greater probability of benefit than harm in the methylprednisolone group with 8 of 9 demonstrating >80% probability of benefit and ≥1% absolute difference in risk of death, transplant or major complications.

Conclusion: Probability of benefit with prophylactic methylprednisolone is high and harm is unlikely. This more in-depth analysis of the data expands the initial clinical evaluation of methylprednisolone provided by the STRESS trial.

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婴儿心脏手术后类固醇减少全身炎症的贝叶斯再分析(应激)试验。
背景:在接受心脏手术的婴儿中,预防性类固醇常被用于减少体外循环的全身炎症反应。STRESS试验发现,在风险调整的初步分析中,随机接受甲基强的松龙治疗(n=599)和安慰剂治疗(n=601)的婴儿发生较差结果的可能性没有差异(调整优势比[OR], 0.86;95% CI, 0.71 ~ 1.05;P = 0.14)。然而,二次分析显示甲基强的松龙可能有益处。为了确保没有不必要地避免潜在有效的治疗,我们使用贝叶斯分析重新分析了应激试验,以评估获益的可能性。方法:我们的贝叶斯分析使用原始应激试验的主要结局指标,即死亡、移植、主要并发症和术后住院时间的分层组合。我们通过比较OR的后验分布来评估获益概率(OR1), OR假设获益与伤害的中性概率与弱先验信念强度(几乎是非信息先验分布)。参考结果在模糊先验分布下计算。为了传达效果的大小,我们使用模型参数来计算甲基强的松龙和安慰剂的死亡、移植或主要并发症的预测风险。分析由10个马尔可夫链蒙特卡罗模拟组成,每个模拟由2000次迭代和1000次迭代老化组成,以确保适当的后验收敛。敏感性分析评估悲观(5%-30%先验获益可能性)、中性和乐观(70%-95%)先验信念,并将控制先验信念的强度分为弱(30%方差)、中等(15%)和强(5%)。结果:在初步分析中,甲基强的松龙获益的后验概率为91%,危害的后验概率为9%。18.8%的受试者发生复合死亡或主要并发症,与甲基强的松龙相关的绝对风险差为-2% (95% CI -3%, +1%)。9项敏感性分析中的每一项都显示甲基强的松龙组的获益概率大于危害概率,其中9项分析中有8项显示获益概率为80%以上,死亡、移植或主要并发症风险的绝对差异≥1%。结论:预防性甲基强的松龙获益概率高,危害不大。这项更深入的数据分析扩展了STRESS试验提供的甲基强的松龙的初步临床评估。
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